{"id":"W4398271353","doi":"10.7910/dvn/pkjufn/j2ubjv","title":"FCC2003.035.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; Environmental science; Meteorology; Atmospheric sciences; Geomagnetic latitude; Remote sensing; Geology; Physics; Materials science; 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":[0.001394487,0.00238146,0.001697571,0.00356713,0.0007322273,0.002865135,0.003760752,0.002634772,0.1402317],"category_scores_gemma":[0.008894242,0.0008843396,0.001574388,0.006409844,0.0004910949,0.001410991,0.001920885,0.00162196,0.1541752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00175111,"about_ca_system_score_gemma":0.002213211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03490138,"about_ca_topic_score_gemma":0.0453941,"domain_scores_codex":[0.99901,0.0002453153,0.0001088163,0.0002922516,0.000174247,0.0001693602],"domain_scores_gemma":[0.9974999,0.0007396092,0.0002551771,0.0006506736,0.000523505,0.0003311657],"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":[0.0000481742,0.000008997469,0.0003845448,0.0003107154,0.00002554979,0.00000782,0.000006972864,0.0002098289,0.00002509352,0.0002755373,0.9976884,0.001008359],"study_design_scores_gemma":[0.0006135487,0.00002830531,0.003002669,0.0004309805,0.00005358715,0.00005749863,0.00004715526,0.001061954,0.0002471101,0.002256119,0.9921657,0.00003531577],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005491921,0.00006239677,0.0000363043,0.00008241543,0.00002261633,0.000005172392,0.9988556,0.0003355001,0.0005450425],"genre_scores_gemma":[0.0004188853,0.00006966975,0.0001588312,0.0001108517,0.00001687374,0.00004367408,0.9984474,0.0001058211,0.0006280734],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8597683,"threshold_uncertainty_score":0.4691219,"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."}}