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Record W2291272170 · doi:10.13140/2.1.3183.9049

Agronomic evaluation of novel green manures for organic grain production in Eastern Canada

2014· article· en· W2291272170 on OpenAlexaboutno aff
Rosalie Madden

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)Environmental scienceOrganic farmingAgronomyGreen manureAgricultural engineeringAgricultural scienceAgroforestryAgricultural economicsGeographyAgricultureBiologyEconomicsEngineering

Abstract

fetched live from OpenAlex

Green manures (GrM) are used to meet organic crop-N needs. Productivity and N-accumulation of three spring-planted full-season GrM in Nova Scotia and two in Québec were compared. Hairy vetch-oats accumulated 123-292 kg biomass-N ha-1 and this was significantly correlated to growing degree days (GDD). In two site years out of four however, red clover was able to fix from the atmosphere a statistically equivalent amount of N as hairy vetch. Green manures were incorporated either in the fall or the spring the following year. Over the course of a 1225 GDD soil incubation, hairy vetch-oats and red clover or red clover-oats mineralized statistically similar rates and quantities of mineral-N (93.7-111.4 kg N ha-1 and 30.0-43.7 kg N ha-1 in soils from Nova Scotia and Québec, respectively). In Nova Scotia, spring incorporation of GrM resulted in greater spring wheat N-uptake (48.6 kg N ha-1) than fall incorporation (40.6 kg N ha-1).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.231
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2014
Admission routes1
Has abstractno

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