Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A dataset containing 195 species occurrences available in GBIF matching the query: { "and" : [ "Country is United States of America", { "or" : [ "DatasetKey is NCSM Mollusk Collection", "DatasetKey is University of Michigan Museum of Zoology, Division of Mollusks", "DatasetKey is Malacology Collection at the Academy of Natural Sciences of Philadelphia", "DatasetKey is Auburn University Museum of Natural History Mollusks", "DatasetKey is NMNH Extant Specimen Records (USNM, US)", "DatasetKey is Delaware Museum of Nature and Science – Mollusks", "DatasetKey is LACM Malacology", "DatasetKey is Canadian Museum of Nature Mollusc Collection", "DatasetKey is Museum of Comparative Zoology, Harvard University" ] }, "HasCoordinate is true", "HasGeospatialIssue is false", "TaxonKey is Villosa taeniata (Conrad, 1834)" ] } The dataset includes 195 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021558-210914110416597/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.
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) | 0.005 | 0.122 |
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 it