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Record W6899354967 · doi:10.5886/jej09d

University of Victoria - Zooarchaeology Lab Collection

2021· dataset· en· W6899354967 on OpenAlexaff

Bibliographic record

VenueCanadensys · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsOsteologyZooarchaeologyIdentification (biology)BioarchaeologyArchaeological science

Abstract

fetched live from OpenAlex

The University of Victoria’s Zooarchaeology Lab (UVicZL) is a comparative osteology collection designed to support the accurate identification of skeletal animal remains from archaeological sites in on the Northwest Coast of North America. The collection is comprised of 2,922 animals compiled over the last 40 years. A substantial percentage of animal bones archaeological sites on the Northwest Coast have been identified here. The comparative collection continues to be used by students, researchers, contractors, and community members engaged in osteological identification.

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)0.002
metaresearch head score (Gemma)0.016
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 score0.320
Threshold uncertainty score0.636

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.016
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0030.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0770.090

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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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