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Record W1924218178 · doi:10.6000/1927-5129.2015.11.70

Rapid Urban Growth and Change in Urban and Municipal Limits of Bahawalpur City, Pakistan: A Spatio-Periodical Discourse

2015· article· en· W1924218178 on OpenAlexvenueno aff
Muhammad Mohsin, Muhammad Nasar-u-minAllah Bhalli

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
Fundersnot available
KeywordsUrbanizationGeographyPopulationCensusPopulation growthUrban areaAgricultureUrban planningLand useSocioeconomicsEnvironmental protectionEconomic growthEconomyCivil engineeringEnvironmental healthArchaeology

Abstract

fetched live from OpenAlex

Cities all around the world being crowded rapidly with accelerating urban growth and resultant urbanization particularly in developing countries. Currently, Bahawalpur City is also experiencing rapid urban growth and change in its urban and municipal limits. Therefore, the key objectives of this research were to overview the urban population growth with passage of time, expansion in urban area and resultant delimitations in municipal limits of the city. Data about population figures and spatial change have been derived from various sources including census reports, Tehsil Municipal Administration (TMA), Punjab Development statistics etc. Periodical urban growth of the city is divided into four phases characterized with notable events that geared up the urban growth; particularly the last phase has brought more rapid changes. The population of the city is also surging rapidly. Urban area of Bahawalpur City was extended from 4,308.40 acres in 1974 to 7,373.9 acres in 2010, and had caused substantial reduction in agricultural land area and significant addition in residential area. Resultantly, City’s municipal limits also have been altered and reclassified due to this urban stress and extended enormously with considerable fluctuations in agricultural and non-agricultural land area. Presently, City is continuously expanding outward, mostly in the form of housing colonies, roads, shops etc.

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 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)0.001
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 score0.009
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.042
GPT teacher head0.279
Teacher spread0.237 · 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 teacher head, 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

Citations8
Published2015
Admission routes1
Has abstractyes

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