{"id":"W6980691341","doi":"","title":"Computational intelligence techniques: a study of scleroderma skin disease","year":2007,"lang":"en","type":"article","venue":"NPARC","topic":"Systemic Sclerosis and Related Diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cluster analysis; Particle swarm optimization; Set (abstract data type); Rough set; Computational intelligence; Data set; Scleroderma (fungus); Genetic programming; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007395817,0.0002274295,0.0002805277,0.001751245,0.0002780543,0.0013844,0.0002320822,0.0003612887,0.001246861],"category_scores_gemma":[0.004381883,0.00005995656,0.0003216091,0.00260333,0.0009898338,0.0008185894,0.000359922,0.0005495886,0.0001663156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005116126,"about_ca_system_score_gemma":0.0004346929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009161827,"about_ca_topic_score_gemma":0.0006337515,"domain_scores_codex":[0.9993926,0.0003134627,0.00002692459,0.00004868188,0.0001784904,0.00003983756],"domain_scores_gemma":[0.9980878,0.001541312,0.0001215715,0.00006890658,0.000132402,0.00004785635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001434253,0.0003116154,0.04524304,0.001070995,0.0003070515,0.001480142,0.002996792,0.02947104,0.004156735,0.4857261,0.007462911,0.4216302],"study_design_scores_gemma":[0.00006230544,0.0005140778,0.1086864,0.0008281952,0.0001558967,0.006232942,0.005618498,0.207944,0.004783137,0.4881502,0.1769536,0.0000707508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6231493,0.1067823,0.1133983,0.0247024,0.0004906523,0.000118781,0.0002694811,0.000126136,0.1309627],"genre_scores_gemma":[0.9557304,0.01641572,0.02332547,0.0004942714,0.0002298545,0.00004763865,0.00009294287,0.00001427081,0.003649542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001751245,"threshold_uncertainty_score":0.004171193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02701952323965698,"score_gpt":0.30567358673513,"score_spread":0.2786540634954729,"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."}}