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Record W4407096098 · doi:10.7451/cbe.2023.65.5.1

Assessing greenhouse gas and ammonia emissions: A comparison of three egg production systems in Québec, Canada

2023· article· en· W4407096098 on OpenAlexfundvenueaboutno aff
Andrea Katherín Carranza-Díaz, A. Dalila Larios-Martínez, Alexis Ruíz-González, Caroline Duchaine, Martine Boulianne, Stéphane Godbout, Sébastien Fournel

Bibliographic record

VenueCanadian Biosystems Engineering · 2023
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsnot available
FundersUniversité de MontréalAustralian GovernmentMinistère de l'Agriculture, des Pêcheries et de l'AlimentationUniversité Laval
KeywordsGreenhouse gasEnvironmental scienceAmmoniaProduction (economics)ChemistryEcologyEconomicsBiology

Abstract

fetched live from OpenAlex

In Quebec, the phase-out of the conventional cage (CC) system for egg production, is expected to be completed by 2036, with a transition to alternative systems such as enriched colonies (ECs) and cage-free (CF) housing. This study aimed to assess Greenhouse gas (GHG), and ammoniac (NH3) emissions associated with those systems. The investigation involved one visit per farm to 30 commercial laying hen facilities in Southern Québec, Canada. The findings revealed that the CF system exhibited the highest numerical average of CO2 emissions (3207 ± 2423 mg h-1 hen-1), followed by CCs (2835 ± 877 mg h-1 hen-1) and ECs (2597 ± 949 mg h-1 hen-1). Furthermore, the EC system had the lowest average CH4 emissions (0.93 ± 0.54 mg h-1 hen-1), while CC (1.07 ± 0.41 mg h-1 hen-1) and CF (1.27 ± 1.11 mg h-1 hen-1) facilities had higher values. Emissions of N2O were similar across all three systems (0.04 to 0.05 ± 0.05 mg h-1 hen-1). The study revealed significant differences in NH3 emissions among CC (2.0 ± 1.0 mg h-1 hen-1), EC (2.5 ± 2.0 mg h-1 hen-1), and CF egg production systems (11.2 ± 15.9 mg h-1 hen-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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.234
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2023
Admission routes3
Has abstractyes

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