Bibliographic record
Abstract
A dataset containing 17449 species occurrences available in GBIF matching the query: { "and" : [ "BasisOfRecord is Human Observation", "Country is Canada", "DatasetKey is EOD – eBird Observation Dataset", "Geometry POLYGON((-123.37904 48.46254,-123.37849 48.46074,-123.37442 48.46033,-123.37441 48.46033,-123.371 48.46118,-123.36933 48.46211,-123.36847 48.46264,-123.36813 48.46314,-123.36777 48.46386,-123.36755 48.46456,-123.36769 48.4652,-123.3688 48.46593,-123.3701 48.46706,-123.37201 48.46893,-123.37282 48.46883,-123.3726 48.46756,-123.3733 48.46729,-123.37311 48.46606,-123.37458 48.46586,-123.37472 48.46585,-123.3758 48.46571,-123.37793 48.46525,-123.37821 48.46469,-123.378 48.46425,-123.37752 48.46289,-123.37904 48.46254))", "HasGeospatialIssue is false", "OccurrenceStatus is Present", "TaxonKey is Aves", "Year 2014-2014" ] } The dataset includes 17449 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021219-231120084113126/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 | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.338 | 0.471 |
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".