Bibliographic record
Abstract
A dataset containing 982 species occurrences available in GBIF matching the query: { "and" : [ { "or" : [ "Country is Canada", "Country is United States of America", "Country is Mexico" ] }, { "or" : [ "DatasetKey is Brigham Young University (BYU) Herpetology Collection (Arctos)", "DatasetKey is Canadian Museum of Nature Amphibian and Reptile Collection", "DatasetKey is Herps Specimens", "DatasetKey is Bell Museum amphibians and reptiles", "DatasetKey is Field Museum of Natural History (Zoology) Amphibian and Reptile Collection", "DatasetKey is UMNH Reptiles and Amphibians Collection (Arctos)", "DatasetKey is Museum of Comparative Zoology, Harvard University", "DatasetKey is UCM Amphibian and Reptile Collection (Arctos)", "DatasetKey is Herpetology" ] }, "TaxonKey is Thamnophis sirtalis parietalis (Say, 1823)" ] } The dataset includes 982 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001222-191105090559680/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 | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.058 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.408 |
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".