{"id":"W2605428776","doi":"10.1145/3054977.3054979","title":"SafeWatch","year":2017,"lang":"en","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Science Foundation","keywords":"Smartwatch; Alertness; Computer science; Distraction; Heading (navigation); Real-time computing; Human–computer interaction; Artificial intelligence; Simulation; Wearable computer; Embedded system; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004826804,0.001928802,0.0008549755,0.001262949,0.0003714532,0.001063938,0.001702329,0.001171802,0.05669709],"category_scores_gemma":[0.002171324,0.0005742944,0.0006257092,0.0005884274,0.0002788353,0.001777632,0.00196753,0.0008321623,0.04788667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000233956,"about_ca_system_score_gemma":0.0005847778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002234005,"about_ca_topic_score_gemma":0.003863097,"domain_scores_codex":[0.99958,0.0000390497,0.00002904884,0.0001555016,0.0001489776,0.00004749804],"domain_scores_gemma":[0.9990877,0.0002248112,0.00006673427,0.00021872,0.0003068845,0.00009518733],"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":[0.003004669,0.0003140676,0.01136391,0.001275663,0.0002234576,0.0007927738,0.0004920854,0.001803799,0.0228597,0.002141694,0.4241708,0.5315574],"study_design_scores_gemma":[0.0005017821,0.001756496,0.04612656,0.0005215885,0.0002785854,0.003467322,0.0004116267,0.04136027,0.07379156,0.009321084,0.8219991,0.0004640259],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"software","genre_gemma":"other","genre_scores_codex":[0.06697895,0.005659389,0.1799542,0.0009941771,0.00194322,0.002291087,0.06896413,0.5817533,0.09146153],"genre_scores_gemma":[0.4485238,0.003307517,0.1405688,0.003199102,0.0006100687,0.002880838,0.1774152,0.02183302,0.2016617],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05669709,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006936083519687994,"score_gpt":0.204323043548108,"score_spread":0.19738696002842,"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."}}