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Record W2039093437 · doi:10.1002/cjce.5450840411

Biosorption of Phenol onto <i>Posidonia oceanica</i> (L.) Seagrass in Batch System: Equilibrium and Kinetic Modelling

2006· article· en· W2039093437 on OpenAlexvenueno aff
Mohamed Chaker Ncibi, Borhane Mahjoub, Mongi Seffen

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
Fundersnot available
KeywordsPosidonia oceanicaBiosorptionSeagrassPhenolBiomass (ecology)ChemistryKinetic energyBlack seaAqueous solutionPulp and paper industryAdsorptionBotanyEnvironmental engineeringEnvironmental scienceBiologyGeologyEcologyPhysicsOrganic chemistryOceanographyEcosystemEngineering

Abstract

fetched live from OpenAlex

Abstract In this research, the biosorption of phenol using the fibres of a Mediterranean seagrass Posidonia oceanica (L.) was studied. Batch experimental procedures were made to investigate the ability of this novel marine biomass to remove phenol from aqueous phase. The influences of pH and contact time at different initial concentrations were evaluated. The results showed that biosorption capacity was enhanced using solution pH equal to 5.2. The modelling results showed that pseudo‐second‐order and Redlich‐Peterson models were found to be the most suitable to satisfactory describe the kinetic and equilibrium adsorption data, respectively.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.995

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)0.0000.000

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 head0.004
GPT teacher head0.144
Teacher spread0.140 · 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 designSimulation or modeling
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

Citations41
Published2006
Admission routes1
Has abstractyes

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