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Isimila Prehistoric Site, Tanzania: Comparative Faunal Datings and ESR, with a Reassessment

2023· article· en· W4390331689 on OpenAlexafffund
Maxine R. Kleindienst, Bonnie A.B. Blackwell, Anne R. Skinner

Bibliographic record

VenueJournal of African Earth Sciences · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsUniversity of Toronto
FundersInstitute of Environmental Science and ResearchUniversity of AlbertaMcMaster UniversityAmerican Philosophical SocietyWilliams CollegeWenner-Gren FoundationUniversity of ChicagoNational Archives of AustraliaField MuseumNational Science Foundation
KeywordsPrehistoryPleistoceneGeologyFaunaExcavationArchaeologyPaleontologySequence (biology)Plateau (mathematics)Early PleistoceneGeographyEcology

Abstract

fetched live from OpenAlex

More than sixty years ago, 1957-58 University of Chicago excavations at the Isimila Prehistoric Site in the Southern Highlands of Tanzania exposed a sequence of Pleistocene deposits that included Earlier Stone Age aggregates. Now, the available correlations with extinct fauna from other dated East African localities and preliminary electron spin resonance (ESR) estimates indicate that the Isimila Formation was deposited over a much longer time range than originally proposed. As originally noted, Earlier Stone Age ‘large cutting tools' or LCT's found in the upper Lisalamagasi Member are more refined than are those found in the Sands units of the lower Lukingi Member. This suggests a correlation with Kalambo Falls Prehistoric Site for the upper member, with new OSL dating at ca. 400–500 ka. The new faunal correlations and ESR estimates indicate that the lower member was deposited between 500 and 900 ka, during the later Early Pleistocene to the early Middle Pleistocene. A reassessment of Isimila including unpublished excavation data raises questions about the Pleistocene human occupations and their palaeoenvironments on the Highlands Plateau.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.097
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.330
Teacher spread0.284 · 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 teacher head, 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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueJournal of African Earth SciencesSame topicPleistocene-Era Hominins and ArchaeologyFrench-language works237,207