{"id":"W6990934301","doi":"","title":"Ep 39: Closers for EVERY team with Greg Jewett","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":"Miami; League; Atlanta; White (mutation); Las vegas; Bay","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":[0.0002872753,0.0006931793,0.0003463543,0.0006765917,0.004725421,0.003475807,0.0006456129,0.001816336,0.8471703],"category_scores_gemma":[0.001891329,0.000360316,0.0002837235,0.0007259556,0.0003955603,0.002753257,0.003633835,0.002127351,0.7593669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009784227,"about_ca_system_score_gemma":0.001024947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01366413,"about_ca_topic_score_gemma":0.05151849,"domain_scores_codex":[0.9996922,0.00002828735,0.000007808209,0.00004758884,0.0001237468,0.0001004377],"domain_scores_gemma":[0.998936,0.0000643017,0.00003805977,0.00005257309,0.000293001,0.0006161162],"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":[0.000004679061,0.000004293559,0.0000444213,0.000007037311,2.169652e-7,0.00002045982,0.00003977573,0.000002339014,0.00002993718,0.0001849778,0.9941598,0.005502004],"study_design_scores_gemma":[0.000001838813,0.000004526097,0.0002326001,0.00001471222,4.342561e-7,0.00002160255,0.0001488154,0.000006768,0.0000303422,0.00007898341,0.9994568,0.000002538271],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005964375,0.0002464771,0.0002704149,0.003648609,0.003990656,0.00005354831,0.001772416,0.001668893,0.9877526],"genre_scores_gemma":[0.0009959828,0.00005920092,0.00008920227,0.0008182904,0.0001659444,0.0000170381,0.0003313406,0.0003895061,0.9971335],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1528297,"threshold_uncertainty_score":0.217993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006732738644839492,"score_gpt":0.1862720928397585,"score_spread":0.179539354194919,"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."}}