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Record W2974560933

진단용 방사선 발생장치의 수시 정도관리 항목 및 기준에 관한 기초 연구

2014· article· ko· W2974560933 on OpenAlexaboutno aff
허예지, 김교태, 노시철, 남상희, 박지군

Bibliographic record

Venuenot available
Typearticle
Languageko
FieldEngineering
TopicMarine and Coastal Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineQuality assuranceQuality (philosophy)Control (management)CommissionMedical physicsOperations managementRisk analysis (engineering)Medical emergencyBusinessComputer sciencePathologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

Diagnostic radiation equipment diagnosis and treatment of disease of recent plays a central role, but this is based on the assumption of an appropriate balance of benefits and risks of diagnostic. If balance is not maintained has the potential to give an adverse effect on the health of the public. In the case of an overseas, the importance of (QA) quality assurance of medical equipment is growing, but evaluation criteria of quality assurance has not been clearly presented in domestic. Therefore, the modernization of medical equipment from the point at which the degree of cycle-by-cycle management system of foreign national to be suitable for diagnostic radiation generator entry and quality control standards by introducing a tailoring is necessary. In this study the most frequently used diagnostic radiation generator X-ray imaging apparatus of the general three-year periodic inspections at any time between the periodic inspection items and quality control methods and standards for the establishment of the United States, Canada and abroad, and international electronic literature search Technical Committee (International Electro-technical Commission, IEC) were compared with the provisions of item. Based on the national quality control items when opening frequent inspection items and standards presented as a basis for setting up study.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.844
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.006

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.

Opus teacher head0.011
GPT teacher head0.244
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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