{"id":"W4398465859","doi":"10.7910/dvn/pkjufn/e7c2sw","title":"FCC2001.325.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":"Earth's magnetic field; Range (aeronautics); Meteorology; Environmental science; Atmospheric sciences; Remote sensing; Physics; Geology; 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":[0.001355327,0.002360683,0.001638407,0.003641107,0.0007227606,0.002873006,0.003695047,0.002573694,0.144866],"category_scores_gemma":[0.007983832,0.0008970462,0.001454519,0.006601954,0.000491664,0.001410878,0.001848371,0.001583347,0.1646842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001772552,"about_ca_system_score_gemma":0.00207485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03376674,"about_ca_topic_score_gemma":0.04375417,"domain_scores_codex":[0.9990435,0.000235709,0.0001058694,0.0002800898,0.0001704572,0.0001644052],"domain_scores_gemma":[0.9976751,0.0006708029,0.0002407041,0.0006056571,0.000488618,0.0003191013],"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":[0.00004467141,0.000008993643,0.0003208459,0.0002840607,0.00002132271,0.00000708228,0.000006549164,0.0002048567,0.00002479192,0.0002749939,0.9978198,0.0009821508],"study_design_scores_gemma":[0.00053248,0.00002756261,0.002698227,0.0003804903,0.0000423443,0.00005137919,0.00004208776,0.001005538,0.000235022,0.001916512,0.9930366,0.00003172034],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005507623,0.00005882801,0.00003590666,0.00007678826,0.00002186792,0.000005039848,0.9987219,0.00035236,0.0006721596],"genre_scores_gemma":[0.0003871229,0.00006070443,0.000137851,0.00009246721,0.00001369911,0.00003690649,0.998538,0.00009859111,0.0006347202],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.855134,"threshold_uncertainty_score":0.4846251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01976153797269264,"score_gpt":0.2759116896298448,"score_spread":0.2561501516571522,"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."}}