{"id":"W4398555880","doi":"10.7910/dvn/pkjufn/iwal49","title":"FCC2003.026.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; Geomagnetic latitude; Atmospheric sciences; 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":[0.001389508,0.002440753,0.001745518,0.003622434,0.0007551666,0.002947827,0.00384281,0.002681951,0.1472036],"category_scores_gemma":[0.00887445,0.000906653,0.001568498,0.00652639,0.0004954797,0.001432091,0.001954935,0.001638741,0.1615736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001769307,"about_ca_system_score_gemma":0.00224077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0351789,"about_ca_topic_score_gemma":0.04530548,"domain_scores_codex":[0.9990128,0.000243044,0.0001060256,0.0002973844,0.0001724665,0.0001682725],"domain_scores_gemma":[0.9974946,0.0007448773,0.000253789,0.0006549984,0.0005140906,0.0003377751],"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":[0.00004837506,0.000008858999,0.0003636341,0.0003072583,0.00002482706,0.000007624351,0.000006942978,0.0002001976,0.00002487996,0.0002719394,0.9977417,0.000993821],"study_design_scores_gemma":[0.0006135295,0.00002759965,0.002795565,0.0004204403,0.00005206935,0.00005478926,0.0000454962,0.0009909493,0.0002361333,0.002194532,0.9925342,0.00003468467],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005217504,0.00006161974,0.0000349859,0.00008229927,0.00002234918,0.000005066322,0.9988595,0.0003377197,0.0005443182],"genre_scores_gemma":[0.000403304,0.00006919965,0.0001558738,0.0001112463,0.00001694115,0.00004369711,0.9984547,0.0001089545,0.0006360393],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8527964,"threshold_uncertainty_score":0.4924451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01972107205665835,"score_gpt":0.2747592075444449,"score_spread":0.2550381354877865,"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."}}