Bibliographic record
Abstract
A dataset containing 2671069 species occurrences available in GBIF matching the query: { "and" : [ "Country is Canada", "Geometry POLYGON((-66.84618 48.07294,-67.98423 47.84612,-69.10636 47.53177,-69.12625 47.12191,-68.87954 47.0861,-68.20308 47.19354,-67.9325 46.83939,-67.83302 45.55013,-67.58631 45.41882,-67.39929 45.08059,-67.1287 45.06069,-67.02922 44.55533,-66.36868 44.68665,-65.97474 44.71848,-65.01177 45.20792,-64.98392 45.39494,-64.55078 45.70125,-63.88626 46.2663,-64.41151 46.54086,-64.50701 46.75972,-64.49906 47.03826,-63.7828 47.71074,-64.17276 48.17233,-64.66618 48.19223,-65.29887 47.89777,-65.80423 48.06489,-66.21011 48.07683,-66.73138 48.10866,-66.84618 48.07294))", "HasCoordinate is true", "HasGeospatialIssue is false", "IucnRedListCategory is one of (LC, DD, NE)", "OccurrenceStatus is Present" ] } The dataset includes 2671069 records from 501 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029553-231120084113126/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 | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.215 | 0.329 |
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".