Bibliographic record
Abstract
Last week, top North American environmental officials announced three crossborder pilot projects and a handful of topics they intend to work on together. Among broad areas identified by the environmental ministers of Canada, Mexico, and the U.S. were resolutions to lay the groundwork for a regional plan to control dioxins, investigate the impact of pollution on children's health, better track transportation of hazardous waste, and enhance compliance and enforcement of environmental laws. The announcement of the joint topics came at the close of a two-day meeting of the Council of the Commission for Environmental Cooperation, which was created through the North American Free Trade Agreement. Also last week, outgoing U.S. EPA Administrator Christine Todd Whitman and Canadian Environment Minister David Anderson announced three cross-border air pollution pilot projects. In the Pacific Northwest, the two countries will identify sources and explore approaches to reduce air pollution from transportation ...
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.131 | 0.056 |
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".