MétaCan
Menu
Back to cohort
Record W2022660687 · doi:10.1071/ea05340

Construction and operation of open-circuit methane chambers for small ruminants

2006· article· en· W2022660687 on OpenAlexaff
Levente J. Klein, A.-D. G. Wright

Bibliographic record

VenueAustralian Journal of Experimental Agriculture · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsDepartment of Environment and Conservation
Fundersnot available
KeywordsMethaneVolume (thermodynamics)Relative humidityEnvironmental scienceCalibrationHumidityMethane emissionsChemistryAnalytical Chemistry (journal)Environmental chemistryMeteorologyMathematicsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

A detailed description of the construction, calibration and operation of 4 open-circuit chambers designed to measure methane emissions from sheep is given. These chambers have accommodated sheep under ad libitum feeding and have been used in short-term experiments and over extended periods of time. A real-time base data acquisition and process control system provided 24 h operation of the methane chambers. The gas volume measurement system consisted of dry test meters and sensors for differential and absolute pressure, temperature and relative humidity. This enabled correction of methane chamber exhaust air volume to standard temperature and pressure. Temperatures and relative humidity during measurements ranged from 21.0 to 23.1°C and 53.8 to 78.9%, respectively. The gas chromatograms were calibrated 3 times a day using commercially available gas standards. Recovery tests were conducted on each chamber by bleeding a methane gas standard into the chamber at a rate similar to methane production by sheep, with 94.4–107.1% of the methane gas recovered. Measurements on 32 sheep gave methane emissions within predicted levels and identified several low methane-producing sheep.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.174

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 head0.043
GPT teacher head0.275
Teacher spread0.232 · 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 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

Citations19
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueAustralian Journal of Experimental AgricultureSame topicRuminant Nutrition and Digestive PhysiologyFrench-language works237,207