{"id":"W4392499491","doi":"10.1145/3643500","title":"exHAR","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Debugging; Computer science; Set (abstract data type); Process (computing); Human–computer interaction; Task (project management); Mental model; Data science; Cognitive science; Psychology; Programming language; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00024823,0.0002007115,0.000259891,0.0002901717,0.0001334355,0.0003682997,0.002430769,0.0001273884,0.000006580602],"category_scores_gemma":[0.0007777528,0.0001343685,0.0001138075,0.0006229774,0.0001800352,0.001052158,0.002309208,0.0004497147,0.00003859707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007347313,"about_ca_system_score_gemma":0.00003006405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002320159,"about_ca_topic_score_gemma":0.000001781751,"domain_scores_codex":[0.9987122,0.000009761596,0.0002458574,0.0005247055,0.0002585966,0.0002488407],"domain_scores_gemma":[0.9986584,0.0003693189,0.0001497876,0.0005975508,0.000201477,0.00002342896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005790776,0.0001782244,0.0009332874,0.0004403617,0.0002040754,0.000008000375,0.002059253,0.000003075978,0.182574,0.02609829,0.01223269,0.7752109],"study_design_scores_gemma":[0.0001458097,0.0005341627,0.000342945,0.001480135,0.00001894475,0.0001248204,0.003397351,0.000939558,0.9111667,0.06137183,0.02020939,0.0002683579],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794191,0.002779944,0.0004431129,0.00585837,0.0009240124,0.0007661057,0.00001001473,0.002210088,0.007589216],"genre_scores_gemma":[0.9981517,0.0002518435,0.0006909348,0.00005934781,0.00003316429,0.0002648188,1.022666e-7,0.0000150158,0.0005330609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7749425,"threshold_uncertainty_score":0.5479388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01432217940609675,"score_gpt":0.2591460713403809,"score_spread":0.2448238919342841,"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."}}