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Record W2168705986 · doi:10.2134/jeq2006.0306

Tile Water Quality following Liquid Swine Manure Application into Standing Corn

2007· article· en· W2168705986 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Environmental Quality · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Soil, Plant Science
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsTileManureEnvironmental scienceWater qualityLiquid manureTile drainageWaste managementQuality (philosophy)AgronomyEnvironmental engineeringPulp and paper industryBiologyEngineeringMaterials scienceEcology

Abstract

fetched live from OpenAlex

The quality of water draining fields fertilized with liquid swine (Sus scrofa) manure (LSM) sidedressed into standing corn (Zea mays L.) at rates ranging from 0 to 94 m(3) ha(-1), either topdressed (TD) onto the surface, or injected (INJ) into the soil once annually for each of three consecutive years was evaluated. Liquid swine manure application rate was a critical driver of preferential flow of LSM to tile as detected by turbidity, concentrations of NH(4)(+)-N, dissolved reactive phosphorus (DRP), and the presence of enteric bacteria (Escherichia coli). Contaminant movement to drains occurred immediately after 75 and 94 m(3) LSM ha(-1) were injected (e.g., 2.5 mg DRP L(-1), 3-yr average). With injection of 56 m(3) ha(-1) or less, drainage water was not turbid and concentrations of NH(4)(+)-N, DRP, and enteric bacteria were dramatically lower than with the higher rates, even when tiles flowed freely during manure application. Application method also affected tile water quality. With TD applications (37 and 56 m(3) ha(-1)), nutrients and bacteria did not move to tiles at the time of application, but with rains that fell within 3 d after application, concentrations increased (e.g., 0.1 mg DRP L(-1)), although less than with INJ. Overall, sidedress injection rates that supplied adequate crop nutrients did not compromise drainage water quality.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 head0.019
GPT teacher head0.270
Teacher spread0.251 · 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