{"id":"W2593272613","doi":"","title":"INTELLIGENT HOME RISK-BASED MONITORING SOLUTIONS FOR POST ARTHROPLASTY SURVEILLANCE","year":2018,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health care; Medicaid; Autonomy; Business; Healthcare delivery; Social security; Economics; Economic growth; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009292039,0.0008824961,0.0006433761,0.001052494,0.0003177835,0.001330125,0.001331429,0.0007495189,0.004734394],"category_scores_gemma":[0.003562303,0.0002400651,0.000529848,0.0004202967,0.0001867879,0.00140153,0.001537802,0.000628185,0.00206487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004371014,"about_ca_system_score_gemma":0.0004591579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00163844,"about_ca_topic_score_gemma":0.002338344,"domain_scores_codex":[0.9991696,0.0001394045,0.00007636665,0.0001171841,0.0004313657,0.00006611775],"domain_scores_gemma":[0.9987078,0.0003287995,0.0002286559,0.0001441374,0.0005050522,0.0000856016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005930492,0.0003510088,0.0193246,0.0005362443,0.0001215179,0.0008834169,0.0005622397,0.01362118,0.01619554,0.004464726,0.04137733,0.9019693],"study_design_scores_gemma":[0.000211211,0.001582535,0.05645654,0.001160227,0.0005501184,0.004694415,0.002207461,0.6117627,0.05347868,0.03933359,0.2282365,0.0003259853],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1066341,0.01586055,0.797477,0.005723655,0.001134964,0.001073681,0.002712542,0.02760593,0.04177762],"genre_scores_gemma":[0.7892518,0.005886829,0.1841022,0.001306538,0.0003525225,0.0004839352,0.002213776,0.0003084266,0.01609392],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004734394,"threshold_uncertainty_score":0.01583815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05278980774300912,"score_gpt":0.2682101410116644,"score_spread":0.2154203332686553,"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."}}