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Record W2988631295 · doi:10.5376/mpb.2019.10.15

Effects of Illumination Intensity on Ornamental Characteristics of <i>Neoregelia</i>

2019· article· en· W2988631295 on OpenAlexvenueno aff
Shuxia Zhan, Shaohua Yu, Xinying Yu, Qunyang Cao, Zhangjian Zhao, Weiyong Wang

Bibliographic record

VenueMolecular Plant Breeding · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsShadingOrnamental plantIntensity (physics)HabitLight intensityHorticultureMathematicsEnvironmental scienceBiologyOpticsArtVisual artsPhysicsPsychology

Abstract

fetched live from OpenAlex

Neoregelia has high ornamental value, which is tolerant to shade and drought. In addition, the daily maintenance and management of it is easy and convenient, so it is very popular with consumers. However, illumination intensity has great impact on its blade color. The four seasons in the south of Yangtze River are distinct, and cooling and shading in summer are contradictory, resulting in difficulty in production. This study introduced the morphological characteristics and growth habit of Neoregelia . Through a series of experiments in both plain and mountain sites, we confirmed that the optimum illumination intensity for most varieties of Neoregelia was 50~55 klx. During production procedure, 50% shading rate could ensure illumination intensity under 55 klx, but some green blade varieties need weaker illumination intensity. The shading rate should be kept under 70% to maintain regular blade color. 70 klx illumination intensity could burn the blade of Neoregelia . This study could provide guidance for production and daily management of Neoregelia .

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.218

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 head0.009
GPT teacher head0.184
Teacher spread0.175 · 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 designBench or experimental
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
Published2019
Admission routes1
Has abstractyes

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