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Record W2299286794 · doi:10.1017/s0003598x00049504

Estimating trajectories of colonisation to the Mariana Islands, western Pacific

2013· article· en· W2299286794 on OpenAlexaff
Scott M. Fitzpatrick, Richard Callaghan

Bibliographic record

VenueAntiquity · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsColonisationChronologySettlement (finance)HistoryGeographyArchaeologyTRACE (psycholinguistics)New guineaEthnologyAncient historyGenealogyColonization

Abstract

fetched live from OpenAlex

The colonisation of the Pacific islands represents one of the major achievements of early human societies and has attracted much attention from archaeologists and historical linguists. Determining the pattern and chronology of colonisation remains a challenge, as new discoveries continue to push back dates of earliest settlement. The length and direction of the colonising voyages has also led to lively debate seeking to trace languages and artefactual techniques and traditions to presumed places of origin. Seafaring simulation models provide one way of resolving these controversies. One of the most remote of these island groups, the Marianas, is shown here to have been settled not from Taiwan or the Philippines, as has been argued inAntiquityby Hunget al. (2011) and Winteret al. (2012), but from New Guinea or Island Southeast Asia to the south. It represents an incredible feat of early navigation over an ocean distance of some 2000km.

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)0.003
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 score0.151
Threshold uncertainty score0.301

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
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 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

Citations92
Published2013
Admission routes1
Has abstractyes

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