{"id":"W3181781118","doi":"10.1109/memea52024.2021.9478710","title":"A Deep Learning Force Estimator System for Intracardiac Catheters","year":2021,"lang":"en","type":"article","venue":"","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Artificial intelligence; Deep learning; Mean squared error; Estimator; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0004113465,0.0006467187,0.0005095838,0.0004551866,0.000291996,0.0004340012,0.0009672329,0.0008248656,0.00311072],"category_scores_gemma":[0.0008613655,0.0003564407,0.0003440994,0.0002648591,0.0001652557,0.0005390029,0.000638383,0.0008846216,0.0009786395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006007674,"about_ca_system_score_gemma":0.000850451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004937076,"about_ca_topic_score_gemma":0.007948135,"domain_scores_codex":[0.9998032,0.00001886943,0.00001435027,0.00006522579,0.000076098,0.00002237572],"domain_scores_gemma":[0.9997522,0.00004315532,0.00003605545,0.00002692177,0.0001187203,0.00002291833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004011445,0.0003110123,0.003403122,0.0002187935,0.0001154361,0.0002861164,0.000082559,0.1261698,0.0690046,0.002129261,0.01163332,0.786245],"study_design_scores_gemma":[0.00002858268,0.0001561703,0.00136694,0.00002130284,0.00002123153,0.0001284931,0.000007000801,0.9798561,0.01457829,0.0006050671,0.003206876,0.00002390702],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02489233,0.0005052818,0.9648443,0.0002869476,0.0002299911,0.0001132308,0.0002709823,0.007100704,0.001756158],"genre_scores_gemma":[0.6824362,0.0005109097,0.3062916,0.0004990774,0.0001247832,0.0003236835,0.0008194316,0.0001355867,0.00885871],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004937076,"threshold_uncertainty_score":0.01040637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006854119067156757,"score_gpt":0.2104104375757176,"score_spread":0.2035563185085609,"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."}}