Probabilistic Scenarios for Private Health Care Entities: Analysis of Medical and Administrative Management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The strategic prospective is a convergence of diverse disciplinary fields, that applied to private health entities at a national level allows to consider the probable future of these companies; This method is based on the use of three softwares: the first called Micmac aims to prioritize the 6 main influential and dependent variables, by using a table of two inputs called structural analysis matrix, the second program called Mactor values relationships of force among the 30 identified actors, studying the convergences and divergences with respect to the associated objectives. In addition, the games of actors are constructed to formulate hypotheses of the system under study. Once established, the Delphi methodology is used. Finally, in the Smic Prob-Expert methodology, the simple and conditioned probabilities of events are determined, represented in 64 possible scenarios and identifying the normative trends, allowing to discern the probabilities of the entities of the sector.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it