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Propagation of Canadian rose ‘John Franklin’

2024· article· en· W6959325554 on OpenAlexaboutno aff

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsnot available
Fundersnot available
KeywordsMicropropagationShootAuxinAxillary budVegetative reproductionSowingNutrientOrnamental plant

Abstract

fetched live from OpenAlex

\nMany researchers are interested in optimizing the clonal micropropagation of ornamental plants. It is known that the varietal specificity of the studied crops makes it necessary to select and optimize the composition of the nutrient medium for each stage of propagation in vitro. The purpose of our research was to identify the effect of the composition and concentration of nutrient hormones on multiple shoot formation, root development in regenerating plants of the rose 'John Franklin' in vitro. A technology has been developed for obtaining a large amount of self-rooted planting material of a winter-hardy decorative rose variety in vitro culture. Clonal micropropagation was performed using vegetative buds as explants. The multiple of shoots is achieved by activating the axillary meristems of the shoots. It has been shown that the efficiency of micropropagation of the 'John Franklin' rose increases on the Murashige and Skoog nutrient medium containing BAP at a concentration of 1.0 mg/l and IAA – 0.5 mg/l. This medium provides high quality regeneration of micro-shoots with a propagation coefficient equal to 5.2. The optimal modification of the nutrient medium at the rooting stage was revealed, and the expediency of using IBA with a concentration of 0.5 mg/l as auxin was noted. The selected conditions allow you to get a larger number of roots on the shoot – 5 pcs. and their greatest length is 51.5 mm.\n

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.212
Teacher spread0.196 · 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
Published2024
Admission routes1
Has abstractyes

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