Bibliographic record
Abstract
A dataset containing 56679 species occurrences available in GBIF matching the query: { "and" : [ { "or" : [ "BasisOfRecord is Observation", "BasisOfRecord is Human Observation", "BasisOfRecord is Specimen", "BasisOfRecord is Occurrence evidence" ] }, { "or" : [ "DatasetKey is iNaturalist Research-grade Observations", "DatasetKey is Observation.org, Nature data from around the World", "DatasetKey is Ontario Breeding Bird Atlas 2001-2005", "DatasetKey is The Second Breeding Bird Atlas of Vermont (2003-2007)", "DatasetKey is Datos observacionales sobre biodiversidad Ministerio del Medio Ambiente 2015", "DatasetKey is Monitoreos trianuales de grupos hidrobiológicos en el Valle del Cerrejón, La Guajira", "DatasetKey is Registros biológicos asociados al monitoreo de la diversidad de aves en paisajes ganaderos 2013-2019", "DatasetKey is University of Michigan Museum of Zoology, Division of Birds", "DatasetKey is Cruzando el Caribe - Construyendo la capacidad para el ecoturismo en el Darién y Urabá", "DatasetKey is Muestreos de fauna silvestre existente en la franja de protección del embalse y áreas de reserva protectora de la Central Hidroeléctrica Sogamoso" ] }, { "or" : [ "Issue is Coordinate rounded", "Issue is Geodetic datum assumed WGS84" ] }, "License is CC-BY-NC 4.0", "OccurrenceStatus is Present", "TaxonKey is Cathartes aura (Linnaeus, 1758)" ] } The dataset includes 56679 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0344738-210914110416597/datasets/export for details. Data from some individual datasets included in this download may be licensed under less restrictive terms.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.369 | 0.487 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".