Bibliographic record
Abstract
A dataset containing 372647942 species occurrences available in GBIF matching the query: { "and" : [ { "and" : [ "Country is one of (United States of America, United States Minor Outlying Islands, American Samoa, Micronesia (Federated States of), Guam, Marshall Islands, Northern Mariana Islands, Puerto Rico, Palau, Virgin Islands (U.S.))", { "not" : { "Issue" : [ "is Country coordinate mismatch" ] } } ] }, { "and" : [ "Year 2022-2024", "TaxonKey is one of (Aves [GBIF Backbone Taxonomy])", "GadmGid is one of (USA)", "DatasetKey is one of (EOD – eBird Observation Dataset, iNaturalist Research-grade Observations, Birda - Global Observation Dataset, MVZ Bird Collection (Arctos), LACM Vertebrate Collection, MLZ Bird Collection (Arctos), KUBI Ornithology Collection, CAS Ornithology (ORN), MVZ Egg and Nest Collection (Arctos), CAS Ornithology Egg & Nest (EGG))", "OccurrenceStatus is one of (Present)", "StateProvince is one of (Ontario, California, Texas, New York, Florida, Pennsylvania, Ohio, Arizona, Massachusetts, Michigan, Washington, North Carolina, Virginia, Illinois, Colorado, Oregon, Wisconsin, New Jersey, Maryland, Minnesota, Georgia, Indiana, Tennessee, Maine, South Carolina, Missouri, Connecticut, New Mexico, Utah, Louisiana, Vermont, New Hampshire, Alabama, Kansas, Montana, Kentucky, Idaho, Delaware, Iowa, Arkansas, Alaska, Nebraska, Nevada, Oklahoma, Rhode Island, West Virginia, Wyoming, Mississippi, District of Columbia, North Dakota, Hawaii, South Dakota, Washington, D.C., Tamaulipas, Chihuahua, Coahuila)" ] } ] } The dataset includes 372647942 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053597-251009101135966/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 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.261 | 0.372 |
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".