{"id":"W4398464888","doi":"10.7910/dvn/pkjufn/411fqa","title":"FCC2003.116.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; 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":[0.001346752,0.002519404,0.001693637,0.003513747,0.0007801381,0.003192984,0.003817059,0.002773406,0.1429415],"category_scores_gemma":[0.007607258,0.0009205433,0.001535441,0.006933029,0.000501845,0.001521629,0.001902089,0.00167028,0.1773308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001852159,"about_ca_system_score_gemma":0.002168228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03608456,"about_ca_topic_score_gemma":0.05011812,"domain_scores_codex":[0.9990086,0.0002325898,0.0001161504,0.0002852192,0.0001814962,0.0001760207],"domain_scores_gemma":[0.9978173,0.0005929589,0.0002114066,0.0005852917,0.0004975153,0.0002955349],"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":[0.00004398375,0.000009594146,0.000273264,0.000295652,0.00002046144,0.000007779935,0.000007020493,0.0001935076,0.00002916031,0.0002880078,0.997931,0.0009005474],"study_design_scores_gemma":[0.0005126633,0.00002635497,0.002260687,0.000355727,0.0000382533,0.00005014338,0.00004125626,0.0008812257,0.0002393307,0.001748437,0.9938158,0.00003019161],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000050931,0.0000577207,0.00003444301,0.0000705119,0.00002302953,0.000005146802,0.9986436,0.0003834699,0.0007311595],"genre_scores_gemma":[0.0003137238,0.0000548893,0.0001333423,0.00008248697,0.0000111898,0.00003158123,0.9986896,0.0001033528,0.0005799116],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8570585,"threshold_uncertainty_score":0.4781871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01967098372359358,"score_gpt":0.2747291653885429,"score_spread":0.2550581816649493,"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."}}