{"id":"W2351022052","doi":"","title":"Face ROI Coding Based on AdaBoost.","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; AdaBoost; Region of interest; Artificial intelligence; Coding (social sciences); JPEG 2000; Computer vision; Face (sociological concept); Face detection; Pattern recognition (psychology); Facial recognition system; Image processing; Image (mathematics); Mathematics; Image compression; Classifier (UML)","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":[0.0005687274,0.0006709446,0.000658737,0.001264417,0.0003821664,0.0005847996,0.0009515039,0.00066936,0.001768155],"category_scores_gemma":[0.001099768,0.0003407789,0.0005618155,0.0006655327,0.0004001893,0.0009750973,0.0004805347,0.0008760773,0.001019734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005393282,"about_ca_system_score_gemma":0.0008042204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004427749,"about_ca_topic_score_gemma":0.004061223,"domain_scores_codex":[0.9995213,0.00006884831,0.00001531649,0.0001054429,0.0002385765,0.00005049646],"domain_scores_gemma":[0.9996536,0.00007364777,0.00002521801,0.0000351155,0.0001908597,0.00002145544],"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":[0.0002838013,0.0001160604,0.00092367,0.0001567857,0.00008575548,0.00009151801,0.00008506362,0.04582521,0.1038274,0.009026425,0.006191462,0.8333868],"study_design_scores_gemma":[0.00002029534,0.0001045631,0.00130361,0.00001772317,0.00003740866,0.0003017833,0.00002646673,0.9110221,0.07662513,0.002584724,0.00791385,0.00004220808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005961229,0.0003738581,0.9910159,0.00004642149,0.0000876579,0.00004947106,0.00002564832,0.0009982033,0.001441533],"genre_scores_gemma":[0.1770583,0.0006421536,0.8156216,0.0001325688,0.00007992435,0.0001581083,0.0002105969,0.0002209737,0.005875696],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004427749,"threshold_uncertainty_score":0.008803964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009470676771127201,"score_gpt":0.2073227673924418,"score_spread":0.1978520906213146,"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."}}