{"id":"W4398751190","doi":"10.7910/dvn/pkjufn/1zfh96","title":"FCC2001.363.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; Physics; Geology; 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":[0.00136494,0.002520879,0.00173067,0.003847513,0.0007729738,0.003053175,0.00378057,0.002776884,0.1434773],"category_scores_gemma":[0.008702626,0.0009447703,0.001573234,0.007051969,0.0005047938,0.001449129,0.00192762,0.001638004,0.1602324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001844735,"about_ca_system_score_gemma":0.002238837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03631542,"about_ca_topic_score_gemma":0.04669172,"domain_scores_codex":[0.9990281,0.0002354212,0.0001061411,0.0002892691,0.0001726129,0.0001686045],"domain_scores_gemma":[0.9975079,0.0007784169,0.000253833,0.0006287247,0.0005019993,0.0003289179],"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":[0.00004566797,0.000008975609,0.0003596781,0.0003395378,0.00002471123,0.000007865673,0.000007476473,0.0002121314,0.00002580403,0.0002850133,0.997666,0.001017114],"study_design_scores_gemma":[0.000585423,0.00002788191,0.002818729,0.0004511791,0.00005143211,0.0000564033,0.00004675151,0.001008392,0.0002386551,0.002126073,0.992554,0.00003502655],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005170887,0.00006704323,0.00003435342,0.00007925076,0.00002110927,0.000004882505,0.998811,0.000345462,0.000585092],"genre_scores_gemma":[0.000395603,0.00007437322,0.0001479333,0.000105972,0.00001502464,0.00004077131,0.9985093,0.0001056509,0.0006053002],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8565227,"threshold_uncertainty_score":0.4799793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01976153797269264,"score_gpt":0.2759116896298448,"score_spread":0.2561501516571522,"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."}}