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Record W2074569360 · doi:10.1080/09593330.2011.575186

Removal of microcystin-LR from spiked water using either activated carbon or anthracite as filter material

2011· article· en· W2074569360 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 · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsRoche (Canada)Institut National de la Recherche Scientifique
Fundersnot available
KeywordsAnthraciteActivated carbonAdsorptionChemistryPowdered activated carbon treatmentWater treatmentActivated charcoalAlgaeBacteriaPortable water purificationEnvironmental chemistryFilter (signal processing)Microcystin-LRPulp and paper industryCyanobacteriaEnvironmental engineeringNuclear chemistryChromatographyEnvironmental scienceBotanyOrganic chemistryBiologyCoal

Abstract

fetched live from OpenAlex

The occurrence of cyanobacterial toxins (blue-green algae) in drinking water sources is a big concern for human health. Removal of microcystin-LR (MC-LR) from drinking water was evaluated at the laboratory pilot scale using either granular activated carbon (GAC) or powdered activated carbon (PAC) and compared with the treatment using anthracite as filter material. Virgin GAC was more effective at removing MC-LR (initial concentration ranging from 9 to 47 microg L(-1)) to reach the World Health Organization recommended level (1.0 microg L(-1)). When the GAC filter was colonized by bacteria, the filter became less effective at removing MC-LR owing to competitive reactions occurring between protein adsorption (released by bacteria) and MC-LR adsorption. Using PAC, the concentration of MC-LR decreased from 22 to 3 microg L(-1) (removal of 86% of MC-LR) by the addition of 100 mg PAC L(-1).

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 categoriesInsufficient payload (model declined to judge)
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 score0.020
Threshold uncertainty score0.983

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)0.0180.000

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 head0.015
GPT teacher head0.204
Teacher spread0.189 · 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