Presentations and recommendations from the workshop on the role of geochemical data in environmental and human health risk assessment, Halifax, 2010
Bibliographic record
Abstract
It is recognized that knowledge of geochemistry is an important component of environmental and human health risk assessments. Although much geochemical information needed to better inform risk assessments exits already, these data are not well represented in many of these assessments. As a step towards improving practice in this area, Health Canada and Environment Canada sponsored a workshop on the role of geochemical data in ecological and human health risk assessments. The Workshop was presented by scientists from the Geological Survey of Canada with recognized expertise in bedrock and surficial sediment geochemistry. The Workshop was by invitation and included federal and provincial representatives and members of the environmental consulting community. The Workshop covered the following topics: Use of geochemical data in risk assessments - a consultant's view Causes of variation in geochemical data - natural spatial (horizontal and vertical) and analytical controls Field sampling and analytical protocols Estimating background geochemical composition Case studies involving geochemical data Discussion of priorities for improving practice and identifying gaps in existing data. One aim of the Workshop was to develop a strategy for improving the guidelines for risk assessments by promoting more rigorous use of geochemical information. More specifically, the focus was on the application of existing geochemical data and on the needs for new types of data and developing tools for their application. Information and ideas from the presentations and discussions are gathered here in a final document. The document includes the Workshop proceedings and also contains lists of recommendations for making updates to existing guidelines, where appropriate. For the purposes of this Workshop, geochemical information was restricted to the chemical elements associated with inorganic substances. The focus was on As, Cd, Cu, Ni, Pb, and Zn, in particular. Issues related to organic substances were not considered. There were presentations on a series of topics relevant to risk assessment, followed by discussions and recommendations for improving practice. The discussions were guided to ensure that Workshop participants were familiar with the concern and also the guideline. Case studies were used to reinforce the concepts. There was also a session dedicated to identifying knowledge gaps and making plans for moving forward. The Workshop was held in the Radisson Hotel in Halifax, Nova Scotia, on March 17th and 18th, 2010. Additional introductory information on the Workshop is provided in the file entitled "Start Here_Executive Summary" and also in the 01_INTRODUCTION directory. This Open File provides a record of the presentations and other documents associated with the Workshop. The contents of Geological Survey of Canada Open File 6645 are organized into 10 directories, representing introductory materials (e.g. agenda and abstracts) and the 9 sessions and areas of subject matter covered at the Workshop. The directories related to the 9 sessions contain pdf files of the presentations. There is a complete listing and more explanation of the directories in the file entitled "Start Here_Executive Summary".
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.145 | 0.081 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".