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Record W2022234880 · doi:10.1139/b09-092

<i>Rhizoctonia</i> fungi enhance the growth of the endangered orchid <i>Cymbidium goeringii</i>

2010· article· en· W2022234880 on OpenAlexafffundvenue
Jianrong Wu, MA Huan-cheng, Mei Lü, Han Su-fen, Youyong Zhu, Hui Jin, Junfeng Liang, Li Liu, Jianping Xu

Bibliographic record

VenueBotany · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsBiologyCymbidiumEndangered speciesOrchidaceaeBotanyRhizoctoniaOrnamental plantInternal transcribed spacerEcologyRhizoctonia solaniPhylogenetic treeHabitat

Abstract

fetched live from OpenAlex

Orchids are among the most prized ornamental plants in many societies throughout the world. As a result, consumer demands have created a significant pressure on wild populations of many species, including Cymbidium goeringii Rchb. f., a rare terrestrial orchid endemic in China, Korea, and Japan. To help conserve natural populations of C. goeringii, we recently started investigating methods to cultivate these orchids. Here we fulfilled Koch’s postulates and demonstrated that fungal strains isolated from the roots of natural Cymbidium plants increased fresh mass, plant height, number of leaves, and root length of C. goeringii, and that the two fungal strains originally isolated from C. goeringii showed overall greater effects on growth than two other strains from other Cymbidium species. Internal transcribed spacer sequence analyses revealed that the four fungal strains likely represented at least two new taxonomic groups, both belonging to the family Ceratobasidiaceae of the Rhizoctonia fungi. Our study demonstrated that these fungal strains could potentially help the commercial cultivation of the increasingly rare and endangered orchid C. goeringii.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.005
GPT teacher head0.207
Teacher spread0.202 · 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

Citations37
Published2010
Admission routes3
Has abstractyes

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