{"id":"W2041556066","doi":"10.1088/0967-3334/27/5/s03","title":"Uses and abuses of EIDORS: an extensible software base for EIT","year":2006,"lang":"ar","type":"article","venue":"Physiological Measurement","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":835,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Suite; Software engineering; Software; Reuse; Interface (matter); Key (lock); Software construction; Personalization; Software framework; Software development; Human–computer interaction; Programming language; World Wide Web; Computer security; Operating system; 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":[0.0003551557,0.0003460177,0.0005470233,0.00008731837,0.0001423063,0.00004295436,0.0001760832,0.000164953,0.0000391164],"category_scores_gemma":[0.0001523549,0.0002539908,0.0002109612,0.0002910406,0.0001899699,0.0001155716,0.00004010065,0.0001604987,0.000007490023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004873644,"about_ca_system_score_gemma":0.00002708732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001431733,"about_ca_topic_score_gemma":0.00003977654,"domain_scores_codex":[0.9980147,0.00008545927,0.0004662198,0.0004902608,0.0004086159,0.000534759],"domain_scores_gemma":[0.9990205,0.0001284274,0.00010461,0.0002734875,0.0003244677,0.0001485507],"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":[0.0003243262,0.001629557,0.005950298,0.001156316,0.0001960546,0.000005404548,0.00006494534,0.003641318,0.9612316,0.001175718,0.003098019,0.02152641],"study_design_scores_gemma":[0.004027643,0.008988583,0.5114524,0.000961494,0.0006529865,0.00000990864,0.0001224963,0.01016378,0.4050584,0.0524931,0.003814129,0.002255035],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852356,0.01035747,0.003102552,0.00008204744,0.000154866,0.000665678,0.0000874662,0.0002241297,0.00009013846],"genre_scores_gemma":[0.9932352,0.0002741272,0.005946459,0.00006525389,0.0003421691,0.0000767469,0.00001984414,0.00002834529,0.0000118159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5561732,"threshold_uncertainty_score":0.9999912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06745386133661634,"score_gpt":0.2392757742309731,"score_spread":0.1718219128943568,"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."}}