Reply to: ‘Evidence recommending antiviral therapy in hepatitis C’
Bibliographic record
Abstract
would predict a good long-term outcome.If it is indeed true that the vast majority (perhaps even all) of individuals achieving SVRs were destined not to develop long-term complications of liver disease, it would follow that SVRs would be associated with non-progressive disease but that antiviral therapy may not provide overall benefit to the treated group.To validate the SVR as a surrogate outcome, RCTs in the future should compare patients treated with regimens that result in larger percentages of SVRs (e.g., 90%) to untreated patients and employ clinical events as the primary outcome.If patients in previous RCTs did not subsequently receive additional treatment, we would encourage the authors of those trials to assess the longterm clinical outcomes retrospectively.As of this time, treatment advocates are supporting treatment that has no level 1 (well designed and executed RCTs) evidence for improved clinical outcomes, but is costly and toxic (including occasional mortal).
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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 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.086 | 0.050 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".