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Record W3170229973 · doi:10.15184/aqy.2021.31

Hidden in plain sight: the archaeological landscape of Mithaka Country, south-west Queensland

2021· article· en· W3170229973 on OpenAlexaff
Michael Westaway, Douglas F. Williams, Kelsey M. Lowe, Nathan Wright, Ray Kerkhove, Jennifer Silcock, Joshua Gorringe, Justyna J. Miszkiewicz, Rachel Wood, Richard E. Adams, Tiina Manne, Shaun Adams, Tony Miscamble, Justin C. Stout, Gabriel Wróbel, Justine Kemp, Brooke Hendry, Max Gorringe, Betty Gorringe, Keiron Lander, Shawnee Gorringe, Ian Andrews, Mark Collard

Bibliographic record

VenueAntiquity · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsSimon Fraser University
FundersGriffith UniversityStrong
KeywordsPluckingArchaeologyGeographyArchaeological recordChannel (broadcasting)HistoryEngineering

Abstract

fetched live from OpenAlex

Ethnohistoric accounts indicate that the people of Australia's Channel Country engaged in activities rarely recorded elsewhere on the continent, including food storage, aquaculture and possible cultivation, yet there has been little archaeological fieldwork to verify these accounts. Here, the authors report on a collaborative research project initiated by the Mithaka people addressing this lack of archaeological investigation. The results show that Mithaka Country has a substantial and diverse archaeological record, including numerous large stone quarries, multiple ritual structures and substantial dwellings. Our archaeological research revealed unknown aspects, such as the scale of Mithaka quarrying, which could stimulate re-evaluation of Aboriginal socio-economic systems in parts of ancient Australia.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.294

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 studies0.0040.003
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.212
Teacher spread0.198 · 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

Citations23
Published2021
Admission routes1
Has abstractyes

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