Bibliographic record
Abstract
A dataset containing 2695 species occurrences available in GBIF matching the query: { "and" : [ "Country is Canada", "DatasetKey is iNaturalist Research-grade Observations", "Geometry POLYGON((-81.82617 43.06889,-78.66211 43.26121,-74.70703 44.71551,-72.86133 46.25585,-74.09098 49.66008,-76.55273 51.28941,-84.55078 55.12865,-89.42489 56.81014,-92.32962 49.58475,-93.86719 48.74895,-85.16602 47.87214,-83.67188 46.19504,-80.5957 45.52174,-79.98047 44.46515,-81.73828 44.46515,-81.82617 43.06889))", "HasCoordinate is true", { "or" : [ "Month is May", "Month is December", "Month is October", "Month is November", "Month is July", "Month is August", "Month is September", "Month is June", "Month is February", "Month is March", "Month is April", "Month is January" ] }, "TaxonKey is Plethodon cinereus (Green, 1818)", "Year 2018-2021" ] } The dataset includes 2695 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072811-210914110416597/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) | 0.257 | 0.407 |
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".