{"id":"W4398395116","doi":"10.7910/dvn/pkjufn/mjuaof","title":"FCC2001.131.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; Environmental science; Meteorology; Atmospheric sciences; Climatology; Geology; Geography; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002191687,0.0003245543,0.0006993422,0.0001573422,0.00008475593,0.00004055596,0.0002311129,0.0003085797,0.02231221],"category_scores_gemma":[0.0005041665,0.0003206187,0.0006621066,0.0002039014,0.00005433352,0.0001122357,0.0002351292,0.0005565627,0.3419124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001170899,"about_ca_system_score_gemma":0.0005814218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002897478,"about_ca_topic_score_gemma":0.00003359884,"domain_scores_codex":[0.9978695,0.000101264,0.0003916411,0.0006037495,0.0006480749,0.0003857779],"domain_scores_gemma":[0.9972693,0.00003176035,0.0001364523,0.001594044,0.00007847375,0.0008900248],"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":[0.0005248216,0.0001247473,0.000006111685,0.001625802,0.0003196384,0.001033168,0.000005823513,5.394964e-7,0.000009764306,0.000004016994,0.9954214,0.0009241649],"study_design_scores_gemma":[0.002349033,0.00006288938,0.000342746,0.000245333,0.001833861,0.0001463416,0.00002407334,0.00001020235,0.000005069061,0.000009404514,0.9947039,0.0002671368],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001865425,0.00002083822,0.00006213649,0.0000454966,0.0006424385,0.000744204,0.9979497,0.00009953282,0.0004169861],"genre_scores_gemma":[0.00001782296,0.001433232,0.0001893026,0.003304547,0.001196848,0.00004546903,0.9935471,0.00003243485,0.0002332855],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3196003,"threshold_uncertainty_score":0.9999246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02001585367733536,"score_gpt":0.2764444766597631,"score_spread":0.2564286229824277,"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."}}