{"id":"W4398308134","doi":"10.7910/dvn/pkjufn/jqy0ky","title":"FCC2003.018.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; Meteorology; Environmental science; Atmospheric sciences; Ran; Geology; Geography; Physics; Computer science; 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":[0.001383204,0.002363109,0.001696147,0.003531187,0.0007477091,0.002881858,0.003734166,0.002644517,0.1466216],"category_scores_gemma":[0.009005377,0.0008989247,0.001536481,0.006461448,0.0004893125,0.001401617,0.001921892,0.001627008,0.1536351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001768899,"about_ca_system_score_gemma":0.002240992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03554337,"about_ca_topic_score_gemma":0.04649314,"domain_scores_codex":[0.9990326,0.0002395837,0.0001051396,0.0002900707,0.0001687766,0.0001637986],"domain_scores_gemma":[0.9974595,0.0007777872,0.0002616741,0.0006487803,0.0005159614,0.0003363242],"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":[0.00004881548,0.000008738555,0.0003839604,0.0003194634,0.00002530737,0.00000760516,0.000007067202,0.0002003975,0.00002362659,0.0002790726,0.9977048,0.0009912153],"study_design_scores_gemma":[0.0006305285,0.00002714066,0.002957145,0.0004368253,0.00005341787,0.0000544215,0.00004628446,0.0009680775,0.0002290643,0.002205387,0.9923571,0.00003465296],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005221926,0.00006155005,0.00003408172,0.0000839205,0.00002174067,0.000004928068,0.9988807,0.0003181476,0.00054269],"genre_scores_gemma":[0.0004296394,0.00007249293,0.0001593703,0.0001174514,0.00001744108,0.0000459273,0.998386,0.0001096,0.0006619981],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8533784,"threshold_uncertainty_score":0.4904981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01974063151291724,"score_gpt":0.2747542936527088,"score_spread":0.2550136621397915,"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."}}