{"id":"W6976968203","doi":"10.6084/m9.figshare.13185987.v1","title":"Additional file 1 of A study protocol for a predictive algorithm to assess population-based premature mortality risk: Premature Mortality Population Risk Tool (PreMPoRT)","year":2020,"lang":"en","type":"article","venue":"Figshare","topic":"Health Promotion and Cardiovascular Prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bruyère; Ottawa Hospital; University of Ottawa; Institute for Clinical Evaluative Sciences; Statistics Canada; Public Health Ontario; University of Toronto","funders":"","keywords":"Protocol (science); Population; Population health; Risk assessment; Risk factor; Community health; Data collection; Health data","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005271536,0.0009975981,0.00133348,0.001303601,0.001084786,0.001193656,0.001407556,0.0009289808,0.7867531],"category_scores_gemma":[0.04596997,0.0007362282,0.0009975734,0.002029172,0.0002699701,0.001043702,0.0007840153,0.001356603,0.1115493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001133773,"about_ca_system_score_gemma":0.002972652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0059388,"about_ca_topic_score_gemma":0.009394511,"domain_scores_codex":[0.99865,0.0005595567,0.0002834286,0.0002246941,0.0001796481,0.0001026249],"domain_scores_gemma":[0.9771716,0.0166027,0.001226193,0.001179791,0.003315618,0.0005041756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001373039,0.0003046902,0.002094784,0.002531307,0.00008018905,0.0000325103,0.0001166753,0.00037732,0.00004534438,0.0007465996,0.970782,0.02151561],"study_design_scores_gemma":[0.04223812,0.002477563,0.0448598,0.01257608,0.001047314,0.0007011262,0.0009459062,0.007222663,0.001184622,0.02487924,0.861539,0.0003285592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"protocol","genre_scores_codex":[0.0009969478,0.00009182676,0.00415153,0.0003757581,0.0001217105,0.01445703,0.9745515,0.0005920914,0.004661487],"genre_scores_gemma":[0.0321856,0.0005312838,0.0397463,0.00255597,0.0004163911,0.3544367,0.5345768,0.002023492,0.03352744],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.7867531,"threshold_uncertainty_score":0.3041708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0843848983633939,"score_gpt":0.3839648794203397,"score_spread":0.2995799810569458,"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."}}