Bibliographic record
Abstract
A dataset containing 5219962 species occurrences available in GBIF matching the query: { "and" : [ { "or" : [ "Country is Brazil", "Country is Mexico", "Country is Colombia", "Country is Argentina", "Country is Canada", "Country is Peru", "Country is Venezuela (Bolivarian Republic of)", "Country is Chile", "Country is Ecuador", "Country is Guatemala", "Country is Cuba", "Country is Bolivia (Plurinational State of)", "Country is Haiti", "Country is Dominican Republic", "Country is Honduras", "Country is Paraguay", "Country is Nicaragua", "Country is El Salvador", "Country is Costa Rica", "Country is Panama", "Country is Puerto Rico", "Country is Uruguay", "Country is Jamaica", "Country is Trinidad and Tobago", "Country is Guyana", "Country is Suriname", "Country is Guadeloupe", "Country is Martinique", "Country is Bahamas", "Country is Belize", "Country is Barbados", "Country is French Guiana", "Country is Saint Lucia", "Country is Curaçao", "Country is Aruba", "Country is Saint Vincent and the Grenadines", "Country is Virgin Islands (U.S.)", "Country is Grenada", "Country is Antigua and Barbuda", "Country is Dominica", "Country is Bermuda", "Country is Cayman Islands", "Country is Greenland", "Country is Saint Kitts and Nevis", "Country is Sint Maarten (Dutch part)", "Country is Turks and Caicos Islands", "Country is Saint Martin (French part)", "Country is Virgin Islands (British)", "Country is Netherlands", "Country is Anguilla", "Country is Saint Barthélemy", "Country is Saint Pierre and Miquelon", "Country is Montserrat", "Country is Falkland Islands (Malvinas)", "Country is United States of America" ] }, "TaxonKey is Diptera" ] } The dataset includes 5219962 records from 529 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040386-181108115102211/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 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.255 | 0.321 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".