Bibliographic record
Abstract
A dataset containing 467 species occurrences available in GBIF matching the query: { "and" : [ "TaxonKey is Progne subis (Linnaeus, 1758)", "Country is Canada", "Geometry POLYGON((-130.341796 50.847572,-126.826171 49.296471,-124.189453 48.253941,-123.090820 48.224672,-122.827148 48.661942,-122.827148 49.009050,-113.950195 48.980216,-114.609374 49.724479,-114.916992 50.597186,-115.971679 51.234407,-117.202148 52.321910,-119.355468 53.409531,-119.926757 53.800650,-120.014648 54.085173,-120.014648 56.632063,-120.014648 59.998986,-139.306640 60.064840,-138.647460 59.712097,-137.8125 59.288331,-137.680664 58.699775,-136.538085 59.040554,-135.834960 59.489726,-135.527343 59.689926,-135 59.153403,-133.769531 58.516651,-133.022460 57.727619,-132.451171 57.350237,-132.275390 56.920996,-131.264648 56.218923,-130.166015 56.022948,-130.297851 55.578344,-130.209960 55.203953,-130.473632 54.952385,-130.825195 54.851315,-131.352539 54.444491,-133.198242 54.418929,-133.549804 54.213861,-133.549804 53.722716,-130.341796 50.847572))", "HasCoordinate is true", "HasGeospatialIssue is true" ] } The dataset includes 467 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016555-151016162008034/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 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.300 | 0.435 |
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; the direct Gemma label and the distilled Codex classifier 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".