{"id":"W2919599595","doi":"10.2196/11449","title":"A National Assessment of Access to Technology Among Nursing Home Residents: A Secondary Analysis","year":2019,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agency for Healthcare Research and Quality","keywords":"Nursing homes; Nursing; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001452512,0.0001494863,0.0005668192,0.00182644,0.0002654315,0.00001806739,0.0004491326,0.0002234103,0.0009147229],"category_scores_gemma":[0.00008082206,0.0001491798,0.00009757068,0.002650737,0.00003788847,0.0003036702,0.0001752286,0.0008727502,0.0001066267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001504544,"about_ca_system_score_gemma":0.002075121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007875276,"about_ca_topic_score_gemma":0.0006917318,"domain_scores_codex":[0.9970229,0.0003930198,0.0008866022,0.0004314629,0.0005481231,0.0007179147],"domain_scores_gemma":[0.9981536,0.000358165,0.0005040202,0.0004453566,0.000400382,0.0001384678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009738547,0.00004581108,0.9919778,0.0004648099,0.0001479603,0.000001572817,0.001032715,0.0001476786,0.0003756017,0.001740493,0.002359292,0.001696529],"study_design_scores_gemma":[0.0005644358,0.00006616008,0.9923062,0.001136772,0.00004560081,0.000001155904,0.001325862,0.002415871,0.00003202058,0.001018847,0.0009309478,0.000156116],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9643195,0.00009052693,0.001764638,0.002984128,0.0005061516,0.001935135,0.00001504392,0.0001336666,0.02825125],"genre_scores_gemma":[0.9965717,0.000004619427,0.0006677447,0.0005578427,0.0001301899,0.000531276,0.0000177899,0.00002815286,0.001490653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03225227,"threshold_uncertainty_score":0.9999986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04562137383340995,"score_gpt":0.5069907752125035,"score_spread":0.4613694013790935,"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."}}