GIS Application and Architectural Design for the Assessment of Urban Infrastructural Renovation: Case of the Nsam Market in the Yaounde III Municipality, Cameroon
Bibliographic record
Abstract
Markets, whose creation needs heavy investment, are seen as centres for economic and financial transactions. To this effect, they play an important role in the survival of city dwellers as well as the embellishment of the city. In 2006, Nsam market was created in the Nsam quarter Yaounde with little financial concentration. Over the years, this market has outlived its usefulness to the extent that its present functioning is an eyesore. Amongst the causes to this are the facts that, the market was created following no predefined standards, the city has grown and the market can no longer handle the dependent population. From field observations, this study aimed at proposing a complete renovated plan for the Nsam market in Yaounde, Cameroon. The study relied on secondary and primary sources of data collected and treated following some pre-set standards. These data enabled an analysis of the diagnosis of the situation prevailing there where it led to the conclusion of a complete renovation of the market. This renovated market is expected to better the working conditions of traders, create more jobs which will boost revenue collection and embellishment of the city amongst others.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".