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Record W7161776118 · doi:10.82308/54497

Effect of pre- and post- UV disinfection conditions on photoreactivation of fecal coliforms from a physiochemical wastewater effluent

2009· dissertation· en· W7161776118 on OpenAlexaboutno aff
Catherine Hallmich

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsnot available
Fundersnot available
KeywordsEffluentPhotolyaseWastewaterFecal coliform

Abstract

fetched live from OpenAlex

Diminuer la photoréactivation des bactéries suivant leur désinfection à l’UV peut entraîner une baisse considérable des coûts du capital et d’opération. Les objectifs de cette étude visent à déterminer quelles conditions, avant ou après le rayonnement à l’UV, permettent de diminuer la photoréactivation des coliformes fécaux contenus dans les eaux traitées de la Station d’Épuration des Eaux Usées de Montréal. Les résultats indiquent qu’à des doses d’UV de 10 et 20 mJ/cm2, un retard de 3 heures à l’illumination photoréactivante permet de prévenir la photoréactivation. De plus, une lumière photoréactivante de minimum 440 lux est nécessaire pour initier la photoréactivation, et 700 lux et plus est requis pour obtenir une photoréactivation maximale.Des expériences supplémentaires démontrent qu’une irradiation à la lumière visible avant ou pendant la désinfection à l’UV permet de diminuer la photoréactivation. L’effet est plus grand pour les bactéries d’hiver, chez lesquelles la photoréactivation diminue de moitié. Aussi, l’effet de la pré-illumination à la lumière visible est conservé pendant au moins 30 minutes. Finalement, les résultats suggèrent que les bactéries d’été ont une plus grande sensibilité à l’inactivation à l’UV et une plus faible capacité à photoréactiver que leurs consoeurs d’hiver.

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 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 score0.310
Threshold uncertainty score0.760

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 head0.002
GPT teacher head0.244
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Citations0
Published2009
Admission routes1
Has abstractyes

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