{"id":"W2099340215","doi":"10.1109/ccece.2006.277846","title":"Imaging of Electrode Movement and Conductivity Change in Electrical Impedance Tomography","year":2006,"lang":"en","type":"article","venue":"","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Electrical impedance tomography; Electrode; Iterative reconstruction; Tomography; Electrical impedance; Electrical resistivity tomography; Materials science; Smoothness; Conductivity; Sensitivity (control systems); Acoustics; Boundary (topology); Medical imaging; Electrical resistivity and conductivity; Biomedical engineering; Computer vision; Computer science; Artificial intelligence; Electronic engineering; Physics; Optics; Mathematics; Electrical engineering; Engineering; Mathematical analysis","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":[0.0001039499,0.0001431242,0.0002049724,0.0002942322,0.00001809759,0.0000108069,0.0000694142,0.00004119849,0.00001134601],"category_scores_gemma":[0.000003423194,0.0001266204,0.00005893243,0.0009954291,0.00004475941,0.0001432949,0.00001419492,0.0001499039,6.902138e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002571022,"about_ca_system_score_gemma":0.000004848311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006277228,"about_ca_topic_score_gemma":0.0002468849,"domain_scores_codex":[0.9990841,0.00001646971,0.0002183549,0.0001822048,0.0001281399,0.0003707722],"domain_scores_gemma":[0.9997808,0.00003469017,0.00002370238,0.0001007409,0.000019879,0.00004013184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001802531,0.0001435191,0.7112119,0.00006722069,0.0000189926,0.00000731625,0.00004950623,0.00004350637,0.2386726,0.005982588,0.0003508802,0.043434],"study_design_scores_gemma":[0.0006627238,0.0001206387,0.691749,0.00002241762,0.00001405521,0.000006357222,0.000008799514,0.04103168,0.2586634,0.0071115,0.000219848,0.0003895238],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910467,0.005712157,0.0006125299,0.00008813969,0.00003091054,0.0001856831,0.00000274297,0.0001387142,0.002182445],"genre_scores_gemma":[0.9991204,0.0002590011,0.0004118532,0.00009006018,0.00005673952,0.00003401085,0.000002343281,0.00001324387,0.00001234879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04304447,"threshold_uncertainty_score":0.5163431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006251455874463315,"score_gpt":0.2050881695086489,"score_spread":0.1988367136341856,"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."}}