{"id":"W4230563760","doi":"10.1017/9781108332835.014","title":"Appendix: Order Statistics","year":2020,"lang":"en","type":"other","venue":"","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Statistics; Order statistic; Order (exchange); Mathematics; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00284439,0.001259386,0.001107651,0.005105541,0.000613317,0.002177442,0.001421465,0.001082237,0.6439023],"category_scores_gemma":[0.05230848,0.0006667995,0.0006218745,0.00684197,0.0002817723,0.001725467,0.0008171114,0.001980106,0.4066977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001624661,"about_ca_system_score_gemma":0.003445082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01135679,"about_ca_topic_score_gemma":0.01076084,"domain_scores_codex":[0.9969426,0.0006662856,0.0004100719,0.000310922,0.001497307,0.0001728091],"domain_scores_gemma":[0.9558297,0.02247333,0.001716567,0.003556347,0.01593641,0.0004876304],"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":[0.00003558315,0.0000301671,0.000388597,0.0002165578,0.000008113374,0.00002091604,0.00001189634,0.0006619582,0.00006404911,0.004634628,0.9656292,0.02829841],"study_design_scores_gemma":[0.0001139537,0.00009194055,0.004246436,0.0004115202,0.00002494763,0.0001980499,0.00008580252,0.003638973,0.0006735993,0.03161626,0.958832,0.00006662485],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001213442,0.0005371135,0.04038806,0.001778901,0.001727343,0.0008560843,0.8581553,0.00440823,0.09093556],"genre_scores_gemma":[0.01882441,0.001813235,0.05764625,0.001332533,0.001459558,0.001869881,0.7407669,0.004323148,0.171964],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3560977,"threshold_uncertainty_score":0.5079302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1366499130650013,"score_gpt":0.413880563665666,"score_spread":0.2772306506006648,"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."}}