{"id":"W4398395116","doi":"10.7910/dvn/pkjufn/mjuaof","title":"FCC2001.131.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; Climatology; Geology; Geography; 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":[0.001228818,0.002483315,0.0016615,0.0033326,0.0007678987,0.003107665,0.003563767,0.002629573,0.1586279],"category_scores_gemma":[0.00669204,0.0009356332,0.001442392,0.006101196,0.0004860777,0.001444691,0.001919429,0.001594871,0.1936021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001761438,"about_ca_system_score_gemma":0.002014403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03355018,"about_ca_topic_score_gemma":0.04658795,"domain_scores_codex":[0.9991077,0.0002061784,0.00009973939,0.0002638951,0.0001610599,0.000161474],"domain_scores_gemma":[0.9980258,0.0005469644,0.000184385,0.000525185,0.0004450234,0.0002725578],"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":[0.00004215638,0.000009856888,0.0002528052,0.0002821548,0.00001857672,0.000007204387,0.000006912459,0.0001842403,0.00003167991,0.000286597,0.9979689,0.0009089395],"study_design_scores_gemma":[0.0005352777,0.00002651181,0.002129913,0.0003342818,0.00003480198,0.00004638098,0.00004075918,0.0008430699,0.0002575217,0.001738764,0.9939839,0.0000288785],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004674482,0.0000490917,0.00003293724,0.00006438228,0.00002104466,0.00000481204,0.9986553,0.0003805468,0.0007450865],"genre_scores_gemma":[0.0003159403,0.00005071839,0.000129452,0.00008150119,0.00001065106,0.00003068386,0.9986385,0.0001135797,0.0006290604],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8413721,"threshold_uncertainty_score":0.5306633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02001585367733536,"score_gpt":0.2764444766597631,"score_spread":0.2564286229824277,"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."}}