Protocolo de testes de aceitação em equipamentos de imagem por ressonância magnética
Bibliographic record
Abstract
OBJETIVO: Este trabalho tem como objetivo criar um protocolo de testes de aceitação para equipamentos de imagem por ressonância magnética e demonstrar como e quais tipos de dispositivos de teste podem ser usados para a coleta de dados. MATERIAIS E MÉTODOS: Para cada um dos 15 testes selecionados foram elaborados a definição, o procedimento, a forma de análise e o critério de aceitação. RESULTADOS: Através dos testes de aceitação descritos é possível verificar características técnicas que constam nas propostas de venda dos fabricantes, assim como estabelecer valores de referências para serem utilizados em posteriores testes de constância. CONCLUSÃO: Futuros programas de garantia da qualidade em imagem por ressonância magnética devem considerar testes semelhantes ou iguais aos descritos neste trabalho.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".