Les impacts de la technologie RFID et du réseau EPC sur la gestion de la chaîne d'approvisionnement : le cas de l'industrie du commerce de détail
Bibliographic record
Abstract
DÉDICACEÀ ma famille et ma belle-famille La réalisation de cette thèse doctorale n'aurait pas été possible sans l'apport de plusieurs personnes que j'aimerais remercier.En premier lieu, je remercie vivement les professeurs Louis-André Lefebvre et Élisabeth Lefebvre qui ont agi respectivement comme directeur et codirectrice de recherche.Leur encadrement exemplaire, leur implication continue et leur soutien inconditionnel furent pour moi une source d'inspiration quant à la bonne conduite de ce projet et ma décision de poursuivre ma carrière en enseignement et en recherche.Je tiens aussi à exprimer mes plus sincères remerciements aux professeurs Mario Bourgault, Pierre Hadaya, Peter Kropf et Samuel Pierre, qui ont accepté de siéger sur le jury de ma thèse.Je tiens également à remercier mes amis et collègues du Centre ePoly, spécialement M. Ygal Bendavid pour sa précieuse collaboration, MM.Harold Boeck, Jaouad Daoudi et Carl St-
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".