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Record W4394697345 · doi:10.5334/joad.121

A Critical Inventory and Associated Chronology of the Middle Stone Age and Later Stone Age in Northwest Africa

2024· article· en· W4394697345 on OpenAlexaff
Solène Boisard, Eslem Ben Arous

Bibliographic record

VenueJournal of Open Archaeology Data · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsChronologyArchaeologyStone AgeMiddle Stone AgeAncient historyGeographyHistoryPleistocene

Abstract

fetched live from OpenAlex

The study of human evolution and cultural patterns relies on empirical evidence provided by the archaeological record. Accessing dependable archaeological data from scholarly publications can often be challenging due to the variability in site documentation and the diversity of academic practices in publication processes. This study presents a comprehensive synthesis of the published literature documenting dated and undated archaeological materials from the Middle Stone Age and Later Stone Age in Northwest Africa, notably Morocco, Algeria, Tunisia and Libya. No previously published open-access database exists for these chronocultural periods in the region. Our dataset encompasses 993 sites and 1152 dates spanning approximately 370,000 to 8,000 years ago. Through a critical evaluation of the dates, we reveal qualitative and quantitative disparities and highlight the potential of the current archaeological record. While only ~10% of sites are dated and ~4.5% have reliable dates associated with a human occupation, this database holds significant potential for demographic and taxonomic meta-analyses as well as for methodological studies associated with chronological data in archaeology.

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 score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0120.018
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.099
GPT teacher head0.361
Teacher spread0.263 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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