Bibliographic record
Abstract
The concept of telemedicine is neither new nor novel. It has been a part of healthcare for more than a century, if not longer. The integration of telecommunications into the practice of medicine implies that no one should be without access to healthcare. Communications, as we understand it today, are based on telephony or the internet—both wired and wireless. Yet there were various communication modalities dating into antiquity that were used for medicine. In the modern era, telemedicine has been applied in a plethora of settings, including human spaceflight, military applications, disasters, humanitarian crisis, home health care, and, of course, the rapid increase in utilization during the COVID-19 pandemic. Since the beginning of the twentieth century, healthcare has evolved, and with continuous improvements in telecommunications and computer technology, telemedicine has become a necessary tool in the practice of medicine worldwide; whereby literally every clinical discipline has been impacted. As the first quarter of the twenty-first century comes to a close, the world’s population has access to more information and healthcare resources than in all of human history. This chapter provides an overview of the advancement of telemedicine across time and its impact on current practice.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".