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Record W2113034465 · doi:10.1080/00071668.2011.643766

Ventilation rates in large commercial layer hen houses with two-year continuous monitoring

2012· article· en· W2113034465 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBritish Poultry Science · 2012
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsnot available
FundersPurdue University
KeywordsVentilation (architecture)Environmental scienceAirflowAnimal scienceMeteorologyEngineeringBiologyPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

1. Ventilation controls the indoor environment and is critical for poultry production and welfare. Ventilation is also crucial for assessing aerial pollutant emissions from the poultry industry. Published ventilation data for commercial layer houses have been limited, and are mostly based on short-term studies, mainly because monitoring airflow from large numbers of fans is technically challenging. 2. A two-year continuous ventilation monitoring trial was conducted at two commercial manure belt houses (A and B), each with 250 000 layers and 88 130-cm exhaust fans. All the fans were individually monitored with fan rotational speed sensors or vibration sensors. Differential static pressures across the house walls were also measured. Three fan performance assessment methods were applied periodically to determine fan degradations. Fan models were developed to calculate house ventilations. 3. A total of 693 and 678 complete data days, each containing >16 h of valid ventilation data, were obtained in houses A and B, respectively. The two-year mean ventilation rates of houses A and B were 2·08 and 2·10 m(3) h(-1) hen(-1), corresponding to static pressures of -36·5 and -48·9 Pa, respectively. For monthly mean ventilation, the maximum rates were 4·87 and 5·01 m(3) h(-1) hen(-1) in July 2008, and the minimum were 0·59 and 0·81 m(3) h(-1) hen(-1) in February 2008, for houses A and B, respectively. 4. The two-year mean ventilation rates were similar to those from a survey in Germany and a 6-month study in Indiana, USA, but were much lower than the 8·4 and 6·2 m(3) h(-1) hen(-1) from a study in Italy. The minimum monthly mean ventilation rates were similar to the data obtained in winter in Canada, but were lower than the minimum ventilation suggested in the literature. The lower static pressure in house B required more ventilation energy input. The two houses, although identical, demonstrated differences in indoor environment controls that represented potential to increase ventilation energy efficiency, and reduce carbon footprints and operational costs.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.380

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 communication0.0000.001
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 head0.019
GPT teacher head0.281
Teacher spread0.262 · 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