{"id":"W2075225575","doi":"10.1088/0967-3334/32/7/s09","title":"Evaluation of EIT system performance","year":2011,"lang":"es","type":"article","venue":"Physiological Measurement","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Electrical impedance tomography; Computer science; Imaging phantom; Calibration; Noise (video); Software; Position (finance); Set (abstract data type); Controller (irrigation); Electronic engineering; Computer vision; Electrical impedance; Artificial intelligence; Image (mathematics); Engineering; Optics; Electrical engineering; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.002045624,0.0002353056,0.0003638502,0.00007430707,0.00005307971,0.000008326753,0.000224175,0.0001330939,0.0001458535],"category_scores_gemma":[0.00006341151,0.0001659735,0.0001738552,0.0003723019,0.00006869392,0.00006645099,0.00003543394,0.0001807707,0.00008184412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002548818,"about_ca_system_score_gemma":0.00004223495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002329259,"about_ca_topic_score_gemma":5.365179e-7,"domain_scores_codex":[0.9971289,0.0002395278,0.0004305363,0.0002713983,0.001580639,0.0003489679],"domain_scores_gemma":[0.9987037,0.00001268788,0.0001222761,0.0002601057,0.0008115377,0.00008971473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002315688,0.001363428,0.008886357,0.003254336,0.001033686,0.000002556956,0.0003006234,0.002878872,0.667411,0.006319003,0.0003652982,0.3079533],"study_design_scores_gemma":[0.0008263132,0.001434287,0.7669116,0.000814891,0.0007312041,0.000002464975,0.00004593639,0.06608228,0.1620424,0.0005561546,0.00007788134,0.0004746511],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9727199,0.0038194,0.0001545834,0.000005363151,0.0002742837,0.0004664274,0.000005497643,0.0001376532,0.02241687],"genre_scores_gemma":[0.9993229,0.0002556528,0.0002042245,0.000006299344,0.0001216927,0.0000729403,0.000001776087,0.0000129906,0.000001512977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7580252,"threshold_uncertainty_score":0.6768203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2119440028232888,"score_gpt":0.2497254463499755,"score_spread":0.03778144352668669,"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."}}