{"id":"W2071821890","doi":"10.1145/2522968.2522978","title":"Object class detection","year":2013,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Class (philosophy); Object detection; Key (lock); Data science; Object (grammar); Boom; Artificial intelligence; Machine learning; Pattern recognition (psychology); Computer security","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001991957,0.001408667,0.001838255,0.007290903,0.0009263491,0.002788876,0.00319799,0.002180023,0.009342822],"category_scores_gemma":[0.005883444,0.0004747112,0.001285929,0.004163788,0.000738973,0.003600652,0.001516791,0.001140436,0.01893836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009627513,"about_ca_system_score_gemma":0.001460415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003427453,"about_ca_topic_score_gemma":0.004728172,"domain_scores_codex":[0.9971539,0.000231904,0.0001046684,0.0008378729,0.001467656,0.0002039156],"domain_scores_gemma":[0.9972014,0.0007094645,0.0002057151,0.0003831802,0.001399296,0.0001009031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003964327,0.00007725442,0.002179163,0.001025649,0.00006333188,0.00008898724,0.00005573679,0.0004422815,0.004412441,0.003771903,0.05804216,0.9298015],"study_design_scores_gemma":[0.00003994429,0.0002613294,0.01702516,0.001870034,0.0004153351,0.006463128,0.0006116581,0.03660217,0.04096868,0.03381891,0.8617221,0.0002015849],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.0155831,0.1730748,0.683074,0.003232447,0.004056589,0.001373965,0.00625406,0.01055765,0.1027933],"genre_scores_gemma":[0.1671227,0.168261,0.5305737,0.005955955,0.003559373,0.001099343,0.02508247,0.001432882,0.09691251],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.009342822,"threshold_uncertainty_score":0.03125483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07827523128352543,"score_gpt":0.3657628754005727,"score_spread":0.2874876441170472,"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."}}