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Record W2799899291 · doi:10.1139/cjz-2017-0230

Dental enamel hypoplasias in Holocene bighorn sheep (<i>Ovis</i> <i>canadensis</i>) in eastern Washington state, USA

2018· article· en· W2799899291 on OpenAlexvenueno aff
R. Lee Lyman

Bibliographic record

VenueCanadian Journal of Zoology · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOvis canadensisExtant taxonHypoplasiaEnamel paintBiologyMammalOvisEnamel hypoplasiaMolarDental enamelHoloceneZoologyArchaeologyDentistryAnatomyEcologyGeographyPaleontologyEvolutionary biologyMedicine

Abstract

fetched live from OpenAlex

Dental enamel hypoplasias have been documented in extant and fossil mammal species and attributed to several kinds of physiological stress. They have not previously been reported among bighorn sheep (Ovis canadensis Shaw, 1804). Forty-six (36.8%) of 125 mandibular molars (m1, m2, m3) of bighorn recovered from disturbed Holocene archaeological deposits in eastern Washington state display several kinds of hypoplasias. The exact ontogenetic age of the individual animals when hypoplasias formed cannot be determined. The majority of the hypoplasias occur near the root–enamel junction of the m3, suggesting that most individuals were young adults when the defect formed. Physiological stress associated with reproductive costs, winter nutritional deficits, or both seems likely.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.231
Teacher spread0.211 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2018
Admission routes1
Has abstractyes

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