Location of a new banking agency in Sfax: a multi-criteria approach
Bibliographic record
Abstract
Sfax is an important economic pole in Tunisia, distinguished in all economic sectors of activity by its increasing rate of employment. Besides, many new projects are implemented in Sfax as well as in its suburbs. These factors contribute to increase the necessity of resorting to banks either to deposit the collected funds or to obtain credits. Since banks play an important and indispensable role for the promotion of the national economy, Tunisian banks follow propagation policies in order to ensure coverage of Tunisian territory through the installation of news banking agencies. To maximise its profitability, the 'Tunisian Development Bank' carry out a survey in order to choose the best sites to set up its new agencies. In this framework, we will develop in this paper a preference disaggregation approach based on PROMETHEE method. The proposed approach deduces, in an objective way, PROMETHEE's parameters from binary preference relations provided by the decision maker and then allows ranking the different sites for the setting up of the new banking agency.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".