{"id":"W4398280573","doi":"10.7910/dvn/pkjufn/tlxoe7","title":"FCC2003.177.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; Geomagnetic latitude; Remote sensing; Geology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001286798,0.002468483,0.001624157,0.003542692,0.0007687269,0.003037285,0.003713641,0.002684049,0.1488929],"category_scores_gemma":[0.007320072,0.0009279754,0.001521341,0.006480101,0.0005044802,0.001459931,0.001901994,0.001647203,0.1765316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001805495,"about_ca_system_score_gemma":0.00214426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03554078,"about_ca_topic_score_gemma":0.04647999,"domain_scores_codex":[0.9990919,0.0002134622,0.0001038019,0.0002631854,0.0001662899,0.0001613248],"domain_scores_gemma":[0.9978257,0.000607385,0.0002078081,0.0005783216,0.0004777482,0.0003030552],"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":[0.00004230845,0.000009310761,0.000278198,0.0002789611,0.0000201203,0.000007234367,0.000006922239,0.0001919844,0.00002776763,0.0002850214,0.9979464,0.0009058557],"study_design_scores_gemma":[0.0005205424,0.00002581082,0.002300511,0.0003354795,0.00003720851,0.00004772407,0.00004186127,0.0009192338,0.0002419525,0.001825383,0.993674,0.00003032951],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005148694,0.00005372956,0.00003461001,0.00007270544,0.00002274044,0.000005173148,0.9986796,0.0003779761,0.0007019618],"genre_scores_gemma":[0.0003411614,0.00005576748,0.0001371297,0.00009026586,0.00001240581,0.00003476204,0.9985873,0.000109602,0.0006317894],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8511071,"threshold_uncertainty_score":0.4980962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01972866413264182,"score_gpt":0.2748712961665105,"score_spread":0.2551426320338687,"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."}}