{"id":"W3193997552","doi":"10.5383/jttm.03.02.004","title":"A Posture Recognition System to Track Drivers’ Activities While Driving","year":2021,"lang":"en","type":"article","venue":"International Journal of Traffic and Transportation Management","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Qatar National Research Fund; Fonds National de la Recherche Luxembourg; Qatar Foundation","keywords":"Computer science; Virtual reality; Track (disk drive); Simulation; Human–computer interaction; Driving simulator; Test (biology); Warning system; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002203776,0.0004911445,0.0003211982,0.0006359299,0.0001892394,0.0002519541,0.0004293212,0.0005280999,0.002053304],"category_scores_gemma":[0.0004337305,0.0002210559,0.000250823,0.0002323359,0.00008841878,0.0003458472,0.0003044635,0.0003084501,0.001244472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000178281,"about_ca_system_score_gemma":0.0002653803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00159243,"about_ca_topic_score_gemma":0.001936076,"domain_scores_codex":[0.9998248,0.00001812444,0.00001332808,0.00006176718,0.0000590219,0.00002292478],"domain_scores_gemma":[0.9997411,0.00003517174,0.00003406827,0.00002352723,0.0001359426,0.00003013958],"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":[0.0005988441,0.0006309938,0.01134586,0.0002070478,0.00008728654,0.00025532,0.0001738551,0.002080423,0.4764003,0.0004056637,0.004660842,0.5031536],"study_design_scores_gemma":[0.0004024622,0.005252222,0.2343313,0.000116926,0.0006600244,0.005236355,0.0003069741,0.371893,0.358712,0.001105082,0.02165027,0.0003333453],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3841385,0.001383976,0.5923997,0.0002974116,0.0006415586,0.0005694411,0.001007321,0.01068986,0.008872293],"genre_scores_gemma":[0.8671507,0.0003857531,0.125137,0.0003263031,0.0001233343,0.0003372925,0.0007238701,0.00006686871,0.005748836],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002053304,"threshold_uncertainty_score":0.006868958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01683272605470387,"score_gpt":0.2981257234579994,"score_spread":0.2812929974032956,"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."}}