{"id":"W4398755115","doi":"10.7910/dvn/pkjufn/cvxpjg","title":"FCC2001.067.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; Remote sensing; Atmospheric sciences; Geology; Physics; Aerospace engineering; Magnetic field; 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":[0.001404249,0.002349237,0.001733218,0.003658464,0.000755905,0.002950918,0.003759276,0.002652845,0.1532951],"category_scores_gemma":[0.009144684,0.0009034876,0.001517449,0.00654757,0.0004890565,0.001438863,0.001932731,0.001608495,0.1658364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001764207,"about_ca_system_score_gemma":0.002224557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03390895,"about_ca_topic_score_gemma":0.04458025,"domain_scores_codex":[0.9990035,0.0002501497,0.0001066744,0.0002979681,0.0001738268,0.0001678757],"domain_scores_gemma":[0.9973857,0.0008089817,0.0002644277,0.000665658,0.0005325391,0.0003426617],"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":[0.00004633816,0.000008545873,0.0003623454,0.0003068807,0.00002400482,0.000007227186,0.000006850606,0.000190049,0.00002279464,0.0002746963,0.997749,0.001001192],"study_design_scores_gemma":[0.0005894583,0.00002684613,0.002814063,0.0004372803,0.00005103107,0.00005226227,0.00004471329,0.0009430802,0.000225003,0.002187788,0.9925947,0.00003388346],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000503932,0.00006257132,0.0000350062,0.00008482564,0.00002200093,0.000004993182,0.9988235,0.0003289593,0.0005877592],"genre_scores_gemma":[0.0004124016,0.00007284234,0.0001547664,0.0001149249,0.00001729958,0.00004518025,0.9983848,0.0001116434,0.0006862052],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.846705,"threshold_uncertainty_score":0.512823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01975139362270359,"score_gpt":0.2758061501033529,"score_spread":0.2560547564806493,"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."}}