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Record W4295993398 · doi:10.1016/j.eururo.2022.08.036

Erratum to “Effect of Simulation-based Training on Surgical Proficiency and Patient Outcomes: A Randomised Controlled Clinical and Educational Trial” [Eur Urol 2022;81:385–393]

2022· erratum· en· W4295993398 on OpenAlexaff
Abdüllatif Aydın, Kamran Ahmed, Takashige Abe, Nicholas Raison, Mieke Van Hemelrijck, Hans Garmo, Hashim U. Ahmed, Furhan Mukhtar, Ahmed Al‐Jabir, Oliver Brunckhorst, Nobuo Shinohara, Wei Zhu, Guohua Zeng, John P. Sfakianos, Mantu Gupta, Ashutosh Tewari, Ali Serdar Gözen, Jens Rassweiler, Andreas Skolarikos, Thomas Kunit, Thomas Knoll, Felix Moltzahn, George N. Thalmann, Andrea G. Lantz Powers, Ben H. Chew, Kemal Sarıca, Muhammad Shamim Khan, Prokar Dasgupta, Umair Baig, H. Aya, Mohammed Husnain Iqbal, Francesca Kum, Matthew Bultitude, Jonathan D. Glass, Azhar Abbas Khan, Jonathan Makanjuola, John E. McCabe, Azi Samsuddin, Craig McIlhenny, James Brewin, Shashank Kulkarni, Sikandar Khwaja, Md Waliul Islam, Howard Marsh, Taher Bhat, Benjamin J. Thomas, Mark L. Cutress, Fadi Housami, Timothy Nedas, T. S. Bates, Rono Mukherjee, Stuart L. Graham, M Bordenave, Charles Coker, Shwan Ahmed, Andrew Symes, Robert C. Calvert, C.O. Lynch, Ronán Long, Jacob M. Patterson, Nicholas J. Rukin, Shahid Ali Khan, Ranan Dasgupta, Stephen L. Brown, Ben Grey, Waseem Mahmalji, Wayne Lam, W Scheitlin, Norbert Saelzler, Marcel Fiedler, Shuhei Ishikawa, Yoshihiro Sasaki, Ataru Sazawa, Yuichiro Shinno, Tango Mochizuki, Jan Peter Jessen, Roland Steiner, Gunnar Wendt‐Nordahl, Nabil Atassi, Heiko Kohns, Ashley Cox, Ricardo Rendon, Joseph Lawen, Greg Bailly, T. Donald Marsh

Bibliographic record

VenueEuropean Urology · 2022
Typeerratum
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of British ColumbiaDalhousie University
Fundersnot available
KeywordsMedicinePhysical therapySimulation trainingMedical physicsRandomized controlled trialGeneral surgerySurgerySimulation

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.071
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0480.009

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.

Opus teacher head0.048
GPT teacher head0.391
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractno

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