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Record W4229947653 · doi:10.1017/cbo9781139087582

Human Adaptation in the Asian Palaeolithic

2012· book· en· W4229947653 on OpenAlexaff
Ryan Rabett

Bibliographic record

VenueCambridge University Press eBooks · 2012
Typebook
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsArthur B. McDonald-Canadian Astroparticle Physics Research Institute
Fundersnot available
KeywordsModernityAdaptation (eye)ColonizationPleistoceneGeographyCharacter (mathematics)Relation (database)HistoryEthnologyArchaeological recordEcologyArchaeologyBiologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

This book examines the first human colonization of Asia and particularly the tropical environments of Southeast Asia during the Upper Pleistocene. In studying the unique character of the Asian archaeological record, it reassesses long-accepted propositions about the development of human 'modernity.' Ryan J. Rabett reveals an evolutionary relationship between colonization, the challenges encountered during this process – especially in relation to climatic and environmental change – and the forms of behaviour that emerged. This book argues that human modernity is not something achieved in the remote past in one part of the world, but rather is a diverse, flexible, responsive and ongoing process of adaptation.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.050
GPT teacher head0.255
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations48
Published2012
Admission routes1
Has abstractyes

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