{"id":"W4398344948","doi":"10.7910/dvn/pkjufn/um2luv","title":"FCC2003.182.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; Geography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001309142,0.002516326,0.001663954,0.003599504,0.000753583,0.003040395,0.003735731,0.002706868,0.1415486],"category_scores_gemma":[0.007649261,0.0009335121,0.001546921,0.006657361,0.0005135997,0.00145909,0.001887126,0.001670139,0.166059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001802213,"about_ca_system_score_gemma":0.002118333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03623333,"about_ca_topic_score_gemma":0.04679611,"domain_scores_codex":[0.9990672,0.0002217942,0.0001053824,0.0002737628,0.0001688427,0.000162953],"domain_scores_gemma":[0.9978058,0.00062484,0.0002140724,0.0005837188,0.000466647,0.0003048731],"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":[0.00004351445,0.000009229873,0.0003008568,0.0002797231,0.00002139361,0.000007383356,0.000006879637,0.0002049129,0.00002644929,0.0002792106,0.9979328,0.0008876635],"study_design_scores_gemma":[0.0005551964,0.00002754337,0.002561635,0.0003561093,0.00004155924,0.00005196223,0.00004433782,0.0009957888,0.0002412062,0.001912968,0.9931794,0.00003234396],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005439006,0.00005586333,0.00003477732,0.00007442717,0.00002342951,0.000004971936,0.9987317,0.0003733071,0.000647162],"genre_scores_gemma":[0.0003618968,0.00005763572,0.0001369638,0.00009105465,0.00001293503,0.000034857,0.9985971,0.0001072286,0.0006001858],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8584514,"threshold_uncertainty_score":0.4735273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198027158184057,"score_gpt":0.2752688456576101,"score_spread":0.2554661298392044,"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."}}