First estimates of the probability of survival in a small-bodied, high-elevation frog (Boreal Chorus Frog, <i>Pseudacris</i> <i>maculata</i>), or how historical data can be useful
Bibliographic record
Abstract
In an era of shrinking budgets yet increasing demands for conservation, the value of existing (i.e., historical) data are elevated. Lengthy time series on common, or previously common, species are particularly valuable and may be available only through the use of historical information. We provide first estimates of the probability of survival and longevity (0.67–0.79 and 5–7 years, respectively) for a subalpine population of a small-bodied, ostensibly common amphibian, the Boreal Chorus Frog (Pseudacris maculata (Agassiz, 1850)), using historical data and contemporary, hypothesis-driven information–theoretic analyses. We also test a priori hypotheses about the effects of color morph (as suggested by early reports) and of drought (as suggested by recent climate predictions) on survival. Using robust mark–recapture models, we find some support for early hypotheses regarding the effect of color on survival, but we find no effect of drought. The congruence between early findings and our analyses highlights the usefulness of historical information in providing raw data for contemporary analyses and context for conservation and management decisions.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".