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Record W4312851992 · doi:10.5334/joad.94

Presenting the AfriArch Isotopic Database

2022· article· en· W4312851992 on OpenAlexaff
Steven T. Goldstein, Sean Hixon, Erin M. Scott, Jesse Wolfhagen, Victor Iminjili, Anneke Janzen, Kendra L. Chritz, Elizabeth Sawchuk, Emmanuel Ndiema, Judith Sealy, Abigail Chipps Stone, Gretchen Zoeller, Leanne N. Phelps, Ricardo Fernandes

Bibliographic record

VenueJournal of Open Archaeology Data · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRadiocarbon datingHoloceneArchaeologyStable isotope ratioGeologyGeography

Abstract

fetched live from OpenAlex

AfriArch is an archaeological and paleoenvironmental data community designed to integrate datasets related to human-environmental interactions in Holocene Africa. Here we present a dataset of bioarchaeological stable isotope (C/N/O) and radiocarbon measurements from African archaeological sites spanning the Holocene. Modern measurements, when reported together with archaeological data in original publications, are also included. The dataset consists of 5568 entries and covers the entirety of Africa, though most isotopic research has been concentrated in southern Africa. The AfriArch isotopic dataset can be used in paleodietary, paleodemography, paleoclimatic, and paleoenvironmental studies. It can also be employed to highlight data gaps across space and time and set future research agendas.

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 categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.999
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.010
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.023

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 head0.087
GPT teacher head0.305
Teacher spread0.219 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations10
Published2022
Admission routes1
Has abstractyes

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