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Record W2462086583 · doi:10.2166/wst.2004.0278

The development of experimental procedures for the evaluation of additives to attenuate manure odour, and the impact of these additives on workers, animals and the environment

2004· article· en· W2462086583 on OpenAlexaff
Daniel I. Massé, Jacques Lavoie, G. Barnet, F. Croteau, Edward Topp, L. Masse

Bibliographic record

VenueWater Science & Technology · 2004
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailAgriculture and Agri-Food Canada
Fundersnot available
KeywordsManureDilutionVolatilisationEnvironmental scienceWaste managementPulp and paper industryVentilation (architecture)ChemistryEnvironmental engineeringEnvironmental chemistryEngineeringAgronomyMechanical engineering

Abstract

fetched live from OpenAlex

The objective of this project was to develop a laboratory research protocol to evaluate the effect of additives on manure odour and physico-chemical characteristics, and establish conditions that are representative of those found in farm storage structures (temperature, solids content, pH, ventilation above the manure surface, storage period). The results suggested that system configuration might have an impact on additive effect. An open system should be used when it is recommended that additives be applied in the animal diet or the gutters. Additionally, the surface/depth ratio of the gutter should be respected, since it will impact on the relative importance of the aerobic layer and on ammonia volatilization. On the other hand, a closed system should be used when the additive is applied to the manure storage tank, especially if the tank has a cover. Odour analysis still requires fundamental research to establish reliable procedures and protocols, especially in the area sample collection and dilution levels required to decrease H2S concentration to safe levels for the panellists. Odour analysis should also be conducted in triplicate, because of the possible large experimental error due to dilution, the human factors, and also instrumental error.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.033
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.297
Teacher spread0.271 · 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.

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

Citations1
Published2004
Admission routes1
Has abstractyes

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