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Record W2039300721 · doi:10.1260/0263-6174.30.6.521

Evaluation of Biological Treatments for the Adsorption of Phenol from Polluted Waters

2012· article· en· W2039300721 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

VenueAdsorption Science & Technology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsChemistryPhenolBacteriaAdsorptionCalcium alginateActivated carbonChromatographyBiomass (ecology)Nuclear chemistryCalciumEnvironmental chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

In this study, we describe the efficiency of three biological techniques (using Pseudomonas aeruginosa) for the removal of phenol from polluted water. We explore the possibilities of elimination with free bacteria present in solution, fixed bacteria on granular activated carbon (GAC) and immobilized bacteria in calcium alginate beads. Our study results show that for all the three methods the removal of phenol from solution (300 mg l −1 ) is complete. The kinetic constants for phenol removal are equivalent for two methods, namely, bacteria fixed on the GAC and those immobilized in calcium alginate beads (≈0.2 h −1 ), while for the free bacteria in solution, it is about half of this value. We also report how the biomass production in solution depends on the method applied. The concentration seems to act as a regulator for the amount of bacteria released in solution.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.056
GPT teacher head0.298
Teacher spread0.242 · 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