{"id":"W2296536497","doi":"","title":"RE@CT - Immersive Production and Delivery of Interactive 3D Content","year":2012,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Human Motion and Animation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Research (Canada)","funders":"","keywords":"Computer science; Animation; Reuse; Key (lock); Motion capture; Process (computing); Multimedia; Post-production; Studio; Representation (politics); Computer animation; Computer graphics (images); Production (economics); Human–computer interaction; Motion (physics); Artificial intelligence; Engineering","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":[0.001279389,0.0001963496,0.0002443379,0.0001528331,0.00008794702,0.00007152705,0.0002232906,0.00009232709,0.0001288624],"category_scores_gemma":[0.0003945322,0.0002173978,0.00008538044,0.0001019851,0.0001101498,0.0002032424,0.0002785928,0.0003792083,0.00001856803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001056925,"about_ca_system_score_gemma":0.00003331978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000344809,"about_ca_topic_score_gemma":0.0004098792,"domain_scores_codex":[0.9981655,0.000852973,0.0003491516,0.00029052,0.0001779914,0.0001638085],"domain_scores_gemma":[0.9979488,0.0001929082,0.0002445237,0.0005966911,0.0009311659,0.00008594137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001213171,0.002137433,0.01055088,0.005239742,0.001553586,0.00001108193,0.2458132,0.004669829,0.3084452,0.03290999,0.007654347,0.3808934],"study_design_scores_gemma":[0.001106216,0.000001547989,0.05664221,0.009320437,0.0002948288,0.00003077899,0.003981454,0.08051354,0.8383672,0.001205922,0.0071098,0.00142609],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.936945,0.001671566,0.04000564,0.001158696,0.0006045519,0.0004880535,0.0000455626,0.0001868684,0.01889412],"genre_scores_gemma":[0.9931636,0.0008249897,0.004662585,0.00001398932,0.00002919866,0.00002737127,0.0001679271,0.00002966479,0.001080669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.529922,"threshold_uncertainty_score":0.8865227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02628148190232238,"score_gpt":0.2214602207410976,"score_spread":0.1951787388387752,"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."}}