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Record W2007521001 · doi:10.1179/pan.2007.019

A Morphometric Approach to Assessing Late Paleoindian Projectile Point Variability on the Southern High Plains

2007· article· en· W2007521001 on OpenAlexaff
Briggs Buchanan, Eileen Johnson, Richard E. Strauss, Patrick J. Lewis

Bibliographic record

VenuePlains Anthropologist · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProjectile pointAssemblage (archaeology)GeologyArchaeologyGeographyProjectilePaleontologyCavePhysical geographyTypologyPoint (geometry)GeometryMathematics

Abstract

fetched live from OpenAlex

Late Paleoindian typology on the southern High Plains has suffered from overlapping definitions and subjectivity in assigning individual projectile points to types. To address perceived projectile point variability in the region, assemblages from several localities on the southern High Plains are examined for statistical differences in shape. Digital photographs of projectile points are used to digitize point outlines. Landmark coordinate data then are used to delineate 10 interlandmark characters. Multivariate analysis of projectile points from eight assemblages reveals that the primary difference in point shape lies between long points with narrow bases and short points with wide bases. Analysis of characters by raw material type or source discerned no significant differences. Variation in point form represented by most of the assemblages, including the Plainview and Milnesand type assemblages, overlaps to a significant degree. The Lubbock Lake FA5-17 assemblage, consisting of long points with narrow bases, appears most distinct in terms of shape and raw material selection indicating the contemporaneity of different point forms and perhaps technological traditions in the region by approximately 10,000 years ago.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.005
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 head0.045
GPT teacher head0.332
Teacher spread0.287 · 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; both teacher heads agree on what is shown here.

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

Citations39
Published2007
Admission routes1
Has abstractyes

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