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Record W2973085625 · doi:10.2166/wst.2019.302

Treatment of feces from beef cattle fed the enteric methane inhibitor 3-nitrooxypropanol

2019· article· en· W2973085625 on OpenAlexafffund
Valentine Nkongndem Nkemka, K. A. Beauchemin, Xiying Hao

Bibliographic record

VenueWater Science & Technology · 2019
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaAlberta Livestock and Meat Agency
KeywordsFecesAnaerobic digestionFeedlotAnimal scienceBeef cattleDigestion (alchemy)Dry matterAnaerobic exerciseForageChemistryGompertz functionBiologyMethaneFood scienceAgronomyMathematicsMicrobiologyChromatographyEcology

Abstract

fetched live from OpenAlex

Abstract The study evaluated the residual effect of the known enteric methane inhibitor 3-nitrooxypropanol (3NOP) on anaerobic digestion of cattle feces (feces) in a CH4 potential batch test and two consecutive runs of an anaerobic leach bed reactor at a solids retention time of 40 days. The feces used in this study were collected from beef cattle fed forage- (backgrounding) or grain- (finishing) based diets supplemented with 3NOP in feedlot and metabolism studies. The results showed that CH4 yields were not significantly different from treatments using control feces and feces collected from cattle fed a diet supplemented with 3NOP in both CH4 potential and leach bed studies. Spiking feces with 200 mg 3NOP kg−1 dry matter decreased CH4 production rate by 8.0–18.1% estimated from the Gompertz equation, increased the lag phase time (0.4–3.4 d) in all the treatments, while there was no significant difference in the overall CH4 yield. Results from this study showed that 3NOP can be used as an effective enteric CH4 inhibitor with no residual effect on anaerobic digestion.

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 score0.011
Threshold uncertainty score0.216

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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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

Citations11
Published2019
Admission routes2
Has abstractyes

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