{"id":"W2783437277","doi":"10.1145/3161179","title":"SafeDrive","year":2018,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Mitacs; National Science Foundation","keywords":"Gesture; Computer science; Wearable computer; Distracted driving; Artificial intelligence; Smartwatch; Real-time computing; Computer vision; Simulation; Human–computer interaction; Poison control; Embedded system","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":[0.000411583,0.001292405,0.0006382086,0.0008893696,0.0004101649,0.0009611016,0.001536331,0.0009177699,0.04698259],"category_scores_gemma":[0.002387592,0.0003639752,0.0006107789,0.0002588363,0.0002750952,0.001240244,0.001852067,0.000656502,0.0253303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002308943,"about_ca_system_score_gemma":0.0005508694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001473752,"about_ca_topic_score_gemma":0.00268951,"domain_scores_codex":[0.9994969,0.000049967,0.00003234004,0.0001472803,0.0002132882,0.00006024481],"domain_scores_gemma":[0.9992723,0.0001296911,0.00006607027,0.0001528848,0.0002686757,0.0001103815],"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":[0.001826293,0.0004667922,0.01585123,0.0008865677,0.0001525996,0.0005903334,0.00061061,0.00208999,0.02724645,0.002503247,0.1730132,0.7747627],"study_design_scores_gemma":[0.0004985043,0.002826062,0.04832566,0.0005807107,0.0003107618,0.006918702,0.0005969583,0.04565964,0.06679025,0.006808066,0.8202744,0.0004102674],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.199307,0.007665665,0.3753303,0.002406795,0.002173191,0.002205217,0.01981758,0.2045571,0.1865372],"genre_scores_gemma":[0.676874,0.003581118,0.122623,0.003604548,0.0004250154,0.001732388,0.02739136,0.008108624,0.15566],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04698259,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006253644753485771,"score_gpt":0.2204904017058824,"score_spread":0.2142367569523967,"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."}}