The ethological shortfall: case study of an endangered shorebird
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Poor knowledge of animal behaviour impedes understanding of ecology and evolution and reduces human appreciation of the natural world. We call this the ‘ethological shortfall’, parallel to Linnean and other knowledge shortfalls in conservation biology and systematics. We analysed sound recordings of breeding spoon-billed sandpipers (Scolopacidae: Calidris pygmaea ), a critically endangered species. Sixteen years of field research, and a focused short-term study, provided material for our study. All the species’ calls are unique within its clade; hence our findings have immediate practical use for detecting individuals within the breeding period. No sound recordings exist for the lengthy non-breeding period, when most anthropogenic impacts occur. This gap needs to be filled, so that inventories and automated detection can be conducted in that period. We discovered information that is new and has scientific and practical applications at both the species and higher taxonomic levels (e.g., species-specificity of brief ‘alarm’ notes). We conclude that a useful account of endangered species’ behaviour can be obtained through first-hand knowledge of natural history, a research plan based on knowledge of related species, and targeted sampling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it