MétaCan
Menu
Back to cohort
Record W4406217526 · doi:10.5772/intechopen.1008471

Sorption of Phenolic Compounds from Woodwaste Leachate by Peat Media

2024· book-chapter· en· W4406217526 on OpenAlexfundno aff
Najat Kamal, Rosa Galvez‐Cloutier, Gerardo Buelna, Abdelaziz Baçaoui

Bibliographic record

VenueIntechOpen eBooks · 2024
Typebook-chapter
Languageen
FieldEngineering
TopicSlime Mold and Myxomycetes Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSorptionChemistryLeachatePhenolEnvironmental chemistryLangmuirFreundlich equationChromatographyOrganic chemistryAdsorptionNuclear chemistry

Abstract

fetched live from OpenAlex

This study contributes to the clarification of sorption mechanism of phenolic compounds in woodwaste leachate by peat, and it is a part of the project which aims to clarify and contribute to determine and evaluate the sorption mechanism part of phenolic compounds in a trickling biofilter. To achieve this objective, mechanisms were studied separately by isolation of each process, and sorption mechanism was followed in the present study by inhibiting the biological process. The kinetic study showed that the maximum sorption capacity was reached between 20 and 24 h at 10°C and between 16 and 20 h at 20°C. However, it is during the first hours that the sorption process is high. The maximum sorption capacity was evaluated at 68.5 mg/kg (57.87% of the initial concentration) for the most polar compounds: 4-nitrophenol, phenol, and 2-chlorophenol and at 35.2 mg/kg of peat for the least polar compounds such as 2,4-dimethylphenol under conditions of pH 4 and at 10°C. The description of sorption results was evaluated by a kinetic and thermodynamic study and modeling by Langmuir and Freundlich isotherm.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.019
GPT teacher head0.224
Teacher spread0.205 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueIntechOpen eBooksSame topicSlime Mold and Myxomycetes ResearchFrench-language works237,207