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Record W2033082242 · doi:10.1139/s02-040

Occurrence and removal of plant sterols in pulp and paper mill effluents

2003· article· en· W2033082242 on OpenAlexfundvenueaboutno aff
Zahid Khan, Eric R. Hall

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2003
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEffluentCampesterolPhytosterolPaper millActivated sludgeStigmasterolWastewaterPulp and paper industrySterolSewage treatmentChemistryPulp (tooth)Environmental chemistryBiologyEnvironmental scienceFood scienceEnvironmental engineeringChromatographyCholesterol

Abstract

fetched live from OpenAlex

Pulp and paper mill effluents (PPMEs) are believed to contain some naturally occurring endocrine disrupting chemicals (EDCs) such as phytosterols or plant sterols, which may be related to a variety of physiological and morphological abnormalities in fish inhabiting receiving waters. Analyses of effluent streams from two Canadian pulp mills confirmed the presence of five different phytosterols in PPMEs. Sterol contents of biologically treated as well as untreated effluents are presented. ββ-Sitosterol, ββ-sitostanol (or stigmastanol), and campesterol formed the major fraction of plant sterols in PPMEs, accounting for 70 % or more of the total phytosterol content measured. Sterols entering the activated sludge treatment systems were generally removed from the effluents with average removal efficiencies of 72 and 66% for the two mills surveyed. Sorption and biodegradation may be responsible for the observed removal of plant sterols across the biological wastewater treatment systems. Key words: ββ-sitosterol, stigmastanol, campesterol, removal and mass flow of phytosterols or plant sterols, hormone disruptors, pulp mill effluents, activated sludge, industrial wastewater treatment.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
models splitAgreement compares identical category sets and study designs across arms.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.198

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 head0.006
GPT teacher head0.201
Teacher spread0.194 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Bench 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

Citations31
Published2003
Admission routes3
Has abstractyes

Explore more

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