{"id":"W2515212949","doi":"10.5430/jha.v5n6p14","title":"Idaho rural physician technology usage over time","year":2016,"lang":"en","type":"article","venue":"Journal of Hospital Administration","topic":"Radiology practices and education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"The Internet; Medicine; Workforce; Health information technology; Family medicine; Rural area; Health care; Rural health; Economic growth; World Wide Web","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":[],"consensus_categories":[],"category_scores_codex":[0.0001659843,0.00007729297,0.0001760459,0.0001136852,0.00003595103,0.0000125559,0.00006359307,0.00009831355,0.0001505358],"category_scores_gemma":[0.0001751375,0.00004726807,0.00007843139,0.000106015,0.00009163577,0.0004433738,0.000006754329,0.0001330237,0.00009589997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007127035,"about_ca_system_score_gemma":0.0001838604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.542365e-7,"about_ca_topic_score_gemma":3.190912e-7,"domain_scores_codex":[0.9993502,0.00001959423,0.0002919738,0.00007135175,0.0001484187,0.0001184064],"domain_scores_gemma":[0.99919,0.0000460676,0.0004234256,0.0001124308,0.0001557233,0.00007240636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002063459,0.004132445,0.3313181,0.00005959821,0.000611335,0.0004791548,0.0007631821,0.000001233378,0.4929822,0.003851533,0.05153237,0.1122054],"study_design_scores_gemma":[0.006091071,0.0690854,0.8105966,0.0006441323,0.0006231758,0.003101635,0.001680434,0.00005447293,0.0703146,0.006293482,0.03098533,0.0005295974],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725357,0.00009301791,0.000153155,0.02535096,0.0004860909,0.00008099712,0.000001586405,0.00001315489,0.001285323],"genre_scores_gemma":[0.9974715,0.00005403941,0.0005343193,0.00018603,0.0007347152,0.000001618697,0.00000269568,0.000007867024,0.001007253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4792786,"threshold_uncertainty_score":0.1927536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006294448159442223,"score_gpt":0.2852904857235878,"score_spread":0.2789960375641456,"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."}}