Aplicació web per a realitzar comandes en restaurants
Bibliographic record
Abstract
L'objectiu d'aquest TFG és desenvolupar una aplicació web que permeti als usuaris poder fer comandes en línia estant físicament en un restaurant. L'usuari de l'aplicació podrà escanejar un codi QR que li permetrà accedir a la carta del restaurant. Un cop allà, trobarà els plats organitzats per categories i podrà afegir els plats a la cistella i així fer la comanda. Un cop feta la comanda, el restaurant rep en temps real aquesta comanda. L'usuari també podrà saber en temps real (en el navegador) l'estat de la seva comanda. Per altre costat, tenim el panel d'administració del restaurant on l'administrador del restaurant podrà afegir, editar o eliminar els plats, les categories, veure les comandes rebudes i també canviar l'estat de les comandes. El canvi de l'estat de la comanda permet enviar una notificació a l'usuari en temps real. També podrà veure estadístiques del restaurant com el nombre de comandes que té i els beneficis.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.018 |
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".