Comments on Brodie and Post: Climate‐driven declines in wolverine populations: causal connection or spurious correlation?
Bibliographic record
Abstract
Abstract The recent paper by Brodie and Post (“Nonlinear responses of wolverine populations to declining winter snowpack”, Popul Ecol 52:279–287, ) reports conclusions that are unsupportable, in our opinion, due to both mis‐interpretations of current knowledge regarding the wolverine's (Gulo gulo) association with snow, and the uncritical use of harvest data to index wolverine populations. The authors argue that, because the wolverine is a snow‐dependent species, average annual provincial snowfall, based on weather station data, can be expected to correlate strongly and positively with wolverine population numbers, which in turn can be accurately indexed by trapper harvests. Thus, correlations between declines in wolverine harvests and declining average snowpack are interpreted to reflect a climate‐driven decrease in wolverine populations. This conclusion overstates the nature of the wolverine's association with snow, and makes unsupportable assumptions about the reliability of harvest data as a proxy for population size.
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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 | 0.015 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.043 | 0.038 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".