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Record W2612797311 · doi:10.31686/ijier.vol5.iss4.654

Equilibrium and Kinetic Studies of Cu(Ii) Removal from Aqueous Solutions Using a Kenyan Micaceous Mineral.

2017· article· en· W2612797311 on OpenAlexaff
John N. Wabomba, Paul M. Shiundu, John Mmari Onyari, Ernest K. Yanful

Bibliographic record

VenueInternational Journal for Innovation Education and Research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsWestern University
Fundersnot available
KeywordsSorptionCopperMicaChemistrySorbentLangmuirFreundlich equationAqueous solutionMineralZincX-ray photoelectron spectroscopyCopper extraction techniquesInorganic chemistryNuclear chemistryAdsorptionMaterials scienceMetallurgyChemical engineeringPhysical chemistry

Abstract

fetched live from OpenAlex

Copper (II) sorption on a Kenyan micaceous mineral (Mica-K) was studied in the batch mode. The effects of different experimental parameters such as; initial concentration, contact time, sorbent dose, pH, particle size, agitation speed, competition and temperature on the kinetics of copper removal were studied. The sorption pattern of copper onto Mica-K followed Langmuir and Freundlich isotherms. Thermodynamic parameters for copper sorption on Mica-K were also determined. X-ray photoelectron spectroscopic (XPS) analysis of metal ion-equilibrated Mica-K, demonstrated that copper, cadmium and Zinc containing nodules existed on the surface of Mica-K.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.805
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.183
GPT teacher head0.462
Teacher spread0.279 · 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 designBench or experimental
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

Citations0
Published2017
Admission routes1
Has abstractyes

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Same venueInternational Journal for Innovation Education and ResearchSame topicAdsorption and biosorption for pollutant removalFrench-language works237,207