MétaCan
Menu
Back to cohort
Record W3082091357

A new report of rhizome rot of Sweet flag (Acorus calamus L.) caused by Sclerotium rolfsii from West Bengal, India

2018· article· en· W3082091357 on OpenAlexaboutno aff
Siddharth Singh, Goutam Mondal

Bibliographic record

VenueJournal of Pharmacognosy and Phytochemistry · 2018
Typearticle
Languageen
FieldMedicine
TopicMedicinal Plants and Neuroprotection
Canadian institutionsnot available
Fundersnot available
KeywordsSclerotiumRhizomeAcorus calamusBiologyCultivarWest bengalHorticultureBotany
DOInot available

Abstract

fetched live from OpenAlex

Acorus calamus L. is an important medicinal plant commonly known as ‘Sweet flag’ or ‘Bach’ and generally distributed in temperate countries like, North America, Canada and Europe. The plant is found throughout in India, predominantly in Himalayan and sub Himalayan regions. The rhizome rot of Sweet flag was observed in a field experiment conducted with five cultivars, viz., Aihagaripalli, Gaddipalli, Munipalli, Nagireddigudem and Symbolia in the year of 2015 in the medicinal garden, Kalyani, Nadia, West Bengal, India. The disease caused by Sclerotium rolfsii Sacc. was recorded for the first time in India. Symptoms of the disease, morphology of the pathogen and incidence were studied in details. The disease incidence was observed on all the cultivars and the maximum was on Aihagaripalli (10.12%) followed by Symbolia (8.49%) and Nagireddigudem (6.19%) and the minimum was on Munipalli (3.99%).

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.284
Teacher spread0.269 · 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 designCase report
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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pharmacognosy and PhytochemistrySame topicMedicinal Plants and NeuroprotectionFrench-language works237,207