- About ARC
We conduct scientific research and applied research to evaluate chemicals for their potential harmful effects to humans and the environment through chemical hazard, exposure and risk assessment.
We develop, apply and evaluate databases and models that are used for chemical hazard, exposure and risk assessment.
We conduct research with and for colleagues and representatives in academia, industry and government.
If you would like to know more about the company, our research or our consulting services please contact Dr. Jon Arnot.
Several thousand chemicals are currently used in society and thousands of new chemicals are developed annually. Globally, legislative programs seek to identify and regulate chemicals that pose hazards and risks to humans and the environment. Scientific methods, tools and expertise are required to identify chemical hazards and minimize the potential for undesirable effects (risks) to humans and ecosystems.
Our research strives to improve the scientific understanding of the potential hazards and risks chemicals may cause to humans and the environment. Often measured information is limited and there is a recognized need to minimize animal testing. It is not possible to measure “all of chemicals in all things” for chemical assessments due to analytical limitations and enormous financial costs. To address these issues, we develop and evaluate databases of measured information and develop and evaluate models based on measured data and scientific theory. The models can be used to interpret the measured data and to complement measurements by addressing data gaps for chemical assessments. The models also can be used to make predictions (hypotheses) to guide research needs (e.g. when there are no measured data) and to inform experimental testing. In turn the model predictions (hypotheses) can be tested with new measurements. This iterative process of model development, prediction and testing is envisaged to improve scientific understanding and provide confidence in applying the models for chemical assessments. Some of the models we have developed are used in regulatory programs and these models can also be used to promote “green chemistry” and sustainability.
Chemical hazard (or PBT) assessment relates to (1) Persistence in the environment (rates of chemical degradation), (2) Bioaccumulation in a range of species (plants, invertebrates, fish, birds, and mammals, including humans), and (3) Toxicity in ecological species and humans.
Chemical risk assessment relates to quantifying the proximity of chemical exposure concentrations to chemical concentrations associated with effects and estimating the uncertainty in these calculations. We develop, apply and evaluate mass balance models to simulate and assess chemical fate and transport in the environment, bioaccumulation in organisms and in food webs, aggregate exposures to humans and ecological species through contact with chemicals in environmental media (air, water, soil, sediment and food), and potential risk.
The databases of chemical information are used to develop, apply and evaluate Quantitative Structure-Activity Relationships (QSARs) to estimate key chemical properties such as partition coefficients, biodegradation half-lives (e.g., by microorganisms), and biotransformation half-lives in organisms (e.g., in fish and mammals). This chemical information is used in hazard, exposure and risk assessment.
- Models & Databases
Models & Databases
This website contains models and databases that we have developed or co-developed and links to other websites with models and databases.
The downloadable materials included on this website are provided to interested parties at no cost; however, to download any material you need to first request a password by sending an e-mail with your name and affiliation and download of interest to The registration information also provides us with contact information so that we can send notifications for model updates.
The models are updated occasionally to address potential errors and “bugs in the code” and to reflect scientific advancements. The most recent versions of the models and databases are most relevant since they include updates and possibly corrections to previous versions. Users are strongly encouraged to read the associated papers listed with the models and the “help” and “about” information accompanying the models (when included) before using them.
Thank you for your interest in these models.
For more information about these models and databases please contact Jon Arnot.
- RAIDAR (Risk Assessment, IDentification And Ranking ) model
- FHX (Far-field Human eXposure) model
- FHX-CAN (Far-field Human eXposure in Canada) model
- AQUAWEB (Aquatic Food Web) model
- Screening-level BCF and BAF models
- San Francisco Bay Food Web Bioaccumulation model
- Fish biotransformation rate constant (or half-life) QSARs
To download any material you need to first request a password by sending an e-mail with your name and affiliation and download of interest to Jon Arnot. The registration information also provides us with contact information so that we can send notifications for model updates.
The models are in various formats and may not run on all operating systems and configurations. The executable software models are only compatible using most Windows operating systems.
Note: To run the software models (RAIDAR, FHX, FHX-CAN) the "System Settings -> Language Settings -> Numbers" of your computer must use the period (.) as the decimal separator rather than the comma (,) .
- BCF and BAF database
- Fish biotransformation rate constant (kM) database
The Excel spreadsheet models and databases are expected to work using Microsoft Office or other similar programs (Note: Visual Basic for Applications support is often required).
Jon Arnot, PhD
Dr. Jon Arnot founded ARC Arnot Research & Consulting in January 2010 after several years of part-time research and consulting as a sole proprietor during his graduate studies and postdoctoral appointment. Jon completed a two year Natural Sciences and Engineering Research Council (NSERC) of Canada postdoctoral fellowship under the supervision of Professor Frank Wania at the University of Toronto Scarborough. His PhD at Trent University was completed in 2008 under the supervision of Professor Emeritus Don Mackay and his Masters of Environmental Toxicology at Simon Fraser University was supervised by Professor Frank Gobas.
Over the past 10 years his research has included the development, application and evaluation of methods and models for assessing the exposure, hazard and risk of organic chemicals to humans and the environment including the AQUAWEB, RAIDAR, FHX, and FHX-CAN mass balance models.
In collaboration with the U.S. EPA, Environment Canada and Syracuse Research Corporation he developed a QSAR to estimate primary biotransformation rates for fish from chemical structure. Jon has co-developed models that are used for regulatory purposes in Canada, the U.S. and Europe (e.g., models included in U.S. EPA’s EPI Suite™ and the OECD Toolbox).
Jon is actively involved in research developing methods and tools to help better understand chemical hazard, exposure and risk for applications in various regulatory programs.
James Armitage, PhD
Dr. James Armitage is a Postdoctoral Banting Fellow with Professor Frank Wania at the University of Toronto Scarborough (2011-2013).
He completed his doctoral degree in 2009 at Stockholm University under the supervision of Ian T. Cousins and Michael McLachlan.
His PhD thesis focused on modeling the global fate and transport of perfluorinated surfactants such as PFOS and long-chain perfluorocarboxylic acids (PFCAs) and exploring the influence of physical-chemical property uncertainty on key model outputs such as long-range atmospheric and oceanic transport potential.
He completed his Master’s thesis under the supervision of Professor Frank Gobas modeling the bioaccumulation of organic chemicals in terrestrial food chains. James is actively involved in research developing models to assess the impacts of climate change on contaminant transport and bioaccumulation of ionogenic organic chemicals.
Trevor N. Brown, PhD
Dr. Trevor Brown is currently a postdoctoral fellow in the Department of Analytical Environmental Chemistry Helmholtz Centre for Environmental Research-UFZ in Leipzig, Germany under the supervision of Professor Kai-Uwe Goss. Trevor completed his PhD in Environmental Chemistry at the University of Toronto Scarborough under the supervision of Frank Wania in 2011.
His research has focused on modeling chemical fate in the environment and chemical property prediction including the development of the Iterative Fragment Selection (IFS) method. He has undertaken or collaborated on several projects involving the compilation and prioritization of large lists of commercial and industrial substances. More recent research is focused on the development and validation of QSARs using the IFS methods for the prediction of both physical-chemical properties and biotransformation rates and the development of physiologically based pharmacokinetic (PBPK) models.
For more information on Trevor’s research, please visit his homepage at UFZ http://www.ufz.de/index.php?en=22287
Nicolas Gilbert, MSc
Nicolas Gilbert received a M.Sc. in applied biosciences from the University Of Ontario Institute Of Technology in 2011.
There he investigated the role of urban wetland community structure and function in organic contaminant fate.
His research focused on the biodegradation of agricultural herbicides, as well as the phylogenetic and physiological characterization of microbial communities in different urban wetland types. He is currently pursuing a PhD in environmental science.
Lauren Hughes, MSc
Lauren Hughes received a M.Sc. in chemical physics from Dalhousie University and began working at the Canadian Environmental
Modelling Centre in 2003. She has been involved in the development and coding of several chemical fate models including the
Biosolids-Amended Soil: Level 4 (BASL4) model that examines the fate of chemicals introduced to soil environments through contaminated sludge amendments.
Her modeling research has focused on chemical fate and transport from agricultural soils, including plant uptake, and accumulation in terrestrial food chains and in adjacent aquatic systems and more recently includes revisions to RAIDAR and FHX software and revisions to the EQC model for Dow Corning.
Liisa Toose, MSc
Liisa Toose(Reid) completed her M.Sc. at the Canadian Environmental Modelling Centre at Trent University in 2005 with Don Mackay.
Her research has focused on modelling the global transport of single and multi-species contaminants to the Arctic, although her projects have included modelling the fate of these contaminants at smaller scales as well, in lakes, agricultural ponds and soils.
More recently, Liisa has been working with Jon to revise the RAIDAR model to improve simulations for ionic organic chemicals and bioaccumulation in plants, including the treatment plant biotransformation, and to include the calculation of trophic magnification factors (TMFs) in various food webs.
Lynn McCarty, PhD
Dr. McCarty received B.Sc. and M.Sc. degrees from Brock University and a Ph.D. from the University of Waterloo.
He has spent over 30 years examining various aspects of toxicology and environmental contamination, with emphasis on the aquatic environment.
He has been involved in numerous projects examining actual and potential effects for a wide variety of contaminants in an assortment of situations. This included the preparation of a number of air and water quality guidelines for the Ontario and Canadian Governments.
As well, he carried out critical reviews of various environmental quality guidelines, protocols, and risk assessments, for, among others, Environment Canada (including CEPA), the Canadian Council of Ministers of the Environment (CCME), and the U.S. Environmental Protection Agency. In 2005 Dr. McCarty was a member of the U.S. EPA Science Advisory Board Aquatic Life Criteria Consultative Panel.
Dr. McCarty has been an involved in a number of risk assessment projects and also provided expert witness testimony. These include: effects associated with the siting and operation of domestic and hazardous waste treatment facilities (sewage, landfill, and incineration); siting and operation of nuclear and hydroelectric power stations, effects of liquid and solid wastes from pulp and paper mills, effects of past, current, and proposed mining operations; effects associated water, sediment, and soil contamination by petroleum products; and effects of pesticides in agriculture and forestry. Also, reports for FIFRA and UN ECE POP RC evaluation have been prepared.
Dr. McCarty has been an invited expert at a number of workshops and expert panels sponsored by CNTC, Health Canada, SETAC, US EPA, and US Army Corps of Engineers examining, employing, and/or developing environmental quality guidelines, and risk assessments.
Included in the over 60 peer-reviewed publications is co-authorship of two chapters in the second edition of the standard reference book "Fundamentals of Aquatic Toxicology" (Rand, 1995). As well, several of his publications are commonly cited by regulatory agencies around the world in various protocols, guidelines, and regulations.
He continues to publish in the primary scientific literature, make presentations at professional scientific meetings, and currently serves on the editorial board of Human and Ecological Risk Assessment. The Province of Ontario recognized his scientific work by awarding him the Ontario MOE Excellence in Research - Water Quality in 1990.
Don Mackay, PhD
Dr. Don Mackay is Director Emeritus of the Centre for Environmental Modelling and Chemistry at Trent University. He is Professor Emeritus at Trent University and the University of Toronto. The principal activities are (i) compilation of physical chemical data on organic contaminants, (ii) development of models describing the environmental fate and effects of chemical contaminants and (iii) various studies relating to policies for chemical management in the environment.
He is the author or co-author of over 600 research papers, articles, book chapters and technical reports, including over 300 peer-reviewed publications and author, editor or co-editor more than a dozen books.
More details about Don and his research are available at his homepage at the
Canadian Centre for Environmental Modelling and Chemistry (CEMC) website.
Frank Wania, PhD
Dr. Frank Wania is a Professor in the Department of Physical and Environmental Sciences, University of Toronto Scarborough and is affiliated with the graduate Departments of Chemistry and Chemical Engineering and Applied Chemistry, University of Toronto.
Dr. Wania has worked on the development, evaluation and application of environmental fate and transport models for 20 years.
His research interests currently include the development and application of novel air sampling techniques for semi-volatile organic contaminants, the understanding of differences in contaminant accumulation along climatic gradients, the identification of new environmental contaminants by theoretical means, the quantification of the role of snow in the environmental fate of pollutants, and the model-based exploration of differences in human exposure to bioaccumulating substances.
More details about Frank and his research group, including current projects are available at his homepage at the
University of Toronto Scarborough website.
Permission Request Form
RAIDAR (Risk Assessment, IDentification And Ranking ) model
RAIDAR is an evaluative, regional-scale, mass balance model for screening level exposure and risk assessment. The model simulates chemical fate and transport in the environment, bioaccumulation in a range of species, food web bioaccumulation, far-field exposures to humans and representative ecological species, and effects (risk).
The general intent of the model is to screen and prioritize large numbers of chemicals based on hazard, exposure and risk assessment objectives for more comprehensive, higher-tiered assessments. The model has been used for high-throughput risk assessments for Environment Canada to address legislation outlined under the Canadian Environmental Protection Act 1999.
Full details of the model are available in the following publications:
- Arnot JA, Mackay D, Parkerton TF, Zaleski RT, Warren CS. 2010. Multimedia modelling of human exposure to chemical substances: the roles of biomagnification and biotransformation. Environ Toxicol Chem 29(1): 45-55.
- Arnot JA, Mackay D. 2008. Policies for chemical hazard and risk priority setting: Can persistence, bioaccumulation, toxicity and quantity information be combined? Environ Sci Technol 42: 4648-4654.
- Arnot JA, Mackay D, Webster E, Southwood J. 2006. Screening level risk assessment model for chemical fate and effects in the environment. Environ Sci Technol 40: 2316-2323.
The RAIDAR model is currently being revised to:
Simulate fate, bioaccumulation and exposure for ionogenic organic chemicals:
- Arnot JA, Armitage JM, Reid L, Wania F, Mackay D. 2012. Simulating ionogenic chemical fate, bioaccumulation and exposure with RAIDAR. SETAC Conference, November May 20-24, Berlin, Germany.
Calculate Trophic Magnification Factors (TMFs) in various food webs:
- Arnot JA, Burkhard L, Reid L. 2011. Applying multimedia models to calculate trophic magnification factors (TMFs): exploring basic assumptions and the role of the physical environment. SETAC Conference, May 15-19, Milan, Italy.
- Arnot JA, Burkhard L, Reid L. 2010. Exploring the use of multimedia fate and bioaccumulation models to calculate trophic magnification factors (TMFs). SETAC Conference, November 7-11, Portland, OR.
RAIDAR Ver.2.00 (Released March 2012)
RAIDAR Ver.2.01 (Released July 2012 to address a minor display error in Ver.2.00)
FHX (Far-field Human eXposure) model
FHX is an evaluative, regional-scale, mass balance model for screening level far-field human exposure assessment. The general objective of the FHX model is to provide information on far-field human exposures to chemicals by linking information on physical-chemical properties and chemical emissions to the environment with simulations for chemical fate in the physical environment (air, water, soil and sediment), food web bioaccumulation (including aquatic and agricultural food chains), and multimedia contact rates (inhalation of outdoor air, ingestion of drinking water and foodstuffs) for different human age classes representing the Canadian population.
The FHX model was co-developed with scientists at Health Canada and is currently parameterized using Health Canada Exposure Factor Data (ca. 1998) for seven age classes. The model calculates chemical intake rates and intake fractions.
Full details of the model are available in the following publications:
-Arnot JA, Mackay D, Sutcliffe R, Lo B. 2010. Estimating farfield organic chemical exposures, intake rates and intake fractions to human age classes. Environ Modell Softw 25:1166-1175.
Versions for Download: FHX Ver.1.11 (Released March 2012)
Download FHX Ver.1.11
For earlier versions of the FHX model, please go the Canadian Centre for Environmental Modelling and Chemistry (CEMC) website
FHX-CAN (Far-field Human eXposure in Canada) model
FHX-CAN is an evaluative, regional-scale, mass balance model for screening level far-field human exposure assessments in selected regional areas of Canada. The general objective of the FHX-CAN model is to provide information on far-field human exposures to chemicals by linking information on physical-chemical properties and chemical emissions to the environment with simulations for chemical fate in the physical environment (air, water, soil and sediment), food web bioaccumulation (including aquatic and agricultural food chains), and multimedia contact rates (inhalation of outdoor air, ingestion of drinking water and foodstuffs) for seven human age classes in five specific Canadian regions. The model calculates chemical intake rates and intake fractions.
The FHX-CAN model was developed for Health Canada and is based on the FHX model and includes regional environments from the ChemCAN model.
Most details of the model are available in the following publications:
- Arnot JA, Mackay D, Sutcliffe R, Lo B. 2010. Estimating farfield organic chemical exposures, intake rates and intake fractions to human age classes. Environ Modell Softw 25:1166-1175.
- Webster E, Mackay D, Di Guardo A, Kane D, Woodfine D. 2004. Regional differences in chemical fate model outcome. Chemosphere 55: 1361-1376.
Versions for Download:
FHX-CAN Ver.1.11 (Released March 2012)
Download FHX-CAN Ver.1.11
AQUAWEB (Aquatic Food Web) model
AQUAWEB is a site-specific bioaccumulation model for aquatic food webs and provides estimates of chemical concentrations in organisms of aquatic food webs from chemical concentrations in the water and the sediment. The model is presented in rate constant format for assessing the bioaccumulation of non-ionic hydrophobic organic chemicals at steady-state.
For zooplankton, aquatic invertebrates and fish the model calculates rates of chemical uptake from the water and the diet and rates of chemical elimination to the water, feces and the “pseudo-loss” mechanism of growth dilution. Metabolic biotransformation rate data can also be included as a mechanism of chemical elimination (see database and the BCFBAF module of US EPA EPI Suite™). AQUAWEB is a modification of a previous food web model (Gobas 1993). The models are intended to estimate chemical concentrations and associated bioconcentration factors (BCF), bioaccumulation factors (BAF) and biota-sediment accumulation factors (BSAF) of non-ionic hydrophobic organic chemicals. The models are useful for assessing exposure and risks of chemicals in the water and sediment to organisms in aquatic ecosystems and higher trophic level organisms that eat aquatic species such as birds and mammals, including humans.
Both the Gobas 1993 and Arnot and Gobas 2004 models have been evaluated using empirical data from three different freshwater ecosystems involving 1,019 observations for 35 species and 64 chemicals and are coded in one Microsoft Excel™ workbook. The AQUAWEB model also forms the basis of the U.S. Environmental Protection Agency’s KABAM model used primarily for pesticide assessments.
Full details of the 2004 model are available in the following publication:
- Arnot JA, Gobas FAPC. 2004. A food web bioaccumulation model for organic chemicals in aquatic ecosystems. Environ Toxicol Chem 23(10): 2343–2355.
Versions for Download:
Screening-level BCF and BAF models
This model provides screening-level estimates of the bioaccumulation factor (BAF) for generic fish species in lower, middle and upper trophic levels of aquatic food webs. The model also provides screening-level estimates of the bioconcentration factor (BCF) for water exposures only (i.e., in laboratory bioconcentration tests). The models require only the octanol-water partition coefficient (KOW) of the chemical and the metabolic biotransformation rate constant as input parameters (see database and the BCFBAF module of U. S. EPA’s EPI Suite™).
The BAF models are derived from the parameterization and calibration of a mechanistic bioaccumulation model to a large database of evaluated measured BAFs. The measured BAFs are for chemicals that are poorly metabolized and are grouped into lower, middle and upper trophic levels of fish species. The model is calibrated to each trophic level of measured BAF values thus providing estimates that are in general agreement with measured BAFs, thus capturing the overall food web biomagnification potential of chemicals in aquatic food webs for screening assessments.
The model is intended to estimate BCFs and BAFs for non-ionic organic chemicals only. Thus it provides generic estimates in absence of site-specific measurements or estimates. The model can be used to predict dietary concentrations for higher trophic level predators (e.g., birds and mammals) including human exposure concentrations from fish in their diet. A previous version of the model has been used to categorize chemicals for their potential to bioaccumulate in aquatic food webs for Environment Canada to address legislation outlined under the Canadian Environmental Protection Act 1999. The model is coded in a Microsoft Excel™ workbook.
General information on the model is available in the following publication:
- Arnot JA, Gobas FAPC. 2003. A generic QSAR for assessing the bioaccumulation potential of organic chemicals in aquatic food webs. QSAR Comb Sci 22(3): 337-345.
Versions for Download:
BCFBAF Ver1.2 model (Spreadsheet Model)
Download BCFBAF VER1.2
OR available in U. S. EPA’s EPI Suite
San Francisco Bay Food Web Bioaccumulation model
This model was developed to assess the effects of PCBs in wildlife and fishermen in San Francisco Bay and to identify potential risk management actions. The objective of this model is to estimate the concentrations of PCBs in a set of key species that reside in the Bay as a result of PCB concentrations in sediments and water in the Bay.
The species that are the main focus of the study are the double-crested cormorant (Phalacrocorax auritus), the Forster’s tern (Sterna Forsteri), and the harbor seal (Phoca vitulina richardsi), as well as three fish species that are frequently caught by fishermen in the Bay, i.e. shiner surfperch (Cymatogaster aggregata), jacksmelt (Atherinopsis californiensis) and white croaker (Genyonemus lineatus). The fish species are important end-points of the model because of their role in passing PCBs to fishermen. Double-crested cormorants, Forster’s terns and harbor seals are included in the model because they have been identified as sensitive receptors of PCBs.
The model can be used to determine what concentrations of PCBs in the water and sediments of the Bay need to be reached to achieve an adequate margin of safety in wildlife and humans exposed to PCBs in the Bay area. This information can be used as part of a Total Maximum Daily Loading (TMDL) characterization to formulate remedial actions to achieve desired water quality goals.
The model is in the form of a Microsoft Excel™ workbook.
General information on the model is available in the following publication:
- Gobas FAPC, Arnot JA. 2010. Food web bioaccumulation model for polychlorinated biphenyls in San Francisco Bay, California, USA. Environ Toxicol Chem 29:1385-1395.
For more information on this model please contact Jon Arnot or Frank Gobas.
Contact Jon Arnot
Fish biotransformation rate constant (or half-life) QSARs
The fish biotransformation rate constant (kM) database - July 2008 has so far been used to develop two QSARs that can be used to predict screening-level kM estimates from chemical structure (i.e., SMILES notation). The predictions can be used for screening level bioaccumulation hazard assessments, exposure and risk assessments, comparisons with other in vivo and in vitro estimates, and as a contribution to testing strategies that reduce animal usage.
The first “kM-QSAR” is included in the BCFBAF module of the U. S. EPA’s EPI Suite™ software package and details about this QSAR are provided in the following publication:
- Arnot JA, Meylan W, Tunkel J, Howard PH, Mackay D, Bonnell M, Boethling RS. 2009. A quantitative structure-activity relationship for predicting metabolic biotransformation rates for organic chemicals in fish. Environ Toxicol Chem 28(6): 1168-1177.
Versions for Download:
Download Here - U. S. EPA’s EPI Suite™
The second “kM-QSAR” has recently been developed using the Iterative Fragment Selection QSAR method developed by Trevor Brown.
Details about this QSAR are provided in the following publication:
- Brown TN, Arnot JA, Wania F. 2012. Iterative fragment selection: A group contribution approach to predicting fish
biotransformation half-lives. In press Environ Sci Technol DOI: 10.1021/es301182a
Download - IFS_Fish_HLQSAR
The IFS Fish HLQSAR Ver1.0 model is also available for download at Frank Wania’s web page
Fish biotransformation rate constant (kM) database
More than 5,400 bioaccumulation measurements in fish for more than 1,000 organic chemicals were critically reviewed to compile a database of 1,535 kM estimates for 702 organic chemicals. Biotransformation rates range over six orders of magnitude across a diverse domain of chemical classes and structures. Screening-level uncertainty analyses provide guidance for the selection and interpretation of kM values.
Details about the database are available in the following publication:
- Arnot JA, Mackay D, Parkerton TF, Bonnell M. 2008. A database of fish biotransformation rates for organic chemicals. Environ Toxicol Chem 27(11): 2263-2270.
Versions for Download:
Download Here - kMdatabase
BCF and BAF database
This database is the result of a review of 392 scientific papers and publicly available bioaccumulation data sources and includes 5,317 BCFs and 1,656 BAFs measured for 842 organic chemicals in 219 aquatic species. The data were subject to a data quality evaluation and scoring method.
Details about the database and the data quality assessment method are available in the following publication:
- Arnot JA, Gobas FAPC. 2006. A review of bioconcentration factor (BCF) and bioaccumulation factor (BAF) assessments for organic chemicals in aquatic organisms. Environ Rev 14: 257-297.
Versions for Download: >
Download Here - BCF and BAF database - 2006
Limitations of liability and disclaimer of warranty
ARC Arnot Research & Consulting Inc. and all associated collaborators do not guarantee, warrant, or make any representations, either expressed or implied, regarding the use, or the results of the use of the materials provided with regards to reliability, accuracy, correctness, or otherwise. There are no warranty rights granted to users of the models or databases provided.
Users assume the entire risk as to the results and performance of the models and databases. ARC Arnot Research & Consulting Inc. and all associated collaborators are not liable under any circumstances, for any damages whatsoever, arising out of the use, or the inability to use, the models and databases provided, even if advised of the possibility of such damages.
Terms and Conditions
Any use of a web site or its contents or both (collectively: "Web Site") hosted by ARC Arnot Research & Consulting Inc. ("ARC") is subject to the following terms and conditions. Use of a Web Site hosted by ARC is conclusive evidence that the user has read, understood, and accepted the following terms and conditions. If you do not want to accept the following terms and conditions, do not use a Web Site hosted by ARC.
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