{"id":"W4366822592","doi":"10.1007/s11548-023-02908-z","title":"FAST skill assessment from kinematics data using convolutional neural networks","year":2023,"lang":"en","type":"article","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Ultrasound in Clinical Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Carleton University","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Kinematics; Artificial neural network; Deep learning; Machine learning; Sensitivity (control systems); Domain knowledge; Domain (mathematical analysis); Pattern recognition (psychology)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007683021,0.0001143217,0.000447487,0.0002276835,0.00006307936,0.00003790284,0.0003190825,0.0001289262,0.00007537133],"category_scores_gemma":[0.0002287364,0.00009369208,0.000139372,0.0001515858,0.0001800363,0.0001538782,0.00017273,0.0004053146,0.000003508265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006038862,"about_ca_system_score_gemma":0.0001685309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008150229,"about_ca_topic_score_gemma":0.000001084567,"domain_scores_codex":[0.9983475,0.0001369087,0.0008390799,0.0002037804,0.0003207598,0.0001519693],"domain_scores_gemma":[0.9944499,0.004359543,0.0004425957,0.0002329534,0.0003874637,0.0001275346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003741069,0.0005489696,0.8786467,0.00002153612,0.003148002,0.00079042,0.00009417465,0.02310645,0.0007347758,0.0007090179,0.05184178,0.03998405],"study_design_scores_gemma":[0.0004362634,0.00003067509,0.5140404,0.00006940521,0.0000800352,0.001900195,0.00001353789,0.4821804,0.000001285118,0.0003629685,0.0008251058,0.00005980517],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7206916,0.0001836578,0.2724064,0.003930163,0.00260006,0.00006036718,0.00007446083,0.00002612546,0.00002714496],"genre_scores_gemma":[0.9597145,0.0002665593,0.03507694,0.001378454,0.002704059,0.000001567608,0.0008295279,0.00001221334,0.00001613078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4590739,"threshold_uncertainty_score":0.3820652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1075940199263055,"score_gpt":0.3951398952028256,"score_spread":0.2875458752765201,"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."}}