Bibliographic record
Abstract
Note: Page numbers in italic refer to figures and/or tables ablation 21, 23 cold 25 continuous wave 23-4 plasma-induced 21, 26-7, 37 pulsed laser 24-5, 37 ablative recoil 26 absorption coefficient 17, 18, 19 acute myocardial ischemia canine models 66-7 ovine models 67-8 porcine models 68 rat models 65-6 ameroid constrictor 69-70, 71-2 anatomic myocardial perfusion index (AMP) 83-4 anatomy, historical studies 1, 49 anesthesia cardioprotective effects 41-2 for TMR in conjunction with CABG 113 for TMR as sole therapy 89, 113 angina early trials of TMR 9-13 as indication for TMR 81-2 refractory 68, 84, 89 clinical trials of TMR as sole therapy 91-9 unstable 83, 84, 89 clinical trials of TMR as sole therapy 99-100 angiogenesis 34-6, 49, 81, 140 in end-stage coronary artery disease 75 exercise-induced 130 factors involved 138-9 histologic evidence 58-62, 140-1 inflammation-mediated 57 ischemia-related 11 need for future studies 144 tissue perfusion evidence 141-4 angiopoietins 140 angiotensin II 164 animal models 16, 65, 73, 75-6 acute myocardial ischemia 65-8
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.913 | 0.899 |
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".