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Record W2884172521 · doi:10.25120/qar.21.2018.3649

Deliberate selection of rocks in the construction of the Gummingurru Stone Arrangement Site Complex, Darling Downs, Queensland

2018· article· en· W2884172521 on OpenAlexaff
Elena Piotto, Anne Ross, Cassandra Perryman, Sean Ulm

Bibliographic record

VenueQueensland Archaeological Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsHeritage College
FundersAustralian Institute of Aboriginal and Torres Strait Islander Studies
KeywordsArchaeologySelection (genetic algorithm)Site selectionStatistical analysisRock artGeographyHistoryLawComputer scienceArtificial intelligenceStatisticsMathematicsPolitical science

Abstract

fetched live from OpenAlex

This paper uses statistical analyses to examine the hypothesis that the creators of the Gummingurru Stone Arrangement Site Complex, southeast Queensland, deliberately selected rocks, based on size and shape, for the production of motifs at the site. As Gummingurru is an Aboriginal site, the literature that frames the research concerns Aboriginal cultural Law and worldviews. However, because the data are archaeological measurements, quantitative statistical methods are also employed. These quantitative results demonstrate deliberate selection of rocks occurred in the construction of four of the motifs at Gummingurru. We conclude that there are archaeological signatures of human behaviour in response to the requirements of cultural Laws with respect to the choice of raw materials, at least in stone arrangement sites.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.063
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.091
GPT teacher head0.385
Teacher spread0.294 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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Same venueQueensland Archaeological ResearchSame topicPleistocene-Era Hominins and ArchaeologyFrench-language works237,207