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Record W4385432852 · doi:10.4236/jmmce.2023.114008

Physic, Chemical and Mineralogical Characterizations of Clays Used in the Making of Traditional Ceramics in the City of Katiola, C ôte d’Ivoire

2023· article· en· W4385432852 on OpenAlexaff
Isabelle Linda He, Grah Patrick Atheba, N’guadi Blaise Allou, Patrick Drogui, My Alı El Khakani, Gildas K. Gbassi

Bibliographic record

VenueJournal of Minerals and Materials Characterization and Engineering · 2023
Typearticle
Languageen
FieldMaterials Science
TopicClay minerals and soil interactions
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsKaoliniteMineralogyScanning electron microscopeFourier transform infrared spectroscopyQuartzMuscoviteCeramicMaterials sciencePotteryNuclear chemistryMetallurgyChemistryAnalytical Chemistry (journal)Chemical engineeringArchaeologyComposite materialEnvironmental chemistry

Abstract

fetched live from OpenAlex

In C ?te d’Ivoire, traditional ceramics are widely used in the form of pottery. The latter is used to store food, water and cereals. Analyzes (X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), inductive plasma optical emission spectrometry (ICP-OES), scanning electron microscopy (SEM) and analysis thermal gravimetric (ATG)) were carried out to determine the morphology, the chemical, physical and pedological constituents of these raw materials. It appears from this study that the clays used in the Mangoro pottery of Katiola contain silica SiO2, alumina Al2O3 and iron oxide Fe2O3 as well as kaolinite, muscovite, smectite and quartz.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.067
GPT teacher head0.270
Teacher spread0.203 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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