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A New Record to Rust Fungi of South Western Province Kandahar, Afghanistan

2022· article· en· W4298140294 on OpenAlexaff
Hayatullah Ahmadi, L. I. Changtian, Qudratullah Ehsan

Bibliographic record

VenueInternational Journal of Plant & Soil Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsWeedRust (programming language)FungusPucciniaAgricultureBiologyGeographyWeed controlAgronomyBotanyEcology

Abstract

fetched live from OpenAlex

A rust fungus occurring on Centaurea iberica leaves from Arghandab district, southwestern province Kandahar Afghanistan is described and illustrated. A critical morphological and microscopical examination revealed it to be Puccinia calcitrapae. After conducting a literature survey, it was found that this fungus is the first record to be reported from southwestern province Kandahar. A detailed taxonomic description of this fungus along with its distribution is provided. Weeds cause serious problems in agriculture in Afghanistan especially in southwestern province Kandahar. These plants reduce yield and the quality of crops by competing for water, nutrients and sunlight. The improper or excessive usage of herbicides has led to development of resistance in some weed species while contaminating the environment; therefore, biological control has an increasing role as an alternative method for controlling special weed. Previous studies in other countries revealed that this rust fungus are good biological control agents for these weeds.

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)0.001
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 score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.232
Teacher spread0.218 · 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
Published2022
Admission routes1
Has abstractyes

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