{"id":"W4327772883","doi":"10.1109/ickecs56523.2022.10060220","title":"Based on Python Technology for Public Health and Economic Indicators","year":2022,"lang":"en","type":"article","venue":"","topic":"Global Health Care Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Public health; Python (programming language); Economic indicator; Computer science; Public economics; Economics; Medicine; Macroeconomics; Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003125542,0.001576608,0.001066458,0.002254794,0.0005747985,0.003322493,0.00213942,0.000773183,0.05711446],"category_scores_gemma":[0.01441412,0.0008145164,0.001790786,0.002471968,0.0008558359,0.004538218,0.002929541,0.002744817,0.02283606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000891613,"about_ca_system_score_gemma":0.002161487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002368765,"about_ca_topic_score_gemma":0.00117803,"domain_scores_codex":[0.997809,0.0006025605,0.0003574074,0.0003940805,0.0005864688,0.0002505627],"domain_scores_gemma":[0.9947443,0.002446745,0.000475985,0.001063707,0.000993334,0.0002758484],"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":[0.001667705,0.0005213931,0.01082565,0.002450705,0.0003010118,0.000951926,0.001451888,0.01637146,0.01048168,0.1366189,0.4583803,0.3599774],"study_design_scores_gemma":[0.0005737852,0.0002090412,0.009612205,0.0006033388,0.000195576,0.0007117877,0.0002449923,0.1531375,0.03094398,0.1277458,0.675723,0.0002990057],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00442487,0.0002316785,0.6283688,0.0008741845,0.0004482948,0.0006662717,0.01961643,0.3253313,0.02003812],"genre_scores_gemma":[0.1449021,0.001086313,0.679031,0.002025555,0.0005434169,0.006789454,0.05250038,0.07740435,0.03571745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05711446,"threshold_uncertainty_score":0.1910669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07878702387424606,"score_gpt":0.449308894766813,"score_spread":0.3705218708925669,"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."}}