{"id":"W4303684372","doi":"10.1186/s12961-022-00902-6","title":"A framework for considering the utility of models when facing tough decisions in public health: a guideline for policy-makers","year":2022,"lang":"en","type":"letter","venue":"Health Research Policy and Systems","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Impact","funders":"Australian Research Council","keywords":"Public health; Deliberation; Pace; Health policy; Pandemic; Process (computing); Health administration; Health services research; Public relations; Public policy; Political science; Management science; Business; Infectious disease (medical specialty); Medicine; Coronavirus disease 2019 (COVID-19); Disease; Economics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","research_integrity"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.09273076,0.0005206923,0.001997833,0.003202198,0.006595772,0.0001587631,0.001331941,0.0009486651,0.00009555515],"category_scores_gemma":[0.09897036,0.000422918,0.0002269511,0.002752955,0.0006785866,0.0003273755,0.000929956,0.006875059,0.00000694322],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.005166467,"about_ca_system_score_gemma":0.07131834,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1664817,"about_ca_topic_score_gemma":0.006182909,"domain_scores_codex":[0.961029,0.02070929,0.007053623,0.001400071,0.003072023,0.00673601],"domain_scores_gemma":[0.8659161,0.1247602,0.003121749,0.002140129,0.002488733,0.001573012],"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":[0.00007464367,0.00002302868,0.00006277566,0.006940725,0.00002719098,0.000002065224,0.03715998,0.00003859187,4.691995e-7,0.05498555,0.8974141,0.003270919],"study_design_scores_gemma":[0.001188437,0.0004406715,0.00003159893,0.001478212,0.00000261796,0.00001003049,0.01528517,0.01264365,1.28949e-7,0.07844107,0.8902595,0.0002188831],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0001132054,0.001261282,0.04773984,0.9207119,0.0007088606,0.02188671,0.006931197,0.00006622037,0.0005807654],"genre_scores_gemma":[0.01283688,0.001654591,0.008815994,0.9495759,0.00616076,0.01927996,0.0003381372,0.0001549594,0.001182836],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1602988,"threshold_uncertainty_score":0.9998223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9577754020375087,"score_gpt":0.7517697861122502,"score_spread":0.2060056159252585,"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."}}