{"id":"W3001077026","doi":"10.1503/cmaj.1095841","title":"How hospitals can protect themselves from cyber attack","year":2020,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Information and Cyber Security","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Stephen's University","funders":"","keywords":"Ransom; Hacker; Computer security; Computer science; Health care; Internet privacy; Medical emergency; Medicine; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005774998,0.0001116864,0.0001624459,0.00006465527,0.0002748226,0.0008177483,0.0007849355,0.0002237916,0.0005721885],"category_scores_gemma":[0.001228858,0.00009877888,0.00009190507,0.0002834196,0.00001951074,0.0006491999,0.00004493316,0.0007696472,0.0001940806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003987406,"about_ca_system_score_gemma":0.001843176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00139432,"about_ca_topic_score_gemma":0.01104461,"domain_scores_codex":[0.9978148,0.000132247,0.000276871,0.000153722,0.001229078,0.0003933012],"domain_scores_gemma":[0.9973788,0.00006744447,0.0002254169,0.0001245817,0.0002713099,0.001932402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003974173,0.00002425348,0.02004415,0.00001094928,0.0002269684,0.0004456629,0.02361988,0.00001089687,0.00001772564,0.01468348,0.8230783,0.1178337],"study_design_scores_gemma":[0.0008125369,0.00006457567,0.02015507,0.00003058213,0.000008221542,0.00005268002,0.0006977468,0.01019004,0.0001354046,0.001137938,0.9663889,0.0003262689],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.07557607,0.0001895437,0.0174865,0.8989379,0.001425278,0.0002375432,0.00006155596,0.0001203951,0.00596521],"genre_scores_gemma":[0.9189979,0.00003584337,0.001456763,0.07689287,0.002307434,0.000007684528,0.00001017803,0.000009601427,0.0002817432],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8434218,"threshold_uncertainty_score":0.7885565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01039226897917829,"score_gpt":0.2076560190821838,"score_spread":0.1972637501030055,"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."}}