{"id":"W2737529060","doi":"10.1136/jclinpath-2017-204520","title":"Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing","year":2017,"lang":"en","type":"article","venue":"Journal of Clinical Pathology","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University of Toronto; Princess Margaret Cancer Centre; University Health Network","funders":"Princess Margaret Cancer Foundation; Genome Canada","keywords":"Linear regression; Simple linear regression; Simple (philosophy); Computer science; Computational biology; Data mining; Statistics; Medicine; Biology; Mathematics; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2649491,0.004725188,0.003916049,0.007265071,0.002350353,0.00721187,0.004493898,0.004300962,0.002061856],"category_scores_gemma":[0.3275656,0.002799119,0.004520129,0.006615666,0.004565711,0.004236171,0.004168279,0.009991189,0.00168688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00457697,"about_ca_system_score_gemma":0.007270899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005559299,"about_ca_topic_score_gemma":0.007019552,"domain_scores_codex":[0.7244467,0.188588,0.01706178,0.02221345,0.04639312,0.001296993],"domain_scores_gemma":[0.5630354,0.3046919,0.03953892,0.03527343,0.05651478,0.0009456645],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003268198,0.0008623092,0.0553333,0.01124753,0.01004604,0.000708409,0.005150687,0.09127207,0.07069667,0.04573361,0.03453623,0.671145],"study_design_scores_gemma":[0.0005422157,0.003534494,0.06459183,0.003953114,0.003867786,0.002889126,0.001192885,0.5355266,0.1784778,0.08032229,0.1229163,0.002185605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005942638,0.004623082,0.9829374,0.0005955309,0.0005922643,0.000652955,0.0005418641,0.00307621,0.001038178],"genre_scores_gemma":[0.06661962,0.001790472,0.924897,0.000992586,0.0002208836,0.002302879,0.0007232617,0.001663922,0.0007892821],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7350509,"threshold_uncertainty_score":0.9064487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8698920011840419,"score_gpt":0.7294773631251671,"score_spread":0.1404146380588748,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}