{"id":"W2583343583","doi":"","title":"3D Flashback: An Informative Application for Dance.","year":2017,"lang":"en","type":"article","venue":"ERCIM news/ERCIM news online edition","topic":"Human Motion and Animation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Linguistic Association","funders":"","keywords":"Flashback; Dance; Computer science; Visual arts; Art; Chemistry; Combustion","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001542303,0.0002750201,0.0002637104,0.0001431833,0.0005112932,0.0002574053,0.0003721473,0.0002000684,0.0001324438],"category_scores_gemma":[0.00009956583,0.0002934138,0.0001047206,0.00008374634,0.0000629854,0.002625107,0.00003585771,0.0002402484,0.0002835533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001395121,"about_ca_system_score_gemma":0.00003597947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000675374,"about_ca_topic_score_gemma":0.001110572,"domain_scores_codex":[0.9986326,0.00002404551,0.000484218,0.0002876447,0.0002461031,0.0003254082],"domain_scores_gemma":[0.9987,0.00003734809,0.0002356335,0.0006857144,0.0001825551,0.0001587009],"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":[0.0001446886,0.0005288672,0.001108414,0.000601239,0.00009481908,0.000002411826,0.003672353,0.01326475,0.01618599,0.006283135,0.1461361,0.8119773],"study_design_scores_gemma":[0.002929705,0.0003619825,0.04525873,0.0002152544,0.00008381203,0.000008667291,0.001914782,0.6860539,0.003819966,0.004430815,0.2538527,0.001069734],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3856181,0.00007117091,0.5931044,0.001741673,0.004250841,0.002324496,0.0009133952,0.001661204,0.0103147],"genre_scores_gemma":[0.9577408,0.000284409,0.02403923,0.0005099928,0.008379833,0.0004327763,0.007837537,0.000124662,0.000650764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8109075,"threshold_uncertainty_score":0.9999518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02353568100647748,"score_gpt":0.2968503718518763,"score_spread":0.2733146908453988,"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."}}