{"id":"W4398315567","doi":"10.7910/dvn/pkjufn/y7xhkb","title":"FCC2002.088.ran","year":2020,"lang":"el","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":"Earth's magnetic field; Range (aeronautics); Environmental science; Meteorology; Remote sensing; Atmospheric sciences; Physics; Geology; 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":[0.0006932653,0.0008035427,0.00149306,0.0001964254,0.0002721169,0.0001326388,0.0006783915,0.0006715887,0.06126454],"category_scores_gemma":[0.001656462,0.0008438479,0.001360557,0.0004670893,0.0001643142,0.0003196331,0.0007132993,0.00125785,0.7426407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003192557,"about_ca_system_score_gemma":0.001115002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004282962,"about_ca_topic_score_gemma":0.00007081547,"domain_scores_codex":[0.9944005,0.0004148548,0.001006955,0.001402964,0.001757338,0.001017364],"domain_scores_gemma":[0.9939076,0.0001285247,0.0003923698,0.003196719,0.0001598624,0.002214972],"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":[0.001589798,0.00040896,0.00003666638,0.004357437,0.001040775,0.002280146,0.00004506668,0.000002906268,0.00004618684,0.00002431069,0.9849179,0.005249834],"study_design_scores_gemma":[0.005784904,0.000162652,0.001465385,0.0009405182,0.005139051,0.0001566565,0.000203293,0.00009159909,0.0000152757,0.00001514672,0.9853253,0.0007002392],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001171917,0.0001054169,0.000312787,0.00008173831,0.002390157,0.001608038,0.9942698,0.0001450614,0.0009697724],"genre_scores_gemma":[0.0004645975,0.00540357,0.0002535424,0.004588377,0.00367142,0.00008914439,0.9848117,0.00009732815,0.000620287],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6813761,"threshold_uncertainty_score":0.9994012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02069068419926492,"score_gpt":0.2721937963162187,"score_spread":0.2515031121169538,"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."}}