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Record W2739797061 · doi:10.5539/jsd.v10n4p31

Determination Model of Suitable Coastal Transit-Oriented Development Location, Case Study: Paotere, Makassar

2017· article· en· W2739797061 on OpenAlexvenueno aff
Andi Bachtiar Arief, Ananto Yudono, Arifuddin Akil, Muhammad Isran Ramli, Amran Rahim

Bibliographic record

VenueJournal of Sustainable Development · 2017
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsnot available
Fundersnot available
KeywordsUnavailabilityPort (circuit theory)Transit (satellite)Transport engineeringShoreGeographic information systemRedundancy (engineering)Computer scienceGeographyCartographyPublic transportEngineeringStatisticsMathematicsGeology

Abstract

fetched live from OpenAlex

Commuter and local society, the users of Paotere local port who took round trip to small islands and other island as well, experienced redundancy of cost, time and travel distance in fulfilling their whole needs at the shore of Makassar. Traveling by using motorized vehicle at the shore of Makassar was taken due to the unavailability of needed goods in the port and its neighborhood within radius 500 meters. This research is aimed at establishing determination model of suitable location for spatial planning of coastal Transit-Oriented Development (TOD) in order to eliminate redundancy of cost, time and travel distance. It applied expert system and spatial analysis method based on geographic information system (GIS). The result showed that the most suitable location for coastal TOD development was in local Port and its neighborhood, it was at some grids, 581-585 and 540-542 within walking radius. Used determination model was determination in which, relied on highest value of the location with supports from its neighborhood location as well and the correlation among; certainty factor, commuter’s activity and local society.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.769

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 head0.021
GPT teacher head0.246
Teacher spread0.225 · 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 designSimulation or modeling
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
Published2017
Admission routes1
Has abstractyes

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