{"id":"W4398681920","doi":"10.7910/dvn/pkjufn/a07pra","title":"FCC2003.084.ran","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Cardiovascular Health and Disease Prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Range (aeronautics); Earth's magnetic field; Ran; Environmental science; Meteorology; Atmospheric sciences; Physics; Computer science; Aerospace engineering; Engineering; Magnetic field","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001434201,0.0023837,0.001698377,0.003603214,0.0007430968,0.002904177,0.003772416,0.002654395,0.1413997],"category_scores_gemma":[0.00914417,0.0008868559,0.001580465,0.006506966,0.0004990448,0.001414236,0.001929459,0.001631005,0.1576445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001756909,"about_ca_system_score_gemma":0.002267154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03526122,"about_ca_topic_score_gemma":0.04581523,"domain_scores_codex":[0.9989964,0.0002488946,0.000108409,0.0002970547,0.0001774811,0.0001718394],"domain_scores_gemma":[0.9974355,0.0007608287,0.0002619954,0.0006683216,0.0005320986,0.0003413191],"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":[0.00004803595,0.000008987886,0.0003863904,0.0003037567,0.00002540052,0.000007591763,0.00000690768,0.0002010014,0.00002481417,0.0002671015,0.997727,0.0009930208],"study_design_scores_gemma":[0.0006234266,0.00002855087,0.003065412,0.00043704,0.00005431568,0.00005664249,0.00004797475,0.001015742,0.0002422684,0.002189892,0.992203,0.00003568794],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005461052,0.00006199731,0.00003451299,0.00008324847,0.00002254096,0.000005092293,0.9988742,0.0003238498,0.0005399337],"genre_scores_gemma":[0.0004081266,0.00006908377,0.000153343,0.0001097812,0.00001694893,0.00004427019,0.9984525,0.0001039307,0.0006419456],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8586003,"threshold_uncertainty_score":0.4730292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973706749555086,"score_gpt":0.2748691842451595,"score_spread":0.2551321167496087,"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."}}