Bibliographic record
Abstract
A dataset containing 1760 species occurrences available in GBIF matching the query: { "and" : [ "BasisOfRecord is Human Observation", "Continent is one of (Africa, Asia, Oceania, North America)", "Country is one of (Australia, United States of America, South Africa, New Zealand, Canada)", "DatasetKey is one of (iNaturalist Research-grade Observations, IMOS - Animal Tracking Facility - Acoustic Tracking - Quality Controlled Detections (2007 -2021), SA Fauna, TOPPWS, Diving into the vertical dimension of elasmobranch movement ecology (2000-2019), White shark (Carcharodon carcharias) tagging along eastern Australia (2007-2017))", "IucnRedListCategory is VU", "Month is one of (January, February, March, April, May, July, June, August, September, October, November, December)", "PublishingOrg is one of (5fa89f68-9af0-4a0d-8998-ea39695c1db9, 4c46f883-69c1-42ac-8a20-4cdba2afb9a6, 28eb1a3f-1c15-4a95-931a-4af90ecb574d, 6772852d-ca2e-496f-9bea-dcf86134cb19)", "TaxonKey is Carcharodon carcharias", "Year 1000-2025" ] } The dataset includes 1760 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049788-251009101135966/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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.103 |
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; both teacher heads 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".