GerdQ: uno strumento per la diagnosi e la gestione della malattia da reflusso gastroesofageo nella medicina generale
Bibliographic record
Abstract
La diagnosi e la gestione della malattia da reflusso gastroesofageo (MRGE) richiedono un nuovo approccio, soprattutto dopo la Consensus Conference di Montreal del 2006. La definizione di malattia è ora centrata sul paziente, sull’analisi dei suoi sintomi che possono alterare la qualità della vita. GerdQ, questionario “paziente centrato”, basato su recenti evidenze scientifiche, autosomministrato, è di aiuto per il medico di Medicina Generale, anche per la sua semplicità e facilità di utilizzo, senza necessità di altri test diagnostici, quali endoscopia del tratto digestivo superiore e/o procedure diagnostiche specialistiche (ad esempio, pH impedenzometria esofagea 24 ore). GerdQ offre tre applicazioni nella pratica clinica: 1) nella malattia da reflusso gastroesofageo, accuratezza diagnostica per lo specialista e per il medico di Medicina Generale; 2) nella valutazione dell’impatto della malattia sulla qualità di vita, contribuendo a definire la scelta terapeutica; 3) nella valutazione dell’efficacia a lungo termine del trattamento terapeutico.
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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 | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".