Jean-Philippe Monfet, ing. CEM, Rcx. Ingénieur en environnement et santé sécurité au travail (SST)
Bibliographic record
Abstract
La littérature émergente sur l’industrie 4.0 et les mégadonnées (big data) suggère que les technologies de l’information (TI) et la durabilité environnementale doivent aller de pair (Jabbour et collab., 2017; de Sousa Jabbour et collab., 2018). Dans le cadre de ce numéro spécial sur les reconfigurations des échanges marchands, il semblait pertinent d’interroger Jean-Philippe Monfet, ingénieur en environnement et en énergie, qui travaille présentement à la création d’une application mobile proposant des services de covoiturage entre particuliers. Son projet a récemment pris un tout autre virage avec la progression de la pandémie de la COVID-19. Le voici dans un entretien qu’il a bien voulu accorder à la revue O&T.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.166 | 0.081 |
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".