Determination Model of Suitable Coastal Transit-Oriented Development Location, Case Study: Paotere, Makassar
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".