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Record W3137001314 · doi:10.5539/jas.v13n4p128

Callogenesis and in vitro Regeneration of Baru (Dipteryx alata Vog.) Esprouts

2021· article· en· W3137001314 on OpenAlexvenueno aff
Victória Maria Ingre Targa, Francilina Araújo Costa, Josimara Nolasco Rondon, Wagner Campos Otoni

Bibliographic record

VenueJournal of Agricultural Science · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsnot available
Fundersnot available
KeywordsCallusShootInoculationExplant cultureMurashige and Skoog mediumHorticulturePetri dishBotanyChemistryBiologyIn vitro

Abstract

fetched live from OpenAlex

The aim of this study was to evaluate the effect of different concentrations of 6-benzylaminopurine (BAP) and naphthalene acetic acid (ANA) on calogenesis and regeneration from baru leaf and apex segments. The explants were obtained from baru plants previously established in vitro from almonds and cauline apices. The leaf segments were placed in Petri dishes containing MS medium (Murashige & Skoog, 1962) with concentrations (0.0, 2.0, 3.0, 4.0 and 5.0 mg L-1) BAP combined with ANA (0.0 and 2.0 mg L-1). The shoot apices were inoculated in test tubes with the same medium using the concentrations (0.0, 0.5, 1.0 and 1.5 mg L-1) BAP combined (0.0 and 0.1 mg L-1) ANA. After 25 days of inoculation, the percentages of callus and texture in leaf explants and apices were evaluated. The number of shoots was also evaluated by the Scott-Knott test at 5% of probability. The most efficient concentration in the formation of callus in leaves was 3.0 mg L-1 BAP + 2.0 mg L-1 ANA (68.88%), at apexes the most efficient concentration was 1.0 mg L-1 BAP without ANA with 100% calogenesis. The most effective concentration was 1.0 mg L-1 BAP without ANA with an average of 1.90 of shoots in relation to the concentrations evaluated.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.008
GPT teacher head0.224
Teacher spread0.216 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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