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Record W7096816762

Influence ofDay Length on the Growth ofStem, Flowering, the Morphology ofFlower Clusters, and Seed-8et in Buckwheat (Fagopyrum esculentum Moench)

2015· article· en· W7096816762 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed and Plant Biochemistry
Canadian institutionsnot available
Fundersnot available
KeywordsMorphology (biology)Period (music)Cluster (spacecraft)Main stemSignificant differenceCluster sizeDay lengthPlant morphology
DOInot available

Abstract

fetched live from OpenAlex

The pwpose of this study was to demonstrate the changes to main stem growth, flowering, morphology of flower clusters, and seed-set as affected by day length and to clarifY the difference among the cu1tiv ~ and the growth parameters. For this study we used Shinanonatsusoba (summer eco-type) and Miyazakizairai (autumn eco-type) and BLO 1999 (a long cluster line which usually develops DM clusters in Kade research Ltd., Canada). A long day period influenced main stem growth, flowering, and seed-set as was found in previous studies. FlUthennore, it was shown that a long day period increased the frequency ofOM clusters, the length offlower clusters and the mnnber of sub-flower-c1usters per cluster in Shinanonatsusoba and Miyazakizairai as well as in Bill 1999. It is confumed that the effects of day-length period varied among the growth parameters and that there were three types of responses to day length. The varietal difference between the summer and autumn eco-type cu1tiv ~ was elucidated, and was shown to be involved in the responses to day length in four groups of parameters; the main stem elongation; the first flowering node and the first flowering day; the elevating rate of flowering cluster position; and

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 score0.603
Threshold uncertainty score0.191

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 head0.017
GPT teacher head0.188
Teacher spread0.172 · 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
Published2015
Admission routes1
Has abstractyes

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