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Record W2029225590 · doi:10.1080/09593332608618542

Biosorption of Pentachlorophenol by Fungal Biomass from Aqueous Solutions: a Factorial Design Analysis

2005· article· en· W2029225590 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

VenueEnvironmental Technology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsBiosorptionPentachlorophenolFactorial experimentBiomass (ecology)Aqueous solutionChemistryPulp and paper industryEnvironmental scienceEnvironmental engineeringWaste managementEnvironmental chemistryMathematicsAdsorptionBiologyEngineeringOrganic chemistryEcologyStatisticsSorption

Abstract

fetched live from OpenAlex

A 2(5-1) fractional factorial design was conducted for the biosorption of pentachlorophenol (PCP) using Aspergillus niger biomass. Effects of several factors on the percentage removal of PCP from aqueous solutions were evaluated. These factors were as follows: type of biomass (autoclaved- chemically modified); pH (3-11); concentration (1-10 mgl(-1)); temperature (6-32 degrees C); and dissolved oxygen (2.5-20 mgl(-1)). Time of shaking (equilibrium time), volume of the solution and mass of biomass were kept constant. The results showed that type of biomass and pH had a larger impact on the removal of PCP. Concentration of PCP in the aqueous solution, temperature, and dissolved oxygen only marginally affected the removal efficiency of PCP.

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)0.000
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 categoriesInsufficient payload (model declined to judge)
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 score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0130.002

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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