Bibliographic record
Abstract
A dataset listing the 114 species recorded in GBIF matching the query: { "and" : [ "BasisOfRecord is Human Observation", "Country is Canada", "DatasetKey is EOD – eBird Observation Dataset", "Geometry POLYGON((-121.99426 49.06705,-121.99424 49.06183,-121.99797 49.05555,-122.00494 49.04861,-122.00948 49.04672,-122.01225 49.04408,-122.01298 49.04095,-122.01203 49.03842,-122.0095 49.03469,-122.00477 49.03506,-121.99989 49.03258,-121.99294 49.03526,-121.98217 49.04046,-121.97717 49.04413,-121.97337 49.04692,-121.97074 49.05333,-121.96305 49.05595,-121.96015 49.0601,-121.96421 49.06517,-121.97383 49.06794,-121.97645 49.07251,-121.97812 49.07642,-121.98123 49.07778,-121.98435 49.07807,-121.98612 49.07564,-121.99136 49.07227,-121.99426 49.06705))", "HasGeospatialIssue is false", "OccurrenceStatus is Present", "TaxonKey is Aves", "Year 2012-2022" ] } The dataset's 114 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022381-231120084113126/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 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.516 | 0.680 |
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".