{"id":"W4398400116","doi":"10.7910/dvn/pkjufn/1gpp5k","title":"FCC2001.097.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; Meteorology; Environmental science; Atmospheric sciences; Geology; Geography; Physics; Engineering; Aerospace engineering; 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":[0.001387215,0.002308625,0.001693741,0.003657562,0.0007482447,0.002914565,0.003705161,0.002636345,0.1489359],"category_scores_gemma":[0.009166976,0.0008911009,0.001515765,0.006563494,0.000482392,0.001418324,0.00191518,0.001612848,0.1585529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001787626,"about_ca_system_score_gemma":0.002272261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03480957,"about_ca_topic_score_gemma":0.04571119,"domain_scores_codex":[0.9990094,0.0002455909,0.0001078264,0.0002954064,0.0001739588,0.0001677859],"domain_scores_gemma":[0.9973617,0.0008230305,0.0002692362,0.0006600823,0.0005411399,0.0003448779],"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":[0.00004733255,0.000008665693,0.0003824369,0.0003123901,0.00002440159,0.000007411842,0.000006876585,0.0001941033,0.00002311458,0.0002795575,0.997708,0.001005837],"study_design_scores_gemma":[0.0005991878,0.00002718379,0.002997291,0.0004532824,0.00005247895,0.00005400676,0.00004565982,0.0009541053,0.0002265056,0.002188228,0.9923678,0.00003432102],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005135379,0.00006189767,0.00003382561,0.0000832936,0.00002139179,0.000004932806,0.9988507,0.0003128305,0.0005797391],"genre_scores_gemma":[0.0004149245,0.0000720465,0.0001515886,0.0001134506,0.0000168093,0.00004455085,0.9984121,0.0001063978,0.0006680193],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8510641,"threshold_uncertainty_score":0.4982404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01975139362270359,"score_gpt":0.2758061501033529,"score_spread":0.2560547564806493,"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."}}