{"id":"W4398283525","doi":"10.7910/dvn/pkjufn/slbqpj","title":"FCC2002.084.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; Ran; Meteorology; Environmental science; Atmospheric sciences; Remote sensing; Geology; Geography; Physics; Computer science; Magnetic field; Aerospace engineering; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002152913,0.0003190919,0.0006857648,0.0001002238,0.00008312074,0.00004009464,0.0002279272,0.0003001397,0.02126017],"category_scores_gemma":[0.0005696606,0.0003148088,0.0006538356,0.0001908984,0.00005242878,0.000108935,0.0002341019,0.0005481627,0.3024728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000114933,"about_ca_system_score_gemma":0.000453971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001748564,"about_ca_topic_score_gemma":0.00003033565,"domain_scores_codex":[0.9977635,0.00009892276,0.0003852949,0.0005906487,0.0007898912,0.0003717056],"domain_scores_gemma":[0.9973347,0.00003340824,0.0001338802,0.001569912,0.00006711036,0.0008609928],"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":[0.0005383437,0.0001214971,0.000006527118,0.001617064,0.0003109127,0.001008239,0.000005445614,4.474379e-7,0.00001058846,0.000003963788,0.9951327,0.001244274],"study_design_scores_gemma":[0.002203698,0.00006171298,0.0002820842,0.0002433149,0.001813751,0.0001430399,0.00002098709,0.00001021954,0.000006487868,0.000009269094,0.9949428,0.0002626777],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001439849,0.00001907203,0.0001002815,0.00003711866,0.0006147406,0.0007155156,0.9979896,0.00009165312,0.000417626],"genre_scores_gemma":[0.00002404841,0.001175265,0.0001856027,0.003091822,0.001151196,0.00004483618,0.9940828,0.0000319352,0.0002124763],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2812127,"threshold_uncertainty_score":0.9999304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198179097441933,"score_gpt":0.2741131898192298,"score_spread":0.2542952800750365,"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."}}