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 286 species occurrences available in GBIF matching the query: { "and" : [ { "or" : [ "BasisOfRecord is Observation", "BasisOfRecord is Specimen" ] }, { "or" : [ "Country is United States of America", "Country is Canada", "Country is Saint Pierre and Miquelon", "Country is Viet Nam" ] }, { "or" : [ "PublishingOrg is 7b8aff00-a9f8-11d8-944b-b8a03c50a862", "PublishingOrg is ae447c50-b8a8-11d8-92a4-b8a03c50a862" ] }, "MediaType is Image", { "or" : [ "DatasetKey is Field Museum of Natural History (Botany) Seed Plant Collection", "DatasetKey is E. C. Smith Herbarium (ACAD)", "DatasetKey is Marie-Victorin Herbarium (MT) - Plantes vasculaires", "DatasetKey is The New York Botanical Garden Herbarium (NY)", "DatasetKey is R. L. McGregor Herbarium Vascular Plants Collection", "DatasetKey is NMNH Extant Specimen Records (USNM, US)", "DatasetKey is Tropicos MO Specimen Data", "DatasetKey is Botany Division, Yale Peabody Museum", "DatasetKey is Canadian Museum of Nature Herbarium", "DatasetKey is University of British Columbia Herbarium (UBC) - Vascular Plant Collection" ] }, "HasCoordinate is true", "TaxonKey is Carex scoparia Schkuhr ex Willd." ] } The dataset includes 286 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013327-171219132708484/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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.102 |
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