Assessing Migratory Double Breeding through Complementary Specimen Densities and Breeding Records
Bibliographic record
Abstract
We re-evaluate the plausibility that five species of birds that breed in late summer in northwestern Mexico are migratory double breeders that first bred earlier in the same season to the north.We use data aggregated from scientific collections to generate abundance indices that adjust counts of specimens in collections by collecting effort, which we measure as the number of passerines collected in the same region and time period as the species of interest.Our abundance indices generally show displaced phenologies, such that presumed double breeders arrive and breed early in the north, then later in northwestern Mexico.We also compare breeding records for these regions, but these records could not be corrected for effort.Our phenologies suggest that the breeding populations of the Yellow-billed Cuckoo (Coccyzus americanus) from the western U.S. and northwestern Mexico may be derived from birds that bred earlier in eastern North America.Similarly, Orchard Orioles (Icterus spurius) breeding in late summer in northwestern Mexico and on the Mexican plateau may be derived from birds that attempted to breed earlier in North America.Our abundance indices and other new data suggest migratory double breeding is less likely in the Hooded Oriole (I.cucullatus) and probably not occurring in the Yellow-breasted Chat (Icteria virens) and Cassin's Vireo (Vireo cassinii).
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".