Bibliographic record
Abstract
A dataset containing 317074 species occurrences available in GBIF matching the query: { "and" : [ "TaxonKey is Rodentia", { "or" : [ "Country is United States of America", "Country is Canada" ] }, "HasCoordinate is true", "Geometry POLYGON((-168 82,-168 40,-46.4 40,-46.4 82,-168 82))", "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" ] }, "EventDate is greater than or equal to 1898-01-01" ] } The dataset includes 317074 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003432-170627171947987/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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.244 |
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".