(NFPRER) Health Prioritization Sub-Group Assessment of Comparative Human Health Risk-based Prioritization Schemes
Bibliographic record
Abstract
This report describes an assessment of comparative human health risk-based prioritization schemes carried out by the Network for Environmental Risk Assessment and Management (NERAM) under contract to the Canadian Council of Ministers of the Environment (CCME) National Framework for Petroleum Refinery Emission Reductions (NFPRER) Health Prioritization sub-group. The Health Prioritization sub-group, composed of members representing non-governmental organizations, the petroleum industry, provinces and federal government, is one of several sub-groups formed by the CCME to facilitate the development of the National Framework The National Framework will provide the principles and methods for jurisdictions to establish performance-based facility emissions caps for criteria air pollutants and air toxics from the petroleum refinery industry. The objective of this assessment was to provide a critical evaluation of prioritization schemes to assist the Health Prioritization subgroup in prioritizing reductions of air emissions from petroleum refineries. The study was initiated in January, 2003 and a draft final report was submitted to the sub-
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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 | 0.084 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".