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Record W3095518742

Identification of the most conservative plant species for promising natural enemies of arthropods pests of Vegetable crops

2020· article· en· W3095518742 on OpenAlexaboutno aff
Akhtar Ali Khan, Ajaz Ahmad Kundoo, Z. H. Khan

Bibliographic record

VenueJournal of Entomology and Zoology Studies · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyWeedDandelionPredationPopulationCropThistleAgronomyBeneficial insectsBiological pest controlHorticultureEcology
DOInot available

Abstract

fetched live from OpenAlex

Conservative plants were identified from three different districts of Kashmir viz: Srinagar, Ganderbal and Budgam during 2016-2018. A total of 20 different plant species suitable for the important natural enemies were identified. Carrot family (caraway, coriander, wild carrot, dill, fennel), butter cup, buckwheat, dandelion, yarrow, Canada thistle, may weed act as attract for the predators. Marigold, dill, coriander and onion were act as repellent plants for insect pests of vegetables. Maize was act as barrier crop for aphids and flying insects and cowpea act as alternate host for egg laying of borer and cut worms that help in avoid damage in main crops. The conservative plants that attract beneficials against Cruciferous and Solanaceous insect Pests were identified. Maximum population of predators and parasitoids were recorded in the month of May in Dill, coriander, onion and wild carrot. While as maximum population of predators and parasitoids were recorded in the month of July-August in Marigold, fennel, dandelion, clover and cowpea. Flowering periods of conservative plants play important role in the activity of natural enemies. The visiting periods of different kinds of natural enemies for conservative plants ranges from February to November, whereas the majority of the natural enemies visit the flowers from the month of April to September during both years.

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)0.001
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 score0.537
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.043
GPT teacher head0.264
Teacher spread0.220 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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