Are we accurately estimating the potential role of pollution in the decline of species at risk in Canada?
Bibliographic record
Abstract
Pollution is a pervasive, albeit often invisible, threat to biodiversity in Canada. Currently, the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) relies on expert opinion to assess the scope (i.e., the proportion of a species’ population that may be affected) of pollution to species at risk. Here, we describe a spatially explicit, quantitative method for assessing the scope of pollution as a threat to species at risk in Canada. Using this method, we quantified the geographic co-occurrence of 488 terrestrial and freshwater species and pollution sources and determined that, on average, 57% of the mapped occurrences of each species at risk co-occurred with at least one pollution source. Furthermore, we found a weak correlation between the scope of the threat of pollution as assessed by COSEWIC expert panels and the geographic overlap of species occurrences and pollution sources that we determined with our quantitative method. Experts frequently identified scope of pollution as absent or negligible even for species with extensive co-occurrence with pollution sources, especially vascular plants. Clearly, a quantitative approach is needed to make accurate estimates of the scope of pollution as a threat to species at risk in Canada.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".