{"id":"W2416063719","doi":"10.1145/2901790.2901887","title":"Heartefacts","year":2016,"lang":"en","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Fundação para a Ciência e a Tecnologia; Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Computer science; CLIPS; Multimedia; Heartbeat; Mobile device; Smartwatch; Human–computer interaction; World Wide Web; Artificial intelligence; Wearable computer; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007685485,0.0007087567,0.0003437194,0.0004930741,0.0003453562,0.00123243,0.0008636868,0.0008583541,0.04133379],"category_scores_gemma":[0.002715701,0.0002763557,0.0004123643,0.0001930073,0.0002598572,0.0009180282,0.001233258,0.0005140521,0.01019684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001786358,"about_ca_system_score_gemma":0.0002334043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003294698,"about_ca_topic_score_gemma":0.0006963176,"domain_scores_codex":[0.999676,0.00006229669,0.0000214321,0.00008574458,0.0001142219,0.00004039779],"domain_scores_gemma":[0.9990016,0.0003320519,0.00006849763,0.0001509424,0.000208289,0.0002386781],"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":[0.004299505,0.0004889019,0.009687083,0.001797273,0.0001679271,0.001189497,0.002735932,0.0004662735,0.1280845,0.006913413,0.1583144,0.6858554],"study_design_scores_gemma":[0.0009719743,0.003371192,0.09957253,0.0005081816,0.0004555317,0.006244461,0.001280478,0.008704461,0.0694794,0.005592166,0.8035815,0.0002380331],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.2875678,0.006436097,0.3642939,0.003375219,0.002805676,0.00424662,0.01117229,0.05631504,0.2637875],"genre_scores_gemma":[0.5661851,0.003945139,0.1692267,0.004061667,0.001202537,0.003574002,0.009392267,0.004393132,0.2380195],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04133379,"threshold_uncertainty_score":0.1382753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04989854174940635,"score_gpt":0.333730325631739,"score_spread":0.2838317838823327,"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."}}