Fig. 1 in Effects of bat white-nose syndrome on hibernation and swarming aggregations of bats in Ontario
Bibliographic record
Abstract
Fig. 1. Changes in counts of hibernating bats at 10 hibernacula in southern Ontario and 1 hibernaculum in northern Ontario (Dorion). The assemblage of hibernating bats in these sites is dominated by little brown bats, but to minimize the time spent in the sites we did not identify individuals to species. These counts, therefore, represent all five hibernating species at the monitored sites. The data are presented as (A) absolute counts of bats and (B) the size of hibernating bat populations relative to the first year of counting, expressed as a percentage. For Dorion, we averaged the counts prior to 2015 and used these as the "first year". Dashed lines are intended to help visualize overall trends at sites that were uncounted for some years, but do not imply a linear trend in bat aggregations during the years when no survey was conducted. The red dashed lines represent the first confirmed cases of WNS for the southern hibernacula (2010) and at Dorion (2016).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".