{"id":"W2468212864","doi":"10.1145/2897824.2925984","title":"JALI","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Face recognition and analysis","field":"Computer Science","cited_by":174,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Computer science; Animation; Computer facial animation; Facial motion capture; Retargeting; Motion capture; Facial muscles; Computer animation; Articulation (sociology); Workflow; Viseme; Speech recognition; Human–computer interaction; Artificial intelligence; Motion (physics); Computer graphics (images); Speech synthesis; Communication; Facial recognition system; Pattern recognition (psychology); Psychology; Face detection","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009278535,0.00008160652,0.00007904429,0.0002431147,0.000143894,0.00004292483,0.0005261585,0.00004982308,0.0001734062],"category_scores_gemma":[0.00001779541,0.00005476557,0.000148227,0.0006439062,0.00004486321,0.0002719859,0.000004982503,0.00007971696,0.0003553513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001208812,"about_ca_system_score_gemma":0.00001840192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006384302,"about_ca_topic_score_gemma":0.00002508267,"domain_scores_codex":[0.9993051,0.00003425158,0.0001117354,0.0002211184,0.0001784757,0.0001492755],"domain_scores_gemma":[0.9990627,0.0001382369,0.0000249457,0.0006375032,0.00005539845,0.00008122087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004509234,0.0001880472,0.0001329371,0.000004361118,0.00008626177,0.000006305906,0.00009126306,0.00002299533,0.001864953,0.0292176,0.0005584763,0.9678223],"study_design_scores_gemma":[0.005737453,0.0009904618,0.007657942,0.0005138378,0.0003284119,0.0001321882,0.0001964725,0.01620383,0.1636427,0.5878198,0.2139104,0.002866437],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00180978,0.00001504741,0.9838766,0.01338485,0.0001617511,0.00003376968,0.000007616162,0.0001902965,0.0005202879],"genre_scores_gemma":[0.9835687,0.000417411,0.01360153,0.00147173,0.00001435917,0.00001518694,5.368718e-7,0.000006905562,0.0009036721],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9817589,"threshold_uncertainty_score":0.456744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02378708272425275,"score_gpt":0.2459245240169211,"score_spread":0.2221374412926683,"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."}}