Renal denervation – a novel method for the treatment of resistant hypertension
Bibliographic record
Abstract
ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Kądziela J, Florczak E, Januszewicz A, Witkowski A. Renal denervation – a novel method for the treatment of resistant hypertension. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej. 2010;6(4):173-176. doi:10.5114/pwki.2010.17631. APA Kądziela, J., Florczak, E., Januszewicz, A., & Witkowski, A. (2010). Renal denervation – a novel method for the treatment of resistant hypertension. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, 6(4), 173-176. https://doi.org/10.5114/pwki.2010.17631 Chicago Kądziela, Jacek, Elżbieta Florczak, Andrzej Januszewicz, and Adam Witkowski. 2010. "Renal denervation – a novel method for the treatment of resistant hypertension". Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej 6 (4): 173-176. doi:10.5114/pwki.2010.17631. Harvard Kądziela, J., Florczak, E., Januszewicz, A., and Witkowski, A. (2010). Renal denervation – a novel method for the treatment of resistant hypertension. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, 6(4), pp.173-176. https://doi.org/10.5114/pwki.2010.17631 MLA Kądziela, Jacek et al. "Renal denervation – a novel method for the treatment of resistant hypertension." Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej, vol. 6, no. 4, 2010, pp. 173-176. doi:10.5114/pwki.2010.17631. Vancouver Kądziela J, Florczak E, Januszewicz A, Witkowski A. Renal denervation – a novel method for the treatment of resistant hypertension. Advances in Interventional Cardiology/Postępy w Kardiologii Interwencyjnej. 2010;6(4):173-176. doi:10.5114/pwki.2010.17631.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".