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Record W2263726607

Evaluation and Selection of the Optimal Scheme of Industrial Structure Adjustment Based on DEA

2006· article· en· W2263726607 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDongbei Nongye Daxue xuebao · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicEvaluation Methods in Various Fields
Canadian institutionsScience North
Fundersnot available
KeywordsData envelopment analysisScheme (mathematics)Selection (genetic algorithm)Rank (graph theory)Computer scienceScale (ratio)Mathematical optimizationOperations researchMathematicsArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

In the paper, the advanced assessment method of DEA (Date Envelopment Analysis) had been used to evaluate relative efficiency and select the optimal scheme of agricultural industrial structure adjustment. According to the results of DEA models, we analyzed scale benefits of every optional schemes, probed deeply the ultimate reason for not DEA efficient, which clarified the method and approach to improve these optional schemes. Finally, a new method had been proposed to rank and select the optimal scheme. The research is significant to direct the practice of the adjustment of agricultural industrial structure.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0020.000

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 head0.029
GPT teacher head0.300
Teacher spread0.270 · 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