Le choix de traitement en triade incluant un patient âgé apte en soins palliatifs : à la recherche d’un modèle théorique
Bibliographic record
Abstract
The elderly in palliative care are confronted with difficult decisions relating to treatments. The philosophy of palliative care, namely, including the patient and his/her family right away, leads the doctor to consult with the two parties involved when choosing a treatment. As no theoretical model allows us to understand how the decision-making process hinges on the trio (a capable elderly person, a family caregiver, and the doctor) in a context of palliative care, we propose one which was developed from three strategies of document analysis: theoretical synthesis, theoretical analysis, and theoretical derivation. According to our model, the decision-making process depends on individual factors influencing the decision of the participant, expectations and attitudes as to the role, the level of confidence amongst the parties involved, the manner in which they communicate with each other, their mutual understanding of the clinical and ethical issues, and, finally, their ability to cooperate.
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".