{"id":"W2918957947","doi":"10.2196/10967","title":"Augmented Reality in Medicine: Systematic and Bibliographic Review","year":2019,"lang":"en","type":"review","venue":"JMIR mhealth and uhealth","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":334,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Augmented reality; MEDLINE; Computer science; Medicine; Human–computer interaction; Political science","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.008476643,0.001754558,0.006146691,0.03287476,0.001274802,0.003584055,0.002257688,0.002111338,0.01106312],"category_scores_gemma":[0.05227442,0.0009622515,0.005752564,0.03267135,0.001220869,0.003349723,0.002497493,0.001370554,0.001072172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004327597,"about_ca_system_score_gemma":0.01890295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007359372,"about_ca_topic_score_gemma":0.0188296,"domain_scores_codex":[0.9874064,0.003111326,0.005128354,0.0008864167,0.003108174,0.000359325],"domain_scores_gemma":[0.9465743,0.03751632,0.008602102,0.001113704,0.005783263,0.0004102878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00007095138,0.00001669235,0.0008638751,0.9499779,0.002353482,0.0001720539,0.0003173358,0.00006871762,0.0001209667,0.0003614631,0.003487497,0.04218899],"study_design_scores_gemma":[0.0000487298,0.00006342946,0.002678206,0.949466,0.01638236,0.0004470135,0.0003350334,0.00005136463,0.0001378948,0.0003172244,0.03004429,0.0000284149],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008744635,0.9959092,0.0003071521,0.0003606619,0.0001765485,0.0004159852,0.001135245,0.00001900385,0.0008017406],"genre_scores_gemma":[0.008573274,0.9883112,0.0008908896,0.0004605654,0.0001387268,0.0007867913,0.0006335215,0.00001114495,0.0001937959],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9671252,"threshold_uncertainty_score":0.04482931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1934074404119424,"score_gpt":0.4725285687368745,"score_spread":0.2791211283249322,"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."}}