MétaCan
Menu
Back to cohort
Record W2159224190 · doi:10.1061/9780784412435.084

Population Forecast and Control in the Development of International New District: A Case Study on Fengdong New District in Xixian New Area

2012· article· en· W2159224190 on OpenAlexaff
Yuan Lv, Kewei Liu, Xin Dong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsScience North
Fundersnot available
KeywordsPopulationControl (management)Urban districtPopulation controlValue (mathematics)Computer scienceLake districtGeographyOperations researchEnvironmental planningEngineeringArtificial intelligenceSociologyResearch methodologyDemographyFamily planning

Abstract

fetched live from OpenAlex

The construction of Xi-xian New Area has started up. Fengdong New District, the core city of Xi-xian New Area will be built as an international modern city in the following twenty years. Population is the most powerful support to the construction of new district, forecasting the population properly is beneficial to the goal of the new district's construction. In the light of the inadaptability of the traditional methods to the new district, this article tries to form a population forecast and control framework containing analogical, structural, economical, ecological, dynamic and superior control factors. The population forecast result shows that it is close to the goal of superior planning and has the universal significance and the value of popularization.

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 score0.083
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.044
GPT teacher head0.252
Teacher spread0.208 · 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

Explore more

Same topicRemote Sensing and Land UseFrench-language works237,207