{"id":"W2110492869","doi":"10.2196/medinform.4286","title":"Optimizing Patient Preparation and Surgical Experience Using eHealth Technology","year":2015,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Patient-Provider Communication in Healthcare","field":"Health Professions","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Cancer Council NSW; National Health and Medical Research Council; Medical Research Council; Hunter Medical Research Institute","keywords":"eHealth; Health care; Medicine; Nursing","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":[0.002626399,0.000377142,0.0002900873,0.0006175319,0.0004666416,0.001658259,0.0005937424,0.0005188801,0.004099491],"category_scores_gemma":[0.0121981,0.000129217,0.0005553709,0.0003340289,0.0003386672,0.001420039,0.00156442,0.0005867215,0.0008983322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003718279,"about_ca_system_score_gemma":0.0009718904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004583605,"about_ca_topic_score_gemma":0.0009138571,"domain_scores_codex":[0.9985238,0.0008127347,0.0001202794,0.0001121515,0.0002754247,0.0001557061],"domain_scores_gemma":[0.9976394,0.0015057,0.0002791578,0.0001457577,0.0001899314,0.0002400341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000474367,0.002017041,0.0378349,0.00105487,0.00009313957,0.0005758163,0.003715622,0.003555354,0.01143694,0.001826824,0.008974156,0.928441],"study_design_scores_gemma":[0.001670792,0.01915656,0.5214912,0.005504101,0.0008955734,0.007225644,0.02480824,0.04386836,0.08579827,0.019698,0.2689339,0.0009493278],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7839021,0.005898362,0.1405766,0.009956989,0.0005177887,0.00174824,0.0006518343,0.002184993,0.05456315],"genre_scores_gemma":[0.8779101,0.004239196,0.1109365,0.001086174,0.000280839,0.000833246,0.0003408236,0.0001045353,0.004268635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004099491,"threshold_uncertainty_score":0.01388991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2122833175363009,"score_gpt":0.4849637380804074,"score_spread":0.2726804205441065,"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."}}