{"id":"W2781371487","doi":"10.1177/1539449217741136","title":"Constructing the 32-item Fitness-to-Drive Screening Measure","year":2017,"lang":"en","type":"article","venue":"OTJR Occupational Therapy Journal of Research","topic":"Physical Activity and Health","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Measure (data warehouse); Psychology; Computer science; Applied psychology; Data mining","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":[],"consensus_categories":[],"category_scores_codex":[0.003220582,0.00009580014,0.0002986263,0.0002029108,0.001222479,0.0001485502,0.0004611058,0.00006311584,0.0001414285],"category_scores_gemma":[0.001749557,0.00005767238,0.0001438469,0.0001928661,0.0003708185,0.0002182956,0.00007463899,0.001100545,0.00002088279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001179568,"about_ca_system_score_gemma":0.0006741937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006423853,"about_ca_topic_score_gemma":0.00001858324,"domain_scores_codex":[0.9972944,0.0002714181,0.000298566,0.0001400117,0.001665883,0.0003296942],"domain_scores_gemma":[0.9962712,0.001124001,0.0003102566,0.000348611,0.00166732,0.0002786284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008683908,0.0006019167,0.5045298,0.00006385527,0.0004349098,0.0001227064,0.00130847,0.0000438247,0.01215585,0.0102407,0.004161017,0.457653],"study_design_scores_gemma":[0.003567885,0.001899365,0.9705505,0.0008137195,0.0000187802,0.0004515065,0.00115288,0.0004877884,0.006373056,0.003803314,0.01073501,0.0001461849],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9723169,0.0002290055,0.001421262,0.02176216,0.0001331286,0.0003057357,0.000009882569,0.000006778122,0.003815204],"genre_scores_gemma":[0.9959709,0.0000900684,0.002011432,0.000319224,0.001352243,0.000005799963,0.000001644517,0.0000140557,0.0002345989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4660207,"threshold_uncertainty_score":0.9402444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4339373631427509,"score_gpt":0.5367446222395694,"score_spread":0.1028072590968185,"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."}}