{"id":"W4384103470","doi":"10.22214/ijraset.2023.54675","title":"Find Missing Person using HAAR CASCADE","year":2023,"lang":"en","type":"article","venue":"International Journal for Research in Applied Science and Engineering Technology","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Haar-like features; Identification (biology); Cascade; Artificial intelligence; Face (sociological concept); Process (computing); Cover (algebra); Haar; Machine learning; Computer vision; Data mining; Facial recognition system; Face detection; Pattern recognition (psychology); Engineering; Operating system","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":[0.002806195,0.0000773746,0.0001285747,0.004018737,0.0002359755,0.0001392739,0.0004025165,0.00009452512,0.000004194435],"category_scores_gemma":[0.00154844,0.00007402368,0.00002386372,0.001993947,0.000350726,0.00009946919,0.0001602045,0.0006212899,0.00000584141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007101832,"about_ca_system_score_gemma":0.0004282316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001884655,"about_ca_topic_score_gemma":0.000001333871,"domain_scores_codex":[0.9982145,0.000005083954,0.0001645822,0.0002579479,0.0008367369,0.000521159],"domain_scores_gemma":[0.9991364,0.0002307535,0.00002873432,0.0001144045,0.0003654556,0.0001242444],"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":[0.00006571663,0.00004203412,0.0007595429,0.00005130238,0.00002632694,0.000299385,0.0002990389,0.00408868,0.9354388,0.005804311,0.001107676,0.05201725],"study_design_scores_gemma":[0.002545262,0.0002516586,0.006490677,0.001025876,0.00001379914,0.00199458,0.001509522,0.8621745,0.06694632,0.01330219,0.04342986,0.0003157558],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9293672,0.0001028366,0.002291761,0.06729123,0.000472798,0.0002697289,0.000002569573,0.0001261564,0.00007575773],"genre_scores_gemma":[0.9918315,0.00008731945,0.007603224,0.0002375674,0.000163788,0.00002712794,0.000001030717,0.00001553383,0.00003290281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8684924,"threshold_uncertainty_score":0.3585877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1738888810819288,"score_gpt":0.4702060472038425,"score_spread":0.2963171661219136,"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."}}