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Record W1910390263 · doi:10.4141/cjps-2014-269

Can surface residue alleviate water and heat stress?

2014· article· en· W1910390263 on OpenAlexaffvenue
H. Wang, Yantai Gan, Kirsten Brandt, Yong He, Xiaobo Qin, Z. Li

Bibliographic record

VenueCanadian Journal of Plant Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCanolaSativumResidue (chemistry)PisumBrassicaStrawAgronomyWater stressMoistureCrop residueWater contentHorticultureChemistryBiologyAgriculture

Abstract

fetched live from OpenAlex

Wang, H., Gan, Y., Brandt, K., He, Y., Qin, X. and Li, Z. 2015. Can surface residue alleviate water and heat stress? Can. J. Plant Sci. 95: 197–200. Surface-placed residue increased the near soil surface moisture and reduced root heat stress. The improved micro environment resulted in greater root length for wheat (Triticum aestivum L.) and canola (Brassica napus) and 34, 8 and 8% higher yield, 7, 52 and 20% more straw and 7, 5, and 7.5 cm taller than the non-residue check for wheat, canola and dry pea (Pisum sativum), respectively.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score0.984

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 head0.013
GPT teacher head0.179
Teacher spread0.166 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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