{"id":"W2107995835","doi":"10.1109/tbme.2006.872813","title":"Automated search for arthritic patterns in infrared spectra of synovial fluid using adaptive wavelets and fuzzy C-Means analysis","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Humber River Regional Hospital; University of Toronto","funders":"","keywords":"Pattern recognition (psychology); Wavelet; Artificial intelligence; Fuzzy logic; Computer science; Matrix (chemical analysis); Materials science","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":[0.00009806429,0.0001815115,0.0003987129,0.0009930371,0.00005024262,0.00001649682,0.00009362625,0.0001706907,0.0001330379],"category_scores_gemma":[0.000009250049,0.0001904184,0.0001638512,0.001530528,0.00007495179,0.00006367666,0.000001653275,0.0002239556,6.321924e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001363375,"about_ca_system_score_gemma":0.00003847863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000346718,"about_ca_topic_score_gemma":0.00003668767,"domain_scores_codex":[0.998732,0.000007950935,0.0003897843,0.0002774784,0.0002606305,0.0003321358],"domain_scores_gemma":[0.9994745,0.000194948,0.00003840324,0.0001503994,0.00003895888,0.0001028149],"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":[0.0001040916,0.0005641817,0.0004023917,0.0003489965,0.0009195086,0.00002929231,0.000156413,0.2581595,0.7382056,0.0000662796,0.000007722341,0.001036031],"study_design_scores_gemma":[0.0007010103,0.00005793189,0.000467856,0.00005887767,0.0003744517,0.00000649093,0.00009905569,0.6440606,0.3539933,0.00001073166,0.000007413778,0.0001623205],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4746266,0.00005489762,0.5249395,0.00001377306,0.00003040528,0.00005063977,0.0001440507,0.00009433463,0.00004570521],"genre_scores_gemma":[0.995922,0.0000295902,0.003892115,0.000005025943,0.00005431962,0.00001738107,0.00002543987,0.00002229092,0.00003182436],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5212954,"threshold_uncertainty_score":0.7765039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01321386461102538,"score_gpt":0.255011269229201,"score_spread":0.2417974046181756,"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."}}