The Reliability of Brood Patches in Assessing Reproductive Status in the Marbled Murrelet: Words of Caution
Bibliographic record
Abstract
The assumption that brood patches identify incubating birds is a pervasive one in avian literature, and as a result, brood patches are often used to infer breeding status. Although the developmental stages of the brood patch with specific reproductive stages in passerines have been described, this information for seabirds is not often reported. Thus, for birds whose breeding activities are not easily observed, it is difficult to confirm (1) that it is valid to assume that a bird which has some stage of brood patch is a nester or putative nester, and (2) whether specific stages of brood patch development reflect specific stages of the breeding cycle. We tested the utility of brood patch scores to infer breeding status in a non-colonial seabird, the Marbled Murrelet (Brachyramphus marmoratus), a species always captured away from the nest site. We confirmed the breeding status of murrelets with brood patches, and assessed the specific stages of brood patch development to the timing of egg-production (using a physiological analysis) and the onset of incubation (using radio telemetry). Murrelets with brood patches were not always nesters or putative nesters (58% of birds with brood patches were producing eggs, and 56% of radio-tagged birds with brood patches began incubation), and brood patch score did not predict which birds were more likely to become egg-producers or incubators. Specific brood patch stages did not always correlate with specific breeding stages (e.g., the brood patch of egg-producers ranged from absent to fully-developed). Birds with fully developed brood patches took from 3-30 days to start incubation. Brood patch development accurately depicted the average population incubation time, but we caution against using brood patches to predict the timing of an individual breeding attempt, and suggest that when possible, researchers should try to confirm breeding activities using other methods.
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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 | 0.068 | 0.207 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".