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 63424 species occurrences available in GBIF matching the query: { "and" : [ { "or" : [ "BasisOfRecord is Observation", "BasisOfRecord is Machine Observation", "BasisOfRecord is Human Observation" ] }, { "or" : [ "Country is Canada", "Country is United Kingdom of Great Britain and Northern Ireland", "Country is Russian Federation", "Country is Sweden", "Country is Finland", "Country is Iceland", "Country is Netherlands", "Country is France", "Country is United States of America" ] }, { "or" : [ "PublishingOrg is 06fcbbf0-0562-11d8-b851-b8a03c50a862", "PublishingOrg is e2e717bf-551a-4917-bdc9-4fa0f342c530", "PublishingOrg is d3978a37-635a-4ae3-bb85-7b4d41bc0b88", "PublishingOrg is 6ea87510-0561-11d8-b851-b8a03c50a862" ] }, "Issue is Coordinate rounded", "Year 2010-2018", { "or" : [ "DatasetKey is EOD – eBird Observation Dataset", "DatasetKey is Artportalen (Swedish Species Observation System)", "DatasetKey is Field Museum of Natural History (Zoology) Bird Collection", "DatasetKey is Norwegian Species Observation Service", "DatasetKey is University of Michigan Museum of Zoology, Division of Birds", "DatasetKey is UWBM Ornithology Collection" ] }, "TaxonKey is Bubo scandiacus (Linnaeus, 1758)", "License is CC0 1.0", "HasCoordinate is true", "HasGeospatialIssue is false" ] } The dataset includes 63424 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012070-181003121212138/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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.404 |
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