Bibliographic record
Abstract
A dataset containing 89521 species occurrences available in GBIF matching the query: { "and" : [ "BasisOfRecord is Human Observation", "Country is Canada", { "or" : [ "Geometry POLYGON((-359 0,-1 0,-1 90,-359 90,-359 0))", "Geometry POLYGON((-180 0,-1 0,-1 90,-180 90,-180 0))" ] }, "HasCoordinate is true", "HasGeospatialIssue is false", "Issue is Continent derived from coordinates", "Month is one of (January, February, March, December)", "OccurrenceStatus is Present", "PublishingOrg is e2e717bf-551a-4917-bdc9-4fa0f342c530", "TaxonKey is Bubo scandiacus (Linnaeus, 1758)", "Year 1000-2023" ] } The dataset includes 89521 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004659-230918134249559/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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.614 |
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; both teacher heads 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".