{"id":"W3004546137","doi":"10.1002/cjs.11535","title":"A backward procedure for change‐point detection with applications to copy number variation detection","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Simons Foundation","keywords":"Change detection; Computer science; Exploit; Variation (astronomy); Point (geometry); Detection theory; Copy-number variation; Sequence (biology); Algorithm; Data mining; Artificial intelligence; Mathematics; Detector; Telecommunications; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02441444,0.002145501,0.002733533,0.004319907,0.001943621,0.001805532,0.004294108,0.003066906,0.009259497],"category_scores_gemma":[0.06697075,0.001482721,0.003573433,0.004139795,0.002602234,0.002591775,0.00393386,0.006639914,0.003951742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135508,"about_ca_system_score_gemma":0.005021591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005868172,"about_ca_topic_score_gemma":0.006535465,"domain_scores_codex":[0.9877466,0.007356648,0.0006987268,0.001738081,0.002097099,0.0003628022],"domain_scores_gemma":[0.9577467,0.03247494,0.001342856,0.003927005,0.003977356,0.0005310478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008889011,0.0004092897,0.008386294,0.000771112,0.001166153,0.0007906187,0.0006380969,0.08886517,0.02251372,0.1617901,0.0148599,0.6989207],"study_design_scores_gemma":[0.0001856673,0.0002974854,0.002414637,0.00007993956,0.0001862425,0.0006109346,0.00005562625,0.8548925,0.009480246,0.1117039,0.01987508,0.0002177754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009225233,0.0001081815,0.997912,0.0001068845,0.00008391303,0.00007399701,0.00009889399,0.0005278449,0.0001657991],"genre_scores_gemma":[0.02166876,0.000189261,0.9745083,0.00019347,0.0001444385,0.0005423254,0.0004759686,0.0005155168,0.00176199],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02441444,"threshold_uncertainty_score":0.1291175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01630795286666407,"score_gpt":0.2231343164309163,"score_spread":0.2068263635642522,"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."}}