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Record W2151977709 · doi:10.3382/ps.2010-01314

Heat and moisture production by broilers during simulated cold weather transport

2011· article· en· W2151977709 on OpenAlexaff
Jon Watts, Lynette Graff, M.L. Strawford, T.G. Crowe, N. A. Burlinguette, H.L. Classen, P.J. Shand

Bibliographic record

VenuePoultry Science · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMoistureAnimal scienceBroilerEnvironmental scienceAir temperatureCold weatherBiologyMeteorologyGeography

Abstract

fetched live from OpenAlex

To ensure broiler welfare during winter transport, it is necessary to manage heat and moisture accumulation within the transport vehicles. Hence, it is necessary to determine heat production (HP) and moisture production (MP) rates under representative conditions. An environmental chamber containing a standard transport drawer was used. Cold air was drawn from outside the building, warmed to the desired temperature, and passed through the drawer at 0.35 m(3)/s. Broilers were fasted for 7 h, placed into the drawer, and exposed to test conditions within the chamber for 3 h. Air temperature and RH were measured upstream and downstream of the insulated bird compartment at 1-min intervals. Differences in the paired temperature and RH values were used to calculate sensible HP and MP for each 1 min of confinement. Effects of temperatures between -8 and -18°C and a control (+20°C) were measured for birds in 2 conditions. In condition A, there were 15 birds/drawer. Birds were 32 to 33 d old and weighed 1.8 kg. Packing density was approximately 27 kg/drawer (31 kg/m(2)). In condition B, there were 19 or 22 birds/drawer. The drawers with 19 birds contained birds that were 39 to 40 d old that weighed 2.68 kg. In the drawers with 22 birds, the birds were 35 to 36 d old and weighed 2.29 kg. In either case, the packing density was approximately 50 kg/drawer (59 kg/m(2)). Thus, the birds in condition B were bigger, more numerous, and more tightly packed than the birds in condition A. Drawers were balanced for sex. At +20°C, HP and MP rates were similar to other published values. However, for both conditions, HP and MP rates increased with decreasing exposure temperatures. In condition A, HP was 6.08 ± 0.43 W/kg and MP was 4.46 g/h per kg at 20°C compared with 87.5 ± 10.3 W/kg and 22.08 ± 5.05 g/h per kg at -15°C. In condition B, HP was 8.12 ± 1.24 W/kg and MP was 5.53 ± 1.68 g/h per kg at 20°C compared with 45.92 ± 1.95 W/kg and 12.33 ± 0.22 g/h per kg at -18°C.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.287

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 head0.016
GPT teacher head0.193
Teacher spread0.177 · 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 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

Citations21
Published2011
Admission routes1
Has abstractyes

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