MétaCan
Menu
Back to cohort
Record W2387242116

SCREENING AND IDENTIFICATION OF RICE GERMPLASMS WITH COLD-RISISTANCE AT SEEDLING STAGE

2011· article· en· W2387242116 on OpenAlexaff
Li Jing-quan

Bibliographic record

VenueJournal of Nuclear Agricultural Sciences · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSeedlingGermplasmJaponicaJaponica riceBiologyCold toleranceAgronomyCold stressHorticultureCultivarBotanyGene
DOInot available

Abstract

fetched live from OpenAlex

13 rice germplasm displaying cold resistance at seedling stage including 3 Indica varieties and 10 Japonica varieties have been identified from 84 varieties in Micro-core Rice Collection screened by natural low temperature.Further cold treatment in climate chamber showed that cold resistance of above 13 rice germplasms reached level of 1 to 4,of which Japonica 87-304 reached level 1 under continuous low temperature treatment.In altered low temperature condition,the leaves of cold sensitive varieties Sanbaili and Jiabala were scorched and died gradually after recovery to room temperature,but leaves of cold resistant varieties Guihuahuang and Sujiang 2 were not scorched distinctly.The extent of leaf curling and chlorophyll fading under cold stress within a comparatively short period could be applied as an efficient index for identification of cold resistance during seedling stage.The research provides novel rice germplasm for cold resistance breeding and a basis for cloning cold resistance genes in rice.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.047
GPT teacher head0.240
Teacher spread0.192 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Nuclear Agricultural SciencesSame topicGABA and Rice ResearchFrench-language works237,207