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Record W2884078481 · doi:10.20546/ijcmas.2018.706.201

Distribution of Boleteceous Mushrooms in India, Some New Records from Sal Forest of Central India

2018· article· en· W2884078481 on OpenAlexfundno aff
Rajnish Kumar Verma, Vimal Pandro

Bibliographic record

VenueInternational Journal of Current Microbiology and Applied Sciences · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
FundersIndian Council of Forestry Research and EducationTerry Fox Research Institute
KeywordsBoletusBiologyWest bengalBotanyGeographyMushroom

Abstract

fetched live from OpenAlex

An account of Boleteceous mushrooms reported from different part of India is given. Total 84 species of Boletaceae were compiled from literature with records of habitat, distribution and references. Boletus spp. are the most common (37 species) followed by Strobilomyces (9 species), Tylopilus (7 species), Boletellus (6 species), Xerocomus (5 species), Suillus (3 species), Chalciporus, Retiboletus and Pulveroboletus (2 species each), Australoboletus, Borofutus, Hemileccinum, Hortiboletus, Leccinum. Octaviania, Phylloporus, Retiboletus, Rhodactina, Suillellus, Xerocomellus (one species each). Among Indian states, Himachal Pradesh and Sikkim represent the most boletes mushroom (16 species each) followed, Meghalaya (13), West Bengal (11), Madhya Pradesh and Uttarakhand (7 each), Jammu & Kashmir (5) Chhattisgarh and Kerala (4) and rest of states showed 3 or less number of species. Six species of boletes namely: Boletellus ananas, B. chrysenteroides, B. dissiliens, B. pseudochrysenteroides, B. corneri and Boletus edulis were recorded for the first time from sal forest of central India (Chhattisgarh and Madhya Pradesh). These fungi are known to form ectomycorrizal association with sal trees.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.338

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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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 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

Citations11
Published2018
Admission routes1
Has abstractyes

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