{"id":"W4398466762","doi":"10.7910/dvn/pkjufn/l9ow1b","title":"FCC2003.090.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; Atmospheric sciences; Meteorology; 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":[0.001404474,0.002408421,0.001685673,0.003670983,0.0007315097,0.002888574,0.003690818,0.002648185,0.1370799],"category_scores_gemma":[0.008943371,0.0008891624,0.001568049,0.006620945,0.0004935441,0.001415464,0.001925227,0.001645861,0.15126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001802895,"about_ca_system_score_gemma":0.002319409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03691289,"about_ca_topic_score_gemma":0.04783022,"domain_scores_codex":[0.999003,0.0002407162,0.0001099864,0.0002945701,0.0001788951,0.0001728074],"domain_scores_gemma":[0.9974741,0.0007511889,0.0002593401,0.0006482982,0.00052763,0.0003393966],"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":[0.00004818887,0.000008865873,0.0003747528,0.000302554,0.00002476695,0.000007525926,0.000006821085,0.0001995783,0.00002501787,0.0002659044,0.9977525,0.0009834633],"study_design_scores_gemma":[0.0006188196,0.00002858601,0.003119283,0.0004390378,0.0000541082,0.00005702035,0.00004770848,0.001008224,0.000244055,0.00220813,0.9921395,0.00003557081],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005321668,0.00006052767,0.00003274357,0.00008032942,0.00002187721,0.000004867519,0.9988984,0.0003144772,0.0005335513],"genre_scores_gemma":[0.0003997193,0.00006810678,0.0001455634,0.0001078756,0.00001643331,0.00004163749,0.9984992,0.000100741,0.0006206814],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8629201,"threshold_uncertainty_score":0.458578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973706749555086,"score_gpt":0.2748691842451595,"score_spread":0.2551321167496087,"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."}}