Acquisition d’information dans un modèle intertemporel en temps continu
Bibliographic record
Abstract
Cet article examine la demande d’information et la valeur de l’information dans un modèle intertemporel en temps continu. Le modèle étudié est un modèle à information incomplète où la technologie d’information est contrôlée par l’investisseur moyennant un coût. Le mécanisme bayésien continu de révision des croyances produit, pour cette structure, une distribution postérieure gaussienne à tout point du temps. Le contrôle de la technologie d’information est équivalent au contrôle de l’estimateur de la position de la variable d’état (espérance conditionnelle) ainsi que de la précision de cet estimateur (variance conditionnelle). La demande d’information, dans notre modèle, se compose de deux termes, qui résultent du conflit entre deux objets d’apprentissage. Sous l’hypothèse d’une offre de précision stochastique et inélastique, le prix d’équilibre de l’information est dérivé et sa structure analysée.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".