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Record W2778282648 · doi:10.29173/comp32

Identification of a Palaeoindian occupation in compressed stratigraphy: A case study from Ahai Mneh (FiPp-33)

2017· article· en· W2778282648 on OpenAlexaffvenueabout
Matt Rawluk, Aileen Reilly, Peter Stewart, Gabriel Yanicki

Bibliographic record

VenueCOMPASS · 2017
Typearticle
Languageen
FieldComputer Science
TopicImage Processing and 3D Reconstruction
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsProjectile pointStratigraphyArchaeologyIdentification (biology)GeologyPoint (geometry)GeographyAssemblage (archaeology)PaleontologyHistoryPhysical geographyEcology

Abstract

fetched live from OpenAlex

The 2010 University of Alberta Institute of Prairie Archaeology field school produced thousands of artifacts including diagnostic projectile points that provide evidence of multiple occupations spanning a 10,000 year period. As is typical of archaeological sites with limited surface deposition, a lack of visible stratigraphy makes it difficult to associate the assemblage with these temporal and cultural diagnostics, or assess changing occupation patterns over time. The authors present here a method reliant upon diligent attention to three-point proveniencing and analysis using low-cost, easily accessible software to complement the otherwise weak stratigraphic record; the resulting empirically segretated data show multiple components, the earliest of which correlates with an Agate Basin/Hell Gap complex occupation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.448

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 communication0.0000.001
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 head0.026
GPT teacher head0.304
Teacher spread0.278 · 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 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

Citations1
Published2017
Admission routes3
Has abstractyes

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