Bibliographic record
Abstract
A dataset containing 0 species occurrences available in GBIF matching the query: { "and" : [ "BasisOfRecord is Specimen", "DatasetKey is one of (Herpetofauna de la reserva de la biósfera Valle de Tehuacán-Cuicatlán (etapa final), Inventario herpetofaunístico del valle semiárido de Tehuacán-Cuicatlán (continuación), Herpetology Collection - Royal Ontario Museum, Evaluación del riesgo de extinción de setenta y tres especies de lagartijas (Sauria) incluidas en la Norma Oficial Mexicana-059-SEMARNAT-2001, Formación de una base de datos y elaboración de un atlas de la herpetofauna de México (Anfibiosreptiles), Digitalización y Sistematización de las Colecciones Biológicas Nacionales del Instituto de Biología, UNAM (vertebrados), Inventario herpetofaunístico del valle semiárido de Tehuacán-Cuicatlán, Computarización de las colecciones de vertebrados terrestres de la Escuela Nacional de Ciencias Biológicas, IPN Fase 4 (Anfibios y reptiles), Computarización de las colecciones de vertebrados terrestres de la Escuela Nacional de Ciencias Biológicas, IPN - Fases 2, MSB Amphibian and Reptile Collection (Arctos))", "HasCoordinate is true", "HasGeospatialIssue is false", "PublishingOrg is one of (ff90b050-c256-11db-b71b-b8a03c50a862, ff418020-1d67-11d9-8435-b8a03c50a862, 939ed180-aa7b-11db-8edf-b8a03c50a862)", "TaxonKey is Phyllodactylus bordai Taylor, 1942", "Year 1950-2024" ] } The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028202-240626123714530/datasets/export for details.
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 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.388 | 0.469 |
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".