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Record W2972848949 · doi:10.5539/jas.v11n16p233

Effect of Flooding Under the Gas Exchange of Cocoa Seedlings

2019· article· en· W2972848949 on OpenAlexvenueno aff
Vinícius de Souza Oliveira, Ana Paula Braido Pinheiro, Basílio Cerri Neto, Sara Dousseau Arantes, Cleidson Alves da Silva, Jeane Crasque, Maria Luiza Pereira Barbosa Pinto, Glêyce Pereira Santos, André Lucas Reboli Pagoto, Adriel Lima Nascimento, José Altino Machado Filho, Robson Prucoli Posse, Sheila Cristina Prucoli Posse, Carlos Alberto Spaggiari Souza, Omar Schmildt, Edílson Romais Schmildt

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to water stress
Canadian institutionsnot available
Fundersnot available
KeywordsTranspirationTheobromaStomatal conductanceFlooding (psychology)Environmental scienceHorticultureAgronomyBotanyBiologyPhotosynthesis

Abstract

fetched live from OpenAlex

Under flooding conditions, plants exhibit morphological and physiological characteristics that indicate that the plant is undergoing stress. In this sense, the objective of this work was to evaluate the gas exchange of cocoa (Theobroma cacao L.) seedlings submitted to different times of flooding. The study was carried out at the experimental farm of the Capixaba Institute for Research Technical Assistance and Rural Extension, in Linhares, North of the State of Espírito Santo, Brazil. The experimental design was completely randomized. The treatments consisted in the flooding of the seedlings on days 0 (without flooding), 1, 2, 4 and 8. The seedlings were evaluated for gas exchange by characteristics: liquid assimilation of CO2; stomatal conductance; transpiration rate; water use efficiency. The gas exchange of cocoa seedlings were influenced by the flooding period in which they were submitted with a decrease in the values liquid assimilation of CO2, stomatal conductance and transpiration rate after the fourth day of flooding, after this period the seedlings developed morphological modifications that allowed them to adapt the flooding conditions, improving the liquid assimilation of CO2.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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 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

Citations1
Published2019
Admission routes1
Has abstractyes

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