Bibliographic record
Abstract
The US Food and Drug Administration (FDA) has defined a medical device as a health care product that does not achieve it's purpose by chemical action or by being metabolized. This means that a vast number of products are considered medical devices. Such devices play an essential role in the practice of medicine. The FDA classifies medical devices in three classes, depending on the risk of the device. Since Class I and II devices have relatively simple requirements for getting to the market, this review will focus on "implantable devices", which, in general, belong to Class III. The European Union and Canada use a slightly different classification system. While early generations of medical devices were introduced without much testing, either technical or clinical, the process of introducing a Class III medical device from concept to clinical practice has become strongly regulated and requires extensive technological and clinical testing. The modern era of implantable medical devices may be considered to have started in the 1920s with development of artificial hips. The implantable pacemaker was another milestone and pacemakers and cardioverters/defibrillators have since saved millions of lives and created commercial giants in the medical device industry. This review will include some examples of cardiovascular devices. Similar considerations apply to the total implantable device market, although clinical and technological applications obviously vary considerably.
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 | 0.035 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".