APLICAÇÃO DO FITRADEOFF PARA PROBLEMÁTICA DE ORDENAÇÃO DE PROTOCOLOS DE TRIAGEM: ESTUDO DE CASO NAS UNIDADES DE PRONTO ATENDIMENTO DE NATAL/RN
Bibliographic record
Abstract
The present study aims to develop a multicriteria model to support the decision to choose the screening protocol best suited to the organizational context of the Emergency Care Units (UPAs) of Natal, Rio Grande do Norte (RN).For that, the FITradeoff method was used for the sorting problem due to both the adequacy of this method to the analyzed decision problem and the potential characteristics associated with the application of FITradeoff, such as: flexibility and high interaction with the decision maker during the preference modeling process.Finally, it was possible to identify that according to the organizational structure of the UPAS Natal / RN, there is a preference structure between the protocols, ordering them by Australian Triage Scale, Canadian Triage Acuity Scale, Spanish Triaje System, Manchester Triage System and Emergency Severity Index.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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; both teacher heads agree on what is shown here.
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".