Application of a global age-coding system (“WRP”), based on molts and plumages, for use in demographic and other studies of birds
Bibliographic record
Abstract
Abstract Determination of a bird’s age or cohort is critical for studies on avian demography, occurrence patterns, behavior, and conservation management. Age designations have largely been developed in north-temperate regions and utilize calendar-based or seasonally based codes; however, in tropical regions and in the southern hemisphere, these coding systems have limited utility at best. To address these issues, we had previously devised the “WRP system,” based on the nomenclature of Humphrey and Parkes (H–P) and Howell et al., which defines molts in an evolutionary context applicable to birds globally. Here we refine and build upon core concepts and definitions of the WRP coding system, resolving key limitations that were identified during its first decade of use. The WRP system employs a three-letter alpha code in which each letter describes a different aspect of H–P terminology: the molt cycle (which informs a bird’s age) and molt and plumage status within the cycle (each of which can also inform age). Here we recommend the continued use of most of the original (“core”) WRP coding while augmenting the system with an optional adjunct-code entry for comprehensiveness, clarity, and flexibility, and we clarify a few additional codes to cover less common molting and plumage strategies. For most users, from 7 to 13 core and 1 adjunct WRP code will be sufficient to describe all plumages and provide molt status and ages for demographic studies or other purposes. The revised WRP system is flexible enough to be adapted to the specific goals of programs while also providing core codes that can facilitate the comparison of avian age, molt, and plumage status on a global basis. We anticipate that our revised and standardized version of the WRP system will be easily adopted and could eventually replace calendar-based and seasonally based coding.
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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 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.052 | 0.024 |
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".