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Record W3009619317 · doi:10.13031/trans.13559

Surface Covers Affect Liquid Manure Temperature, Albedo, and Evaporation

2020· article· en· W3009619317 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.

fundA Canadian funder is recorded on the work.
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

VenueTransactions of the ASABE · 2020
Typearticle
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsnot available
FundersAgriculture and Agri-Food Canada
KeywordsManureLiquid manureEvaporationEnvironmental scienceStrawAerationEnvironmental engineeringChemistryAgronomyMeteorology

Abstract

fetched live from OpenAlex

Highlights Evaporation from clear water, manure, and separated liquid manure was 4.6 mm d -1 on average. Straw, foam, geotextile, and roof covers decreased evaporation by 54%, 53%, 31%, and 21%, respectively. Albedo was highest for floating foam covers and lowest for metal roof covers. Straw, foam, and geotextile increased manure temperature compared to uncovered manure. ABSTRACT. Evaporation is a key component of the surface energy budget of liquid manure. Models rely on accurate energy budgets to predict manure temperature, which in turn is used to model temperature-dependent greenhouse gas emissions from liquid manure storages. Due to lack of data, it has been assumed that liquid manure has similar evaporative properties to water; however, this assumption may be inaccurate. Many factors, including manure crusting, covers, and turbidity, are all likely to affect the surface energy budget and the evaporation rate. This experiment investigated the differences in evaporation between eight treatments, including water, dyed water, raw and separated liquid manure, and four commonly used covers (straw, geotextile, foam, and roof), by measuring weekly evaporation. Albedo, surface temperatures, and internal temperatures were also measured to determine treatment effects. Over the 10-week study, no significant difference was found between the evaporation rates of water, raw manure, and separated liquid manure, with an average rate of 4.6 mm d -1 . Notably, the raw manure did not form a consistent surface crust, which may explain the similarities in evaporation rates in this study and is unlikely to represent manure with a crust. Overall, covers significantly decreased evaporative losses by between 21% and 54% compared to uncovered raw manure. Average evaporation rates of the covered treatments were 1.9 mm d -1 for straw cover, 2.0 mm d -1 for foam cover, 2.9 mm d -1 for geotextile cover, and 3.4 mm d -1 under a roof cover. Similarities between each treatment and water as well as between the four covered treatments and the uncovered raw manure were found using linear regression on weekly evaporation. Generally, the uncovered treatments were more similar and could be predicted (high R 2 ) by multiple linear regression with environmental variables, while the covered treatments differed more and were not as well predicted (lower R 2 ). Results from this study can help adjust evaporation rates in biophysical models to improve estimates of manure temperature, tank holding capacity, and emission predictions. Keywords: Evaporation, Dairy manure, Liquid manure, Manure covers, Manure management.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.420

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 head0.026
GPT teacher head0.269
Teacher spread0.243 · 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