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Record W4396234608 · doi:10.1139/cjb-2024-0020

Three helmet-orchid species share abundant fungi of Serendipitaceae regardless of altitude

2024· article· en· W4396234608 on OpenAlexvenueno aff
Jiao Qin, Zhou‐Dong Han, You Wu, Hong Wang, Shi‐Bao Zhang

Bibliographic record

VenueBotany · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsBiologyAltitude (triangle)BotanyEcology

Abstract

fetched live from OpenAlex

The tiny terrestrial orchids (plant height less than 8 cm) in the genus Corybas dependent on mycorrhizal fungal (OMF) partners for seed germination and seedling development. The OMF community of the Corybas remains poorly understood, although the relevant knowledge is very important for in situ and ex situ conservation of these orchids. In this study, we characterized OMF richness and compositions of three helmet-orchid species, i.e., Corybas geminigibbus, C. himalaicus, and C. shanlinshiensis, from their natural habitats by using Illumina sequencing of the internal transcribed spacer 2 region. We found that fungal colonization was restricted in the rhizomes of the helmet-orchids instead of their tuberoids, and serendipitoid fungi were predominant, while tulasnelloid were absent in the three investigated Corybas species regardless of their altitude. The three Corybas species shared 27 serendipitoid operational taxonomic units that are different to those of their related orchids, the genera of Cyrtostylis and Stigmatodactylus. Corybas shanlinshiensis alone had a range of ectomycorrhizal fungi (mainly russuloid and thelephoroid) broader than C. himalaicus and C. geminigibbus. Our study provides new information about terrestrial orchid–fungi associations and may further contribute to orchid conservation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.052
GPT teacher head0.225
Teacher spread0.174 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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