Bibliographic record
Abstract
A dataset containing 218 species occurrences available in GBIF matching the query: { "and" : [ "Country is Canada", { "or" : [ "Month is November", "Month is October", "Month is December", "Month is September" ] }, "Year 2011-2019", "Geometry POLYGON((-80.5957 45.77304,-81.62842 45.29591,-82.33154 43.10676,-82.96875 42.47793,-83.05664 41.80997,-79.03564 42.75282,-79.07959 43.21895,-77.08008 43.85608,-75.80566 44.50215,-74.86084 44.95485,-74.00391 45.26499,-74.37744 45.57345,-75.14648 45.55806,-76.13525 45.28045,-76.83838 45.77304,-77.36572 46.06347,-78.79395 46.42816,-80.5957 45.77304))", "TaxonKey is Odocoileus virginianus (Zimmermann, 1780)", "HasGeospatialIssue is false" ] } The dataset includes 218 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001830-190320150433242/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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.190 | 0.294 |
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".