The comparison of the procedure of the classification system of selected counties with Iran
Bibliographic record
Abstract
Introduction: today, health care with desired quality, without one complete and effective procedure of the classification system it is impossible. In this system, the results of the care treatment will be registered in the patient's file with the standard codes. These codes are the basis of analysis the information for health care personnel, the investigators, policy - makers and the health - planners. Actually there is no one unique procedure of the classification system which can be used in the world, and is necessary that every country regarding to its goals, laws national. Interests and standards, considers to establish such a system. The main goal of this research is studying and comparing the national procedure of the classification - system in America, Australia , England, Canada, and northern, Europe countries (Denmark) Finland, Norway, Swede, Iceland) mean- while they have the best classification system in the whole world, they are compiled in English too. This research is dealing with a survey on the procedure of the classification system of our country too. Methodology: collecting information was made with library study, Internet and e.mail Results: for the present time the ICD-IO-PCS system in America, ACHI-I in Australia, and NCSP in the northern euro countries are used and ICPM and ICD-G-CM systems are used in our Country for the procedure of the classification. In this research, while mentioning to the short history and the process of the promotion of these systems, the advantages and the constraints were alluded. Conclusion: Regarding to the constraints of the effectiveness of actual classification system of procedures in our country, the necessity of drafting one classification system of national procedure is perceived. This system can record the information with all details. The abilities of recording the information in this system must be planned in such a way that while regarding to the goals, laws, national interests and standards could correspond with the development of diagnostic and therapeutic technologies and presentation of the health - care in the meantime.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".