Bibliographic record
Abstract
A dataset containing 485 species occurrences available in GBIF matching the query: { "and" : [ { "or" : [ "TaxonKey is Parkesia motacilla (Vieillot, 1809)", "TaxonKey is Seiurus motacilla (Vieillot, 1809)" ] }, { "or" : [ "Country is United States of America", "Country is Canada" ] }, "HasCoordinate is true", "HasGeospatialIssue is false", { "or" : [ "BasisOfRecord is Human Observation", "BasisOfRecord is Machine Observation", "BasisOfRecord is Observation", "BasisOfRecord is Material sample", "BasisOfRecord is Living Specimen", "BasisOfRecord is Literature Occurrence", "BasisOfRecord is Specimen" ] }, { "or" : [ "Month is August", "Month is May", "Month is June", "Month is July" ] }, { "or" : [ "DatasetKey is Borror Lab of Bioacoustics (BLB), Ohio State University", "DatasetKey is Vertebrate Zoology Division - Ornithology, Yale Peabody Museum", "DatasetKey is CUMV Bird Collection", "DatasetKey is Macaulay Library Audio and Video Collection", "DatasetKey is NYSM Birds", "DatasetKey is Ohio State University Tetrapod Division - Bird Collection (OSUM)", "DatasetKey is University of Michigan Museum of Zoology, Division of Birds", "DatasetKey is Birds Specimens", "DatasetKey is KUBI Ornithology Collection", "DatasetKey is WFVZ Bird Collections", "DatasetKey is iNaturalist Research-grade Observations" ] } ] } The dataset includes 485 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029951-160910150852091/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 | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.413 | 0.515 |
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".