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Record W1986511045 · doi:10.2190/na.35.2.c

Thermally Modified Rock: The Experimental Study of “Fire-Cracked” Byproducts of Hot Rock Cooking

2014· article· en· W1986511045 on OpenAlexaff
Anthony P. Graesch, Tianna DiMare, Gregson Schachner, David M. Schaepe, John Dallen

Bibliographic record

VenueNorth American Archaeologist · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsNative Mental Health Association of Canada
Fundersnot available
KeywordsCobbleMiddenArchaeologyHearthGeologyHuman settlementEnvironmental scienceMining engineeringGeography

Abstract

fetched live from OpenAlex

Despite its ubiquity in residential middens at many North American archaeological sites, thermally modified rock (TMR) is among the least studied elements of the archaeological record. TMR assemblages, however, may provide key insights into routine cooking practices, patterns of refuse disposal, and midden formation processes. This article outlines the results of experimental research aimed at understanding the conditions by which TMR assemblages were created in residential settlements in the Pacific Northwest. We present baseline data addressing the thermal properties of the hearth, the rate and circumstances of cobble fracturing, the extent to which different kinds of cobbles break when exposed to heat for varying durations, and the effectiveness of hot cobbles at achieving cooking temperatures.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.224
Teacher spread0.207 · 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 designBench or experimental
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

Citations22
Published2014
Admission routes1
Has abstractyes

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