Bibliographic record
Abstract
A dataset containing 9561 species occurrences available in GBIF matching the query: { "and" : [ "BasisOfRecord is Human Observation", "Continent is North America", "Country is Canada", "DatasetKey is iNaturalist Research-grade Observations", "GbifRegion is North America", "Geometry POLYGON((-80.14155 45.06872,-80.60743 45.44894,-81.65136 45.42047,-82.23968 45.11012,-83.72667 42.87962,-83.1484 41.14479,-73.89596 44.11879,-73.97857 46.18406,-77.1771 46.05555,-77.91729 46.30499,-78.40498 46.32663,-78.32111 46.10565,-78.13778 46.15232,-78.09444 46.06565,-77.91445 46.11898,-77.8804 46.05884,-77.68592 46.11002,-77.51702 45.77223,-77.83946 45.66987,-77.80363 45.57262,-77.87017 45.5368,-77.84458 45.4805,-77.99812 45.41908,-78.20342 45.33161,-78.32229 45.58256,-78.63928 45.4868,-78.86711 45.41086,-79.07513 45.78067,-79.76853 45.41746,-79.70579 45.32501,-80.14155 45.06872))", "HasCoordinate is true", "HasGeospatialIssue is false", "StateProvince is Ontario", "TaxonKey is Alliaria petiolata", "Year 2015-2025" ] } The dataset includes 9561 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026017-250711103210423/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 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.229 | 0.364 |
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".