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Record W2352102472

The Effect of GA_3 and GA_(4+7) treatment on inducing seedless and Berry Growth of Kyoho Grape

2005· article· en· W2352102472 on OpenAlex
Zhuang Zhi-min

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Quality and Safety Studies
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsBerryHorticultureGibberellinBotanyMathematicsBiology
DOInot available

Abstract

fetched live from OpenAlex

GA3 and GA4+7 were evaluated at 10-days ,1-day, prebloom and bloom and 2 concentrations for inducing of seedless of Kyoho grape. GA3 and CPPU were treated 10-days postbloom once at 3concentratinos for promoting berry size. Every treatment effectively increased seedless rate of Kyoho grape over control treatment. GA3 had little more effect than GA4+7 on inducing seedless of Kyoho grape. The treatments of 1-day prebloom with GA3 were great increase in seedless rate than of 10-days prebloom. The best treatment for inducing seedless of Kyoho grape was 1-day prebloom 12.5mgL-1 GA3+10-days postbloom 12. 5mgL-1 GA3. The seedless rate was 90.91%. GA4+7 effectively increased grape fruit seat rate. The best treatment was 1-day prebloom 25 mgL-1 GA4+7 +10 day postbloom 25mgL-1 GA3+20 mgL-1 CPPU. The fruit seat rate was increased over control by up to 123.1%. GA3 had the tendency to increase the berry L/D, but GA4+7 to decrease .

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.124

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.233
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

Quick stats

Citations1
Published2005
Admission routes1
Has abstractyes

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