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Record W3081516750

Evaluation of finger millet genotypes against three major diseases in east and south eastern coastal plain zone of Odisha

2020· article· en· W3081516750 on OpenAlexaboutno aff
Sushri Sangita Bal, Satendra Kumar, I.O.P. Mishra, PM Mahapatra, RK Panigrahi, P. Panda

Bibliographic record

VenueJournal of Pharmacognosy and Phytochemistry · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsSuccessor cardinalAgricultureNonprobability samplingSocioeconomicsGeographyScheduleMultistage samplingQuarter (Canadian coin)Distribution (mathematics)Economic growthAgricultural economicsSociologyMathematicsDemographyEconomicsPopulationManagement
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates the socio-economic distribution of farm youths engaged in agripreneurship. The study was conducted in five agro-climatic zones of Odisha state. The purposive random sampling method was followed for the selection of respondents which includes 250 farm youths from five districts. The data was collected with the help of self-structured interview schedule and focused group discussions. The findings of this study revealed that around three quarter of farm youths are of more than 30 years of age with majority of them attaining higher secondary education and more than three fourth fourths of them have small operational holdings. Most of the respondents attain medium level of annual income and training exposure with greater access to social media. This study provides a reasonable coverage of key socio-economic dimensions that will help the policy maker while formulating any strategies for the farm youth who are extremely important target group for agricultural development perspective in rural areas, as their dissociation from farming will deprive the sector from next generation successor.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.167

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 head0.048
GPT teacher head0.252
Teacher spread0.204 · 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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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