{"meta":{"query_hash":"8d208bb40552","filters":{"venue":"Metrika"},"cohort_total":85,"direct_labels_cover":0,"predictions_cover":85,"exported":85,"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/8d208bb40552","api":"https://metacan.xera.ac/api/v1/cohort?venue=Metrika"},"results":[{"id":"W109547034","doi":"10.1007/s00184-013-0461-9","title":"Some results on constructing general minimum lower order confounding $$2^{n-m}$$ 2 n - m designs for $$n\\le 2^{n-m-2}$$ n ≤ 2 n - m - 2","year":2013,"lang":"en","type":"article","venue":"Metrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Mathematics; Combinatorics; Order (exchange); Zhàng; Statistics","score_opus":0.21584645927730445,"score_gpt":0.4501946779864947,"score_spread":0.23434821870919026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W109547034","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":[0.002623458,0.00021061729,0.9960412,0.00012154525,0.000024933935,0.000100536774,0.00008533641,0.0001124795,0.00067988125],"genre_scores_gemma":[0.033355094,0.00031250875,0.96244943,0.0003257023,0.000110659916,0.0010898601,0.00033620678,0.0001401991,0.0018803326],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98214436,0.012947921,0.00076042814,0.0019422314,0.0017339041,0.000471191],"domain_scores_gemma":[0.9210578,0.06835026,0.0025523435,0.0054910295,0.0019389839,0.00060953165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.026953744,0.0035070647,0.004312712,0.002256452,0.0010723603,0.0016884892,0.00353164,0.0025936041,0.009078755],"category_scores_gemma":[0.07080456,0.0029866432,0.004193091,0.0022126662,0.003105465,0.0035638157,0.0041131373,0.003988793,0.0012976249],"study_design_candidate":"simulation_or_modeling","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":[0.00219841,0.0007500199,0.002968636,0.002059099,0.0007158068,0.00021207177,0.00060655107,0.19481543,0.014933548,0.43847942,0.0061245994,0.33613634],"study_design_scores_gemma":[0.0007486202,0.001082637,0.0014861436,0.00023659563,0.00022313796,0.0001554532,0.00006886994,0.43440327,0.0049090097,0.54870117,0.007884555,0.000100505975],"about_ca_topic_score_codex":0.0010417665,"about_ca_topic_score_gemma":0.0020543349,"teacher_disagreement_score":0.026953744,"about_ca_system_score_codex":0.0020867963,"about_ca_system_score_gemma":0.0040652524,"threshold_uncertainty_score":0.14254671},"labels":[],"label_agreement":null},{"id":"W1964770733","doi":"10.1007/s001840100127","title":"Multivariate stable ARMA processes with time dependent coefficients","year":2001,"lang":"en","type":"article","venue":"Metrika","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Mathematics; Uniqueness; Autoregressive model; Autoregressive–moving-average model; Multivariate statistics; Class (philosophy); Simple (philosophy); Applied mathematics; Autoregressive integrated moving average; Operator (biology); Matrix (chemical analysis); Set (abstract data type); Moving average; Statistics; Time series; Mathematical analysis; Computer science","score_opus":0.033867465365381585,"score_gpt":0.22754858452915652,"score_spread":0.19368111916377495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964770733","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10043591,0.0012118638,0.8914663,0.0011596618,0.0001684265,0.00004736289,0.0003205094,0.00027110288,0.00491877],"genre_scores_gemma":[0.93201756,0.0020102414,0.048139676,0.000148496,0.0003640386,0.00014146621,0.0003838137,0.00011430036,0.016680378],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99848,0.0007031655,0.00006900166,0.00031783592,0.00025469466,0.00017526507],"domain_scores_gemma":[0.99002105,0.006256638,0.0018885593,0.0008324533,0.0007668443,0.00023444108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043201754,0.0015620883,0.0018378996,0.0014120586,0.000661525,0.0034249707,0.0016733714,0.0032722033,0.0043972144],"category_scores_gemma":[0.022299357,0.001262936,0.0014026413,0.0025409914,0.001778736,0.004188178,0.0014936222,0.0033941518,0.0013988793],"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":[0.00022072636,0.00006195016,0.0033824977,0.000093588525,0.00016255533,0.0003528181,0.00020800583,0.3930577,0.0023206363,0.5801808,0.0013582441,0.0186004],"study_design_scores_gemma":[0.000022628874,0.000022658027,0.0007263933,0.00001372063,0.000036445632,0.00006179924,0.000016657088,0.91359776,0.00031419238,0.084479466,0.00068051403,0.000027777853],"about_ca_topic_score_codex":0.0025727688,"about_ca_topic_score_gemma":0.0022110709,"teacher_disagreement_score":0.0043972144,"about_ca_system_score_codex":0.0008211714,"about_ca_system_score_gemma":0.00070660625,"threshold_uncertainty_score":0.022847533},"labels":[],"label_agreement":null},{"id":"W1964863669","doi":"10.1007/s00184-005-0026-7","title":"Evaluating expectations of L-statistics by the Steffensen inequality","year":2006,"lang":"en","type":"article","venue":"Metrika","topic":"Mathematical Inequalities and Applications","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Order statistic; Statistics; Inequality; Constant (computer programming); Scale parameter; Distribution (mathematics); Scale (ratio); Applied mathematics; Mathematical analysis","score_opus":0.2073185972680014,"score_gpt":0.44040781492978315,"score_spread":0.23308921766178176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964863669","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024858633,0.0011923495,0.9640746,0.0014551282,0.00015662986,0.000025771724,0.00013200226,0.0001478234,0.007957013],"genre_scores_gemma":[0.7460444,0.003725461,0.22557011,0.0011786828,0.0012571249,0.0002747297,0.0008593113,0.0006911092,0.02039914],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99379116,0.0037756383,0.00025545174,0.00053597835,0.0011405922,0.0005011869],"domain_scores_gemma":[0.9645494,0.029412534,0.0016295718,0.001102349,0.0022572328,0.0010489476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014511125,0.0015255379,0.0019077185,0.0025146692,0.0007412212,0.004336366,0.0024366411,0.0022459999,0.005159496],"category_scores_gemma":[0.05719339,0.0010264623,0.0013291548,0.0015926249,0.0046933754,0.0079846475,0.0031339389,0.003909721,0.0011139744],"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":[0.00011731347,0.000031706593,0.0011120386,0.0001137027,0.00006659371,0.00014305252,0.00020131742,0.03352944,0.0015222083,0.95067525,0.0013455078,0.011141888],"study_design_scores_gemma":[0.000016719894,0.000042966396,0.0005248535,0.00004550225,0.000016476475,0.000060949573,0.0000448236,0.2965414,0.00097096513,0.7004357,0.0012660192,0.00003352781],"about_ca_topic_score_codex":0.0035636448,"about_ca_topic_score_gemma":0.00236539,"teacher_disagreement_score":0.014511125,"about_ca_system_score_codex":0.0026644825,"about_ca_system_score_gemma":0.002062406,"threshold_uncertainty_score":0.07674307},"labels":[],"label_agreement":null},{"id":"W1966686133","doi":"10.1007/s00184-012-0403-y","title":"Compound weighted Poisson distributions","year":2012,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"McMaster University","keywords":"Mathematics; Poisson distribution; Index of dispersion; Compound Poisson distribution; Statistics; Zero-inflated model; Dispersion (optics); Distribution (mathematics); Factorial; Applied mathematics; Poisson regression; Mathematical analysis","score_opus":0.10519673599883851,"score_gpt":0.3899020412199301,"score_spread":0.2847053052210916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966686133","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016116597,0.00055209454,0.9728262,0.0004685606,0.00015690728,0.00009757407,0.00034588738,0.00017730785,0.009258957],"genre_scores_gemma":[0.49160573,0.0033835897,0.41329718,0.0008733611,0.0009537229,0.00093366724,0.0024029585,0.00060394936,0.08594592],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971513,0.0009292737,0.00017974156,0.00073586556,0.00076645095,0.00023741685],"domain_scores_gemma":[0.9899451,0.005073995,0.0012729615,0.0015733823,0.0017862063,0.00034833333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004945779,0.0012199687,0.0016456117,0.0028043748,0.000940243,0.0032023918,0.0026204374,0.0022232293,0.013415039],"category_scores_gemma":[0.024954855,0.0010585574,0.0016881821,0.0034090574,0.0019285887,0.0061243973,0.0024670393,0.0026466376,0.0034605642],"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":[0.00006240615,0.000025979201,0.0009222125,0.000071048424,0.00005056571,0.00019323816,0.00011403617,0.021871926,0.0010553761,0.9509544,0.0029349597,0.02174386],"study_design_scores_gemma":[0.000017357925,0.000027823935,0.00065458415,0.00003277517,0.000042516316,0.0005553834,0.000079717945,0.21999386,0.0012538218,0.7682686,0.009029027,0.00004453645],"about_ca_topic_score_codex":0.0014171725,"about_ca_topic_score_gemma":0.0012925048,"teacher_disagreement_score":0.013415039,"about_ca_system_score_codex":0.0018147081,"about_ca_system_score_gemma":0.001250213,"threshold_uncertainty_score":0.044877768},"labels":[],"label_agreement":null},{"id":"W1967232970","doi":"10.1007/s00184-010-0306-8","title":"Asymptotic properties of maximum likelihood estimators based on progressive Type-II censoring","year":2010,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Council","keywords":"Mathematics; Censoring (clinical trials); Independent and identically distributed random variables; Estimator; Asymptotic distribution; Maximum likelihood; Strong consistency; Statistics; Consistency (knowledge bases); Type (biology); Kaplan–Meier estimator; Random variable; Applied mathematics; Discrete mathematics","score_opus":0.055548639403038884,"score_gpt":0.3333104091440815,"score_spread":0.2777617697410426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967232970","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00943706,0.000612982,0.9875479,0.00029770096,0.000035142017,0.000034547043,0.00007673489,0.00016486863,0.0017930156],"genre_scores_gemma":[0.54505074,0.0037925462,0.43960497,0.00046278565,0.0006973555,0.00069488556,0.001144292,0.0005474692,0.008004864],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9950104,0.0030735622,0.00022068803,0.00051305606,0.00093751407,0.000244732],"domain_scores_gemma":[0.898043,0.089562625,0.0035501467,0.0052592233,0.0028834068,0.000701521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020024097,0.0014428206,0.0019219512,0.0024244045,0.0006781268,0.0029030584,0.0037109004,0.002322675,0.004777038],"category_scores_gemma":[0.15528484,0.0012083638,0.0014634305,0.002495512,0.003766793,0.005814232,0.0031454887,0.003866813,0.001336175],"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":[0.00032296774,0.00008749422,0.0042736293,0.00043777828,0.00020447714,0.0003119924,0.0004893574,0.16038013,0.0026143189,0.75217295,0.002392617,0.07631236],"study_design_scores_gemma":[0.00006326173,0.00007234969,0.001705826,0.00012069712,0.00006042086,0.00029152478,0.000069330956,0.64597136,0.001225076,0.34889755,0.0014600377,0.00006259881],"about_ca_topic_score_codex":0.0012652262,"about_ca_topic_score_gemma":0.000885629,"teacher_disagreement_score":0.020024097,"about_ca_system_score_codex":0.0013528527,"about_ca_system_score_gemma":0.001798994,"threshold_uncertainty_score":0.1058988},"labels":[],"label_agreement":null},{"id":"W1967488547","doi":"10.1007/s00184-006-0083-6","title":"Generalized linear mixed models with informative dropouts and missing covariates","year":2006,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Covariate; Missing data; Generalized linear mixed model; Estimator; Mathematics; Generalized linear model; Statistics; Mixed model; Longitudinal data; Generalized estimating equation; Econometrics; Computer science; Data mining","score_opus":0.05670873068460871,"score_gpt":0.3348015824166259,"score_spread":0.2780928517320172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967488547","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":[0.004096823,0.0007206173,0.9928624,0.000893383,0.000116139134,0.00011221178,0.0004908516,0.00022857456,0.0004789691],"genre_scores_gemma":[0.15320383,0.002163066,0.82667094,0.0011232771,0.0007987858,0.0029120175,0.0020603188,0.00033164938,0.01073616],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.96011597,0.031911384,0.0013502993,0.0040696063,0.0016857428,0.0008670371],"domain_scores_gemma":[0.84879434,0.12771489,0.007438566,0.01231106,0.0028934109,0.0008478372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.050628453,0.0037755675,0.0066174804,0.0030283502,0.0019773948,0.0047609783,0.011750545,0.006291816,0.009660915],"category_scores_gemma":[0.13701606,0.0043582995,0.0054581873,0.005296051,0.0051368056,0.008006485,0.005483829,0.009338352,0.0019570952],"study_design_candidate":"simulation_or_modeling","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":[0.00067370856,0.00023550612,0.0030232966,0.0007524999,0.0013349929,0.0006942374,0.00081642834,0.084504545,0.0002697399,0.8439364,0.005654848,0.05810381],"study_design_scores_gemma":[0.00021198549,0.00008191645,0.00051286136,0.000134108,0.0003460705,0.00023467478,0.00008179163,0.24937156,0.00019060809,0.7451903,0.003583696,0.000060451075],"about_ca_topic_score_codex":0.00678916,"about_ca_topic_score_gemma":0.009105979,"teacher_disagreement_score":0.050628453,"about_ca_system_score_codex":0.0025127323,"about_ca_system_score_gemma":0.0046565686,"threshold_uncertainty_score":0.26775205},"labels":[],"label_agreement":null},{"id":"W1972302252","doi":"10.1007/s00184-008-0176-5","title":"Prediction of k-records from a general class of distributions under balanced type loss functions","year":2008,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Mathematics; Weibull distribution; Exponential function; Type (biology); Bayesian probability; Exponential type; Statistics; Mean squared error; Class (philosophy); Exponential family; Applied mathematics; Bayes estimator; Mathematical analysis; Computer science; Artificial intelligence","score_opus":0.11323585667756782,"score_gpt":0.33234264752065346,"score_spread":0.21910679084308565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972302252","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30479744,0.00055676646,0.6914698,0.0010506079,0.000056387256,0.000081008155,0.0010394726,0.0004067719,0.000541822],"genre_scores_gemma":[0.94632286,0.00075109466,0.046970714,0.00016848448,0.0002206389,0.00012310751,0.0026782192,0.00007724618,0.0026876235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977385,0.00062726537,0.0001713385,0.00082623604,0.00028408988,0.0003524208],"domain_scores_gemma":[0.9739914,0.0190587,0.0024625827,0.0024433779,0.0014178702,0.00062609464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010271791,0.001054149,0.0023286783,0.0014508222,0.0006920825,0.0025078692,0.0034843779,0.0038310417,0.0014730976],"category_scores_gemma":[0.0335795,0.0008355698,0.0011937483,0.0018472914,0.0018809438,0.0064552245,0.0019524745,0.0029527799,0.0008157503],"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":[0.0023579868,0.00047876197,0.054359045,0.00037156173,0.00040624055,0.00062011764,0.00056704343,0.7670043,0.007901713,0.057507765,0.0042374376,0.10418801],"study_design_scores_gemma":[0.000026304684,0.000055003296,0.0033718485,0.000016821725,0.000019566203,0.00008016919,0.00005018798,0.9757378,0.00077450223,0.019623326,0.0002256925,0.000018816076],"about_ca_topic_score_codex":0.0032631536,"about_ca_topic_score_gemma":0.0023717866,"teacher_disagreement_score":0.010271791,"about_ca_system_score_codex":0.0014027675,"about_ca_system_score_gemma":0.0011941617,"threshold_uncertainty_score":0.054323077},"labels":[],"label_agreement":null},{"id":"W1973746887","doi":"10.1007/s00184-013-0462-8","title":"Shrinkage estimation for the mean of the inverse Gaussian population","year":2013,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Mathematics; Shrinkage; Statistics; Estimation; Inverse Gaussian distribution; Inverse; Gaussian; Applied mathematics; Population mean; Population; Shrinkage estimator; Mathematical analysis; Mean squared error; Geometry; Minimum-variance unbiased estimator; Estimator; Demography; Distribution (mathematics); Minimax estimator","score_opus":0.06752974827852377,"score_gpt":0.3499977326993922,"score_spread":0.28246798442086846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973746887","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":[0.0038308704,0.0001647665,0.9953192,0.00015477804,0.000029429486,0.000010422754,0.000023125234,0.00007035805,0.00039702686],"genre_scores_gemma":[0.281872,0.0021706405,0.7036882,0.00035533076,0.0004842513,0.000383253,0.0006539042,0.0005290233,0.009863387],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99829286,0.00079466787,0.00007441654,0.00040165122,0.00032332714,0.000113156224],"domain_scores_gemma":[0.9919052,0.005712493,0.00047096526,0.0007541796,0.00097643706,0.00018061184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006441034,0.0009698702,0.0014773196,0.0013766118,0.0005360579,0.0015417549,0.0018644911,0.0017769396,0.002259587],"category_scores_gemma":[0.03363827,0.0008627356,0.0014466116,0.0010850483,0.0025475272,0.003148286,0.002793557,0.003868494,0.0010835615],"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":[0.00024449523,0.00008845071,0.002781198,0.0004503264,0.00021448026,0.00016386628,0.0006128008,0.35584912,0.011970469,0.45210132,0.004588881,0.17093459],"study_design_scores_gemma":[0.000015311112,0.00003527335,0.00063153735,0.00004595189,0.000027466565,0.000114719944,0.00004071116,0.8884584,0.0017310007,0.10673369,0.002128064,0.00003792382],"about_ca_topic_score_codex":0.002382278,"about_ca_topic_score_gemma":0.0021042228,"teacher_disagreement_score":0.006441034,"about_ca_system_score_codex":0.0009830358,"about_ca_system_score_gemma":0.0015879878,"threshold_uncertainty_score":0.034063816},"labels":[],"label_agreement":null},{"id":"W1974773094","doi":"10.1007/s00184-010-0321-9","title":"Log-concavity and monotonicity of hazard and reversed hazard functions of univariate and multivariate skew-normal distributions","year":2010,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Monotonic function; Mathematics; Univariate; Multivariate statistics; Hazard; Skew; Hazard ratio; Statistics; Property (philosophy); Multivariate analysis; Multivariate stable distribution; Skew normal distribution; Multivariate normal distribution; Econometrics; Applied mathematics; Normal distribution; Mathematical analysis; Confidence interval; Computer science; Normal-Wishart distribution; Chemistry","score_opus":0.036217831379311234,"score_gpt":0.32424764795012595,"score_spread":0.2880298165708147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974773094","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12662195,0.0013791319,0.8636304,0.001657129,0.000066772074,0.00012560953,0.00061720604,0.0002619621,0.0056398967],"genre_scores_gemma":[0.83726203,0.0028390868,0.14772023,0.00050042965,0.0003591229,0.00052273204,0.0010494423,0.00038291773,0.009363931],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.994358,0.00307902,0.00028048342,0.0008997434,0.00086875993,0.0005139693],"domain_scores_gemma":[0.8962781,0.08119819,0.007363524,0.005585699,0.007963184,0.001611339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01798769,0.0010773019,0.0021147411,0.0023539686,0.0008127569,0.0029730645,0.0034181464,0.001234174,0.0055461023],"category_scores_gemma":[0.12556712,0.0016969822,0.0021140962,0.0020741294,0.0055676964,0.0073953723,0.002156099,0.004724464,0.00078370684],"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":[0.0004616683,0.00018628359,0.020674326,0.00045290464,0.00019751042,0.00059092947,0.0015691378,0.059216727,0.003056085,0.852475,0.002909947,0.05820948],"study_design_scores_gemma":[0.00005608528,0.00011016175,0.009889293,0.00008606482,0.00007440054,0.0010695369,0.00025646618,0.3226424,0.0011949469,0.6622752,0.0022581262,0.00008737505],"about_ca_topic_score_codex":0.003693376,"about_ca_topic_score_gemma":0.0026777454,"teacher_disagreement_score":0.01798769,"about_ca_system_score_codex":0.0021031906,"about_ca_system_score_gemma":0.0033356133,"threshold_uncertainty_score":0.09512907},"labels":[],"label_agreement":null},{"id":"W1989419563","doi":"10.1007/s00184-006-0102-7","title":"Minimax estimation of constrained parametric functions for discrete families of distributions","year":2006,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Mathematics; Mean squared error; Estimator; Minimax; Applied mathematics; Parametric statistics; Negative binomial distribution; Statistics; Minimax estimator; Bayes' theorem; Exponential family; Binomial (polynomial); Poisson distribution; Minimum-variance unbiased estimator; Mathematical optimization; Bayesian probability","score_opus":0.04396108562757465,"score_gpt":0.3479690320625621,"score_spread":0.3040079464349874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989419563","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0074568046,0.00030109298,0.99151987,0.0002163985,0.000012639006,0.000017656499,0.00004055389,0.000054685002,0.0003803701],"genre_scores_gemma":[0.5542626,0.0020809001,0.43536016,0.00027219785,0.00025279223,0.000663513,0.0006643406,0.00036051107,0.006082972],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968137,0.0019567336,0.00011339769,0.0005332793,0.000446711,0.00013618692],"domain_scores_gemma":[0.97452533,0.022507777,0.0011664856,0.0008363756,0.0006703405,0.0002936506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010422808,0.0016814427,0.0031730281,0.0019287713,0.00075505296,0.0025992154,0.002955131,0.002445032,0.0019389874],"category_scores_gemma":[0.04457105,0.0017467161,0.001461304,0.0018082793,0.0033508867,0.004745479,0.0036268942,0.0037955553,0.0003664823],"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":[0.00027519968,0.0001050379,0.0010823432,0.0003569257,0.00019400884,0.00011739199,0.00030639407,0.73094875,0.002124833,0.19952147,0.0016850245,0.06328256],"study_design_scores_gemma":[0.000015538915,0.000027429032,0.00017389597,0.000023798508,0.000009474033,0.000037413036,0.00001837684,0.9248327,0.00037302807,0.07406892,0.00040571246,0.000013767767],"about_ca_topic_score_codex":0.0017482768,"about_ca_topic_score_gemma":0.0010030522,"teacher_disagreement_score":0.010422808,"about_ca_system_score_codex":0.0017545393,"about_ca_system_score_gemma":0.001413752,"threshold_uncertainty_score":0.05512178},"labels":[],"label_agreement":null},{"id":"W1995263220","doi":"10.1007/s00184-009-0281-0","title":"Exact inference for progressively Type-I censored exponential failure data","year":2009,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Censoring (clinical trials); Mathematics; Estimator; Exponential distribution; Statistics; Order statistic; Inference; Monte Carlo method; Parametric statistics; Accelerated life testing; Statistical hypothesis testing; Statistical inference; Applied mathematics; Computer science; Weibull distribution; Artificial intelligence","score_opus":0.1762191863140877,"score_gpt":0.4485392128648354,"score_spread":0.2723200265507477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995263220","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":[0.0108096525,0.00031087262,0.9879,0.00028046753,0.000034918947,0.000024153533,0.0001327511,0.00014407205,0.00036310777],"genre_scores_gemma":[0.6584143,0.0022961164,0.32671538,0.0006255426,0.00051192794,0.00041755332,0.0019959281,0.00029997353,0.0087232655],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9944258,0.0027027603,0.00037557835,0.0012354011,0.0008212231,0.0004392736],"domain_scores_gemma":[0.9109234,0.07229689,0.0049448498,0.008788355,0.002277052,0.00076942134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.022580422,0.001338843,0.0032186941,0.0020681699,0.0007896233,0.002493213,0.005567659,0.0025196308,0.0043294583],"category_scores_gemma":[0.10666487,0.0017641749,0.0022225208,0.0026890312,0.0036916777,0.0068735103,0.0039617037,0.00482519,0.0008938893],"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":[0.0006612712,0.00021031576,0.013689907,0.0006421276,0.0005217955,0.00055977114,0.0006146948,0.37329838,0.0023070886,0.48117828,0.0036478522,0.12266836],"study_design_scores_gemma":[0.00005361879,0.000056452354,0.0016230464,0.000063833184,0.000052371517,0.00014707018,0.00006817427,0.6597144,0.0008219407,0.33651927,0.0008405575,0.000039290382],"about_ca_topic_score_codex":0.0035699236,"about_ca_topic_score_gemma":0.0035794077,"teacher_disagreement_score":0.022580422,"about_ca_system_score_codex":0.0017819521,"about_ca_system_score_gemma":0.002088801,"threshold_uncertainty_score":0.119418144},"labels":[],"label_agreement":null},{"id":"W1997198246","doi":"10.1007/s00184-006-0078-3","title":"Estimation and optimal designs for linear Haar-wavelet models","year":2006,"lang":"en","type":"article","venue":"Metrika","topic":"Mathematical functions and polynomials","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Mathematics; Estimator; Haar; Best linear unbiased prediction; Eigenvalues and eigenvectors; Applied mathematics; Linear model; Expression (computer science); Haar wavelet; Covariance matrix; Wavelet; Matrix (chemical analysis); Mathematical optimization; Discrete wavelet transform; Algorithm; Statistics; Wavelet transform; Computer science; Artificial intelligence","score_opus":0.14253978824662672,"score_gpt":0.3412996294473144,"score_spread":0.19875984120068768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997198246","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":[0.0025124254,0.00015681669,0.9969503,0.00007331237,0.000016501159,0.000012641179,0.000019239811,0.000038800972,0.00021993069],"genre_scores_gemma":[0.26140642,0.0014999186,0.7324875,0.00019837113,0.00022846233,0.0004653232,0.00043750272,0.00015314702,0.003123335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9942426,0.0035867665,0.00025497525,0.00086807983,0.00074149226,0.00030615975],"domain_scores_gemma":[0.9837172,0.012271756,0.0011948099,0.0011723486,0.0013728447,0.00027099435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010104514,0.0015568747,0.0018354903,0.0010414897,0.00056630245,0.0018070516,0.0017214089,0.0026084972,0.0029293394],"category_scores_gemma":[0.039807104,0.0020825802,0.0012554647,0.0010727211,0.00196233,0.003171552,0.002284712,0.0028240413,0.0010744301],"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":[0.00068226096,0.00020443658,0.0011472848,0.00064709916,0.00025882668,0.00009863014,0.0003163469,0.4198395,0.009343881,0.3518235,0.0020881097,0.21355024],"study_design_scores_gemma":[0.00005855287,0.00016354572,0.00024347288,0.000059171583,0.000061017938,0.000049183927,0.0000344382,0.8661811,0.0026203124,0.1290038,0.0014819195,0.000043423457],"about_ca_topic_score_codex":0.0008843577,"about_ca_topic_score_gemma":0.0010822801,"teacher_disagreement_score":0.010104514,"about_ca_system_score_codex":0.0009640698,"about_ca_system_score_gemma":0.0018016659,"threshold_uncertainty_score":0.053438365},"labels":[],"label_agreement":null},{"id":"W1997870135","doi":"10.1007/s00184-008-0181-8","title":"Reconstruction of past records","year":2008,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Australian National University","keywords":"Mathematics; Pareto principle; Reliability (semiconductor); Epoch (astronomy); Exponential function; Poisson distribution; Homogeneous; Poisson process; Set (abstract data type); Statistics; Exponential distribution; Pareto distribution; Applied mathematics; Combinatorics; Computer science; Mathematical analysis","score_opus":0.1204718695031669,"score_gpt":0.3540741290207192,"score_spread":0.2336022595175523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997870135","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11322164,0.0014312001,0.879605,0.0007027459,0.00016246036,0.000024463183,0.001423975,0.0008667019,0.002561794],"genre_scores_gemma":[0.7959049,0.0017956451,0.19316882,0.00007123022,0.00019913344,0.000033856253,0.0030922813,0.00015301866,0.005581149],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996598,0.00007646257,0.000021236414,0.00014210872,0.00006527118,0.000035099583],"domain_scores_gemma":[0.99868983,0.0004949885,0.0001517705,0.00042955522,0.00017362082,0.000060241873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008081036,0.0004310456,0.00055893045,0.0016601093,0.00035653057,0.0015436021,0.0010727993,0.0009655291,0.0026995928],"category_scores_gemma":[0.005510526,0.000650055,0.00074119854,0.0018484191,0.00064187264,0.002409424,0.0008285598,0.0012669058,0.0015071601],"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":[0.00075610285,0.0001265655,0.031141616,0.0004489386,0.00029889517,0.00057078886,0.00054591574,0.36567175,0.019670224,0.069048494,0.0062910733,0.5054297],"study_design_scores_gemma":[0.000020556014,0.00003912198,0.007947351,0.000051189225,0.00004173439,0.0003031868,0.00011546423,0.94435847,0.004460801,0.035622057,0.007007726,0.000032236],"about_ca_topic_score_codex":0.0035894834,"about_ca_topic_score_gemma":0.0028643913,"teacher_disagreement_score":0.0035894834,"about_ca_system_score_codex":0.00040157425,"about_ca_system_score_gemma":0.0005378218,"threshold_uncertainty_score":0.009030998},"labels":[],"label_agreement":null},{"id":"W2001327040","doi":"10.1007/s00184-006-0028-0","title":"Some Improved Tests for Multivariate One-Sided Hypotheses","year":2006,"lang":"en","type":"article","venue":"Metrika","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Science Foundation","keywords":"Mathematics; Multivariate statistics; Intersection (aeronautics); Statistical hypothesis testing; Statistics; Null hypothesis; Boundary (topology); Multivariate analysis; Null (SQL); Likelihood-ratio test; Score test; Econometrics; Data mining; Computer science; Mathematical analysis","score_opus":0.22358334188613477,"score_gpt":0.43935482387969393,"score_spread":0.21577148199355917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001327040","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":[0.009460067,0.0008686114,0.9849311,0.00064602407,0.0003865249,0.00016277061,0.00058117555,0.0005740919,0.0023896133],"genre_scores_gemma":[0.10694444,0.0008354739,0.88102925,0.0008166036,0.0019931484,0.0009484266,0.0018505558,0.00042838437,0.0051537557],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9653728,0.023371525,0.0019288707,0.0035229975,0.0049077147,0.0008960476],"domain_scores_gemma":[0.771085,0.19965914,0.004994734,0.014747635,0.008009004,0.0015043321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04608582,0.0030728942,0.004241744,0.005702229,0.0016642547,0.0032131623,0.0068623805,0.0028030442,0.021842042],"category_scores_gemma":[0.18178476,0.0014764316,0.004719359,0.0058410433,0.0042995,0.0072675543,0.0044979057,0.0070294,0.0032273661],"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":[0.0024925678,0.00050580775,0.0088081835,0.001809752,0.0016366736,0.0012852732,0.0008575388,0.02614887,0.007054615,0.35826284,0.018978314,0.5721595],"study_design_scores_gemma":[0.0007385978,0.0011921165,0.010651776,0.00029179687,0.0012811163,0.0012247987,0.00024239674,0.20354171,0.0058557815,0.7560711,0.018607227,0.00030150166],"about_ca_topic_score_codex":0.0010114994,"about_ca_topic_score_gemma":0.0014832803,"teacher_disagreement_score":0.04608582,"about_ca_system_score_codex":0.0015653283,"about_ca_system_score_gemma":0.0027294154,"threshold_uncertainty_score":0.24372804},"labels":[],"label_agreement":null},{"id":"W2007332315","doi":"10.1007/s00184-010-0297-5","title":"Dispersive ordering of fail-safe systems with heterogeneous exponential components","year":2010,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Science Foundation","keywords":"Mathematics; Order statistic; Lambda; Combinatorics; Independent and identically distributed random variables; Order (exchange); Exponential distribution; Random variable; Exponential function; Hazard ratio; Statistics; Discrete mathematics; Mathematical analysis; Confidence interval; Physics","score_opus":0.052196978781856085,"score_gpt":0.3174588659834167,"score_spread":0.26526188720156063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007332315","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20855758,0.00030041052,0.78533626,0.0004912933,0.00007290146,0.000051481595,0.00017662582,0.00019768422,0.0048157405],"genre_scores_gemma":[0.97217834,0.00027313817,0.020676522,0.000082086066,0.000073101386,0.00006643464,0.00016824281,0.000073460316,0.0064086216],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99846077,0.00030984674,0.00009671285,0.00022236437,0.000623603,0.00028671284],"domain_scores_gemma":[0.9891166,0.0053984127,0.0020891572,0.0007229325,0.0017186349,0.00095420185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020967976,0.001076734,0.0013652049,0.0019012982,0.0010433149,0.0021416333,0.0015799069,0.0010449508,0.0028411031],"category_scores_gemma":[0.012222596,0.00066377356,0.00061661616,0.0010309701,0.002098963,0.0026328508,0.0021720736,0.0015974606,0.00033955954],"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":[0.00051397516,0.00009234404,0.0032991124,0.00013796563,0.00008419607,0.00085498113,0.00047852343,0.37701035,0.009232969,0.5919654,0.0012710517,0.015059081],"study_design_scores_gemma":[0.000018465907,0.00008344652,0.00074993295,0.000014749568,0.000021900842,0.00009964256,0.00010305056,0.82578087,0.0015237964,0.17102304,0.0005533378,0.000027866921],"about_ca_topic_score_codex":0.0026319092,"about_ca_topic_score_gemma":0.0022874312,"teacher_disagreement_score":0.0028411031,"about_ca_system_score_codex":0.0016003737,"about_ca_system_score_gemma":0.0013326672,"threshold_uncertainty_score":0.011611521},"labels":[],"label_agreement":null},{"id":"W2007573942","doi":"10.1007/s00184-005-0404-1","title":"A recursive method for orthogonal designs","year":2005,"lang":"en","type":"article","venue":"Metrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge; University of Manitoba","funders":"","keywords":"Mathematics; Class (philosophy); Orthogonal array; Algorithm; Algebra over a field; Applied mathematics; Computer science; Pure mathematics; Artificial intelligence; Statistics","score_opus":0.35246597602917273,"score_gpt":0.5510554251208561,"score_spread":0.1985894490916834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007573942","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":[0.00026875432,0.000051173156,0.99937016,0.000018088478,0.000014779177,0.00004286316,0.000012355851,0.00006946916,0.00015240171],"genre_scores_gemma":[0.011521973,0.00012893946,0.9863381,0.000060039147,0.000044824155,0.00076814275,0.00005376729,0.0000921371,0.0009920561],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9774984,0.017970793,0.0006129218,0.0014291354,0.0020073026,0.00048140125],"domain_scores_gemma":[0.97208357,0.02283929,0.00095616194,0.0023986886,0.0015172075,0.00020509354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019196965,0.0018021882,0.0029481817,0.0018125906,0.0009376889,0.0013709598,0.002612737,0.0019778693,0.010120662],"category_scores_gemma":[0.044473037,0.0017576154,0.0031182026,0.0017582555,0.00221338,0.0021935145,0.0024739348,0.0035929454,0.0025718575],"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":[0.0006432425,0.00030213923,0.000574616,0.0009551672,0.00049107586,0.000092853195,0.0003563562,0.0679583,0.008049289,0.46668428,0.0039091352,0.4499837],"study_design_scores_gemma":[0.00051775173,0.0009502658,0.0010931314,0.0002656327,0.0003722682,0.00026369173,0.000061628685,0.6668012,0.0071412236,0.29397964,0.028378004,0.00017556245],"about_ca_topic_score_codex":0.0020431576,"about_ca_topic_score_gemma":0.0031905246,"teacher_disagreement_score":0.019196965,"about_ca_system_score_codex":0.0012359022,"about_ca_system_score_gemma":0.0036887869,"threshold_uncertainty_score":0.10152453},"labels":[],"label_agreement":null},{"id":"W2008954435","doi":"10.1007/s00184-011-0359-3","title":"Robust analysis of longitudinal data with nonignorable missing responses","year":2011,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Missing data; Outlier; Estimator; Longitudinal data; Statistics; Mathematics; Robust statistics; Maximum likelihood; Econometrics; Computer science; Data mining","score_opus":0.41964674663354634,"score_gpt":0.41038221634336625,"score_spread":0.009264530290180095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008954435","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":[0.0019812963,0.0006990237,0.9964714,0.00032566453,0.000054204073,0.00003306749,0.00016331399,0.00013729314,0.00013475069],"genre_scores_gemma":[0.18082175,0.0031491201,0.80709183,0.00048438986,0.00071497646,0.0012425956,0.0016263883,0.0004314844,0.0044375504],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9663105,0.026159948,0.0013926411,0.0034552256,0.002051348,0.00063024595],"domain_scores_gemma":[0.8390761,0.1374448,0.007469251,0.011763502,0.0035123462,0.0007341157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.052574854,0.0018656584,0.004435734,0.002807071,0.0010306083,0.0025366852,0.0062348093,0.0024162082,0.00413537],"category_scores_gemma":[0.18196677,0.0020659163,0.0037330254,0.0030966483,0.002993492,0.0031182724,0.0033544288,0.004575608,0.0008894654],"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":[0.00088791765,0.00026368035,0.005845984,0.0018304074,0.00482446,0.0007476556,0.0005545851,0.16665053,0.0023045167,0.614821,0.008127007,0.19314227],"study_design_scores_gemma":[0.00012103493,0.00011132931,0.0016537805,0.00014337632,0.00033475083,0.00017455779,0.00005602491,0.3873316,0.00082574715,0.6055059,0.0036789405,0.000062984735],"about_ca_topic_score_codex":0.005243961,"about_ca_topic_score_gemma":0.0041253963,"teacher_disagreement_score":0.052574854,"about_ca_system_score_codex":0.0015083539,"about_ca_system_score_gemma":0.004144647,"threshold_uncertainty_score":0.27804577},"labels":[],"label_agreement":null},{"id":"W2009876446","doi":"10.1007/s00184-009-0243-6","title":"Stochastic monotonicity of the MLEs of parameters in exponential simple step-stress models under Type-I and Type-II censoring","year":2009,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Monotone polygon; Censoring (clinical trials); Applied mathematics; Trinomial; Estimator; Type (biology); Exponential function; Monotonic function; Simple (philosophy); Exponential family; Statistics; Combinatorics; Mathematical analysis","score_opus":0.09751186175116561,"score_gpt":0.35212801472286426,"score_spread":0.25461615297169865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009876446","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18401456,0.0011358471,0.8063194,0.0028466242,0.000085734966,0.00010951612,0.0009638596,0.00037247824,0.004151946],"genre_scores_gemma":[0.93818474,0.0016563772,0.05305406,0.00051920617,0.00033876274,0.0003272894,0.0011847572,0.00028839448,0.004446299],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9947049,0.003087638,0.000287818,0.0008897788,0.00055652345,0.0004734626],"domain_scores_gemma":[0.792276,0.18764383,0.008648233,0.0066303276,0.0033569285,0.0014447066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023754071,0.001339771,0.0032979634,0.0018258109,0.0006062031,0.0034640243,0.003939808,0.0026050059,0.0059016114],"category_scores_gemma":[0.17046164,0.001999869,0.0018501908,0.0016152244,0.00674049,0.007840829,0.0026106702,0.0053678616,0.00073290244],"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":[0.0007566383,0.00023391817,0.02771565,0.0010781391,0.00048046466,0.0011335528,0.0013182496,0.2634946,0.0049471483,0.6524967,0.0032154473,0.043129448],"study_design_scores_gemma":[0.00008985818,0.00012338393,0.008106499,0.0001505796,0.00010240061,0.00055225793,0.00023868239,0.56918657,0.0013329175,0.41907892,0.0009317527,0.00010627173],"about_ca_topic_score_codex":0.0021669278,"about_ca_topic_score_gemma":0.0016900935,"teacher_disagreement_score":0.023754071,"about_ca_system_score_codex":0.001225798,"about_ca_system_score_gemma":0.00150389,"threshold_uncertainty_score":0.12562507},"labels":[],"label_agreement":null},{"id":"W2010246637","doi":"10.1007/s00184-012-0389-5","title":"D-optimal two-level orthogonal arrays for estimating main effects and some specified two-factor interactions","year":2012,"lang":"en","type":"article","venue":"Metrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Victoria","keywords":"Mathematics; Orthogonal array; Orthogonal matrix; Factor (programming language); Matrix (chemical analysis); Combinatorics; Construct (python library); Applied mathematics; Mathematical optimization; Algorithm; Orthogonal basis; Statistics; Taguchi methods; Computer science","score_opus":0.24529758869099522,"score_gpt":0.4749035942362205,"score_spread":0.2296060055452253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010246637","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":[0.0013907583,0.00007624481,0.99805695,0.000045091434,0.0000143273965,0.00006286158,0.00007583054,0.00013864339,0.00013935324],"genre_scores_gemma":[0.028196352,0.00008398751,0.96989286,0.00010126412,0.000023739154,0.0009873338,0.00022206634,0.00008923395,0.00040320383],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9674605,0.025889436,0.001069571,0.0031626304,0.001574675,0.00084311276],"domain_scores_gemma":[0.9304754,0.06124373,0.0016834105,0.004487263,0.0016363891,0.00047370605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02313112,0.0024579908,0.0034799697,0.0015724623,0.0007847983,0.0016322674,0.0026823706,0.0029671083,0.0059994794],"category_scores_gemma":[0.076892376,0.0022079728,0.0035154552,0.0020959426,0.0026910575,0.00222587,0.003365675,0.0031074025,0.0014782399],"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":[0.0056236377,0.0008985399,0.0034667132,0.0019263697,0.0014186689,0.000253034,0.00064643344,0.22298484,0.027982736,0.22795866,0.0049179373,0.50192255],"study_design_scores_gemma":[0.0007945188,0.0009889841,0.002324411,0.00016698804,0.0002849108,0.0001995983,0.00010872462,0.78498656,0.013068772,0.19106391,0.0058401283,0.00017247029],"about_ca_topic_score_codex":0.0014276686,"about_ca_topic_score_gemma":0.0016005596,"teacher_disagreement_score":0.02313112,"about_ca_system_score_codex":0.0011310424,"about_ca_system_score_gemma":0.0030252652,"threshold_uncertainty_score":0.12233049},"labels":[],"label_agreement":null},{"id":"W2013198476","doi":"10.1007/s00184-008-0182-7","title":"Existence of balanced sampling plans avoiding cyclic distances","year":2008,"lang":"en","type":"article","venue":"Metrika","topic":"graph theory and CDMA systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Mathematics; Sampling (signal processing); Statistics; Calculus (dental); Orthodontics; Computer science; Telecommunications","score_opus":0.03748381395675505,"score_gpt":0.22632852735766015,"score_spread":0.1888447134009051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013198476","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38923433,0.0006651227,0.582987,0.00087429653,0.000053017455,0.00021371152,0.00076704205,0.00052362273,0.024681913],"genre_scores_gemma":[0.7828075,0.00074487255,0.20240241,0.00026677392,0.0000619489,0.00045735162,0.0012098952,0.0002487619,0.011800442],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99885464,0.0003181657,0.000046016346,0.00019158216,0.00032364612,0.00026599487],"domain_scores_gemma":[0.99132115,0.0060190083,0.0007957648,0.0006265532,0.0006397142,0.0005978704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012394511,0.0007882302,0.0011748647,0.0014066786,0.0012293514,0.0025803188,0.0014401486,0.0015096427,0.006252665],"category_scores_gemma":[0.012242589,0.0012011926,0.000653053,0.0017993143,0.0014965193,0.0025458774,0.002528748,0.0016391004,0.00072345696],"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":[0.00082815625,0.00018936781,0.0018927221,0.00025256953,0.000076971046,0.00021440041,0.00046427228,0.112093225,0.011900371,0.8207667,0.004890264,0.046431143],"study_design_scores_gemma":[0.00018733653,0.00017534627,0.0007367682,0.000060901162,0.000039593786,0.00021583955,0.00024609087,0.47120148,0.0054781996,0.51805234,0.0035702302,0.000035832756],"about_ca_topic_score_codex":0.0019804658,"about_ca_topic_score_gemma":0.0019928461,"teacher_disagreement_score":0.006252665,"about_ca_system_score_codex":0.0014801268,"about_ca_system_score_gemma":0.0018275889,"threshold_uncertainty_score":0.020917296},"labels":[],"label_agreement":null},{"id":"W2014482732","doi":"10.1007/s00184-014-0503-y","title":"Applications of the Rosenthal-type inequality for negatively superadditive dependent random variables","year":2014,"lang":"en","type":"article","venue":"Metrika","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":77,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Superadditivity; Mathematics; Independent and identically distributed random variables; Random variable; Estimator; Type (biology); Consistency (knowledge bases); Sequence (biology); Inequality; Statistics; Discrete mathematics; Mathematical economics; Mathematical analysis","score_opus":0.10116082806676391,"score_gpt":0.3733441551468434,"score_spread":0.2721833270800795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014482732","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02126183,0.003774985,0.9345915,0.004708298,0.00023321915,0.0000612262,0.00024234426,0.00006458308,0.03506197],"genre_scores_gemma":[0.6767902,0.00982219,0.28296235,0.0015260312,0.0016981973,0.0004987261,0.00035534555,0.00014438835,0.02620257],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99424666,0.003345453,0.00025148908,0.00063790835,0.0011573689,0.0003611289],"domain_scores_gemma":[0.9651027,0.029158488,0.0015056663,0.001489966,0.0020541556,0.00068899104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012079849,0.0017475538,0.0024865414,0.0028865247,0.0014611891,0.0032046714,0.0026318317,0.002344485,0.006344367],"category_scores_gemma":[0.03415308,0.0009134959,0.002859419,0.0028126275,0.0064912215,0.0068147117,0.004821521,0.0067892633,0.00047951794],"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":[0.0000094701345,0.000011935326,0.00019791789,0.00004229839,0.00002471487,0.00003766692,0.00007090021,0.005684447,0.00012494446,0.9907053,0.00044087286,0.0026494612],"study_design_scores_gemma":[0.000006738732,0.0000107844335,0.00014482613,0.000022816912,0.000011806603,0.000030197072,0.000017613878,0.039531898,0.000066071996,0.95935273,0.00079320616,0.00001135588],"about_ca_topic_score_codex":0.004233718,"about_ca_topic_score_gemma":0.0042944406,"teacher_disagreement_score":0.012079849,"about_ca_system_score_codex":0.004369736,"about_ca_system_score_gemma":0.0027907304,"threshold_uncertainty_score":0.06388509},"labels":[],"label_agreement":null},{"id":"W2017277832","doi":"10.1007/s00184-014-0508-6","title":"Limit results for concomitants of order statistics","year":2014,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Limit (mathematics); Lemma (botany); Order statistic; Statistics; Order (exchange); Mathematical statistics; Applied mathematics; Calculus (dental); Mathematical economics; Mathematical analysis","score_opus":0.1149128916902165,"score_gpt":0.399142740989464,"score_spread":0.2842298492992475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017277832","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05594425,0.0048672557,0.898959,0.003902861,0.000493401,0.000059548813,0.00045599852,0.0003581987,0.034959555],"genre_scores_gemma":[0.725991,0.0107995495,0.21570033,0.0023336383,0.003263238,0.0005568778,0.0009798027,0.0009004776,0.03947512],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99502385,0.00202544,0.00039504998,0.00081827614,0.0013000751,0.00043746736],"domain_scores_gemma":[0.928792,0.05490342,0.0040250067,0.0033533922,0.0056612464,0.0032648777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013636708,0.0018953435,0.0027916448,0.0070730858,0.0028618183,0.006387537,0.004029386,0.0028380393,0.008824946],"category_scores_gemma":[0.0758255,0.0015857877,0.0030744972,0.005847241,0.009037191,0.019267173,0.007364978,0.008862137,0.0013229467],"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":[0.000023277453,0.000020123987,0.00032757747,0.00006816913,0.000019953144,0.000059193848,0.00016392852,0.000995327,0.00018226852,0.9948337,0.00048724882,0.0028192475],"study_design_scores_gemma":[0.000009691022,0.000016170145,0.00020774295,0.000026830568,0.000022748842,0.00010115946,0.000040580006,0.017447717,0.00014520898,0.98059183,0.0013728561,0.000017618335],"about_ca_topic_score_codex":0.0025419912,"about_ca_topic_score_gemma":0.002042442,"teacher_disagreement_score":0.013636708,"about_ca_system_score_codex":0.003379571,"about_ca_system_score_gemma":0.002327157,"threshold_uncertainty_score":0.07211864},"labels":[],"label_agreement":null},{"id":"W2018021189","doi":"10.1007/s00184-013-0463-7","title":"Optimal and robust designs for trigonometric regression models","year":2013,"lang":"en","type":"article","venue":"Metrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Trigonometry; Mathematics; Minimax; Optimal design; Trigonometric functions; Regression analysis; Applied mathematics; Regression; Differentiation of trigonometric functions; Function (biology); Inverse trigonometric functions; Mathematical optimization; Algorithm; Statistics; Mathematical analysis","score_opus":0.3965849092122878,"score_gpt":0.44954812061816074,"score_spread":0.052963211405872956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018021189","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025753682,0.0001832656,0.99651116,0.00008255018,0.00002832139,0.00009463225,0.00003577576,0.000087627006,0.00040130585],"genre_scores_gemma":[0.19046362,0.00051317445,0.8050384,0.00017605985,0.00011679885,0.0020169716,0.00019556134,0.00012934447,0.0013500485],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.94356704,0.046755966,0.0012251879,0.0041183666,0.003400967,0.0009324717],"domain_scores_gemma":[0.9273336,0.05963439,0.005682104,0.0042720665,0.0026161992,0.00046164016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.043591097,0.0025180217,0.0035958332,0.0017411653,0.00063947076,0.002116381,0.0029810767,0.0032098864,0.005289828],"category_scores_gemma":[0.10768103,0.0023750744,0.0026798372,0.001211786,0.0032792888,0.002695011,0.0026257357,0.0031816564,0.0010316176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024872916,0.00052665325,0.0010252673,0.0016573074,0.00076629827,0.00010883475,0.0003004482,0.4230445,0.00830821,0.39068964,0.0014364811,0.1696491],"study_design_scores_gemma":[0.00056977634,0.001310243,0.0010171494,0.00019273345,0.00023453435,0.000056578323,0.000051763647,0.74908096,0.0055133426,0.2385993,0.0032645636,0.000109107925],"about_ca_topic_score_codex":0.0008471145,"about_ca_topic_score_gemma":0.00073222205,"teacher_disagreement_score":0.043591097,"about_ca_system_score_codex":0.0018433013,"about_ca_system_score_gemma":0.0034965002,"threshold_uncertainty_score":0.2305345},"labels":[],"label_agreement":null},{"id":"W2019555413","doi":"10.1007/s00184-007-0141-8","title":"A new class of inverse Gaussian type distributions","year":2007,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Outlier; Inverse Gaussian distribution; Applied mathematics; Probability density function; Gaussian; Likelihood function; Kernel (algebra); Inverse distribution; Kernel density estimation; Distribution (mathematics); Probability distribution; Heavy-tailed distribution; Statistics; Estimation theory; Mathematical analysis; Combinatorics; Estimator","score_opus":0.08475922801872311,"score_gpt":0.3859026734270121,"score_spread":0.301143445408289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019555413","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":[0.011172547,0.0006741009,0.97873265,0.00036662133,0.00018476372,0.000027373146,0.000116374424,0.00026586442,0.008459809],"genre_scores_gemma":[0.5169337,0.0032826161,0.43329674,0.0016064938,0.0018879545,0.0003453019,0.00098708,0.00086320087,0.040796883],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978764,0.0005709383,0.00009328394,0.0005317965,0.0007192538,0.00020844964],"domain_scores_gemma":[0.995717,0.0017008653,0.00050243974,0.0006688666,0.0010701219,0.00034071036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027075603,0.0011127642,0.0015196285,0.0024518417,0.0011732706,0.003454349,0.002262808,0.0019213622,0.0039866827],"category_scores_gemma":[0.011955335,0.00078146067,0.001817713,0.0017673345,0.002723204,0.0037638939,0.0026796588,0.0042674625,0.0014077987],"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":[0.00006646709,0.000033467266,0.0010907243,0.00007041431,0.000041094874,0.00017725858,0.0002081891,0.008927085,0.002354054,0.95000577,0.003666449,0.03335891],"study_design_scores_gemma":[0.00002591333,0.00004974294,0.00077314273,0.0000431233,0.000032435062,0.0011144006,0.00008160499,0.22102316,0.0012575445,0.75697625,0.018560104,0.00006259843],"about_ca_topic_score_codex":0.0010714419,"about_ca_topic_score_gemma":0.0007969797,"teacher_disagreement_score":0.0039866827,"about_ca_system_score_codex":0.0011365577,"about_ca_system_score_gemma":0.0011703846,"threshold_uncertainty_score":0.014319122},"labels":[],"label_agreement":null},{"id":"W2020963260","doi":"10.1007/s00184-012-0423-7","title":"On properties of dependent progressively Type-II censored order statistics","year":2012,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Order statistic; Censoring (clinical trials); Copula (linguistics); Statistics; Econometrics","score_opus":0.11182406925507823,"score_gpt":0.3693720222960685,"score_spread":0.2575479530409903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020963260","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040069357,0.001590255,0.94956076,0.0012278568,0.00013336836,0.00007514443,0.0005067453,0.0002515928,0.006584911],"genre_scores_gemma":[0.7493982,0.0076790582,0.21497475,0.0015309664,0.001436895,0.000717192,0.002243908,0.0008522618,0.021166861],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9941229,0.0030103032,0.00036907475,0.0008592813,0.0012112142,0.00042733306],"domain_scores_gemma":[0.80347556,0.16643363,0.010261662,0.0095603615,0.00742283,0.0028459271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.022801714,0.0019065376,0.0026280605,0.0040774234,0.0012422233,0.0038535823,0.0037481277,0.0024379152,0.005267579],"category_scores_gemma":[0.14214239,0.0014856848,0.0024989126,0.0038997412,0.007358556,0.0100448225,0.0038859139,0.006815461,0.0010644236],"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":[0.00015285019,0.00006674418,0.0034335682,0.00024806464,0.0000903214,0.00026874032,0.0005707737,0.03450727,0.0016977477,0.94221026,0.001802433,0.014951156],"study_design_scores_gemma":[0.000029457411,0.00007986587,0.0017253193,0.00010869811,0.000053910342,0.00030157744,0.000104266706,0.27922547,0.00083973445,0.71595764,0.0015092074,0.000064873],"about_ca_topic_score_codex":0.0029162962,"about_ca_topic_score_gemma":0.002144414,"teacher_disagreement_score":0.022801714,"about_ca_system_score_codex":0.0025002859,"about_ca_system_score_gemma":0.0025418606,"threshold_uncertainty_score":0.12058842},"labels":[],"label_agreement":null},{"id":"W2023060931","doi":"10.1007/s00184-008-0173-8","title":"Minimax robust designs for field experiments","year":2008,"lang":"en","type":"article","venue":"Metrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Minimax; Mathematics; Estimator; Covariance matrix; Covariance; Mathematical optimization; Field (mathematics); Optimal design; Least-squares function approximation; Robust statistics; Spatial correlation; Algorithm; Statistics","score_opus":0.6510149411035311,"score_gpt":0.5186700726877603,"score_spread":0.13234486841577076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023060931","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00080925255,0.00023741992,0.99828786,0.000073456664,0.000023610097,0.00009005318,0.000034810164,0.000080830076,0.00036263064],"genre_scores_gemma":[0.11299853,0.0007144328,0.8782745,0.00025307582,0.00016766452,0.0040688543,0.00025853704,0.00019052968,0.0030739375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9719644,0.022733385,0.0006596721,0.002445285,0.0017074152,0.0004898683],"domain_scores_gemma":[0.94199353,0.050425325,0.0029290193,0.0025991157,0.0016656525,0.00038732617],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03657962,0.0036826124,0.005258637,0.002041924,0.0008153769,0.0022291404,0.0035095352,0.0035540743,0.0062943804],"category_scores_gemma":[0.06897468,0.0028052682,0.0026207564,0.0013517843,0.0040048026,0.0025573703,0.0033053854,0.004763102,0.0012094013],"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":[0.001912465,0.00031138986,0.000604681,0.001759743,0.0008129232,0.00009765154,0.00025493503,0.46276832,0.0052144984,0.38692075,0.0026460947,0.1366966],"study_design_scores_gemma":[0.00047258916,0.00076121534,0.00050305104,0.00015679926,0.00012594921,0.00004916754,0.0000242381,0.74836546,0.0026762206,0.24276572,0.00403498,0.00006461484],"about_ca_topic_score_codex":0.0008783143,"about_ca_topic_score_gemma":0.00068526564,"teacher_disagreement_score":0.9634204,"about_ca_system_score_codex":0.0020028127,"about_ca_system_score_gemma":0.0031409706,"threshold_uncertainty_score":0.19345385},"labels":[],"label_agreement":null},{"id":"W2026258530","doi":"10.1007/s00184-015-0541-0","title":"Generalized projection discrepancy and its applications in experimental designs","year":2015,"lang":"en","type":"article","venue":"Metrika","topic":"Mathematical Approximation and Integration","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Natural Science Foundation of China","keywords":"Chatterjee; Mathematics; Projection (relational algebra); Inference; Measure (data warehouse); Applied mathematics; Combinatorics; Algorithm; Artificial intelligence; Computer science","score_opus":0.22396660817008993,"score_gpt":0.39846148550170424,"score_spread":0.1744948773316143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026258530","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":[0.0030277874,0.0006729713,0.994749,0.00038759082,0.000086670414,0.00004664197,0.000046433644,0.00007929256,0.0009035361],"genre_scores_gemma":[0.19038379,0.0012246412,0.80257094,0.000587638,0.00039061558,0.0012385482,0.00025777175,0.00024084092,0.003105196],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.92378825,0.0626328,0.0023940215,0.0048119132,0.0056463517,0.0007266918],"domain_scores_gemma":[0.64497524,0.31688753,0.008565896,0.019565895,0.008371881,0.0016335723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08314241,0.002496558,0.0053783758,0.003957087,0.0015706044,0.004103338,0.0049614636,0.005267337,0.004170235],"category_scores_gemma":[0.25449738,0.0025807042,0.0031707212,0.0047288784,0.0122724315,0.006636729,0.0091249,0.0055144755,0.0005982196],"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":[0.00030081053,0.000068572044,0.001595236,0.00041478296,0.0002444691,0.00011551999,0.00040987553,0.045791287,0.0005172879,0.9124505,0.0010502816,0.037041444],"study_design_scores_gemma":[0.00007188781,0.00012764207,0.00061403256,0.000098675824,0.00006116034,0.0001552088,0.000073835385,0.2045864,0.00036795338,0.7914194,0.0023798898,0.000043951677],"about_ca_topic_score_codex":0.00174843,"about_ca_topic_score_gemma":0.00085304456,"teacher_disagreement_score":0.08314241,"about_ca_system_score_codex":0.0034291316,"about_ca_system_score_gemma":0.004825156,"threshold_uncertainty_score":0.43970436},"labels":[],"label_agreement":null},{"id":"W2032200036","doi":"10.1007/s00184-010-0331-7","title":"Parametric inference from system lifetime data under a proportional hazard rate model","year":2010,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Ministerio de Ciencia y Tecnología; Chinese University of Hong Kong; University of Hong Kong","keywords":"Mathematics; Estimator; Applied mathematics; Monte Carlo method; Parametric statistics; Statistical inference; Inference; Method of moments (probability theory); Statistics; Exponential distribution; Algorithm; Computer science","score_opus":0.18810501568332402,"score_gpt":0.4117774269083066,"score_spread":0.22367241122498258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032200036","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02640262,0.00013535962,0.9722487,0.00027743704,0.000022352206,0.00004044247,0.00019825564,0.00019957976,0.00047516968],"genre_scores_gemma":[0.7749005,0.0007818491,0.2163833,0.00023328973,0.00021869528,0.0003852755,0.0016815187,0.00021712978,0.005198455],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9932462,0.0041090455,0.00031850018,0.001273982,0.00072414026,0.0003280556],"domain_scores_gemma":[0.8851293,0.10325151,0.0041293693,0.0053852242,0.001731975,0.0003727663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024559408,0.0009142944,0.0021831673,0.0019731768,0.0005839802,0.0023863951,0.0035941454,0.0016935349,0.004901008],"category_scores_gemma":[0.12135249,0.0012434905,0.0021514036,0.0021198904,0.0021896907,0.00529162,0.0024366525,0.00372841,0.00064496446],"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":[0.00068626116,0.0002723288,0.018585572,0.000529314,0.0006504284,0.00059719576,0.00094687875,0.51243764,0.0020315666,0.31511605,0.0026502248,0.14549652],"study_design_scores_gemma":[0.000047521567,0.000074980126,0.0016994496,0.000029186755,0.00006342789,0.00013773264,0.00006890176,0.81788087,0.00062605774,0.17864858,0.0006990586,0.000024205483],"about_ca_topic_score_codex":0.0035127467,"about_ca_topic_score_gemma":0.0017336922,"teacher_disagreement_score":0.024559408,"about_ca_system_score_codex":0.0009903164,"about_ca_system_score_gemma":0.0016658724,"threshold_uncertainty_score":0.12988412},"labels":[],"label_agreement":null},{"id":"W2034067380","doi":"10.1007/s00184-012-0410-z","title":"A moment-based test for extreme-value dependence","year":2012,"lang":"en","type":"article","venue":"Metrika","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Mathematics; Test statistic; Estimator; Applied mathematics; Bivariate analysis; Copula (linguistics); Statistics; Computation; Statistical hypothesis testing; Algorithm; Econometrics","score_opus":0.29693236870418277,"score_gpt":0.4142410493822738,"score_spread":0.11730868067809103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034067380","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":[0.22866507,0.00042592984,0.7606796,0.0012385487,0.00015454649,0.00018288937,0.000978011,0.0006902811,0.006985152],"genre_scores_gemma":[0.916211,0.00013392641,0.079431765,0.00031786857,0.00028698222,0.0002910968,0.00137647,0.00010232784,0.0018484816],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9825393,0.010847195,0.0008697483,0.0022383824,0.0027499483,0.0007554166],"domain_scores_gemma":[0.74913996,0.22775544,0.007422248,0.009244689,0.0042194915,0.002218137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019397406,0.0008481903,0.0023996867,0.005049071,0.0010703126,0.002564586,0.0031248364,0.0029833282,0.011166337],"category_scores_gemma":[0.14574802,0.000525776,0.0021157789,0.0026861401,0.0030162625,0.0047874977,0.0037734627,0.0030202945,0.0010621323],"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":[0.008264488,0.0018760249,0.16794589,0.00075432076,0.003836032,0.0022357395,0.000806983,0.12563652,0.013427082,0.38455305,0.009827795,0.28083614],"study_design_scores_gemma":[0.00048776556,0.0019711007,0.043057404,0.00013873252,0.0003192691,0.001877632,0.00032859555,0.72200644,0.003392021,0.22308455,0.0031253665,0.0002111613],"about_ca_topic_score_codex":0.0006490042,"about_ca_topic_score_gemma":0.00044165648,"teacher_disagreement_score":0.019397406,"about_ca_system_score_codex":0.0007758788,"about_ca_system_score_gemma":0.0015957094,"threshold_uncertainty_score":0.10258454},"labels":[],"label_agreement":null},{"id":"W2036603753","doi":"10.1007/s00184-015-0537-9","title":"Schur properties of convolutions of gamma random variables","year":2015,"lang":"en","type":"article","venue":"Metrika","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Convexity; Random variable; Cumulative distribution function; Gamma distribution; Generalized gamma distribution; Stochastic ordering; Schur complement; Convolution (computer science)","score_opus":0.38666991597151074,"score_gpt":0.3752267383036059,"score_spread":0.011443177667904814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036603753","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20915864,0.0016911917,0.75213814,0.001554517,0.00014047298,0.00011792022,0.00033755452,0.00025449425,0.034606986],"genre_scores_gemma":[0.9352651,0.0018992446,0.045627233,0.0004161955,0.00042483,0.00022908955,0.00030755982,0.00019062888,0.015640194],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970879,0.0012325154,0.00014175245,0.00032118315,0.000801171,0.00041544606],"domain_scores_gemma":[0.9710651,0.021934407,0.0024236536,0.0011474072,0.0022267094,0.0012026193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067010312,0.0016403619,0.0015407937,0.0038457797,0.0011818042,0.004453436,0.0018528529,0.0019304382,0.007225194],"category_scores_gemma":[0.03491186,0.0011370177,0.0018847344,0.0019860647,0.0051235342,0.006750615,0.002420643,0.0030246484,0.00090715714],"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":[0.0000423874,0.000024479175,0.00038781133,0.000055190772,0.00002450148,0.00010491692,0.00020084076,0.0104143405,0.0007401887,0.98325646,0.000558724,0.0041902303],"study_design_scores_gemma":[0.00001345036,0.000026622449,0.00034526523,0.000026244172,0.000015008625,0.00013352177,0.000052921783,0.13409801,0.00043771588,0.86422336,0.0005915713,0.00003641999],"about_ca_topic_score_codex":0.003064075,"about_ca_topic_score_gemma":0.0024022805,"teacher_disagreement_score":0.007225194,"about_ca_system_score_codex":0.0021552306,"about_ca_system_score_gemma":0.0018162281,"threshold_uncertainty_score":0.035438895},"labels":[],"label_agreement":null},{"id":"W2038682698","doi":"10.1007/s00184-012-0382-z","title":"Default models based on scale mixtures of Marshall-Olkin copulas: properties and applications","year":2012,"lang":"en","type":"article","venue":"Metrika","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Copula (linguistics); Mathematics; Laplace transform; Econometrics; Applied mathematics; Parametric statistics; Statistics; Mathematical analysis","score_opus":0.05766549078931896,"score_gpt":0.22226014448622908,"score_spread":0.16459465369691012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038682698","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07548392,0.0016760882,0.9188347,0.0007274255,0.00011489671,0.00007036414,0.00018425062,0.00040510038,0.0025032968],"genre_scores_gemma":[0.9217293,0.0021825174,0.06602914,0.00027523682,0.00041009497,0.00023473379,0.00041746613,0.0003290944,0.008392428],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982337,0.0009802848,0.00008374697,0.0003315288,0.00018401377,0.0001867781],"domain_scores_gemma":[0.98304635,0.012359789,0.0020874226,0.0009424476,0.0008475426,0.0007163759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009090487,0.0018394713,0.0036467768,0.0016948372,0.0010429403,0.0036004507,0.0037569266,0.0029428604,0.0032672924],"category_scores_gemma":[0.030840274,0.0015415715,0.0023305048,0.0024695378,0.0029485223,0.006816707,0.002357207,0.0036746697,0.0005487734],"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":[0.00012576373,0.00011176838,0.0028298066,0.00010002413,0.00023769884,0.00018986895,0.00034232353,0.556851,0.00073263654,0.42304653,0.0026705097,0.012762],"study_design_scores_gemma":[0.000008634269,0.000007689092,0.00026645703,0.000009657038,0.000018035873,0.000020694508,0.000015100754,0.9457301,0.000042743974,0.05370113,0.00015986148,0.000019832407],"about_ca_topic_score_codex":0.0052763415,"about_ca_topic_score_gemma":0.0043687844,"teacher_disagreement_score":0.009090487,"about_ca_system_score_codex":0.0016791743,"about_ca_system_score_gemma":0.00118229,"threshold_uncertainty_score":0.048075616},"labels":[],"label_agreement":null},{"id":"W2038954288","doi":"10.1007/s001840000051","title":"Relevance weighted likelihood for dependent data","year":2000,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National University of Singapore; University of Maryland, Baltimore County","keywords":"Mathematics; Estimator; Relevance (law); Asymptotic distribution; Likelihood function; Nonparametric statistics; Consistency (knowledge bases); Smoothing; Econometrics; Nonparametric regression; Statistics; Maximum likelihood","score_opus":0.15986745843628836,"score_gpt":0.40894964184460786,"score_spread":0.2490821834083195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038954288","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":[0.0022443323,0.0006025836,0.99602497,0.0004354874,0.0000335931,0.000033120512,0.00008762318,0.00012631922,0.00041194411],"genre_scores_gemma":[0.23152909,0.002118858,0.753449,0.000667288,0.0008300301,0.0010563211,0.0017772231,0.00057877373,0.0079934625],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9792473,0.0155848265,0.00080295076,0.0022384375,0.0017262121,0.0004004244],"domain_scores_gemma":[0.8814953,0.103677355,0.003160212,0.008487442,0.0024722742,0.0007074075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.028826714,0.0014862884,0.00327447,0.0032508452,0.001232858,0.003971285,0.005549596,0.004280303,0.004966254],"category_scores_gemma":[0.16042255,0.0024094458,0.0024568043,0.004099855,0.0039645215,0.0071327593,0.004803562,0.0061948863,0.0015402524],"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":[0.00059841725,0.00018341915,0.002862165,0.001465561,0.0008623522,0.00082438014,0.00076756015,0.11547642,0.0019360356,0.70405537,0.008854621,0.1621137],"study_design_scores_gemma":[0.00008542141,0.000040903247,0.0007017617,0.0000738594,0.00008187889,0.00031530988,0.00004332304,0.31339592,0.00048852357,0.68121696,0.003516362,0.000039679282],"about_ca_topic_score_codex":0.0021229107,"about_ca_topic_score_gemma":0.0018141294,"teacher_disagreement_score":0.028826714,"about_ca_system_score_codex":0.0017308581,"about_ca_system_score_gemma":0.0023595765,"threshold_uncertainty_score":0.15245205},"labels":[],"label_agreement":null},{"id":"W2042888778","doi":"10.1007/s001840000073","title":"Comparison of test vs. control treatments using distance optimality criterion","year":2000,"lang":"en","type":"article","venue":"Metrika","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Optimality criterion; Optimal design; Mathematical optimization; Set (abstract data type); Optimal control; Expression (computer science); Statistics; Computer science","score_opus":0.01867736601017582,"score_gpt":0.2966239304629356,"score_spread":0.2779465644527598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042888778","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9552451,0.0010545726,0.032363478,0.00036346258,0.0009729245,0.0010386786,0.001984231,0.00036672674,0.006610853],"genre_scores_gemma":[0.9722944,0.000264421,0.017439533,0.00022770463,0.000056822668,0.0010945563,0.0013179772,0.00014830496,0.007156249],"study_design_codex":"randomized_trial","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99764425,0.0011872204,0.00022125132,0.00044097216,0.00033908332,0.00016721166],"domain_scores_gemma":[0.99096054,0.0064439806,0.000473115,0.00083298027,0.0008269986,0.00046235853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025081746,0.00067248906,0.0025746857,0.00090960704,0.00048580277,0.001029361,0.0012330149,0.0015267215,0.008502676],"category_scores_gemma":[0.010956693,0.00024365204,0.00081638794,0.0006456677,0.0009275498,0.00094567944,0.0006199423,0.0011203613,0.00074523455],"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":[0.52602375,0.020830609,0.003519091,0.0026236586,0.0013769995,0.00019298823,0.00044503534,0.012056504,0.22460507,0.010215665,0.0048987423,0.19321194],"study_design_scores_gemma":[0.031697564,0.30473986,0.07470755,0.00041262768,0.0051353,0.00043743686,0.0019273197,0.10414227,0.42242157,0.024800109,0.028966956,0.0006114588],"about_ca_topic_score_codex":0.001997897,"about_ca_topic_score_gemma":0.0016308274,"teacher_disagreement_score":0.008502676,"about_ca_system_score_codex":0.000691704,"about_ca_system_score_gemma":0.0009176605,"threshold_uncertainty_score":0.02844423},"labels":[],"label_agreement":null},{"id":"W2042999809","doi":"10.1007/s00184-012-0402-z","title":"On the nearness of record values to order statistics from Pitman’s measure of closeness","year":2012,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Closeness; Order statistic; Statistics; Statistic; Exponential family; Monotonic function; Sufficient statistic; Sample (material); Measure (data warehouse); Scale parameter; Scale (ratio); Exponential distribution; Sample size determination; Mathematical analysis; Data mining; Computer science","score_opus":0.11837051087462222,"score_gpt":0.3757251399246848,"score_spread":0.25735462905006257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042999809","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10092641,0.0013887737,0.88950425,0.0011263946,0.00010337378,0.00005552981,0.00018775211,0.000091455266,0.0066159945],"genre_scores_gemma":[0.8128316,0.0019191268,0.18098335,0.00046179065,0.00046865837,0.00022546097,0.000446142,0.00014107572,0.0025227936],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9896965,0.005531521,0.00074818387,0.0018823158,0.0018276299,0.0003137567],"domain_scores_gemma":[0.8534093,0.12647092,0.006652407,0.006419112,0.0052487836,0.0017995181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017031891,0.00072143285,0.0020720942,0.0059080045,0.002015652,0.0042760274,0.0025298754,0.0023323603,0.0025827559],"category_scores_gemma":[0.15035994,0.00090968236,0.0020920588,0.0057284515,0.0097884135,0.015878031,0.006014615,0.004787062,0.00034839878],"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":[0.00016235578,0.000037752503,0.00542774,0.00020082804,0.00011139347,0.00014756154,0.0013484025,0.036432352,0.0010520117,0.9279295,0.0005755131,0.026574628],"study_design_scores_gemma":[0.000012782873,0.00012840267,0.002825326,0.00007404112,0.000042788783,0.00029666076,0.00031921786,0.119826496,0.00066086854,0.8739126,0.0018468518,0.00005386904],"about_ca_topic_score_codex":0.0016031823,"about_ca_topic_score_gemma":0.00079740933,"teacher_disagreement_score":0.017031891,"about_ca_system_score_codex":0.0020899028,"about_ca_system_score_gemma":0.0011920569,"threshold_uncertainty_score":0.09007436},"labels":[],"label_agreement":null},{"id":"W2044544009","doi":"10.1007/s00184-010-0330-8","title":"On the detectability of different forms of interaction in regression models","year":2010,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Saskatchewan","funders":"University of Saskatchewan","keywords":"Mathematics; Pairwise comparison; Contrast (vision); Context (archaeology); Regression; Regression analysis; Interaction; Statistics; Artificial intelligence; Computer science","score_opus":0.11987187431605989,"score_gpt":0.40065021786984995,"score_spread":0.28077834355379006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044544009","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":[0.09241462,0.002228283,0.89627427,0.0036947958,0.00019858935,0.00019666695,0.00039411828,0.0006735609,0.00392514],"genre_scores_gemma":[0.82964444,0.0012865956,0.16092663,0.0015398863,0.0010993192,0.0009897444,0.00094807503,0.00056856335,0.0029967998],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.7719544,0.17844242,0.008722389,0.023610348,0.013323356,0.003947044],"domain_scores_gemma":[0.059207343,0.9157891,0.0069758007,0.0150406975,0.0017977577,0.0011892837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.16205795,0.0028878504,0.0075784926,0.0061157974,0.0035896574,0.00867544,0.010445234,0.010156624,0.0059302174],"category_scores_gemma":[0.59839135,0.0042798356,0.00889236,0.0052472404,0.02355625,0.019447371,0.0133207925,0.017055506,0.00069193577],"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":[0.005908566,0.0010558768,0.118215114,0.002456013,0.0070896028,0.003418171,0.0045740185,0.07676539,0.0051698736,0.5927078,0.0042122025,0.17842741],"study_design_scores_gemma":[0.00051745225,0.0011888361,0.016558127,0.0002559118,0.0011858621,0.0014070331,0.0005304821,0.28373396,0.002199689,0.68975943,0.0024085632,0.00025461378],"about_ca_topic_score_codex":0.0017090604,"about_ca_topic_score_gemma":0.0012245004,"teacher_disagreement_score":0.16205795,"about_ca_system_score_codex":0.0021881796,"about_ca_system_score_gemma":0.0029176679,"threshold_uncertainty_score":0.8570546},"labels":[],"label_agreement":null},{"id":"W2046348640","doi":"10.1007/s001840000092","title":"Conditional inference procedures for the Laplace distribution when the observed samples are progressively censored","year":2000,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Laplace transform; Statistics; Laplace distribution; Confidence interval; Inference; Conditioning; Laplace's method; Distribution (mathematics); Applied mathematics; Tolerance interval; Coverage probability; Type (biology); Sample (material); Exponential distribution; Mathematical analysis","score_opus":0.15721298118889054,"score_gpt":0.3779272048771436,"score_spread":0.22071422368825305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046348640","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":[0.0016502901,0.00016401714,0.9975401,0.00011906981,0.00001959322,0.000026379923,0.000059895305,0.00013790924,0.0002827478],"genre_scores_gemma":[0.1801644,0.0018742629,0.8088459,0.00047290843,0.0004953621,0.0007411348,0.0013506371,0.00047964018,0.005575803],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9921484,0.0044924826,0.00043139473,0.001394191,0.0011567087,0.00037681733],"domain_scores_gemma":[0.90525377,0.08335608,0.0030181785,0.0045851395,0.0031319028,0.0006549679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023755953,0.0016264484,0.002354692,0.0038559865,0.0011409107,0.0032135749,0.0050223414,0.0025053632,0.0074878423],"category_scores_gemma":[0.120634966,0.0018744825,0.0026533876,0.0030603458,0.0040307874,0.0066596605,0.003857778,0.0064321635,0.0016332554],"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":[0.0003489447,0.00015869262,0.0038853975,0.0004893207,0.00046508218,0.00035437508,0.0007933561,0.13123612,0.0019796137,0.7070254,0.0038433354,0.14942041],"study_design_scores_gemma":[0.000065362896,0.00004585309,0.0009638978,0.00013606035,0.000101429796,0.00021397705,0.00007676648,0.58850384,0.0013785206,0.40619385,0.002249709,0.00007075608],"about_ca_topic_score_codex":0.0044566314,"about_ca_topic_score_gemma":0.0053014047,"teacher_disagreement_score":0.023755953,"about_ca_system_score_codex":0.0018953435,"about_ca_system_score_gemma":0.00348561,"threshold_uncertainty_score":0.12563497},"labels":[],"label_agreement":null},{"id":"W2049081094","doi":"10.1007/s00184-005-0006-y","title":"A note on the uniform asymptotic normality of location M-estimates","year":2006,"lang":"en","type":"article","venue":"Metrika","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mathematics; Parametric statistics; Asymptotic distribution; Normality; Scale (ratio); Statistics; Local asymptotic normality; Robustness (evolution); Applied mathematics; Point (geometry); Scale parameter; Estimator; Geometry; Geography","score_opus":0.09120269793899985,"score_gpt":0.3994918867845784,"score_spread":0.30828918884557854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049081094","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":[0.005769435,0.0029179035,0.9776145,0.0032134107,0.00071467715,0.0000308299,0.00027617498,0.00019826704,0.00926469],"genre_scores_gemma":[0.40968108,0.01201159,0.5419822,0.008734723,0.009275258,0.00087922846,0.0011394268,0.0013314709,0.014965055],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98066574,0.011833937,0.0011189799,0.0030271008,0.002785343,0.00056878215],"domain_scores_gemma":[0.7669017,0.19536844,0.0055440213,0.020147776,0.010438781,0.0015993109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03911636,0.0015951914,0.00350974,0.0034221136,0.002065996,0.0040977667,0.004150317,0.003988842,0.005725402],"category_scores_gemma":[0.19688672,0.001556304,0.003541637,0.003898328,0.011939169,0.01083871,0.008003748,0.012634617,0.0017077699],"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":[0.00017133908,0.00003114059,0.0021129535,0.00029567775,0.00014817601,0.00038847505,0.000529155,0.007460159,0.0012259184,0.9520456,0.007029701,0.028561734],"study_design_scores_gemma":[0.000034058565,0.0000880406,0.0015441922,0.00013318632,0.000087309076,0.00044756205,0.000079259255,0.03847227,0.0013052939,0.94866174,0.009073748,0.00007324706],"about_ca_topic_score_codex":0.002430434,"about_ca_topic_score_gemma":0.001222539,"teacher_disagreement_score":0.03911636,"about_ca_system_score_codex":0.0015593672,"about_ca_system_score_gemma":0.0015043182,"threshold_uncertainty_score":0.2068696},"labels":[],"label_agreement":null},{"id":"W2051625332","doi":"10.1007/s00184-012-0381-0","title":"On the goodness-of-fit procedure for normality based on the empirical characteristic function for ranked set sampling data","year":2012,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"RSS; Mathematics; Goodness of fit; Statistics; Context (archaeology); Normality; Data set; Simple random sample; Econometrics; Computer science; Population","score_opus":0.7426862139722693,"score_gpt":0.5041488291047047,"score_spread":0.2385373848675646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051625332","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":[0.010002073,0.00020902108,0.9884171,0.00025064836,0.000038531278,0.00013504903,0.0000879247,0.00023516678,0.0006244855],"genre_scores_gemma":[0.27275178,0.00054312317,0.722145,0.0004574441,0.0002264858,0.0013458974,0.00076120987,0.00054808107,0.0012209245],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.91025424,0.07599085,0.0021853182,0.0036174203,0.0071587125,0.0007935853],"domain_scores_gemma":[0.53333557,0.4317974,0.0041090604,0.021073082,0.008487199,0.0011977023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.10338694,0.0018391387,0.004883285,0.0064605298,0.002553277,0.0039690956,0.0061543686,0.004371542,0.005854127],"category_scores_gemma":[0.35287374,0.0013122477,0.0042994963,0.0053612567,0.009835822,0.0063930745,0.005738933,0.008428429,0.0010910633],"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":[0.0009280396,0.0003987714,0.01268415,0.00075340265,0.00095779647,0.0005787735,0.0014960812,0.16495092,0.0021845466,0.60505897,0.004791564,0.20521705],"study_design_scores_gemma":[0.0001821766,0.00053878914,0.0047195186,0.00023967064,0.00016167111,0.00044553255,0.00032590324,0.67719275,0.0015566883,0.31180122,0.0026747996,0.0001612869],"about_ca_topic_score_codex":0.0047745015,"about_ca_topic_score_gemma":0.0031868885,"teacher_disagreement_score":0.10338694,"about_ca_system_score_codex":0.002314798,"about_ca_system_score_gemma":0.0052096792,"threshold_uncertainty_score":0.5467689},"labels":[],"label_agreement":null},{"id":"W2054381957","doi":"10.1007/s00184-009-0257-0","title":"Percentile estimators in location-scale parameter families under absolute loss","year":2009,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Estimator; Mathematics; Percentile; Statistics; Equivariant map; Location parameter; Scale parameter; M-estimator; Scale (ratio); Extremum estimator; Exponential function; Mathematical analysis; Geography","score_opus":0.06397227865921261,"score_gpt":0.3706209269972683,"score_spread":0.30664864833805566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054381957","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":[0.016070554,0.0005934119,0.9818284,0.0003486478,0.00002188028,0.000020717845,0.000109680215,0.00017579447,0.00083097734],"genre_scores_gemma":[0.6848007,0.0041468344,0.29956543,0.00051844877,0.00056856946,0.0006062448,0.0013790469,0.0005492076,0.00786549],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9918921,0.00549351,0.00033942456,0.00082720787,0.0010449928,0.00040272545],"domain_scores_gemma":[0.8709379,0.11117384,0.0059019295,0.0070215557,0.0035878026,0.0013768716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027261393,0.0011988311,0.0027157746,0.0035360474,0.0010597788,0.0035383468,0.0035984772,0.0023296247,0.0042267037],"category_scores_gemma":[0.14471596,0.0013191189,0.0015605987,0.00355552,0.00519629,0.009819595,0.004520348,0.0041475217,0.0008862781],"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":[0.0002058658,0.00007220851,0.0060202205,0.0002279446,0.00019057967,0.00023124536,0.00052708574,0.15804204,0.00068747107,0.7895058,0.0029668983,0.041322738],"study_design_scores_gemma":[0.00002419156,0.0000635657,0.0013730533,0.00006799693,0.0000446758,0.00022795124,0.00015122193,0.36937928,0.00047892056,0.6265439,0.0016110529,0.000034185887],"about_ca_topic_score_codex":0.0012529895,"about_ca_topic_score_gemma":0.0008117742,"teacher_disagreement_score":0.027261393,"about_ca_system_score_codex":0.0017056811,"about_ca_system_score_gemma":0.0014011,"threshold_uncertainty_score":0.14417374},"labels":[],"label_agreement":null},{"id":"W2055853044","doi":"10.1007/s00184-006-0066-7","title":"Analysis of Hybrid Life-tests in Presence of Competing Risks","year":2006,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Censoring (clinical trials); Mathematics; Estimator; Statistics; Confidence interval; Monte Carlo method; Bayes' theorem; Scale parameter; Prior probability; Applied mathematics; Exponential distribution; Bayesian probability","score_opus":0.10644976502660618,"score_gpt":0.40363278108014095,"score_spread":0.29718301605353475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055853044","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":[0.1708962,0.00080420123,0.8263879,0.00030759713,0.000036171197,0.000052746665,0.00015235007,0.00019579791,0.0011671036],"genre_scores_gemma":[0.9051998,0.00020735803,0.0921919,0.00006166911,0.00007304402,0.00010087577,0.0003092603,0.00006216204,0.0017938737],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9920294,0.0060317614,0.00020030024,0.00065625244,0.0007346749,0.00034762447],"domain_scores_gemma":[0.82351536,0.16602847,0.0045682224,0.00245128,0.002205278,0.0012314183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019683985,0.0009755786,0.0015780907,0.0025589473,0.00040638787,0.0021099448,0.002325322,0.0015991003,0.003716108],"category_scores_gemma":[0.058655158,0.0005765007,0.0011616622,0.001155,0.0022385346,0.0023150304,0.0019625898,0.0011181723,0.00024453943],"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":[0.001591768,0.00027232486,0.041186165,0.00051075674,0.0012512448,0.0013424826,0.00052943587,0.58651865,0.0043130587,0.25570336,0.0012092527,0.10557147],"study_design_scores_gemma":[0.000042819305,0.00030421678,0.003668687,0.00002360502,0.00007854576,0.000308854,0.0000797336,0.922093,0.0008309491,0.07218425,0.00035005086,0.000035362922],"about_ca_topic_score_codex":0.0008859188,"about_ca_topic_score_gemma":0.0005773255,"teacher_disagreement_score":0.019683985,"about_ca_system_score_codex":0.00084763207,"about_ca_system_score_gemma":0.00093024113,"threshold_uncertainty_score":0.10410011},"labels":[],"label_agreement":null},{"id":"W2062161993","doi":"10.1007/s00184-013-0467-3","title":"Second order longitudinal dynamic models with covariates: estimation and forecasting","year":2013,"lang":"en","type":"article","venue":"Metrika","topic":"Stochastic processes and statistical mechanics","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Estimator; Covariate; Mathematics; Statistics; Variance (accounting); Unobservable; Econometrics; Asymptotic distribution; Applied mathematics; Delta method; Extension (predicate logic); Computer science","score_opus":0.062941031723083,"score_gpt":0.29294427377683124,"score_spread":0.23000324205374822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062161993","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0954592,0.0030373533,0.8956529,0.0029378121,0.00021767651,0.000054411757,0.00097466283,0.00027268924,0.00139325],"genre_scores_gemma":[0.8545158,0.005435586,0.11663098,0.00032421586,0.00065545324,0.00037232094,0.0025346717,0.00011851821,0.019412579],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99854845,0.0007152747,0.00007428539,0.00037480483,0.00011563319,0.0001715574],"domain_scores_gemma":[0.98391366,0.012956026,0.0011699621,0.0008586938,0.00071138336,0.00039025527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008072007,0.0011099217,0.0025230064,0.0015165003,0.00077955174,0.002497703,0.0018719692,0.0029035555,0.004100786],"category_scores_gemma":[0.025518037,0.0015689722,0.0013797382,0.002783759,0.0013359777,0.0029186597,0.0015734851,0.0035021305,0.00085873855],"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":[0.00034731918,0.00023474956,0.022831643,0.00024112685,0.0003690444,0.00027020407,0.0004307168,0.6215042,0.00063595537,0.29746953,0.005597569,0.050067917],"study_design_scores_gemma":[0.000022345746,0.000031732798,0.0021280483,0.000030425625,0.000050732182,0.000037896334,0.00003953099,0.90783924,0.000104225015,0.08843727,0.0012524648,0.000026067735],"about_ca_topic_score_codex":0.017214261,"about_ca_topic_score_gemma":0.019004123,"teacher_disagreement_score":0.017214261,"about_ca_system_score_codex":0.0012966477,"about_ca_system_score_gemma":0.002148568,"threshold_uncertainty_score":0.042689323},"labels":[],"label_agreement":null},{"id":"W2068430062","doi":"10.1007/s00184-013-0453-9","title":"$$L$$ L -statistics from multivariate unified skew-elliptical distributions","year":2013,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Skew; Elliptical distribution; Multivariate statistics; Order statistic; Statistics; L-moment; Distribution (mathematics); Skew normal distribution; Applied mathematics; Multivariate normal distribution; Skewness; Mathematical analysis","score_opus":0.08106762915572019,"score_gpt":0.3610444721739641,"score_spread":0.27997684301824394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068430062","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013143515,0.00022150617,0.984396,0.0001705028,0.00002479674,0.000015486918,0.00009606079,0.00015672992,0.0017753453],"genre_scores_gemma":[0.6132951,0.0016135534,0.37284964,0.0005379999,0.00042506322,0.00025661316,0.00095504057,0.00045566587,0.009611312],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983937,0.0007494174,0.00009672351,0.00029918677,0.0003270486,0.00013383164],"domain_scores_gemma":[0.9915343,0.004981208,0.0009718546,0.0011669659,0.0010848187,0.00026091622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003919568,0.00064083835,0.00092385325,0.0019190346,0.0005237505,0.001966524,0.0012442768,0.00085491117,0.0038484419],"category_scores_gemma":[0.020805739,0.00047588337,0.0009585018,0.0014120948,0.0023573034,0.0036263135,0.0023384208,0.0018438542,0.0010851466],"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":[0.000069035246,0.00002255985,0.0015779233,0.0001042096,0.000041392737,0.000101316364,0.00018504678,0.035077605,0.0023527665,0.91128635,0.0017673967,0.047414284],"study_design_scores_gemma":[0.000010688803,0.000029157716,0.0013703567,0.000044767014,0.000017462635,0.00020195852,0.000056340992,0.3622242,0.0015129471,0.63085216,0.0036384948,0.000041473773],"about_ca_topic_score_codex":0.0010233247,"about_ca_topic_score_gemma":0.0009880094,"teacher_disagreement_score":0.003919568,"about_ca_system_score_codex":0.00095265725,"about_ca_system_score_gemma":0.0009388618,"threshold_uncertainty_score":0.020728946},"labels":[],"label_agreement":null},{"id":"W2069423310","doi":"10.1007/s00184-009-0244-5","title":"On kernel nonparametric regression designed for complex survey data","year":2009,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Mathematics; Estimator; Nonparametric regression; Kernel regression; Statistics; Nonparametric statistics; Mean squared error; Polynomial regression; Kernel method; Kernel (algebra); Local regression; Regression analysis; Computer science; Artificial intelligence; Support vector machine; Discrete mathematics","score_opus":0.518294448224895,"score_gpt":0.4939451645302449,"score_spread":0.024349283694650115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069423310","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":[0.0007205058,0.000113896676,0.99877197,0.000070904076,0.00003074722,0.000013000966,0.000023655946,0.00009237807,0.00016293488],"genre_scores_gemma":[0.096538305,0.0015459266,0.893261,0.00045991718,0.00039962394,0.00057943864,0.00056113466,0.00041713592,0.0062374026],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9893834,0.007657565,0.00040663066,0.0011575277,0.0011135371,0.00028136294],"domain_scores_gemma":[0.96421146,0.024527842,0.0019866454,0.0060785315,0.0028413774,0.00035404804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01996623,0.0014681708,0.0019133486,0.0019386986,0.00069970987,0.001520672,0.0029930337,0.0017525803,0.0033839794],"category_scores_gemma":[0.06350839,0.0010865461,0.0015356,0.004080505,0.002717923,0.0037666787,0.0037780507,0.0037664315,0.0018786016],"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":[0.00015786916,0.0001205062,0.0023228745,0.00042937315,0.00033804763,0.0002555558,0.00038259866,0.13660803,0.0030691023,0.6482585,0.0070864856,0.20097107],"study_design_scores_gemma":[0.00003641869,0.00008131088,0.0010602365,0.000059894082,0.00008289594,0.00017928435,0.000050233877,0.71421945,0.001106098,0.27350485,0.009566717,0.00005253952],"about_ca_topic_score_codex":0.0033925006,"about_ca_topic_score_gemma":0.0026730085,"teacher_disagreement_score":0.01996623,"about_ca_system_score_codex":0.0012014174,"about_ca_system_score_gemma":0.0021732314,"threshold_uncertainty_score":0.10559279},"labels":[],"label_agreement":null},{"id":"W2071787207","doi":"10.1007/s001840300273","title":"Preliminary test ridge regression estimators with student?s t errors and conflicting test-statistics","year":2004,"lang":"en","type":"article","venue":"Metrika","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":63,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Mathematics; Estimator; Statistics; M-estimator; Wald test; Score test; Extremum estimator; Statistical hypothesis testing; Regression; F-test; Regression analysis","score_opus":0.0766650121787617,"score_gpt":0.43252015498775265,"score_spread":0.35585514280899094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071787207","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":[0.008603278,0.00012121237,0.9894134,0.00022127961,0.00009474907,0.000086306296,0.000120872864,0.00035090977,0.0009878901],"genre_scores_gemma":[0.14627044,0.00019421693,0.84710956,0.0004839306,0.00028612773,0.0007188282,0.00087862357,0.00091267074,0.0031455539],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.96760744,0.019601103,0.002578044,0.0036252087,0.00527785,0.0013103368],"domain_scores_gemma":[0.66820884,0.2517788,0.01083531,0.041205227,0.025651678,0.0023201185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.070638,0.0020515195,0.003053784,0.0022818248,0.0013467681,0.0043151528,0.0053780926,0.004889026,0.012615459],"category_scores_gemma":[0.36053467,0.0016100346,0.0031359326,0.00287131,0.0025480108,0.007475163,0.0053226943,0.006901622,0.0037836721],"study_design_candidate":"simulation_or_modeling","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":[0.002640563,0.0010614282,0.04628756,0.0011387158,0.002041124,0.0012675048,0.0012317839,0.06644728,0.013874079,0.4311303,0.014117684,0.418762],"study_design_scores_gemma":[0.00032922652,0.0013099806,0.009905881,0.00031123878,0.00042079893,0.0009485718,0.0004311737,0.5069011,0.025481803,0.44253722,0.011246793,0.00017618212],"about_ca_topic_score_codex":0.00072131085,"about_ca_topic_score_gemma":0.0010022527,"teacher_disagreement_score":0.070638,"about_ca_system_score_codex":0.00079626276,"about_ca_system_score_gemma":0.003012385,"threshold_uncertainty_score":0.3735739},"labels":[],"label_agreement":null},{"id":"W2079361683","doi":"10.1007/s00184-006-0027-1","title":"Bayesian Analysis in the L 1-Norm of the Mixing Proportion Using Discriminant Analysis","year":2006,"lang":"en","type":"article","venue":"Metrika","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Mathematics; Linear discriminant analysis; Mixing (physics); Bayesian probability; Statistics; Discriminant; Posterior probability; Beta distribution; Norm (philosophy); Applied mathematics; Pattern recognition (psychology); Artificial intelligence; Computer science","score_opus":0.02036564289871512,"score_gpt":0.27764735813779534,"score_spread":0.2572817152390802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079361683","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":[0.0025533163,0.00015120493,0.99678326,0.0000859807,0.000012126627,0.0000078375015,0.000026250029,0.00006143152,0.00031858933],"genre_scores_gemma":[0.165041,0.0010690967,0.827733,0.00021278433,0.00021428108,0.00026328483,0.0004057961,0.0004383402,0.0046223574],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99519193,0.0029430077,0.00018341422,0.0007443811,0.0007564607,0.00018081328],"domain_scores_gemma":[0.99008405,0.007707778,0.00048827325,0.0006652337,0.00084214535,0.00021252902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0094751725,0.0012514812,0.0018916541,0.0024567964,0.0009707078,0.0036477158,0.0024862636,0.0018284668,0.0025854008],"category_scores_gemma":[0.028354507,0.0009051597,0.001438367,0.001961543,0.0029862684,0.0041025467,0.003758762,0.0034877406,0.0010302563],"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":[0.00033013313,0.00009649827,0.001490552,0.00038898265,0.00020584608,0.00008507492,0.00031387212,0.2602908,0.0069412733,0.5391688,0.0029203263,0.18776779],"study_design_scores_gemma":[0.000013491495,0.000020583611,0.00035622218,0.000031299933,0.000018579081,0.00004046806,0.00001988018,0.8216825,0.001169625,0.17511989,0.0014889449,0.000038409802],"about_ca_topic_score_codex":0.0024332474,"about_ca_topic_score_gemma":0.0019647202,"teacher_disagreement_score":0.0094751725,"about_ca_system_score_codex":0.0012475983,"about_ca_system_score_gemma":0.0015358143,"threshold_uncertainty_score":0.0501101},"labels":[],"label_agreement":null},{"id":"W2079645022","doi":"10.1007/s00184-015-0530-3","title":"Inference for the bivariate Birnbaum–Saunders lifetime regression model and associated inference","year":2015,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Bivariate analysis; Statistics; Inference; Estimator; Interval estimation; Statistical inference; Econometrics; Monte Carlo method; Regression analysis; Confidence interval; Computer science; Artificial intelligence","score_opus":0.24760836457065588,"score_gpt":0.43546432848400213,"score_spread":0.18785596391334625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079645022","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":[0.019341776,0.0010319611,0.9756232,0.0017443913,0.00009532117,0.00005593093,0.0004057522,0.0002180353,0.0014836584],"genre_scores_gemma":[0.555854,0.0057947855,0.40268013,0.0010312417,0.0012418556,0.0009088945,0.0030884854,0.00050782494,0.028892742],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9945497,0.0033188094,0.0002258171,0.0010305969,0.0005303113,0.00034467463],"domain_scores_gemma":[0.9444463,0.04891266,0.002012582,0.0024100665,0.0016440211,0.00057441514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02178545,0.0013765332,0.0036652612,0.0030949782,0.0012710565,0.003179568,0.0044355,0.0030677042,0.01176616],"category_scores_gemma":[0.096212246,0.0018378246,0.0028001,0.0034603325,0.003642384,0.006648289,0.0031334935,0.006217532,0.001508185],"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":[0.00018351902,0.00013671859,0.007644158,0.00026582822,0.0004408421,0.00027963048,0.00047844974,0.14260998,0.0004681069,0.7839426,0.0057344367,0.05781579],"study_design_scores_gemma":[0.00003972817,0.000031281645,0.0013655797,0.00007842993,0.000112785194,0.00009911977,0.00009052922,0.5126686,0.00021983344,0.4835301,0.0017271833,0.000036783218],"about_ca_topic_score_codex":0.017362049,"about_ca_topic_score_gemma":0.014679993,"teacher_disagreement_score":0.02178545,"about_ca_system_score_codex":0.0027755587,"about_ca_system_score_gemma":0.0036725944,"threshold_uncertainty_score":0.11521387},"labels":[],"label_agreement":null},{"id":"W2082836022","doi":"10.1007/s00184-014-0488-6","title":"On shrinkage estimators in matrix variate elliptical models","year":2014,"lang":"en","type":"article","venue":"Metrika","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministerio de Economía y Competitividad; University of Windsor","keywords":"Shrinkage; Random variate; Mathematics; Shrinkage estimator; Estimator; Scatter matrix; Statistics; Matrix (chemical analysis); Multivariate statistics; Applied mathematics; Multivariate normal distribution; Elliptical distribution; Random variable; Efficient estimator","score_opus":0.10115903103537603,"score_gpt":0.4291708927132577,"score_spread":0.32801186167788166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082836022","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":[0.0037801308,0.0008898519,0.9936977,0.0004117442,0.00004845098,0.000014002126,0.00003181796,0.00006013817,0.0010661458],"genre_scores_gemma":[0.22578968,0.008716296,0.74641305,0.0009695326,0.0012598675,0.0005399232,0.0006386037,0.0006426834,0.015030273],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952992,0.0036080463,0.00015680697,0.00036430714,0.000443712,0.00012781112],"domain_scores_gemma":[0.94946265,0.044587214,0.0017896002,0.0017910695,0.0019238263,0.00044565625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015564801,0.0014924116,0.0015906004,0.001955759,0.0006797243,0.0017178801,0.0021544246,0.00246791,0.0029911262],"category_scores_gemma":[0.06959218,0.001334397,0.0012490972,0.0023206251,0.0044197254,0.0042081643,0.0036098044,0.004736632,0.00090271496],"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":[0.000046175293,0.000038962597,0.0007665941,0.00023997374,0.00008462553,0.00007724356,0.00031975526,0.07278818,0.0012044822,0.88020897,0.0023271244,0.041897953],"study_design_scores_gemma":[0.000018831537,0.000030571966,0.0003937488,0.00009468067,0.000027768507,0.000060972416,0.0000466584,0.29345244,0.00039813702,0.70206416,0.0033751742,0.00003691029],"about_ca_topic_score_codex":0.0025668826,"about_ca_topic_score_gemma":0.0024224333,"teacher_disagreement_score":0.015564801,"about_ca_system_score_codex":0.0011409997,"about_ca_system_score_gemma":0.0012897231,"threshold_uncertainty_score":0.082315505},"labels":[],"label_agreement":null},{"id":"W2084761610","doi":"10.1007/s00184-010-0328-2","title":"R-estimation of the parameters of a multiple regression model with measurement errors","year":2010,"lang":"en","type":"article","venue":"Metrika","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Mathematics; Estimator; Statistics; Linear regression; Regression analysis; Rank (graph theory); Regression; Proper linear model; Robust regression; Observational error; Errors-in-variables models; Applied mathematics; Polynomial regression; Combinatorics","score_opus":0.18709331703462034,"score_gpt":0.39669022030774725,"score_spread":0.2095969032731269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084761610","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":[0.0044294097,0.000298276,0.9936056,0.00018003798,0.000053025546,0.000036524263,0.00017604243,0.00060129305,0.0006197769],"genre_scores_gemma":[0.27541995,0.0012963352,0.7152933,0.00020216883,0.00018724219,0.00043690312,0.0010016653,0.0009150135,0.005247407],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98810416,0.0079941265,0.00043163996,0.0021196723,0.001107431,0.00024296057],"domain_scores_gemma":[0.9696844,0.021211801,0.0029235817,0.0043218555,0.001628632,0.00022963558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00994827,0.002005137,0.0017813136,0.001552368,0.0004752437,0.001703003,0.0019597728,0.0016136741,0.0049963924],"category_scores_gemma":[0.06472141,0.0008924804,0.0021657743,0.002255437,0.0013567979,0.002841484,0.0016126167,0.002999022,0.0046612322],"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":[0.0004273987,0.00018253774,0.01898825,0.0017358242,0.0015735443,0.0006331289,0.00055577524,0.20187418,0.013551276,0.23606032,0.01302951,0.5113882],"study_design_scores_gemma":[0.00010082657,0.0005705926,0.010121179,0.00048472272,0.0004938298,0.0010086749,0.00024481377,0.70018065,0.016371844,0.24906583,0.02118457,0.00017254452],"about_ca_topic_score_codex":0.0021392799,"about_ca_topic_score_gemma":0.0013238802,"teacher_disagreement_score":0.00994827,"about_ca_system_score_codex":0.00064765866,"about_ca_system_score_gemma":0.0022899376,"threshold_uncertainty_score":0.052612126},"labels":[],"label_agreement":null},{"id":"W2086783012","doi":"10.1007/s001840400345","title":"Estimation of P[Y < X] for generalized exponential distribution","year":2005,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":258,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Mathematics; Estimator; Minimum-variance unbiased estimator; Statistics; Exponential distribution; Confidence interval; Scale parameter; Trimmed estimator; Applied mathematics; Exponential function; Asymptotic analysis; Bias of an estimator; Mathematical analysis","score_opus":0.0747487399332935,"score_gpt":0.38561638387067676,"score_spread":0.31086764393738325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086783012","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027860148,0.000199745,0.9706947,0.00020054859,0.000017723814,0.00003165553,0.00011177847,0.00026219027,0.00062147144],"genre_scores_gemma":[0.65247303,0.00082658493,0.33927277,0.00013774874,0.00010170146,0.00018633352,0.0010853133,0.00017097098,0.005745429],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99887925,0.0004978227,0.000046834204,0.00030542442,0.00015732941,0.00011344956],"domain_scores_gemma":[0.9925689,0.005974928,0.0004095063,0.0005217872,0.000422361,0.00010245314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037162881,0.00060378993,0.0007994153,0.0009847527,0.0003826268,0.0012239884,0.0015034984,0.0013476759,0.0030655407],"category_scores_gemma":[0.020815251,0.00045599218,0.00071809103,0.0009188964,0.0010651803,0.002019605,0.00122421,0.0014603358,0.0006731992],"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":[0.00068519555,0.00018119835,0.017726727,0.00040215912,0.00032023375,0.00039002692,0.00044529667,0.48443225,0.01679174,0.17766303,0.003812155,0.29715008],"study_design_scores_gemma":[0.0000259457,0.000038245078,0.0034235036,0.00002360633,0.000024901172,0.00018362804,0.000044557783,0.961475,0.0034479334,0.030299988,0.0009870232,0.000025677977],"about_ca_topic_score_codex":0.0045294915,"about_ca_topic_score_gemma":0.0032717818,"teacher_disagreement_score":0.0045294915,"about_ca_system_score_codex":0.0005910911,"about_ca_system_score_gemma":0.0015878214,"threshold_uncertainty_score":0.019653857},"labels":[],"label_agreement":null},{"id":"W2089256781","doi":"10.1007/s00184-008-0203-6","title":"Estimation of parameters of parallelism model with elliptically distributed errors","year":2008,"lang":"en","type":"article","venue":"Metrika","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Shahrood University of Technology","keywords":"Mathematics; Estimator; Statistics; Applied mathematics; Quadratic equation; Parallelism (grammar); Mixing (physics); Geometry; Computer science","score_opus":0.05507288310678586,"score_gpt":0.2241990501077688,"score_spread":0.16912616700098293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089256781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15452945,0.00018523548,0.8440035,0.00029134905,0.000025715375,0.000024979592,0.00010576435,0.00021193526,0.0006220617],"genre_scores_gemma":[0.90822756,0.00021148782,0.08897719,0.000050507962,0.000029024373,0.000055785258,0.0003413462,0.00009790916,0.002009252],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989698,0.0005413992,0.000060485952,0.00023322226,0.000100085956,0.0000950337],"domain_scores_gemma":[0.99066824,0.007653658,0.00066011824,0.0004962116,0.00040210655,0.00011960158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033036454,0.0006526772,0.001323676,0.0005831698,0.00040203772,0.0015854564,0.0012520148,0.0021092582,0.001375811],"category_scores_gemma":[0.021535061,0.0010271579,0.0010388503,0.00064891047,0.00074052013,0.0020639857,0.0013242218,0.0019377957,0.00042109416],"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":[0.00017426294,0.00004658711,0.004606111,0.000060780523,0.00009799543,0.00009549104,0.00013708496,0.95614445,0.0012546519,0.020532254,0.00029251067,0.016557788],"study_design_scores_gemma":[0.000014807833,0.000013960496,0.00070486555,0.000008860251,0.000012765138,0.000022451148,0.000014194185,0.99137855,0.0005375006,0.0071540587,0.00012688003,0.0000111502295],"about_ca_topic_score_codex":0.006095311,"about_ca_topic_score_gemma":0.0026726208,"teacher_disagreement_score":0.006095311,"about_ca_system_score_codex":0.00059018255,"about_ca_system_score_gemma":0.0010805808,"threshold_uncertainty_score":0.017471552},"labels":[],"label_agreement":null},{"id":"W2092586704","doi":"10.1007/s00184-005-0014-y","title":"Monotonicity of the (reversed) hazard rate of the (maximum) minimum in bivariate distributions","year":2005,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Mathematics; Monotonic function; Hazard ratio; Bivariate analysis; Hazard; Statistics; Econometrics; Applied mathematics; Confidence interval; Mathematical analysis; Chemistry","score_opus":0.048901531614347744,"score_gpt":0.3300938998218602,"score_spread":0.2811923682075125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092586704","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.124583624,0.0012901698,0.85894287,0.003142409,0.00013565035,0.00009635347,0.00059726305,0.00036223567,0.010849462],"genre_scores_gemma":[0.8415341,0.0021561715,0.14601201,0.00077482976,0.00057255966,0.0005569495,0.0006996707,0.00055548444,0.00713825],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9946122,0.0030429657,0.00026268742,0.00091276993,0.00064068916,0.0005286137],"domain_scores_gemma":[0.9053986,0.077326395,0.0056583923,0.0048713684,0.005081238,0.001663907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018893458,0.0007822877,0.0021845335,0.0017547114,0.00079123664,0.003539502,0.0029952016,0.0015828597,0.008359221],"category_scores_gemma":[0.1269277,0.0011144956,0.0018299931,0.0013515514,0.0044991164,0.007762865,0.00300498,0.0058115837,0.0011316425],"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":[0.00060084835,0.000100230776,0.009199369,0.00072324695,0.00012749108,0.00049880985,0.0008885122,0.036854424,0.005334117,0.8946744,0.004061087,0.046937414],"study_design_scores_gemma":[0.0001156785,0.00021567979,0.007124459,0.00023855554,0.00007369962,0.001377298,0.00025206938,0.20722643,0.004173425,0.77573395,0.0033679488,0.00010075495],"about_ca_topic_score_codex":0.0012597662,"about_ca_topic_score_gemma":0.00065781915,"teacher_disagreement_score":0.018893458,"about_ca_system_score_codex":0.0012744319,"about_ca_system_score_gemma":0.0021760447,"threshold_uncertainty_score":0.09991938},"labels":[],"label_agreement":null},{"id":"W2093931098","doi":"10.1007/s00184-011-0373-5","title":"An information theoretical algorithm for analyzing supersaturated designs for a binary response","year":2011,"lang":"en","type":"article","venue":"Metrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Bernoulli's principle; Entropy (arrow of time); Binary number; Measure (data warehouse); Algorithm; Binary data; Information theory; Statistics; Type I and type II errors; Applied mathematics; Mathematical optimization; Computer science; Data mining","score_opus":0.24055488432725156,"score_gpt":0.4568054255120258,"score_spread":0.21625054118477424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093931098","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":[0.0012585369,0.000072236784,0.99772483,0.000070331706,0.000011454114,0.0001968403,0.000085269785,0.0001497128,0.00043085613],"genre_scores_gemma":[0.03686289,0.00014801264,0.959964,0.00014760597,0.00004194019,0.0017698895,0.00024712156,0.00009329273,0.00072524644],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98181826,0.013125967,0.00069414644,0.0018394234,0.0020300979,0.0004920832],"domain_scores_gemma":[0.899996,0.09179911,0.0020435285,0.002928783,0.0027693112,0.00046327815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027106827,0.002810887,0.0046219965,0.0046748193,0.0015823042,0.002699077,0.0034596422,0.0027118358,0.011347085],"category_scores_gemma":[0.06879676,0.002651233,0.0036942672,0.0033107528,0.003576217,0.0037260181,0.0031289714,0.0036577953,0.0015845598],"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":[0.0019013643,0.00047986506,0.0015288546,0.0011859079,0.00070811633,0.00012190067,0.00048304835,0.32244655,0.004463826,0.3550757,0.0038821711,0.30772266],"study_design_scores_gemma":[0.00032238654,0.0004164892,0.00033505698,0.00013417965,0.00014545783,0.000079712896,0.000052671436,0.71051514,0.0019746565,0.28353247,0.002440406,0.000051424173],"about_ca_topic_score_codex":0.002525398,"about_ca_topic_score_gemma":0.0025990028,"teacher_disagreement_score":0.027106827,"about_ca_system_score_codex":0.0033084988,"about_ca_system_score_gemma":0.0075260587,"threshold_uncertainty_score":0.14335626},"labels":[],"label_agreement":null},{"id":"W2114168672","doi":"10.1007/s00184-007-0124-9","title":"Empirical likelihood for average derivatives of hazard regression functions","year":2007,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Mathematics; Empirical likelihood; Covariate; Statistics; Regression analysis; Monte Carlo method; Hazard ratio; Inference; Applied mathematics; Econometrics; Confidence interval; Computer science; Artificial intelligence","score_opus":0.15963161122381855,"score_gpt":0.4447488618463279,"score_spread":0.28511725062250937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114168672","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":[0.018491432,0.0006046287,0.9784297,0.00074525626,0.000038222275,0.000029766712,0.00025207555,0.0002834094,0.0011255958],"genre_scores_gemma":[0.6976023,0.002628818,0.28167734,0.00044123587,0.00047904562,0.0004890361,0.0015919956,0.0007917773,0.014298518],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9946489,0.0034255427,0.00023150591,0.0007365481,0.0006362611,0.00032134025],"domain_scores_gemma":[0.901637,0.08871273,0.003023526,0.003950381,0.0018158593,0.0008605854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01903313,0.0011196812,0.002229535,0.0031198899,0.00089674536,0.0045717848,0.0038085987,0.0025388654,0.007357393],"category_scores_gemma":[0.116527714,0.0014624046,0.0019074532,0.002575691,0.003959779,0.0074943835,0.0025846506,0.005626249,0.0011124727],"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":[0.00017419999,0.00007007374,0.0063527273,0.0002886067,0.00020704918,0.00031547787,0.00049525016,0.14151336,0.0006524646,0.80507,0.003232214,0.041628588],"study_design_scores_gemma":[0.0000332259,0.000026919526,0.0017596411,0.000058448233,0.000042427775,0.00023246187,0.00007319517,0.4148336,0.0003156215,0.58122295,0.0013634525,0.00003802987],"about_ca_topic_score_codex":0.0043996302,"about_ca_topic_score_gemma":0.0029951036,"teacher_disagreement_score":0.01903313,"about_ca_system_score_codex":0.0022167778,"about_ca_system_score_gemma":0.0024478852,"threshold_uncertainty_score":0.10065806},"labels":[],"label_agreement":null},{"id":"W2122839776","doi":"10.1007/s00184-014-0485-9","title":"On extremes of bivariate residual lifetimes from generalized Marshall–Olkin and time transformed exponential models","year":2014,"lang":"en","type":"article","venue":"Metrika","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Residual; Mathematics; Bivariate analysis; Exponential function; Majorization; Applied mathematics; Statistics; Statistical physics; Mathematical analysis; Combinatorics; Algorithm","score_opus":0.06741545556025746,"score_gpt":0.2865873617956848,"score_spread":0.21917190623542732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122839776","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13559571,0.0023727855,0.847665,0.0019941356,0.00016885728,0.000088091765,0.00035814787,0.00031663614,0.011440688],"genre_scores_gemma":[0.943613,0.0029443419,0.037977505,0.00046050886,0.0004645516,0.00020348864,0.0006712426,0.0003086481,0.01335666],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99754363,0.0012929772,0.0001082975,0.0003789786,0.0003540348,0.00032206535],"domain_scores_gemma":[0.9768878,0.016074527,0.0034582585,0.00089761405,0.0016009043,0.0010809347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011346572,0.001659842,0.002541436,0.003486864,0.0011643481,0.0038476451,0.0036086866,0.0030449878,0.00491299],"category_scores_gemma":[0.04588005,0.0012184955,0.002706721,0.0024833311,0.0062361653,0.0070390124,0.004907033,0.0052611916,0.0005712901],"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":[0.00006978786,0.000026990783,0.0009834332,0.00009038311,0.000050497947,0.0001585048,0.00036274758,0.12205876,0.00059646624,0.8709627,0.00097466883,0.0036650782],"study_design_scores_gemma":[0.000014017913,0.00003082158,0.0005333738,0.000056155826,0.00002926358,0.00010953898,0.00013797908,0.47842637,0.0001477528,0.51951516,0.00093788997,0.000061667466],"about_ca_topic_score_codex":0.004833874,"about_ca_topic_score_gemma":0.002841284,"teacher_disagreement_score":0.011346572,"about_ca_system_score_codex":0.0028444335,"about_ca_system_score_gemma":0.0015109234,"threshold_uncertainty_score":0.060007155},"labels":[],"label_agreement":null},{"id":"W2132569857","doi":"10.1007/s00184-007-0155-2","title":"Precedence-type tests based on record values","year":2007,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Nonparametric statistics; Context (archaeology); Type (biology); Test (biology); Statistics; Statistical hypothesis testing; Null hypothesis; Rank (graph theory); Null (SQL); Algorithm; Data mining; Computer science; Combinatorics","score_opus":0.1262479895245397,"score_gpt":0.427341610326031,"score_spread":0.3010936208014913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132569857","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":[0.04150404,0.00026165368,0.94770855,0.0006101006,0.0003831457,0.00025707096,0.0011737683,0.0012662893,0.00683539],"genre_scores_gemma":[0.6228749,0.00030835258,0.36380562,0.0005315796,0.0005417018,0.0010654618,0.0026463014,0.00058669236,0.0076394645],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9601183,0.018087791,0.0038077973,0.007826036,0.008558055,0.0016020674],"domain_scores_gemma":[0.623318,0.3079579,0.012010772,0.042717647,0.01072353,0.003272161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.033057738,0.0011779767,0.0025852176,0.003949633,0.0016881413,0.0037196989,0.004315067,0.0030242098,0.018722394],"category_scores_gemma":[0.29225647,0.000768197,0.0027698246,0.005038783,0.0035718868,0.012323104,0.0033998082,0.0048165433,0.0028480443],"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":[0.0035131332,0.00049219985,0.0736423,0.0007538313,0.0005889214,0.0009711909,0.00081595784,0.013974755,0.0042547197,0.38097474,0.009491658,0.51052654],"study_design_scores_gemma":[0.00050081435,0.0015540743,0.019110978,0.00026649056,0.0003581846,0.0025744298,0.0006411099,0.19366847,0.011358798,0.75828815,0.011508271,0.00017024876],"about_ca_topic_score_codex":0.0011059432,"about_ca_topic_score_gemma":0.0010202408,"teacher_disagreement_score":0.033057738,"about_ca_system_score_codex":0.00082694564,"about_ca_system_score_gemma":0.0037272184,"threshold_uncertainty_score":0.17482811},"labels":[],"label_agreement":null},{"id":"W2135843367","doi":"10.1007/s00184-014-0514-8","title":"Blocked semifoldovers of two-level orthogonal designs","year":2014,"lang":"en","type":"article","venue":"Metrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Fractional factorial design; Factorial experiment; Fraction (chemistry); Mathematics; Block (permutation group theory); Blocking (statistics); Factor (programming language); Mathematical optimization; Design of experiments; Econometrics; Computer science; Statistics; Combinatorics","score_opus":0.37527729619071154,"score_gpt":0.4833293118572496,"score_spread":0.10805201566653805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135843367","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":[0.008891143,0.00014333401,0.98967147,0.00003535984,0.00005023145,0.000214959,0.00011643175,0.0001497856,0.000727242],"genre_scores_gemma":[0.14809966,0.00024427316,0.844428,0.00013695337,0.000085604544,0.003881474,0.00042493455,0.00015670965,0.0025422978],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9357426,0.05287003,0.0019294933,0.004626932,0.0032785588,0.0015523961],"domain_scores_gemma":[0.9190093,0.062579215,0.0037645593,0.010678835,0.0029596507,0.0010084315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04875816,0.002192003,0.0038438016,0.0014677047,0.00069554197,0.001972701,0.0024672528,0.0015573403,0.012047052],"category_scores_gemma":[0.06709173,0.001582168,0.0031098214,0.0012667141,0.0034172125,0.0030295656,0.0036872644,0.002179068,0.001591547],"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":[0.013418832,0.0012597353,0.0027323035,0.0023511422,0.0013969161,0.00015030436,0.00085191434,0.10501077,0.016817134,0.50294507,0.002952999,0.35011286],"study_design_scores_gemma":[0.0016236315,0.0060121682,0.0021051927,0.00028414396,0.00048662515,0.00013108284,0.00013371016,0.5720255,0.012810819,0.39375433,0.010473594,0.00015923983],"about_ca_topic_score_codex":0.00044343254,"about_ca_topic_score_gemma":0.0004902558,"teacher_disagreement_score":0.04875816,"about_ca_system_score_codex":0.0012940032,"about_ca_system_score_gemma":0.0027638976,"threshold_uncertainty_score":0.2578609},"labels":[],"label_agreement":null},{"id":"W2176278866","doi":"10.1007/s00184-015-0566-4","title":"Single change-point detection methods for small lifetime samples","year":2015,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Failure rate; Statistics; Homogeneity (statistics); Parametric statistics; Null hypothesis; Monte Carlo method; Test statistic; Exponential distribution; Statistical hypothesis testing; Statistic; Sample size determination; Applied mathematics; Statistical physics","score_opus":0.5370483513249094,"score_gpt":0.47233757448959257,"score_spread":0.06471077683531679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2176278866","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":[0.0022178313,0.000360114,0.99682236,0.00013109954,0.000043432054,0.000026581656,0.00006349398,0.000112840404,0.00022232704],"genre_scores_gemma":[0.22718324,0.001381353,0.76073545,0.0003967665,0.00054181454,0.0008638246,0.0009121427,0.0004197273,0.007565741],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9935875,0.0031585416,0.00033459812,0.0016857375,0.0010170798,0.00021652284],"domain_scores_gemma":[0.92240316,0.06539821,0.0026891157,0.0066578113,0.0023501555,0.0005015283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019347379,0.0011996662,0.0028099648,0.002878159,0.0010711061,0.0023259073,0.0049611954,0.0026529876,0.0042566075],"category_scores_gemma":[0.09586781,0.0011787298,0.0020061047,0.0023296513,0.0031786105,0.0046457737,0.0030682774,0.00489462,0.001241189],"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":[0.0005920983,0.0001941309,0.00756253,0.0009316578,0.00082895765,0.00042826246,0.0006037738,0.124772504,0.0044118958,0.50387675,0.005875889,0.3499215],"study_design_scores_gemma":[0.00005381647,0.00009364953,0.0013322277,0.000064895496,0.00010348437,0.00027616104,0.00006269214,0.6494417,0.0017685745,0.34226373,0.004497894,0.000041198502],"about_ca_topic_score_codex":0.0017859889,"about_ca_topic_score_gemma":0.001663842,"teacher_disagreement_score":0.019347379,"about_ca_system_score_codex":0.0010247129,"about_ca_system_score_gemma":0.0014120807,"threshold_uncertainty_score":0.102319956},"labels":[],"label_agreement":null},{"id":"W2471288921","doi":"10.1007/s00184-014-0515-7","title":"On estimating the tail index and the spectral measure of multivariate $$\\alpha $$ α -stable distributions","year":2014,"lang":"en","type":"article","venue":"Metrika","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Japan Society for the Promotion of Science","keywords":"Mathematics; Multivariate statistics; Estimator; Measure (data warehouse); Index (typography); Statistics; Spectral measure; Alpha (finance); Econometrics; Mathematical analysis","score_opus":0.02725701277884585,"score_gpt":0.22909634852993802,"score_spread":0.20183933575109217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2471288921","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021429492,0.0002923004,0.97724336,0.0001643044,0.000019362307,0.000022506278,0.000049916976,0.00013143309,0.00064741354],"genre_scores_gemma":[0.5415743,0.0022757126,0.44946417,0.0003093117,0.00039898517,0.00023046433,0.0010036348,0.00044190342,0.0043015797],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99861073,0.0008481841,0.00006849422,0.00020446745,0.00017429203,0.00009388398],"domain_scores_gemma":[0.9715077,0.025433972,0.0010675683,0.0007760243,0.0008492554,0.00036546038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067281974,0.0019091181,0.0017880262,0.0025239056,0.00063012243,0.002562912,0.0023576657,0.0020833167,0.0020526561],"category_scores_gemma":[0.040718164,0.0012467727,0.0014825404,0.0018785355,0.0021423164,0.0041802167,0.002619441,0.002433795,0.00075765606],"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":[0.00022503562,0.00016238034,0.007949042,0.0002007751,0.0001998303,0.00016376756,0.0002767126,0.6531232,0.0040469305,0.20522036,0.0022326445,0.1261993],"study_design_scores_gemma":[0.0000070481215,0.000014383543,0.00042359793,0.000015606518,0.0000073756114,0.000027651464,0.0000184035,0.94301224,0.00037316736,0.0558851,0.00019604657,0.000019366418],"about_ca_topic_score_codex":0.0043372638,"about_ca_topic_score_gemma":0.003485022,"teacher_disagreement_score":0.0067281974,"about_ca_system_score_codex":0.0009437065,"about_ca_system_score_gemma":0.0013756243,"threshold_uncertainty_score":0.035582542},"labels":[],"label_agreement":null},{"id":"W2526674685","doi":"10.1007/s00184-016-0595-7","title":"Blocked factor aliased effect-number pattern and column rank of blocked regular designs","year":2016,"lang":"en","type":"article","venue":"Metrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Mathematics; Column (typography); Ranking (information retrieval); Rank (graph theory); Factor (programming language); Combinatorics; Statistics; Selection (genetic algorithm); Fractional factorial design; Factorial experiment; Geometry; Computer science; Artificial intelligence","score_opus":0.13119729395925922,"score_gpt":0.4245310810891063,"score_spread":0.2933337871298471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2526674685","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":[0.005728517,0.00011171579,0.9925546,0.00008966606,0.000036285033,0.00025804088,0.00023777648,0.00029080574,0.000692478],"genre_scores_gemma":[0.13277926,0.00022777071,0.85987866,0.00016612254,0.000088002314,0.0029101411,0.0004955591,0.00035909956,0.0030954669],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.89399797,0.081793904,0.0037383775,0.010600628,0.0076688393,0.0022002405],"domain_scores_gemma":[0.71917266,0.21496387,0.014257009,0.04228612,0.007855746,0.0014646898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.073553465,0.0035142426,0.0056603914,0.002376458,0.0011330249,0.0032590972,0.0051258053,0.0039029429,0.018226782],"category_scores_gemma":[0.23867953,0.003264438,0.003533582,0.0028078225,0.005783783,0.0062769745,0.0030085251,0.0038847625,0.0026180085],"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":[0.013612698,0.0015731221,0.004808064,0.003381731,0.0018173471,0.00037352188,0.0009311666,0.13431056,0.015916938,0.45013985,0.0053863013,0.3677486],"study_design_scores_gemma":[0.0014926243,0.002655792,0.003301918,0.000318377,0.0006229189,0.00024674885,0.00011810653,0.575275,0.011668664,0.3966697,0.007415223,0.00021487998],"about_ca_topic_score_codex":0.0011121099,"about_ca_topic_score_gemma":0.0012919522,"teacher_disagreement_score":0.073553465,"about_ca_system_score_codex":0.0020321752,"about_ca_system_score_gemma":0.005222987,"threshold_uncertainty_score":0.38899255},"labels":[],"label_agreement":null},{"id":"W2582193","doi":"10.1007/s001840200215","title":"Preliminary test estimators of the parameters of simple linear model with measurement error","year":2003,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical and numerical algorithms","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Estimator; Mathematics; Statistics; Observational error; Errors-in-variables models; Standard error; Delta method; Variance (accounting); Linear model; Applied mathematics; Mean squared error","score_opus":0.10883201471335582,"score_gpt":0.3122783260936506,"score_spread":0.20344631138029476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2582193","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":[0.011498161,0.00024927096,0.98702663,0.00019214317,0.00004900564,0.00004842321,0.000124371,0.00020654315,0.00060551765],"genre_scores_gemma":[0.35345024,0.0006777298,0.638252,0.00023094183,0.00029198444,0.0005945299,0.0017526228,0.00024729336,0.004502632],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99718505,0.0018458992,0.00016091528,0.00029004642,0.00038253664,0.00013546963],"domain_scores_gemma":[0.9089574,0.08104884,0.002895731,0.0036337906,0.0028385553,0.0006256183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010951057,0.001415273,0.0014758749,0.0017282268,0.00047428085,0.0018014258,0.0020401971,0.0024230105,0.005961255],"category_scores_gemma":[0.10469229,0.0008004828,0.0010223965,0.0013572101,0.0016271207,0.003108865,0.00193146,0.0018576947,0.0012211552],"study_design_candidate":"simulation_or_modeling","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":[0.0026144648,0.00039370576,0.016311688,0.001253778,0.00062667765,0.00051616173,0.00061426364,0.28171083,0.01860581,0.3099682,0.007075148,0.3603093],"study_design_scores_gemma":[0.00016248427,0.00044320588,0.005090596,0.00010768331,0.00015187419,0.00031053415,0.00011264115,0.8088263,0.014408157,0.1653523,0.0049535604,0.0000805782],"about_ca_topic_score_codex":0.0012882873,"about_ca_topic_score_gemma":0.0011551782,"teacher_disagreement_score":0.010951057,"about_ca_system_score_codex":0.00070961966,"about_ca_system_score_gemma":0.001363265,"threshold_uncertainty_score":0.05791539},"labels":[],"label_agreement":null},{"id":"W2620087004","doi":"10.1007/s00184-018-0698-4","title":"Efficient estimation of the varying-coefficient partially linear proportional odds model with current status data","year":2018,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Statistics; Current (fluid); Odds; Applied mathematics; Linear model; Estimation; Econometrics; Logistic regression","score_opus":0.18559490912023546,"score_gpt":0.4199071875368653,"score_spread":0.23431227841662983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620087004","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":[0.018825835,0.00042787066,0.97831696,0.0006999741,0.000046380806,0.00009769434,0.00068082724,0.00037493292,0.00052954076],"genre_scores_gemma":[0.46727854,0.00089054066,0.5202302,0.00035983257,0.000287984,0.00075160834,0.0038256885,0.00029463723,0.0060810037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9878649,0.008546819,0.00047376667,0.001957313,0.00067155703,0.0004855677],"domain_scores_gemma":[0.92241,0.06806269,0.0026396995,0.005291799,0.0011437794,0.00045198516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02152576,0.001284217,0.0034149075,0.0015359093,0.0007357614,0.002872356,0.007004602,0.0019480657,0.005168361],"category_scores_gemma":[0.09445239,0.002250332,0.002279094,0.0030537986,0.0019645605,0.0043354398,0.0030665712,0.004029076,0.0012975953],"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":[0.001743404,0.00031772646,0.028822476,0.0008126539,0.0013903725,0.0007891316,0.00069970684,0.5184369,0.0010440925,0.20237389,0.008286194,0.23528343],"study_design_scores_gemma":[0.00009956875,0.00008042688,0.0017354521,0.00004117263,0.000138909,0.00017392678,0.00007780935,0.9021965,0.00028396814,0.093440525,0.0017001488,0.000031588992],"about_ca_topic_score_codex":0.012975418,"about_ca_topic_score_gemma":0.011519122,"teacher_disagreement_score":0.02152576,"about_ca_system_score_codex":0.0012351843,"about_ca_system_score_gemma":0.003363344,"threshold_uncertainty_score":0.11384046},"labels":[],"label_agreement":null},{"id":"W2760946807","doi":"10.1007/s00184-017-0626-z","title":"Stochastic comparisons of order statistics from heterogeneous random variables with Archimedean copula","year":2017,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Copula (linguistics); Mathematics; Order statistic; Statistic; Statistics; Econometrics; Random variable; Stochastic ordering; Applied mathematics","score_opus":0.07773537635964617,"score_gpt":0.36432660099093184,"score_spread":0.28659122463128567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2760946807","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19710517,0.0005527687,0.7993582,0.0003231128,0.0000794788,0.00008801471,0.00017773882,0.00012002864,0.002195509],"genre_scores_gemma":[0.9194013,0.00061869796,0.07636399,0.00013042273,0.00019284793,0.00017850305,0.0005314759,0.00012864808,0.0024542334],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9919355,0.0051814737,0.00035792298,0.0009257328,0.0011671608,0.0004322723],"domain_scores_gemma":[0.868588,0.11461512,0.006204111,0.005769903,0.0034517366,0.0013711217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.025041174,0.0011415026,0.0023629328,0.002997753,0.0006758055,0.0032959545,0.0022355726,0.0017243722,0.0031973226],"category_scores_gemma":[0.08879378,0.0008621411,0.0020901344,0.0023033482,0.0032212667,0.0053914874,0.002359067,0.0022749016,0.00027558795],"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":[0.0004984941,0.00020552981,0.006523756,0.0002417651,0.0004536073,0.00036322133,0.00039438682,0.33670074,0.0015528859,0.6264428,0.0009368285,0.025685985],"study_design_scores_gemma":[0.00003421396,0.00014504764,0.0033580854,0.00003584105,0.00007003812,0.00008273429,0.00011285296,0.77403843,0.00068757747,0.22091283,0.00047247045,0.000049865885],"about_ca_topic_score_codex":0.0018775611,"about_ca_topic_score_gemma":0.0014231551,"teacher_disagreement_score":0.025041174,"about_ca_system_score_codex":0.0019125193,"about_ca_system_score_gemma":0.0017925262,"threshold_uncertainty_score":0.13243198},"labels":[],"label_agreement":null},{"id":"W2781700442","doi":"10.1007/s00184-017-0640-1","title":"Exact inference for Laplace distribution under progressive Type-II censoring based on BLUEs","year":2018,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Quantile; Applied mathematics; Estimator; Order statistic; Laplace distribution; Laplace transform; Statistics; Moment-generating function; Scale parameter; Probability density function; Mathematical analysis","score_opus":0.11062269176798989,"score_gpt":0.42792032316444695,"score_spread":0.31729763139645706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781700442","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011616043,0.00030067808,0.9865454,0.00028389602,0.000050253046,0.00002931972,0.00014707922,0.00029136214,0.0007360476],"genre_scores_gemma":[0.6560853,0.0016763622,0.32644135,0.00066175417,0.0006307642,0.00037512014,0.0017583213,0.0004605409,0.011910531],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952324,0.002429953,0.00020461173,0.0009738806,0.00074030965,0.00041874795],"domain_scores_gemma":[0.94027334,0.050878316,0.0019294486,0.004339364,0.0018456741,0.0007338984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015458022,0.0011844464,0.003024887,0.002244485,0.0009320968,0.0025154217,0.0043119993,0.0021969874,0.0066480874],"category_scores_gemma":[0.08300914,0.0015680746,0.0019263834,0.0024094412,0.004454713,0.0065987553,0.00349329,0.004282641,0.001386188],"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":[0.0007952213,0.00018641065,0.0124313515,0.0005445565,0.00038650702,0.0006952229,0.00068655866,0.30107275,0.0036643133,0.5607199,0.0050804373,0.11373676],"study_design_scores_gemma":[0.000049200888,0.000044138742,0.00125536,0.000058138863,0.000042006726,0.00013870916,0.00006244258,0.7172021,0.0008921094,0.27913845,0.0010843967,0.000032883283],"about_ca_topic_score_codex":0.0038886447,"about_ca_topic_score_gemma":0.0033856314,"teacher_disagreement_score":0.015458022,"about_ca_system_score_codex":0.0015064506,"about_ca_system_score_gemma":0.0019707754,"threshold_uncertainty_score":0.08175081},"labels":[],"label_agreement":null},{"id":"W2795014879","doi":"10.1007/s00184-018-0656-1","title":"Shrinkage estimation in linear mixed models for longitudinal data","year":2018,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Lasso (programming language); Covariate; Mathematics; Penalty method; Shrinkage; Linear model; Statistics; Random effects model; Mixed model; Mathematical optimization; Applied mathematics; Computer science","score_opus":0.2786613555191302,"score_gpt":0.4533145887574207,"score_spread":0.17465323323829052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795014879","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":[0.001547486,0.0008706934,0.9966413,0.00049643696,0.00004698743,0.000025115349,0.00006879785,0.000107878375,0.00019532535],"genre_scores_gemma":[0.12087909,0.005787938,0.8615372,0.00072511233,0.0010332939,0.0014930128,0.0011097081,0.00054723915,0.0068873717],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9773392,0.018216385,0.00088738196,0.0019827615,0.0012078388,0.00036643643],"domain_scores_gemma":[0.837644,0.14892246,0.0043190024,0.0057273936,0.0027302431,0.0006569223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04210999,0.0023545565,0.0037498216,0.0029429162,0.0012060255,0.0031412079,0.005102882,0.0039648153,0.0036232825],"category_scores_gemma":[0.16454688,0.0032334435,0.0031044893,0.0041312836,0.005573634,0.005492451,0.004635235,0.007942145,0.0010299211],"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":[0.00021679848,0.00012204012,0.0024851032,0.0011745514,0.00077888137,0.00026219012,0.0007549596,0.14674476,0.0011272317,0.7496695,0.004472017,0.092191964],"study_design_scores_gemma":[0.000054766828,0.00004481322,0.0004526318,0.00011928159,0.00010934387,0.000102280545,0.000049785984,0.38996738,0.00034904014,0.6058871,0.002814443,0.000049219758],"about_ca_topic_score_codex":0.0068077636,"about_ca_topic_score_gemma":0.0066318177,"teacher_disagreement_score":0.04210999,"about_ca_system_score_codex":0.0021045562,"about_ca_system_score_gemma":0.0038353007,"threshold_uncertainty_score":0.22270155},"labels":[],"label_agreement":null},{"id":"W2895907638","doi":"10.1007/s00184-018-0692-x","title":"Mean mixtures of normal distributions: properties, inference and application","year":2018,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Kurtosis; Estimator; Skewness; Applied mathematics; Skew normal distribution; Range (aeronautics); Normal distribution; Distribution (mathematics); Multivariate normal distribution; Matrix (chemical analysis); Statistics; Multivariate statistics; Mathematical analysis","score_opus":0.06595275040783366,"score_gpt":0.3536716441638419,"score_spread":0.28771889375600823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895907638","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":[0.0030801217,0.00052255584,0.99566,0.00016210519,0.000028008288,0.00001527303,0.000041704694,0.00008755332,0.00040261203],"genre_scores_gemma":[0.2443635,0.003386363,0.74474216,0.00027497375,0.0004816358,0.00038721564,0.0006884198,0.0003262913,0.005349463],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.994167,0.0031314127,0.0002770752,0.0011100102,0.0010886523,0.00022589495],"domain_scores_gemma":[0.9536122,0.03853397,0.0021894937,0.00235764,0.0028375932,0.00046921664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012053121,0.0014665994,0.0024681026,0.0035681296,0.001238756,0.00453343,0.0034025267,0.0026160283,0.0024043578],"category_scores_gemma":[0.07530573,0.0019334622,0.0024354314,0.0038184351,0.0045285346,0.0066648074,0.0033653968,0.005142889,0.0009189161],"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":[0.0002647286,0.000109742905,0.0056191045,0.00037808696,0.00024187203,0.00020593443,0.0007993634,0.15457472,0.0019520244,0.719606,0.0029472155,0.11330118],"study_design_scores_gemma":[0.00001895343,0.000034729987,0.000802969,0.000064925065,0.00004344089,0.00023041369,0.00008075741,0.5761305,0.0007432251,0.41940016,0.002394547,0.000055335262],"about_ca_topic_score_codex":0.0046540317,"about_ca_topic_score_gemma":0.0037261117,"teacher_disagreement_score":0.012053121,"about_ca_system_score_codex":0.0017020127,"about_ca_system_score_gemma":0.0015915115,"threshold_uncertainty_score":0.06374371},"labels":[],"label_agreement":null},{"id":"W2896344278","doi":"10.1007/s00184-018-0690-z","title":"An approximate method for generalized linear and nonlinear mixed effects models with a mechanistic nonlinear covariate measurement error model","year":2018,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"City University of New York; National Science Foundation","keywords":"Covariate; Mathematics; Estimator; Nonlinear system; Applied mathematics; Consistency (knowledge bases); Inference; Asymptotic distribution; Linear model; Statistics; Errors-in-variables models; Computer science; Artificial intelligence","score_opus":0.1623960712519726,"score_gpt":0.40362027872458406,"score_spread":0.24122420747261145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896344278","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":[0.00022564802,0.000090620975,0.9994173,0.00006156349,0.000016300246,0.000014828201,0.000023474391,0.000033671917,0.00011662194],"genre_scores_gemma":[0.01700623,0.00043671316,0.97920585,0.00020017271,0.00013098835,0.0006317342,0.00017211278,0.0001721658,0.0020440097],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99218386,0.0059059495,0.0002574449,0.0006474158,0.00084849575,0.00015679227],"domain_scores_gemma":[0.97735274,0.019012576,0.0007232864,0.0014699299,0.001148953,0.00029248704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014464135,0.0016463732,0.0027070916,0.002305927,0.0011001021,0.0019828132,0.005711543,0.0030428374,0.0059557254],"category_scores_gemma":[0.045206565,0.0017450334,0.002988926,0.003125441,0.0025835852,0.0032935604,0.0040479293,0.004957823,0.0013612153],"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":[0.00018300705,0.000107232125,0.0009292775,0.0006333642,0.00054329855,0.00022178474,0.00040626252,0.17848782,0.0016935548,0.6627736,0.0038184454,0.15020233],"study_design_scores_gemma":[0.00005008825,0.00007082247,0.00029876706,0.00009843571,0.00013759271,0.00017443448,0.00004212363,0.6506726,0.0005184787,0.33925575,0.008625359,0.00005552635],"about_ca_topic_score_codex":0.0071795527,"about_ca_topic_score_gemma":0.010900728,"teacher_disagreement_score":0.014464135,"about_ca_system_score_codex":0.0019076049,"about_ca_system_score_gemma":0.0042669214,"threshold_uncertainty_score":0.076494575},"labels":[],"label_agreement":null},{"id":"W2905188466","doi":"10.1007/s00184-018-0702-z","title":"Some properties of foldover designs with column permutations","year":2018,"lang":"en","type":"article","venue":"Metrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Column (typography); Mathematics; Column generation; Optimal design; Mathematical optimization; Function (biology); Applied mathematics; Statistics; Geometry","score_opus":0.3358189822527115,"score_gpt":0.4444268068932322,"score_spread":0.10860782464052071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905188466","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":[0.011609457,0.0002751476,0.9846236,0.00029027893,0.00003232348,0.00020785898,0.00026236748,0.00012086728,0.0025781197],"genre_scores_gemma":[0.26579106,0.0010508244,0.7206122,0.0008640318,0.00031933666,0.0049167704,0.00089275645,0.00026777486,0.0052851364],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.95464915,0.035685994,0.0017785568,0.0035538585,0.0033149163,0.0010175147],"domain_scores_gemma":[0.7371312,0.23603177,0.008691302,0.012272982,0.004632422,0.0012403348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06519168,0.00226292,0.003750028,0.0023166311,0.0011173236,0.0029003436,0.00286972,0.0026226807,0.01100829],"category_scores_gemma":[0.15708621,0.0022778832,0.0033038885,0.0025823778,0.0048339935,0.0052981996,0.0034449399,0.0033762339,0.001152561],"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":[0.0011589096,0.0002879481,0.0025309292,0.0008786763,0.00046663114,0.00017113784,0.0005386223,0.060395896,0.0041702306,0.8061016,0.0023470437,0.12095237],"study_design_scores_gemma":[0.0003074898,0.0010712328,0.001562067,0.00019382821,0.00016251579,0.00017894444,0.00010620585,0.17743692,0.002604622,0.81302524,0.0032679138,0.000083046114],"about_ca_topic_score_codex":0.00064900605,"about_ca_topic_score_gemma":0.00065313705,"teacher_disagreement_score":0.06519168,"about_ca_system_score_codex":0.0017128813,"about_ca_system_score_gemma":0.004187687,"threshold_uncertainty_score":0.34477067},"labels":[],"label_agreement":null},{"id":"W2910904350","doi":"10.1007/s00184-020-00765-3","title":"The median of a jittered Poisson distribution","year":2020,"lang":"en","type":"preprint","venue":"Metrika","topic":"Point processes and geometric inequalities","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Lambda; Poisson distribution; Mathematics; Estimator; Distribution (mathematics); Combinatorics; Random variable; Simple (philosophy); Statistics; Mathematical analysis; Physics; Quantum mechanics","score_opus":0.13857124847497979,"score_gpt":0.3585744782082484,"score_spread":0.2200032297332686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910904350","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":[0.15797964,0.0021212825,0.8265055,0.0020214422,0.00030896842,0.00005097432,0.00049198396,0.00030588853,0.010214373],"genre_scores_gemma":[0.9162657,0.0028066377,0.061076645,0.00040167777,0.00088026567,0.00020607129,0.00053035474,0.000218378,0.01761422],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976277,0.0007258417,0.0001461011,0.00064502127,0.00053029216,0.00032520367],"domain_scores_gemma":[0.9817665,0.0127928015,0.0018928284,0.00085613993,0.001576096,0.0011155547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005577695,0.0011314442,0.0021998764,0.0034512598,0.001324215,0.005568636,0.0035163155,0.002399285,0.0053886273],"category_scores_gemma":[0.029266324,0.0011403962,0.0013099082,0.0026230034,0.0050852187,0.007955369,0.002910729,0.0036527922,0.0006113138],"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":[0.00015861492,0.000028265906,0.0011689113,0.00009665496,0.00004448802,0.00017735438,0.00025934706,0.039589968,0.001821649,0.94979334,0.0009291411,0.0059322603],"study_design_scores_gemma":[0.000025611218,0.00005452899,0.00074928615,0.000041445706,0.000035454246,0.00020549782,0.00011982309,0.32455158,0.0010749593,0.6715919,0.0014990006,0.00005086264],"about_ca_topic_score_codex":0.0023775243,"about_ca_topic_score_gemma":0.0010901926,"teacher_disagreement_score":0.005577695,"about_ca_system_score_codex":0.003074015,"about_ca_system_score_gemma":0.0015095528,"threshold_uncertainty_score":0.02949804},"labels":[],"label_agreement":null},{"id":"W2920529023","doi":"10.1007/s00184-019-00711-y","title":"On the large-sample behavior of two estimators of the conditional copula under serially dependent data","year":2019,"lang":"en","type":"article","venue":"Metrika","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Australian Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Estimator; Copula (linguistics); Combinatorics; Limiting; Covariate; Mixing (physics); Conditional expectation; Statistics; Random variable; Econometrics; Physics","score_opus":0.0785038158782613,"score_gpt":0.28332526748878845,"score_spread":0.20482145161052714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2920529023","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":[0.22890426,0.0027922897,0.7622079,0.0022894754,0.00014473917,0.0001434257,0.00030912546,0.0006129569,0.0025958337],"genre_scores_gemma":[0.8624634,0.0015279328,0.1313145,0.00047770605,0.00032572946,0.0002851308,0.00094890915,0.00037870617,0.0022780108],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98861444,0.008733156,0.0003679816,0.0011702481,0.0007234936,0.00039074468],"domain_scores_gemma":[0.4709118,0.5032536,0.008639517,0.010880875,0.0049463473,0.0013678655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05427886,0.0014543025,0.002187754,0.0030856028,0.0010077611,0.0035271137,0.0032936665,0.0035163823,0.0026699672],"category_scores_gemma":[0.32642305,0.0016283853,0.0013286177,0.0020657266,0.004741805,0.0076485844,0.002953315,0.0035671992,0.00036970308],"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":[0.0015629907,0.0004735105,0.04845113,0.0007572719,0.0015585687,0.00096150604,0.0018315418,0.40125304,0.0067244526,0.43031496,0.0048940335,0.10121695],"study_design_scores_gemma":[0.000105772844,0.00013379933,0.007679574,0.000101028534,0.00010061432,0.00025569493,0.00011842923,0.9326681,0.00122636,0.056999777,0.0005242594,0.00008654278],"about_ca_topic_score_codex":0.0034410867,"about_ca_topic_score_gemma":0.0023694986,"teacher_disagreement_score":0.05427886,"about_ca_system_score_codex":0.0016249106,"about_ca_system_score_gemma":0.0015819872,"threshold_uncertainty_score":0.28705752},"labels":[],"label_agreement":null},{"id":"W2946464768","doi":"10.1007/s00184-019-00718-5","title":"Robust estimators for one-shot device testing data under gamma lifetime model with an application to a tumor toxicological data","year":2019,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España; Ministerio de Educación, Cultura y Deporte","keywords":"Estimator; Mathematics; Statistics; Gamma distribution; Monte Carlo method; M-estimator; Accelerated life testing; Reliability (semiconductor); Wald test; Maximum likelihood; Divergence (linguistics); Statistical hypothesis testing; Power (physics); Weibull distribution","score_opus":0.5797135336752702,"score_gpt":0.4497564616326367,"score_spread":0.12995707204263351,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946464768","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005699965,0.00027455966,0.99352115,0.00006743959,0.000011704601,0.000020093603,0.00007247145,0.00018935595,0.00014321295],"genre_scores_gemma":[0.2602502,0.0011296065,0.73342,0.00013218074,0.00012945241,0.0003080034,0.0012590955,0.00030585678,0.0030655912],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975374,0.0011442171,0.00015463794,0.000519562,0.0005096691,0.00013460197],"domain_scores_gemma":[0.9682017,0.02482937,0.0022671472,0.0025690852,0.001874778,0.00025792522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0092612775,0.0010549271,0.0017746523,0.002006921,0.0004279997,0.0016072997,0.002928249,0.002318052,0.0014903274],"category_scores_gemma":[0.034807444,0.00074013736,0.0018014464,0.0017824773,0.0013449846,0.0021586304,0.0019819366,0.002746351,0.0005703594],"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":[0.00045610292,0.00025698863,0.004947562,0.0006432726,0.00052876177,0.0003785989,0.00037765392,0.58977497,0.018076263,0.11471148,0.0022932612,0.2675551],"study_design_scores_gemma":[0.000018658924,0.00007845466,0.0016120359,0.00003453271,0.000050785606,0.0001578059,0.000034136025,0.9663305,0.0024496529,0.028206458,0.0009834855,0.00004343778],"about_ca_topic_score_codex":0.0024387387,"about_ca_topic_score_gemma":0.0024225148,"teacher_disagreement_score":0.0092612775,"about_ca_system_score_codex":0.0009786922,"about_ca_system_score_gemma":0.0014476115,"threshold_uncertainty_score":0.048978925},"labels":[],"label_agreement":null},{"id":"W3105189197","doi":"10.1007/s00184-021-00856-9","title":"Consistency of the MLE under a two-parameter Gamma mixture model with a structural shape parameter","year":2022,"lang":"en","type":"article","venue":"Metrika","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Mathematics; Consistency (knowledge bases); Randomness; Shape parameter; Estimator; Estimation theory; Likelihood function; Mixing (physics); Gamma distribution; Mixture model; Applied mathematics; Generalized gamma distribution; Statistics","score_opus":0.024297362825762413,"score_gpt":0.2626929480173383,"score_spread":0.23839558519157586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3105189197","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":[0.023468576,0.0004879092,0.9723442,0.0010782476,0.0000691786,0.000056772173,0.00037854016,0.00047032916,0.0016461565],"genre_scores_gemma":[0.62037545,0.0009256564,0.36793852,0.0008423216,0.00043130663,0.0004920813,0.002875537,0.0017912209,0.0043279533],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9797366,0.012402073,0.0009125075,0.0044662682,0.0016934762,0.000788995],"domain_scores_gemma":[0.75658214,0.2192896,0.005040562,0.012114211,0.0057702325,0.0012033305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.038058545,0.0018235658,0.0050373394,0.0046219807,0.0018791801,0.0077056563,0.0077925758,0.005958411,0.0058722547],"category_scores_gemma":[0.2220529,0.0031378828,0.00310576,0.0031801776,0.007445803,0.010494418,0.005101241,0.007255026,0.0019846899],"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":[0.0012362973,0.00019961408,0.013481485,0.0009440786,0.0010080799,0.0004940201,0.00091468944,0.44569513,0.0035999287,0.46670505,0.0049249465,0.06079665],"study_design_scores_gemma":[0.00014664307,0.00006734252,0.0026011504,0.00016049822,0.00011190455,0.00035204893,0.000102393664,0.6170511,0.001509611,0.3763128,0.0014464554,0.00013816271],"about_ca_topic_score_codex":0.0033789207,"about_ca_topic_score_gemma":0.0022450255,"teacher_disagreement_score":0.038058545,"about_ca_system_score_codex":0.0016347824,"about_ca_system_score_gemma":0.0025432475,"threshold_uncertainty_score":0.20127523},"labels":[],"label_agreement":null},{"id":"W3134564767","doi":"10.1007/s00184-021-00822-5","title":"On a stochastic order induced by an extension of Panjer’s family of discrete distributions","year":2021,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Recursion (computer science); Factorization; Extension (predicate logic); Probability mass function; Convolution of probability distributions; K-distribution; Probability distribution; Applied mathematics; Order (exchange); Inverse distribution; Exponential family; Statistical physics; Heavy-tailed distribution; Statistics; Algorithm","score_opus":0.0933033456957399,"score_gpt":0.38436259449287297,"score_spread":0.2910592487971331,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134564767","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41627815,0.0005378778,0.56299573,0.00069182087,0.000099249184,0.000064357344,0.00031467443,0.00019325652,0.018824782],"genre_scores_gemma":[0.9381927,0.0004887879,0.052215096,0.00018708647,0.00020253636,0.00009318116,0.00026196835,0.00010504893,0.008253536],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986093,0.00040308363,0.0000721085,0.00024829662,0.0004644247,0.00020279744],"domain_scores_gemma":[0.9950405,0.0025456916,0.0006611147,0.0004348458,0.0008185294,0.0004993474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032467304,0.00036175657,0.0006987193,0.001607987,0.00095787604,0.0015260377,0.00069684495,0.0006188939,0.0034184386],"category_scores_gemma":[0.0069949566,0.0003316158,0.0009362012,0.0008645139,0.0021214404,0.002478696,0.0010801175,0.0015595878,0.00032237594],"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":[0.000034277804,0.00002524319,0.0010095153,0.000022084543,0.00001020968,0.00013914998,0.00015595522,0.009093574,0.0013139744,0.9838545,0.0004107848,0.003930901],"study_design_scores_gemma":[0.000028977105,0.00009479839,0.002491578,0.000033081502,0.0000130990375,0.00050528464,0.00010727099,0.2556161,0.0014507048,0.7352975,0.0043170326,0.000044408538],"about_ca_topic_score_codex":0.0022915013,"about_ca_topic_score_gemma":0.001794774,"teacher_disagreement_score":0.0034184386,"about_ca_system_score_codex":0.0014517986,"about_ca_system_score_gemma":0.000980806,"threshold_uncertainty_score":0.017170548},"labels":[],"label_agreement":null},{"id":"W3135039812","doi":"10.1007/s00184-021-00811-8","title":"Checking for model failure and for prior-data conflict with the constrained multinomial model","year":2021,"lang":"en","type":"article","venue":"Metrika","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Institute for Cancer Research; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Education, India; Ministry of Education - Singapore; National Research Foundation Singapore; National Research Foundation","keywords":"Multinomial distribution; Consistency (knowledge bases); Inference; Mathematics; Econometrics; Multinomial probit; Multinomial logistic regression; Statistics; Computer science; Artificial intelligence; Discrete mathematics","score_opus":0.13266981999480235,"score_gpt":0.32249443558338126,"score_spread":0.1898246155885789,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135039812","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":[0.029932242,0.00007784539,0.96723604,0.00064530584,0.000027825325,0.00012189681,0.00024131768,0.00044473883,0.001272793],"genre_scores_gemma":[0.54647315,0.00011576825,0.4504645,0.00044896145,0.00006188756,0.00047788664,0.0007155078,0.00029205007,0.00095025194],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9231551,0.049210932,0.004010119,0.0085141305,0.01301743,0.002092201],"domain_scores_gemma":[0.4139641,0.5230846,0.014762869,0.038188,0.00859889,0.001401511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06123485,0.0013811904,0.0022018997,0.0032641618,0.002226018,0.003922337,0.0045854375,0.003068893,0.0069674137],"category_scores_gemma":[0.4102786,0.0016091334,0.0028502648,0.0028609668,0.0049285404,0.008283768,0.007551028,0.006654924,0.00070306566],"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":[0.001685471,0.00045419202,0.03132316,0.001003308,0.0009418018,0.0027058383,0.0033278796,0.18452066,0.007825467,0.6430373,0.004190097,0.11898487],"study_design_scores_gemma":[0.00014554648,0.00013355548,0.0018431264,0.00018759214,0.00012151925,0.00061176374,0.0003966526,0.47769305,0.007974883,0.50858384,0.0022085416,0.000100032536],"about_ca_topic_score_codex":0.0035736063,"about_ca_topic_score_gemma":0.0034704597,"teacher_disagreement_score":0.06123485,"about_ca_system_score_codex":0.002193954,"about_ca_system_score_gemma":0.0047500576,"threshold_uncertainty_score":0.32384467},"labels":[],"label_agreement":null},{"id":"W3137498593","doi":"10.1007/s00184-023-00897-2","title":"A refined continuity correction for the negative binomial distribution and asymptotics of the median","year":2023,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Centre de Recherches Mathématiques","keywords":"Mathematics; Negative binomial distribution; Binomial distribution; Continuity correction; Binomial (polynomial); Estimator; Distribution (mathematics); Limit (mathematics); Upper and lower bounds; Random variable; Combinatorics; Statistics; Beta-binomial distribution; Mathematical analysis; Poisson distribution","score_opus":0.05968265485861679,"score_gpt":0.358064667786666,"score_spread":0.2983820129280492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137498593","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":[0.0018401158,0.000496417,0.9947241,0.0005416502,0.00020350468,0.000021841226,0.000068361354,0.0001915412,0.0019124042],"genre_scores_gemma":[0.15376769,0.0016692192,0.82447577,0.0010523569,0.0015301775,0.00037407837,0.0004120969,0.0012365566,0.015482093],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9873562,0.0071433065,0.00058221177,0.0020234003,0.002430411,0.00046449082],"domain_scores_gemma":[0.9323976,0.04930873,0.00257543,0.009280904,0.0055122836,0.0009249373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.029151019,0.0010140674,0.0017508803,0.0042028045,0.0018081564,0.003203727,0.005641146,0.0032653443,0.0119046075],"category_scores_gemma":[0.1436618,0.0011801701,0.0025163684,0.0036975632,0.006152849,0.008015208,0.0041545094,0.008751579,0.0031488743],"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":[0.00009962676,0.00003746379,0.0016439514,0.0002099714,0.000063323845,0.00028133343,0.00030046084,0.011455832,0.0019151034,0.92138743,0.0055419905,0.05706354],"study_design_scores_gemma":[0.000045689383,0.0000673715,0.0014898961,0.0001683964,0.000072830546,0.0007460963,0.00008338126,0.16984788,0.0021751418,0.8074272,0.01780565,0.00007049883],"about_ca_topic_score_codex":0.0035186452,"about_ca_topic_score_gemma":0.0030242743,"teacher_disagreement_score":0.029151019,"about_ca_system_score_codex":0.002192005,"about_ca_system_score_gemma":0.0029239808,"threshold_uncertainty_score":0.15416718},"labels":[],"label_agreement":null},{"id":"W3154879949","doi":"10.1007/s00184-021-00815-4","title":"A robust Birnbaum–Saunders regression model based on asymmetric heavy-tailed distributions","year":2021,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Mathematics; Statistics; Regression analysis; Econometrics; Regression","score_opus":0.1410671106164774,"score_gpt":0.3639498892106735,"score_spread":0.2228827785941961,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154879949","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018206941,0.0005206813,0.9784228,0.00050311524,0.000070797825,0.000030969477,0.00018717177,0.00022645909,0.0018309158],"genre_scores_gemma":[0.7867561,0.001875187,0.18362483,0.00034665826,0.00035639098,0.00025893253,0.001109846,0.00032476734,0.025347328],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979215,0.00081595016,0.00007005268,0.0006435975,0.00036826366,0.00018060303],"domain_scores_gemma":[0.99596137,0.002500957,0.0005493874,0.00031950793,0.0005557471,0.00011302823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004607352,0.0012645959,0.0028389115,0.0010623934,0.00050009124,0.0021249177,0.003362019,0.0028306218,0.0034668022],"category_scores_gemma":[0.01150637,0.0010734295,0.0013759081,0.0015845046,0.0015462214,0.00254155,0.0015393023,0.0029375707,0.0014910011],"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":[0.00016418946,0.0000701604,0.0015787034,0.00017917181,0.00017984836,0.00024818437,0.00015102203,0.7846452,0.0023708513,0.17013313,0.003038979,0.037240554],"study_design_scores_gemma":[0.000009431996,0.000018046374,0.00024370878,0.000010980673,0.000023214383,0.000029885907,0.0000074229615,0.9840607,0.00020496716,0.014642128,0.0007322743,0.00001716444],"about_ca_topic_score_codex":0.0072310655,"about_ca_topic_score_gemma":0.00475703,"teacher_disagreement_score":0.0072310655,"about_ca_system_score_codex":0.0011445137,"about_ca_system_score_gemma":0.0015983566,"threshold_uncertainty_score":0.02436626},"labels":[],"label_agreement":null},{"id":"W3195553850","doi":"10.1007/s00184-021-00836-z","title":"The quarter median","year":2021,"lang":"en","type":"article","venue":"Metrika","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Leibniz-Gemeinschaft; Gottfried Wilhelm Leibniz Universität Hannover","keywords":"Mathematics; Multivariate statistics; Pairwise comparison; Quarter (Canadian coin); Equipartition theorem; Normality; Hyperplane; Basis (linear algebra); Property (philosophy); Combinatorics; Statistics; Pure mathematics; Geometry; Geography","score_opus":0.1369162972909448,"score_gpt":0.44476943142331676,"score_spread":0.307853134132372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3195553850","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":[0.26872477,0.0013029318,0.68592703,0.0013617805,0.00027768043,0.000038644775,0.0014959857,0.0004391194,0.040432118],"genre_scores_gemma":[0.96207875,0.00036329246,0.030020943,0.0002733669,0.00032507736,0.000054265707,0.00049578096,0.00010100031,0.006287523],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986002,0.0003733487,0.000059993843,0.00039188788,0.0003734837,0.00020116138],"domain_scores_gemma":[0.9970782,0.0008962011,0.0005787156,0.00069273525,0.00044384215,0.0003103465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013031339,0.00020859072,0.00068979064,0.0012530187,0.00073600793,0.002208039,0.0008110331,0.0006366495,0.009545396],"category_scores_gemma":[0.0069869026,0.00020293587,0.00047717066,0.0014810298,0.0021622449,0.0029376266,0.0020071398,0.0011264279,0.00065941125],"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":[0.00010175855,0.00001633814,0.002273873,0.000040466835,0.00002719233,0.00007905172,0.00011483161,0.011435065,0.0013475554,0.95620865,0.0027223094,0.025632858],"study_design_scores_gemma":[0.000012607903,0.00008087906,0.0036625192,0.000023724331,0.000013612425,0.00027410526,0.00016329747,0.07772493,0.0013321496,0.90349746,0.013187219,0.00002744407],"about_ca_topic_score_codex":0.0008908673,"about_ca_topic_score_gemma":0.0005310782,"teacher_disagreement_score":0.009545396,"about_ca_system_score_codex":0.0009148115,"about_ca_system_score_gemma":0.00059143495,"threshold_uncertainty_score":0.031932473},"labels":[],"label_agreement":null},{"id":"W322166810","doi":"10.1007/s00184-015-0546-8","title":"Representations of the inactivity time for coherent systems with heterogeneous components and some ordered properties","year":2015,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Natural Science Foundation of China","keywords":"Mathematics; Independent and identically distributed random variables; Stochastic ordering; Reliability (semiconductor); Order statistic; Function (biology); Order (exchange); Statistics; Random variable; Applied mathematics; Power (physics)","score_opus":0.17421835046580902,"score_gpt":0.34406076462442875,"score_spread":0.16984241415861973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W322166810","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":[0.02821713,0.0005175284,0.96480966,0.00031824128,0.00005910848,0.00002325195,0.00014210197,0.000092408365,0.0058206045],"genre_scores_gemma":[0.8288019,0.0020786624,0.14789833,0.00034403498,0.0004552006,0.00019668549,0.0006787225,0.00039940892,0.019147076],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994855,0.00018396975,0.00003269561,0.00009228956,0.00012520033,0.00008036085],"domain_scores_gemma":[0.9967673,0.001727201,0.00058585545,0.00027768494,0.00041759896,0.00022449213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018928843,0.0013421591,0.00066475547,0.0016727422,0.00052435265,0.0026000957,0.0015583409,0.0012069087,0.003900591],"category_scores_gemma":[0.0055091437,0.00046855447,0.00090144505,0.0012424026,0.0016932591,0.0039607836,0.0013145674,0.0019917446,0.00067869027],"study_design_candidate":"simulation_or_modeling","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":[0.00004118667,0.000032113127,0.00029919183,0.00006700077,0.000017022392,0.00009778145,0.0001772009,0.036429964,0.0020628944,0.951487,0.0007770103,0.008511676],"study_design_scores_gemma":[0.000009591944,0.000032993026,0.00031522286,0.000027212925,0.00001931851,0.00012279012,0.00008551784,0.5356728,0.0006256562,0.46166584,0.0013963201,0.00002677841],"about_ca_topic_score_codex":0.0012289499,"about_ca_topic_score_gemma":0.00086781563,"teacher_disagreement_score":0.003900591,"about_ca_system_score_codex":0.0010050567,"about_ca_system_score_gemma":0.0007714976,"threshold_uncertainty_score":0.013048768},"labels":[],"label_agreement":null},{"id":"W4200491357","doi":"10.1007/s00184-021-00851-0","title":"A note on the coverage behaviour of bootstrap percentile confidence intervals for constrained parameters","year":2021,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Science Foundation of Fujian Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Percentile; Mathematics; Parametric statistics; Confidence interval; Coverage probability; Inference; Statistics; Sample size determination; Sample (material); Confidence distribution; Boundary (topology); Econometrics; Applied mathematics; Computer science; Artificial intelligence; Mathematical analysis","score_opus":0.18221572746016593,"score_gpt":0.4133302771324255,"score_spread":0.23111454967225956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200491357","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":[0.00890553,0.0080994535,0.96301436,0.009190987,0.000565664,0.000051818897,0.00048655775,0.00063079415,0.009054959],"genre_scores_gemma":[0.41536316,0.007795124,0.5549145,0.0074894545,0.0043018474,0.0005257603,0.0012534029,0.0019345902,0.006422225],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9601719,0.026595049,0.0016314023,0.003392843,0.0072092763,0.0009995442],"domain_scores_gemma":[0.39674643,0.56517124,0.005279625,0.022168184,0.009411227,0.001223389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.057974156,0.0015060655,0.0031673354,0.0042819357,0.0018384903,0.004629175,0.0056092064,0.005051546,0.006913489],"category_scores_gemma":[0.435075,0.0012121323,0.002844132,0.0050554173,0.0074015805,0.0081708,0.006188892,0.011675851,0.00097432465],"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":[0.0006496026,0.000087101565,0.012995044,0.0012865076,0.00081279274,0.002127683,0.0028763402,0.06221474,0.0052184537,0.73054105,0.026360748,0.15482992],"study_design_scores_gemma":[0.000076250755,0.0001937998,0.0067041432,0.00078929024,0.00021064332,0.0017558342,0.00030634896,0.24844594,0.004575744,0.7164641,0.020228969,0.0002489598],"about_ca_topic_score_codex":0.006435751,"about_ca_topic_score_gemma":0.0030121745,"teacher_disagreement_score":0.057974156,"about_ca_system_score_codex":0.0015636277,"about_ca_system_score_gemma":0.0013169905,"threshold_uncertainty_score":0.30660033},"labels":[],"label_agreement":null},{"id":"W4205672610","doi":"10.1007/s00184-021-00852-z","title":"Prediction of future censored lifetimes from mixture exponential distribution","year":2022,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Statistics; Parametric statistics; Prediction interval; Exponential distribution; Sample size determination; Exponential function; Applied mathematics; Mathematical analysis","score_opus":0.0426231360284736,"score_gpt":0.2974603650437099,"score_spread":0.25483722901523626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205672610","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15528442,0.0005888692,0.84247327,0.00028267218,0.00006363033,0.000033003613,0.000259897,0.000313054,0.000701167],"genre_scores_gemma":[0.9472156,0.0006365083,0.04764241,0.00004616535,0.000075910895,0.00006373827,0.0006583424,0.00006858586,0.0035926215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995987,0.000113000686,0.000021723978,0.00013124733,0.00007257193,0.00006277157],"domain_scores_gemma":[0.9935959,0.00480598,0.0005519702,0.00036710963,0.0004997797,0.00017933417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029151803,0.0007272346,0.001003208,0.0010461456,0.00037242105,0.0011212447,0.0016402309,0.0012424322,0.0015421653],"category_scores_gemma":[0.013689903,0.0006457062,0.0009914426,0.00080434454,0.0007973204,0.002083988,0.001114417,0.0017857756,0.0005340025],"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":[0.0002552586,0.000045843935,0.007149626,0.00009714495,0.00006896167,0.00015392838,0.00015822772,0.9348543,0.0015243468,0.023630133,0.0008506345,0.031211488],"study_design_scores_gemma":[0.0000025615145,0.000007541156,0.00047757715,0.000005583642,0.000005865082,0.000022432849,0.0000081139,0.9941194,0.0002199511,0.0050170873,0.00010767439,0.000006306144],"about_ca_topic_score_codex":0.004158919,"about_ca_topic_score_gemma":0.003084689,"teacher_disagreement_score":0.004158919,"about_ca_system_score_codex":0.00076696527,"about_ca_system_score_gemma":0.0006154646,"threshold_uncertainty_score":0.015417099},"labels":[],"label_agreement":null},{"id":"W4214651510","doi":"10.1007/s001840200183","title":"Quantile models and estimators for data analysis","year":2002,"lang":"en","type":"article","venue":"Metrika","topic":"School Choice and Performance","field":"Social Sciences","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Quantile; Quantile regression; Mathematics; Estimator; Statistics; Econometrics; Regression analysis; Conditional probability distribution; Regression","score_opus":0.24404067713216668,"score_gpt":0.40183792045986794,"score_spread":0.15779724332770126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214651510","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":[0.0007818812,0.0040560616,0.9930784,0.00093311665,0.00013348908,0.00004900833,0.00027837546,0.0002956545,0.00039411255],"genre_scores_gemma":[0.09884657,0.012044579,0.87314576,0.0009958663,0.002456303,0.0027360064,0.0023905043,0.0009452915,0.00643924],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.95334256,0.038495913,0.0017664653,0.0028383657,0.002914558,0.00064211944],"domain_scores_gemma":[0.74574345,0.22690794,0.004927833,0.01729005,0.00433754,0.0007932868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.053095773,0.001943358,0.0062046023,0.004360007,0.0015464666,0.0061241165,0.0051714485,0.0052393633,0.010614886],"category_scores_gemma":[0.21411689,0.0028045946,0.003681717,0.011187913,0.0056755887,0.007797562,0.004249179,0.010404758,0.0026479128],"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":[0.00012647761,0.000093709146,0.0028200631,0.00075687235,0.00056511484,0.00010906307,0.00046846847,0.047022857,0.00030762932,0.8094893,0.017410014,0.12083053],"study_design_scores_gemma":[0.00005541022,0.000030084555,0.00094896526,0.00012167989,0.00006643725,0.00007722106,0.000069143585,0.09275956,0.00011035918,0.89587164,0.009855141,0.000034348926],"about_ca_topic_score_codex":0.0062326347,"about_ca_topic_score_gemma":0.0038949763,"teacher_disagreement_score":0.053095773,"about_ca_system_score_codex":0.0038442085,"about_ca_system_score_gemma":0.0044749775,"threshold_uncertainty_score":0.28080064},"labels":[],"label_agreement":null},{"id":"W4296527273","doi":"10.1007/s00184-022-00883-0","title":"A semiparametric multiply robust multiple imputation method for causal inference","year":2022,"lang":"en","type":"article","venue":"Metrika","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"National Institute on Minority Health and Health Disparities; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Causal inference; Propensity score matching; Mathematics; Covariate; Observational study; Statistics; Average treatment effect; Parametric statistics; Econometrics; Semiparametric regression; Regression","score_opus":0.2165900280511105,"score_gpt":0.4543514871875161,"score_spread":0.23776145913640562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296527273","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":[0.0006228616,0.00008911548,0.998587,0.00013791844,0.000027635137,0.000024289622,0.000102145095,0.00015393177,0.00025516102],"genre_scores_gemma":[0.042201914,0.00027772455,0.9515652,0.0002666649,0.00027338363,0.0004120689,0.0006609751,0.00022129591,0.0041206577],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9895891,0.0079448735,0.00035896857,0.00097772,0.00092042336,0.00020892535],"domain_scores_gemma":[0.9672674,0.02490967,0.0011965584,0.004434321,0.0018625112,0.000329571],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012247307,0.0010337268,0.002791921,0.0018619151,0.0011933822,0.002314287,0.0046890494,0.0021239351,0.010993474],"category_scores_gemma":[0.050994042,0.0013792076,0.002853542,0.003292823,0.0012961995,0.0022092853,0.003615058,0.004402601,0.0026652236],"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":[0.0004579997,0.00024335504,0.0024203935,0.00048436224,0.0013471685,0.00040836545,0.00036039602,0.09740296,0.0024582725,0.50744206,0.0154097555,0.37156492],"study_design_scores_gemma":[0.00011507251,0.00010261833,0.0008245081,0.000093630675,0.00021531257,0.0003570971,0.000037277325,0.64157856,0.00079671736,0.3464813,0.009329176,0.000068764064],"about_ca_topic_score_codex":0.002524777,"about_ca_topic_score_gemma":0.0035736235,"teacher_disagreement_score":0.012247307,"about_ca_system_score_codex":0.0007733201,"about_ca_system_score_gemma":0.002504105,"threshold_uncertainty_score":0.06477076},"labels":[],"label_agreement":null},{"id":"W4367051260","doi":"10.1007/s00184-023-00905-5","title":"Comparison of extreme order statistics from two sets of heterogeneous dependent random variables under random shocks","year":2023,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Order statistic; Statistics; Random variable; Order (exchange); Econometrics","score_opus":0.15853808707472253,"score_gpt":0.4178107726210691,"score_spread":0.2592726855463465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367051260","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42412773,0.00032021417,0.57235384,0.00050816074,0.00008697565,0.00011656278,0.00034307232,0.0002072088,0.0019362819],"genre_scores_gemma":[0.97025126,0.00027499898,0.026980044,0.000086256914,0.0000832672,0.00010933822,0.00092232105,0.000059542952,0.0012329523],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956678,0.0021755563,0.00023892731,0.0006897298,0.0008109544,0.00041707963],"domain_scores_gemma":[0.8667394,0.11504163,0.0061751194,0.006455794,0.004107293,0.0014807401],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017557051,0.00079632306,0.0016528165,0.0024713343,0.0006302389,0.003164682,0.001955786,0.002088649,0.0021878777],"category_scores_gemma":[0.078807585,0.0006236385,0.0016898835,0.0015555249,0.0031810664,0.004047545,0.0020229176,0.002521453,0.0002442165],"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":[0.0014554373,0.00038497747,0.027340911,0.0003008744,0.0006736394,0.00060830335,0.00073421805,0.6039586,0.0028441101,0.32253242,0.0016739452,0.037492532],"study_design_scores_gemma":[0.000051512456,0.00016400659,0.01259265,0.000043646276,0.00008489462,0.0001284765,0.00021702409,0.86848617,0.001361853,0.11638727,0.00040588807,0.00007660671],"about_ca_topic_score_codex":0.0017779429,"about_ca_topic_score_gemma":0.00090882304,"teacher_disagreement_score":0.017557051,"about_ca_system_score_codex":0.0016693169,"about_ca_system_score_gemma":0.0012903085,"threshold_uncertainty_score":0.0928517},"labels":[],"label_agreement":null},{"id":"W4388829755","doi":"10.1007/s00184-023-00930-4","title":"Stochastic comparisons of two finite mixtures of general family of distributions","year":2023,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"University Grants Commission","keywords":"Mathematics; Majorization; Stochastic ordering; Order (exchange); Applied mathematics; Reciprocal; Hazard; Parametric statistics; Hazard ratio; Matrix (chemical analysis); Combinatorics; Statistics; Confidence interval","score_opus":0.1185823537703536,"score_gpt":0.40532427282768274,"score_spread":0.28674191905732915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388829755","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25543907,0.0007219022,0.73988104,0.0005907731,0.0001511385,0.00007611835,0.00014578478,0.00017545387,0.0028186697],"genre_scores_gemma":[0.913932,0.0002703795,0.08237492,0.00010667698,0.00011959897,0.00011956168,0.00038366596,0.00008966532,0.0026035383],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99564505,0.0022490944,0.00019390375,0.00092789216,0.00069627655,0.00028779678],"domain_scores_gemma":[0.9433831,0.048371527,0.0028083131,0.0019078936,0.002594244,0.00093488925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017214496,0.00066682976,0.0015151139,0.002305827,0.0007684731,0.003883069,0.0027006175,0.0025389402,0.0035584387],"category_scores_gemma":[0.076134115,0.0007673505,0.0014694519,0.0011935999,0.002774407,0.0053971442,0.0024312169,0.0018307117,0.0003221781],"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":[0.0017046216,0.00019367911,0.011839325,0.00032526292,0.0003943485,0.00042321888,0.0007759523,0.38985077,0.0061894413,0.5415805,0.0009940116,0.04572889],"study_design_scores_gemma":[0.00003674353,0.0001597557,0.0039102584,0.000046223646,0.00006986382,0.00019454963,0.00013782497,0.8754961,0.0013912803,0.117703475,0.00079035014,0.0000636147],"about_ca_topic_score_codex":0.0014447483,"about_ca_topic_score_gemma":0.0012020991,"teacher_disagreement_score":0.017214496,"about_ca_system_score_codex":0.0021772399,"about_ca_system_score_gemma":0.0009994721,"threshold_uncertainty_score":0.091040015},"labels":[],"label_agreement":null},{"id":"W4393929486","doi":"10.1007/s00184-024-00961-5","title":"Estimating the suspected larger of two normal means","year":2024,"lang":"en","type":"article","venue":"Metrika","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Statistics Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Statistics; Mathematics; Computer science","score_opus":0.10762504667771922,"score_gpt":0.44588508304652263,"score_spread":0.3382600363688034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393929486","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":[0.07224721,0.00048343834,0.9243865,0.0006386075,0.00013959095,0.000057934732,0.00012476389,0.0003766997,0.0015452416],"genre_scores_gemma":[0.7107127,0.00044539498,0.28259176,0.00032901383,0.00039660782,0.0002645795,0.00069571397,0.000299046,0.0042652003],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98287326,0.007833662,0.00078285474,0.0057019354,0.0020509874,0.00075737276],"domain_scores_gemma":[0.8131183,0.16266492,0.0050586984,0.012279182,0.004874581,0.0020042441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023581257,0.0014348911,0.0028842047,0.003107476,0.001259423,0.004540356,0.003879579,0.003256945,0.0052182935],"category_scores_gemma":[0.18193741,0.0014035914,0.0027529607,0.0016418236,0.006463566,0.008342032,0.0055599003,0.0060007535,0.000980669],"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":[0.0043395106,0.00038880814,0.048388407,0.00084921886,0.00108627,0.0012611423,0.0024798024,0.13169536,0.016104171,0.50832045,0.0047925394,0.28029433],"study_design_scores_gemma":[0.00013649747,0.00043254552,0.011030602,0.00012788021,0.00017294932,0.00080357265,0.00039542443,0.59648526,0.005184441,0.38128906,0.003788906,0.00015288217],"about_ca_topic_score_codex":0.0021507936,"about_ca_topic_score_gemma":0.0016734576,"teacher_disagreement_score":0.023581257,"about_ca_system_score_codex":0.001770769,"about_ca_system_score_gemma":0.0017929657,"threshold_uncertainty_score":0.1247111},"labels":[],"label_agreement":null},{"id":"W4405020068","doi":"10.1007/s00184-024-00980-2","title":"Reducing multi-collinearity in GLMS with categorical covariates","year":2024,"lang":"en","type":"article","venue":"Metrika","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Science Foundation Ireland","keywords":"Covariate; Categorical variable; Collinearity; Mathematics; Generalized linear model; Estimator; Statistics; Econometrics; Analysis of covariance; Covariance","score_opus":0.17407311869321732,"score_gpt":0.45097707815520294,"score_spread":0.27690395946198565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405020068","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":[0.008917314,0.0003969272,0.9890238,0.00050876476,0.00010643653,0.00007244897,0.00022906886,0.0004302248,0.00031501628],"genre_scores_gemma":[0.17018934,0.0006066244,0.82321936,0.00066191284,0.00043462537,0.00087479723,0.001047487,0.0009601338,0.002005692],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.90708387,0.0796952,0.0022640522,0.0057231756,0.0038451862,0.0013885436],"domain_scores_gemma":[0.7821006,0.18529055,0.0061631296,0.02055836,0.0047309166,0.0011564225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.044824,0.003478034,0.003571174,0.0030853844,0.0026627344,0.0038533732,0.004661101,0.0028588318,0.004214343],"category_scores_gemma":[0.20483685,0.0024033035,0.0067300843,0.0073446305,0.0039606956,0.004080755,0.0070595425,0.0074439077,0.0014418715],"study_design_candidate":"simulation_or_modeling","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":[0.0012168916,0.0006499379,0.027619028,0.0021702677,0.006531416,0.0017141587,0.0054071406,0.20744061,0.0043883636,0.320555,0.017532106,0.40477502],"study_design_scores_gemma":[0.00011940891,0.00032900507,0.0036465935,0.0002728128,0.0005530848,0.00023195955,0.00055185193,0.40731955,0.0014921594,0.57821244,0.0071473815,0.00012377488],"about_ca_topic_score_codex":0.0072429706,"about_ca_topic_score_gemma":0.008304355,"teacher_disagreement_score":0.044824,"about_ca_system_score_codex":0.0016207141,"about_ca_system_score_gemma":0.0057926625,"threshold_uncertainty_score":0.23705482},"labels":[],"label_agreement":null}]}