{"id":"W4239606650","doi":"10.4018/978-1-59904-953-3.ch065","title":"Face Animation","year":2008,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Animation; Component (thermodynamics); Multimedia; Parsing; Computer facial animation; Context (archaeology); Computer animation; Face (sociological concept); Human–computer interaction; Computer graphics (images); Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002507427,0.0007957246,0.0004513104,0.001007204,0.0006185858,0.001351668,0.001074167,0.001112055,0.1225544],"category_scores_gemma":[0.0007093222,0.0002643752,0.0005837159,0.0006278008,0.0003496439,0.001631109,0.001200675,0.0009768235,0.04371517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004946032,"about_ca_system_score_gemma":0.0002507535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005039676,"about_ca_topic_score_gemma":0.0007848006,"domain_scores_codex":[0.9997998,0.00002326517,0.000007619771,0.00004636163,0.0001061852,0.00001679728],"domain_scores_gemma":[0.9998871,0.00003994022,0.000004525205,0.00002423777,0.00003038457,0.00001372337],"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":[0.00006144733,0.00007054787,0.0001585379,0.0006403429,0.00001232301,0.0002654885,0.0003229875,0.002649886,0.01425612,0.1083657,0.1456344,0.7275622],"study_design_scores_gemma":[0.000006137843,0.00003087478,0.0002485783,0.0001594659,0.000006841045,0.001175803,0.00005947939,0.004215358,0.003686387,0.0106896,0.9797035,0.00001809792],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.003723654,0.01822068,0.3476996,0.001192675,0.003319824,0.0003397534,0.0009916596,0.005825495,0.6186866],"genre_scores_gemma":[0.04994189,0.02054864,0.1631698,0.001310648,0.001002313,0.0003951966,0.002286304,0.001771923,0.7595733],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1225544,"threshold_uncertainty_score":0.4099853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02326170379103499,"score_gpt":0.2390722015623028,"score_spread":0.2158104977712678,"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."}}