{"id":"W4391456190","doi":"10.2196/52726","title":"Barriers to Postdischarge Smartphone App Use Among Patients With Traumatic Rib Fractures","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Trauma Management and Diagnosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Smartphone application; Health care; Medical emergency; Tracking (education); Physical therapy; Computer science; Psychology; Multimedia","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":[0.006401655,0.0002119674,0.0004942724,0.0006035285,0.001767613,0.0025042,0.0009694632,0.0008714354,0.00424477],"category_scores_gemma":[0.06899222,0.0002905545,0.0007383525,0.0008420323,0.0007821815,0.001953773,0.002597436,0.001960634,0.0003015823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00127561,"about_ca_system_score_gemma":0.004565594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01015441,"about_ca_topic_score_gemma":0.01406502,"domain_scores_codex":[0.9923328,0.003322275,0.001337404,0.0004245433,0.001443547,0.00113934],"domain_scores_gemma":[0.968317,0.02013004,0.005682,0.0008554959,0.002869109,0.002146342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002422087,0.0009465125,0.8194905,0.001100303,0.0001756934,0.0009263332,0.07013304,0.0001794683,0.0003855931,0.001068787,0.00648619,0.09886535],"study_design_scores_gemma":[0.00006122248,0.001138748,0.7544397,0.003436271,0.0002749282,0.002344021,0.2186556,0.001655215,0.0004630952,0.001451632,0.01593711,0.0001424383],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989242,0.0008892069,0.0004903596,0.005662227,0.0000725655,0.0001548968,0.0002167377,0.00001598896,0.003256072],"genre_scores_gemma":[0.9972003,0.000667101,0.0005795736,0.001081413,0.00002139057,0.0001232463,0.00006564367,0.000006179966,0.0002551364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01015441,"threshold_uncertainty_score":0.03385562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03725758847620294,"score_gpt":0.3751872431367179,"score_spread":0.3379296546605149,"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."}}