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Record W2170803862 · doi:10.1002/cjce.5450850615

Electrochemical Deodorization and Disinfection of Hog Manure

2007· article· en· W2170803862 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsElectrochemistryManureEnvironmental scienceWaste managementPulp and paper industryChemistryEngineeringBiologyElectrodeAgronomy

Abstract

fetched live from OpenAlex

Abstract Electrolysis of liquid hog manure under direct current achieved amelioration of odour, in terms of both odour quality and odour intensity, and simultaneously reduced the population of odour‐causing bacteria by two orders of magnitude. A comparison of anode materials indicated that hydroxyl radical‐forming anodes (boron‐doped diamond and Ebonex) were the most effective, but unfortunately these materials are not yet available commercially in large size format. Dimensionally stable anodes composed of Ti/IrO 2 were found to be satisfactory; lead‐based anodes leached unacceptable quantities of inorganic lead into the treated manure, and graphite anodes tended to disintegrate on long‐term use. The mechanism of action of the bactericidal effect involves a combination of toxicity by O 2 that is released at the anode and hypochlorination due to the chloride ion that is present in manure. The proposed technology was shown to be successful at the 27 L scale in an on‐farm demonstration.

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 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 score0.064
Threshold uncertainty score0.182

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 head0.004
GPT teacher head0.216
Teacher spread0.212 · 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