{"meta":{"query_hash":"941fcb612bba","filters":{"venue":"Encyclopedia of Statistics in Quality and Reliability"},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"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/941fcb612bba","api":"https://metacan.xera.ac/api/v1/cohort?venue=Encyclopedia+of+Statistics+in+Quality+and+Reliability"},"results":[{"id":"W1558634265","doi":"10.1002/9780470061572.eqr137","title":"Sampling in Industrial Standards","year":2007,"lang":"en","type":"other","venue":"Encyclopedia of Statistics in Quality and Reliability","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Innovation, Science and Economic Development Canada","funders":"","keywords":"Standardization; Sampling (signal processing); Formative assessment; International standardization; Political science; Engineering; Telecommunications; Statistics; Mathematics; Law","score_opus":0.1641537713002866,"score_gpt":0.483510237691754,"score_spread":0.3193564663914674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1558634265","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017440646,0.0010052443,0.6171865,0.0000979312,0.002544079,0.00071586744,0.009411765,0.000053480286,0.36724108],"genre_scores_gemma":[0.039555773,0.0072760317,0.82264644,0.000097773875,0.0018727747,0.0000761054,0.00014974414,0.0006128168,0.12771256],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99300665,0.0006493561,0.0025257594,0.0009763976,0.0023939477,0.00044787006],"domain_scores_gemma":[0.9791036,0.018621469,0.0009669968,0.0007332855,0.00039370562,0.00018090705],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.015017284,0.00032761483,0.001162695,0.00083603564,0.000045098892,0.00004244548,0.00048220874,0.0006384856,0.0007990799],"category_scores_gemma":[0.11677551,0.00028444492,0.0000474211,0.00095251016,0.00088131294,0.000101674326,0.00023189247,0.0010697445,0.000008434724],"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":[0.0006185316,0.00066475547,0.30430523,0.0015384138,0.00002154138,0.00007987421,0.001879221,0.0005170557,0.0000025706167,0.11598026,0.061114322,0.51327825],"study_design_scores_gemma":[0.0010355288,0.00009443597,0.03838321,0.0005370216,0.000014435807,7.54352e-7,0.0006020194,0.00010356951,0.0000038579524,0.60007733,0.35858256,0.00056526804],"about_ca_topic_score_codex":0.0012398282,"about_ca_topic_score_gemma":0.0013263867,"teacher_disagreement_score":0.51271296,"about_ca_system_score_codex":0.00022602348,"about_ca_system_score_gemma":0.0003968205,"threshold_uncertainty_score":0.9999608},"labels":[],"label_agreement":null},{"id":"W1559739512","doi":"10.1002/9780470061572.eqr002","title":"Analysis of Variance","year":2007,"lang":"en","type":"other","venue":"Encyclopedia of Statistics in Quality and Reliability","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Variance (accounting); Analysis of variance; Statistics; One-way analysis of variance; Econometrics; Variable (mathematics); Mathematics","score_opus":0.010630437257359737,"score_gpt":0.2816093602867427,"score_spread":0.270978923029383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1559739512","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033342803,0.0017662577,0.11700817,0.000008652923,0.0010213262,0.00040950102,0.0031291007,0.00012682103,0.8731959],"genre_scores_gemma":[0.5022873,0.041447684,0.06494107,0.000084605635,0.00072015834,0.00012520146,0.0006559277,0.00090746046,0.38883054],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985152,0.00011001772,0.0008134165,0.00020666611,0.00021898652,0.000135728],"domain_scores_gemma":[0.99893624,0.00042086618,0.00021721375,0.00033583862,0.000040992163,0.000048841186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095707946,0.00016106444,0.0008001591,0.0004859291,0.000007525913,0.000003172759,0.00009199884,0.0002873835,0.00033037757],"category_scores_gemma":[0.00028167386,0.00015890706,0.00007237283,0.0005715351,0.00014627744,0.000013069185,0.000015429821,0.00020655512,0.0000021578087],"study_design_candidate":"not_applicable","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":[0.0005478994,0.001972479,0.33462986,0.060512085,0.010725666,0.00006040529,0.008184445,0.06598553,0.00024784173,0.11952937,0.20139882,0.19620559],"study_design_scores_gemma":[0.0016045509,0.00012506708,0.29746458,0.0005438853,0.0015350983,9.946075e-7,0.00040249934,0.0650787,0.00003220748,0.0048983,0.62703675,0.0012773473],"about_ca_topic_score_codex":0.0016227122,"about_ca_topic_score_gemma":0.0013107671,"teacher_disagreement_score":0.49895307,"about_ca_system_score_codex":0.00003359094,"about_ca_system_score_gemma":0.00001898618,"threshold_uncertainty_score":0.64800423},"labels":[],"label_agreement":null},{"id":"W1564432298","doi":"10.1002/9780470061572.eqr012","title":"<scp>L</scp>atin Hypercube Designs","year":2007,"lang":"en","type":"other","venue":"Encyclopedia of Statistics in Quality and Reliability","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Latin hypercube sampling; Orthogonality; Hypercube; Computer science; Stratification (seeds); Class (philosophy); Computer experiment; Strengths and weaknesses; Univariate; Space (punctuation); Theoretical computer science; Mathematics; Parallel computing; Simulation; Geometry; Statistics; Artificial intelligence; Multivariate statistics; Monte Carlo method","score_opus":0.1368736867543813,"score_gpt":0.455217255129216,"score_spread":0.3183435683748347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1564432298","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027185795,0.001327115,0.16592112,0.00003140689,0.0009612823,0.00075293606,0.0014348588,0.00006301836,0.8267897],"genre_scores_gemma":[0.00051028584,0.0019326169,0.6493705,0.00010777345,0.00016524162,0.000023921957,0.000039465474,0.00016687361,0.34768334],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9911224,0.0025558297,0.002488799,0.001258067,0.0020415657,0.0005333392],"domain_scores_gemma":[0.9714189,0.025556969,0.0011710129,0.0012980491,0.00027436228,0.00028069702],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.019250145,0.0004925161,0.0014203389,0.00077051297,0.000069025155,0.000069152156,0.00083859294,0.0007619409,0.0013469654],"category_scores_gemma":[0.051606346,0.00040728963,0.00013236418,0.00092157966,0.0012529072,0.0001011619,0.00031843208,0.0007104406,0.00011997292],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009039782,0.0011863719,0.041806623,0.00084116345,0.00005744695,0.000060705574,0.004141852,0.000059045506,0.00018018007,0.053991534,0.8390514,0.05853325],"study_design_scores_gemma":[0.00086765166,0.00030704084,0.046327308,0.0002029776,0.000048364265,0.0000051277784,0.0025454904,0.00024924852,0.00021013002,0.21277726,0.7359985,0.00046087714],"about_ca_topic_score_codex":0.0011685054,"about_ca_topic_score_gemma":0.0001741556,"teacher_disagreement_score":0.48344937,"about_ca_system_score_codex":0.00010451325,"about_ca_system_score_gemma":0.00022362641,"threshold_uncertainty_score":0.9998379},"labels":[],"label_agreement":null},{"id":"W1681165416","doi":"10.1002/9780470061572.eqr105","title":"Group Maintenance Policies","year":2007,"lang":"en","type":"other","venue":"Encyclopedia of Statistics in Quality and Reliability","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Generalization; Feature (linguistics); State (computer science); Computer science; Group (periodic table); Mathematics; Algorithm","score_opus":0.01066407379303127,"score_gpt":0.2700272141882417,"score_spread":0.25936314039521047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1681165416","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010526942,0.0012274758,0.16935569,0.000058657708,0.0010506884,0.0006706434,0.0014251218,0.0002726621,0.8248864],"genre_scores_gemma":[0.014292668,0.21349886,0.44599962,0.00026764112,0.00084524474,0.00015630409,0.0008913948,0.0013011736,0.32274708],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980406,0.00010452606,0.0008734915,0.00035962314,0.0002624455,0.00035929933],"domain_scores_gemma":[0.9987546,0.00043230405,0.00019288411,0.00046284645,0.00006545724,0.0000918604],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011913578,0.0003098135,0.0006451704,0.00027365226,0.000021893522,0.000011009891,0.00016539956,0.00046962893,0.00024453824],"category_scores_gemma":[0.0007276911,0.00029604664,0.000051869512,0.000268505,0.0005165658,0.000049210088,0.0000544118,0.00043313435,0.000008097171],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014218263,0.00063761475,0.017979922,0.018748594,0.00011409051,0.000025499103,0.0022618736,0.007792004,0.000023375771,0.283323,0.62894773,0.04000414],"study_design_scores_gemma":[0.0011826082,0.0001294058,0.041906517,0.0011009739,0.00006232237,0.000003621021,0.00039135013,0.0040975823,0.000017151762,0.069019735,0.88077897,0.0013097882],"about_ca_topic_score_codex":0.0012126956,"about_ca_topic_score_gemma":0.0008134785,"teacher_disagreement_score":0.5021393,"about_ca_system_score_codex":0.00010040572,"about_ca_system_score_gemma":0.000030595627,"threshold_uncertainty_score":0.99994916},"labels":[],"label_agreement":null},{"id":"W4234186239","doi":"10.1002/9780470061572.eqr292","title":"Process Capability Indices, Comparison of","year":2007,"lang":"en","type":"other","venue":"Encyclopedia of Statistics in Quality and Reliability","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Perspective (graphical); Process (computing); Variety (cybernetics); Process capability; Function (biology); Yield (engineering); Interpretation (philosophy); Quality (philosophy); Process capability index; Management science; Statistics; Computer science; Econometrics; Mathematics; Engineering; Epistemology; Work in process; Artificial intelligence; Operations management; Biology; Philosophy; Thermodynamics; Evolutionary biology","score_opus":0.0964562583405649,"score_gpt":0.48415810950056704,"score_spread":0.3877018511600021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234186239","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0316903,0.002523283,0.37203997,0.00008460256,0.0017830848,0.0016148904,0.007847541,0.00010170353,0.5823146],"genre_scores_gemma":[0.6976384,0.0016544396,0.24656509,0.000036564914,0.00041103983,0.00005907461,0.00015117895,0.00035338712,0.053130846],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9921322,0.0006577128,0.0035792927,0.00092044007,0.0023059917,0.00040436324],"domain_scores_gemma":[0.98447096,0.011169887,0.002495375,0.0010143181,0.00064458605,0.00020486137],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.008072769,0.0003833139,0.0018285498,0.00060243555,0.00005152903,0.000018643725,0.0007558276,0.000557014,0.00064497883],"category_scores_gemma":[0.04020461,0.0003202005,0.00007392685,0.0009595475,0.0018903164,0.00010301944,0.000211651,0.00079419924,0.000010371504],"study_design_candidate":"observational","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":[0.0002665802,0.0014031113,0.83660465,0.00628073,0.00003326723,0.000007042444,0.005083015,0.00024700942,0.0000044167537,0.024042726,0.014291452,0.11173597],"study_design_scores_gemma":[0.00087546,0.00024946168,0.2269086,0.00054442446,0.00006168211,8.426329e-7,0.00398477,0.00036267543,0.000116647236,0.72460204,0.04147859,0.0008148016],"about_ca_topic_score_codex":0.0010854375,"about_ca_topic_score_gemma":0.00074282236,"teacher_disagreement_score":0.7005593,"about_ca_system_score_codex":0.00007813924,"about_ca_system_score_gemma":0.00025371782,"threshold_uncertainty_score":0.999925},"labels":[],"label_agreement":null},{"id":"W4242396459","doi":"10.1002/9780470061572.eqr475","title":"Smoothed Function Estimation for Censored Data","year":2007,"lang":"en","type":"other","venue":"Encyclopedia of Statistics in Quality and Reliability","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Censoring (clinical trials); Smoothing; Estimation; Statistics; Computer science; Hazard; Density estimation; Function (biology); Econometrics; Mathematics; Estimator; Engineering","score_opus":0.1111912858963067,"score_gpt":0.43401283877329805,"score_spread":0.3228215528769913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242396459","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009228292,0.00011952186,0.89903456,0.000039260016,0.00047290287,0.00085913483,0.0102335885,0.00005162797,0.08909712],"genre_scores_gemma":[0.00012251177,0.0006204269,0.9788476,0.00002887912,0.0001272521,0.0000306347,0.0006277578,0.00012077637,0.019474143],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973189,0.00034630843,0.0011242355,0.00061554066,0.00033527586,0.00025971825],"domain_scores_gemma":[0.98928064,0.008854717,0.00065132225,0.000988738,0.00013660429,0.00008797187],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004073598,0.0002701921,0.00076784275,0.00018123008,0.000038243274,0.000013001391,0.00026855833,0.00042628945,0.0004439375],"category_scores_gemma":[0.02429743,0.00024171454,0.00003534525,0.00015324152,0.00036462542,0.000038542694,0.00012832665,0.00029008617,0.000002940369],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019001329,0.0003325394,0.0007396963,0.0052679162,0.000034519762,0.0000011954422,0.00014973781,0.0000021456408,0.0000019606166,0.77970576,0.11754152,0.09603297],"study_design_scores_gemma":[0.0006065331,0.0001252674,0.005579603,0.00026221125,0.00012282067,3.6959173e-7,0.000054487147,0.0029937462,0.0000030734454,0.93193907,0.05800057,0.00031225488],"about_ca_topic_score_codex":0.0004783158,"about_ca_topic_score_gemma":0.00024142636,"teacher_disagreement_score":0.15223329,"about_ca_system_score_codex":0.00004005827,"about_ca_system_score_gemma":0.00009252176,"threshold_uncertainty_score":0.9856833},"labels":[],"label_agreement":null},{"id":"W4249269907","doi":"10.1002/9780470061572.eqr291","title":"Process Capability Indices, <scp>B</scp> ayesian Estimation of","year":2007,"lang":"en","type":"other","venue":"Encyclopedia of Statistics in Quality and Reliability","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Inference; Process (computing); Process capability; Estimator; Process capability index; Bayesian probability; Bayesian inference; Computer science; Cluster (spacecraft); Point process; Perspective (graphical); Focus (optics); Data mining; Statistics; Econometrics; Work in process; Mathematics; Engineering; Artificial intelligence; Operations management","score_opus":0.04939993989325606,"score_gpt":0.42280239080866616,"score_spread":0.3734024509154101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249269907","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01957076,0.00078828237,0.66318595,0.000035435434,0.00089898804,0.0011178271,0.0044814274,0.00007771894,0.3098436],"genre_scores_gemma":[0.30432436,0.0020456396,0.6210818,0.000051478197,0.0004173659,0.00009670987,0.00027884947,0.00041451203,0.07128927],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9922346,0.0006861933,0.0031418288,0.001146589,0.0023333486,0.00045745797],"domain_scores_gemma":[0.97690135,0.018649314,0.002501656,0.0010566335,0.0006431781,0.0002478851],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.009076143,0.0004327026,0.0014645575,0.00070589036,0.00006707097,0.000029400715,0.0007190258,0.00062051875,0.0002210477],"category_scores_gemma":[0.09697362,0.00037261864,0.000079544414,0.0011210472,0.0016751131,0.00017989891,0.00018540725,0.00073862454,0.000012727984],"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":[0.00026288084,0.003049976,0.41969946,0.024455527,0.00012250649,0.000049089056,0.014573683,0.0049060136,0.000011374353,0.09575252,0.04609534,0.3910216],"study_design_scores_gemma":[0.0006548118,0.00016142658,0.13322745,0.00047078665,0.00005580378,0.000001542025,0.0018662707,0.0014760778,0.00008075152,0.84535223,0.016335733,0.00031710268],"about_ca_topic_score_codex":0.0008980569,"about_ca_topic_score_gemma":0.00037417648,"teacher_disagreement_score":0.7495997,"about_ca_system_score_codex":0.0001011229,"about_ca_system_score_gemma":0.0003235512,"threshold_uncertainty_score":0.99987257},"labels":[],"label_agreement":null}]}