Bibliographic record
Abstract
A dataset containing 104783 species occurrences available in GBIF matching the query: { "and" : [ "BasisOfRecord is Human Observation", "Country is Canada", "Year 1996-2000", "Geometry POLYGON((-74.13045 45.31011,-74.05521 45.28867,-73.97412 45.31419,-73.96403 45.3055,-73.96261 45.24872,-73.89016 45.24983,-73.83234 45.24555,-73.81616 45.26925,-73.81558 45.29853,-73.71238 45.20028,-73.64904 45.27432,-73.55934 45.21948,-73.46764 45.28633,-73.38218 45.40462,-73.24633 45.38177,-73.16826 45.40581,-73.11195 45.45799,-73.10303 45.53352,-73.19641 45.63927,-73.26645 45.68459,-73.25546 45.71068,-73.2486 45.76561,-73.19229 45.86998,-73.15659 45.98396,-73.17861 45.99467,-73.22525 45.90912,-73.30963 45.88645,-73.44566 45.95238,-73.53218 45.92491,-73.52394 45.86037,-73.59467 45.8329,-73.7677 45.80956,-73.81027 45.8123,-73.94897 45.78209,-74.21703 45.69214,-74.24011 45.70381,-74.25418 45.68232,-74.24873 45.6396,-74.22924 45.63786,-74.23686 45.57443,-74.20472 45.59493,-74.14842 45.54887,-74.18156 45.49403,-74.20879 45.50295,-74.2227 45.38872,-74.18447 45.38367,-74.13045 45.31011))", "DatasetKey is EOD – eBird Observation Dataset", "HasCoordinate is true", "HasGeospatialIssue is false" ] } The dataset includes 104783 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038928-181108115102211/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 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.246 | 0.376 |
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".