Bibliographic record
Abstract
A dataset containing 183262 species occurrences available in GBIF matching the query: { "and" : [ "BasisOfRecord is Specimen", { "or" : [ "Issue is Country coordinate mismatch", "Issue is Country mismatch", "Issue is Country invalid", "Issue is Country derived from coordinates", "Issue is Continent country mismatch", "Issue is Continent invalid", "Issue is Continent derived from coordinates", "Issue is Recorded date mismatch", "Issue is Recorded date invalid", "Issue is Recorded date unlikely", "Issue is Depth not metric", "Issue is Depth unlikely", "Issue is Depth min max swapped", "Issue is Depth non numeric", "Issue is Elevation unlikely", "Issue is Elevation min max swapped", "Issue is Elevation not metric", "Issue is Elevation non numeric", "Issue is Modified date invalid", "Issue is Modified date unlikely", "Issue is Identified date unlikely", "Issue is Identified date invalid", "Issue is Basis of record invalid", "Issue is Type status invalid", "Issue is Multimedia date invalid", "Issue is Multimedia URI invalid", "Issue is References URI invalid", "Issue is Individual count invalid", "Issue is Taxon match higher rank" ] }, "Year 1800-2018", "DatasetKey is Atlantic Reference Centre Museum of Canadian Atlantic Organisms - Invertebrates and Fishes Data", "HasCoordinate is true", { "or" : [ "TaxonKey is Actinopterygii", "TaxonKey is Cephalaspidomorphi" ] }, "HasGeospatialIssue is false" ] } The dataset includes 183262 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030681-180131172636756/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 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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.408 | 0.482 |
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".