Blog fog? Using rapid response to advance science and promote debate
Bibliographic record
Abstract
As editors of Tobacco Control we are always pleased to see readers thinking critically about what they read in this journal and using the ‘Rapid Response’ forum to engage in constructive academic debate. However, the growing use of personal blogs to criticise published articles has led us to reflect on appropriate ways of engaging in such debate and how we as editors should respond to comments made outside the ‘Rapid Response’ forum. This editorial summarises these reflections and clarifies our policy on postpublication discussion of research articles. Tobacco Control provides a valuable forum for analysis, commentary and debate in the field of tobacco control. This includes public presentation of research undertaken and reviewed by scientists and practitioners in the field, so that it may inform and progress scientific inquiry, health policy and debate. While the editors make decisions about what is and is not published in this forum, these decisions are made with expert advice and balancing many factors-–—including research quality, contributions to the field, innovation, international impact and policy relevance. Despite careful review and selection procedures, no journal …
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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 | 0.019 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".