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Record W4211017424 · doi:10.4236/jmmce.2022.102007

Characterization of the Clay Collected in the Locality of Dolisie in Congo-Brazzaville

2022· article· en· W4211017424 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Minerals and Materials Characterization and Engineering · 2022
Typearticle
Languageen
FieldHealth Professions
TopicTherapeutic Uses of Natural Elements
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsKaoliniteIlliteClay mineralsMineralogyGeologyFeldsparCharacterization (materials science)GeochemistryMaterials scienceQuartz

Abstract

fetched live from OpenAlex

This work aims at the characterization of the clay of the locality of Dolisie for its valorization. The mineralogical analysis was determined by the following techniques (DRX, IR, ATG and ATD), chemical analysis was determined by ICP-AES, CEC was assessed by the Metson method. The geothermal properties were determined by the granulometric analysis of the clay soil and allowed us to position the Dolisie clay in the texture triangle, the landings limits obtained allowed to place the Dolisie clay in the abacus of Casagrande and on the workability map of Bain and Highy. Chemical analysis showed that silica alumina as well as iron oxides are the major constituents in Dolisie clay The mineralogical balance showed that kaolinite and illite have similar percentages which are (20.51%) kaolinite, (28.08) illites. This leads us to believe that kaolinite is not the dominant mineral and the IR spectrum shows that kaolinite is poorly crystallized.

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.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.023
GPT teacher head0.300
Teacher spread0.276 · 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