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Record W2077962209 · doi:10.5539/jas.v6n3p140

Comparative Estimation of Technical Efficiency in Livestock-Oil Palm Integration in Johor, Malaysia: Evidence from Full and Partial Frontier Estimators

2014· article· en· W2077962209 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

VenueJournal of Agricultural Science · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsnot available
Fundersnot available
KeywordsInefficiencyEstimatorFrontierLivestockPalm oilProduction (economics)EstimationEconometricsProduction–possibility frontierOrder (exchange)MathematicsEconomicsStatisticsAgricultural engineeringEnvironmental scienceAgricultural scienceGeographyForestryEngineeringMicroeconomics

Abstract

fetched live from OpenAlex

Two full frontiers (DEA and FDH) and two partial frontiers (order-alpha and order-m) were employed on the same data set for comparative estimation of technical efficiency in the goat-oil palm and cattle-oil palm integration systems. Data were collected from 255 livestock-oil palm integrated smallholder farms in Johor, Malaysia for the 2011 production season. Although the estimators differ in their assumptions but the technical efficiency estimates from the four distinct estimators based on the data set used appear to be similar both in magnitude and distribution as most farms produce either on the frontier or very close to the frontier. The small nature of the farms accounts for the negligible inefficiency recorded; as recommendation, larger farm size is indeed a policy tool that can guarantee frontier production to all farms.

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)0.007
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.613
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.044
GPT teacher head0.351
Teacher spread0.307 · 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