{"id":"W2574674378","doi":"10.21700/ijcis.2016.130","title":"A Prototype Hybrid Algorithm to Detect Face Oval Based on Facial Expression Recognition","year":2016,"lang":"en","type":"article","venue":"International Journal of Computing and Information Sciences","topic":"Face recognition and analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Facial expression; Face (sociological concept); Computer science; Facial recognition system; Computer vision; Facial expression recognition; Three-dimensional face recognition; Pattern recognition (psychology); Face detection; Speech recognition","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":[0.0003743821,0.0006403762,0.0008270228,0.0009011539,0.0003831086,0.0006347277,0.001508322,0.0008254671,0.004641044],"category_scores_gemma":[0.000447732,0.0003449091,0.0005642849,0.0006092042,0.0001947433,0.000843805,0.0005686141,0.0004427736,0.001855168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002580851,"about_ca_system_score_gemma":0.0005047484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001626328,"about_ca_topic_score_gemma":0.002135987,"domain_scores_codex":[0.9995925,0.00003870944,0.00001723431,0.000117353,0.0001935974,0.00004049818],"domain_scores_gemma":[0.9997271,0.00004056421,0.00001394351,0.00004003282,0.0001588498,0.00001947785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004287336,0.0001246577,0.001419181,0.00009673937,0.00007062406,0.00008568769,0.00004546042,0.003296364,0.2185924,0.001171111,0.003313033,0.771356],"study_design_scores_gemma":[0.0001155898,0.0007616819,0.009981825,0.00003190197,0.0001877626,0.001977157,0.0001095553,0.7452673,0.2255468,0.00145242,0.01446484,0.000103206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02801315,0.0004422645,0.9669979,0.00007365628,0.000162115,0.0001312482,0.00008296995,0.002078447,0.002018263],"genre_scores_gemma":[0.189397,0.0003591597,0.7999663,0.000176859,0.00007930295,0.0002312863,0.0003972392,0.0001646566,0.009228234],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004641044,"threshold_uncertainty_score":0.01552588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01947388318638007,"score_gpt":0.2882721506473909,"score_spread":0.2687982674610109,"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."}}