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Record W2974688499 · doi:10.3968/11251

Stakeholders’ Perception Towards Participation in Cattle - Oil Palm Integration Projects

2019· article· en· W2974688499 on OpenAlexvenueno aff
Hock Chai Lim, Mohammad Amizi Ayob, Khairiyah Mat

Bibliographic record

VenueCanadian social science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Palm Production and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsPalm oilLivestockBusinessPerceptionDescriptive statisticsMarketingPopulationAgricultural economicsAgricultural scienceEconomicsGeographyForestrySociologyPsychology

Abstract

fetched live from OpenAlex

Having the country moving forward towards high income nations and the increased number of our population, strengthening the food security become one of nation priority. Over the years, the livestock industry seems to be growing constantly and protein livestock products are more sought after. With the vast area of oil palm plantation, there are high potential for farmers to implement the cattle-oil palm integration project. However, the numbers of farmers who took the initiatives are quite low. Therefore, this study will gather and analyze the stakeholders’ perception on the factors that influenced the decision towards implementing cattle integration in oil palm plantation. A total of 150 respondents were involved in this study and several methods used in analyzing the data namely descriptive analysis up to factor analysis. Through the Factor Analysis, the study summarize on the three (3) significant factors that might affect the farmers perception generally. Despite having several other constraints holding back the implementation, all parties’ involvement is required in moving forward to achieve the targeted goals.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.284
Teacher spread0.244 · 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.

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
Published2019
Admission routes1
Has abstractyes

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