Is ST-segment elevation myocardial infarction always a simple diagnosis?
Bibliographic record
Abstract
AMA Zalas K, Kuliczkowski W, Pachana J, Mycka R, Rakoczy B. Is ST-segment elevation myocardial infarction always a simple diagnosis?. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej. 2023;19(3):298-300. doi:10.5114/aic.2023.131488. APA Zalas, K., Kuliczkowski, W., Pachana, J., Mycka, R., & Rakoczy, B. (2023). Is ST-segment elevation myocardial infarction always a simple diagnosis?. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, 19(3), 298-300. https://doi.org/10.5114/aic.2023.131488 Chicago Zalas, Krzysztof, Wiktor Kuliczkowski, Jacek Pachana, Roman Mycka, and Bartosz Rakoczy. 2023. "Is ST-segment elevation myocardial infarction always a simple diagnosis?". Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej 19 (3): 298-300. doi:10.5114/aic.2023.131488. Harvard Zalas, K., Kuliczkowski, W., Pachana, J., Mycka, R., and Rakoczy, B. (2023). Is ST-segment elevation myocardial infarction always a simple diagnosis?. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, 19(3), pp.298-300. https://doi.org/10.5114/aic.2023.131488 MLA Zalas, Krzysztof et al. "Is ST-segment elevation myocardial infarction always a simple diagnosis?." Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, vol. 19, no. 3, 2023, pp. 298-300. doi:10.5114/aic.2023.131488. Vancouver Zalas K, Kuliczkowski W, Pachana J, Mycka R, Rakoczy B. Is ST-segment elevation myocardial infarction always a simple diagnosis?. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej. 2023;19(3):298-300. doi:10.5114/aic.2023.131488.
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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 | 0.003 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".