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Record W7047095418

Exploring enamel inside and out: evidence of developmental disruption among archaeological barren-ground caribou (Rangifer tarandus groenlandicus) from southern Baffin Island, NU

2022· dissertation· en· W7047095418 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2022
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsnot available
Fundersnot available
KeywordsEnamel paintMolarCrown (dentistry)Dental enamelEnamel organTooth enamelTooth crown
DOInot available

Abstract

fetched live from OpenAlex

Teeth are commonly excavated items among archaeological assemblages and provide key insights to the individual from which they develop. Specifically, dental enamel registers evidence of biorhythmic growth (and disruption) within the tooth crown morphology as enamel is deposited. The present research investigates evidence of systemic growth disruption among the molars of archaeological barren-ground caribou (Rangifer tarandus groenlandicus) excavated from the LdFa-1 site in southern Baffin Island, Nunavut, Canada. This study is the first to examine Rangifer crowns from the inside-out, exploring both the internal composition of enamel and surface morphology. With minimal prior data available, the overall focus of this project is to begin establishing locational patterns and frequencies of developmental disruption observed among each molar type (M1-3). Examining growth disruption at the enamel surface is accomplished by generating a profile of each tooth using laser-scanning confocal microscopy (LSCM) and assessed with two recently developed overlay techniques (a 6th order polynomial trendline and a spline curve) (Cares Henriquez and Oxenham 2020; Gamble and Milne 2018). Histological thin sections are then created and observed under polarized light to identify evidence of developmental disruption among the internal enamel matrices. A disruption event is represented by a dark line (accentuated stria of Retzius) where enamel secretion experienced abnormal pause. This study finds the spline curve to be a better fit for analyzing surface profiles via LSCM compared to 6th order polynomial, but the technique produces inaccurate evidence of enamel growth disruption. However, of 39 accentuated striae of Retzius terminating at the outer enamel surface, 23 could be associated with surface defects. This suggests that an LSCM spline curve may be a useful analytical tool for future research, but should only be applied as a supplemental approach to a more established method of identifying enamel growth defects (such as scoring accentuated striae of Retzius). This study incorporates such an approach to the present data, producing initial locational frequencies of surficial developmental disruption (referred to as linear enamel hypoplasia, or LEH) among Rangifer teeth. These trends are then interpreted based on general, yet highly synchronic caribou life-history patterns with potential to result in growth disruption.

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)0.001
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 score0.764
Threshold uncertainty score0.470

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.046
GPT teacher head0.241
Teacher spread0.195 · 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
Published2022
Admission routes1
Has abstractyes

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