Vital rate estimates for the common eider Somateria mollissima, a data-rich exemplar of the seaduck tribe
Bibliographic record
Abstract
This database contains estimates of the following vital rates (as required to parameterise matrix population models), for the common eider (Somateria mollissima): 1st year survival (measured either from hatching, or from fledging, to 1 year old); 2nd year survival; adult annual survival; first breeding (both age-specific recruitment probability, and breeding propensity across potential recruitment ages); breeding propensity of established female breeders; clutch size; hatching success; and fledging success. These estimates are drawn from 134 studies, across the scientific and grey literature – including three previously inaccessible datasets on clutch size that were contributed in response to a call for data through the IUCN Species Survival Commission’s Duck Specialist Group (IDs 127, A and B). This is a relational database, linking estimates and associated metadata to the relevant study (or unique unpublished combination thereof) by a unique ID number in the 'MASTER' sheet. For further information, refer to the associated publication, and/or explanatory notes on the column headings of each sheet (.xlsx version only, but provided in the dataset README .txt file).
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.029 |
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".