VALIDAÇÃO DE MÉTODOS ANALÍTICOS: ESTRATÉGIA E DISCUSSÃO
Bibliographic record
Abstract
Neste trabalho são apresentadas as definições dos parâmetros (seletividade, limites de detecção e quantificação, exatidão, precisão, linearidade, gráfico analítico, sensibilidade e robustez) considerados nos processos de validação de métodos analíticos. A estratégia a ser adotada para a determinação desses parâmetros depende do propósito e da natureza do método. Exemplos são apresentados para a avaliação dos parâmetros no procedimento de validação. ANALYTICAL METHODS VALIDATION: STRATEGY AND DISCUSSION Abstract This paper presents the definitions of the parameters (selectivity, limits of detection and quantification, accuracy, precision, linearity, analytical graphic, sensitivity and ruggedness) considered on analytical methods validation procedures. The strategy to be adopted for determinations of these parameters depends on the purpose and the nature of the method. Some examples are presented for parameters evaluation in a validation procedure.
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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 | 0.136 | 0.166 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".