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Record W2347715373

Study on Grain Yield and Growth Characteristics of Different Japonica Rice Cultivars in Chaohu City

2010· article· en· W2347715373 on OpenAlexvenueno aff
Cao Ming-long

Bibliographic record

VenueSeed · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Soil, Plant Science
Canadian institutionsnot available
Fundersnot available
KeywordsJaponica riceCultivarJaponicaSowingAgronomyYield (engineering)AdaptabilityGrain yieldBiologyGrain qualityHorticultureBotanyMaterials science
DOInot available

Abstract

fetched live from OpenAlex

A field experiment was conducted to study the adaptability,grain yield and stress resistance of stripes disease resistant cultivars of South Japonica 44 and Ningjing No.3 in Chaohu city,with Wuyunjing No.7,a native high-yield rice cultivar as ck,and to explore the optimal nitrogen level and sowing date.The results showed that the average grain yield of Ningjing No.3 was 9067kg/hm2,alone in Wuyunjing No.7 of the 9471kg/hm2,the average output of South Japonica 44 was slightly lower than 8338kg/hm2.The growth stages of three japonica rice cultivars were very similar,growed well and with resistance to common diseases of rice.So,it could conclud that Ningjing No.3 and South Japonica 44 were high-quality rice cultivars,and suitable for the growth in Chaohu city.The experiment also suggested that the optimal N application rate was 240kg/hm for Ningjing No.3 and South Japonica 44,and the sowing date was May 15 to May 25.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.222
Teacher spread0.201 · 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
Published2010
Admission routes1
Has abstractyes

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