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Record W2115004911 · doi:10.1081/pfc-120018452

Odor Measurements for Manure Spreading Using a Subsurface Deposition Applicator

2003· article· en· W2115004911 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Environmental Science and Health Part B · 2003
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of British Columbia
Fundersnot available
KeywordsOdorOlfactometerManureDeposition (geology)Environmental scienceSplashFlux (metallurgy)Environmental engineeringWaste managementMaterials scienceMeteorologyChemistryAgronomyEngineeringEcologyGeologyMetallurgy

Abstract

fetched live from OpenAlex

Odor emissions during manure spreading events have become a source of concern, particularly where farms are located nearby urban areas. The objective of the present study was to compare odor concentrations and odor emission rates due to pig manure application using two different types of applicators, a sub-surface deposition system and a conventional splash-plate applicator. Air samples were collected using a Surface Isolation Flux Chamber and the "bag-in-vacuum chamber" techniques, at 0.5, 1.5 and 2.5 hours after manure application. A three-station forced-choice dynamic dilution olfactometer was used by an odor panel for determining odor concentration. Preliminary results indicated that with the sub-surface deposition system applicator odor emission rate was reduced by 8% to 38% compared to that of the conventional splash-plate applicator. The highest reduction in odor strength and odor emission rate was observed in the most offensive period after manure application. The sub-surface deposition system may be a solution for hog producers who wish to reduce odor complaints from applying manure without the cost and problems associated with deep injection systems.

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)0.001
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 score0.037
Threshold uncertainty score0.242

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.083
GPT teacher head0.325
Teacher spread0.242 · 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