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Record W1968358487 · doi:10.2134/agronj2006.0202

Dry Bean Production in Zero and Conventional Tillage

2007· article· en· W1968358487 on OpenAlexaffabout
Robert E. Blackshaw, L. Molnár, George W. Clayton, K. Neil Harker, T. Entz

Bibliographic record

VenueAgronomy Journal · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsDry beanAgronomyBentazonTillageNo-till farmingPhaseolusConventional tillageSowingCropMathematicsWeedDry matterYield (engineering)BiologySoil waterPhysics

Abstract

fetched live from OpenAlex

Adoption of zero tillage production practices for dry bean ( Phaseolus vulgaris L.) has lagged behind that of many other crops. A field experiment was conducted at two locations on the Canadian prairies to determine the response of dry bean planted into various crop stubbles in conventional and zero tillage. Dry bean emergence was delayed in one of six site years with zero tillage (ZT) compared with conventional tillage (CT) but maturity date was not affected. Dry bean density was never lower with ZT compared with CT and was higher in a few instances. There were no differences in insect or disease infestations between the two tillage treatments. Weed densities were slightly greater with ZT compared with CT but were well controlled with in‐crop applications of sethoxydim and bentazon. Flax ( Linum usitatissimum L.) was the only previous crop to negatively affect dry bean yield as volunteer flax was not adequately controlled with bentazon. Over all previous crop stubbles and years, dry bean yield was similar in both tillage systems. Dry bean yielded 2060 and 2110 kg ha −1 , and 1600 and 1710 kg ha −1 with CT and ZT at Lethbridge and Lacombe, Alberta, respectively. These results indicate that there is potential for successful production of dry bean within ZT cropping 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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.238

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 head0.021
GPT teacher head0.236
Teacher spread0.215 · 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 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

Citations16
Published2007
Admission routes2
Has abstractyes

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