{"id":"W7005897472","doi":"","title":"SHORT CUTS #106 - How To Exploit A Massacre","year":2017,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Phytochemistry Medicinal Plant Applications","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pledge; Favourite; Exploit; Narrative; Prime minister; Government (linguistics); Refugee; Prime time","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":["insufficient_payload"],"category_scores_codex":[0.0009883657,0.000639607,0.0003053769,0.001040169,0.005984243,0.007362124,0.0008901546,0.004913281,0.3493741],"category_scores_gemma":[0.004439666,0.0003627956,0.000346763,0.000655811,0.001195221,0.00414228,0.002645443,0.004091674,0.1961795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00348064,"about_ca_system_score_gemma":0.005961523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07661823,"about_ca_topic_score_gemma":0.2092859,"domain_scores_codex":[0.9988002,0.0001003668,0.00003125709,0.0000842037,0.0006698426,0.0003140744],"domain_scores_gemma":[0.997778,0.0002930686,0.00005796854,0.00016338,0.001082995,0.0006246301],"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":[0.000005596071,0.000007846384,0.00004140177,0.00001756329,4.534112e-7,0.00002200012,0.00008416845,0.000005207056,0.00006617984,0.003066004,0.9880491,0.008634377],"study_design_scores_gemma":[0.000001480731,0.000003116652,0.0001848178,0.00002820152,5.797365e-7,0.00001278099,0.0001550721,0.000006530936,0.00004408275,0.0003179656,0.9992429,0.000002503605],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0007796796,0.00179765,0.0003440086,0.03782335,0.01299078,0.0001592668,0.001557326,0.0007448874,0.9438031],"genre_scores_gemma":[0.002958925,0.0005184598,0.000182377,0.009878672,0.0009054016,0.00004239901,0.000463865,0.0002542134,0.9847957],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6506259,"threshold_uncertainty_score":0.928039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01256580213967823,"score_gpt":0.1961484676303367,"score_spread":0.1835826654906584,"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."}}