{"id":"W3004024954","doi":"10.2196/15860","title":"The Surveillance Outbreak Response Management and Analysis System (SORMAS): Digital Health Global Goods Maturity Assessment","year":2020,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"FP7 International Cooperation; Deutsche Gesellschaft für Internationale Zusammenarbeit; European Commission","keywords":"Outbreak; Digital health; Environmental health; Business; Maturity (psychological); Risk analysis (engineering); Public health; Medicine; Health care; Virology; Political science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.008416154,0.0004544581,0.001182503,0.0001496344,0.00438732,0.0002530557,0.0004554876,0.0002246779,0.00001612692],"category_scores_gemma":[0.0003598706,0.0003528984,0.0001347726,0.00214355,0.0002156715,0.0002492453,0.0004259793,0.0008896787,0.00004354186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001112675,"about_ca_system_score_gemma":0.003536165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000357869,"about_ca_topic_score_gemma":0.0008941053,"domain_scores_codex":[0.9899436,0.003776172,0.002065618,0.001121285,0.0007377033,0.002355637],"domain_scores_gemma":[0.9917923,0.001555281,0.001123061,0.0009242104,0.0002432691,0.004361888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005696632,0.00007664798,0.8548717,0.003593998,0.0001685517,0.000004612745,0.0007751675,0.000002272006,8.586701e-8,0.02609141,0.02299319,0.09085272],"study_design_scores_gemma":[0.0008869868,0.0001945435,0.5298485,0.00002488463,0.000002358543,0.000004955927,0.00245742,0.001379219,2.472826e-9,0.00003673679,0.4649965,0.0001678712],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1339371,0.01901356,0.01479884,0.7918266,0.001168795,0.02052055,0.003413077,0.001603536,0.01371797],"genre_scores_gemma":[0.9650669,0.00577818,0.0005814816,0.02324179,0.0002593983,0.004349641,0.0003610226,0.0000388763,0.0003227694],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8311298,"threshold_uncertainty_score":0.9998923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0358022618917344,"score_gpt":0.3943146470859132,"score_spread":0.3585123851941788,"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."}}