Reflections on the TEAM Trial: Why Clinical Care and Research Should be Reconciled
Bibliographic record
Abstract
The current clinical and research environment is one that renders any true enquiry into the value of commonly performed surgical acts practically impossible. Drawing from the recent failure of Trial on Endovascular Aneurysm Management (TEAM), a trial on the endovascular management of unruptured intracranial aneurysms, I attempt to identify some principles that sustain the current ways of doing clinical research that have paradoxically become major obstacles to trials that aim to assess the potential benefit or harm due to interventions as currently practiced. Clinical research and practice must coalesce into "clinical care trials" if we are to provide patients with optimal, prudent care in the context of uncertainty. This may require a major change in the mentalities of clinicians, scientists, and patients alike, and the adoption of novel strategies for public agencies to support the integration of clinical research and care.
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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 | 0.485 | 0.666 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.070 |
| Scholarly communication | 0.025 | 0.056 |
| Open science | 0.014 | 0.013 |
| Research integrity | 0.082 | 0.135 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".