Cardiac rehabilitation
Bibliographic record
Abstract
GLOSSARY 2 -- 1 APPENDICES SYSTEMATIC LITERATURE REVIEW 3 -- Appendix 1: systematic review Search strategy 3 -- Appendix 2: RCT Search strategy 10 -- Appendix 3: INAHTA member websites searched 17 -- 2 APPENDICES: ANALYSIS OF IMA DATABASE 79 -- Appendix 1: Nomenclature codes used for patient classification 79 -- Appendix 2: Description of patient inclusion and exclusion 85 -- appendix 3: Rehabilitation sequences 86 -- Appendix 4 rehabilitation related data during the entire one-year observation period 87 -- Appendix 5: cost related to rehabilitation 91 -- Appendix 6 socio-demographic patient characteristics 98 -- Appendix 7 Geographical spread of patients in outpatient rehabilitation 99 -- Appendix 8 Cardiac disease related medical care consumption 103 -- Appendix 9: Multivariate analysis 107 -- 3 APPENDIX : SURVEY 109 -- Patient Survey questionnaires 109 -- List of participating hospitals/centres 117 -- Participating cardiologists 117 -- Details on patients’ characteristics 118 -- Details on the participation to the rehabilitation programme 121
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 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.470 | 0.127 |
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".