{"id":"W2030206951","doi":"10.1016/j.ins.2012.09.011","title":"Computerized facial diagnosis using both color and texture features","year":2012,"lang":"en","type":"article","venue":"Information Sciences","topic":"Traditional Chinese Medicine Studies","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Hong Kong Polytechnic University","keywords":"Artificial intelligence; Computer science; Pattern recognition (psychology); Computer vision; Face (sociological concept); Feature (linguistics); Texture (cosmology); Image (mathematics)","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":[0.0002609097,0.00007530586,0.0001355838,0.000128975,0.000256512,0.00004368015,0.00004460879,0.00002760596,0.00003100682],"category_scores_gemma":[0.0001561592,0.00004803749,0.00002109125,0.00022904,0.0002959089,0.001131563,0.00003033141,0.00006415008,0.00001084019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001986732,"about_ca_system_score_gemma":0.00004268826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003227531,"about_ca_topic_score_gemma":0.000002506636,"domain_scores_codex":[0.9992924,0.00001105794,0.0001555653,0.00005368512,0.0003382502,0.0001489898],"domain_scores_gemma":[0.9996669,0.00008545135,0.00006867731,0.00004164022,0.0000507039,0.00008666479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001139663,0.0001106063,0.8828431,0.0002246864,0.00007489225,0.000002520979,0.02167324,0.0001012637,0.0008366607,0.006363071,0.02341905,0.06423689],"study_design_scores_gemma":[0.0006239628,0.0001125408,0.9720787,0.00005301637,0.00002513668,0.0001286141,0.0009266022,0.001369507,0.0001277669,0.00007665472,0.02439805,0.00007943682],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921098,0.000387144,0.0006431963,0.002121039,0.0003788823,0.0001908333,0.00001416141,0.00004142156,0.004113506],"genre_scores_gemma":[0.9946463,0.00003230534,0.003298146,0.001702499,0.0002864779,0.00001030526,0.000009626957,0.000001437531,0.00001297555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08923555,"threshold_uncertainty_score":0.1972909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05299098114516179,"score_gpt":0.3363821884724308,"score_spread":0.283391207327269,"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."}}