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Record W2347483310

Management strategies of land-use space change——Take Kuancheng District,Changchun City,Jilin Province for instance

2015· article· en· W2347483310 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

VenueJournal of Northeast Normal University · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsScience North
Fundersnot available
KeywordsHomogeneity (statistics)HomogeneousLand useSpace (punctuation)Land managementGeographyEnvironmental resource managementEnvironmental planningLand use, land-use change and forestryGridBusinessComputer scienceCivil engineeringEnvironmental scienceMathematics
DOInot available

Abstract

fetched live from OpenAlex

The article takes Kuancheng District,Changchun City,Jilin Province for example,talking about the natural conditions and current land-use space change of Kuancheng District,putting homogeneity changes as the research methods of land-use space change,using GIS technology to make gridded map of land-use space change and establish the homogeneous geographical grid network.Explore the relationship between changes in land homogeneous degree and in land use types,and concluded that in the transition of economic development,the change of homogeneity of Changchun rendered high speed after low speed and the range from next to the city to far away from the city.Propose management strategies of land-use space change pointed at the current problems of Kuancheng District.Put forward management countermeasures following:establishing intensive land development pattern,creating the density of city space,coordinating various functional organically and retaining the city's open space management.It has important guiding significance for rational land use in Kuancheng District.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.059
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.045
GPT teacher head0.209
Teacher spread0.164 · 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