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Record W2512945833 · doi:10.1266/ggs.16-00014

Polar patterning of the spikelet is disrupted in the <i>two opposite lemma</i> mutant in rice

2016· article· en· W2512945833 on OpenAlexfundno aff
Shige-Hiro Sugiyama, Wakana Tanaka, Hiroyuki Hirano

Bibliographic record

VenueGenes & Genetic Systems · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceInstitute of GeneticsUniversity of TokyoMinistry of Education, Culture, Sports, Science and Technology
KeywordsLemma (botany)BiologyMutantOryza sativaPhenotypeBotanyBilateral symmetryGene duplicationPoaceaeGeneticsGene

Abstract

fetched live from OpenAlex

Angiosperms produce diverse flowers and the pattern of floral symmetry is a major factor for flower diversification. Bilaterally symmetric flowers have evolved multiple times in different angiosperm lineages from radially symmetric ancestors. Whereas most monocots produce radially symmetric flowers, grasses such as rice (Oryza sativa) and maize (Zea mays) generate bilaterally symmetric flowers and spikelets. In this paper, we focused on the two opposite lemma (tol) mutant, which displays a pleiotropic phenotype in the spikelet. Close morphological examination revealed that a typical spikelet phenotype of the tol mutant was principally based on the mirror image duplication of the lemma-side half of the spikelet. Other spikelet phenotypes can be explained as the derivation from the spikelet with this duplication. A polar pattern of organ formation along the lemma-palea axis was disrupted by this duplication. Accordingly, tol mutation seems to change the spikelet from bilateral symmetry (monosymmetry) to disymmetry. Thus, the tol mutant provides good genetic material to investigate the regulation of spikelet symmetry in rice.

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 score0.005

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 studies0.0000.001
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 head0.018
GPT teacher head0.233
Teacher spread0.215 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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