{"id":"W2071086297","doi":"10.1145/2808201","title":"SAfeDJ","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Multimedia Computing Communications and Applications","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada); University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; East China Normal University; Swedish Foundation for International Cooperation in Research and Higher Education","keywords":"Mood; Active listening; Computer science; Context (archaeology); Human–computer interaction; Cloud computing; Multimedia; Applied psychology; Psychology; Social psychology","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":[0.0003029512,0.0001568949,0.0001506922,0.0001888174,0.0005992035,0.00004804558,0.0006477715,0.0001143797,0.0001439028],"category_scores_gemma":[0.00003041395,0.0001648639,0.00006443302,0.0003932827,0.0002437477,0.00007271661,0.00004371241,0.0003710825,0.0007704527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004283357,"about_ca_system_score_gemma":0.00004304011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009534818,"about_ca_topic_score_gemma":0.00003856662,"domain_scores_codex":[0.9988518,0.0001660619,0.00031993,0.0003139699,0.0001340101,0.0002142647],"domain_scores_gemma":[0.9969695,0.0005682192,0.0001035672,0.001933127,0.0001766927,0.0002489512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001352454,0.0007554872,0.0001546609,0.00000481015,0.00005992774,3.458651e-7,0.002128228,0.00006778743,0.00007947792,0.006766242,0.0006865305,0.989283],"study_design_scores_gemma":[0.007086839,0.0006349987,0.01046806,0.0001510691,0.0003966861,0.0002229389,0.01625464,0.04085735,0.0004808018,0.01940208,0.9024778,0.001566748],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005161964,0.0006710051,0.946744,0.006272539,0.0003809448,0.001022534,0.00006848407,0.0005606941,0.03911788],"genre_scores_gemma":[0.9184152,0.0001941705,0.07917117,0.0005255875,0.0001022213,0.0004182817,0.0001090517,0.00002894391,0.001035375],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9877163,"threshold_uncertainty_score":0.9902867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09140812908194182,"score_gpt":0.3671197014728504,"score_spread":0.2757115723909086,"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."}}