{"id":"W4398749816","doi":"10.7910/dvn/pkjufn/jmvofz","title":"FCC2003.071.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; Meteorology; Environmental science; Atmospheric sciences; Remote sensing; Physics; Geography; 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":[0.001396179,0.002387553,0.001714204,0.003580289,0.0007473567,0.002916978,0.00372502,0.002653595,0.1433227],"category_scores_gemma":[0.008974701,0.0008957918,0.001577306,0.006493998,0.0004905517,0.001407494,0.001922286,0.001642747,0.155587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001770017,"about_ca_system_score_gemma":0.002260305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03603873,"about_ca_topic_score_gemma":0.04767096,"domain_scores_codex":[0.9990106,0.0002422837,0.0001071886,0.0002942062,0.0001749273,0.0001707612],"domain_scores_gemma":[0.9974255,0.0007851035,0.0002644115,0.0006528458,0.0005327188,0.000339373],"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":[0.00004666387,0.000008823335,0.0003832547,0.0003065726,0.00002509398,0.000007450712,0.000006931911,0.0001989939,0.00002416433,0.0002717746,0.9977429,0.0009775809],"study_design_scores_gemma":[0.0006176812,0.0000274381,0.003037356,0.0004422771,0.0000543743,0.00005522031,0.00004708819,0.0009943695,0.0002399146,0.002204435,0.9922448,0.00003515637],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000519384,0.00006089344,0.00003377647,0.00008166289,0.00002201602,0.000004920512,0.9988902,0.000315203,0.0005393252],"genre_scores_gemma":[0.0004058427,0.00007023955,0.000155415,0.0001132542,0.00001687314,0.00004418342,0.9984397,0.0001062477,0.0006481669],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8566774,"threshold_uncertainty_score":0.4794621,"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."}}