Personalised Dormitory Roommate Matching System Based on Multiple Swarm Genetic Algorithms
Why this work is in the frame
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Bibliographic record
Abstract
In order to allocate suitable dorm rooms for students more effectively and improve the matching degree of interests, living habits and future plans between roommates, this paper designs a personalised dorm room roommate matching system based on multiple swarm genetic algorithms. The system uses Vue framework to build the front-end, which is responsible for user interaction and information collection; the back-end uses Golang language to process the data and call the dormitory allocation procedure; the database uses SQLite to store the data; and the dormitory allocation procedure is based on multiple cluster genetic algorithms written in Python. Student information is collected through a front-end questionnaire, and the user can manually set the weight of each preference. The system will automatically iterate the optimal roommate assignment programme and return the results to the front-end.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it