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Record W2383324525

Establishment of Regeneration System in Vitro of Canada Maple

2013· article· en· W2383324525 on OpenAlexaboutno aff
Yanju Liu

Bibliographic record

VenueJournal of Tianjin Agricultural University · 2013
Typearticle
Languageen
FieldChemistry
TopicPlant-Derived Bioactive Compounds
Canadian institutionsnot available
Fundersnot available
KeywordsExplant cultureCotyledonHypocotylMapleRegeneration (biology)BiologyBotanySeedlingHorticultureIn vitroCell biology
DOInot available

Abstract

fetched live from OpenAlex

In order to establish the effective regeneration system of Canada maple, the aseptic seedlings of Canada maple were selected in the experiment, and the optimum formula for bud regeneration and rooting induction was obtained by using different explants and culture mediums containing different hormone. The results show that the bud regeneration rate was 80% on the No. 2 culture medium(MS+1.0 mg/L BA+0.2 mg/L IAA) with the highest average regeneration number per explant(2.7) and the best regeneration bud quality. The bud regeneration rate of petioles and hypocotyls was the highest(100%), while that of cotyledon was the lowest(77.5%) in explants. The average regeneration number of hypocotyls was the highest(6.5), while that of petioles was the second(3.6), and that of cotyledon was the lowest(2.6). The rooting rate of Canada maple seedlings was 100% on the medium 1/2 MS+0.2 mg/L NAA, the rooting number was the highest(5.9 per bud), and the roots were well developed.

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 score0.980
Threshold uncertainty score0.041

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.145
Teacher spread0.140 · 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
Published2013
Admission routes1
Has abstractyes

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