{"id":"W7052650634","doi":"","title":"SHORT CUTS #210 - Raccoon Thirst Trap","year":2019,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Trap (plumbing); Thirst","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":[0.0007581757,0.0008090163,0.0004977272,0.001072674,0.003328623,0.003881291,0.001030647,0.003419203,0.733893],"category_scores_gemma":[0.0037524,0.0005075391,0.0004634716,0.0006207239,0.0004175543,0.001936518,0.002758436,0.00321168,0.6165371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001635119,"about_ca_system_score_gemma":0.002637355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02268261,"about_ca_topic_score_gemma":0.0872876,"domain_scores_codex":[0.9992065,0.00006530595,0.00002180789,0.00008391834,0.0004655317,0.0001570387],"domain_scores_gemma":[0.9965113,0.0003051983,0.00006635802,0.0002127162,0.001770544,0.001133965],"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":[0.000009441422,0.000007748111,0.00002638628,0.00001062409,2.641244e-7,0.00001261322,0.000007702095,0.00000449799,0.00004776294,0.0002486662,0.9939096,0.005714671],"study_design_scores_gemma":[0.000004452748,0.000009676754,0.0003030759,0.00002342026,5.755779e-7,0.00002194229,0.00006177211,0.0000158483,0.00003710332,0.0001631135,0.9993556,0.000003325928],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0006350085,0.0006591894,0.0005907488,0.01362178,0.0196421,0.0002570944,0.00305282,0.001893135,0.9596481],"genre_scores_gemma":[0.0005829847,0.00009476276,0.00008729364,0.001869979,0.0005745203,0.00003082059,0.0006132745,0.0002298031,0.9959167],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.733893,"threshold_uncertainty_score":0.3795694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006636456404543672,"score_gpt":0.1903942274866734,"score_spread":0.1837577710821298,"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."}}