{"id":"W4398262787","doi":"10.7910/dvn/pkjufn/ai46cm","title":"FCC2003.325.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":"Range (aeronautics); Earth's magnetic field; Environmental science; Atmospheric sciences; Meteorology; Geomagnetic latitude; 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":[0.001394136,0.002431462,0.001656631,0.003606817,0.0007347581,0.002946584,0.00380132,0.00261359,0.1444055],"category_scores_gemma":[0.00793242,0.000913865,0.001521974,0.006587515,0.0005078904,0.001435311,0.001893192,0.001611378,0.1700865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001759128,"about_ca_system_score_gemma":0.002091002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03358289,"about_ca_topic_score_gemma":0.04317844,"domain_scores_codex":[0.9990257,0.0002376523,0.0001093294,0.0002848267,0.0001735613,0.0001689699],"domain_scores_gemma":[0.9976943,0.0006384253,0.0002339874,0.000624455,0.0004879235,0.000320968],"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":[0.00004536046,0.000009271709,0.0003134254,0.0002772321,0.00002182145,0.000007246124,0.000006626349,0.0002058568,0.00002621109,0.0002690928,0.9978595,0.0009582638],"study_design_scores_gemma":[0.0005466644,0.00002833634,0.002612797,0.0003606171,0.00004234025,0.00005249727,0.00004294082,0.001042083,0.0002466062,0.001917613,0.9930751,0.00003229196],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005604485,0.00005645792,0.00003696282,0.00007515289,0.0000227228,0.000005217594,0.9987143,0.000376549,0.0006566751],"genre_scores_gemma":[0.0003744586,0.00005657444,0.0001385028,0.00009003023,0.00001347521,0.00003626777,0.9985722,0.000101654,0.0006167074],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8555945,"threshold_uncertainty_score":0.4830846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0197430599522316,"score_gpt":0.2749926882248495,"score_spread":0.2552496282726179,"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."}}