Bibliographic record
Abstract
A dataset containing 15280 species occurrences available in GBIF matching the query: { "and" : [ { "or" : [ "BasisOfRecord is Machine Observation", "BasisOfRecord is Specimen", "BasisOfRecord is Occurrence evidence", "BasisOfRecord is Human Observation", "BasisOfRecord is Observation", "BasisOfRecord is Material sample" ] }, { "or" : [ "DatasetKey is iNaturalist Research-grade Observations", "DatasetKey is MSU Mammalogy, Ornithology and Vertebrate Paleontology Collections", "DatasetKey is PSM Vertebrates Collection", "DatasetKey is KUBI Mammalogy Collection", "DatasetKey is University of Michigan Museum of Zoology, Division of Mammals", "DatasetKey is University of Wyoming Museum of Vertebrates (UWYMV) Mammal Collection (Arctos)", "DatasetKey is Estimación de la densidad poblacional y dieta del lince (Lynx rufus) Sierra Seri, Sonora y Janos, Chihuahua", "DatasetKey is Canadian Museum of Nature Mammal Collection", "DatasetKey is UWBM Mammalogy Collection (Arctos)", "DatasetKey is MSB Mammal Collection (Arctos)" ] }, "HasCoordinate is true", "HasGeospatialIssue is false", "TaxonKey is Lynx rufus (Schreber, 1777)", "Year 1950-2022" ] } The dataset includes 15280 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0190589-210914110416597/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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.262 | 0.156 |
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; both teacher heads 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".