Response to “Level 2 Observational Studies: A Practical Alternative to Randomized Trials in Plastic Surgery”: Table 1.
Bibliographic record
Abstract
One day when I was a junior medical student, a very important Boston surgeon visited the school and delivered a great treatise on a large number of patients who had undergone successful operation for vascular reconstruction. At the end of the lecture, a young student at the back of the room timidly asked, “Do you have any controls?” Well, the great surgeon drew himself up to his full height, hit the desk, and said, “Do you mean did I not operate on half of the patients?” The hall grew very quiet then. The voice at the back of the room very hesitantly replied, “Yes, that's what I had in mind.” Then the visitor's fist really came down as he thundered, “Of course not. That would have doomed half of them to their death.” God, it was quiet then, and one could scarcely hear the small voice ask, “Which half?”—Erle E. Peacock, Jr.1 Although evidence-based medicine (EBM) principles have been developed over decades, only recently has a systematic, organized commitment to incorporate EBM principles into the specialty of plastic surgery been undertaken.2,3 As such, we are all learning as a group how EBM principles can help us and our patients make better care decisions. In his commentary, Dr Swanson casts doubt on the value of the randomized controlled trial design in surgery;4 however, the collective wisdom of hundreds of scientists, statisticians, epidemiologists, and researchers from around the world have established the randomized controlled trial in the last half century …
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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 | 0.826 | 0.906 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.034 | 0.009 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".