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Record W6946454303 · doi:10.34990/fk2/wlbtyi

Replication Data for: Late Cretaceous Vertebrates of the Manitoba Escarpment

2022· dataset· en· W6946454303 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2022
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsEscarpmentTaphonomyCretaceousSingle specimenVertebrateHolotype

Abstract

fetched live from OpenAlex

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).

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.806
Threshold uncertainty score0.784

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.009
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2340.098

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.

Opus teacher head0.034
GPT teacher head0.267
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations1
Published2022
Admission routes2
Has abstractyes

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