{"id":"W7066008811","doi":"","title":"Episode 65 - Jenn Sharp","year":2020,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Face (sociological concept); Term (time); Population; Feature (linguistics); Margin (machine learning)","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":[0.0007475495,0.0004936598,0.0003985095,0.0006577922,0.007013778,0.00389272,0.001129688,0.004527572,0.4734535],"category_scores_gemma":[0.004011685,0.0003471326,0.0003586872,0.0008638704,0.000692005,0.003196125,0.004086569,0.00576418,0.2037615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004805922,"about_ca_system_score_gemma":0.005280505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1149685,"about_ca_topic_score_gemma":0.3077724,"domain_scores_codex":[0.9992593,0.00006073542,0.00002525677,0.00009136267,0.0002275647,0.0003357801],"domain_scores_gemma":[0.9990226,0.0000679272,0.0000327998,0.0000643426,0.0003618339,0.0004505138],"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":[0.00001032074,0.000008549069,0.0001595238,0.00001655154,7.135643e-7,0.0001993023,0.0002812637,0.000004902598,0.00003992619,0.002119717,0.9919598,0.005199396],"study_design_scores_gemma":[0.000002011629,0.000002717664,0.0002548356,0.00004084776,6.3776e-7,0.00008723568,0.0004940666,0.000005692518,0.00003139735,0.0003943557,0.9986839,0.000002271339],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002047197,0.000918429,0.0003514316,0.03730223,0.004407104,0.0001227118,0.003086159,0.0004497932,0.9513151],"genre_scores_gemma":[0.006790364,0.0003458686,0.00009405623,0.01533333,0.0003586654,0.00004904533,0.0008384292,0.0001836374,0.9760065],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5265465,"threshold_uncertainty_score":0.7510546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0079053633676592,"score_gpt":0.1912855204157166,"score_spread":0.1833801570480574,"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."}}