{"id":"W7071497900","doi":"","title":"SHORT CUTS #100 - The Best Of The Imposter (So Far) pt.2","year":2016,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shot (pellet); Character (mathematics); Cult; Paradise; Documentary film; Front (military)","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":[0.0003546951,0.0007278482,0.0003768284,0.0006238499,0.003940055,0.005204028,0.0005937271,0.001894358,0.5439536],"category_scores_gemma":[0.001890235,0.0004119097,0.0003357681,0.0004410839,0.0005941227,0.002997542,0.002992752,0.003355159,0.3357348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001078145,"about_ca_system_score_gemma":0.0007176292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003861878,"about_ca_topic_score_gemma":0.01342048,"domain_scores_codex":[0.9995911,0.00004772072,0.00001262123,0.00005924182,0.0001900455,0.00009929392],"domain_scores_gemma":[0.9992573,0.00008337505,0.00002438726,0.00006233126,0.0002857024,0.00028699],"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":[0.00001976936,0.000008744883,0.0000527704,0.0000285514,6.427956e-7,0.00004307307,0.0001593552,0.000005886893,0.000169348,0.001557067,0.9800988,0.01785593],"study_design_scores_gemma":[0.000001637461,0.000008861146,0.000377161,0.00004125717,6.049687e-7,0.00006121215,0.0004174762,0.000009295607,0.00008010591,0.0003282895,0.9986709,0.000003096056],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001542619,0.002376615,0.0005380037,0.009758388,0.01871035,0.0001131283,0.001254879,0.0006416197,0.9650644],"genre_scores_gemma":[0.003265175,0.0004185071,0.0001932757,0.00164852,0.000838607,0.00003063123,0.0003955308,0.0003201442,0.9928896],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4560464,"threshold_uncertainty_score":0.6504948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004480521380375534,"score_gpt":0.2057474457650395,"score_spread":0.201266924384664,"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."}}