Évaluation de projets : la valeur actualiséenette optimisée (VAN-O)
Bibliographic record
Abstract
Nous clarifions les fondements de l’évaluation de projet en présence de multiples sources de risque et nous concluons que la méthode VAN telle qu’appliquée dans la plupart des entreprises et organisations viole certains principes fondamentaux de la création de valeur tels l’additivité et l’absence d’arbitrage. L’évaluation d’un projet doit se faire en (i) décomposant les flux monétaires en composantes correspondant aux diverses sources de risque et (ii) actualisant chaque composante à l’aide d’un taux spécifique à cette composante. La valeur du projet est obtenue en sommant les valeurs présentes des diverses composantes. Alternativement, les différentes composantes peuvent être corrigées pour leur risque respectif afin d’obtenir leurs équivalents certains. La valeur du projet est alors obtenue en prenant la somme des équivalents certains actualisée au taux sans risque, identique, unique et observable .
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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".