Bibliographic record
Abstract
A dataset containing 787 species occurrences available in GBIF matching the query: { "and" : [ { "or" : [ "BasisOfRecord is Specimen", "BasisOfRecord is Machine Observation", "BasisOfRecord is Literature Occurrence" ] }, { "or" : [ "Country is Honduras", "Country is Nicaragua", "Country is Costa Rica", "Country is El Salvador", "Country is Mexico", "Country is Guatemala" ] }, { "or" : [ "PublishingOrg is b554c320-0560-11d8-b851-b8a03c50a862", "PublishingOrg is b4640710-8e03-11d8-b956-b8a03c50a862", "PublishingOrg is 493fe050-055d-11d8-b84f-b8a03c50a862", "PublishingOrg is bc092ff0-02e4-11dc-991f-b8a03c50a862", "PublishingOrg is 8edbbde0-055e-11d8-b850-b8a03c50a862", "PublishingOrg is ff418020-1d67-11d9-8435-b8a03c50a862", "PublishingOrg is c0dc3c80-23f9-11dc-98d1-b8a03c50a862", "PublishingOrg is ff90b050-c256-11db-b71b-b8a03c50a862", "PublishingOrg is 6ea87510-0561-11d8-b851-b8a03c50a862" ] }, { "or" : [ "Issue is Coordinate rounded", "Issue is Geodetic datum assumed WGS84", "Issue is Coordinate reprojected" ] }, { "or" : [ "DatasetKey is Mammalogy Collection - Royal Ontario Museum", "DatasetKey is UCLA Donald R. Dickey Bird and Mammal Collection", "DatasetKey is Museum of Comparative Zoology, Harvard University", "DatasetKey is Actualización y enriquecimiento de las bases de datos del proyecto de evaluación y análisis geográfico de la diversidad faunística de Chiapas", "DatasetKey is MVZ Mammal Collection (Arctos)", "DatasetKey is University of Michigan Museum of Zoology, Division of Mammals", "DatasetKey is NMNH Extant Specimen Records (USNM, US)", "DatasetKey is AMNH Mammal Collections", "DatasetKey is KUBI Mammalogy Collection", "DatasetKey is LACM Vertebrate Collection" ] }, { "or" : [ "InstitutionCode is lacm", "InstitutionCode is kunhm", "InstitutionCode is usnm", "InstitutionCode is mvz", "InstitutionCode is rom", "InstitutionCode is nmnh-si", "InstitutionCode is nd", "InstitutionCode is ucla", "InstitutionCode is ummz", "InstitutionCode is ku" ] }, "TaxonKey is Liomys salvini (Thomas, 1893)" ] } The dataset includes 787 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024540-180131172636756/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 | 0.009 |
| 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) | 0.365 | 0.459 |
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".