{"id":"W4398319400","doi":"10.7910/dvn/pkjufn/8irdav","title":"FCC2002.106.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; Ran; Geology; Physics; Chemistry; 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":[0.001312226,0.002504143,0.001657969,0.003528118,0.0007824644,0.00320821,0.003694706,0.002792016,0.1347301],"category_scores_gemma":[0.007626084,0.0008967637,0.0014956,0.006860392,0.0004904923,0.001542342,0.001838479,0.001685182,0.1672224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001813281,"about_ca_system_score_gemma":0.002156525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03682239,"about_ca_topic_score_gemma":0.05113325,"domain_scores_codex":[0.999002,0.0002351534,0.0001147943,0.000281579,0.0001863354,0.000180024],"domain_scores_gemma":[0.9978247,0.0005954851,0.0002040409,0.0005795508,0.0005102713,0.0002859923],"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":[0.000043461,0.00000985099,0.0002896454,0.0002795784,0.000020813,0.000008207053,0.000006949543,0.0001955696,0.00002815105,0.0002886012,0.9979321,0.0008971525],"study_design_scores_gemma":[0.000491771,0.00002627226,0.002372023,0.0003549655,0.00003786584,0.00005138662,0.00004288814,0.0009108851,0.0002419448,0.001702909,0.9937371,0.00003001188],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005400606,0.00005773916,0.0000341,0.00007314494,0.00002382086,0.000005074162,0.9986333,0.0003687802,0.0007500628],"genre_scores_gemma":[0.0003332857,0.00005291532,0.0001301607,0.00008277479,0.000011608,0.00003158643,0.9986738,0.0001003607,0.0005835515],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8652699,"threshold_uncertainty_score":0.450717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01974361018426125,"score_gpt":0.2736903616048372,"score_spread":0.253946751420576,"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."}}