{"meta":{"query_hash":"11bf65fc1936","filters":{"venue":"Advances in Methodology and Statistics"},"cohort_total":2,"direct_labels_cover":0,"predictions_cover":2,"exported":2,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/11bf65fc1936","api":"https://metacan.xera.ac/api/v1/cohort?venue=Advances+in+Methodology+and+Statistics"},"results":[{"id":"W2187948374","doi":"10.51936/zbte1232","title":"Comparing the \"typical score\" across independent groups based on different criteria for trimming","year":2006,"lang":"en","type":"article","venue":"Advances in Methodology and Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Social Sciences and Humanities Research Council of Canada; Universiti Sains Malaysia","keywords":"Trimming; Estimator; Statistics; Mathematics; Truncated mean; Type I and type II errors; Statistic; Robustness (evolution); Test statistic; Econometrics; Statistical hypothesis testing; Computer science","score_opus":0.28104391926889516,"score_gpt":0.48572471499354675,"score_spread":0.2046807957246516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2187948374","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26045766,0.0011506494,0.7264029,0.0006217295,0.00055441784,0.0030250605,0.0007728521,0.0011367695,0.0058779907],"genre_scores_gemma":[0.523076,0.00032202437,0.4697219,0.0003724407,0.0001135541,0.0038218228,0.0012812099,0.00036772306,0.0009233005],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.94156873,0.031558495,0.008461055,0.0075660986,0.009992976,0.00085273676],"domain_scores_gemma":[0.7505793,0.1501674,0.019455977,0.049361117,0.027843084,0.0025932335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08942336,0.0012735971,0.0026425112,0.0062272563,0.0017458467,0.0024652963,0.0027519553,0.0018030986,0.0045534717],"category_scores_gemma":[0.31191504,0.0005396694,0.0021949564,0.004237326,0.003581468,0.0029862497,0.003488001,0.0020934697,0.00086222973],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0061191972,0.0011574863,0.13840236,0.0035044816,0.0047410387,0.0005713001,0.007941336,0.0131274145,0.026786555,0.034090836,0.008905108,0.754653],"study_design_scores_gemma":[0.0018837263,0.010045947,0.5669696,0.001960394,0.004475505,0.0020589258,0.008310634,0.13667525,0.059687354,0.18130787,0.02565359,0.00097124965],"about_ca_topic_score_codex":0.00089158834,"about_ca_topic_score_gemma":0.0014401322,"teacher_disagreement_score":0.08942336,"about_ca_system_score_codex":0.0012467763,"about_ca_system_score_gemma":0.001471942,"threshold_uncertainty_score":0.47292155},"labels":[],"label_agreement":null},{"id":"W4206808247","doi":"10.51936/aclg1736","title":"How to objectively rate investment experts in absence of full disclosure?","year":2008,"lang":"en","type":"article","venue":"Advances in Methodology and Statistics","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Simon Fraser University","keywords":"Econometrics; Kurtosis; Random walk; Economics; Computer science; Equity (law); Benchmark (surveying); Statistics; Mathematics","score_opus":0.22832440791031713,"score_gpt":0.4585202506711018,"score_spread":0.23019584276078467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206808247","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29417616,0.001607253,0.67917997,0.004284445,0.00062783,0.0003410439,0.00092489074,0.00068633637,0.018172113],"genre_scores_gemma":[0.8370161,0.0005568785,0.15797183,0.00038789285,0.00021354677,0.00015303415,0.00034629763,0.00006802892,0.0032864735],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9878127,0.006806504,0.001071926,0.0012904968,0.002649994,0.00036839076],"domain_scores_gemma":[0.9628386,0.016340243,0.008468765,0.00429335,0.007139122,0.0009199269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020272512,0.0005693112,0.00089376874,0.0017795956,0.00032516135,0.0032026565,0.00095884484,0.0014128946,0.0017534713],"category_scores_gemma":[0.10559111,0.0002505348,0.00033466888,0.00097411487,0.0008082646,0.0039521884,0.0010886908,0.0009691507,0.0015836495],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017759152,0.0004899086,0.14894436,0.0006751595,0.0003070504,0.00043022956,0.002349248,0.04005378,0.018600695,0.041190874,0.015767537,0.7294152],"study_design_scores_gemma":[0.00020966375,0.0013893333,0.07811099,0.000430521,0.00016591875,0.0023506603,0.003794452,0.781388,0.03423022,0.07978177,0.017666066,0.0004823478],"about_ca_topic_score_codex":0.0009101896,"about_ca_topic_score_gemma":0.0012365587,"teacher_disagreement_score":0.020272512,"about_ca_system_score_codex":0.00057769904,"about_ca_system_score_gemma":0.0007343831,"threshold_uncertainty_score":0.10721254},"labels":[],"label_agreement":null}]}