{"id":"W3206836900","doi":"10.1007/s11517-021-02454-3","title":"Development of a tissue discrimination electrode embedded surgical needle using vibro-tactile feedback derived from electric impedance spectroscopy","year":2021,"lang":"en","type":"article","venue":"Medical & Biological Engineering & Computing","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Electrical impedance; Biomedical engineering; Computer science; Electrode; Electrode array; Naive Bayes classifier; MATLAB; Acoustics; Artificial intelligence; Support vector machine; Physics; Engineering; Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003019806,0.0004284134,0.0007094359,0.0001546486,0.0001172897,0.00004304282,0.0003546711,0.0003844234,0.0002469335],"category_scores_gemma":[0.0002952436,0.0003663091,0.0001748888,0.0013017,0.00005732401,0.00007810714,0.0001441135,0.000743408,0.00001849098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001792275,"about_ca_system_score_gemma":0.0001333935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001807997,"about_ca_topic_score_gemma":0.000004280603,"domain_scores_codex":[0.997058,0.00007414243,0.0008357585,0.0005518115,0.0005626683,0.0009176128],"domain_scores_gemma":[0.9988173,0.000415517,0.0001040798,0.0002301988,0.00009341934,0.0003394649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002216768,0.0001156916,0.0006177188,0.00008781334,0.00009366528,0.00008094172,0.0001766909,0.005676314,0.9710221,0.00006717857,0.00002145303,0.02201822],"study_design_scores_gemma":[0.0004755973,0.00008121105,0.006604253,0.0001746447,0.00002389479,0.00005570488,0.00003034938,0.3653834,0.6261088,0.00004441841,0.0005717395,0.0004459784],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8119143,0.001995932,0.1850867,0.00002466491,0.0002553869,0.0001296547,0.000004272541,0.0003851429,0.0002039016],"genre_scores_gemma":[0.9218831,0.0001437149,0.07745714,0.00003082882,0.0003644445,0.000008049595,0.00006761634,0.00004125563,0.000003837262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3597071,"threshold_uncertainty_score":0.9998789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01383098039454282,"score_gpt":0.2470807556898041,"score_spread":0.2332497752952613,"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."}}