Fleiss’ Kappa scores for QC inter-rater variability experiments.

<p>Fleiss’ Kappa agreement scores for QC pipelines across four raters suggest high inter-rater variability. Different levels of agreement as presented in Landis and Koch20 are shaded in with labels to the right of the plot. SLANT-TICV, TractSeg CC4, and TractSeg CSTleft are QCed with “almost p...

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المؤلف الرئيسي:	Michael E. Kim (21956727) (author)
مؤلفون آخرون:	Chenyu Gao (9501623) (author), Nancy R. Newlin (21956730) (author), Gaurav Rudravaram (21956733) (author), Aravind R. Krishnan (21956736) (author), Karthik Ramadass (13949238) (author), Praitayini Kanakaraj (9193371) (author), Kurt G. Schilling (9193353) (author), Blake E. Dewey (19066193) (author), David A. Bennett (229710) (author), Sid O’Bryant (6449120) (author), Robert C. Barber (21956739) (author), Derek Archer (21956742) (author), Timothy J. Hohman (8356254) (author), Shunxing Bao (21956745) (author), Zhiyuan Li (205620) (author), Bennett A. Landman (7623857) (author), Nazirah Mohd Khairi (21956748) (author)
منشور في:	2025
الموضوعات:	Biophysics Cell Biology Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified quantitative outlier detection thorough quality control rater variability experiment several processing pipelines proposed method satisfies low time cost robust visual qc scalable quality control div >< p automated qc method following design criteria data processing pipelines quality data scalable manner design criteria comparison experiment time spent time consuming qc pipeline yet necessary slight differences quick visualization preprocessed data erroneous conclusions easily shared also provide algorithm failure 3 .) 2 .) 1 .)
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Fleiss’ Kappa scores for QC inter-rater variability experiments.

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