{"id":"W2128427171","doi":"10.1145/2638728.2641324","title":"Activity tracking","year":2014,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Accelerometer; Gyroscope; Activity tracker; BitTorrent tracker; Computer science; Tracking (education); Raw data; Artificial intelligence; Computer vision; Eye tracking; Engineering; Embedded system; Wearable computer; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005050867,0.0008831628,0.0007971553,0.001832901,0.0004526072,0.001408041,0.000985394,0.0007529771,0.02451156],"category_scores_gemma":[0.002299244,0.0003072766,0.0004558014,0.001845359,0.0001537757,0.0008981828,0.001053062,0.0006272697,0.02680286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003430827,"about_ca_system_score_gemma":0.0007813609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005812217,"about_ca_topic_score_gemma":0.01045536,"domain_scores_codex":[0.9991844,0.00006513831,0.00004789303,0.0004217347,0.0002145187,0.00006629097],"domain_scores_gemma":[0.9991245,0.0001017957,0.00007833949,0.0001873771,0.0004473987,0.00006067536],"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":[0.0004634702,0.0002655279,0.03579327,0.0006257597,0.000149122,0.0001617462,0.0003250143,0.005309272,0.01278927,0.005389912,0.1127732,0.8259544],"study_design_scores_gemma":[0.0001501314,0.0006640942,0.1547028,0.000702203,0.000300415,0.001904729,0.0005963263,0.09385004,0.03328329,0.01365354,0.6999856,0.0002068337],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06275629,0.002907912,0.5805184,0.0006615008,0.001544526,0.001960431,0.09510051,0.029192,0.2253585],"genre_scores_gemma":[0.3570935,0.003295673,0.3234293,0.001417783,0.0003831015,0.002465865,0.112603,0.001603461,0.1977083],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02451156,"threshold_uncertainty_score":0.0819993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03177536590813239,"score_gpt":0.2534987770957262,"score_spread":0.2217234111875938,"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."}}