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Record W1851614022 · doi:10.1139/cjb-2015-0111

An efficient temporary immersion system for micropropagation of hybrid hazelnut

2015· article· en· W1851614022 on OpenAlexafffundvenue
Jyoti Latawa, Mukund R. Shukla, Praveen K. Saxena

Bibliographic record

VenueBotany · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsUniversity of Guelph
FundersUniversity of Guelph
KeywordsShootMicropropagationBiologyCultivarBotanyMurashige and Skoog mediumHorticultureAcetic acidAcclimatizationExplant cultureIn vitroBiochemistry

Abstract

fetched live from OpenAlex

An efficient protocol for the micropropagation of hybrid hazelnut (Corylus L.) was developed using a temporary immersion system (TIS) for the proliferation of shoots in a liquid medium. Growth and proliferation of shoots as well as the length and number of nodes in developing shoots were significantly improved by combining two forms of chelated iron: ethylenediamine-N,N′-di-(ortho-hydroxyphenyl) acetic acid (FeEDDHA), and FeSO 4 /EDTA (FeEDTA). The use of TIS with optimized concentrations of FeEDTA and FeEDDHA significantly increased the number of shoots, shoot height, leaf area, and chlorophyll content in all of the four cultivars tested, compared with a semi-solid medium. Proliferated shoots developed roots on a semi-solid medium containing 2.5 μmol/L indole-3-butyric acid and rooted plantlets acclimatized in greenhouse conditions with 80% survival.

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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.242
Teacher spread0.227 · 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

Citations54
Published2015
Admission routes3
Has abstractyes

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