Replication Data for: Late Cretaceous Vertebrates of the Manitoba Escarpment
Bibliographic record
Abstract
This dataset (SuppMat5) contains a catalogue of over 6,500 marine vertebrate specimens collected from Upper Cretaceous geologic units exposed along the Manitoba escarpment in east-central Saskatchewan and southwestern Manitoba and housed in Canadian institutions. Information was collected from museum catalogues and verified through in-person collection surveys between March 2020 and September 2021. Associated specimen information provided in this catalogue includes: 1) Institutional (host museum, specimen number); 2) Taxonomic (class, order, family, genus, and species); 3) Taphonomic (articulation style, identified skeletal elements, estimated skeletal completeness); 4) Biostratigraphic (lithostratigraphic formation, member, unit, and geologic age); 5) locality (region collected from); and for select specimens, 6) associated publications; and 7) ecological information (tooth guild, minimum and maximum body mass estimates). Specimens are grouped by represented individuals, except for select specimens of chondrichthyan teeth collected from the Ashville and Favel formations.Biostratigraphic correlations made between the Upper Cretaceous vertebrate faunal assemblages of Manitoba and those of other Western Interior Seaway localities across North America using this dataset and provided museum catalogues are included as tables in a separate file (SuppMat6).
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.234 | 0.098 |
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".