{"id":"W2998237518","doi":"10.20380/gi2018.12","title":"It's the Gesture That (re)Counts: Annotating While Running to Recall Affective Experience","year":2018,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Annotation; Recall; Computer science; Gesture; Visualization; Multimedia; Artificial intelligence; Cognitive psychology; Psychology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002636308,0.0001469543,0.0001275454,0.00001924873,0.001889586,0.0003001337,0.002907304,0.00004981941,0.00003520908],"category_scores_gemma":[0.00001308053,0.0001212129,0.0000646192,0.000419923,0.000220573,0.0002880391,0.001139525,0.0002939146,0.00001677981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002126795,"about_ca_system_score_gemma":0.0003312803,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007764673,"about_ca_topic_score_gemma":0.0301558,"domain_scores_codex":[0.9988742,0.0000800848,0.0001743796,0.0003114031,0.0002774575,0.0002824577],"domain_scores_gemma":[0.9977146,0.0001539965,0.0001151169,0.001726731,0.0002016571,0.00008789436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[4.940883e-7,0.00002866611,0.0003246276,0.00001367039,0.00004104026,0.000001419117,0.08395676,0.00008372674,0.0001602067,0.006715954,0.8711419,0.03753153],"study_design_scores_gemma":[0.0001546211,0.00003731284,0.003041067,0.0001641248,0.00001018404,0.00001057415,0.002670859,0.05735074,0.0003182776,0.0004091379,0.9354062,0.0004268932],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0117473,0.0007783067,0.8870288,0.0539148,0.001237337,0.0005249107,0.000006486067,0.0003167949,0.04444534],"genre_scores_gemma":[0.8049404,0.00001276517,0.162151,0.03215291,0.0002868674,0.00004938832,0.00000537699,0.00001376254,0.0003875005],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7931931,"threshold_uncertainty_score":0.9994098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0616332551326987,"score_gpt":0.3041881070239626,"score_spread":0.2425548518912639,"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."}}