{"id":"W6981553601","doi":"","title":"Ep.57 - Buy Gold and Raisin Bran: The Brexit and Canada","year":2016,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Digital Imaging in Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Brexit; Context (archaeology); European union; Kingdom","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005211493,0.000917978,0.0005853187,0.00159587,0.005437124,0.006002039,0.001256711,0.008753532,0.3000095],"category_scores_gemma":[0.003358637,0.0005542485,0.0005591884,0.003250556,0.002006991,0.003277894,0.001567115,0.00525044,0.09905279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01118255,"about_ca_system_score_gemma":0.01008169,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6027412,"about_ca_topic_score_gemma":0.7913904,"domain_scores_codex":[0.9993601,0.00005045217,0.00003216954,0.00008594727,0.0003189065,0.0001523862],"domain_scores_gemma":[0.9990309,0.0002494274,0.0000458561,0.00005410904,0.0004704039,0.0001492976],"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":[0.000009004677,0.000005071772,0.00007776362,0.00005100981,0.000001783867,0.00003757266,0.00008183403,0.00002215255,0.00002752046,0.0111512,0.9807087,0.007826268],"study_design_scores_gemma":[0.000005698044,0.000002961276,0.001040315,0.0002162783,0.000002552414,0.00002729764,0.0001663378,0.0000161795,0.00003563504,0.001693736,0.9967861,0.000006936263],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00046246,0.03197005,0.0001875567,0.04690183,0.006147697,0.00007637408,0.004548936,0.0001659104,0.9095392],"genre_scores_gemma":[0.003507599,0.007845353,0.0001035875,0.013393,0.0010583,0.00006326201,0.0006304836,0.0001462078,0.9732521],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3972588,"threshold_uncertainty_score":0.9984515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004313952958198567,"score_gpt":0.1871716255634354,"score_spread":0.1828576726052368,"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."}}