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Record W2923292821 · doi:10.7717/peerj.8211

Soil and plant phytoliths from the<i>Acacia-Commiphora</i>mosaics at Oldupai Gorge (Tanzania)

2019· article· en· W2923292821 on OpenAlexaff
Julio Mercader, Siobhán Clarke, Mariam Bundala, Julien Favreau, Jamie Inwood, Makarius Itambu, Fergus Larter, Patrick Lee, Garnet Lewiski-McQuaid, Neduvoto P. Mollel, Aloyce Mwambwiga, Robert Patalano, María Soto, Laura Tucker, Dale Walde

Bibliographic record

VenuePeerJ · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSilicon Effects in Agriculture
Canadian institutionsUniversity of TorontoCochraneUniversity of Calgary
Fundersnot available
KeywordsPhytolithAcaciaAcacia mangiumTopsoilGeographyGenusBiologyEcologySoil waterBotanyAgroforestry

Abstract

fetched live from OpenAlex

This article studies soil and plant phytoliths from the Eastern Serengeti Plains, specifically the Acacia-Commiphora mosaics from Oldupai Gorge, Tanzania, as present-day analogue for the environment that was contemporaneous with the emergence of the genus Homo . We investigate whether phytolith assemblages from recent soil surfaces reflect plant community structure and composition with fidelity. The materials included 35 topsoil samples and 29 plant species (20 genera, 15 families). Phytoliths were extracted from both soil and botanical samples. Quantification aimed at discovering relationships amongst the soil and plant phytoliths relative distributions through Chi–square independence tests, establishing the statistical significance of the relationship between categorical variables within the two populations. Soil assemblages form a spectrum, or cohort of co-ocurring phytolith classes, that will allow identifying environments similar to those in the Acacia - Commiphora ecozone in the fossil record.

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)0.000
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 score0.412
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.183
Teacher spread0.175 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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