Bibliographic record
Abstract
A dataset containing 552 species occurrences available in GBIF matching the query: { "and" : [ "TaxonKey is Tringa incana (Vieillot, 1816)", "Country is Canada", "Geometry POLYGON((-131.879882 51.808614,-128.144531 50.092393,-126.123046 48.951366,-124.409179 48.370847,-122.871093 48.253941,-122.915039 48.980216,-113.90625 49.009050,-114.565429 49.667627,-114.960937 50.708634,-116.586914 51.727028,-119.53125 53.696706,-119.970703 53.930219,-119.970703 60.020952,-139.086914 60.042903,-139.130859 59.756395,-137.592773 59.040554,-137.636718 58.881942,-136.801757 58.972667,-135.966796 59.310767,-135.747070 59.601095,-135.439453 59.645540,-135.175781 59.153403,-133.637695 58.401711,-132.978515 57.586558,-132.539062 56.920996,-131.440429 56.365250,-130.517578 56.022948,-130.253906 55.503749,-130.517578 55.153766,-130.737304 54.546579,-131.264648 54.418929,-132.451171 54.342148,-133.813476 54.290881,-131.879882 51.808614))", "HasCoordinate is true" ] } The dataset includes 552 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016682-151016162008034/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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.304 | 0.443 |
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; the direct Gemma label and the distilled Codex classifier 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".