Bibliographic record
Abstract
Objectives：Since the order for medical treatment as outpatient has begun in Korea, there have been no requests due to the absence of specific details relating to its enforcement and lack of understanding of related specialists. We reviewed current guidelines and administrative conditions for order for medical treatment as outpatient in Korea, and examined examples of operation and related regulations of developed countries. Methods：Korean studies concerning development of the order for medical treatment as outpatient were inquired. We investigated the guidelines of other countries including U.S.A., Australia, United Kingdom and Canada. The survey of related specialists for the improvement of order for medical treatment as outpatient was performed. Results：Related specialists agreed that current order for medical treatment as outpatient needed more detailed guidelines for candidate patients, processes and management for noncompliance. Additionally, majority of the specialists suggested that candidates for order for medical treatment as outpatient should be extended for not only hospitalized patients but also patients in community. Conclusions：We reviewed detailed considerations regarding candidate recipients within current legislation, complemented post-enforcement report, management procedures, and stipulated actions for noncompliance, to be used as practical guidelines for application. More fundamental measures than complementation of guidelines, such as modification of related legislature will be needed to increase usage, and further details with reference to confidentiality of recipients and safety measures and financial support of treatment personnel will be needed.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".