{"id":"W3191313977","doi":"","title":"Machine Learning in Expressive Gestural Interaction","year":2016,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Human Motion and Animation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Human–computer interaction; Communication; Psychology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002691554,0.0004106515,0.0003896548,0.0003126369,0.0002472557,0.0003150693,0.0005880005,0.0003511948,0.00126609],"category_scores_gemma":[0.001107531,0.0004318319,0.0001927973,0.000250437,0.0001250236,0.0004051836,0.0004862565,0.001278166,0.0004838592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005147449,"about_ca_system_score_gemma":0.00008105213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00109663,"about_ca_topic_score_gemma":0.002182512,"domain_scores_codex":[0.9934917,0.004462072,0.0006990433,0.0006191864,0.0003106802,0.0004173094],"domain_scores_gemma":[0.9967866,0.001019331,0.0004100798,0.0008312901,0.0007876336,0.0001650768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005332995,0.0009439496,0.0231508,0.0009321325,0.0002207535,0.00003643687,0.05838346,0.0171785,0.07787057,0.4238102,0.001392372,0.3960274],"study_design_scores_gemma":[0.002891369,0.000001658484,0.08737374,0.02132055,0.00008597405,0.00005431923,0.0007524845,0.6135899,0.08514117,0.01217402,0.1747409,0.00187398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3832653,0.003089371,0.3829951,0.02573515,0.00157153,0.0008612973,0.00008226032,0.0009403836,0.2014597],"genre_scores_gemma":[0.9540956,0.0013318,0.01170068,0.00003224895,0.00007396277,0.00006790452,0.0004231785,0.00007755236,0.03219705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5964114,"threshold_uncertainty_score":0.9998133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416639549181979,"score_gpt":0.2282834105302611,"score_spread":0.2141170150384413,"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."}}