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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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 teacher head, 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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