{"id":"W1489203962","doi":"","title":"Addressing Elderly Mobility Issues in Wisconsin","year":2011,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Gerontology; Quarter (Canadian coin); Social isolation; TRIPS architecture; Crash; Business; Medicine; Psychology; Environmental health; Geography; Engineering; Transport engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007740888,0.00005659145,0.00006857339,0.00006651229,0.0000136271,0.000007461532,0.00004231542,0.00003642986,0.0008286363],"category_scores_gemma":[0.00000682799,0.00005677326,0.00001548568,0.0001760382,0.00002516419,0.0001230404,0.000001770439,0.00007405543,0.00003011261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001396228,"about_ca_system_score_gemma":0.000008247547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002478702,"about_ca_topic_score_gemma":0.001709142,"domain_scores_codex":[0.9995995,0.000005549636,0.0001752366,0.00007758746,0.00004268932,0.00009948709],"domain_scores_gemma":[0.9998155,0.000008884252,0.00000608807,0.0001268952,0.00002126798,0.0000213618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006669774,0.001661095,0.4488297,0.0006569708,0.000173578,0.0000676067,0.05635169,0.01813963,0.04051219,0.2268386,0.009026594,0.1976756],"study_design_scores_gemma":[0.0004557465,0.00003084395,0.9581555,0.00003894047,0.000007128416,0.000001610218,0.001109856,0.004240449,0.02695018,0.004012265,0.004717071,0.000280374],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9368662,0.00006724946,0.007251693,0.0000565602,0.0001082291,0.000112075,0.000003762882,0.000351176,0.05518301],"genre_scores_gemma":[0.9942025,0.000006377592,0.005550547,0.00003608187,0.000007234639,0.00001349817,0.000005712549,0.000007057321,0.0001709785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5093258,"threshold_uncertainty_score":0.9072987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09566425498895637,"score_gpt":0.292183580531605,"score_spread":0.1965193255426486,"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."}}