{"id":"W1965463297","doi":"10.1007/s11042-012-1352-1","title":"Robust semi-automatic head pose labeling for real-world face video sequences","year":2013,"lang":"en","type":"article","venue":"Multimedia Tools and Applications","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Pose; Face (sociological concept); Frame (networking); Ground truth; Interpolation (computer graphics); Pattern recognition (psychology); 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":[0.0001164349,0.0001202878,0.0001389135,0.00006825289,0.0002709758,0.0003141974,0.0002983366,0.00005246488,0.00004601514],"category_scores_gemma":[0.00003308306,0.0001018769,0.00003909344,0.0002458551,0.00004549514,0.0006302014,0.00008049838,0.00006629446,0.000167164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001689927,"about_ca_system_score_gemma":0.000030285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002078391,"about_ca_topic_score_gemma":0.00006750906,"domain_scores_codex":[0.9990667,0.00001934975,0.0002316322,0.000338888,0.0001189177,0.0002245265],"domain_scores_gemma":[0.9989981,0.0003754382,0.00008696699,0.0003049119,0.000106554,0.0001280323],"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":[0.000001290192,0.00009615126,0.0004282735,0.00007976471,0.00001600854,3.416781e-7,0.0005313381,0.0004226452,0.02277341,0.00275611,0.01058752,0.9623072],"study_design_scores_gemma":[0.0005635103,0.00003841491,0.003502741,0.0001089348,0.00001713494,0.000003848006,0.0002009043,0.9537504,0.006892016,0.008192979,0.02638276,0.0003463416],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04929763,0.0002826351,0.9398999,0.005521653,0.0001594814,0.002730114,0.0000897721,0.0004734725,0.001545381],"genre_scores_gemma":[0.2566932,0.0004514247,0.7309595,0.001082074,0.0003520262,0.008366674,0.0002017816,0.00002822597,0.001865073],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9619608,"threshold_uncertainty_score":0.4154421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05692627969358233,"score_gpt":0.2934819565276538,"score_spread":0.2365556768340715,"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."}}