{"id":"W4398262713","doi":"10.7910/dvn/pkjufn/vfoe2i","title":"FCC2003.040.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; Atmospheric sciences; Environmental science; Meteorology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00140466,0.002477871,0.001705425,0.003691697,0.0007299665,0.002887885,0.003736533,0.002697018,0.1389597],"category_scores_gemma":[0.008822919,0.0009108156,0.001581397,0.006514369,0.0004995298,0.001423392,0.001934415,0.001669273,0.1542707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001781596,"about_ca_system_score_gemma":0.002279997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03618897,"about_ca_topic_score_gemma":0.04677372,"domain_scores_codex":[0.9990059,0.0002405578,0.000108176,0.0002929838,0.0001794874,0.0001730661],"domain_scores_gemma":[0.9975061,0.0007374374,0.0002551743,0.000646545,0.0005177744,0.0003369775],"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":[0.00004797696,0.000008922012,0.0003602992,0.0002995956,0.00002478741,0.000007455715,0.000006850471,0.0002034657,0.00002575276,0.0002656858,0.997775,0.0009741754],"study_design_scores_gemma":[0.0006324404,0.00002890863,0.002993549,0.000423562,0.00005361063,0.00005590216,0.00004699625,0.001030741,0.0002510927,0.00224482,0.9922028,0.00003566704],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005235031,0.0000592313,0.00003344628,0.00008097587,0.00002236849,0.000004855231,0.9989057,0.000328028,0.0005130064],"genre_scores_gemma":[0.0003957489,0.00006802197,0.0001504543,0.0001075704,0.00001676151,0.00004168621,0.998491,0.0001060769,0.0006225333],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8610403,"threshold_uncertainty_score":0.4648665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973706749555086,"score_gpt":0.2748691842451595,"score_spread":0.2551321167496087,"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."}}