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Record W2110375980 · doi:10.5376/ijh.2015.05.0010

Managing Farm Risk: Issues and Strategies in Plantain Production in Osun State, Nigeria

2015· article· en· W2110375980 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Horticulture · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)State (computer science)BusinessGeographyEnvironmental protectionAgricultural scienceEnvironmental scienceComputer scienceEconomics

Abstract

fetched live from OpenAlex

The study examined various risks and their management strategies in plantain production under tropical condition. A multi-stage sampling procedure was used to select two hundred plantain farmers in the two ecological zones within Osun State, Nigeria. Primary data collected were analyzed using descriptive statistics and importance index. A comparison of the results of the two zones was undertaken. The results of the analyses revealed that shortage of capital, poor transportation system and shortage of labor (in that order of importance) were the important risks confronting plantain farmers in the study area. Diversification of income sources, native safeguard and diversification of farm enterprises were the most common strategies employed to manage the risks in the study area. Research effort should be directed at obtaining effective and efficient storage and processing technology to reduce or eliminate risk associated with the high perishable nature of plantain.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
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 head0.011
GPT teacher head0.255
Teacher spread0.245 · 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