Bibliographic record
Abstract
A dataset containing 379 species occurrences available in GBIF matching the query: { "and" : [ "Country is Canada", "Geometry POLYGON((-126.00793 48.94563,-123.88891 48.27784,-123.31812 48.25919,-123.15024 48.40841,-123.26216 48.63972,-123.01967 48.78894,-123.3032 48.99413,-123.4002 48.99413,-120.68369 49.02475,-122.50967 51.40647,-125.86393 51.67441,-127.15029 53.6069,-133.27258 54.48407,-133.68431 53.37418,-126.00793 48.94563))", "HasCoordinate is true", "HasGeospatialIssue is false", "OccurrenceStatus is Present", "TaxonKey is Chrysemys picta bellii (Gray, 1831)" ] } The dataset includes 379 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000990-250226211518916/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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.190 | 0.302 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".