{"id":"W2097353049","doi":"10.1109/tbme.2010.2052618","title":"A Resistive Mesh Phantom for Assessing the Performance of EIT Systems","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; HEC Montréal; Polytechnique Montréal","funders":"Canadian Institutes of Health Research","keywords":"Imaging phantom; Electrical impedance tomography; Resistive touchscreen; Electrical impedance; Resistor; Acoustics; Calibration; Distortion (music); Electronic engineering; Computer science; Physics; Optics; Engineering; Voltage; Electrical engineering; Computer vision","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":[0.0002020126,0.0001588565,0.0001927266,0.0001926479,0.0000923666,0.00002922077,0.0001815954,0.0001347277,0.000009934999],"category_scores_gemma":[0.00001009065,0.0001121223,0.0001222323,0.000570951,0.00008102746,0.00009828395,6.64915e-7,0.0004453942,0.000002988581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002143944,"about_ca_system_score_gemma":0.00001810174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007901208,"about_ca_topic_score_gemma":0.000001800682,"domain_scores_codex":[0.9990671,0.000006727202,0.0002653334,0.0001387423,0.000230921,0.0002912309],"domain_scores_gemma":[0.9993999,0.0002553265,0.0000260402,0.000173194,0.00004399607,0.000101538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003106806,0.0001540481,0.0000222929,0.00074376,0.0002463345,0.000002575521,0.0001357444,0.1287461,0.8230585,0.0002215991,0.0002951422,0.04634281],"study_design_scores_gemma":[0.0003057818,0.0001177874,0.0002307195,0.0001053905,0.00004446193,0.00001134893,0.00001710302,0.8926752,0.1026948,0.000003170069,0.003612247,0.0001819907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3691179,0.0001193026,0.6285589,0.00005114855,0.001575333,0.0002309206,0.00003302286,0.0002557745,0.00005766447],"genre_scores_gemma":[0.9982522,0.00008045727,0.001333875,0.000008647523,0.0001498171,0.0001137923,0.000002270021,0.00002918306,0.00002977824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7639291,"threshold_uncertainty_score":0.4572214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006394359803995483,"score_gpt":0.2210609092614987,"score_spread":0.2146665494575032,"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."}}