Bibliographic record
Abstract
A dataset containing 5684 species occurrences available in GBIF matching the query: { "and" : [ "Country is Canada", "Geometry POLYGON((-141.10554 61.46591,-140.3596 54.46818,-126.64832 45.62335,-121.56876 48.18089,-107.85749 48.8558,-117.30619 62.24738,-141.10554 61.46591))", "TaxonKey is one of (Frankliniella tritici (Fitch, 1855), Speranza argillacearia (Packard, 1874), Altica sylvia Malloch, 1919, Frankliniella occidentalis (Pergande, 1895), Scirtothrips ruthveni Shull, 1909, Rhagoletis mendax Curran, 1932, Ericaphis scammelli (Mason, 1940), Choristoneura rosaceana (Harris, 1841), Operophtera bruceata (Hulst, 1886), Operophtera brumata (Linnaeus, 1758), Spilonota ocellana (Denis & Schiffermüller), 1775, Archips rosana (Linnaeus, 1758), Grapholita packardi (Zeller, 1875), Malacosoma disstria Hübner, Dasineura oxycoccana (Johnson, 1899), Malacosoma californica (Packard, 1864), Tetranychus urticae Koch, 1836, Caliroa cerasi (Linnaeus, 1758), Parthenolecanium corni apuliae (Nuzzaci, 1969), Drosophila suzukii (Matsumura, 1931), Caloptilia porphyranthes (Meyrick, 1921), Phyllonorycter diversella (Braun, 1916), Otiorhynchus singularis (Linnaeus, 1767), Polydrusus sericeus (Schaller, 1783), Otiorhynchus ovatus (Linnaeus, 1758), Otiorhynchus rugosostriatus (Goeze, 1777), Otiorhynchus sulcatus (Fabricius, 1775), Sciopithes obscurus LeConte, 1876)" ] } The dataset includes 5684 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0303546-220831081235567/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 | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.329 | 0.421 |
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".