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Record W2393326942

Research Progress and Tendency in Wheat Low Temperature Genotypes

2008· article· en· W2393326942 on OpenAlexaff
Zhang Songwu, Changfa Wang

Bibliographic record

VenueZhongguo nongye Kexue · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Agricultural Sciences
Canadian institutionsScience North
Fundersnot available
KeywordsCanopyAgronomyOvercastBiologyAdaptabilityEnvironmental scienceEcologyGeographyMeteorology
DOInot available

Abstract

fetched live from OpenAlex

Low temperature wheat genotypes are a group of wheat with a slightly low canopy (plant) temperature and the research on their biological characters and utilization in wheat breeding has been done at home and abroad for more than 20 years, making great progress. The research contents and advances include the following respects: wheat genotypes with slightly low canopy temperature have been verified to exist in nature; these wheat genotypes, which present cold temperature, are superior to conventional wheat materials in some important biological characters and particularly prominently so in metabolic function and cellular structure; when they suffer such stresses as drought, high temperature and overcast and rainy weather they still keep on their superiority in some of their important biological characters so that they have a wide range of ecological adaptability; slightly low canopy temperatures of these genotypes are closely correlated with low temperatures of their second heat sources and their vigorous plants; because their low canopy temperatures can be inherited, they can exert favorable influence on the temperatures of their offspring while crossing with other wheat materials, and in particular the discovery of coldness-source wheat—contributor to low temperature, has further formed good conditions for breeding high-quality low temperature wheat varieties with a high and stable yield. Therefore, low temperature wheat genotypes are of great research importance and have a great prospect.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.247
Teacher spread0.232 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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