Bibliographic record
Abstract
A dataset containing 9696 species occurrences available in GBIF matching the query: { "and" : [ "BasisOfRecord is one of (Human Observation, Observation)", "Country is Canada", "Geometry POLYGON((-74.03626 45.36278,-73.98277 45.32458,-73.89106 45.30012,-73.80701 45.30318,-73.63736 45.32763,-73.47688 45.35209,-73.40352 45.45754,-73.36837 45.59509,-73.37143 45.69138,-73.37448 45.73876,-73.41422 45.78155,-73.51509 45.79072,-73.57928 45.76015,-73.64194 45.73417,-73.67404 45.67915,-73.70613 45.64553,-73.77185 45.63024,-73.85438 45.6333,-73.9094 45.60732,-73.96901 45.563,-74.0546 45.48505,-74.06835 45.40252,-74.03626 45.36278))", "HasCoordinate is true", "HasGeospatialIssue is false", "OccurrenceStatus is Present", "TaxonKey is Bubo virginianus" ] } The dataset includes 9696 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000713-251120083545085/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 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.186 | 0.294 |
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".