{"id":"W4398615005","doi":"10.7910/dvn/pkjufn/0k05en","title":"FCC2003.009.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; Atmospheric sciences; Environmental science; Meteorology; Remote sensing; Geology; Physics; Materials science; Computer 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002166592,0.0003229302,0.0006962548,0.0001548667,0.00008376925,0.00004021943,0.0002261889,0.0003048252,0.0204937],"category_scores_gemma":[0.0005489139,0.0003192948,0.0006259744,0.0002238626,0.00005286875,0.0001098189,0.0002233174,0.0005508633,0.3334778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000113311,"about_ca_system_score_gemma":0.0006274713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002537703,"about_ca_topic_score_gemma":0.00002866708,"domain_scores_codex":[0.9978879,0.0001039457,0.0003891363,0.0005994398,0.0006420597,0.0003775258],"domain_scores_gemma":[0.9972934,0.00002800811,0.0001369856,0.001583579,0.0000856207,0.0008723918],"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":[0.0004961379,0.0001218268,0.000005952108,0.001560362,0.0003142312,0.0009670444,0.000005617806,4.425034e-7,0.000008803359,0.000004650634,0.995586,0.0009288669],"study_design_scores_gemma":[0.00229913,0.00006258929,0.0003502326,0.000243568,0.001784182,0.0001342235,0.00002449185,0.000008972879,0.000005727013,0.000008285192,0.9948127,0.000265882],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001528152,0.00002141697,0.00007297113,0.00004077725,0.0006630594,0.0007484276,0.9979167,0.0000960668,0.0004253226],"genre_scores_gemma":[0.00001639723,0.001268704,0.0002088128,0.003275197,0.001112604,0.00004469817,0.9938144,0.00003184146,0.0002273289],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3129841,"threshold_uncertainty_score":0.9999259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01954226926405431,"score_gpt":0.2744679213394577,"score_spread":0.2549256520754034,"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."}}