{"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":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72100925,0.0010328909,0.20023675,0.00404277,0.011266639,0.0050116642,0.00034124297,0.00048355735,0.05657524],"genre_scores_gemma":[0.34926704,0.000008838144,0.6348654,0.0013894114,0.0009890705,0.00024788195,0.000022722159,0.000084297164,0.013125358],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9942446,0.00069039816,0.0014246955,0.001241164,0.0015270191,0.0008721604],"domain_scores_gemma":[0.9884434,0.008846829,0.0005724344,0.0010596839,0.0007208745,0.0003568185],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006412335,0.00041868672,0.00071667205,0.0009185899,0.0004685348,0.00097067264,0.0011149396,0.00023007004,0.00084201887],"category_scores_gemma":[0.022011872,0.00033293082,0.00029923732,0.0018739898,0.0002970428,0.0010920377,0.00020426213,0.00027570926,0.0010868325],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018061275,0.0007756439,0.0007324273,0.00002681161,0.0002420461,0.000046724297,0.0011725018,0.0010315342,0.48286828,0.11444703,0.20965958,0.1871913],"study_design_scores_gemma":[0.013917529,0.00392186,0.0011163066,0.00013416618,0.0000858581,0.00009065209,0.006399761,0.036901724,0.5315659,0.21476705,0.18833137,0.0027677934],"about_ca_topic_score_codex":0.00015783249,"about_ca_topic_score_gemma":0.000002562574,"teacher_disagreement_score":0.43462864,"about_ca_system_score_codex":0.00015544446,"about_ca_system_score_gemma":0.00020782619,"threshold_uncertainty_score":0.99991226},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8080803,0.0018403771,0.17380123,0.000092276314,0.00015923123,0.0002713058,0.00008633544,0.00009108101,0.0155778695],"genre_scores_gemma":[0.99267477,0.00022075245,0.0023261008,0.00007518512,0.00006731869,0.000017642635,0.000014043905,0.000028448154,0.004575745],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986927,0.000010029777,0.0004216597,0.0004236643,0.000074510965,0.00037747074],"domain_scores_gemma":[0.99928075,0.00007835343,0.00019477648,0.00027009542,0.00009024703,0.00008575637],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004713754,0.0001596904,0.00033777792,0.0002873247,0.00014998314,0.00008395612,0.00020539798,0.00007502747,0.00044590316],"category_scores_gemma":[0.00042089637,0.00015656684,0.00004445193,0.00093466265,0.000028710536,0.0002435394,0.000049193648,0.00012632624,0.0012222291],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079029996,0.0018989823,0.94265115,0.0003377442,0.00023781492,0.00009353748,0.0022947926,0.019666282,0.00036369392,0.010794572,0.0009431836,0.019927945],"study_design_scores_gemma":[0.010528359,0.0012501124,0.12688787,0.00031572583,0.00009172547,0.00005125497,0.00031244726,0.31442192,0.0044626216,0.01948654,0.5189505,0.0032408903],"about_ca_topic_score_codex":0.0008651858,"about_ca_topic_score_gemma":0.00010943114,"teacher_disagreement_score":0.8157633,"about_ca_system_score_codex":0.000084025,"about_ca_system_score_gemma":0.00005515413,"threshold_uncertainty_score":0.9995554},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39586365,0.00036033805,0.58414936,0.0009733833,0.000068882575,0.00081174105,0.00077352655,0.00010515282,0.016893936],"genre_scores_gemma":[0.84164506,0.0000031843178,0.15524158,0.000041734434,0.00008322726,0.00013230942,0.000058080146,0.000023441791,0.0027714162],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985604,0.00016463983,0.0005992408,0.00013300298,0.00038285853,0.00015985133],"domain_scores_gemma":[0.99474573,0.004366235,0.00026596032,0.00042488766,0.00016862275,0.000028561728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008908474,0.00010203619,0.00021962565,0.00004182611,0.00013475548,0.00002538417,0.0001875983,0.00004014368,0.00026712424],"category_scores_gemma":[0.0017797777,0.00006863103,0.000060972,0.00037304184,0.00008317668,0.00002851533,0.00004172716,0.00008935399,0.000022279517],"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":[0.0000023009723,0.0001766527,0.00007143419,0.00010715947,0.00001669171,1.3594963e-7,0.00039183343,0.0000066269104,0.0015564181,0.957324,0.038561907,0.001784826],"study_design_scores_gemma":[0.0002870571,0.000051927225,0.00015925552,0.000022246246,0.00008479877,0.000002127836,0.0016805838,0.0041061416,0.0072695236,0.9840854,0.0021085257,0.00014242463],"about_ca_topic_score_codex":0.00014943468,"about_ca_topic_score_gemma":0.000024486126,"teacher_disagreement_score":0.44578138,"about_ca_system_score_codex":0.000023021717,"about_ca_system_score_gemma":0.000021289998,"threshold_uncertainty_score":0.29248232},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024754917,0.00008423862,0.96090317,0.0008996438,0.00013989005,0.00020010387,0.000605293,0.00021190092,0.0122008715],"genre_scores_gemma":[0.9628482,0.0000033620236,0.035950575,0.000076767,0.00010201102,0.000051917938,0.00035661756,0.000010751422,0.0005998055],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999113,0.0000469319,0.00024484022,0.0001110438,0.00020035935,0.00028379873],"domain_scores_gemma":[0.99877363,0.00061277975,0.00007383122,0.0002415702,0.00009702322,0.00020116649],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002424546,0.00010127094,0.00014023765,0.00006785121,0.0001990526,0.000029542589,0.00010678815,0.000055336106,0.0015278009],"category_scores_gemma":[0.0009429912,0.00009143774,0.000057328816,0.00061054726,0.00006183694,0.000109130095,0.000029177963,0.00010248852,0.0008243062],"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":[0.000001909159,0.00024977798,0.00055911724,0.000008540695,0.000011842,2.6098894e-7,0.000026778696,5.467603e-8,0.0001310692,0.96702147,0.030409154,0.0015800592],"study_design_scores_gemma":[0.0008948706,0.00003378584,0.07810572,0.000022866463,0.0001703007,0.00003270702,0.00012186826,0.0018047831,0.0062880465,0.5307913,0.3812271,0.0005066946],"about_ca_topic_score_codex":0.000006901074,"about_ca_topic_score_gemma":0.0000010565334,"teacher_disagreement_score":0.9380933,"about_ca_system_score_codex":0.00008889067,"about_ca_system_score_gemma":0.000014804704,"threshold_uncertainty_score":0.9999537},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7356798,0.000074415315,0.25332344,0.0010903182,0.000510967,0.001163235,0.00018585635,0.00039831147,0.0075736837],"genre_scores_gemma":[0.94999206,4.490104e-7,0.049779534,0.000050791852,0.000029869965,0.00005366706,0.000014783785,0.000017209884,0.00006163856],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990398,0.000026096974,0.00028851285,0.00017410984,0.00028636755,0.00018509153],"domain_scores_gemma":[0.99892235,0.00026214414,0.00014374981,0.00032134436,0.00025253542,0.00009788042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018190984,0.00012296351,0.00018717794,0.00012864117,0.00013221921,0.000020808562,0.00014368001,0.00007184458,0.0004852841],"category_scores_gemma":[0.003457879,0.00009759094,0.00005059143,0.0005019207,0.00010334292,0.000038767786,0.000030102015,0.00018143847,0.000087601344],"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":[0.000116101925,0.0019368975,0.0015617469,0.00051962817,0.00006825491,0.000006677437,0.0002635874,0.000068956106,0.023915062,0.93182254,0.0032485623,0.036471996],"study_design_scores_gemma":[0.003288085,0.0010420723,0.019627305,0.00073129404,0.00035893967,0.000020188261,0.00020556914,0.1888811,0.5603618,0.21908264,0.0052054855,0.0011955115],"about_ca_topic_score_codex":0.0000032285263,"about_ca_topic_score_gemma":0.0000011054454,"teacher_disagreement_score":0.7127399,"about_ca_system_score_codex":0.000023994238,"about_ca_system_score_gemma":0.00006745546,"threshold_uncertainty_score":0.53135204},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026594415,0.00008954873,0.9678066,0.00009836242,0.000034946384,0.00014240961,0.000022910976,0.00006118922,0.005149623],"genre_scores_gemma":[0.11905342,0.0000072410057,0.8806721,0.00005322398,0.0000454209,0.000007630454,0.000005445744,0.000014613691,0.00014087175],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990774,0.00009585925,0.00027470893,0.00014926979,0.00019666324,0.00020612824],"domain_scores_gemma":[0.99862945,0.0009380509,0.0001142185,0.00014883901,0.00010059736,0.00006881802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034158054,0.00014666103,0.00028968515,0.00011308417,0.000099764045,0.000073239215,0.00007243015,0.00006104014,0.000046428915],"category_scores_gemma":[0.00044679435,0.00010121657,0.000024608531,0.00029494884,0.0000874651,0.00015455559,0.00003422451,0.00010386709,0.0000050062695],"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":[0.000037241894,0.000037480862,0.00019246395,0.0000664039,0.000022623635,0.0000071092118,0.00019068313,0.000014097902,0.00013090503,0.99037015,0.0002696298,0.008661217],"study_design_scores_gemma":[0.000709847,0.00007316968,0.00047200258,0.000046094676,0.00004969942,0.000011346241,0.000047370788,0.048541706,0.0023992744,0.94733,0.00014973192,0.00016973374],"about_ca_topic_score_codex":0.00013510398,"about_ca_topic_score_gemma":0.000009883523,"teacher_disagreement_score":0.09245901,"about_ca_system_score_codex":0.000020237101,"about_ca_system_score_gemma":0.000030253315,"threshold_uncertainty_score":0.41274917},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29858324,0.000025799984,0.6937124,0.00014445001,0.00013908905,0.00013329218,0.006091963,0.00005666162,0.0011130597],"genre_scores_gemma":[0.9819266,0.000022626937,0.016041756,0.00001908015,0.00005857751,0.000028801958,0.0012946833,0.00000968712,0.0005981539],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9989688,0.000045291134,0.00045995862,0.0001601918,0.00023916797,0.00012660744],"domain_scores_gemma":[0.9986239,0.00045745383,0.00019224714,0.00028940034,0.00036212083,0.00007487593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008929375,0.00009738257,0.00022960035,0.00008893886,0.00011839267,0.0000044573894,0.0000983353,0.000081222104,0.0008834904],"category_scores_gemma":[0.0008357676,0.00009363579,0.000081265774,0.00086381927,0.00017647735,0.00005608956,0.000024218756,0.00009532333,0.0000491124],"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":[0.00005357812,0.0008490509,0.012867227,0.000040011197,0.00014950984,0.0000012288477,0.00008463852,0.00015010177,0.006452162,0.9336325,0.044933952,0.00078603165],"study_design_scores_gemma":[0.0020511774,0.00023497568,0.74790007,0.000059057922,0.00034328835,0.000018440032,0.00017315177,0.016379684,0.014804232,0.20728834,0.010419282,0.00032832],"about_ca_topic_score_codex":0.00008518422,"about_ca_topic_score_gemma":0.000009424308,"teacher_disagreement_score":0.7350328,"about_ca_system_score_codex":0.000069207505,"about_ca_system_score_gemma":0.00007848217,"threshold_uncertainty_score":0.96736},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023241077,0.0000087907465,0.9720891,0.0024569994,0.000087619504,0.0011121507,0.0000927044,0.00004025184,0.0008713193],"genre_scores_gemma":[0.963797,0.000001057549,0.03536887,0.00011195951,0.000021435211,0.00022895994,0.000040828138,0.000008148518,0.00042178822],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993426,0.00003656303,0.0002611194,0.00008982185,0.00017473198,0.000095145566],"domain_scores_gemma":[0.99838936,0.0009937931,0.0001612963,0.00030526696,0.00011949228,0.000030810963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022286148,0.00006643392,0.000092497336,0.000035552042,0.00018476874,0.00002752764,0.00016512358,0.000036573503,0.0003423685],"category_scores_gemma":[0.0019055502,0.000036946698,0.00007074118,0.0003678595,0.000057361074,0.00007115569,0.000024436784,0.000054247677,0.00004483829],"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":[0.0000020584896,0.00005099418,0.00030367743,0.000038975344,0.000014342485,9.615251e-9,0.00011170255,0.0001325141,0.00017002772,0.9696171,0.01658782,0.01297076],"study_design_scores_gemma":[0.0003855837,0.0000171467,0.14952512,0.000021832839,0.00009438544,0.0000010342079,0.00016421585,0.3003389,0.0016092759,0.5460878,0.001654548,0.00010013416],"about_ca_topic_score_codex":0.000097118376,"about_ca_topic_score_gemma":0.00004039311,"teacher_disagreement_score":0.9405559,"about_ca_system_score_codex":0.000034438825,"about_ca_system_score_gemma":0.000012236326,"threshold_uncertainty_score":0.3748695},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5925451,0.000020018251,0.40479034,0.00030275568,0.000043517277,0.00023323059,0.0016983805,0.000030405134,0.0003362394],"genre_scores_gemma":[0.95954555,0.000017150896,0.04020478,0.000015703321,0.00001203064,0.000020825646,0.00007547065,0.000007782365,0.000100734294],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9990466,0.000060061644,0.00039022302,0.00021391365,0.00013916881,0.00015003789],"domain_scores_gemma":[0.9982733,0.0009078882,0.00021265676,0.000249645,0.00021204246,0.00014447838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003733646,0.00012792673,0.00029269734,0.00009841712,0.00017323525,0.000022077642,0.00006747999,0.00014848821,0.0001285942],"category_scores_gemma":[0.0022574202,0.00012103062,0.00003992599,0.00034710902,0.00040042357,0.00010146332,0.00008920082,0.00026843708,0.000003129207],"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":[0.000033381333,0.00022874301,0.009035608,0.000113177426,0.00005569137,6.004662e-7,0.00011370466,0.0000013385402,0.024753282,0.96200913,0.00041841902,0.0032369418],"study_design_scores_gemma":[0.0021657927,0.00010807974,0.85264915,0.00003731116,0.0003396836,0.000019462765,0.00014433503,0.009328139,0.011952552,0.1207694,0.0021842,0.0003019041],"about_ca_topic_score_codex":0.0001410298,"about_ca_topic_score_gemma":0.00008598706,"teacher_disagreement_score":0.84361356,"about_ca_system_score_codex":0.000015622702,"about_ca_system_score_gemma":0.000043132753,"threshold_uncertainty_score":0.49354854},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03739722,0.000029586425,0.95299554,0.00023244563,0.00004935719,0.0005208959,0.0069565726,0.00006161208,0.0017567466],"genre_scores_gemma":[0.86014,0.0000023572886,0.13825513,0.0000041451453,0.000016793916,0.0001456627,0.0011801837,0.000009166897,0.00024655223],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987428,0.00003195455,0.0006805817,0.00016579848,0.00021624369,0.00016261825],"domain_scores_gemma":[0.99682295,0.0021926605,0.00033231292,0.00024545984,0.00035777467,0.000048843023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002348619,0.000119484954,0.00029399066,0.00026758344,0.00011781078,0.000013035702,0.000103102575,0.00006993511,0.00013028277],"category_scores_gemma":[0.0037305874,0.00011291812,0.0001449277,0.0013516723,0.00025048933,0.00006604291,0.000016582746,0.00005372309,0.000009683539],"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":[0.000015401289,0.0002798676,0.00017186649,0.00012432992,0.000026231945,7.186703e-8,0.000011216782,0.00034827966,0.0007936239,0.98913115,0.006265046,0.0028329205],"study_design_scores_gemma":[0.0025466064,0.00029859194,0.03111434,0.00009000151,0.0006230527,0.000006747545,0.00045913403,0.14809833,0.03446412,0.77761483,0.004215216,0.0004689861],"about_ca_topic_score_codex":0.00004779799,"about_ca_topic_score_gemma":0.0000074983263,"teacher_disagreement_score":0.82274276,"about_ca_system_score_codex":0.000045671357,"about_ca_system_score_gemma":0.000057461115,"threshold_uncertainty_score":0.4604667},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033973712,0.000030175372,0.99243206,0.001611772,0.000056906105,0.00054649694,0.0011039509,0.0001388578,0.0006823823],"genre_scores_gemma":[0.7800174,0.000003455212,0.21837333,0.000104462,0.00007417649,0.00003685612,0.0011189457,0.000008491133,0.00026290785],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991557,0.000023002083,0.00023134987,0.00023938464,0.00017512853,0.00017546077],"domain_scores_gemma":[0.9986038,0.00052399514,0.00010297033,0.00049464003,0.00019198419,0.00008259195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016683247,0.00009770069,0.00014546904,0.000057600722,0.00010985127,0.000057566253,0.00031792503,0.00005706206,0.00029598887],"category_scores_gemma":[0.0047074216,0.000086421234,0.000028815948,0.00036638492,0.000034745015,0.0001111408,0.00003949208,0.00007049309,0.0000808474],"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":[0.000025001636,0.00022597279,0.00003147164,0.000024328643,0.000014916331,9.235031e-7,0.000028394732,0.0000012048204,0.0006886193,0.895079,0.07691745,0.026962712],"study_design_scores_gemma":[0.002831113,0.00042899,0.02053245,0.000099315985,0.00028032745,0.000011459999,0.0001598375,0.040211108,0.006583261,0.7113133,0.21673837,0.00081047125],"about_ca_topic_score_codex":0.000001361361,"about_ca_topic_score_gemma":0.0000017811958,"teacher_disagreement_score":0.77662003,"about_ca_system_score_codex":0.000022043221,"about_ca_system_score_gemma":0.000042718457,"threshold_uncertainty_score":0.5635564},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061833065,0.00009288895,0.9343526,0.0001516376,0.00006448973,0.00042746594,0.0000306696,0.000073711126,0.0029735195],"genre_scores_gemma":[0.21225901,0.0000045878396,0.78430957,0.000036900405,0.00016592324,0.00007462641,0.000016545511,0.000026262966,0.0031065738],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920297,0.000025949952,0.0002996919,0.00016133153,0.00012400502,0.00018606811],"domain_scores_gemma":[0.9985869,0.0010465846,0.00007834858,0.00018037442,0.000056961475,0.0000508324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048053727,0.000119550015,0.00023203141,0.00011996879,0.000111561916,0.00004489237,0.000058277383,0.00008257899,0.00008522825],"category_scores_gemma":[0.0005057924,0.00009976163,0.00006621296,0.00016002893,0.00002841133,0.00011464994,0.000021366342,0.00005437637,0.000016656133],"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":[0.000061120205,0.00029112012,0.000014461353,0.00043151033,0.000048022983,0.0000016253041,0.00016581644,0.0032416978,0.000899571,0.94209903,0.036237385,0.01650862],"study_design_scores_gemma":[0.00040681873,0.00007695477,0.0000070981137,0.00001892428,0.000060431463,0.0000062569957,0.000014511585,0.55048233,0.00417194,0.44226527,0.0023656315,0.00012381132],"about_ca_topic_score_codex":0.000017872864,"about_ca_topic_score_gemma":0.0000034276563,"teacher_disagreement_score":0.5472407,"about_ca_system_score_codex":0.000021146569,"about_ca_system_score_gemma":0.000017575661,"threshold_uncertainty_score":0.4068161},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1655371,0.000014408351,0.81101006,0.00016337716,0.00010506953,0.0001247156,0.00009405556,0.00007460373,0.022876598],"genre_scores_gemma":[0.92171705,0.000011990371,0.07756862,0.000018508359,0.000035100446,0.000014929325,0.000015479302,0.000005237526,0.00061307946],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999482,0.000020848223,0.0002281367,0.00008222852,0.00011717908,0.00006963585],"domain_scores_gemma":[0.99933666,0.0002789965,0.00009359968,0.00014044342,0.00011052615,0.000039793606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009429325,0.000046333425,0.00010845084,0.00007098935,0.00006493474,0.0000025854256,0.00005232374,0.00003186241,0.000731913],"category_scores_gemma":[0.0008023916,0.000043396154,0.00003677259,0.00039148954,0.0000797996,0.000034684403,0.000008808417,0.000045747427,0.000071710725],"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":[0.000007143483,0.00012742568,0.0030120378,0.000027074604,0.000014358369,9.584088e-7,0.00005898976,0.0000012194425,0.0004533001,0.9496891,0.016807185,0.029801194],"study_design_scores_gemma":[0.0017146454,0.00017471002,0.22959124,0.00007733191,0.00010813273,0.00035826841,0.00029157344,0.0041204663,0.030315092,0.7060487,0.026666382,0.0005334396],"about_ca_topic_score_codex":0.0000062935583,"about_ca_topic_score_gemma":9.738153e-7,"teacher_disagreement_score":0.7561799,"about_ca_system_score_codex":0.000021219204,"about_ca_system_score_gemma":0.00001712053,"threshold_uncertainty_score":0.80139345},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077145575,0.00018320105,0.9902287,0.00010936152,0.0001590294,0.00061580556,0.00012363409,0.00013171924,0.0007339944],"genre_scores_gemma":[0.07835277,0.000005032745,0.9188854,0.00008710197,0.0003257746,0.00011848432,0.0000070557744,0.00004749796,0.0021708654],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988013,0.00006063563,0.00034784578,0.0002876525,0.00014800749,0.00035455453],"domain_scores_gemma":[0.9930679,0.0063421885,0.00012912248,0.00028320673,0.000105701634,0.000071859504],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00044530327,0.00016564476,0.00035256852,0.000106993,0.00009460473,0.000029610534,0.00012875789,0.00008313241,0.000024111983],"category_scores_gemma":[0.009262978,0.00014022405,0.000101604426,0.00016744764,0.000041009534,0.00011409637,0.000038035952,0.00009322141,0.000009133341],"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":[0.00007952531,0.00036925173,0.000016524997,0.00012019501,0.000040672694,0.0000030603023,0.00004522026,0.00001991643,0.0831529,0.8846805,0.00091897824,0.030553225],"study_design_scores_gemma":[0.0009132852,0.00010042384,0.00020363378,0.000024676814,0.000054087912,8.8614274e-7,0.000011433967,0.0055964063,0.029055994,0.9620894,0.0017546384,0.00019514382],"about_ca_topic_score_codex":0.000057461642,"about_ca_topic_score_gemma":0.00001807679,"teacher_disagreement_score":0.07740886,"about_ca_system_score_codex":0.000043753775,"about_ca_system_score_gemma":0.000022332593,"threshold_uncertainty_score":0.99908245},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49630865,0.000009917547,0.5023433,0.00004982941,0.0001122435,0.00023331339,0.00016044627,0.000041068426,0.00074123236],"genre_scores_gemma":[0.9876453,0.0000010662358,0.012097279,0.0000074635755,0.000030023797,0.000038529506,0.000055691053,0.000012755875,0.000111884896],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991844,0.000024113408,0.00026124786,0.0001446442,0.0002489555,0.0001366311],"domain_scores_gemma":[0.99910396,0.00027980146,0.00014007377,0.00024604387,0.00014493887,0.00008515565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009943999,0.0000974653,0.00018996585,0.000074826865,0.00007668947,0.000025881904,0.00012572198,0.000047801557,0.00028308757],"category_scores_gemma":[0.00031735539,0.00007991011,0.0000385519,0.0002565417,0.00008633608,0.000039406328,0.000027534245,0.00010855727,0.000049064663],"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":[0.00006950251,0.0004930423,0.0010553658,0.00025746447,0.00014722638,0.0000106897905,0.00030747007,0.000249429,0.06225734,0.9328299,0.0010556469,0.0012668938],"study_design_scores_gemma":[0.020098463,0.0016599662,0.07898598,0.0010160821,0.0019337708,0.0009310362,0.0042034765,0.36724168,0.36332086,0.08311869,0.07239782,0.005092163],"about_ca_topic_score_codex":0.000047736892,"about_ca_topic_score_gemma":0.000013139264,"teacher_disagreement_score":0.84971124,"about_ca_system_score_codex":0.000018183055,"about_ca_system_score_gemma":0.000016195872,"threshold_uncertainty_score":0.325864},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029923155,0.00074568746,0.9832095,0.0013356627,0.00041078287,0.0005630949,0.000035677887,0.000058613532,0.010648696],"genre_scores_gemma":[0.025938883,0.0000051301945,0.9653576,0.00097311323,0.0003222901,0.00010659588,0.0000031197133,0.000026661302,0.0072666323],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960463,0.0008728302,0.00069000607,0.00071636966,0.0012309544,0.00044353062],"domain_scores_gemma":[0.9918412,0.0066884016,0.00024005343,0.00060173124,0.00040664332,0.00022199626],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.010869766,0.00020482772,0.00043661363,0.00063280325,0.00017736702,0.00021083088,0.00088355417,0.00012258765,0.0015210918],"category_scores_gemma":[0.012444907,0.00015644789,0.00031975,0.0018055225,0.00007324012,0.0003986522,0.0001199511,0.00014131499,0.0008161183],"study_design_candidate":"design_other","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":[0.00024199154,0.00013723678,0.00015578774,0.0000021139715,0.00003505978,0.0000037413977,0.00048641628,0.00035542014,0.042113245,0.022867847,0.024841085,0.9087601],"study_design_scores_gemma":[0.0012885927,0.00058170425,0.00076082617,0.000008795505,0.000037872225,0.000031510866,0.0006303738,0.02289604,0.26159716,0.07154842,0.64016783,0.00045086627],"about_ca_topic_score_codex":0.000008708784,"about_ca_topic_score_gemma":0.000006114182,"teacher_disagreement_score":0.90830916,"about_ca_system_score_codex":0.00011989407,"about_ca_system_score_gemma":0.000099545614,"threshold_uncertainty_score":0.99996185},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019925924,0.00007020244,0.9743714,0.000018032211,0.00002347851,0.00006604128,0.00013486017,0.000024509263,0.0053655724],"genre_scores_gemma":[0.17128623,0.0000047943395,0.8285444,0.000008589446,0.00001020601,0.0000018411873,0.000008749619,0.0000101082705,0.00012510017],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9988077,0.00017219101,0.0002940143,0.0002890256,0.00025208428,0.00018497555],"domain_scores_gemma":[0.99675053,0.0019818675,0.00016627024,0.0009036513,0.00012342661,0.00007424476],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010821993,0.00011135826,0.00044205773,0.00042432206,0.000056757024,0.00002359898,0.0003907544,0.000043817927,0.0009712942],"category_scores_gemma":[0.0034718201,0.00007911532,0.00004661586,0.001868425,0.00010853141,0.00010533658,0.00010638155,0.00009013322,0.0000040566724],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016740024,0.0014324083,0.37129128,0.00048737923,0.0059728827,0.00028700245,0.0015170015,0.000012246424,0.00084813545,0.46458092,0.002079678,0.14981705],"study_design_scores_gemma":[0.0015394393,0.001220206,0.51502556,0.00043128978,0.017391302,0.000039598992,0.0007691563,0.033180334,0.018453209,0.4100202,0.0006791207,0.0012505831],"about_ca_topic_score_codex":0.0002199258,"about_ca_topic_score_gemma":0.00008101698,"teacher_disagreement_score":0.15136029,"about_ca_system_score_codex":0.000013700879,"about_ca_system_score_gemma":0.000057918372,"threshold_uncertainty_score":0.99994195},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6295856,0.000041158324,0.369886,0.000083538085,0.000019431094,0.00015962706,0.000077386954,0.000009225437,0.00013801118],"genre_scores_gemma":[0.9925381,0.0000048206516,0.0073986542,0.000018222465,0.0000035911232,0.000003965269,0.000008503799,0.0000041656685,0.000019994106],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99936897,0.00003430738,0.00025502592,0.000101422076,0.00014337305,0.00009687807],"domain_scores_gemma":[0.9992677,0.00032167588,0.000106789725,0.00017603324,0.000097541306,0.000030278115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000106293,0.00006604746,0.00015683266,0.00005968072,0.000044346987,0.0000061157043,0.00009048494,0.00003845042,0.000022286324],"category_scores_gemma":[0.00059867394,0.000051611634,0.000024321445,0.000475073,0.000061741695,0.000036081434,0.000033978245,0.00006679548,8.31779e-7],"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":[0.000050609156,0.0004333588,0.00022049849,0.0000606112,0.00002395408,2.406701e-7,0.00030398305,0.016956974,0.0018024544,0.97618806,0.00020863503,0.0037506456],"study_design_scores_gemma":[0.001201262,0.00017577849,0.04372245,0.0001288911,0.00011341426,0.000002227181,0.00046715265,0.32307625,0.024066491,0.6067802,0.000023547138,0.00024238494],"about_ca_topic_score_codex":0.000034701665,"about_ca_topic_score_gemma":0.00000979811,"teacher_disagreement_score":0.36940786,"about_ca_system_score_codex":0.000023295583,"about_ca_system_score_gemma":0.000021203754,"threshold_uncertainty_score":0.21046615},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38492474,0.0003917816,0.6104289,0.00008840591,0.0023354793,0.0005303588,0.00007386669,0.000055549008,0.0011708923],"genre_scores_gemma":[0.40218022,0.0000012951805,0.5960952,0.00013003389,0.0006972505,0.0000649158,0.000004694588,0.000026310294,0.00080008927],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99657416,0.0005208848,0.0006987725,0.0005964412,0.0009256558,0.00068409514],"domain_scores_gemma":[0.98813534,0.01054821,0.00030502,0.0004696904,0.00013420482,0.00040755305],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0041704797,0.00030816975,0.0005282599,0.00063093094,0.0003361921,0.00036108657,0.0004434913,0.0000740653,0.0004738838],"category_scores_gemma":[0.008681199,0.00024640816,0.00021112633,0.00085283216,0.00013492655,0.0013833229,0.00022689214,0.00026277817,0.0002273536],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007677729,0.0007734816,0.010579915,0.00007500141,0.00021500596,0.00002007475,0.0035699415,0.0017094751,0.52248305,0.035138153,0.0046145488,0.42005357],"study_design_scores_gemma":[0.011717256,0.0014739662,0.0757645,0.0002057254,0.0002405157,0.0003771662,0.0029029555,0.2864211,0.5637947,0.03710878,0.017262248,0.002731124],"about_ca_topic_score_codex":0.000013261014,"about_ca_topic_score_gemma":0.000003748408,"teacher_disagreement_score":0.41732246,"about_ca_system_score_codex":0.00013417381,"about_ca_system_score_gemma":0.00004941707,"threshold_uncertainty_score":0.9999988},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9753134,0.0016241204,0.013959808,0.000002863865,0.00040690816,0.000064644,0.000019117264,0.00015588544,0.008453226],"genre_scores_gemma":[0.9990236,0.00014652354,0.00065549783,0.000004887732,0.000044261233,0.00000752287,0.0000033578021,0.000014526632,0.00009980855],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993329,0.000031508473,0.00021986413,0.000107611566,0.00013209191,0.00017604572],"domain_scores_gemma":[0.999564,0.00016714683,0.00003780395,0.00017369377,0.000015638036,0.000041744006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020827868,0.00009741361,0.000203033,0.0001209123,0.00008789898,0.0000064596143,0.00014604285,0.00004235886,0.000018479916],"category_scores_gemma":[0.000051392955,0.00009206351,0.00006285318,0.00044003574,0.000044472796,0.00007818874,0.000009383638,0.00010922918,0.000015760588],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016914602,0.00019632022,0.25149193,0.0022522593,0.0005983009,0.00013485417,0.015753957,0.029214134,0.6018243,0.07913149,0.0013927052,0.017840624],"study_design_scores_gemma":[0.0032651199,0.0003353622,0.13915162,0.0014661954,0.00012571944,0.00033221958,0.0062794467,0.017073927,0.7561564,0.019379353,0.053754423,0.0026802167],"about_ca_topic_score_codex":0.000008393876,"about_ca_topic_score_gemma":0.0000057892603,"teacher_disagreement_score":0.15433212,"about_ca_system_score_codex":0.000018206963,"about_ca_system_score_gemma":0.0000042528623,"threshold_uncertainty_score":0.3754241},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09067345,0.00012750231,0.9044628,0.0006509693,0.00029052506,0.0011624062,0.00024714976,0.000019204097,0.0023659712],"genre_scores_gemma":[0.99441683,0.000008914766,0.00436551,0.00012741536,0.00007747295,0.000120933706,0.000005747093,0.000005907097,0.0008712942],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974807,0.0006116902,0.0005861132,0.00036551902,0.00078418234,0.00017178642],"domain_scores_gemma":[0.9896677,0.008391908,0.00027832415,0.00080360257,0.0007960422,0.00006243003],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0066673863,0.000101689395,0.00031737288,0.00012467311,0.00024519392,0.00006215058,0.0008418136,0.000077391276,0.000128576],"category_scores_gemma":[0.014413475,0.000054831045,0.0001753025,0.0012095423,0.00018517395,0.00014995619,0.00015235755,0.000098206176,0.000027583266],"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":[0.0013175673,0.0014975367,0.04112209,0.000106694235,0.00024073162,2.1830367e-7,0.0068178065,0.0056186295,0.007104295,0.515059,0.008996552,0.41211888],"study_design_scores_gemma":[0.0022685037,0.000129163,0.012018731,0.000013735218,0.00005184719,0.0000012098639,0.0005415007,0.008876707,0.037394237,0.8571304,0.08138539,0.00018857277],"about_ca_topic_score_codex":0.00012643644,"about_ca_topic_score_gemma":0.00008857277,"teacher_disagreement_score":0.9037434,"about_ca_system_score_codex":0.000029418034,"about_ca_system_score_gemma":0.00009587618,"threshold_uncertainty_score":0.99388856},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009242251,0.000005402246,0.98903507,0.00029423457,0.00005699868,0.00026196413,0.0038628443,0.000039328705,0.0055199373],"genre_scores_gemma":[0.45042786,0.0000024673936,0.5483862,0.000082730905,0.00003303039,0.00004639336,0.00023698797,0.00001111546,0.00077320624],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991647,0.00003395438,0.00039881578,0.00012774434,0.00015148838,0.00012329117],"domain_scores_gemma":[0.9952208,0.0039175223,0.00017113688,0.0002233519,0.00040547393,0.00006173611],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00039219123,0.00007291798,0.000185793,0.000055047953,0.000055932243,0.00001108562,0.000099657715,0.000044460277,0.00008621057],"category_scores_gemma":[0.01875478,0.00006642745,0.000030247442,0.00029800233,0.000059267888,0.000020517846,0.000014552067,0.000042159423,0.000037415484],"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":[0.000026113896,0.00007967591,0.00001572688,0.000048100585,0.000011008318,5.251408e-8,0.000023346991,0.0000037026641,0.000097550634,0.93545485,0.057069898,0.0071699987],"study_design_scores_gemma":[0.0027362807,0.00018541382,0.0028693818,0.000028733783,0.000098202625,0.0000011654029,0.000047424997,0.043733295,0.004426334,0.8621381,0.083529726,0.00020593387],"about_ca_topic_score_codex":0.0000034250806,"about_ca_topic_score_gemma":0.0000040514724,"teacher_disagreement_score":0.44950363,"about_ca_system_score_codex":0.000018609744,"about_ca_system_score_gemma":0.000025699826,"threshold_uncertainty_score":0.98951066},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11715357,0.0029170644,0.87424165,0.00020824857,0.0003018419,0.0010257247,0.000012361443,0.0000576498,0.0040818704],"genre_scores_gemma":[0.29401916,0.00004118477,0.7016501,0.00011069596,0.00006531829,0.0001658094,0.0000023043383,0.000024554669,0.0039208913],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969438,0.000356936,0.0006517481,0.0007392657,0.0008829942,0.0004252555],"domain_scores_gemma":[0.9941409,0.004413602,0.00023547752,0.000568401,0.00034838024,0.00029320957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004260291,0.00023334596,0.0004775964,0.0015473153,0.00022440481,0.00056180015,0.0006516173,0.00014314077,0.00074581924],"category_scores_gemma":[0.0051587527,0.00015554465,0.0001590311,0.0030260584,0.00011887606,0.0011381591,0.00020883851,0.0001251921,0.00021025634],"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":[0.00034569314,0.00033859632,0.0011894973,0.000020322077,0.000061033374,0.0000055449714,0.00071207475,0.026751354,0.042869918,0.0056241853,0.05152092,0.8705609],"study_design_scores_gemma":[0.0027940914,0.0012229538,0.003451882,0.000037612852,0.000044088723,0.000024766845,0.001610721,0.85401666,0.069504626,0.058704212,0.007763904,0.0008244746],"about_ca_topic_score_codex":0.000040053947,"about_ca_topic_score_gemma":3.590646e-7,"teacher_disagreement_score":0.8697364,"about_ca_system_score_codex":0.000069147005,"about_ca_system_score_gemma":0.000042012365,"threshold_uncertainty_score":0.81661975},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005546127,0.000015653259,0.9791854,0.0004168963,0.00007364161,0.00013747919,0.0001822899,0.000068897265,0.014373614],"genre_scores_gemma":[0.86517143,0.0000036102906,0.13303463,0.000060660757,0.000050202092,0.000003995947,0.00013841948,0.000009742318,0.0015273021],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992028,0.00001629732,0.00031869469,0.00011388416,0.00018498022,0.00016334043],"domain_scores_gemma":[0.99886346,0.0004915198,0.00010694175,0.00023036567,0.0001435968,0.00016409885],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00027483248,0.000076261924,0.00013877555,0.000098281824,0.000062692496,0.000009803353,0.00010752569,0.000058840105,0.0011231643],"category_scores_gemma":[0.0020496075,0.00007106731,0.000050074705,0.0010588178,0.00005534088,0.000036939124,0.000023097058,0.00008323124,0.00018187294],"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":[0.000008853868,0.00007675409,0.00016986573,0.000013042561,0.000011477534,9.1923704e-7,0.000026130181,5.833747e-7,0.0005267988,0.94736207,0.047064364,0.0047391746],"study_design_scores_gemma":[0.0014534133,0.00014324413,0.052717004,0.000054125434,0.00019105543,0.000013979319,0.00030300178,0.0014844094,0.027295154,0.72347355,0.19244091,0.0004301771],"about_ca_topic_score_codex":0.00002839679,"about_ca_topic_score_gemma":0.00003097814,"teacher_disagreement_score":0.8596253,"about_ca_system_score_codex":0.0000592122,"about_ca_system_score_gemma":0.00007029787,"threshold_uncertainty_score":0.99978995},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16788387,0.00022829381,0.82473713,0.0002890105,0.00025238798,0.0007674418,0.0009293248,0.00013951049,0.004773003],"genre_scores_gemma":[0.92565256,0.000004151222,0.073451385,0.00004395151,0.00002764337,0.000037907797,0.0000427988,0.000012843574,0.00072674773],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991044,0.000041646388,0.000270619,0.0000992911,0.00029395585,0.00019011588],"domain_scores_gemma":[0.99898845,0.00025355906,0.00013571596,0.00019064659,0.00033975116,0.0000918899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001699115,0.000096174925,0.00015722522,0.00007060896,0.00009721554,0.000010406087,0.00009056025,0.00004554283,0.0006272987],"category_scores_gemma":[0.0036333709,0.00007360964,0.000020031819,0.00037604722,0.00007176824,0.000045017692,0.000033627886,0.00007769346,0.00014141435],"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":[0.000025651565,0.0005637152,0.00017269631,0.000064564694,0.0000226386,3.0247554e-7,0.00015406689,0.0000034948553,0.0007686188,0.9870603,0.00800842,0.0031555237],"study_design_scores_gemma":[0.006165437,0.0018054203,0.061034728,0.0006804271,0.00091950083,0.000043203596,0.0012265453,0.01177733,0.37632298,0.50216645,0.035518475,0.002339476],"about_ca_topic_score_codex":0.0000040578225,"about_ca_topic_score_gemma":8.121446e-7,"teacher_disagreement_score":0.7577687,"about_ca_system_score_codex":0.000038516024,"about_ca_system_score_gemma":0.00003337626,"threshold_uncertainty_score":0.6868481},"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":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09346684,0.0017324559,0.87465906,0.00034019677,0.0013093065,0.0008356279,0.00001683484,0.00010848507,0.027531223],"genre_scores_gemma":[0.31608784,0.000019881973,0.66846305,0.0008426637,0.00015771348,0.00013161564,0.0000025509842,0.000028287692,0.014266396],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9968915,0.00029263424,0.0006287255,0.0006344471,0.0011369014,0.00041580104],"domain_scores_gemma":[0.99419814,0.0045267646,0.00017224369,0.00068640773,0.00021964853,0.00019678482],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0024025494,0.00020359024,0.0003997012,0.00047442733,0.0003041475,0.00011597097,0.0009061345,0.0001264453,0.0014597742],"category_scores_gemma":[0.0074743386,0.00016053383,0.00025073215,0.0012299173,0.000101898804,0.00033175395,0.0001377324,0.00010297024,0.0004610923],"study_design_candidate":"bench_or_experimental","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":[0.0010588418,0.0009058571,0.009250909,0.0000111634545,0.00011819814,0.00010806535,0.0037560845,0.0004393229,0.33443058,0.0033092478,0.5007689,0.1458428],"study_design_scores_gemma":[0.0011390671,0.0009187782,0.0010297152,0.000008009474,0.0000106066145,0.000033493954,0.00075926154,0.0021332817,0.92283016,0.0026462607,0.06813199,0.00035937468],"about_ca_topic_score_codex":0.000027609567,"about_ca_topic_score_gemma":9.794308e-7,"teacher_disagreement_score":0.5883996,"about_ca_system_score_codex":0.000067280125,"about_ca_system_score_gemma":0.00007081567,"threshold_uncertainty_score":0.999453},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90772045,0.00040927719,0.07864918,0.00018700179,0.000048195023,0.0012703012,0.0000030382273,0.00012233079,0.011590217],"genre_scores_gemma":[0.88525295,0.000011092053,0.11228264,0.000041874264,0.000056825214,0.00061026844,0.000015965405,0.000019534697,0.00170882],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992923,0.00006168567,0.00023945012,0.00014518172,0.00016202132,0.000099339035],"domain_scores_gemma":[0.9996024,0.00010251732,0.00006187547,0.000109136716,0.000053738393,0.00007034494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033486,0.00008765482,0.00014217799,0.0001468062,0.000035360747,0.000031717216,0.00005096065,0.000048575384,0.000069271875],"category_scores_gemma":[0.0005085464,0.000067453264,0.00002296143,0.00034320506,0.000013664099,0.00014045983,0.000020997537,0.000059992944,0.000021663673],"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":[0.00001304657,0.00031190852,0.00011288276,0.000040554405,0.0000058252235,3.0279097e-7,0.0016516879,2.6927728e-7,0.0026121116,0.99396133,0.0005526651,0.0007374283],"study_design_scores_gemma":[0.0022779943,0.00022080108,0.0001669921,0.000054679524,0.00003131714,0.000014414415,0.004398115,0.035038777,0.21766919,0.734108,0.005620981,0.00039875612],"about_ca_topic_score_codex":0.00001334576,"about_ca_topic_score_gemma":0.000011202492,"teacher_disagreement_score":0.25985333,"about_ca_system_score_codex":0.000068990164,"about_ca_system_score_gemma":0.00002052111,"threshold_uncertainty_score":0.27506644},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045077223,0.000011643426,0.9494027,0.00048944575,0.00011043612,0.0002984037,0.0030855099,0.00021721021,0.0013074172],"genre_scores_gemma":[0.8461661,0.0000016646007,0.15216765,0.00009005015,0.00006278306,0.000060546954,0.0011724852,0.000014417475,0.00026430632],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857974,0.00005097933,0.000435784,0.0003818547,0.00035849615,0.00019315777],"domain_scores_gemma":[0.9970088,0.00146926,0.00018372221,0.0009646546,0.00020909104,0.00016449449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005038529,0.00014213905,0.0002183767,0.00014162641,0.00013971806,0.00009384765,0.00049091916,0.00010980175,0.0006196352],"category_scores_gemma":[0.005098371,0.00012447673,0.00003830386,0.0007905334,0.00008641914,0.00014972998,0.00015407044,0.00027488222,0.0006061567],"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":[0.000007968992,0.00014397463,0.00015839408,0.000025114601,0.000026028009,0.0000011074972,0.000008841279,0.0001744295,0.00049479894,0.99125975,0.0067610247,0.0009385657],"study_design_scores_gemma":[0.0003021947,0.000007166052,0.007570927,0.000015380776,0.00007104986,0.0000025316801,0.000027702476,0.78219867,0.00028429186,0.20855692,0.0007916807,0.0001715132],"about_ca_topic_score_codex":0.00002652375,"about_ca_topic_score_gemma":0.000019809742,"teacher_disagreement_score":0.80108887,"about_ca_system_score_codex":0.000048459493,"about_ca_system_score_gemma":0.000167985,"threshold_uncertainty_score":0.77911204},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1267406,0.0015482506,0.86593086,0.0014377184,0.00072645565,0.0006509318,0.00007416991,0.00008073826,0.0028102736],"genre_scores_gemma":[0.96803993,0.000005078419,0.029247,0.0004200077,0.00014942288,0.000064240696,0.0000024658223,0.000009574751,0.0020623042],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974885,0.00012392686,0.00044763196,0.00037685473,0.0010923839,0.00047070018],"domain_scores_gemma":[0.9939999,0.004727625,0.00014157529,0.00068702456,0.00022299465,0.00022087405],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00630663,0.00012776586,0.00023930873,0.00032226255,0.00018836763,0.00012191475,0.0007068342,0.00009137422,0.00031625136],"category_scores_gemma":[0.011066041,0.00008618615,0.00017392782,0.0010883933,0.00008260528,0.00046236496,0.000082315404,0.00009707299,0.00046171423],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025757466,0.0026329118,0.48747388,0.00005891243,0.00004489888,0.0000044538547,0.0015144764,0.0031804761,0.008877067,0.049097482,0.03365796,0.4131999],"study_design_scores_gemma":[0.0030146728,0.00059650355,0.05406673,0.000042836313,0.00008494079,0.000011025027,0.0004510006,0.11035584,0.074272916,0.19158566,0.56456715,0.0009507524],"about_ca_topic_score_codex":0.00003213919,"about_ca_topic_score_gemma":0.000019014722,"teacher_disagreement_score":0.8412993,"about_ca_system_score_codex":0.00006694889,"about_ca_system_score_gemma":0.00009390791,"threshold_uncertainty_score":0.99726415},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9251088,0.005239418,0.06043019,0.00045907847,0.000430598,0.00034946043,0.000036069687,0.000029888135,0.007916501],"genre_scores_gemma":[0.9955056,0.000023333045,0.002857834,0.000017155025,0.000023918647,0.000006983922,4.5198286e-7,0.0000036031809,0.001561122],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976865,0.00028999196,0.00067150174,0.00021339399,0.0009950714,0.0001435527],"domain_scores_gemma":[0.9975903,0.00058386946,0.00023519265,0.00053142087,0.00096398,0.00009523754],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0055780997,0.000076136566,0.00038098806,0.00033174074,0.000047590547,0.000027658474,0.0005266845,0.000069341426,0.00009112243],"category_scores_gemma":[0.013158678,0.000044686905,0.00011003638,0.0011651405,0.00032726987,0.0002413868,0.000120055636,0.000070658825,0.00006150558],"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":[0.007559242,0.0049901158,0.17182809,0.0004762577,0.00075544347,0.000012635998,0.030929636,0.04796043,0.16776001,0.3535775,0.08557517,0.12857547],"study_design_scores_gemma":[0.009082704,0.0005949174,0.0046067624,0.0001747109,0.00012167915,0.000012605006,0.003681963,0.027237,0.3603144,0.54053074,0.053165235,0.00047727395],"about_ca_topic_score_codex":0.00025950445,"about_ca_topic_score_gemma":0.00002803919,"teacher_disagreement_score":0.19255438,"about_ca_system_score_codex":0.000022073013,"about_ca_system_score_gemma":0.0002736734,"threshold_uncertainty_score":0.9951539},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8268398,0.017536808,0.12110454,0.00039580764,0.0003262911,0.0008656802,0.0004706402,0.00006943713,0.032391],"genre_scores_gemma":[0.99769616,0.00012253864,0.0015610402,0.000038900384,0.00014432122,0.000090309615,0.000016804559,0.000015594862,0.00031434317],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99923277,0.000009116294,0.00033289546,0.0001840948,0.000047168418,0.0001939355],"domain_scores_gemma":[0.99942183,0.000051834555,0.00015642676,0.00026157996,0.000032687603,0.00007560653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002880224,0.00010122081,0.0002458138,0.00031737823,0.000091415684,0.000020344178,0.00010284598,0.000083620376,0.000045484885],"category_scores_gemma":[0.00007375614,0.000100690835,0.0000664263,0.0003647431,0.000073037874,0.0001548326,0.000026166874,0.00007413192,0.00004967086],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009821946,0.0010165726,0.4597932,0.00018530493,0.00005249075,3.2289873e-7,0.00094443996,0.0073773987,0.00048125617,0.49605906,0.0019419672,0.03204977],"study_design_scores_gemma":[0.0014550115,0.00021379144,0.7142078,0.000073506315,0.00004500467,0.0000028653992,0.00013371096,0.08328761,0.0051379004,0.043196812,0.15149064,0.0007553058],"about_ca_topic_score_codex":0.00016366353,"about_ca_topic_score_gemma":0.000015118509,"teacher_disagreement_score":0.45286223,"about_ca_system_score_codex":0.000035015368,"about_ca_system_score_gemma":0.000011886587,"threshold_uncertainty_score":0.4106053},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013518627,0.00042543182,0.96957964,0.00029935775,0.00023351857,0.00048318753,0.0006171304,0.00012169385,0.01472142],"genre_scores_gemma":[0.015768759,0.00011722508,0.98103344,0.00016718815,0.00014812098,0.00003238808,0.000032322325,0.000024715384,0.0026758586],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99884975,0.000068111476,0.0002731337,0.00032637405,0.00021051742,0.00027209517],"domain_scores_gemma":[0.9958371,0.0031375429,0.00005270991,0.0008202152,0.00006297407,0.000089478126],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00074199325,0.000112309484,0.00022450864,0.00004882423,0.000068536945,0.0000333797,0.0004735704,0.000060901497,0.0021360202],"category_scores_gemma":[0.004996799,0.0000909665,0.00003365201,0.00023316668,0.00002676892,0.00007521129,0.00006767039,0.00010095242,0.00013863422],"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":[0.000046369256,0.00012174293,0.000054305052,0.00006309726,0.000028341794,0.000003861079,0.00003335663,1.1470256e-7,0.0001310903,0.07180278,0.015855437,0.9118595],"study_design_scores_gemma":[0.00065212906,0.00012722875,0.00023186546,0.00003510101,0.000069060996,0.000004741294,0.000013471189,0.0059239464,0.0023364248,0.84936494,0.14103408,0.0002070243],"about_ca_topic_score_codex":0.000013722996,"about_ca_topic_score_gemma":0.000010191743,"teacher_disagreement_score":0.9116525,"about_ca_system_score_codex":0.000020691261,"about_ca_system_score_gemma":0.000029734227,"threshold_uncertainty_score":0.99877614},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3504645,0.0020297454,0.64440024,0.000012120278,0.00017636291,0.00042729752,0.000089650406,0.00022686491,0.0021732308],"genre_scores_gemma":[0.9902372,0.000026401529,0.009520317,0.000007260829,0.000040579576,0.000012995647,0.000010893705,0.000026600763,0.00011779087],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991169,0.00003064101,0.00037839884,0.00014051358,0.00015025926,0.00018328839],"domain_scores_gemma":[0.9995171,0.00010327048,0.000066889035,0.00022077296,0.000044666514,0.00004729495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008329742,0.00014030014,0.00037974355,0.00007904631,0.000040369734,0.000016803653,0.00008608779,0.00005714245,0.00010554158],"category_scores_gemma":[0.00005462756,0.00014221342,0.00005411885,0.00031881325,0.0000220373,0.0001743597,0.0000039524894,0.00006031429,0.0000131718425],"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":[0.00004858922,0.000086056185,0.045727927,0.00004891215,0.000052345815,0.0000016450463,0.000086252476,0.9328032,0.008132053,0.000015318816,0.000025948413,0.012971731],"study_design_scores_gemma":[0.0015027198,0.00007622029,0.008591977,0.000049218415,0.000062471445,0.000001929031,0.000014227883,0.98341084,0.004900352,0.000014042683,0.0012169,0.00015911579],"about_ca_topic_score_codex":0.00003273679,"about_ca_topic_score_gemma":0.0000042518486,"teacher_disagreement_score":0.63977265,"about_ca_system_score_codex":0.00016084326,"about_ca_system_score_gemma":0.00000581656,"threshold_uncertainty_score":0.57992953},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.097248256,0.000023457904,0.898798,0.00039510225,0.00011071232,0.00028105103,0.0016243828,0.000022655659,0.0014964169],"genre_scores_gemma":[0.8923828,0.0000027728195,0.107154265,0.000120067365,0.00003921747,0.00004214696,0.000054362263,0.00001304781,0.00019133472],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989262,0.000107106105,0.00035604258,0.00010686613,0.00035558752,0.00014817384],"domain_scores_gemma":[0.9955641,0.003460966,0.000172432,0.0003560097,0.0003596136,0.000086852124],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00043646505,0.000097209726,0.00021793222,0.00006241672,0.000061899074,0.000009887697,0.0001720654,0.000047079437,0.0012102142],"category_scores_gemma":[0.007111153,0.00006826899,0.00003531748,0.00057829666,0.00006767382,0.000030513818,0.000032807864,0.000082743136,0.00009613994],"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":[0.000020238214,0.00026064258,0.00052341004,0.00002442338,0.00003081509,8.137301e-8,0.00025853465,0.000007866875,0.0003685762,0.9759774,0.014573845,0.007954175],"study_design_scores_gemma":[0.00060250383,0.00013182401,0.056373283,0.00012787295,0.00022603932,6.595042e-7,0.0005868407,0.0018053885,0.02809732,0.90462065,0.0070992196,0.00032842092],"about_ca_topic_score_codex":0.00007282503,"about_ca_topic_score_gemma":0.000008702278,"teacher_disagreement_score":0.79513454,"about_ca_system_score_codex":0.000028047018,"about_ca_system_score_gemma":0.000028977507,"threshold_uncertainty_score":0.9997028},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93842745,0.0000030210629,0.059418738,0.000040959916,0.000101829166,0.000131315,0.000005569833,0.0000049256237,0.0018662114],"genre_scores_gemma":[0.97999954,0.000002489743,0.019961564,0.0000068513646,0.0000056934505,0.000009097159,2.3098288e-7,0.0000042451456,0.00001031326],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993118,0.000097343574,0.00027468387,0.00008772749,0.00015393471,0.00007453213],"domain_scores_gemma":[0.99520564,0.0043215426,0.00013222189,0.00027114074,0.000050894192,0.000018534054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062600005,0.00006265333,0.00018603129,0.00007755281,0.000012890317,0.0000033351214,0.00010408467,0.000048772254,0.0001605015],"category_scores_gemma":[0.00649945,0.00002922385,0.00004198955,0.00015693455,0.00004682736,0.000029500672,0.000033019714,0.00022704675,7.748455e-7],"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":[0.000084209445,0.00030883725,0.0011164768,0.00008887486,0.000006096603,1.9760063e-7,0.00028570893,0.0000028891702,0.03147098,0.9056693,0.00002792536,0.06093855],"study_design_scores_gemma":[0.00010611511,0.00009139023,0.0038848848,0.0000612536,0.0000046144373,2.163587e-7,0.00005156518,0.0073165526,0.16839017,0.8200611,0.0000026847765,0.000029448684],"about_ca_topic_score_codex":0.00002257672,"about_ca_topic_score_gemma":0.000038546666,"teacher_disagreement_score":0.1369192,"about_ca_system_score_codex":0.000013493989,"about_ca_system_score_gemma":0.000007751544,"threshold_uncertainty_score":0.77809185},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010652406,0.00017169406,0.9668522,0.011450755,0.00003880085,0.0015959626,0.008840018,0.0001485997,0.0002495455],"genre_scores_gemma":[0.9874473,0.00002583751,0.008080812,0.00031355597,0.000090835376,0.0013113589,0.0016499014,0.000013054616,0.0010673039],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989878,0.00006171916,0.00028009896,0.00018938885,0.00027398564,0.00020702159],"domain_scores_gemma":[0.99519104,0.004051445,0.00016136096,0.0002579558,0.00028150505,0.000056714754],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002130205,0.00012856832,0.00013871735,0.000016109727,0.00061211013,0.00011146195,0.00027547224,0.000056064462,0.0012320423],"category_scores_gemma":[0.005928427,0.000073145275,0.00007745755,0.0002878147,0.00020131994,0.00006920353,0.000018866138,0.000110690366,0.00006846419],"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":[0.000039401322,0.00012968988,0.0003471173,0.000048359176,0.000037477996,2.3255537e-7,0.00008486338,0.00005269155,0.000017388287,0.91309285,0.080516994,0.0056329556],"study_design_scores_gemma":[0.00090071734,0.00004809507,0.17504615,0.000060899918,0.0001639081,0.000007346031,0.0003400366,0.012929184,0.0006682981,0.65760624,0.15197505,0.00025407693],"about_ca_topic_score_codex":0.000009129587,"about_ca_topic_score_gemma":0.000023226048,"teacher_disagreement_score":0.97679496,"about_ca_system_score_codex":0.00005202967,"about_ca_system_score_gemma":0.00007147599,"threshold_uncertainty_score":0.999681},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022883404,0.000029907133,0.96950287,0.0002003074,0.00004783854,0.0001788458,0.000017407458,0.000030250187,0.0071091615],"genre_scores_gemma":[0.6513577,0.0000016072748,0.34839413,0.000045807283,0.000025165278,0.000008812707,0.0000025883094,0.000008834983,0.00015533839],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992088,0.00006396484,0.0002657162,0.00011439039,0.00020465835,0.00014244876],"domain_scores_gemma":[0.9960873,0.0033826153,0.00012419488,0.00027112247,0.000111099165,0.000023665209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006411172,0.00009114446,0.00017450692,0.000055457138,0.000060505532,0.000009177544,0.0001082925,0.000039066563,0.000044950662],"category_scores_gemma":[0.0030156393,0.00005577977,0.000039982737,0.00032194375,0.000065655295,0.00004139678,0.000022794116,0.000089561225,0.000012112271],"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":[0.000022176526,0.00010824729,0.000082391445,0.00006835004,0.0000068548825,7.875266e-7,0.000037243255,0.00049726263,0.0004482438,0.99145305,0.00023453489,0.0070408755],"study_design_scores_gemma":[0.00015109054,0.00007244371,0.0014816042,0.00003733433,0.00003191089,0.000001086346,0.000016198726,0.013419124,0.022631554,0.96177894,0.0003007018,0.00007804012],"about_ca_topic_score_codex":0.000040326886,"about_ca_topic_score_gemma":0.000012687056,"teacher_disagreement_score":0.6284743,"about_ca_system_score_codex":0.000035284083,"about_ca_system_score_gemma":0.0000180341,"threshold_uncertainty_score":0.36102197},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01639857,0.000006264237,0.97264194,0.004132967,0.00011551501,0.001444074,0.005087232,0.000042118125,0.00013128873],"genre_scores_gemma":[0.9882162,4.1140393e-7,0.008609036,0.0011382767,0.000118550415,0.00064457854,0.0012114617,0.000015968057,0.000045490455],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989891,0.00007463632,0.00032042945,0.00018338728,0.00022667008,0.00020574406],"domain_scores_gemma":[0.9880376,0.010897298,0.00019139136,0.0006633349,0.00015100933,0.00005936522],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001430465,0.000119092794,0.00016936111,0.000040267205,0.00029098135,0.000032441843,0.0002921875,0.00006145315,0.0002354367],"category_scores_gemma":[0.014365997,0.000067120294,0.00006959927,0.000303515,0.000056811645,0.00006200321,0.000031112384,0.000109769266,0.000026519112],"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":[0.00021711604,0.00043597713,0.00021191256,0.00018615487,0.00003667477,1.1498227e-8,0.00007165658,0.000014437405,0.000093796676,0.96519905,0.03268621,0.0008469918],"study_design_scores_gemma":[0.002900641,0.0005289093,0.070822954,0.00020113298,0.00090991694,0.0000022791053,0.0005652998,0.5193093,0.0023039766,0.33261457,0.069182515,0.0006585126],"about_ca_topic_score_codex":0.0000014204462,"about_ca_topic_score_gemma":9.5090775e-7,"teacher_disagreement_score":0.9718177,"about_ca_system_score_codex":0.00003753232,"about_ca_system_score_gemma":0.00004324599,"threshold_uncertainty_score":0.9939364},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4526267,0.00012516062,0.5405621,0.00031607042,0.00016358908,0.00020436128,0.000010281695,0.00007570605,0.0059160455],"genre_scores_gemma":[0.6729191,0.000014435252,0.32654777,0.00023624409,0.000022252652,0.000007700039,0.0000018524184,0.00000945058,0.00024123475],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988716,0.00008725685,0.00032677822,0.00022698911,0.00021726175,0.00027010316],"domain_scores_gemma":[0.99821895,0.0012905938,0.000058554822,0.00028383342,0.000071210416,0.000076862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039088776,0.00013616995,0.00026366476,0.00018904415,0.00004315636,0.00004163264,0.00015144155,0.000080674254,0.00026836427],"category_scores_gemma":[0.0019050734,0.00011607579,0.000045818582,0.00062921987,0.000066036584,0.0000710611,0.000023645925,0.00015314353,0.00008966702],"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":[0.00006606561,0.0011120699,0.018556213,0.00020671822,0.00004688479,0.000039973722,0.0016081547,0.00030659413,0.00043364312,0.6942563,0.005343231,0.27802414],"study_design_scores_gemma":[0.00044203442,0.000114770584,0.23786865,0.0000843783,0.000028695285,0.0000045925317,0.00025861984,0.009000583,0.00081761094,0.7504595,0.0006376579,0.00028291112],"about_ca_topic_score_codex":0.000055964803,"about_ca_topic_score_gemma":0.000025431033,"teacher_disagreement_score":0.27774122,"about_ca_system_score_codex":0.000057876947,"about_ca_system_score_gemma":0.000037157068,"threshold_uncertainty_score":0.4733433},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6090244,0.0000366286,0.38819614,0.000054601285,0.0000078817375,0.000098854594,0.00025628033,0.000016358206,0.0023088425],"genre_scores_gemma":[0.9853184,0.0000018906749,0.014560925,0.0000065199633,0.00000557318,0.000009909462,0.000062884865,0.0000033724145,0.000030523166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99913985,0.000047184694,0.00044602389,0.000099867226,0.00018087045,0.000086207896],"domain_scores_gemma":[0.9979594,0.0015156559,0.00020338585,0.00017884032,0.00011348194,0.000029272232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027759586,0.000052066865,0.0002513331,0.00029867026,0.00001750281,0.0000048984366,0.00009674089,0.000016169934,0.00022059753],"category_scores_gemma":[0.0030755594,0.000050852523,0.000064235224,0.001758594,0.000055759007,0.000022932656,0.000020718137,0.000047627465,0.0000052313585],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000790836,0.0005502232,0.122345574,0.0000925698,0.000108645196,0.0000014636743,0.000045591656,0.0032089108,0.0010393854,0.87030876,0.00097231835,0.0013186675],"study_design_scores_gemma":[0.00029788038,0.00001231344,0.83160335,0.000026096233,0.000310019,3.8825692e-7,0.00005653551,0.123313256,0.0055258228,0.03865808,0.000104332925,0.00009191193],"about_ca_topic_score_codex":0.00032928694,"about_ca_topic_score_gemma":0.00006353431,"teacher_disagreement_score":0.8316507,"about_ca_system_score_codex":0.000016304508,"about_ca_system_score_gemma":0.000017159884,"threshold_uncertainty_score":0.36819538},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.065442614,0.00007874094,0.93302196,0.000052052164,0.000035705794,0.00026153773,0.000012595248,0.00004862653,0.0010461763],"genre_scores_gemma":[0.5797231,0.0000017587729,0.4200387,0.00002101053,0.0000075614757,0.000030087967,0.0000034291727,0.000014905929,0.00015940188],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991542,0.0000133210215,0.00021947232,0.00021234386,0.00018915026,0.00021153134],"domain_scores_gemma":[0.99871236,0.00076716766,0.00010137542,0.00013216036,0.00020566837,0.00008124235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017292764,0.00013508748,0.00021637307,0.00008782241,0.00008959591,0.00008744817,0.00006876456,0.00005404325,0.0003049001],"category_scores_gemma":[0.0011475895,0.00010017233,0.000013608273,0.00031270267,0.000028583085,0.0002148237,0.00003867704,0.000103719685,0.000016880109],"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":[0.000044607466,0.00009691464,0.00008076969,0.00065728056,0.00009922763,0.000011483736,0.0003616345,0.0008497893,0.000088320776,0.92598176,0.00023280147,0.071495436],"study_design_scores_gemma":[0.0002522306,0.000082588704,0.000113744594,0.00003383141,0.000025893773,0.000023278966,0.000038796417,0.5567816,0.000021097527,0.44253528,0.0000031023203,0.000088578905],"about_ca_topic_score_codex":0.000022138902,"about_ca_topic_score_gemma":0.000035593366,"teacher_disagreement_score":0.5559318,"about_ca_system_score_codex":0.00002689071,"about_ca_system_score_gemma":0.00002817129,"threshold_uncertainty_score":0.4084909},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073376633,0.00001537385,0.98217314,0.0009789999,0.00012208865,0.0004373529,0.0055591343,0.00022702798,0.0031492256],"genre_scores_gemma":[0.6011285,0.00000473947,0.39586842,0.00012680763,0.00009009488,0.00018800986,0.0016556003,0.000022712682,0.00091510284],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984786,0.00008824779,0.0004956661,0.00030378316,0.00031116288,0.00032255144],"domain_scores_gemma":[0.99644446,0.002405924,0.00012150893,0.0004378026,0.00031645675,0.0002738535],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001353495,0.00018822004,0.00025916015,0.000077023615,0.0002311925,0.0001224598,0.00022232284,0.00011728522,0.009147404],"category_scores_gemma":[0.0040967194,0.00017201652,0.000067388246,0.00054494356,0.00014253885,0.0001097142,0.00006250634,0.00021289615,0.004120476],"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":[0.000002858204,0.00021643544,0.00008337491,0.000008262834,0.000030097577,0.0000015170192,0.000028250572,0.0000012408555,0.0006072483,0.9427893,0.05204309,0.0041883076],"study_design_scores_gemma":[0.0005445194,0.000021120555,0.03547325,0.000012721957,0.00008801482,0.0000016569003,0.00004765991,0.019007789,0.0009915946,0.93303263,0.010516161,0.00026286225],"about_ca_topic_score_codex":0.00034628788,"about_ca_topic_score_gemma":0.000011331149,"teacher_disagreement_score":0.5937908,"about_ca_system_score_codex":0.00009725507,"about_ca_system_score_gemma":0.00004450729,"threshold_uncertainty_score":0.9966549},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011694992,0.00006104492,0.9845753,0.00010471844,0.00012950903,0.00044136643,0.0005037634,0.000067510744,0.0024218247],"genre_scores_gemma":[0.29711103,0.0000089512005,0.70214975,0.0002775861,0.00004692196,0.0000069689527,0.0001256515,0.000015527714,0.00025756584],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99831086,0.00034868577,0.0003401153,0.00040415878,0.00030885058,0.00028731013],"domain_scores_gemma":[0.98132885,0.017320618,0.00014226268,0.0009570168,0.00014030279,0.00011093987],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0026001637,0.0001692126,0.0003802205,0.0002419849,0.0001617059,0.000042663007,0.0005762849,0.000089396664,0.00020658519],"category_scores_gemma":[0.061760873,0.00012244798,0.000044693723,0.0009117661,0.00003058593,0.000055961576,0.00010380397,0.00012247698,0.000031471216],"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":[0.00057977944,0.0009194237,0.00069505314,0.00009348284,0.000047949496,0.000008022559,0.00007709003,0.000002494354,0.0020413694,0.2760177,0.16322134,0.5562963],"study_design_scores_gemma":[0.0014744718,0.0013462013,0.07265225,0.00010130993,0.00006660657,0.000003165981,0.000012263779,0.024190962,0.0023399477,0.89496213,0.002417934,0.000432742],"about_ca_topic_score_codex":0.000025769239,"about_ca_topic_score_gemma":0.0000052681457,"teacher_disagreement_score":0.61894447,"about_ca_system_score_codex":0.000034801298,"about_ca_system_score_gemma":0.00003026551,"threshold_uncertainty_score":0.9461423},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0742262,0.0001978789,0.92421466,0.00009785697,0.00006959367,0.0003719442,0.00019403122,0.00011757211,0.00051025965],"genre_scores_gemma":[0.25234678,0.000024177483,0.74726254,0.00005109358,0.000033193308,0.000021729154,0.000007593591,0.000044592034,0.00020829332],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984835,0.00004923135,0.00036053205,0.000382188,0.00038283976,0.00034173473],"domain_scores_gemma":[0.99340147,0.0057756416,0.00020639757,0.00029634824,0.000114472234,0.00020568534],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00041428042,0.00026339016,0.0003941593,0.00012928453,0.00020609026,0.000045723973,0.00013365492,0.00008511702,0.000014324871],"category_scores_gemma":[0.0087014595,0.00018802249,0.000025056916,0.00029890807,0.00015913665,0.00011733197,0.00010611431,0.00026046572,0.000006472837],"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":[0.00061858265,0.004841287,0.070047595,0.0022307844,0.00033475063,0.002073273,0.011849607,0.0015552896,0.005626248,0.7366563,0.0020177101,0.16214857],"study_design_scores_gemma":[0.007949895,0.0065790424,0.01786216,0.0019283117,0.0008058449,0.0004609619,0.0025096468,0.011933036,0.017279591,0.929414,0.001401963,0.0018755614],"about_ca_topic_score_codex":0.000011716248,"about_ca_topic_score_gemma":0.000005717885,"teacher_disagreement_score":0.19275768,"about_ca_system_score_codex":0.00006679086,"about_ca_system_score_gemma":0.000046353158,"threshold_uncertainty_score":0.9996487},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09361949,0.0002399516,0.9050117,0.0003329616,0.00006023619,0.00013683041,0.0000017253082,0.000011132332,0.0005859431],"genre_scores_gemma":[0.81839436,0.0000032242328,0.18146081,0.000056946647,0.000026164375,0.000004069936,0.0000017080966,0.0000033678375,0.000049350987],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981491,0.00042385602,0.00042909928,0.00030734882,0.00046115904,0.00022945547],"domain_scores_gemma":[0.9986832,0.000103767896,0.0002629911,0.0008673015,0.000061114435,0.00002162904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018710849,0.00012016437,0.0003307596,0.00090853986,0.00011930614,0.00008135865,0.0009085684,0.000052631625,0.000005639099],"category_scores_gemma":[0.000059236103,0.00006162653,0.00044090673,0.013923673,0.00004994389,0.00018302504,0.00012321548,0.00013118378,2.9804121e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019016594,0.00083844893,0.54835236,0.000084203995,0.0021493305,0.000052459287,0.0054888637,0.046197783,0.011911414,0.17788652,0.00013864071,0.20688097],"study_design_scores_gemma":[0.000118582364,0.000014859112,0.40517595,0.000010517322,0.0017401912,0.0000034139498,0.000052503394,0.5743581,0.0048702615,0.013455746,0.000054457865,0.00014543666],"about_ca_topic_score_codex":0.002112896,"about_ca_topic_score_gemma":0.0011400627,"teacher_disagreement_score":0.72477484,"about_ca_system_score_codex":0.000049475853,"about_ca_system_score_gemma":0.000038879207,"threshold_uncertainty_score":0.6689863},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0043667206,0.00005897172,0.99227625,0.001890374,0.00004331472,0.00038514557,0.00023095596,0.00009725515,0.00065099826],"genre_scores_gemma":[0.96737003,0.000020789408,0.03160681,0.00018732937,0.000016735472,0.000127486,0.000054003063,0.000011695546,0.000605111],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991469,0.000047023703,0.0002419955,0.00017063343,0.00022605773,0.00016740825],"domain_scores_gemma":[0.99607456,0.0031404376,0.00013840964,0.00022333162,0.0002898709,0.00013342216],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0005619332,0.00011149832,0.00015635852,0.000056758945,0.00018569178,0.00007104141,0.0001487859,0.00007676951,0.000030448999],"category_scores_gemma":[0.016337987,0.00007298542,0.000032619704,0.00037135056,0.00008913256,0.00007362509,0.00005742643,0.00010279094,0.000022945178],"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":[0.0000180522,0.000102281665,0.00019716527,0.000018801618,0.000029934748,1.5522353e-7,0.00022789607,0.00042904238,0.000063784726,0.9786518,0.015175439,0.00508562],"study_design_scores_gemma":[0.0005553964,0.000028244172,0.0017397508,0.0000232561,0.000054611068,3.896188e-7,0.00007883682,0.52802426,0.00007220217,0.46826905,0.0010492292,0.000104757986],"about_ca_topic_score_codex":0.000019555708,"about_ca_topic_score_gemma":0.000011013341,"teacher_disagreement_score":0.96300334,"about_ca_system_score_codex":0.00005822165,"about_ca_system_score_gemma":0.00009857067,"threshold_uncertainty_score":0.9919478},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018684471,0.000020541218,0.96902555,0.000078674995,0.00013802096,0.00018820167,0.000010599185,0.00008536803,0.011768562],"genre_scores_gemma":[0.3792896,0.0000032634225,0.6201633,0.000085924046,0.00003742789,0.00001615112,0.0000012714505,0.000029358573,0.00037369312],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99837667,0.00021538806,0.00038810424,0.00033989016,0.0002997096,0.00038023505],"domain_scores_gemma":[0.99550533,0.003859306,0.00006841783,0.00038349393,0.000034326098,0.00014915249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011146648,0.0001893451,0.00040730447,0.00022434906,0.00004517413,0.000025142243,0.00017386423,0.00011326117,0.00009256739],"category_scores_gemma":[0.0044105686,0.00015824153,0.00006656037,0.00034892984,0.000043620148,0.000092156086,0.000056930996,0.0002814978,0.00008068728],"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":[0.000030041512,0.00013120448,0.000012117459,0.000038070622,0.0000067688716,0.00001145076,0.000060049595,0.0057610893,0.000050383576,0.9841615,0.0001327678,0.009604565],"study_design_scores_gemma":[0.00036418924,0.000078731435,0.000022267028,0.000028277727,0.000012273907,0.0000011727691,0.00000435183,0.33267,0.0001996749,0.66627157,0.00021980832,0.00012770077],"about_ca_topic_score_codex":0.00000866848,"about_ca_topic_score_gemma":0.0000037423126,"teacher_disagreement_score":0.36060512,"about_ca_system_score_codex":0.000059124715,"about_ca_system_score_gemma":0.000014526443,"threshold_uncertainty_score":0.6452902},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2574707,0.000007893587,0.74211353,0.00004079264,0.000045333072,0.00019201943,0.000009147229,0.000013919131,0.000106678075],"genre_scores_gemma":[0.505889,4.9310523e-7,0.49407205,0.000004705933,0.00000167143,0.0000068572554,1.8393627e-7,0.000008871855,0.00001615191],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900645,0.000060494658,0.0002510337,0.000117269454,0.0004626358,0.00010209277],"domain_scores_gemma":[0.9987341,0.0004848643,0.00024494823,0.00034595403,0.00015427072,0.00003582787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063854875,0.00008739426,0.00020750989,0.000053077794,0.000029381688,0.0000026271791,0.00012325961,0.000045849152,0.0000030651156],"category_scores_gemma":[0.0046503115,0.00004493433,0.000050458646,0.00019652247,0.00009517049,0.0000425516,0.00003115629,0.0001389695,1.67506e-7],"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":[0.0006117157,0.0010611083,0.001284526,0.0009635333,0.00017495989,0.0000018935974,0.0022366215,0.1214874,0.3740729,0.19498953,0.00044213203,0.30267367],"study_design_scores_gemma":[0.00042765847,0.000063037,0.00012393548,0.00012168224,0.00005439003,9.813881e-7,0.000035437017,0.57632273,0.21916576,0.20360184,0.0000109176935,0.00007162868],"about_ca_topic_score_codex":0.000010112401,"about_ca_topic_score_gemma":0.000033250337,"teacher_disagreement_score":0.45483533,"about_ca_system_score_codex":0.000015983755,"about_ca_system_score_gemma":0.000036110916,"threshold_uncertainty_score":0.5567193},"labels":[],"label_agreement":null},{"id":"W2086783012","doi":"10.1007/s001840400345","title":"Estimation of P[Y &lt; 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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04126844,0.000024458202,0.95624584,0.0005502073,0.00004757623,0.00038929968,0.0011092738,0.00007246743,0.00029240764],"genre_scores_gemma":[0.80816305,0.0000030256767,0.19038485,0.000027154687,0.00006352531,0.00012986959,0.0010295497,0.000008576424,0.0001903914],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912256,0.000026631278,0.00039654502,0.00013553948,0.00018478939,0.00013393578],"domain_scores_gemma":[0.9990099,0.0004369622,0.00016557358,0.00017649466,0.00015302097,0.000058022728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024829316,0.000085604246,0.00016807934,0.000055561075,0.00008611407,0.000015278883,0.00008693365,0.000056249046,0.00027454566],"category_scores_gemma":[0.001714554,0.00008294704,0.00008570328,0.00028973568,0.00004565594,0.000078827565,0.000013431882,0.000036108915,0.000034189092],"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":[0.000021085729,0.00015562422,0.000004230654,0.000044786386,0.000013049687,3.6697873e-8,0.000022062835,0.00028319485,0.0013786403,0.9420796,0.0146756135,0.041322052],"study_design_scores_gemma":[0.0025363297,0.00008553005,0.0017567498,0.00002996442,0.00022944422,0.0000035109217,0.000023939365,0.5838116,0.09929411,0.2736933,0.03823784,0.00029768093],"about_ca_topic_score_codex":0.0000028292209,"about_ca_topic_score_gemma":0.0000019910212,"teacher_disagreement_score":0.76689464,"about_ca_system_score_codex":0.00006507457,"about_ca_system_score_gemma":0.000022798484,"threshold_uncertainty_score":0.3382482},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55515695,0.00022980761,0.44394425,0.000038973387,0.000022976119,0.00007930535,0.000104566854,0.0000100554935,0.00041312317],"genre_scores_gemma":[0.9201044,0.000119513265,0.07964033,0.00001459388,0.000005525053,0.000005965984,0.000029184595,0.000011686012,0.000068842666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988636,0.00000799051,0.00065757724,0.00022601809,0.0000678762,0.00017694982],"domain_scores_gemma":[0.9992043,0.000063343105,0.00034896098,0.00027155594,0.0000615591,0.00005028375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028787376,0.00011174647,0.00044397573,0.00022856772,0.000048275346,0.000004700148,0.00014085893,0.0000832749,0.000015122356],"category_scores_gemma":[0.00029953656,0.00011261323,0.00009556743,0.0004807118,0.000120322606,0.00013554587,0.000022023933,0.00009584806,0.000013842975],"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":[0.00014984034,0.00023547096,0.041814096,0.00007012549,0.00005379849,0.0000024110766,0.00065428915,0.90893424,0.000037711667,0.045615528,0.0001167864,0.0023157336],"study_design_scores_gemma":[0.00045469851,0.00013793241,0.011966514,0.000017345612,0.000009585129,0.000001681994,0.000013173915,0.9735599,0.0007735023,0.012858124,0.00007057309,0.00013695587],"about_ca_topic_score_codex":0.00023489233,"about_ca_topic_score_gemma":0.000007835896,"teacher_disagreement_score":0.36494744,"about_ca_system_score_codex":0.00003498306,"about_ca_system_score_gemma":0.000035248137,"threshold_uncertainty_score":0.4592234},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5798508,0.00005281969,0.40434006,0.008455003,0.00016314679,0.0010568136,0.0023193676,0.000043125896,0.0037188833],"genre_scores_gemma":[0.99430907,0.000005822647,0.005326315,0.00008398067,0.000012937936,0.000034649223,0.000012409596,0.0000062495615,0.00020857387],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989105,0.00014614259,0.00048582128,0.00012737248,0.00018250411,0.00014765043],"domain_scores_gemma":[0.9983703,0.0007268549,0.00026007261,0.00048492046,0.000121689285,0.0000362006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041840633,0.00009327313,0.00019535096,0.000052034502,0.0000951135,0.000007703702,0.0003347543,0.000058573354,0.0002195572],"category_scores_gemma":[0.002776077,0.000057956542,0.00012649017,0.0011692987,0.00017600905,0.00004140719,0.000094542454,0.00014399874,0.000019376817],"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":[0.000009506698,0.00034450364,0.0013930626,0.00003241186,0.00001847781,9.235579e-8,0.000094401046,0.00012886031,0.0019851208,0.99095494,0.0036020423,0.0014365749],"study_design_scores_gemma":[0.0017581605,0.00002742792,0.42240587,0.00012508812,0.0001668899,0.0000028124698,0.00016639038,0.021059953,0.09740128,0.44239298,0.014224321,0.00026882748],"about_ca_topic_score_codex":0.00004159602,"about_ca_topic_score_gemma":0.000071009694,"teacher_disagreement_score":0.548562,"about_ca_system_score_codex":0.000085751875,"about_ca_system_score_gemma":0.00007629459,"threshold_uncertainty_score":0.3323424},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06704495,0.00007822056,0.93105054,0.00006453394,0.00029327738,0.0009014246,0.000091103335,0.00007678652,0.0003991612],"genre_scores_gemma":[0.3325186,0.0000013799837,0.6670806,0.00014835242,0.00003351416,0.000113706395,0.000018193816,0.000013802236,0.00007183221],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996929,0.0010216151,0.0006958692,0.00037635127,0.00059820985,0.00037896205],"domain_scores_gemma":[0.99327743,0.0051979367,0.0001740266,0.0005454048,0.0005962408,0.00020896336],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.014118853,0.00018369507,0.00032542343,0.0009940831,0.00022829058,0.00028172726,0.00070629444,0.0001510296,0.00043958038],"category_scores_gemma":[0.010960015,0.00013640254,0.00019975015,0.0016271903,0.00020241048,0.001604183,0.0000568422,0.0000957525,0.0000756941],"study_design_candidate":"design_other","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":[0.011459767,0.00034665846,0.00029946715,0.000008650315,0.00007312114,0.0000062245103,0.007957794,0.00004132967,0.14022447,0.031050107,0.0022911453,0.8062413],"study_design_scores_gemma":[0.0027539702,0.0061726444,0.003364693,0.000016022903,0.000079986276,0.000016531205,0.0064657433,0.4998658,0.41903555,0.054366417,0.007204305,0.0006583404],"about_ca_topic_score_codex":0.000009574099,"about_ca_topic_score_gemma":2.7172422e-7,"teacher_disagreement_score":0.80558294,"about_ca_system_score_codex":0.00008073886,"about_ca_system_score_gemma":0.0001013713,"threshold_uncertainty_score":0.9973711},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.090793245,0.000065785476,0.9051676,0.0000972359,0.00017462973,0.00018461028,0.000036808073,0.000032209497,0.0034478926],"genre_scores_gemma":[0.34860647,0.000004641673,0.6508056,0.00005686648,0.00007401001,0.0000111131785,0.0000025701402,0.000012797415,0.0004259351],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990331,0.00006373744,0.00034235278,0.00015916067,0.00018504044,0.00021660462],"domain_scores_gemma":[0.9939661,0.005465277,0.00012309515,0.00019773706,0.0001636025,0.00008418217],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0010610755,0.0000992101,0.00025418864,0.00014167024,0.00006963448,0.00000898192,0.000093267416,0.00007872486,0.00019928649],"category_scores_gemma":[0.0106505165,0.000071296396,0.000088623136,0.0003776415,0.000058525824,0.00003299764,0.000035255383,0.00009727516,0.0000076030356],"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":[0.0006352039,0.0013200635,0.026048105,0.0007113779,0.00020322956,0.000012483916,0.0019888186,0.0000017135263,0.02418076,0.28207174,0.044740386,0.61808616],"study_design_scores_gemma":[0.001131114,0.00072926056,0.047850814,0.00016043408,0.00008928997,0.000004537395,0.00039433627,0.00057140406,0.07756216,0.85524774,0.0159677,0.00029121854],"about_ca_topic_score_codex":0.0000026530672,"about_ca_topic_score_gemma":0.000004491992,"teacher_disagreement_score":0.61779493,"about_ca_system_score_codex":0.000022789554,"about_ca_system_score_gemma":0.000028286604,"threshold_uncertainty_score":0.99768317},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48323306,0.00035652515,0.5142789,0.00018097018,0.00024358538,0.00020102356,0.00008280848,0.000061883824,0.0013612369],"genre_scores_gemma":[0.96869993,0.000035262008,0.029324576,0.00006737532,0.00011441804,0.000007648179,0.000013083682,0.000020271073,0.0017174244],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99748826,0.00024138555,0.00061045965,0.00046900587,0.0009519826,0.00023892749],"domain_scores_gemma":[0.99561673,0.0035207379,0.00013820373,0.00047966614,0.000114647584,0.0001300382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019170801,0.00019054912,0.0004913701,0.00044295253,0.0000673483,0.00011378734,0.00041340853,0.0001257834,0.00048851024],"category_scores_gemma":[0.002951711,0.00013366787,0.000101376354,0.0004829695,0.00009757065,0.00023997058,0.000058206726,0.00010392985,0.00006671955],"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":[0.0036886325,0.00091489044,0.0011648211,0.00007944589,0.0005800142,0.000036988484,0.0040261527,0.2548421,0.12653252,0.3726279,0.05276782,0.1827387],"study_design_scores_gemma":[0.0026386427,0.00035646412,0.0044323145,0.00007131878,0.00009523304,0.000002789667,0.000027899778,0.5069151,0.010702638,0.47172394,0.0025675565,0.00046607124],"about_ca_topic_score_codex":0.00015623045,"about_ca_topic_score_gemma":0.0000039866404,"teacher_disagreement_score":0.4854669,"about_ca_system_score_codex":0.000015326765,"about_ca_system_score_gemma":0.00003525251,"threshold_uncertainty_score":0.54508173},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016387371,0.000007732835,0.9413939,0.0004226311,0.00015564232,0.00024154993,0.000049834623,0.00019839394,0.041142926],"genre_scores_gemma":[0.8983762,0.0000016955314,0.0998959,0.00034554084,0.000057950667,0.00001379772,0.000039462695,0.000012931278,0.0012565006],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99913454,0.000029497554,0.0002412656,0.00016253405,0.00025476495,0.00017741577],"domain_scores_gemma":[0.9972449,0.0021697236,0.000072942144,0.0002626631,0.00014405025,0.00010573865],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004958083,0.00009037548,0.00011402874,0.00012261968,0.00009955424,0.000023730743,0.0001126686,0.00005489812,0.0010015906],"category_scores_gemma":[0.0056293546,0.000080268095,0.000037101487,0.0007429372,0.000040998755,0.00002937762,0.00001103574,0.000098138495,0.0005378189],"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":[0.00006343966,0.00054940255,0.0016858999,0.00004328555,0.00001242691,0.000004485479,0.00004006135,0.000023734663,0.00047012142,0.8814967,0.052344818,0.063265584],"study_design_scores_gemma":[0.0016045906,0.0006440101,0.17497599,0.0001586221,0.000114866,0.000005748516,0.00012364326,0.041982915,0.020506516,0.68640256,0.0727016,0.0007789428],"about_ca_topic_score_codex":0.0000055633454,"about_ca_topic_score_gemma":0.000006033386,"teacher_disagreement_score":0.8819888,"about_ca_system_score_codex":0.000066478395,"about_ca_system_score_gemma":0.000028306667,"threshold_uncertainty_score":0.9999116},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4543784,0.00026947775,0.50601923,0.00011563785,0.0006441883,0.00023488795,0.0000298866,0.00005729061,0.03825101],"genre_scores_gemma":[0.6848846,0.0000023832613,0.3129402,0.00014902012,0.00006205802,0.00000582887,0.0000012997021,0.000013807327,0.0019407712],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99565256,0.0009499584,0.00076058396,0.0005099947,0.0018086171,0.00031829474],"domain_scores_gemma":[0.99393123,0.004551451,0.0003324896,0.00072136236,0.00028405897,0.0001794247],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007986927,0.00018749706,0.00049219356,0.0006211272,0.000086846936,0.00008890627,0.00091393734,0.00008466536,0.0013804634],"category_scores_gemma":[0.00890927,0.00014222483,0.00022469295,0.0020146442,0.0001920477,0.00022621019,0.00018203403,0.00012894842,0.00036751106],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019819636,0.00028788278,0.034456544,0.000009249624,0.00007714237,0.000008028149,0.00065868645,0.000781576,0.6739311,0.037401482,0.00677264,0.24541746],"study_design_scores_gemma":[0.0018607487,0.00056240446,0.022835813,0.000021441996,0.000038490984,0.000015629723,0.00045631302,0.009432342,0.9115029,0.03832646,0.014479727,0.00046771762],"about_ca_topic_score_codex":0.000040563405,"about_ca_topic_score_gemma":0.0000058779524,"teacher_disagreement_score":0.24494974,"about_ca_system_score_codex":0.00004227752,"about_ca_system_score_gemma":0.000065219756,"threshold_uncertainty_score":0.9995324},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002472369,0.00024439575,0.99457854,0.00016196106,0.0004994352,0.00044696152,0.000024363408,0.00010837345,0.0014635816],"genre_scores_gemma":[0.010891137,0.0000044230146,0.9882277,0.0001539526,0.0003144378,0.00015846155,0.0000029782257,0.000029430623,0.000217473],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987799,0.00032025416,0.00028210558,0.00023213425,0.00012386923,0.0002617222],"domain_scores_gemma":[0.99447143,0.0047569145,0.00011314803,0.00025489216,0.00023058009,0.00017301316],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0025415206,0.00013831377,0.00030355697,0.00014622795,0.000057525347,0.00004455715,0.00013264704,0.00009681384,0.000066520835],"category_scores_gemma":[0.03119162,0.00011507842,0.00008206951,0.00032743192,0.0000382031,0.00005246854,0.000053853993,0.00009440069,0.000019864929],"study_design_candidate":"design_other","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":[0.000041428048,0.000095483665,0.000025634508,0.00005858947,0.000021643697,5.386884e-7,0.00033267366,1.1398845e-7,0.003963775,0.033445053,0.0004395171,0.96157557],"study_design_scores_gemma":[0.00057457027,0.00070873805,0.00020882483,0.000028330169,0.000084115236,0.000006295773,0.00016018235,0.0025144797,0.10142803,0.84368926,0.050362825,0.00023433716],"about_ca_topic_score_codex":0.00006593523,"about_ca_topic_score_gemma":0.000021704649,"teacher_disagreement_score":0.9613412,"about_ca_system_score_codex":0.00007852543,"about_ca_system_score_gemma":0.000022945627,"threshold_uncertainty_score":0.97696906},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51222086,0.0010731828,0.48027122,0.0009829081,0.00027995967,0.00024476342,0.00008234956,0.000018872888,0.004825899],"genre_scores_gemma":[0.9979842,0.000020057694,0.0017076387,0.000066510904,0.00008654387,0.000012091196,0.000004328859,0.000009479677,0.00010920026],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990591,0.000050746836,0.00041714625,0.00021308883,0.000056444496,0.00020349926],"domain_scores_gemma":[0.9988407,0.0005281782,0.0002457889,0.00031416948,0.000039148865,0.00003203887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021741022,0.00010605259,0.0003028967,0.000087747525,0.00030155585,0.00005421959,0.00019125114,0.00006040367,0.000027570206],"category_scores_gemma":[0.002672685,0.00006998377,0.00009169937,0.00035182032,0.00014279404,0.000079352314,0.000051256084,0.0002204224,0.000019148347],"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":[0.00008437273,0.000049654664,0.016823225,0.000015576072,0.000030282617,1.2510971e-7,0.0005380551,0.0031540839,0.000010186266,0.9737718,0.00010474753,0.005417867],"study_design_scores_gemma":[0.0013996921,0.000051101568,0.049645737,0.00002360324,0.000012848054,7.607884e-7,0.000027459313,0.7377622,0.000100337886,0.20781791,0.0030354306,0.00012291111],"about_ca_topic_score_codex":0.0011403266,"about_ca_topic_score_gemma":0.00004921817,"teacher_disagreement_score":0.7659539,"about_ca_system_score_codex":0.000033700366,"about_ca_system_score_gemma":0.000011169863,"threshold_uncertainty_score":0.31996468},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95290565,0.00028975215,0.044910952,0.00018562225,0.00033558818,0.0005751982,0.0000604641,0.000054510296,0.0006822296],"genre_scores_gemma":[0.9749336,0.000015723006,0.02232553,0.00010361938,0.00005458532,0.000031557913,8.801397e-7,0.000032938202,0.0025015634],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9947487,0.0016758987,0.0008496238,0.000754683,0.0015491043,0.00042197626],"domain_scores_gemma":[0.9908096,0.0073789363,0.00037681538,0.00091339933,0.0002485384,0.00027266188],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004439486,0.00029825838,0.00079626235,0.00041250954,0.00010168666,0.00011958615,0.0006979012,0.00018087716,0.002986459],"category_scores_gemma":[0.006077186,0.0001785013,0.00021347895,0.00125468,0.00035859057,0.00026337575,0.00021934698,0.00010235728,0.0003822023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021951771,0.000078094374,0.07483106,0.000009854433,0.0000539892,0.00001638457,0.00020752553,5.3144436e-7,0.6693814,0.000026047395,0.0023946972,0.2527809],"study_design_scores_gemma":[0.0027180782,0.0005425186,0.035990994,0.000049492708,0.000036796195,0.000015037444,0.000082212726,0.00012287425,0.95573056,0.00090141996,0.0035065503,0.0003034641],"about_ca_topic_score_codex":0.00008956648,"about_ca_topic_score_gemma":0.0000062591876,"teacher_disagreement_score":0.28634918,"about_ca_system_score_codex":0.000069227324,"about_ca_system_score_gemma":0.00004819607,"threshold_uncertainty_score":0.9979249},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2689397,0.00014314357,0.7283844,0.00014740325,0.00007357033,0.0006235614,0.000099643294,0.00004217286,0.0015464043],"genre_scores_gemma":[0.65548986,0.0000012152954,0.34439185,0.00002038277,0.000002873082,0.000009883457,4.293034e-7,0.000012845375,0.00007064195],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987517,0.000055588105,0.00031080938,0.00014018554,0.0005759476,0.00016577641],"domain_scores_gemma":[0.99848115,0.0008270301,0.00016179618,0.00030401678,0.0001637499,0.00006226362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034191427,0.000119425655,0.0002807939,0.000047527305,0.000038742568,0.000003048638,0.00015427878,0.00003855038,0.000032605585],"category_scores_gemma":[0.004501095,0.00006499808,0.000075090975,0.0004792446,0.000135299,0.000022470025,0.000030409341,0.000096508855,0.000002487066],"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":[0.0037497797,0.04112057,0.16791032,0.011702735,0.004229929,0.00012448618,0.0115285665,0.09896186,0.026322756,0.38981876,0.04757084,0.19695938],"study_design_scores_gemma":[0.002524133,0.0031211155,0.004962558,0.0003362251,0.00076564506,0.000023758856,0.0004121451,0.4902371,0.24252689,0.25376475,0.00059212575,0.0007335595],"about_ca_topic_score_codex":0.000021631218,"about_ca_topic_score_gemma":0.0000023655,"teacher_disagreement_score":0.39127523,"about_ca_system_score_codex":0.000027857923,"about_ca_system_score_gemma":0.000059012622,"threshold_uncertainty_score":0.5388557},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.092651516,0.00004366742,0.90613174,0.00006641974,0.0001807661,0.0003132189,0.00019470109,0.000025724901,0.00039227438],"genre_scores_gemma":[0.5768702,0.0000020592317,0.42301232,0.00001517596,0.00004547709,0.000008087118,0.0000122373385,0.000010245351,0.000024229717],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983296,0.0000970883,0.0003943441,0.00027983604,0.0006553333,0.00024382744],"domain_scores_gemma":[0.9981665,0.00042822238,0.00024284644,0.00078301557,0.00030238277,0.000077035475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008347368,0.0001239883,0.00019302659,0.00006774115,0.00011404198,0.000018448643,0.00036647287,0.000033602326,0.00008510857],"category_scores_gemma":[0.0037634291,0.000069399706,0.000030074016,0.0005024713,0.000249159,0.000028400482,0.00023950086,0.00013153031,0.000010895886],"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":[0.00033127825,0.0024798163,0.0012155018,0.000495466,0.00010992188,0.0000019751403,0.001378934,0.27175257,0.0006495475,0.49994814,0.0020836643,0.21955319],"study_design_scores_gemma":[0.00028034844,0.0001425804,0.00070975977,0.00008806997,0.00006662885,0.0000014603703,0.000008037207,0.98144,0.0024320842,0.014536929,0.00019516239,0.00009893878],"about_ca_topic_score_codex":0.000010513981,"about_ca_topic_score_gemma":0.0000046281734,"teacher_disagreement_score":0.7096874,"about_ca_system_score_codex":0.000038629903,"about_ca_system_score_gemma":0.00026098598,"threshold_uncertainty_score":0.4505448},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009327737,0.000021491614,0.98535585,0.00011173241,0.00005108406,0.0003178535,0.0039293496,0.000045277142,0.0008396021],"genre_scores_gemma":[0.72073454,0.0000018289039,0.2788207,0.000018025346,0.00002164969,0.000033202406,0.0002422416,0.000015634263,0.00011221683],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99887127,0.000054602093,0.00037606215,0.00020661567,0.00030793433,0.00018350636],"domain_scores_gemma":[0.99679774,0.0017791295,0.00039010932,0.0006566779,0.0002543079,0.000122021],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016105309,0.00014704934,0.00038252873,0.00006107679,0.00031914184,0.00008001675,0.00030636016,0.000048189544,0.00061282207],"category_scores_gemma":[0.003165661,0.000120151366,0.00003394774,0.00012928729,0.0002646233,0.000042484935,0.000056644625,0.00010909335,0.000043230422],"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":[0.00028669453,0.0006929759,0.0009278302,0.00008919183,0.00030447522,0.0000098013925,0.0001636725,0.0012509201,0.0002657056,0.9789043,0.011707756,0.005396695],"study_design_scores_gemma":[0.013402214,0.00037781004,0.03298576,0.00031379834,0.0012781406,0.000027538883,0.00020991662,0.22238009,0.005335215,0.7191219,0.003471118,0.0010965359],"about_ca_topic_score_codex":0.00022778087,"about_ca_topic_score_gemma":0.000099585086,"teacher_disagreement_score":0.71140677,"about_ca_system_score_codex":0.000025235615,"about_ca_system_score_gemma":0.00006385344,"threshold_uncertainty_score":0.6709972},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014034399,0.000009602542,0.98240423,0.00068495166,0.00010649468,0.000478251,0.00065688987,0.00014580031,0.0014793742],"genre_scores_gemma":[0.97773564,0.0000011557449,0.02110059,0.000153279,0.000107934255,0.0001342188,0.00043824484,0.000013095363,0.00031583192],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991472,0.000033536166,0.00020758485,0.00021093906,0.00019918,0.00020155477],"domain_scores_gemma":[0.99796283,0.0011956136,0.000110998546,0.00024065573,0.00040842514,0.000081467224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015694404,0.00011697006,0.00013733716,0.000055374516,0.0003144323,0.000040956853,0.000106223444,0.000066274515,0.0004718544],"category_scores_gemma":[0.0041892105,0.000102078906,0.000043498487,0.00046040775,0.000097121934,0.00004894476,0.000022542758,0.00007435286,0.00011889769],"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":[0.00006385839,0.0002560169,0.000086585474,0.000039223698,0.000013334295,3.2020426e-7,0.000028934715,0.000032188258,0.00012878542,0.981634,0.013473105,0.004243601],"study_design_scores_gemma":[0.0038145885,0.0022800798,0.024482477,0.00039133857,0.00027649847,0.0000042694724,0.00022586231,0.33827323,0.06097822,0.47893256,0.08920474,0.001136129],"about_ca_topic_score_codex":0.0000026559671,"about_ca_topic_score_gemma":0.000002026267,"teacher_disagreement_score":0.96370125,"about_ca_system_score_codex":0.00010497177,"about_ca_system_score_gemma":0.000044668268,"threshold_uncertainty_score":0.5166475},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003824939,0.00002206724,0.9944977,0.00008285406,0.00022206079,0.00027124563,0.0001518907,0.000037196536,0.0008900399],"genre_scores_gemma":[0.14779058,0.0000025578372,0.8519486,0.000022365182,0.000107069034,0.000018939701,0.000030040983,0.000013475121,0.00006632852],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989826,0.00006642524,0.00028735993,0.00029810757,0.0001560395,0.0002094699],"domain_scores_gemma":[0.9974897,0.0017289529,0.00007099745,0.0005662314,0.00009307293,0.000051053572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011193531,0.00010036527,0.00021961365,0.0001381384,0.00005244423,0.000029671946,0.00031952746,0.000064771426,0.000091410395],"category_scores_gemma":[0.006348171,0.00008645223,0.000023484665,0.0003455384,0.000061337625,0.00017891171,0.00012108093,0.00008168169,0.000024839197],"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":[0.0000704571,0.00018347186,0.00044531326,0.00016838193,0.000025063047,0.0000060378015,0.000154166,0.000014089499,0.00008805468,0.78868246,0.004773215,0.20538926],"study_design_scores_gemma":[0.00025069894,0.00006786665,0.0005066851,0.000027132839,0.000017034185,0.0000012164298,0.000008582254,0.44639987,0.00046029183,0.5519993,0.0001879671,0.00007338485],"about_ca_topic_score_codex":0.00002737519,"about_ca_topic_score_gemma":0.000052091586,"teacher_disagreement_score":0.44638577,"about_ca_system_score_codex":0.00002611837,"about_ca_system_score_gemma":0.000029951829,"threshold_uncertainty_score":0.7599812},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04622371,0.000077359,0.9513818,0.00022410597,0.000019471985,0.00025326732,0.0002377259,0.000059324713,0.0015232116],"genre_scores_gemma":[0.983547,0.000008879272,0.016159559,0.000029909861,0.000035941364,0.000069286914,0.00006401839,0.000005341074,0.00008010601],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999312,0.000028092552,0.00025865075,0.0001413928,0.00015018432,0.0001096682],"domain_scores_gemma":[0.9991252,0.00023218984,0.000107083986,0.00020877186,0.00026328085,0.00006350161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017008925,0.00007679297,0.00012379704,0.00005661906,0.00012399234,0.000017796903,0.00009458379,0.00004560793,0.00012362975],"category_scores_gemma":[0.0013900163,0.00006404355,0.000020625908,0.00039235462,0.00027230213,0.00006070066,0.000038424885,0.000054482352,0.0000361759],"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":[0.000008118233,0.00009272923,0.0003176112,0.000042718522,0.000009512655,5.3260536e-8,0.000093872484,2.2750568e-7,0.005095,0.98299736,0.0010094515,0.010333337],"study_design_scores_gemma":[0.0012983731,0.00030699954,0.045322668,0.00012234194,0.00019358387,0.00001434241,0.00024441758,0.022220854,0.27816397,0.62484705,0.026663607,0.00060179416],"about_ca_topic_score_codex":0.000028573957,"about_ca_topic_score_gemma":0.000013085533,"teacher_disagreement_score":0.9373233,"about_ca_system_score_codex":0.00002238298,"about_ca_system_score_gemma":0.000027246317,"threshold_uncertainty_score":0.261162},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015614756,0.00006298822,0.9959326,0.000054587646,0.00013146127,0.0017717183,0.00021339348,0.00015926028,0.000112563066],"genre_scores_gemma":[0.005150107,0.000009216254,0.9939245,0.00020661594,0.00021817682,0.0003193609,0.000017002589,0.00010487159,0.000050143764],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970035,0.0004966253,0.0005493491,0.0007291095,0.00064496585,0.0005764395],"domain_scores_gemma":[0.996591,0.0013714067,0.0002485486,0.0006434859,0.0008272599,0.00031832015],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0032313678,0.00043644322,0.00094590476,0.0002192541,0.00025403738,0.00010401563,0.00029155824,0.00017990814,0.000014104254],"category_scores_gemma":[0.0029180117,0.0003169203,0.00009433879,0.00041263347,0.0001257043,0.00015358519,0.000073495554,0.00018529201,0.0000038626295],"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":[0.0012280896,0.00069017836,0.0000028947259,0.0053215744,0.00035987401,0.000013708031,0.000579899,0.00032292196,0.018170334,0.9619175,0.000080383485,0.011312618],"study_design_scores_gemma":[0.0014935695,0.0008146174,0.0000012144728,0.00019172704,0.00043740132,0.000006899633,0.000013859295,0.58528197,0.01553417,0.3959396,0.000011920703,0.00027304213],"about_ca_topic_score_codex":0.0000362842,"about_ca_topic_score_gemma":0.000032312004,"teacher_disagreement_score":0.5849591,"about_ca_system_score_codex":0.00007058181,"about_ca_system_score_gemma":0.00012006439,"threshold_uncertainty_score":0.9999283},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9356642,0.0013231107,0.054572422,0.00017413104,0.00032631037,0.0004380278,0.000012407741,0.000055162505,0.0074342205],"genre_scores_gemma":[0.8956702,0.000003963974,0.100704506,0.0001239389,0.00010540812,0.000021294485,3.8673235e-7,0.000014707005,0.003355595],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974621,0.00034773463,0.00043474717,0.00035075934,0.0011878781,0.00021679915],"domain_scores_gemma":[0.99810606,0.000575536,0.00019280236,0.00048729577,0.00054781366,0.00009050179],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018961336,0.00012612679,0.00029579713,0.00042977405,0.00015015533,0.00013408014,0.0005176616,0.000051335017,0.0005547834],"category_scores_gemma":[0.0023782407,0.00007781876,0.00007490203,0.0016663437,0.00056817563,0.0005312785,0.00008945886,0.00006337914,0.00033651045],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004418535,0.00031689604,0.009063251,0.00001171054,0.000088418295,0.000007638058,0.0041450183,0.00008024626,0.95536894,0.010099988,0.004885552,0.015490499],"study_design_scores_gemma":[0.00047639594,0.001093597,0.006659205,0.00002606392,0.000022712307,0.000009112856,0.0017475076,0.00092857087,0.9803903,0.00528811,0.0031690737,0.00018932694],"about_ca_topic_score_codex":0.000063739324,"about_ca_topic_score_gemma":0.00001454795,"teacher_disagreement_score":0.046132084,"about_ca_system_score_codex":0.00003879783,"about_ca_system_score_gemma":0.00010665853,"threshold_uncertainty_score":0.6074489},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4662391,0.01727452,0.38290522,0.0873996,0.00900704,0.0047073336,0.00881114,0.0011106025,0.022545446],"genre_scores_gemma":[0.9961987,0.0005141881,0.0017962828,0.000062137195,0.00036195846,0.00005148844,0.0002467348,0.000030542804,0.0007379726],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99811,0.0001175143,0.000650337,0.00028481375,0.000560687,0.0002766552],"domain_scores_gemma":[0.9968004,0.0016886308,0.0005926603,0.00056739076,0.00026565135,0.000085239364],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001025043,0.0002303472,0.000527823,0.00015138148,0.000102978156,0.000083027204,0.00059547386,0.0001973104,0.00004150819],"category_scores_gemma":[0.009493772,0.00015624762,0.00024101575,0.0008933964,0.00008098514,0.0000349786,0.00058000005,0.00050253153,0.000016629527],"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":[0.0003337725,0.00044761057,0.0005013785,0.01158927,0.0013643957,0.000038945713,0.005832573,0.000013418187,0.00025746576,0.72296005,0.15784428,0.098816864],"study_design_scores_gemma":[0.00028098642,0.0000875353,0.00038090366,0.00019379974,0.0001542442,0.0000025685317,0.00048932445,0.0002673326,0.0057468526,0.96472967,0.027397215,0.00026958995],"about_ca_topic_score_codex":0.0001196755,"about_ca_topic_score_gemma":0.000019590647,"teacher_disagreement_score":0.5299596,"about_ca_system_score_codex":0.00008315574,"about_ca_system_score_gemma":0.00014055161,"threshold_uncertainty_score":0.9988497},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97955555,0.0002169758,0.01508513,0.00017044456,0.0005178507,0.00032274742,0.0035421245,0.0000064229807,0.00058275997],"genre_scores_gemma":[0.99893063,0.000013909878,0.0006610643,0.00012519432,0.000029985986,0.0000079910615,0.00009921481,0.000012395737,0.000119582095],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99894965,0.000027086244,0.0004972252,0.0002655884,0.00010180875,0.0001586605],"domain_scores_gemma":[0.998283,0.00037893403,0.00034918525,0.0009234511,0.000043111588,0.000022296528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010175813,0.00009572512,0.00027854883,0.00010166848,0.000078550205,0.000017714206,0.0006426356,0.000057330028,0.0007451452],"category_scores_gemma":[0.0006337868,0.00006993753,0.000091522765,0.00027952986,0.00004869977,0.00010309365,0.0002231739,0.00013562068,0.00008160327],"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":[0.000020534737,0.00016841089,0.29261884,0.000014906671,0.000026822147,1.5249567e-7,0.000068651294,0.0019586312,0.00007612784,0.70465726,0.00026813435,0.00012149857],"study_design_scores_gemma":[0.0027204454,0.00020590563,0.5523123,0.00007126191,0.00007279244,0.000002058506,0.00015784406,0.08339817,0.0033243154,0.35050017,0.0067676455,0.0004670725],"about_ca_topic_score_codex":0.0007676549,"about_ca_topic_score_gemma":0.00013609948,"teacher_disagreement_score":0.35415712,"about_ca_system_score_codex":0.000037059985,"about_ca_system_score_gemma":0.000048017242,"threshold_uncertainty_score":0.8158817},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024464985,0.0000062808904,0.9690926,0.0008117634,0.000015943126,0.0017835216,0.0031137236,0.00022170805,0.0004894535],"genre_scores_gemma":[0.29792297,2.6790588e-7,0.69827783,0.00055723364,0.000041066098,0.0001648506,0.002897659,0.000030604264,0.00010753004],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980221,0.0000419081,0.00041860563,0.0008466609,0.0003523663,0.0003183916],"domain_scores_gemma":[0.99542135,0.0016244878,0.00018073125,0.0022247988,0.00027836804,0.00027027391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007181694,0.00019928713,0.00030483137,0.00010132072,0.00016638805,0.00010991246,0.0011912951,0.00007605721,0.000104849336],"category_scores_gemma":[0.0035870476,0.00017191841,0.000017411454,0.0008611456,0.00004880826,0.0003445381,0.00037884052,0.00013237358,0.00018679029],"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":[0.00025808442,0.0021366877,0.00094318774,0.000337401,0.000103154205,0.0000015958558,0.000064492764,0.05688881,0.004106565,0.9115951,0.011190619,0.012374318],"study_design_scores_gemma":[0.00053144584,0.0001665731,0.0015905623,0.000032045456,0.000107281514,0.0000065889376,0.000058642283,0.9784943,0.00015910584,0.017605182,0.0009817256,0.00026655063],"about_ca_topic_score_codex":0.000014811764,"about_ca_topic_score_gemma":0.000023236726,"teacher_disagreement_score":0.92160547,"about_ca_system_score_codex":0.0000789685,"about_ca_system_score_gemma":0.00014478406,"threshold_uncertainty_score":0.7010629},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15097634,0.00034140193,0.8461948,0.0009012173,0.00028628192,0.00030887985,0.000019352286,0.000048614074,0.0009231059],"genre_scores_gemma":[0.60645205,0.0000010716908,0.3918605,0.0010930366,0.000017253677,0.000033045577,9.785923e-7,0.000013192843,0.0005288992],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977762,0.00039566934,0.00030494574,0.0005114773,0.0006444835,0.0003672294],"domain_scores_gemma":[0.99820936,0.0003676943,0.00020531754,0.0010317791,0.00009712832,0.00008871284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050371443,0.00022779606,0.0003430167,0.000172017,0.00029079456,0.00008205481,0.0013700202,0.000054324817,0.00008945972],"category_scores_gemma":[0.00009128621,0.00013755467,0.00020251349,0.001284253,0.00013725171,0.00019719717,0.0006883991,0.0004444759,0.0000016095267],"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":[0.00037870026,0.00038021867,0.00263718,0.00012198737,0.00060582435,0.00007004819,0.0060694846,0.045580246,0.0102172755,0.7076533,0.004684408,0.22160134],"study_design_scores_gemma":[0.0010669036,0.00022256882,0.0009313565,0.0000145673675,0.000062694744,0.00014642511,0.000043444183,0.84253186,0.0033244134,0.15085962,0.0004481827,0.00034797247],"about_ca_topic_score_codex":0.000035104713,"about_ca_topic_score_gemma":0.000011319598,"teacher_disagreement_score":0.7969516,"about_ca_system_score_codex":0.00006366025,"about_ca_system_score_gemma":0.00019094019,"threshold_uncertainty_score":0.5609316},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21339938,0.00002623437,0.783784,0.00019165751,0.000032190077,0.00013745656,0.0020182335,0.000030293892,0.00038060558],"genre_scores_gemma":[0.98833877,0.0000025866636,0.010698538,0.00005317201,0.000007833212,0.000022922299,0.00077062164,0.000011521697,0.000094064795],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988662,0.00008090593,0.00040777368,0.0002113783,0.00029787174,0.00013586559],"domain_scores_gemma":[0.9980297,0.0007684432,0.00017016681,0.00041499094,0.0005173,0.00009939157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001604364,0.000107335596,0.0002534755,0.00006687779,0.00007223738,0.000010936437,0.000100092686,0.000093168725,0.00028631167],"category_scores_gemma":[0.0046843463,0.000098155,0.00005913127,0.0009109273,0.00006959254,0.00004519289,0.00003292932,0.00013989881,0.000019317822],"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":[0.000016985843,0.00070239464,0.0000070435517,0.000037328533,0.000024336408,7.74719e-7,0.000043615582,0.00003158611,0.07588573,0.9180867,0.0032081911,0.00195529],"study_design_scores_gemma":[0.003242618,0.0007512171,0.03337306,0.0003472662,0.0004838171,0.000012023544,0.0011703077,0.03255277,0.17621985,0.7499968,0.0009934561,0.00085680257],"about_ca_topic_score_codex":0.000016480106,"about_ca_topic_score_gemma":0.0000028574368,"teacher_disagreement_score":0.77493936,"about_ca_system_score_codex":0.00003574558,"about_ca_system_score_gemma":0.00007511985,"threshold_uncertainty_score":0.5607939},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006613346,0.00023949551,0.9891974,0.0032911638,0.000037853424,0.00035112293,0.00009622916,0.00006435349,0.00010906726],"genre_scores_gemma":[0.5085928,0.000008233486,0.49062896,0.00043592372,0.000036756148,0.000038619903,0.000017991684,0.000009362768,0.00023137216],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988697,0.000021678257,0.00015899028,0.00052706816,0.00014986629,0.00027270507],"domain_scores_gemma":[0.9985994,0.00029543712,0.000072474606,0.00072695327,0.00023121314,0.00007451295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004962974,0.00014124246,0.00018986374,0.000045419452,0.0002463803,0.0002825799,0.0007518834,0.00006942696,7.690675e-7],"category_scores_gemma":[0.00017699668,0.000097112155,0.000040422525,0.00020705868,0.00007676912,0.00027174142,0.00028187045,0.000116825,4.9824223e-7],"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":[0.0002780774,0.0002737777,0.00014040858,0.00033860837,0.00036254528,0.000019095734,0.005863228,0.24723077,0.017865568,0.45050395,0.011997738,0.26512623],"study_design_scores_gemma":[0.0009634867,0.000050369395,0.000004379625,0.000018030798,0.000027052287,0.000014207844,0.0000654118,0.993221,0.0022263234,0.0020373524,0.0012166351,0.00015578246],"about_ca_topic_score_codex":0.000005679894,"about_ca_topic_score_gemma":0.000028631493,"teacher_disagreement_score":0.7459902,"about_ca_system_score_codex":0.000013281586,"about_ca_system_score_gemma":0.00033589095,"threshold_uncertainty_score":0.3960119},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03190604,0.000011486474,0.96478087,0.001203648,0.0009970772,0.0005191249,0.0003555031,0.000037174654,0.00018907156],"genre_scores_gemma":[0.9503867,0.000021239013,0.04902369,0.000035129746,0.00012490353,0.000051872226,0.00001024535,0.000010811503,0.00033537674],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993375,0.000118129115,0.00018672945,0.00010254611,0.0001349933,0.00012009099],"domain_scores_gemma":[0.99026835,0.009317448,0.00012275195,0.0001556576,0.00011008586,0.000025696027],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0008185234,0.00006688808,0.00015275845,0.000029951216,0.00013487852,0.0000190854,0.000099024066,0.000050224986,0.000010748636],"category_scores_gemma":[0.019647598,0.000035121448,0.000051541054,0.0005344351,0.00014003606,0.000019648338,0.0000508821,0.000089934256,0.000001503803],"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":[0.00015051494,0.00006292293,0.0033323532,0.00013246798,0.00009390893,6.270688e-7,0.0009329188,0.0000014607682,0.0007175662,0.5903492,0.024142794,0.3800833],"study_design_scores_gemma":[0.000732871,0.00014458848,0.106700025,0.000055470093,0.00016139842,0.0000023914074,0.0003993778,0.015987117,0.010724131,0.86305654,0.0019263276,0.000109774446],"about_ca_topic_score_codex":0.000036963673,"about_ca_topic_score_gemma":0.00006123937,"teacher_disagreement_score":0.9184807,"about_ca_system_score_codex":0.000025661857,"about_ca_system_score_gemma":0.000026718604,"threshold_uncertainty_score":0.9886103},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011396614,0.00004552144,0.98400974,0.003137964,0.00008187312,0.00026690392,0.0010384445,0.00023741237,0.0100424485],"genre_scores_gemma":[0.89980775,0.0000104303535,0.09741686,0.00048740365,0.00003636853,0.00012841095,0.0009215909,0.000029281553,0.0011618902],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808645,0.00012867928,0.00045588057,0.00044098607,0.00054736494,0.00034062334],"domain_scores_gemma":[0.9971611,0.0014195153,0.00015027818,0.000647333,0.00037751306,0.00024428882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031105775,0.00022289663,0.00030347664,0.0002904372,0.0003721383,0.000089422596,0.00017923045,0.00013659256,0.0006810386],"category_scores_gemma":[0.006531362,0.0001982527,0.00016893538,0.002898657,0.000079356076,0.0000714747,0.000049306578,0.00026285785,0.00024236972],"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":[0.000031731972,0.00095896487,0.00010405533,0.000053968386,0.00002323998,0.000010386397,0.000013233076,0.00629223,0.00013874695,0.943975,0.0438605,0.004537954],"study_design_scores_gemma":[0.0010881311,0.000045036733,0.0010540133,0.000081055776,0.0000926302,0.000005090939,0.00005962582,0.8647436,0.004755389,0.12521829,0.002542693,0.00031444302],"about_ca_topic_score_codex":0.0000038809053,"about_ca_topic_score_gemma":0.0000052212467,"teacher_disagreement_score":0.8986681,"about_ca_system_score_codex":0.00027601677,"about_ca_system_score_gemma":0.00022948181,"threshold_uncertainty_score":0.80845106},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00073984143,0.00034776583,0.98331976,0.0019444762,0.00028411153,0.000055847715,0.000007753424,0.00003197246,0.013268491],"genre_scores_gemma":[0.033951264,0.00006377727,0.9601082,0.000279285,0.00014632927,0.000017418466,0.0000018390379,0.000017498814,0.0054143933],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992987,0.00011149113,0.00014408703,0.00011953529,0.00015584075,0.00017037864],"domain_scores_gemma":[0.99642754,0.0031406959,0.000029999574,0.00026577394,0.00007365663,0.0000623333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038838905,0.000059235746,0.00011086772,0.000016242186,0.00011814847,0.000028941811,0.000083467494,0.000029272227,0.00012456051],"category_scores_gemma":[0.0044415505,0.000035929916,0.000044120847,0.00018870775,0.000036623842,0.000025878835,0.000029783294,0.00009714374,0.000034607026],"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":[0.0000042048036,0.000027752,0.000012207597,0.000010772375,0.000017850876,0.000028717117,0.0001272203,4.823192e-7,0.0003430148,0.85042536,0.008679079,0.14032333],"study_design_scores_gemma":[0.00011314908,0.000013573368,0.000027077165,0.0000049259233,0.0000123469745,0.0000053632266,0.0001689236,0.000333351,0.0034431552,0.9237175,0.07210394,0.00005671724],"about_ca_topic_score_codex":9.42915e-7,"about_ca_topic_score_gemma":0.000019570163,"teacher_disagreement_score":0.14026661,"about_ca_system_score_codex":0.000013504289,"about_ca_system_score_gemma":0.000023191333,"threshold_uncertainty_score":0.53172714},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7419231,0.00015041979,0.25456125,0.00057108846,0.00006343944,0.0018202487,0.0005124773,0.00005712337,0.00034089416],"genre_scores_gemma":[0.9968471,0.0000010673718,0.0025623345,0.000011748108,0.000010143935,0.00018634854,0.00001966298,0.000007397742,0.00035423136],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994294,0.000054659333,0.00016896233,0.000101900834,0.00016970243,0.000075381584],"domain_scores_gemma":[0.99919295,0.0002551826,0.00011671272,0.00018707759,0.00019454854,0.00005354441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010555073,0.00006226928,0.00014386192,0.00002726164,0.00007886838,0.000022804237,0.00007027341,0.000022212684,0.000006043858],"category_scores_gemma":[0.0006688569,0.00003717135,0.000020116588,0.00015095164,0.00009238501,0.000043107917,0.000027736489,0.000030866402,0.00000457766],"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":[0.00043687836,0.0019340235,0.0033497633,0.0010080849,0.00042735846,0.0000013209882,0.0011748656,0.0015338472,0.019689258,0.9531393,0.015047973,0.0022573366],"study_design_scores_gemma":[0.013579175,0.00120879,0.042466547,0.00070345623,0.0011031765,0.00015664473,0.002061477,0.5995025,0.10134386,0.2246559,0.011859665,0.0013588225],"about_ca_topic_score_codex":0.000042927495,"about_ca_topic_score_gemma":0.000003244115,"teacher_disagreement_score":0.7284834,"about_ca_system_score_codex":0.000034561723,"about_ca_system_score_gemma":0.000030674615,"threshold_uncertainty_score":0.15158038},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2025636,0.000035938414,0.7935261,0.00043772138,0.00020773041,0.00039472064,0.0003462091,0.0000192975,0.0024686619],"genre_scores_gemma":[0.82118636,0.000010718385,0.17817053,0.000295613,0.000013629825,0.0000341777,0.0000036637214,0.000011582011,0.0002737516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99885404,0.00018639237,0.00035273287,0.00020109175,0.00021747724,0.00018827202],"domain_scores_gemma":[0.9894241,0.009859888,0.00013706509,0.0003296642,0.0001955963,0.00005368468],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00074307935,0.000117445,0.00030987142,0.000046547,0.00005163829,0.000038145823,0.00017235582,0.000058818347,0.00069317775],"category_scores_gemma":[0.014228141,0.0000811602,0.00015229802,0.00019199633,0.0001380728,0.000022576458,0.000037117163,0.00013202049,0.000007060141],"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":[0.00007528866,0.00028159074,0.00036340172,0.00017253835,0.0000708156,0.000018991765,0.0005590009,0.0000025754402,0.00810609,0.96164507,0.0020851335,0.02661952],"study_design_scores_gemma":[0.001085862,0.0006491769,0.0034139815,0.00039669833,0.00021532497,0.000017630851,0.00071682915,0.0016662176,0.2660135,0.7248092,0.00070240017,0.00031316382],"about_ca_topic_score_codex":0.000016180207,"about_ca_topic_score_gemma":0.000004957573,"teacher_disagreement_score":0.6186227,"about_ca_system_score_codex":0.000020459061,"about_ca_system_score_gemma":0.000068360976,"threshold_uncertainty_score":0.9940754},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09232542,0.00016042481,0.8599266,0.0015003057,0.0005137131,0.0003915499,0.044530332,0.00018134179,0.000470318],"genre_scores_gemma":[0.98405355,0.000008538523,0.007286991,0.000041905278,0.00022271788,0.00012304727,0.007979692,0.000012412929,0.00027116938],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.998821,0.00011259248,0.00034404642,0.00018812795,0.00041003278,0.00012415438],"domain_scores_gemma":[0.99911565,0.00029640313,0.00017822544,0.00024381148,0.00010147258,0.000064451],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00017279656,0.000096441756,0.00017219229,0.00005825683,0.0002297953,0.00001318462,0.00014204062,0.000054084685,0.0033897131],"category_scores_gemma":[0.00046337312,0.00009730368,0.00008271848,0.0005622522,0.000042352185,0.00004573435,0.00006591125,0.00016770264,0.000018643994],"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":[0.00007670024,0.00059534435,0.00047126363,0.0000307083,0.000073041374,0.0000018557752,0.00021824075,0.00005841259,0.0043351687,0.7696629,0.21990937,0.0045670024],"study_design_scores_gemma":[0.0037830116,0.0003480751,0.14070801,0.00003535935,0.0005848171,0.000017818997,0.002563556,0.02731589,0.024966529,0.29932398,0.49969378,0.0006591661],"about_ca_topic_score_codex":0.000021156324,"about_ca_topic_score_gemma":9.636784e-7,"teacher_disagreement_score":0.8917281,"about_ca_system_score_codex":0.000094261,"about_ca_system_score_gemma":0.000028878301,"threshold_uncertainty_score":0.99752134},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8079901,0.011929392,0.119726405,0.0051861675,0.000659499,0.00077305146,0.0003207714,0.00027398072,0.053140685],"genre_scores_gemma":[0.98961973,0.00068566913,0.007440246,0.0001316278,0.00018201476,0.000007879771,0.000021361977,0.000004723027,0.0019067333],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999347,0.00002554799,0.00009241052,0.00019153359,0.00017410921,0.000169447],"domain_scores_gemma":[0.9993805,0.00018652786,0.00003417908,0.0002894765,0.00003307521,0.00007622101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005899575,0.000047309917,0.000118090764,0.00017553207,0.0002889068,0.000080074205,0.00028529152,0.00004242737,0.0002707866],"category_scores_gemma":[0.0003028133,0.000043252057,0.000034370558,0.0010932762,0.000053824,0.0005069788,0.000042488806,0.000039481496,0.0000220853],"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":[0.000041998122,0.00024097093,0.4758046,0.00008000485,0.0010904393,0.000004607781,0.017042547,0.0022730879,0.000028680217,0.0322671,0.22489683,0.24622913],"study_design_scores_gemma":[0.00023305404,0.000022423117,0.0030084895,0.0000039844085,0.00032934916,1.690076e-7,0.00055000494,0.766018,0.000021603786,0.0014972531,0.22815922,0.00015647408],"about_ca_topic_score_codex":0.001155719,"about_ca_topic_score_gemma":0.001868299,"teacher_disagreement_score":0.7637449,"about_ca_system_score_codex":0.000011369919,"about_ca_system_score_gemma":0.000012304694,"threshold_uncertainty_score":0.29649234},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017726697,0.00010516801,0.9794436,0.00009662742,0.00020772271,0.0013102087,0.00015135287,0.0006618801,0.00029672257],"genre_scores_gemma":[0.35654062,0.000005835547,0.6417468,0.00011406535,0.000046052017,0.0010740494,0.0000439137,0.000049217677,0.0003794246],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99772954,0.0002814224,0.00053228735,0.0004879778,0.00050248747,0.0004662554],"domain_scores_gemma":[0.9897999,0.009030602,0.00034575516,0.0004691737,0.00024870335,0.0001058315],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017183789,0.00026310203,0.00043573798,0.0008192428,0.00035803494,0.000048741174,0.0004126917,0.00009664786,0.00019156066],"category_scores_gemma":[0.014069833,0.00027157564,0.00015767357,0.002070228,0.000035955363,0.00022302123,0.00029686547,0.00041334293,0.000008246522],"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":[0.0010552038,0.00319036,0.019953702,0.0010460749,0.00062561006,0.00008173134,0.0055164737,0.08420505,0.0457361,0.31059527,0.03743588,0.49055853],"study_design_scores_gemma":[0.002958827,0.0014339762,0.00074467,0.000035383146,0.00020103478,0.000038164624,0.0011256759,0.29991245,0.04444151,0.6272716,0.020619411,0.0012173349],"about_ca_topic_score_codex":0.00010968204,"about_ca_topic_score_gemma":0.0000340752,"teacher_disagreement_score":0.4893412,"about_ca_system_score_codex":0.00040560003,"about_ca_system_score_gemma":0.00010052431,"threshold_uncertainty_score":0.99997365},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053668674,0.00009754708,0.94099396,0.00006576227,0.00009853211,0.0003783724,0.004247553,0.00009163184,0.00035793436],"genre_scores_gemma":[0.91807383,0.000019747838,0.08078837,0.000022393135,0.000021098696,0.000039720802,0.0008407208,0.00002230572,0.0001718237],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99807936,0.00014130143,0.0008473758,0.00022824686,0.00049418194,0.00020956309],"domain_scores_gemma":[0.9941577,0.0047013587,0.0003461113,0.0003586771,0.00034013996,0.000096020696],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003906142,0.00016039622,0.00059941784,0.00016046627,0.00007895908,0.000020986274,0.00019283169,0.00007651176,0.0014611065],"category_scores_gemma":[0.002271413,0.00014724351,0.00007688149,0.00081438647,0.00009793118,0.000031011037,0.0000651994,0.00010662289,0.00008614902],"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":[0.00090239156,0.0016808227,0.0058373837,0.00043727923,0.00088867405,0.000014187635,0.0010554204,0.027083524,0.0089924345,0.9037961,0.03059179,0.01871999],"study_design_scores_gemma":[0.015822608,0.000098294026,0.0045972886,0.00009371212,0.0006006007,0.0000038088863,0.00055993604,0.36798012,0.03040504,0.5785478,0.00083444495,0.00045634885],"about_ca_topic_score_codex":0.0001415378,"about_ca_topic_score_gemma":0.000061432795,"teacher_disagreement_score":0.86440516,"about_ca_system_score_codex":0.000041604788,"about_ca_system_score_gemma":0.000060127342,"threshold_uncertainty_score":0.9994517},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.084223635,0.000035905785,0.9102899,0.00010115634,0.000044018296,0.00017715312,0.00438991,0.00005258109,0.00068573264],"genre_scores_gemma":[0.97645247,0.0000039922343,0.022922589,0.000007748776,0.000013759047,0.000027916192,0.00041904606,0.0000080247955,0.00014442496],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988818,0.000046283327,0.00055302645,0.00011575204,0.0002632042,0.00013991237],"domain_scores_gemma":[0.99753135,0.0016146048,0.00026648518,0.00026405713,0.00026372832,0.00005975589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021764763,0.00008875995,0.00031537592,0.00018450693,0.000049395665,0.000004201577,0.00015012432,0.00004120785,0.00013125832],"category_scores_gemma":[0.0023031197,0.00008345346,0.00009870511,0.0014400013,0.00017365377,0.000022200229,0.000045750818,0.00007204422,0.00002903204],"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":[0.000007438114,0.00021940764,0.00015221155,0.00008637791,0.000040138344,2.540741e-7,0.000048604572,0.0011403639,0.010364619,0.9704372,0.017041836,0.00046154522],"study_design_scores_gemma":[0.002855704,0.00022828749,0.10053941,0.00020914574,0.0005448979,0.0000029103255,0.00037793542,0.23410572,0.09297265,0.56601816,0.0016277331,0.0005174199],"about_ca_topic_score_codex":0.00004516413,"about_ca_topic_score_gemma":0.0000035979215,"teacher_disagreement_score":0.89222884,"about_ca_system_score_codex":0.00001776613,"about_ca_system_score_gemma":0.000045073142,"threshold_uncertainty_score":0.34031335},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0084622,0.0003106458,0.9851453,0.00016126824,0.00029502116,0.0001239712,0.000030934465,0.00008946222,0.0053812177],"genre_scores_gemma":[0.23253022,0.0000019891163,0.7667358,0.000025729012,0.000103646766,0.0000085656175,0.0000013168411,0.000018539928,0.000574215],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991041,0.00009874209,0.00025924033,0.00014731311,0.00021078752,0.000179848],"domain_scores_gemma":[0.9966759,0.0029613727,0.0000474482,0.00021769557,0.000060956667,0.000036600075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080638635,0.00009079421,0.00018399188,0.000073746676,0.00005951275,0.000026447846,0.00012680971,0.00002676923,0.0001993385],"category_scores_gemma":[0.0026389894,0.000053883472,0.00006912764,0.00045958246,0.000055536653,0.000060406568,0.00004939422,0.00017106556,0.000013636247],"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":[0.000005948754,0.000035189438,0.000021595437,0.00016493074,0.000051543513,0.000015824698,0.00050901435,0.0003256659,0.0016058821,0.95574486,0.00087773526,0.040641803],"study_design_scores_gemma":[0.0001372106,0.000029459217,0.000019855383,0.000066435416,0.00006782464,0.0000068361337,0.00004155732,0.21364868,0.004641248,0.77998024,0.0012774142,0.00008323412],"about_ca_topic_score_codex":0.000010491999,"about_ca_topic_score_gemma":0.000007167373,"teacher_disagreement_score":0.22406803,"about_ca_system_score_codex":0.000019072302,"about_ca_system_score_gemma":0.000023262197,"threshold_uncertainty_score":0.31593075},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0099989185,0.0003861769,0.9883591,0.00013238983,0.00014839247,0.00019294994,0.000014110915,0.00011550584,0.00065247715],"genre_scores_gemma":[0.3002994,0.000012429855,0.6990435,0.000017388176,0.00004481754,0.000020934685,0.0000020552955,0.000022313943,0.0005371435],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989089,0.000117980635,0.00024822896,0.0003055614,0.00017328022,0.00024607015],"domain_scores_gemma":[0.9976595,0.00202387,0.000026328275,0.00017581052,0.000038669546,0.00007583071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007861474,0.00012808423,0.0002631704,0.00016424007,0.00004513907,0.000049342718,0.00008421101,0.00006878008,0.0000438102],"category_scores_gemma":[0.0019872042,0.000090188005,0.00003460022,0.00075363106,0.000039677383,0.00008414517,0.000033733726,0.000353832,0.000016909848],"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":[0.00008685135,0.00041437178,0.00020239454,0.00044012902,0.00006758716,0.000511006,0.0012340232,0.0006674715,0.0011455846,0.9444864,0.00051827636,0.05022593],"study_design_scores_gemma":[0.00093041145,0.00018579788,0.00026313085,0.00018830407,0.0000747863,0.000036969483,0.00014875621,0.29961935,0.0039080116,0.69063896,0.0036229345,0.00038260513],"about_ca_topic_score_codex":0.00011346126,"about_ca_topic_score_gemma":0.00004310366,"teacher_disagreement_score":0.29895186,"about_ca_system_score_codex":0.00008773085,"about_ca_system_score_gemma":0.00005255684,"threshold_uncertainty_score":0.367776},"labels":[],"label_agreement":null}]}