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Record W1995931657 · doi:10.5539/ass.v8n7p219

Land Intensive Utilization Evaluation of Linhai Industrial Zone in Xingcheng City

2012· article· en· W1995931657 on OpenAlexvenueno aff
Yongping Sun, Liping Li, Huiyuan Mao

Bibliographic record

VenueAsian Social Science · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsnot available
Fundersnot available
KeywordsDelphi methodDelphiIndex (typography)Land useBusinessIndustrial parkResearch ObjectEnvironmental resource managementSustainable developmentAnalytic hierarchy processEnvironmental economicsEnvironmental planningComputer scienceGeographyEnvironmental scienceOperations researchCivil engineeringEconomicsPolitical scienceMathematicsEngineering

Abstract

fetched live from OpenAlex

Rigorously promoting the intensive use of land of industrial zone is of great significance to relieve the contradiction of land supply and demand, and even to guarantee the comprehensive coordinated and sustainable development of local economy and society. This article takes the Linhai Industrial Zone in Xingcheng, Liaoning province as the research object. Combined with the local reality, this essay selects 6 level two indexes and 14 level three indexes from three aspects including the situation of land utilization, land use efficiency and management performance to make an evaluation system and uses the Delphi method to determine the index weight and the evaluation factor score, and to evaluate the intensive use level of lands in the development zone. The results show that the industrial park land intensive utilization degree is the medium level; the land development and utilization intensity is relatively high; land use structure is not reasonable; the land use efficiency still remains to rise.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.136
GPT teacher head0.319
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2012
Admission routes1
Has abstractyes

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