GalliForm, a database of Galliformes occurrence records from the Indo-Malay and Palaearctic, 1800–2008
Bibliographic record
Abstract
Historical as well as current species distribution data are needed to track changes in biodiversity. Species distribution data are found in a variety of sources, each of which has its own distinct bias toward certain taxa, time periods or places. We present GalliForm, a database that comprises 186687 galliform occurrence records linked to 118907 localities in Europe and Asia. Records were derived from museums, peer-reviewed and grey literature, unpublished field notes, diaries and correspondence, banding records, atlas records and online birding trip reports. We describe data collection processes, georeferencing methods and quality-control procedures. This database has underpinned several peer-reviewed studies, investigating spatial and temporal bias in biodiversity data, species' geographic range changes and local extirpation patterns. In our rapidly changing world, an understanding of long-term change in species' distributions is key to predicting future impacts of threatening processes such as land use change, over-exploitation of species and climate change. This database, its historical aspect in particular, provides a valuable source of information for further studies in macroecology and biodiversity conservation.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".