{"id":"W4398626431","doi":"10.7910/dvn/pkjufn/1964hw","title":"FCC2002.174.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":"Earth's magnetic field; Range (aeronautics); Meteorology; Environmental science; Atmospheric sciences; Remote sensing; Geography; Geology; Physics; Magnetic field; Engineering; Aerospace 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001254491,0.002377813,0.001595411,0.003656581,0.0007333129,0.00309011,0.003551969,0.002611831,0.1598041],"category_scores_gemma":[0.007482174,0.0009071243,0.001397878,0.006855406,0.0004907243,0.001451409,0.001853054,0.00159819,0.18119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001726913,"about_ca_system_score_gemma":0.002052814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03316805,"about_ca_topic_score_gemma":0.04312846,"domain_scores_codex":[0.9991252,0.0002068498,0.0000978855,0.0002574813,0.0001585242,0.0001541042],"domain_scores_gemma":[0.9978197,0.0006272063,0.0002177516,0.0005610705,0.0004601338,0.000314208],"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":[0.00004111643,0.000008343667,0.0002797832,0.0002674554,0.00001873985,0.000006893146,0.000006771112,0.0001773439,0.00002481676,0.0002827129,0.9980052,0.0008807511],"study_design_scores_gemma":[0.0004970826,0.00002406751,0.002272137,0.0003362635,0.00003554664,0.00004454808,0.00004115253,0.0007921112,0.0002096745,0.00178914,0.9939297,0.00002867241],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004888588,0.00005349693,0.00003242296,0.00007385104,0.00002199307,0.000004646123,0.9987187,0.0003384177,0.0007076733],"genre_scores_gemma":[0.0003640273,0.00005949353,0.0001335725,0.00009483586,0.00001332986,0.00003497385,0.9985153,0.000113729,0.000670756],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8401959,"threshold_uncertainty_score":0.5345979,"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."}}