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Record W2969559908

Research Advance and Prospect on New and Breeding of High-tech for Landscape and Ornamental Plants

2004· article· en· W2969559908 on OpenAlexvenueno aff
Kongshu Ji

Bibliographic record

Venue分子植物育种 · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Genetic and Mutation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOrnamental plantMutation breedingMolecular breedingPlant breedingBiotechnologyBiologyAgroforestryEcologyAgronomy
DOInot available

Abstract

fetched live from OpenAlex

With the development on landscape market, research on breeding of landscape and ornamental plants was developed fast. Base on the traditional breeding techniques, breeding of new and high-techs in landscape and ornamental plants,including modern biotechnology, space mutation breeding, low energy ion breeding were reviewed.Mainly, current research advances were discussed on genetic and cell engineering technologies exploiting in plant stature and flower shape, color and fragrance, growth and development, life lengthening, pest and disease resistance, and adverse circumstance tolerance. Research situation and advances on breeding of space mutation and low energy ion, and relation techniques used for bring forth new germplasms of landscape and ornamental plants were reviewed. Research advances of the related departments at home were also introduced. The prospect was made for breeding techniques of landscape and ornamental plants, focused on development breeding of modern biotechnology, space mutation and low energy ion for landscape and ornamental plants.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.051
GPT teacher head0.299
Teacher spread0.249 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2004
Admission routes1
Has abstractyes

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