{"id":"W4398400556","doi":"10.7910/dvn/pkjufn/jahkbo","title":"FCC2002.012.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; Meteorology; Atmospheric sciences; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002196928,0.000318586,0.0006837287,0.00009995174,0.00008169268,0.00003962358,0.0002260861,0.0002998651,0.02103695],"category_scores_gemma":[0.000564268,0.0003143785,0.0006522306,0.0001877497,0.00005212999,0.0001113607,0.000233526,0.0005473698,0.2943887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001147886,"about_ca_system_score_gemma":0.0004430409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001689511,"about_ca_topic_score_gemma":0.00003012866,"domain_scores_codex":[0.997768,0.00009931417,0.0003845313,0.0005854258,0.0007883638,0.0003743004],"domain_scores_gemma":[0.997337,0.00003338761,0.0001335609,0.001561596,0.00006648013,0.0008679817],"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":[0.0005389405,0.000123127,0.00000635515,0.00161731,0.0003106573,0.0009562547,0.000005690595,4.346257e-7,0.00001048935,0.000003767088,0.9952049,0.001222055],"study_design_scores_gemma":[0.002225166,0.00006178885,0.0003386077,0.0002405862,0.001829741,0.0001359217,0.00002356554,0.00001018193,0.000006338933,0.000007254064,0.9948586,0.000262228],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001637699,0.00002281312,0.000066095,0.00004091175,0.0006190429,0.0007154917,0.9980263,0.00009387597,0.0003990626],"genre_scores_gemma":[0.00002226724,0.001157322,0.000189205,0.003109941,0.001140457,0.00004548169,0.9940628,0.00003256032,0.0002399568],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2733517,"threshold_uncertainty_score":0.9999309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01990997797315357,"score_gpt":0.2742524758843823,"score_spread":0.2543424979112288,"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."}}