{"id":"W4398627858","doi":"10.7910/dvn/pkjufn/whgtln","title":"FCC2003.128.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; Ran; Environmental science; Meteorology; Atmospheric sciences; Geology; Geography; Physics; Computer science; 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":[0.001249687,0.002526678,0.001654988,0.003335862,0.0007395642,0.003200207,0.003642093,0.002710247,0.1494365],"category_scores_gemma":[0.006606209,0.0009307488,0.001569213,0.006649542,0.0004810876,0.001498968,0.001888576,0.001610988,0.1911409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001725386,"about_ca_system_score_gemma":0.002087552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03581244,"about_ca_topic_score_gemma":0.05056706,"domain_scores_codex":[0.9990844,0.0002084645,0.0001102275,0.0002586968,0.0001661133,0.000172045],"domain_scores_gemma":[0.9980749,0.0005069221,0.0001759802,0.0005223865,0.0004606573,0.0002591768],"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":[0.00004284517,0.00001001972,0.0002588053,0.0002983186,0.0000204701,0.000008066547,0.000006845024,0.0001881299,0.00003296543,0.0002622176,0.9979861,0.0008852908],"study_design_scores_gemma":[0.0005430625,0.00002818665,0.00217914,0.0003498916,0.00003795172,0.00005177796,0.00004284405,0.0008886884,0.0002680451,0.001664844,0.9939148,0.00003069188],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004973702,0.00005206453,0.00003293887,0.00006177128,0.00002222314,0.000004962191,0.9986601,0.0004051956,0.0007110363],"genre_scores_gemma":[0.0002955331,0.00005030048,0.0001282665,0.00007672123,0.00001021669,0.00002940718,0.998728,0.0001105335,0.0005711479],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8505635,"threshold_uncertainty_score":0.4999148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01972852596165399,"score_gpt":0.2748657995760567,"score_spread":0.2551372736144027,"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."}}