{"id":"W4312979111","doi":"10.2196/34387","title":"Architecture Assessment of the Chilean Epidemiological Surveillance System for Notifiable Diseases (EPIVIGILA): Qualitative Study","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Architecture; Software deployment; Information system; Computer science; Pandemic; Epidemiology; Medicine; Data science; Business; Environmental health; Disease; Coronavirus disease 2019 (COVID-19); Political science; Geography; Infectious disease (medical specialty)","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":[0.04211065,0.0002929544,0.0006774692,0.003494233,0.002214763,0.003982048,0.001057634,0.0006971555,0.001674562],"category_scores_gemma":[0.05813561,0.0003806471,0.0005188358,0.003307821,0.003050157,0.004114591,0.00309553,0.0008728415,0.00008248261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01308644,"about_ca_system_score_gemma":0.01889343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01837628,"about_ca_topic_score_gemma":0.01908153,"domain_scores_codex":[0.9786606,0.01584782,0.001701835,0.0007860762,0.002139965,0.0008637023],"domain_scores_gemma":[0.931408,0.05306864,0.005329349,0.0008304972,0.007792152,0.001571371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001183235,0.00007294238,0.0617642,0.01094864,0.0001140988,0.0009907847,0.876938,0.0001834635,0.0009548584,0.006116031,0.001711457,0.04008731],"study_design_scores_gemma":[0.00001663757,0.0001307918,0.02496167,0.005730156,0.0001023897,0.0002942827,0.9424535,0.0003124814,0.0003852392,0.0006790117,0.02490288,0.00003106524],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675166,0.007749191,0.003618455,0.005772588,0.00005899848,0.001168021,0.0007452889,0.00002262572,0.01334814],"genre_scores_gemma":[0.9927268,0.002975916,0.002423886,0.000461971,0.000009722122,0.000543186,0.0001586978,0.00001027491,0.0006895451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04211065,"threshold_uncertainty_score":0.2227051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0766638175276662,"score_gpt":0.4775288154947652,"score_spread":0.400864997967099,"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."}}