{"id":"W2946334032","doi":"10.1159/000499067","title":"Effects of Age on Obstacle Avoidance while Walking and Deciphering Text versus Audio Phone Messages","year":2019,"lang":"en","type":"article","venue":"Gerontology","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre for Interdisciplinary Research in Rehabilitation; Jewish Rehabilitation Hospital; Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; McGill University; Centre Intégré de Santé et de Services Sociaux des Laurentides","funders":"","keywords":"Phone; Obstacle; Phone call; Psychology; Audiology; Physical medicine and rehabilitation; Computer science; Medicine; History; Linguistics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001231209,0.0001263923,0.0002862581,0.00007242114,0.00005503521,0.00001048568,0.0001075784,0.0001275713,0.003480328],"category_scores_gemma":[0.00006844891,0.0001255115,0.00004798823,0.00005839418,0.000062885,0.00007270906,0.00003455566,0.000169473,0.0008630175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004384346,"about_ca_system_score_gemma":0.000008382806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006714108,"about_ca_topic_score_gemma":0.0001340818,"domain_scores_codex":[0.9989934,0.0001604404,0.0002365304,0.0002837613,0.00008979923,0.0002360617],"domain_scores_gemma":[0.9987856,0.0007368475,0.0001438852,0.0002576331,0.00002776608,0.00004827333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.009920528,0.001585577,0.02508884,0.001163712,0.001742436,0.0005831383,0.09415215,0.0002783627,0.1692416,0.1155563,0.04031039,0.540377],"study_design_scores_gemma":[0.01052798,0.001119942,0.905991,0.0001858311,0.00006048189,0.00006751458,0.00227615,0.0002052297,0.01076679,0.0002623888,0.06802118,0.0005155429],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9182498,0.0004898211,0.0002626595,0.0001135533,0.002891534,0.0001875688,0.000001923787,0.00007004353,0.07773306],"genre_scores_gemma":[0.9945202,0.00001608377,0.0001933048,0.0001722912,0.00005689734,0.00002870794,0.000003069975,0.00001549699,0.004993989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8809021,"threshold_uncertainty_score":0.9999149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02936604808245435,"score_gpt":0.3305323884759204,"score_spread":0.3011663403934661,"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."}}