{"meta":{"query_hash":"dedcd1d62568","filters":{"topic":"Direction-of-Arrival Estimation Techniques"},"cohort_total":286,"direct_labels_cover":0,"predictions_cover":286,"exported":286,"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/dedcd1d62568","api":"https://metacan.xera.ac/api/v1/cohort?topic=Direction-of-Arrival+Estimation+Techniques"},"results":[{"id":"W1487824527","doi":"10.1109/sam.2002.1191082","title":"Adaptive beamforming with sidelobe control using second-order cone programming","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Beamforming; Adaptive beamformer; Second-order cone programming; Minimum-variance unbiased estimator; Control theory (sociology); Cone (formal languages); Quadratic programming; Quadratic equation; Computer science; Mathematics; Power (physics); Regular polygon; Convex optimization; Mathematical optimization; Algorithm; Control (management); Telecommunications","score_opus":0.018216555351045487,"score_gpt":0.25164310941506046,"score_spread":0.23342655406401497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1487824527","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":[0.006187862,0.000022255663,0.9802236,0.000033088058,0.00006483303,0.0003632847,7.077429e-7,0.0003993417,0.012705027],"genre_scores_gemma":[0.452374,2.04668e-7,0.5473984,0.00008480265,0.0000042825973,0.000015161223,1.8704858e-7,0.0000066535995,0.00011631588],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896157,0.000052366344,0.0002639304,0.00025812272,0.00023587915,0.00022812396],"domain_scores_gemma":[0.99904895,0.00009412689,0.00017869163,0.00028271668,0.00033056684,0.00006495881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030228548,0.00013499742,0.0002004357,0.0001276375,0.0000985947,0.00008272367,0.00023016932,0.00004614634,0.00005829791],"category_scores_gemma":[0.000073850046,0.00011107067,0.00003475839,0.0005441929,0.00006785931,0.0008320402,0.000032825592,0.000085594846,0.000003899533],"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":[0.000050515333,0.0003312598,0.0026109964,0.00008506545,0.0002261507,0.00002271481,0.0014613057,0.00589471,0.0107567115,0.80181736,0.00020217049,0.17654102],"study_design_scores_gemma":[0.0020407427,0.00088364567,0.00023866764,0.0002097586,0.000048370228,0.00024943284,0.00043868835,0.61357665,0.36507285,0.008673107,0.007697504,0.0008705997],"about_ca_topic_score_codex":0.00008649204,"about_ca_topic_score_gemma":0.00003171523,"teacher_disagreement_score":0.7931443,"about_ca_system_score_codex":0.00005324512,"about_ca_system_score_gemma":0.00016039764,"threshold_uncertainty_score":0.45293307},"labels":[],"label_agreement":null},{"id":"W1491306579","doi":"10.1109/sam.2002.1191059","title":"Wideband array signal processing using MCMC methods","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Reversible-jump Markov chain Monte Carlo; Markov chain Monte Carlo; Wideband; Maximum a posteriori estimation; Robustness (evolution); Computer science; Cramér–Rao bound; Algorithm; Bayesian probability; Monte Carlo method; Array processing; Direction of arrival; Signal processing; A priori and a posteriori; Nonlinear system; Estimation theory; Mathematics; Maximum likelihood; Artificial intelligence; Electronic engineering; Statistics; Telecommunications; Engineering; Physics","score_opus":0.04905118048791222,"score_gpt":0.36757870787867614,"score_spread":0.3185275273907639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1491306579","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":[0.00054134923,0.000052378255,0.96302724,0.00003722718,0.000077642355,0.000079065634,8.776527e-8,0.00032773646,0.035857297],"genre_scores_gemma":[0.20843384,7.666872e-7,0.7913425,0.00006844854,0.0000068577383,0.0000034916382,7.95428e-8,0.0000052049227,0.00013883594],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991169,0.00014392746,0.00022482581,0.00020852576,0.00016949416,0.00013635088],"domain_scores_gemma":[0.99940413,0.000089369525,0.00011496761,0.00020799405,0.00013663394,0.000046906756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007058352,0.00008658315,0.00012927754,0.000121761586,0.00008575817,0.00009872903,0.00026341245,0.000040251834,0.000060595677],"category_scores_gemma":[0.000097426535,0.000076590404,0.000038004793,0.0005041933,0.00003807618,0.0006733189,0.00002753828,0.000059745253,0.0000029289406],"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":[0.0000017788769,0.00006894565,0.00037162242,0.000050515686,0.000010832204,0.0000013170528,0.00046551274,0.00043537104,0.3488267,0.08267512,0.00018894718,0.56690335],"study_design_scores_gemma":[0.000052323026,0.000020533585,0.000030340025,0.000028847235,0.0000035417283,0.000017214392,0.00001013766,0.076027505,0.901303,0.020940008,0.0014632241,0.00010331335],"about_ca_topic_score_codex":0.000023503244,"about_ca_topic_score_gemma":7.9555286e-7,"teacher_disagreement_score":0.56680006,"about_ca_system_score_codex":0.000031060015,"about_ca_system_score_gemma":0.00011594477,"threshold_uncertainty_score":0.3123266},"labels":[],"label_agreement":null},{"id":"W1508948970","doi":"10.1109/vetecs.2006.1683360","title":"Experimental Antenna Array Calibration with ADAptive LInear Neuron (ADALINE) Network","year":2006,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Artificial neural network; Calibration; Antenna (radio); Context (archaeology); Antenna array; Direction of arrival; Smart antenna; Electronic engineering; Algorithm; Directional antenna; Artificial intelligence; Engineering; Telecommunications; Mathematics","score_opus":0.012773020086391605,"score_gpt":0.23645868042236917,"score_spread":0.22368566033597756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1508948970","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":[0.003889623,0.000038790753,0.98614246,0.0001788962,0.00011930875,0.00013807879,9.469733e-7,0.00053250813,0.008959371],"genre_scores_gemma":[0.58717847,9.74161e-7,0.41225412,0.000106219784,0.000073422256,0.000011077308,0.0000038070148,0.000007409818,0.00036447888],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991231,0.00004844125,0.00021346942,0.0002486801,0.00022431296,0.00014202956],"domain_scores_gemma":[0.9994426,0.000037732538,0.000111337795,0.0002693269,0.00010583041,0.000033207278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007674097,0.00010857207,0.0001170608,0.000048034457,0.00006213259,0.000048082038,0.00021035306,0.000035750065,0.00002043298],"category_scores_gemma":[0.000005833127,0.000089788664,0.000031397813,0.00038504033,0.000043016924,0.0006194316,0.000046359444,0.0000572876,0.000006677114],"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":[0.00015528523,0.0008401161,0.0023259467,0.00002311115,0.000043285156,0.00003970605,0.00048097075,0.026633259,0.31578425,0.6315775,0.01724419,0.0048523745],"study_design_scores_gemma":[0.00014217249,0.0002452428,0.0006633604,0.000017220113,0.0000025359768,0.0000134772245,0.00001191852,0.32497147,0.67173964,0.0016930237,0.00037609975,0.00012382741],"about_ca_topic_score_codex":0.00019762349,"about_ca_topic_score_gemma":0.000022827502,"teacher_disagreement_score":0.6298845,"about_ca_system_score_codex":0.000023836958,"about_ca_system_score_gemma":0.00005180802,"threshold_uncertainty_score":0.36614755},"labels":[],"label_agreement":null},{"id":"W1522978537","doi":"10.1109/icassp.1989.267002","title":"Direction of arrival estimation in the presence of noise with unknown, arbitrary covariance matrices","year":2003,"lang":"en","type":"article","venue":"International Conference on Acoustics, Speech, and Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; McMaster University","funders":"","keywords":"Direction of arrival; Estimator; Covariance matrix; Noise (video); Algorithm; Covariance; Probability density function; Covariance function; Mathematics; Sigma; Computer science; Function (biology); Matrix (chemical analysis); Applied mathematics; Statistics; Physics; Artificial intelligence; Telecommunications","score_opus":0.022502169099000102,"score_gpt":0.28245681677973644,"score_spread":0.25995464768073634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1522978537","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":[0.053122457,0.00006351419,0.939207,0.00017631067,0.00009263184,0.00017840098,0.0000056324616,0.000039725506,0.007114306],"genre_scores_gemma":[0.8637387,0.000046285477,0.1361344,0.000030508274,0.0000108855575,0.000009380326,0.0000019120978,0.0000046789073,0.000023224538],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863786,0.00008613357,0.00040156938,0.00023275983,0.0005385447,0.000103117854],"domain_scores_gemma":[0.99863183,0.00021462346,0.00044884658,0.00014728073,0.0005319637,0.000025449659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049651874,0.00012236084,0.00018014973,0.00023453857,0.000050355226,0.000091899485,0.0004449101,0.000051875315,0.000012775939],"category_scores_gemma":[0.00021933489,0.00009334311,0.000023663019,0.0003576047,0.00016605543,0.00061046565,0.000028761002,0.00014656874,4.5913225e-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":[0.000277995,0.00079424743,0.0033487838,0.00070169894,0.00006208038,0.000022100974,0.0035789718,0.02316014,0.09171308,0.6036775,0.000060764716,0.27260262],"study_design_scores_gemma":[0.00034986704,0.00028022737,0.003928437,0.000889368,0.000017067447,0.000042037707,0.00021451207,0.8688804,0.07852908,0.04667508,0.000022460352,0.00017145724],"about_ca_topic_score_codex":0.000057088135,"about_ca_topic_score_gemma":0.0000050007297,"teacher_disagreement_score":0.8457203,"about_ca_system_score_codex":0.000025051775,"about_ca_system_score_gemma":0.00018537634,"threshold_uncertainty_score":0.38064215},"labels":[],"label_agreement":null},{"id":"W1528409897","doi":"10.1002/navi.16","title":"Self-Contained Antenna Array Calibration using GNSS Signals","year":2012,"lang":"en","type":"article","venue":"NAVIGATION Journal of the Institute of Navigation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Computer science; Beamforming; Antenna (radio); Calibration; Antenna array; SIGNAL (programming language); Electronic engineering; Direction of arrival; Global Positioning System; Projection (relational algebra); Algorithm; Telecommunications; Engineering; Mathematics; Statistics","score_opus":0.02545806697957131,"score_gpt":0.2892398970894763,"score_spread":0.26378183010990497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1528409897","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":[0.37349787,0.00011786551,0.6244248,0.00030229596,0.0013250757,0.00017783124,0.0000035882617,0.00004916082,0.00010147271],"genre_scores_gemma":[0.8182864,0.000009789963,0.18148762,0.000040162526,0.0001502402,0.0000022055315,0.0000058009095,0.0000089399,0.0000088172565],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976566,0.0002180457,0.0010730465,0.00012681293,0.000761525,0.00016398774],"domain_scores_gemma":[0.99598414,0.00008446725,0.0022630107,0.00036244382,0.0012113659,0.000094577765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012948975,0.00014880483,0.00028923582,0.00018381116,0.00014622314,0.00006225452,0.00061270804,0.000113539456,0.000003767126],"category_scores_gemma":[0.00021183526,0.000119594246,0.00019487868,0.0009340673,0.00009775394,0.0045844503,0.00006797472,0.00022906094,0.0000015096865],"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":[0.00004861417,0.00039445492,0.0046293433,0.00023923536,0.0001313815,0.000003841452,0.0037544917,0.0087905,0.9448853,0.028816128,0.00010935932,0.008197364],"study_design_scores_gemma":[0.00045325563,0.00009326037,0.00144611,0.00078684627,0.00007477825,0.00028470115,0.000053167987,0.043804716,0.943384,0.009062339,0.00040231584,0.00015451573],"about_ca_topic_score_codex":0.000024096622,"about_ca_topic_score_gemma":8.1458415e-7,"teacher_disagreement_score":0.44478855,"about_ca_system_score_codex":0.00019109939,"about_ca_system_score_gemma":0.0003659268,"threshold_uncertainty_score":0.4876912},"labels":[],"label_agreement":null},{"id":"W1534252773","doi":"10.1109/iscas.2015.7169106","title":"Real-Valued ESPRIT for two-dimensional DOA estimation of noncircular signals for acoustic vector sensor array","year":2015,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Azimuth; Direction of arrival; Computational complexity theory; Algorithm; Computer science; Matching (statistics); Sensor array; Cramér–Rao bound; Estimation theory; Mathematics; Telecommunications; Statistics","score_opus":0.03679856018157619,"score_gpt":0.3186876752174134,"score_spread":0.28188911503583725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1534252773","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":[0.009468591,0.000011846016,0.9880993,0.0002487103,0.00026181294,0.0010091877,0.00002312769,0.0003314173,0.000546037],"genre_scores_gemma":[0.38363564,2.915577e-7,0.61604494,0.000043050684,0.000027588136,0.00011049865,0.000012110432,0.00001186315,0.00011400091],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984773,0.000054883913,0.00051260163,0.00032703314,0.0004296039,0.00019860436],"domain_scores_gemma":[0.9976467,0.0004885223,0.0003183938,0.00042381167,0.0010094614,0.00011311408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008998237,0.00015143635,0.00030995606,0.00018301456,0.000056518413,0.000039563947,0.00035545282,0.00007699943,0.000010721268],"category_scores_gemma":[0.0007694169,0.00014086391,0.00013404893,0.00028661266,0.00005547057,0.00043919025,0.000048188736,0.000042265547,0.0000064133606],"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":[0.00010817231,0.0002605698,0.00002085772,0.00026992118,0.000077898316,8.644987e-7,0.0004523503,0.26603714,0.6633736,0.054821715,0.0058719357,0.0087049715],"study_design_scores_gemma":[0.00044302034,0.000205327,0.000028188058,0.000032847354,0.00001866842,0.0000036278805,0.0000068716445,0.5577407,0.43274775,0.008634995,0.000037014936,0.000101006146],"about_ca_topic_score_codex":0.00009867879,"about_ca_topic_score_gemma":0.0000037343216,"teacher_disagreement_score":0.37416705,"about_ca_system_score_codex":0.00008726121,"about_ca_system_score_gemma":0.0002568231,"threshold_uncertainty_score":0.57442635},"labels":[],"label_agreement":null},{"id":"W1536251062","doi":"10.1109/acssc.1999.832401","title":"BER improvement in a TDMA/FDMA cellular system using antenna array","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Capon; Beamforming; Time division multiple access; Rayleigh fading; Computer science; Electronic engineering; SIGNAL (programming language); Fading; Algorithm; Telecommunications; Channel (broadcasting); Engineering","score_opus":0.01709883797470727,"score_gpt":0.24490127793064537,"score_spread":0.2278024399559381,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1536251062","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":[0.02612129,0.00002552699,0.9607003,0.000030754883,0.00023167534,0.0001796928,4.4923962e-7,0.0002708874,0.012439446],"genre_scores_gemma":[0.6383774,9.590901e-7,0.3613962,0.00003962247,0.0000048472707,0.000009076207,2.0095341e-7,0.0000052336727,0.00016644422],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99896234,0.000064575484,0.0003313892,0.00025587485,0.00021379773,0.00017200233],"domain_scores_gemma":[0.99930525,0.000027318278,0.00010735744,0.0004035686,0.000113354676,0.00004317526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037848865,0.00009789683,0.00015377539,0.0001580666,0.000034325734,0.000053334126,0.00024625583,0.000044617496,0.000016707634],"category_scores_gemma":[0.000039861006,0.00009178093,0.000043860142,0.00050525775,0.000017872446,0.00032688805,0.000047667745,0.00005859647,0.000013348068],"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":[0.0000015748064,0.00011323406,0.00069208007,0.00011208108,0.000011003951,0.000016982684,0.0002649671,0.00009855807,0.7947244,0.1970487,0.000059465616,0.0068569575],"study_design_scores_gemma":[0.00014056849,0.00003623577,0.00006584128,0.00007939677,0.0000027809479,0.000013521829,0.000060958355,0.08185857,0.9157573,0.0015272355,0.00033593734,0.00012164541],"about_ca_topic_score_codex":0.00016490981,"about_ca_topic_score_gemma":0.000009928251,"teacher_disagreement_score":0.61225617,"about_ca_system_score_codex":0.0001366635,"about_ca_system_score_gemma":0.00008540415,"threshold_uncertainty_score":0.37427175},"labels":[],"label_agreement":null},{"id":"W1540437205","doi":"10.1109/iscas.2015.7169222","title":"Multi-beamforming with uniform linear array and algebraic integer quantization based DCT","year":2015,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Discrete cosine transform; Algebraic number; Quantization (signal processing); Integer (computer science); Beamforming; Mathematics; Discrete mathematics; Computer science; Algorithm; Mathematical analysis; Artificial intelligence; Image (mathematics); Statistics","score_opus":0.03639060343457019,"score_gpt":0.27788002126167716,"score_spread":0.24148941782710698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1540437205","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":[0.006727271,0.000007206845,0.99040943,0.00020352904,0.0000585494,0.00014332189,4.5806823e-7,0.0004074806,0.002042729],"genre_scores_gemma":[0.3870834,9.36438e-7,0.6127155,0.00008985557,0.000005631223,0.000005885777,0.000002098148,0.0000052903615,0.00009138865],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993096,0.000022498934,0.00017741208,0.0001844753,0.00020218856,0.0001038124],"domain_scores_gemma":[0.9992973,0.000045113156,0.00009909734,0.0002415587,0.00023658991,0.00008032702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030729434,0.0000932057,0.00011145385,0.00015932789,0.00003840441,0.000054260792,0.00020147252,0.000038703383,0.000005616975],"category_scores_gemma":[0.00009602137,0.000069603644,0.00001551124,0.00038262192,0.000048578968,0.0007598404,0.00004018264,0.000055208653,0.000006595985],"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":[0.00026312124,0.0015807383,0.05140345,0.00058980804,0.00018976063,0.000022538943,0.012693033,0.030851444,0.05585833,0.54949915,0.0030914505,0.29395714],"study_design_scores_gemma":[0.00035222512,0.00016627483,0.00030773814,0.000046359244,0.0000035623739,0.000007102664,0.00004767659,0.83798575,0.15982363,0.00064723333,0.00048916443,0.00012327796],"about_ca_topic_score_codex":0.00010444419,"about_ca_topic_score_gemma":0.000033822074,"teacher_disagreement_score":0.80713433,"about_ca_system_score_codex":0.000029037543,"about_ca_system_score_gemma":0.00010134567,"threshold_uncertainty_score":0.2838354},"labels":[],"label_agreement":null},{"id":"W1543105097","doi":"10.1109/arrays.1988.18038","title":"Systolic array for 2-D adaptive beamforming","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Beamforming; Adaptive beamformer; Computer science; Manifold (fluid mechanics); Systolic array; Cube (algebra); Process (computing); Algorithm; Mathematics; Combinatorics; Engineering; Embedded system; Telecommunications","score_opus":0.02433123193734909,"score_gpt":0.26858439050557387,"score_spread":0.24425315856822477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1543105097","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":[0.00025003584,0.000011576289,0.94584805,0.000052097712,0.00013774436,0.00021234607,6.5757433e-7,0.0003046384,0.05318285],"genre_scores_gemma":[0.2926224,8.747224e-7,0.7068585,0.000056772347,0.0000058143423,0.000044111333,2.1443992e-7,0.0000036318838,0.00040766012],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994569,0.000018045364,0.00015869016,0.00014614,0.0001057791,0.00011443856],"domain_scores_gemma":[0.999455,0.00009733744,0.000074753734,0.00022484797,0.00011493877,0.00003313426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022549034,0.00006161902,0.00009822292,0.00008783757,0.000051581148,0.000025988713,0.00023820817,0.000028169336,0.000010266659],"category_scores_gemma":[0.00012039869,0.000055190376,0.00004768956,0.00021181973,0.000017759196,0.0003735603,0.000015463089,0.000026584774,0.000007746251],"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":[0.0000011433218,0.000019530731,0.000017631197,0.000011871983,0.0000059950144,9.6746966e-8,0.00014696353,0.000034281242,0.0033040573,0.98425055,0.00053197367,0.011675938],"study_design_scores_gemma":[0.0001279071,0.0001250569,0.000029383524,0.000026413358,0.0000035192022,0.000010422702,0.00003644099,0.014595868,0.91509444,0.05984677,0.009975188,0.00012860949],"about_ca_topic_score_codex":0.000016926184,"about_ca_topic_score_gemma":0.0000023896912,"teacher_disagreement_score":0.9244037,"about_ca_system_score_codex":0.00002844007,"about_ca_system_score_gemma":0.00004661872,"threshold_uncertainty_score":0.22505982},"labels":[],"label_agreement":null},{"id":"W1544476852","doi":"10.23919/oceans.2011.6107316","title":"Angle of arrival estimation based on warped delay-and-sum (WDAS) beamforming technique","year":2011,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Beamforming; Narrowband; Computer science; Angle of arrival; Algorithm; Direction of arrival; Transformation (genetics); Function (biology); Adaptive beamformer; Telecommunications; Antenna (radio)","score_opus":0.022940611925198803,"score_gpt":0.25141907346706,"score_spread":0.2284784615418612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1544476852","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":[0.006059349,0.0000033576275,0.97595865,0.000051578812,0.00006487696,0.0003242646,0.0000016959403,0.0004826097,0.017053608],"genre_scores_gemma":[0.49373242,8.8656446e-7,0.50616616,0.00003880307,0.0000027565663,0.000031405638,0.0000010834906,0.0000053795097,0.000021089043],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989584,0.00004216612,0.00036257267,0.00023960814,0.00026067576,0.00013659053],"domain_scores_gemma":[0.99903566,0.00009653274,0.00021809213,0.0004515878,0.00014101669,0.000057100286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042857995,0.0001267101,0.00018750975,0.00031547333,0.000050345192,0.000018067289,0.00038184747,0.0000815634,0.000039253635],"category_scores_gemma":[0.000117130614,0.00011486135,0.00005527525,0.0003685577,0.00006793371,0.0005109115,0.00009178279,0.0000803105,0.000004669414],"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":[0.00011424432,0.0009969465,0.0027066905,0.00037787601,0.0000504157,0.000009661264,0.0021173686,0.0021911093,0.05149999,0.5406002,0.0007168735,0.39861864],"study_design_scores_gemma":[0.000101253914,0.00023169431,0.00054884865,0.00006420082,0.000004857205,0.000005547,0.000005215175,0.4090015,0.5798204,0.010089705,0.000029114864,0.000097653385],"about_ca_topic_score_codex":0.00019189138,"about_ca_topic_score_gemma":0.0000044235594,"teacher_disagreement_score":0.5305105,"about_ca_system_score_codex":0.000030680767,"about_ca_system_score_gemma":0.00005617047,"threshold_uncertainty_score":0.468391},"labels":[],"label_agreement":null},{"id":"W1552475743","doi":"10.1109/acssc.2004.1399544","title":"A recursive filter-based algorithm for maximum likeihood localisation of narrow-band autoregressive sources","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Likelihood function; Algorithm; Autoregressive model; Computer science; Maximum likelihood; Expectation–maximization algorithm; Maximization; Computational complexity theory; Estimation theory; Set (abstract data type); Function (biology); Filter (signal processing); Kalman filter; Matrix (chemical analysis); Data set; Mathematical optimization; Mathematics; Artificial intelligence; Statistics","score_opus":0.014971461762077753,"score_gpt":0.2632171021581201,"score_spread":0.24824564039604236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1552475743","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":[0.0011483198,0.000075081756,0.996053,0.00084857445,0.00012417401,0.00039960587,0.000014078716,0.0002786463,0.0010585608],"genre_scores_gemma":[0.194315,0.0000016555674,0.8052526,0.00014416479,0.000045038185,0.00007375169,0.000009289722,0.000009546763,0.00014891927],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988708,0.000057144247,0.000372222,0.00026915545,0.00027263156,0.00015806839],"domain_scores_gemma":[0.99857587,0.00024303238,0.00035834342,0.00034126456,0.00042580214,0.000055690034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029425783,0.00013017673,0.00020804835,0.00020952299,0.00006032922,0.000042592907,0.00043501618,0.00008078502,0.000037397698],"category_scores_gemma":[0.00011084416,0.000117528834,0.00010563159,0.00024443792,0.00008639305,0.0004739081,0.000033994744,0.000051422474,0.0000041476587],"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":[0.00001634653,0.00021119116,0.00005212981,0.000059418435,0.000024974452,6.118148e-7,0.001213638,0.0013967794,0.0016018781,0.008778469,0.0043673324,0.9822772],"study_design_scores_gemma":[0.00029276445,0.00020514267,0.000054284927,0.000048731632,0.000007348711,0.0000017755847,0.00002399786,0.43957505,0.5504479,0.008135662,0.0011077443,0.00009960963],"about_ca_topic_score_codex":0.000050683157,"about_ca_topic_score_gemma":0.000009319622,"teacher_disagreement_score":0.9821776,"about_ca_system_score_codex":0.000054879012,"about_ca_system_score_gemma":0.00011406492,"threshold_uncertainty_score":0.47926867},"labels":[],"label_agreement":null},{"id":"W1554855718","doi":"10.1109/iscas.2004.1328779","title":"A novel wideband DOA estimation technique based on harmonic source model for a uniform linear array","year":2004,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Wideband; Waveform; Covariance matrix; Computer science; Direction of arrival; Algorithm; Singular value decomposition; Harmonic; SIGNAL (programming language); A priori and a posteriori; Trigonometric functions; Estimation theory; Electronic engineering; Mathematics; Acoustics; Antenna (radio); Telecommunications; Engineering; Physics","score_opus":0.026380192187363902,"score_gpt":0.2801097452739815,"score_spread":0.2537295530866176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1554855718","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":[0.00017064174,0.000001604207,0.99534595,0.000968838,0.000044091023,0.00092767447,0.0000062133386,0.0010128624,0.0015221342],"genre_scores_gemma":[0.29827523,5.963314e-7,0.7009594,0.00032485297,0.000008085445,0.00026132268,0.0000056086246,0.000014175046,0.00015075204],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988091,0.000010312471,0.0003461338,0.0003417077,0.00028921966,0.00020352652],"domain_scores_gemma":[0.99889404,0.00011605322,0.00017664784,0.00053158123,0.00021033674,0.00007131558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040875596,0.00017296313,0.00018528607,0.00029283046,0.000104876824,0.00006506405,0.00049172825,0.00010557716,0.0000039115243],"category_scores_gemma":[0.00016443389,0.00015733883,0.000103991595,0.00042455696,0.000043470725,0.00051306473,0.000038049242,0.00010459098,0.0000062850872],"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":[0.000023517265,0.00023253172,0.0000020242383,0.000051411425,0.0000060266902,1.6941205e-7,0.00016307055,0.89457786,0.045837466,0.04696253,0.00011592962,0.012027458],"study_design_scores_gemma":[0.00033739145,0.00013365189,0.0000026465732,0.0000638731,0.0000036225872,0.0000028143847,0.0000012048104,0.59010255,0.39303932,0.01614143,0.0000632478,0.0001082778],"about_ca_topic_score_codex":0.00007507138,"about_ca_topic_score_gemma":0.000009132656,"teacher_disagreement_score":0.34720185,"about_ca_system_score_codex":0.00015284595,"about_ca_system_score_gemma":0.0002566452,"threshold_uncertainty_score":0.64160913},"labels":[],"label_agreement":null},{"id":"W1559820134","doi":"10.1109/iswcs.2005.1547647","title":"Joint Estimation of Channel Parameters for MIMO Communication Systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"MIMO; Multipath propagation; Computer science; Channel (broadcasting); Joint (building); Subspace topology; Communications system; Multi-user MIMO; Delay spread; Electronic engineering; Control theory (sociology); Algorithm; Telecommunications; Engineering","score_opus":0.04037797355419205,"score_gpt":0.2869664014624398,"score_spread":0.24658842790824775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1559820134","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":[0.0041953065,0.000055187607,0.99275583,0.00056116475,0.000081861705,0.00043069912,0.0000023244736,0.00023240139,0.0016852355],"genre_scores_gemma":[0.5372769,0.0000056404874,0.4625808,0.000019242982,0.000003282628,0.000056423047,0.0000032433672,0.0000029015844,0.000051535964],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992264,0.000043064607,0.00038325132,0.000120031145,0.00014671411,0.00008055606],"domain_scores_gemma":[0.99884874,0.00014237434,0.00027670013,0.00050729705,0.00019951127,0.000025368925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043305018,0.00006546689,0.0001486074,0.000144804,0.000039361894,0.0000344371,0.00037760704,0.00004072692,0.0000019440042],"category_scores_gemma":[0.000117241754,0.00006205464,0.000052246865,0.00019317878,0.000034627603,0.00052448636,0.00006094083,0.000029680295,0.000004067543],"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":[0.00000993998,0.00021693786,0.000017809152,0.00023206738,0.00003536549,4.1239367e-8,0.001187853,0.18178615,0.002652593,0.62216425,0.004268314,0.18742867],"study_design_scores_gemma":[0.00009748734,0.000056728783,0.00008296147,0.000057866353,0.0000038084238,0.0000016074334,0.00001677197,0.87160456,0.123316,0.004556357,0.00014920227,0.000056677916],"about_ca_topic_score_codex":0.00013359799,"about_ca_topic_score_gemma":0.0000044702506,"teacher_disagreement_score":0.6898184,"about_ca_system_score_codex":0.000039533334,"about_ca_system_score_gemma":0.000023665925,"threshold_uncertainty_score":0.2530515},"labels":[],"label_agreement":null},{"id":"W1565873823","doi":"10.1109/acssc.2000.910915","title":"High-resolution sensor array processing in the presence of multiple wideband chirp signals","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Chirp; Wideband; Polynomial; Estimator; Algorithm; Computer science; Phase (matter); Beamforming; Estimation theory; Mathematics; Control theory (sociology); Electronic engineering; Telecommunications; Engineering; Statistics; Mathematical analysis; Physics; Artificial intelligence","score_opus":0.028470612357972824,"score_gpt":0.25817176285048404,"score_spread":0.22970115049251122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1565873823","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":[0.03769761,0.00008419604,0.9574064,0.000653812,0.000052616862,0.00026071622,9.839936e-7,0.00014880371,0.003694879],"genre_scores_gemma":[0.84596115,0.000007157686,0.15384026,0.000050987535,0.000009835701,0.000016418522,2.9419175e-7,0.0000029447235,0.00011097485],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990158,0.00010086749,0.0002920483,0.00017688636,0.00029197035,0.00012240285],"domain_scores_gemma":[0.99920094,0.00020838667,0.00016469767,0.00030015394,0.0001073159,0.00001847685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003871754,0.00007578745,0.00012570544,0.00011715352,0.00004942834,0.00004693838,0.0004977794,0.000036459463,0.00002397345],"category_scores_gemma":[0.00027230263,0.000053106713,0.00002937874,0.0005275517,0.0000655729,0.00054752955,0.00003803703,0.00006926339,0.0000045059014],"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":[0.00003305826,0.001382398,0.010679656,0.00043194604,0.000022023352,0.000009015725,0.017883528,0.019013343,0.5808519,0.0347605,0.007445815,0.3274868],"study_design_scores_gemma":[0.00019484936,0.00007367826,0.0050673946,0.00011342104,0.0000027627082,0.0000066551047,0.0000547911,0.44449982,0.5464208,0.003294355,0.00016009308,0.00011138429],"about_ca_topic_score_codex":0.0002506371,"about_ca_topic_score_gemma":0.000024870229,"teacher_disagreement_score":0.80826354,"about_ca_system_score_codex":0.00001405992,"about_ca_system_score_gemma":0.000014263396,"threshold_uncertainty_score":0.2165629},"labels":[],"label_agreement":null},{"id":"W1574772950","doi":"10.1109/icdsp.2002.1027882","title":"A multitarget beamforming algorithm based on a one-step prediction Kalman filter","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Kalman filter; Algorithm; Recursive least squares filter; Fading; Computer science; Beamforming; Robustness (evolution); Additive white Gaussian noise; Block (permutation group theory); Adaptive beamformer; Least-squares function approximation; Wireless; Adaptive filter; Control theory (sociology); Mathematics; Estimator; White noise; Telecommunications; Artificial intelligence; Decoding methods; Statistics","score_opus":0.01726490520109532,"score_gpt":0.2474492018360279,"score_spread":0.23018429663493256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1574772950","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":[0.00033865593,0.0000037631905,0.96857625,0.00011731944,0.00023419064,0.00022520022,0.0000051372754,0.000660684,0.029838813],"genre_scores_gemma":[0.12073508,0.0000011535407,0.8786018,0.00026639146,0.000015208973,0.00004190468,0.0000041271396,0.000008642759,0.00032569023],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988986,0.000059212027,0.00026222545,0.00027714286,0.00033532816,0.00016745052],"domain_scores_gemma":[0.9992144,0.000087271,0.0000944433,0.00042852442,0.000110448746,0.00006492741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033128512,0.000115653886,0.00012811234,0.00023072469,0.00007776567,0.00004726203,0.0002672429,0.00006262685,0.00009590924],"category_scores_gemma":[0.00011419706,0.00010938545,0.000064549466,0.00035715397,0.000024252626,0.00051188486,0.000031669893,0.00008961223,0.00002825342],"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":[0.000022654203,0.0016996781,0.0019005657,0.0001237442,0.00007351521,0.00000847922,0.00073478685,0.0066447654,0.005929113,0.18853436,0.011771259,0.7825571],"study_design_scores_gemma":[0.00023723733,0.00019403026,0.00057626393,0.000044882774,0.0000037475006,0.000003025101,0.0000062345384,0.9007854,0.09234572,0.001173594,0.004514836,0.00011503406],"about_ca_topic_score_codex":0.000047702782,"about_ca_topic_score_gemma":0.0000030730575,"teacher_disagreement_score":0.8941406,"about_ca_system_score_codex":0.000060661965,"about_ca_system_score_gemma":0.000051402687,"threshold_uncertainty_score":0.44606093},"labels":[],"label_agreement":null},{"id":"W1591653913","doi":"10.1109/icosp.2000.894525","title":"Multiple-array based detection in correlated noise fields","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Noise (video); Computer science; Noise measurement; Detection theory; Electronic engineering; Algorithm; Artificial intelligence; Noise reduction; Telecommunications; Engineering; Detector","score_opus":0.016846305601971655,"score_gpt":0.2292901560293737,"score_spread":0.21244385042740205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1591653913","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":[0.015177831,0.000009359992,0.97325224,0.00024728678,0.00022004118,0.00013858036,2.7527312e-7,0.00052129437,0.010433098],"genre_scores_gemma":[0.9270794,0.000002764704,0.07249995,0.00013358219,0.000005447464,0.00001784327,3.9921983e-7,0.00000420004,0.00025642093],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992759,0.000044649318,0.00023269183,0.00018642367,0.00014650353,0.00011381219],"domain_scores_gemma":[0.9993979,0.00014039085,0.00006938828,0.00029213092,0.000065045875,0.000035161363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014000843,0.00007594855,0.00009838828,0.00023511885,0.00002980547,0.000028934559,0.00026119256,0.00008770737,0.00015770018],"category_scores_gemma":[0.00016995687,0.00007387607,0.000038057085,0.000607417,0.000018409955,0.00033702463,0.000024962816,0.0001078393,0.00004506062],"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":[0.000029411487,0.000817575,0.015169722,0.000068703426,0.000018198249,0.000015602678,0.0013022411,0.009290698,0.086246155,0.0044542784,0.0028291054,0.8797583],"study_design_scores_gemma":[0.00019820847,0.000048249934,0.002408217,0.000013971793,8.192197e-7,0.0000018090099,0.0000022724525,0.69894326,0.29782483,0.00029532422,0.00019332868,0.000069694564],"about_ca_topic_score_codex":0.00024098226,"about_ca_topic_score_gemma":0.00014735253,"teacher_disagreement_score":0.91190153,"about_ca_system_score_codex":0.000038585873,"about_ca_system_score_gemma":0.000009114402,"threshold_uncertainty_score":0.30125788},"labels":[],"label_agreement":null},{"id":"W1593533099","doi":"10.1109/vetecs.2004.1390546","title":"Joint domain localized adaptive processing for CDMA systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Telecommunications link; Code division multiple access; Beamforming; Single antenna interference cancellation; Joint (building); Interference (communication); Multiuser detection; Space-division multiple access; Adaptive beamformer; Algorithm; Computer engineering; Real-time computing; Electronic engineering; Computer network; Telecommunications; Decoding methods; Engineering; Channel (broadcasting)","score_opus":0.03287781838050877,"score_gpt":0.27966530495975933,"score_spread":0.24678748657925056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1593533099","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":[0.00040380296,0.000076793855,0.9880713,0.00037365552,0.0001009212,0.00043216677,0.0000011921971,0.00059905177,0.009941067],"genre_scores_gemma":[0.36352143,9.486371e-7,0.63591844,0.00006604728,0.000034453966,0.00008961196,4.848197e-7,0.0000056082245,0.00036295614],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913543,0.000030659852,0.00029718856,0.00021059872,0.00018530014,0.00014084503],"domain_scores_gemma":[0.9993212,0.000050731487,0.0001496109,0.00022046814,0.00021284471,0.000045146466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003595275,0.00008721955,0.00016498848,0.000105869214,0.000067121684,0.00009637891,0.00028317596,0.000042958833,0.000004997823],"category_scores_gemma":[0.000038790666,0.0000739828,0.000051092004,0.00022956551,0.000032115015,0.00056699506,0.000057726644,0.000035792073,0.000008224617],"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":[0.00001999036,0.00011675277,0.000016824742,0.00014204383,0.000018357725,6.9375625e-7,0.0009100742,0.0016422716,0.0034102108,0.6677378,0.0052666077,0.32071838],"study_design_scores_gemma":[0.0002973018,0.000111937625,0.00002567998,0.00010398437,0.0000028553818,0.000009223929,0.00006383862,0.90310276,0.0749641,0.011160119,0.010013774,0.00014444023],"about_ca_topic_score_codex":0.000037914884,"about_ca_topic_score_gemma":0.0000046231194,"teacher_disagreement_score":0.90146047,"about_ca_system_score_codex":0.00006728602,"about_ca_system_score_gemma":0.000070408925,"threshold_uncertainty_score":0.3016931},"labels":[],"label_agreement":null},{"id":"W1597665604","doi":"10.1109/sam.2002.1190990","title":"Robust adaptive beamforming for general-rank signal models using worst-case performance optimization","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Adaptive beamformer; Robustness (evolution); Beamforming; Computer science; Covariance matrix; Signal subspace; Diagonal; Rank (graph theory); Algorithm; SIGNAL (programming language); Signal processing; Subspace topology; Control theory (sociology); Mathematical optimization; Mathematics; Artificial intelligence; Digital signal processing; Noise (video); Telecommunications","score_opus":0.08878996660869783,"score_gpt":0.2666056991209507,"score_spread":0.1778157325122529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1597665604","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":[0.0058682007,0.000014138194,0.98942477,0.000013254785,0.00010879211,0.0003829958,0.0000019476324,0.0002575624,0.0039283284],"genre_scores_gemma":[0.2616292,0.0000050385393,0.73817027,0.00003861424,0.000014349057,0.000029603672,0.0000013746137,0.000010106798,0.00010143001],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900305,0.000036354722,0.0003114341,0.00026947897,0.00017745033,0.000202208],"domain_scores_gemma":[0.99918103,0.000066036104,0.00016209543,0.00024234889,0.00029218674,0.000056321678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003617064,0.00013221314,0.00015138109,0.00018309202,0.00020092375,0.000071188086,0.00021478887,0.000061682345,0.000021870073],"category_scores_gemma":[0.000028929411,0.00012946298,0.000060920545,0.0004113106,0.000030168463,0.0018733307,0.000044912453,0.00005553939,6.6507505e-7],"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":[0.000004865336,0.000023334664,0.0000064812284,0.00001292732,0.00000695971,0.0000015270869,0.00011755346,0.9356556,0.00017972387,0.058891453,0.000027902875,0.0050716484],"study_design_scores_gemma":[0.00016646889,0.00008438166,5.401648e-7,0.000028424192,0.000008290514,0.00012161088,0.00001885637,0.9488294,0.047703546,0.0028675206,0.000017912826,0.00015306502],"about_ca_topic_score_codex":0.000041596926,"about_ca_topic_score_gemma":0.0000022487482,"teacher_disagreement_score":0.255761,"about_ca_system_score_codex":0.00008122437,"about_ca_system_score_gemma":0.00009288867,"threshold_uncertainty_score":0.52793473},"labels":[],"label_agreement":null},{"id":"W1601377232","doi":"10.1109/pacrim.2003.1235754","title":"A closed-form analytical model characterizing fading envelope correlation across a wideband array","year":2004,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Fading; Wideband; Envelope (radar); Correlation function (quantum field theory); Covariance; Covariance matrix; Antenna array; Antenna (radio); Correlation; Algorithm; Closed-form expression; Spatial correlation; Computer science; Electronic engineering; Mathematics; Statistics; Telecommunications; Mathematical analysis; Radar; Spectral density; Engineering; Decoding methods; Geometry","score_opus":0.02693967596181206,"score_gpt":0.29694751632574456,"score_spread":0.2700078403639325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1601377232","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":[0.0822952,0.000003136931,0.90989935,0.00048391454,0.00010928227,0.00013889515,0.0000016478161,0.00047387707,0.0065946714],"genre_scores_gemma":[0.74961156,0.000003522307,0.24997802,0.00016583879,0.000013536407,0.000010557948,0.0000026651742,0.000007124357,0.00020715116],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988093,0.000012960482,0.0003679402,0.00028905133,0.00028223527,0.00023852762],"domain_scores_gemma":[0.9992796,0.000048072383,0.00014629675,0.0003213815,0.00012490351,0.000079713405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032509936,0.00012821016,0.00018173047,0.000121561636,0.00012837653,0.00014784618,0.00037563063,0.00008041488,0.000008923927],"category_scores_gemma":[0.000098718105,0.00011898587,0.00007006402,0.00045309064,0.00004965029,0.0013511827,0.00009670253,0.000120078555,0.00002657343],"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":[0.0000340309,0.0002942545,0.0035141937,0.000081160324,0.000065183805,0.0000090737285,0.013070195,0.03402207,0.106014885,0.7099317,0.00021721885,0.13274607],"study_design_scores_gemma":[0.00030811873,0.00005382227,0.004133484,0.00007893275,0.000005418153,0.000014019345,0.000023895991,0.80280447,0.15958257,0.032667406,0.00010781707,0.00022005205],"about_ca_topic_score_codex":0.0000520969,"about_ca_topic_score_gemma":0.000010219016,"teacher_disagreement_score":0.7687824,"about_ca_system_score_codex":0.00013048427,"about_ca_system_score_gemma":0.00010005698,"threshold_uncertainty_score":0.48521027},"labels":[],"label_agreement":null},{"id":"W1606321935","doi":"10.1109/sam.2002.1191029","title":"Direction of arrival estimation in sparse arrays in the presence of unknown colored block-correlated noise fields","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Direction of arrival; Estimator; Noise (video); Algorithm; Identifiability; Covariance matrix; Computer science; Mathematics; Colors of noise; Parametric statistics; Noise reduction; Statistics; Artificial intelligence; Telecommunications","score_opus":0.013863708839741714,"score_gpt":0.25586046110625804,"score_spread":0.24199675226651632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1606321935","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":[0.35851067,0.000020477826,0.6286829,0.00017259276,0.00020623032,0.00045691317,7.919897e-7,0.00009570093,0.011853719],"genre_scores_gemma":[0.9167245,0.000010384512,0.08316117,0.000017274528,0.0000021035019,0.000028448962,8.332518e-7,0.0000036024044,0.000051679603],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99860233,0.00023368261,0.0005480675,0.00019725627,0.00029396077,0.0001246971],"domain_scores_gemma":[0.99883586,0.00034687037,0.0002652133,0.00039587158,0.00013565124,0.000020535841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080154167,0.00009860718,0.00020333227,0.000291121,0.00002171714,0.0000159648,0.00042152786,0.00009751558,0.000014493759],"category_scores_gemma":[0.00069064216,0.000079999445,0.000045205634,0.0012762598,0.000072575895,0.00038909496,0.000037595382,0.00013592384,0.0000015737987],"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":[0.0001427524,0.0023196037,0.025849562,0.00032189442,0.000051670922,0.000013238538,0.015217003,0.33709362,0.052867133,0.50750446,0.0012572884,0.057361785],"study_design_scores_gemma":[0.0003665932,0.00017883621,0.016068125,0.00013162712,0.000006305149,0.00000957229,0.000072620795,0.6401418,0.33075607,0.012095437,0.000052991687,0.00012005504],"about_ca_topic_score_codex":0.00058039284,"about_ca_topic_score_gemma":0.00013960736,"teacher_disagreement_score":0.55821383,"about_ca_system_score_codex":0.000033264474,"about_ca_system_score_gemma":0.00007319022,"threshold_uncertainty_score":0.32622826},"labels":[],"label_agreement":null},{"id":"W1606440527","doi":"10.1109/wimob.2005.1512809","title":"Cramer-Rao bounds for different vector-hydrophone's configurations located near a pressure-release boundary","year":2006,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Hydrophone; Acoustics; Underwater; Boundary (topology); Sound pressure; Underwater acoustics; Geology; Computer science; Physics; Mathematics; Mathematical analysis","score_opus":0.008720051941394764,"score_gpt":0.24535914327983063,"score_spread":0.23663909133843586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1606440527","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":[0.011400755,0.00009925197,0.9797367,0.0007434483,0.00034182396,0.0006331977,0.000022627624,0.0009884381,0.0060337577],"genre_scores_gemma":[0.9310699,0.000002769875,0.066470236,0.00012330442,0.00004980204,0.00018580686,0.000036004112,0.00001777069,0.0020443976],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985718,0.0000514109,0.00044459218,0.00037447945,0.0002977131,0.00025997133],"domain_scores_gemma":[0.9986885,0.00015930436,0.00018439238,0.00057192857,0.00031280625,0.00008304541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012487614,0.0001927471,0.0002501766,0.00013179243,0.0002944557,0.00046257745,0.00051146693,0.00008761292,0.000090501395],"category_scores_gemma":[0.000075147545,0.00017445169,0.00012233286,0.00038735857,0.00017398299,0.00051578326,0.00007930581,0.00009253865,0.00002202202],"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":[0.000110763234,0.0021096126,0.0006384622,0.0003964055,0.0002505822,0.000008067006,0.0007337166,0.0075406004,0.11372667,0.69684404,0.13936786,0.038273245],"study_design_scores_gemma":[0.00054861704,0.00027554153,0.00395173,0.000040403753,0.0000382977,0.000007889274,0.0000063011908,0.68037003,0.24015729,0.027608804,0.046636056,0.00035901248],"about_ca_topic_score_codex":0.0010025923,"about_ca_topic_score_gemma":0.00007209472,"teacher_disagreement_score":0.91966915,"about_ca_system_score_codex":0.00004962624,"about_ca_system_score_gemma":0.00018702036,"threshold_uncertainty_score":0.7113933},"labels":[],"label_agreement":null},{"id":"W1606569297","doi":"10.1109/acssc.2000.910969","title":"Linearly constrained minimum variance beamformers, synthetic aperture magnetometry, and MUSIC in MEG applications","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Coquitlam College","funders":"","keywords":"Orientation (vector space); Magnetoencephalography; Subspace topology; Minimum-variance unbiased estimator; Computer science; Point (geometry); Variance (accounting); Uncorrelated; Algorithm; Interference (communication); Pattern recognition (psychology); Artificial intelligence; Speech recognition; Mathematics; Statistics; Neuroscience; Telecommunications","score_opus":0.015062500290060123,"score_gpt":0.2287495581805207,"score_spread":0.21368705789046058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1606569297","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":[0.0014032774,0.00018911326,0.9648364,0.0012320569,0.00004631826,0.0003819659,0.0000046803475,0.00029900292,0.031607155],"genre_scores_gemma":[0.68771505,0.00004131086,0.31111485,0.00031925493,0.000012449808,0.00009057011,0.0000013458341,0.0000066647485,0.0006985239],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991051,0.000026466983,0.00026692243,0.00028952587,0.00015983554,0.00015214382],"domain_scores_gemma":[0.9991863,0.00024342691,0.00008324161,0.00035886923,0.000064808126,0.000063359286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015679108,0.00010804843,0.00015398904,0.00026411985,0.000045643075,0.000065947126,0.0003497325,0.00007119783,0.00016010304],"category_scores_gemma":[0.00009250946,0.00010209551,0.000027558961,0.0008885929,0.00011319905,0.00035809499,0.00007776421,0.000093073206,0.000024036985],"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":[0.000005358381,0.0005208448,0.0012134814,0.00015838852,0.000028007466,0.000006306932,0.001389156,0.000045153884,0.012274304,0.26135054,0.0034249993,0.71958345],"study_design_scores_gemma":[0.0009122153,0.00034022966,0.0048463084,0.0001369278,0.000019635709,0.00013307684,0.000105702275,0.9328848,0.009999797,0.011373749,0.038498484,0.0007490506],"about_ca_topic_score_codex":0.00003975734,"about_ca_topic_score_gemma":0.000012879089,"teacher_disagreement_score":0.9328397,"about_ca_system_score_codex":0.000021478536,"about_ca_system_score_gemma":0.000018411172,"threshold_uncertainty_score":0.4163334},"labels":[],"label_agreement":null},{"id":"W1642281920","doi":"10.1109/icassp.1989.266994","title":"A systolic MUSIC system for VLSI implementation","year":2003,"lang":"en","type":"article","venue":"International Conference on Acoustics, Speech, and Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Technical University of Nova Scotia","funders":"","keywords":"Computer science; Interval (graph theory); Singular value decomposition; Very-large-scale integration; Noise (video); Computation; Block (permutation group theory); Value (mathematics); Decomposition; Algorithm; Sampling (signal processing); Speech recognition; Mathematics; Artificial intelligence; Embedded system","score_opus":0.047965473141386265,"score_gpt":0.3277990828883787,"score_spread":0.27983360974699245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1642281920","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":[0.007687647,0.000027177843,0.98489565,0.00013025051,0.00032654442,0.00027822552,0.000017308736,0.00018176013,0.0064554294],"genre_scores_gemma":[0.9027037,0.000007890462,0.097025156,0.00007984943,0.000051970303,0.000041944666,0.000008266155,0.000009431595,0.00007181489],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987673,0.000038155624,0.00037162035,0.00030795948,0.00035681183,0.00015813368],"domain_scores_gemma":[0.99873114,0.0000838049,0.00028538998,0.00011892428,0.00072120177,0.00005956498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034898246,0.00014150591,0.00016973246,0.00022049808,0.00013369722,0.0002828517,0.00033181018,0.000056454115,0.000034758625],"category_scores_gemma":[0.00007883458,0.00013960605,0.000041306674,0.00013048177,0.000052127238,0.00045244006,0.00003676301,0.000081721264,0.0000032974203],"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":[0.00002392844,0.0000746499,0.000118292584,0.0004186061,0.00003390907,0.000005214997,0.00059735874,0.00014939615,0.036802422,0.63729876,0.0002446483,0.32423282],"study_design_scores_gemma":[0.0010073107,0.00035770555,0.0003059968,0.0007848682,0.00004916008,0.00010346789,0.0015034735,0.81366307,0.13392608,0.047295894,0.00053724775,0.00046569668],"about_ca_topic_score_codex":0.000023420485,"about_ca_topic_score_gemma":0.0000037625946,"teacher_disagreement_score":0.895016,"about_ca_system_score_codex":0.00009845876,"about_ca_system_score_gemma":0.0001861565,"threshold_uncertainty_score":0.56929696},"labels":[],"label_agreement":null},{"id":"W1680304476","doi":"10.1109/nrc.2002.999747","title":"Theoretical analysis of small sample size behaviour of eigenvector projection technique applied to STAP","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Subspace topology; Clutter; Dimension (graph theory); Eigenvalues and eigenvectors; Projection (relational algebra); Estimator; Sample size determination; Rank (graph theory); Space-time adaptive processing; Interference (communication); Signal subspace; Algorithm; Sample (material); Noise (video); Mathematics; Signal-to-noise ratio (imaging); Computer science; Mathematical optimization; Statistics; Artificial intelligence; Radar; Telecommunications; Combinatorics; Physics","score_opus":0.014237293104500864,"score_gpt":0.2686100172845983,"score_spread":0.2543727241800975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1680304476","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":[0.025940545,0.0000015612318,0.96475697,0.000031327796,0.000031619053,0.0005725792,0.000010376043,0.00021883777,0.008436218],"genre_scores_gemma":[0.5380587,7.167815e-7,0.4618373,0.0000148563495,0.000001484736,0.00006686058,9.4003474e-7,0.0000042059764,0.000014927023],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99872506,0.000084286505,0.00048514767,0.00028686196,0.0002799009,0.00013876201],"domain_scores_gemma":[0.99852514,0.0004184309,0.00020152483,0.0005181701,0.000275711,0.000061006318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063195295,0.00011477251,0.00034557685,0.00053650344,0.00002575866,0.00001590034,0.00037811653,0.00008087605,0.00026072492],"category_scores_gemma":[0.0006037703,0.000103562685,0.0001341291,0.0024177204,0.000093523304,0.00008440041,0.000078937934,0.00006355362,0.0000011636223],"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":[0.000008918228,0.00016769824,0.0025559678,0.000018611097,0.000071374976,1.2193163e-7,0.00019379069,0.000120208264,0.0418238,0.95199525,0.00002677873,0.0030174477],"study_design_scores_gemma":[0.000061958104,0.00017018807,0.005188554,0.000009840294,0.00010299498,8.940446e-7,0.000026981797,0.004440913,0.96061975,0.029240511,0.000020155265,0.00011728723],"about_ca_topic_score_codex":0.0003575461,"about_ca_topic_score_gemma":0.00004233111,"teacher_disagreement_score":0.92275476,"about_ca_system_score_codex":0.000043285374,"about_ca_system_score_gemma":0.00007826446,"threshold_uncertainty_score":0.42231637},"labels":[],"label_agreement":null},{"id":"W1761004645","doi":"10.1002/dac.2568","title":"Hybrid MUSIC Dolph–Chebyshev algorithm for a smart antenna system","year":2013,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Smart antenna; Computer science; Chebyshev filter; Antenna array; Antenna (radio); Sensor array; Gate array; Beamforming; Field-programmable gate array; Electronic engineering; Algorithm; Computer hardware; Telecommunications; Directional antenna; Engineering","score_opus":0.024975566529892634,"score_gpt":0.2838749265330155,"score_spread":0.25889936000312286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1761004645","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":[0.0034052483,0.00063834636,0.9914169,0.000774803,0.0018628258,0.00048410599,0.000011238199,0.00012431438,0.0012822631],"genre_scores_gemma":[0.8156779,0.000068097375,0.1838575,0.00005556394,0.00013121848,0.000093523195,0.0000070356796,0.000012671726,0.000096490934],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99753076,0.00023309301,0.0012312544,0.00014308837,0.0007286245,0.00013320682],"domain_scores_gemma":[0.9929188,0.00044166797,0.0016787578,0.00069633056,0.004178075,0.0000863725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012859125,0.00013746713,0.00033238195,0.00047977758,0.00007972178,0.00036267185,0.0029821452,0.00005542584,0.000009422446],"category_scores_gemma":[0.00016304106,0.00012436183,0.00019534127,0.00018293962,0.000058662754,0.0014392602,0.00022902088,0.00016068344,0.000024062789],"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":[0.00006224732,0.00075646286,0.0008795858,0.00019319887,0.0013122102,0.000019439834,0.002476132,0.0012577279,0.010449696,0.31492355,0.032862037,0.6348077],"study_design_scores_gemma":[0.001078707,0.00020526056,0.0009516814,0.0013381059,0.000026859303,0.0008652852,0.00046658766,0.96429616,0.007922855,0.0049544116,0.017617838,0.0002762739],"about_ca_topic_score_codex":0.00027261896,"about_ca_topic_score_gemma":0.0000013673919,"teacher_disagreement_score":0.9630384,"about_ca_system_score_codex":0.00022704434,"about_ca_system_score_gemma":0.00012778508,"threshold_uncertainty_score":0.5541617},"labels":[],"label_agreement":null},{"id":"W1802852998","doi":"10.1109/ssap.1994.572473","title":"An Application Of A Statistical Array Processing Scheme For Low-angle Tracking","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Université Laval","funders":"","keywords":"Computer science; Scheme (mathematics); Tracking (education); Mathematics","score_opus":0.017540414182509748,"score_gpt":0.3279532566894649,"score_spread":0.31041284250695517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1802852998","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":[0.0030192242,0.0000072987987,0.99528056,0.000122255,0.000012434948,0.00023000376,0.0000028586871,0.0002434471,0.0010819122],"genre_scores_gemma":[0.49132255,1.8329644e-7,0.50859797,0.000021859467,0.000012761325,0.00003131735,0.0000023386701,0.0000030173837,0.000008001853],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999331,0.000011961195,0.00024584008,0.00017718434,0.00014351467,0.00009052861],"domain_scores_gemma":[0.9993443,0.00006134231,0.00013073378,0.00021571165,0.00021273864,0.000035213518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021991902,0.000055885397,0.00010300992,0.00007004602,0.00003699187,0.000038279395,0.0002670473,0.00003168945,0.0000088060315],"category_scores_gemma":[0.00005780604,0.000053314714,0.000020963376,0.00018590163,0.000032558768,0.0006641195,0.000013238731,0.000028776256,0.0000019734678],"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":[0.000003885978,0.00013945991,0.00011645288,0.000071770635,0.0000021470617,2.3520869e-8,0.00021844027,0.000094161274,0.10743357,0.12266627,0.000056690333,0.7691971],"study_design_scores_gemma":[0.000068952235,0.00005052987,0.0003280452,0.000015289817,0.0000018645264,8.672877e-7,0.000007750789,0.49894568,0.49422708,0.006030885,0.00027094904,0.000052107036],"about_ca_topic_score_codex":0.0000126378145,"about_ca_topic_score_gemma":0.0000057397033,"teacher_disagreement_score":0.769145,"about_ca_system_score_codex":0.00002191855,"about_ca_system_score_gemma":0.00004679399,"threshold_uncertainty_score":0.2174111},"labels":[],"label_agreement":null},{"id":"W1813679446","doi":"10.1109/siu.2006.1659679","title":"Applications of Basis Selection Algorithms in Communication Problems","year":2006,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Matching pursuit; Algorithm; Basis pursuit; Set (abstract data type); Basis (linear algebra); Channel (broadcasting); Computer science; Selection (genetic algorithm); Matching (statistics); Mathematics; Mathematical optimization; Compressed sensing; Artificial intelligence; Statistics","score_opus":0.009453114979551765,"score_gpt":0.25633696304075604,"score_spread":0.24688384806120428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1813679446","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":[0.0013193978,0.000031614516,0.9817765,0.000203985,0.000010310581,0.00029988104,7.5810374e-7,0.00021059297,0.016146977],"genre_scores_gemma":[0.6058481,0.000010444608,0.393878,0.000007607817,0.0000036188987,0.0001255574,0.0000037156353,0.000002734572,0.00012022256],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931073,0.000044212487,0.00031978288,0.00012461843,0.00013342513,0.000067256326],"domain_scores_gemma":[0.9992629,0.000059395905,0.00015696533,0.00034154003,0.00016808276,0.000011059271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002566382,0.000050670118,0.00009311439,0.00023137148,0.000030584477,0.000016582011,0.0003677808,0.0000386267,0.000009502428],"category_scores_gemma":[0.000011076273,0.00005222493,0.000024639274,0.0010318463,0.000033375723,0.00033389317,0.000059650527,0.00005041552,0.0000033554047],"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":[0.0000017320649,0.00056357513,0.012418371,0.000072307645,0.000007412884,4.3765766e-8,0.0002479183,0.003492253,0.009014087,0.62001175,0.0010558029,0.35311475],"study_design_scores_gemma":[0.0002491496,0.00007231014,0.02958696,0.00006260139,0.0000050352296,0.0000046885266,0.000017545792,0.46296236,0.38407323,0.11968757,0.0030947435,0.00018381496],"about_ca_topic_score_codex":0.0020361484,"about_ca_topic_score_gemma":0.00025217255,"teacher_disagreement_score":0.6045287,"about_ca_system_score_codex":0.000040613617,"about_ca_system_score_gemma":0.000029500632,"threshold_uncertainty_score":0.30780607},"labels":[],"label_agreement":null},{"id":"W1841006872","doi":"10.1109/ssap.1992.246894","title":"Optimal array signal processing in unknown noise environments via parametric approaches","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Weighting; Parametric statistics; Noise (video); Set (abstract data type); Computer science; Algorithm; Signal processing; Parametric model; Mathematics; Artificial intelligence; Statistics; Digital signal processing; Image (mathematics)","score_opus":0.03096048455392592,"score_gpt":0.24097238799429677,"score_spread":0.21001190344037085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1841006872","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":[0.011692795,0.00005281738,0.9729182,0.000038701994,0.00002877721,0.00017354234,1.4950884e-7,0.00013645735,0.01495854],"genre_scores_gemma":[0.5815353,0.0000019423103,0.4182766,0.000022751501,0.0000028893248,0.00002141198,3.8679812e-7,0.0000047141366,0.00013402659],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988389,0.000076482786,0.00029381382,0.00031410603,0.0002818786,0.00019483677],"domain_scores_gemma":[0.99952114,0.00004472745,0.000118333046,0.0002396216,0.000019817171,0.000056386016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038199613,0.00012210224,0.00015300402,0.00033805816,0.000043197586,0.000064669664,0.00036668358,0.000060350954,0.00003473957],"category_scores_gemma":[0.000057504727,0.0001136374,0.00003672439,0.0009984733,0.000055308454,0.0006477192,0.000044545195,0.000100883095,0.000017662067],"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":[0.000014344084,0.0016322973,0.01020682,0.00012356623,0.00002073663,0.000009988156,0.0012411218,0.03929279,0.032133423,0.05129063,0.00015695274,0.86387736],"study_design_scores_gemma":[0.0002938969,0.000107231,0.0032419066,0.0000343194,0.000004916216,0.000014966714,0.000029166293,0.38646173,0.60424554,0.004265756,0.0009876633,0.00031292782],"about_ca_topic_score_codex":0.000014820236,"about_ca_topic_score_gemma":0.000001033728,"teacher_disagreement_score":0.8635644,"about_ca_system_score_codex":0.0000675666,"about_ca_system_score_gemma":0.00004879491,"threshold_uncertainty_score":0.46339986},"labels":[],"label_agreement":null},{"id":"W1857608169","doi":"10.1109/ssp.2005.1628600","title":"Adaptive linear estimators, using biased cramer-RAO bound","year":2005,"lang":"en","type":"article","venue":"IEEE/SP 13th Workshop on Statistical Signal Processing, 2005","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Estimator; Mathematics; Singular value decomposition; Cramér–Rao bound; Applied mathematics; Upper and lower bounds; Estimation theory; Fisher information; Matrix (chemical analysis); Mathematical optimization; Statistics; Algorithm; Mathematical analysis","score_opus":0.046181362140935475,"score_gpt":0.3374801407416287,"score_spread":0.2912987786006932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1857608169","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":[0.0023651402,0.00016680572,0.9939186,0.00037340232,0.00019212216,0.00035265993,0.000049138827,0.00069517904,0.001886952],"genre_scores_gemma":[0.42773739,0.0000071324394,0.57133204,0.00042892326,0.00021420795,0.000024813633,0.000009378952,0.000041372645,0.00020476684],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99615115,0.00017511834,0.00092787447,0.0008834808,0.001081269,0.0007811107],"domain_scores_gemma":[0.99733114,0.0008089422,0.00052686577,0.0005050219,0.00040254596,0.00042550857],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005897654,0.0004798409,0.0005757258,0.00036117077,0.0003844753,0.00039939416,0.0008679943,0.00024108739,0.000326857],"category_scores_gemma":[0.00033468215,0.00046119158,0.00011036226,0.00095362565,0.00044549935,0.0010954161,0.0001197748,0.0005796551,0.00015392313],"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":[0.00022644468,0.0012609622,0.00008881098,0.00014464298,0.00007488544,0.00006891825,0.00054011965,0.04971095,0.0015006539,0.031150592,0.015316339,0.89991665],"study_design_scores_gemma":[0.00041678897,0.00021631291,0.000094744144,0.00050644606,0.00004003436,0.000025774852,0.0000186802,0.9761283,0.012158165,0.0059914845,0.0038528596,0.0005504466],"about_ca_topic_score_codex":0.000056045254,"about_ca_topic_score_gemma":0.0000137593515,"teacher_disagreement_score":0.9264173,"about_ca_system_score_codex":0.00031717957,"about_ca_system_score_gemma":0.0005647223,"threshold_uncertainty_score":0.999784},"labels":[],"label_agreement":null},{"id":"W1860423707","doi":"10.1109/icassp.1980.1171035","title":"An experimental study of the MEM applied to array antennas in the presence of multipath","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"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","keywords":"Multipath propagation; Uncorrelated; Wavenumber; Radar; Antenna array; Acoustics; Antenna (radio); Plane wave; Computer science; Physics; Optics; Mathematics; Telecommunications; Statistics","score_opus":0.023187816443965944,"score_gpt":0.31278996978724977,"score_spread":0.2896021533432838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1860423707","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":[0.9049285,0.000004688538,0.09091949,0.00012710632,0.0000379522,0.0007348393,5.233151e-7,0.00005318175,0.003193737],"genre_scores_gemma":[0.9500983,2.2322439e-7,0.049746554,0.000072370894,0.00000626777,0.000058024525,6.440116e-8,0.0000026396624,0.000015600977],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990991,0.00008906267,0.00025340499,0.0001616265,0.00031826794,0.000078552825],"domain_scores_gemma":[0.99912226,0.00006907322,0.00009910742,0.0006434948,0.000047427126,0.000018641516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003640708,0.00006373581,0.00011005106,0.00006751309,0.000026845013,0.000016297952,0.001178243,0.000015842366,0.000007090936],"category_scores_gemma":[0.000026174988,0.000036157355,0.000021761294,0.00042421985,0.0000394807,0.0002034828,0.00011436184,0.000044692202,0.0000011102662],"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":[0.000027386332,0.005245183,0.005764677,0.000010557084,0.000010396563,3.919678e-7,0.09926682,0.0019439922,0.85002464,0.020435518,0.00020823951,0.017062187],"study_design_scores_gemma":[0.00016840876,0.0002861284,0.011654546,0.000010448094,0.0000011686562,7.196425e-7,0.0034229702,0.010931485,0.9733441,0.000109949615,0.000020408688,0.000049708837],"about_ca_topic_score_codex":0.00024262194,"about_ca_topic_score_gemma":0.00010655604,"teacher_disagreement_score":0.12331941,"about_ca_system_score_codex":0.000014773943,"about_ca_system_score_gemma":0.000016787064,"threshold_uncertainty_score":0.21894883},"labels":[],"label_agreement":null},{"id":"W1867665577","doi":"10.1109/icassp.1982.1171473","title":"Simulation for testing array response","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Roads University","funders":"","keywords":"Beamforming; Computer science; Subroutine; Noise (video); Fortran; Algorithm; Star (game theory); SIGNAL (programming language); Signal processing; Mathematics; Computer hardware; Artificial intelligence; Digital signal processing","score_opus":0.05158814363020936,"score_gpt":0.33550387080782873,"score_spread":0.28391572717761937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1867665577","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":[0.0053369408,0.0000028440825,0.9897649,0.0005061599,0.000044363158,0.00017917847,4.2862263e-7,0.0005190879,0.0036460871],"genre_scores_gemma":[0.48279345,3.7962135e-8,0.51690006,0.00006113007,0.000014556259,0.000011199268,1.6727854e-7,0.0000020904806,0.00021726977],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951255,0.000028373992,0.00016628746,0.00012114293,0.000095873445,0.0000757776],"domain_scores_gemma":[0.99814576,0.0013854813,0.00007424596,0.00019263702,0.00018003843,0.000021835749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047642263,0.000044064644,0.000056241606,0.000086493405,0.0000447012,0.00003292369,0.00019031188,0.00002300407,0.000007436864],"category_scores_gemma":[0.0016117491,0.00004160708,0.000025227338,0.00023066584,0.000010499223,0.0004464282,0.000021010666,0.000019792706,0.000009309287],"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":[0.000103041646,0.0000787199,0.00023625686,0.000018600665,0.00000670254,1.5687938e-7,0.0004367855,0.17171067,0.086826935,0.03970544,0.0007949329,0.70008177],"study_design_scores_gemma":[0.00011422538,0.00005920257,0.0005896314,0.00000780897,9.2171217e-7,5.388678e-7,0.000001616538,0.8153915,0.17735662,0.003310908,0.0031175571,0.000049483835],"about_ca_topic_score_codex":0.0000045977117,"about_ca_topic_score_gemma":0.0000010058894,"teacher_disagreement_score":0.7000323,"about_ca_system_score_codex":0.000026549198,"about_ca_system_score_gemma":0.0000319681,"threshold_uncertainty_score":0.19295305},"labels":[],"label_agreement":null},{"id":"W1873267190","doi":"10.1109/pacrim.1993.407231","title":"Adaptive beamforming via two-dimensional cosine transform","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Discrete cosine transform; Algorithm; Adaptive beamformer; Computer science; Autocorrelation matrix; Signal processing; Beamforming; Convergence (economics); Domain (mathematical analysis); Autocorrelation; Set (abstract data type); Mathematics; Artificial intelligence; Digital signal processing; Telecommunications; Statistics; Mathematical analysis","score_opus":0.022053243815072326,"score_gpt":0.24670362653300862,"score_spread":0.2246503827179363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1873267190","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":[0.00097552885,0.000022653545,0.9457849,0.00053281453,0.000089855654,0.00013779067,9.843195e-7,0.00045755156,0.051997878],"genre_scores_gemma":[0.5804969,0.0000014606285,0.4187509,0.00015755497,0.000012107466,0.000009694896,6.1512907e-7,0.0000045729203,0.00056621124],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917805,0.000013874653,0.00022219357,0.00018241761,0.00026334726,0.00014009167],"domain_scores_gemma":[0.9994938,0.00006258055,0.00006153169,0.00021722243,0.000109394176,0.000055474164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012629981,0.00009255365,0.00011980407,0.00011943434,0.00006511403,0.000022558914,0.00029473798,0.000031012325,0.0002645406],"category_scores_gemma":[0.000011181037,0.00008148209,0.000054852102,0.00032575935,0.00004013859,0.00068089366,0.000048595677,0.00006516231,0.000059166538],"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":[0.0000085142465,0.00025589988,0.000029925523,0.000014677458,0.000031073574,0.0000055800315,0.00071744807,0.0017825975,0.0078118565,0.15996408,0.0045991447,0.8247792],"study_design_scores_gemma":[0.00019269052,0.00012611358,0.00004593071,0.000025288482,0.0000030002188,0.000026754484,0.000003721985,0.8065082,0.18070558,0.011704059,0.00053366454,0.00012504571],"about_ca_topic_score_codex":0.000074717114,"about_ca_topic_score_gemma":0.000008385041,"teacher_disagreement_score":0.82465416,"about_ca_system_score_codex":0.000035435787,"about_ca_system_score_gemma":0.0000120499635,"threshold_uncertainty_score":0.33227432},"labels":[],"label_agreement":null},{"id":"W1877480292","doi":"10.1109/vetecs.2004.1389015","title":"Comparative study of uplink and downlink beamforming algorithms in UTRA/TDD","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Telecommunications link; Beamforming; Computer science; WSDMA; Rake; Electronic engineering; Duplex (building); Smart antenna; Bit error rate; Algorithm; Rake receiver; Real-time computing; Computer network; Channel (broadcasting); Precoding; MIMO; Antenna (radio); Telecommunications; Multipath propagation; Engineering; Directional antenna","score_opus":0.03003558882162022,"score_gpt":0.32348430582048177,"score_spread":0.29344871699886155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1877480292","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":[0.4368659,0.000024930312,0.5583974,0.00010755259,0.00003588688,0.0003215473,3.8589732e-7,0.00012429775,0.004122086],"genre_scores_gemma":[0.6757479,0.0000033489298,0.3241795,0.000014300815,0.0000058978962,0.000010077007,2.3843847e-7,0.0000016985954,0.000037055284],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991894,0.000030148827,0.00034186273,0.00018683789,0.00015701835,0.00009474819],"domain_scores_gemma":[0.9994766,0.000086389264,0.000113199545,0.0002113011,0.00008164836,0.00003082581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026631303,0.000079951766,0.0002164359,0.0001938583,0.000025804633,0.00002165246,0.00025665486,0.000029241473,0.000008313964],"category_scores_gemma":[0.000013658943,0.00007089587,0.000016581627,0.00035852316,0.000036303034,0.0005162149,0.00012025802,0.00007197211,0.000002362711],"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":[0.000021508009,0.0028461153,0.012241667,0.00006116876,0.000068820664,0.000004003477,0.045467123,0.0027911607,0.0049532116,0.036337037,0.00034614382,0.89486206],"study_design_scores_gemma":[0.0008351933,0.0006329874,0.019404287,0.000050726732,0.0000063311795,0.0000068746212,0.0008583732,0.8070093,0.16841103,0.0023787003,0.00019329193,0.0002129207],"about_ca_topic_score_codex":0.00020112115,"about_ca_topic_score_gemma":0.000100707104,"teacher_disagreement_score":0.89464915,"about_ca_system_score_codex":0.000022963943,"about_ca_system_score_gemma":0.000021216529,"threshold_uncertainty_score":0.28910497},"labels":[],"label_agreement":null},{"id":"W1893886650","doi":"10.1109/icassp.1981.1171369","title":"An adaptive interference canceller using Kalman filtering","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Beamwidth; Interference (communication); Kalman filter; Computer science; Convergence (economics); Single antenna interference cancellation; SIGNAL (programming language); Antenna (radio); Adaptive filter; Algorithm; Process (computing); Control theory (sociology); Telecommunications; Artificial intelligence; Decoding methods","score_opus":0.0461417763042081,"score_gpt":0.31219880013459694,"score_spread":0.2660570238303889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1893886650","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":[0.031291023,0.000009010236,0.9580105,0.000056651745,0.000074719974,0.000064265645,5.155807e-7,0.0003483498,0.010144994],"genre_scores_gemma":[0.5634314,0.0000012400882,0.4364241,0.000049487655,0.000017337714,0.0000028799655,1.1718256e-7,0.0000028839358,0.000070573005],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993702,0.000025928357,0.00017075505,0.00020086356,0.00011545987,0.00011677644],"domain_scores_gemma":[0.9995008,0.00002075346,0.00007232862,0.00026909565,0.00008789498,0.00004912062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010772576,0.00007699103,0.00009166544,0.00009832651,0.000043738008,0.00005097404,0.00048304512,0.000026406895,0.000084545274],"category_scores_gemma":[0.0000096497,0.000073429,0.000023252202,0.00018979925,0.000028579596,0.0010316885,0.00010766206,0.000053145322,0.000010754409],"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":[0.00001614921,0.00017802832,0.00034868735,0.000019006146,0.00002215459,0.0000029652676,0.0026119538,0.012349786,0.19159365,0.1272474,0.00060929894,0.6650009],"study_design_scores_gemma":[0.000033845263,0.00007846823,0.00023473376,0.000026348067,0.0000011135012,0.000004414741,0.000015726811,0.69027615,0.30822885,0.0008019886,0.00021325993,0.00008510934],"about_ca_topic_score_codex":0.00032472514,"about_ca_topic_score_gemma":0.00006807376,"teacher_disagreement_score":0.67792636,"about_ca_system_score_codex":0.00006413528,"about_ca_system_score_gemma":0.00003939938,"threshold_uncertainty_score":0.29943478},"labels":[],"label_agreement":null},{"id":"W1907083912","doi":"10.1109/spect.1988.206212","title":"Spectrum and flat spectral line representation: geometric approach","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Representation (politics); Spectrum (functional analysis); Uncorrelated; Spectral line; Line (geometry); Noise (video); Spectral resolution; Transformation (genetics); Resolution (logic); Matrix representation; Matrix (chemical analysis); Mathematics; Computer science; Artificial intelligence; Physics; Image (mathematics); Geometry; Statistics","score_opus":0.026556548583794835,"score_gpt":0.27558013807690473,"score_spread":0.2490235894931099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1907083912","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":[0.008261054,0.000060339677,0.88749254,0.00021377353,0.00009430335,0.00012767373,2.7067517e-7,0.00029255118,0.10345748],"genre_scores_gemma":[0.5606916,0.000018202787,0.43840966,0.0000338055,0.000014497387,0.00000603355,7.348626e-7,0.0000037129698,0.00082177465],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991506,0.000043357548,0.00020287822,0.00027227096,0.00020140376,0.00012954493],"domain_scores_gemma":[0.999415,0.00006660979,0.000073265124,0.00034344694,0.000044878798,0.000056832843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024443452,0.00008136268,0.00012437873,0.0003310267,0.000045901794,0.000076503755,0.00021011436,0.000034959245,0.00005396574],"category_scores_gemma":[0.00013488579,0.000074005555,0.000032746928,0.001418818,0.000038949365,0.00043417406,0.000056379693,0.000062865925,0.000008772598],"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":[0.000002970123,0.00010160311,0.0054198448,0.000027964166,0.00001943029,0.00000307713,0.00018394337,0.00016485326,0.0008509066,0.97333735,0.0017241077,0.018163959],"study_design_scores_gemma":[0.0004347844,0.00022405441,0.0132198995,0.000009930802,0.000009906095,0.00015387445,0.000038277423,0.07903251,0.8108606,0.09448527,0.0012041122,0.0003268167],"about_ca_topic_score_codex":0.00003361583,"about_ca_topic_score_gemma":0.0000019225288,"teacher_disagreement_score":0.87885207,"about_ca_system_score_codex":0.000019853951,"about_ca_system_score_gemma":0.000024673402,"threshold_uncertainty_score":0.3017859},"labels":[],"label_agreement":null},{"id":"W1908180374","doi":"10.1109/arrays.1988.18055","title":"A systolic architecture for the symmetric tridiagonal eigenvalue problem","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Technical University of Nova Scotia","funders":"","keywords":"Tridiagonal matrix; Eigenvalues and eigenvectors; QR decomposition; Matrix (chemical analysis); Eigendecomposition of a matrix; Symmetric matrix; Applied mathematics; Generalized eigenvector; Computer science; Mathematics; Systolic array; Algorithm; Set (abstract data type); Inverse iteration; Matrix decomposition; State-transition matrix","score_opus":0.01821465101067877,"score_gpt":0.2616180202540315,"score_spread":0.24340336924335276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1908180374","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":[0.00018493354,0.00016750795,0.98393303,0.00060114847,0.0001480407,0.00069746736,0.0000020314592,0.00029530202,0.013970561],"genre_scores_gemma":[0.30239266,0.000010179554,0.69653493,0.00021433667,0.000021412297,0.00027320918,6.080801e-7,0.0000092002365,0.0005434571],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991063,0.00006612768,0.00022532661,0.00020832638,0.00022340388,0.0001705194],"domain_scores_gemma":[0.9987193,0.00061085506,0.00010244832,0.0003970418,0.00012900523,0.000041365576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005641742,0.00009759069,0.00012668446,0.00021763152,0.00011304596,0.000066168504,0.0005793369,0.00004208838,0.000014993522],"category_scores_gemma":[0.00033272387,0.00006139836,0.00009877658,0.0010088846,0.000036491238,0.00013278106,0.000044149256,0.00007538561,0.000007695546],"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":[0.0000019672004,0.000032977896,0.000021644593,0.00002998055,0.000015260859,1.8988113e-7,0.00010982197,0.00038159292,0.00016614285,0.9231724,0.001839817,0.07422817],"study_design_scores_gemma":[0.00080018747,0.00046207395,0.0007039883,0.00006916664,0.00004469438,0.00014776741,0.000035236975,0.12104573,0.23781061,0.53237563,0.10599805,0.00050683814],"about_ca_topic_score_codex":0.0000332133,"about_ca_topic_score_gemma":0.0000048325787,"teacher_disagreement_score":0.39079678,"about_ca_system_score_codex":0.000029361543,"about_ca_system_score_gemma":0.00011031876,"threshold_uncertainty_score":0.25037524},"labels":[],"label_agreement":null},{"id":"W1917266630","doi":"10.1109/wcnc.1999.796795","title":"A new robust beamforming method with antennae calibration errors","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Polyhedron; Beamforming; Calibration; Computer science; Constraint (computer-aided design); Regular polygon; Algorithm; Quadratic programming; Robustness (evolution); Simple (philosophy); Mathematical optimization; Adaptive beamformer; Quadratic equation; Mathematics; Geometry; Telecommunications","score_opus":0.020689762430407623,"score_gpt":0.27047913255565437,"score_spread":0.24978937012524674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1917266630","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":[0.00023856251,0.000007619301,0.98238736,0.00020461676,0.00006978785,0.00012731616,1.6645855e-7,0.00044031336,0.016524237],"genre_scores_gemma":[0.029493399,0.0000013860645,0.96943057,0.000103817874,0.0000065744744,0.000006897516,5.480095e-7,0.000006711933,0.0009501077],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99923944,0.000054948872,0.0001858515,0.00020046145,0.00019808931,0.00012117536],"domain_scores_gemma":[0.999413,0.000055437893,0.00010154208,0.0002864221,0.000076757606,0.00006683626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028428846,0.00008761205,0.00011443735,0.00012829255,0.000050003327,0.00006157881,0.00023701478,0.00003547537,0.00005329069],"category_scores_gemma":[0.00006781172,0.000068226545,0.000028091763,0.0005641785,0.000013310787,0.0009952963,0.000029613318,0.00005330338,0.0000035239866],"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":[0.0000067500137,0.000052617335,0.0006782163,0.000021948445,0.00002294427,0.000003163933,0.00076444907,0.0058368375,0.0038963498,0.89656746,0.002041312,0.09010798],"study_design_scores_gemma":[0.0002697477,0.00020694437,0.00024742217,0.00005222367,0.000009480612,0.00007039173,0.000069153866,0.48939878,0.49169227,0.01565553,0.002066193,0.00026184387],"about_ca_topic_score_codex":0.00022515455,"about_ca_topic_score_gemma":0.000034268385,"teacher_disagreement_score":0.8809119,"about_ca_system_score_codex":0.000023159195,"about_ca_system_score_gemma":0.00013202985,"threshold_uncertainty_score":0.27821976},"labels":[],"label_agreement":null},{"id":"W1932422152","doi":"10.1109/ssap.2000.870085","title":"Array processing in the presence of unknown nonuniform sensor noise: a maximum likelihood direction finding algorithm and Cramer-Rao bounds","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Algorithm; Estimator; Cramér–Rao bound; White noise; Direction of arrival; Noise (video); Array processing; Mathematics; Estimation theory; Likelihood function; Covariance matrix; Diagonal; Applied mathematics; Iterative method; Sensor array; Signal processing; Computer science; Statistics; Telecommunications; Artificial intelligence","score_opus":0.0174420446930167,"score_gpt":0.2582520880181709,"score_spread":0.2408100433251542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1932422152","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":[0.012794983,0.00014520451,0.96754575,0.0006526306,0.00011263979,0.00031860013,0.0000015320848,0.00022783804,0.018200807],"genre_scores_gemma":[0.6234022,0.00004888735,0.37619886,0.000057870166,0.000020410675,0.000030503516,5.255661e-7,0.000007621209,0.0002331658],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873185,0.00007252752,0.00035655053,0.00027903373,0.0003516868,0.00020835597],"domain_scores_gemma":[0.9991601,0.00013923913,0.0002081599,0.0003160265,0.00013787486,0.00003860521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051866355,0.00012977944,0.00018150636,0.00024882777,0.00011841723,0.0001625521,0.00041994007,0.00006428455,0.000015817282],"category_scores_gemma":[0.00012375438,0.00009840521,0.000037269027,0.0009437389,0.00010737203,0.0009275221,0.00007499699,0.00014208723,0.0000025982106],"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":[0.0000024201026,0.00016023127,0.00066281366,0.000088402594,0.0000050319663,0.0000022973672,0.0036319676,0.000027496748,0.0048007593,0.001222614,0.00020416739,0.9891918],"study_design_scores_gemma":[0.00041076387,0.000267427,0.0067447782,0.0003624581,0.000014723415,0.00010160816,0.00039238497,0.8569204,0.119009525,0.013362783,0.0020470212,0.00036612086],"about_ca_topic_score_codex":0.00018853685,"about_ca_topic_score_gemma":0.000022241691,"teacher_disagreement_score":0.9888257,"about_ca_system_score_codex":0.000035342964,"about_ca_system_score_gemma":0.00002877857,"threshold_uncertainty_score":0.4012848},"labels":[],"label_agreement":null},{"id":"W1951109917","doi":"10.1109/ssap.1994.572461","title":"An Efficient Self-Calibrating Direction-of-Arrival Estimator","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"McMaster University","funders":"","keywords":"Computer science; Estimator; Direction of arrival; Calibration; Telecommunications; Statistics; Mathematics","score_opus":0.007417883474236736,"score_gpt":0.267528917930755,"score_spread":0.2601110344565183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1951109917","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":[0.068365,0.00001897736,0.9161002,0.00022339594,0.00022176025,0.0001838375,0.0000014944168,0.0016384452,0.013246871],"genre_scores_gemma":[0.5159334,0.0000011056096,0.48395628,0.000030894123,0.000029002693,0.000009352908,6.6795883e-7,0.000007058203,0.000032214215],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853843,0.000075609314,0.0004935771,0.00032545108,0.00037792145,0.00018901682],"domain_scores_gemma":[0.99875253,0.00012324152,0.0002355066,0.0005939245,0.00018422156,0.00011059899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003872972,0.00014154702,0.0002134874,0.00021374601,0.000101574835,0.00007452523,0.0006457034,0.00006484987,0.00006184263],"category_scores_gemma":[0.00008778547,0.00013191401,0.00007663361,0.0005888966,0.000048205984,0.0007789375,0.00011014314,0.00008300919,0.000020583104],"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":[0.000014342013,0.001830423,0.004173831,0.00013325691,0.00007132162,0.0000027887843,0.0025249638,0.0654178,0.03561769,0.5762272,0.0015322461,0.31245416],"study_design_scores_gemma":[0.00009379998,0.00008707925,0.0012014208,0.000020293202,0.000004543702,0.000007799623,0.0000120080995,0.7146569,0.2829041,0.0004639842,0.00042845082,0.00011962696],"about_ca_topic_score_codex":0.000054935703,"about_ca_topic_score_gemma":0.000004647501,"teacher_disagreement_score":0.6492391,"about_ca_system_score_codex":0.00005171369,"about_ca_system_score_gemma":0.00009283926,"threshold_uncertainty_score":0.5379297},"labels":[],"label_agreement":null},{"id":"W1966110067","doi":"10.1121/1.4782960","title":"Robust adaptive beamforming: Evolution of approaches, analysis, and comparison.","year":2008,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Constraint (computer-aided design); Adaptive beamformer; Beamforming; Mathematical optimization; Computer science; Quadratic equation; Quadratic programming; Algorithm; Mathematics; Telecommunications","score_opus":0.04923712620946307,"score_gpt":0.2539117645517204,"score_spread":0.2046746383422573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966110067","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":[0.010123086,0.000280386,0.9887827,0.0005695195,0.000038596783,0.00007743432,0.0000023480945,0.000012529564,0.00011342248],"genre_scores_gemma":[0.6068824,0.000081906626,0.39298707,0.000025901734,0.000012556023,3.9037025e-7,7.784909e-8,0.0000024007422,0.0000073003594],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985929,0.0001388405,0.00055626745,0.00008513206,0.00051191275,0.00011493898],"domain_scores_gemma":[0.99785787,0.0004006997,0.0011070018,0.00030549624,0.0002785095,0.000050399587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006509699,0.00009159215,0.00041678525,0.000058334226,0.00012787904,0.0000063538246,0.00075376336,0.00004772986,0.0000032586597],"category_scores_gemma":[0.00014535995,0.000052701915,0.00034172487,0.0009743522,0.0008862861,0.00019217774,0.00022331922,0.00023539693,1.6669968e-7],"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":[0.00035713753,0.0018181225,0.017485067,0.00021879621,0.00457343,0.0000011784782,0.017828014,0.8268571,0.021682123,0.0028630386,0.02364649,0.0826695],"study_design_scores_gemma":[0.00012425017,0.00026293905,0.011471315,0.00003365585,0.0003961881,0.00003507936,0.00077633234,0.97962415,0.005873792,0.0012980377,0.000040724724,0.00006350932],"about_ca_topic_score_codex":0.00012435028,"about_ca_topic_score_gemma":5.6954974e-7,"teacher_disagreement_score":0.5967593,"about_ca_system_score_codex":0.00006602304,"about_ca_system_score_gemma":0.0001045812,"threshold_uncertainty_score":0.3265558},"labels":[],"label_agreement":null},{"id":"W1971196735","doi":"10.5383/juspn.03.01.005","title":"An Efficient Channel Estimator for Frequency Hopping System via Propagator Method","year":2011,"lang":"en","type":"article","venue":"Journal of Ubiquitous Systems and Pervasive Networks","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Estimator; Propagator; Channel (broadcasting); Frequency-hopping spread spectrum; Statistical physics; Computer science; Mathematics; Physics; Statistics; Telecommunications; Mathematical physics","score_opus":0.026621968057328613,"score_gpt":0.27527702314951175,"score_spread":0.24865505509218314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971196735","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":[0.007335852,0.0012039171,0.98840034,0.000024943904,0.0020094477,0.0006942766,0.0000043306695,0.00012131248,0.00020560261],"genre_scores_gemma":[0.76695776,0.000018591823,0.2325157,0.000017262044,0.0004166496,0.000047246067,5.9759026e-7,0.000020276248,0.00000590989],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977822,0.00026747663,0.0010144871,0.00029074596,0.000345861,0.00029927003],"domain_scores_gemma":[0.99666137,0.00021100065,0.0013953126,0.00036997904,0.0011180791,0.00024426167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020047342,0.00022356355,0.0006214305,0.0002628635,0.00017924722,0.0001409357,0.0006353782,0.00016492032,0.0000012106392],"category_scores_gemma":[0.00007393176,0.00017820897,0.00016687003,0.0002753564,0.00004606953,0.0005255366,0.00006267896,0.00019584985,5.0454395e-7],"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":[0.00073955156,0.0021078568,0.0032950472,0.010676247,0.0016894782,0.0005221024,0.031194722,0.392341,0.029973844,0.38235274,0.0035880785,0.14151934],"study_design_scores_gemma":[0.0003655198,0.0011566821,0.00025162552,0.0011205549,0.00005755471,0.0011823142,0.00038890023,0.9914394,0.0032598933,0.0004983218,0.00005094426,0.00022829628],"about_ca_topic_score_codex":0.00016494544,"about_ca_topic_score_gemma":0.0000032273044,"teacher_disagreement_score":0.7596219,"about_ca_system_score_codex":0.00010704342,"about_ca_system_score_gemma":0.00013468931,"threshold_uncertainty_score":0.7267151},"labels":[],"label_agreement":null},{"id":"W1976489202","doi":"10.1121/1.4831119","title":"Eigenspace dynamics of sample covariance matrices","year":2013,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Eigenvalues and eigenvectors; Sample mean and sample covariance; Covariance; Covariance matrix; Algorithm; Computer science; Computation; Sample (material); Estimation of covariance matrices; Mathematics; Statistics; Physics; Estimator","score_opus":0.009880456980408642,"score_gpt":0.25140129687168067,"score_spread":0.24152083989127202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976489202","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":[0.0035303575,0.00008889099,0.9903875,0.0055892603,0.0001374095,0.00011352276,0.000007899313,0.000019373017,0.000125782],"genre_scores_gemma":[0.38065714,0.00022658957,0.61882585,0.0002358671,0.000023584125,8.967607e-7,9.992937e-8,0.0000052012424,0.000024794876],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864304,0.00012102007,0.0005101434,0.00007195923,0.0005138853,0.00013995222],"domain_scores_gemma":[0.9967292,0.0011142973,0.001150296,0.00043110602,0.0005255218,0.000049577648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005605862,0.00009200948,0.00029140207,0.000024415122,0.00007978838,0.000019712636,0.0014924542,0.00004713361,0.00003250837],"category_scores_gemma":[0.00045678037,0.000051435338,0.00027235362,0.0005466105,0.00050345366,0.00025698662,0.00027093355,0.00021919007,0.00000211966],"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":[0.00019136917,0.001729923,0.003822647,0.00094632804,0.0014767013,0.0000013295003,0.0106255105,0.14442801,0.112977676,0.015667211,0.19185922,0.5162741],"study_design_scores_gemma":[0.00012735571,0.00024583592,0.002094931,0.0000992254,0.000077463774,0.000023434168,0.00041086465,0.9602869,0.010386226,0.025899444,0.0002623005,0.00008602421],"about_ca_topic_score_codex":0.00039010236,"about_ca_topic_score_gemma":6.701013e-7,"teacher_disagreement_score":0.8158589,"about_ca_system_score_codex":0.00005517908,"about_ca_system_score_gemma":0.00009764345,"threshold_uncertainty_score":0.2773376},"labels":[],"label_agreement":null},{"id":"W1978869461","doi":"10.1109/ccece.2012.6335024","title":"Performance analysis of 2-D DOA estimation via L-shaped array","year":2012,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Azimuth; Direction of arrival; Algorithm; Sensor array; Computer science; Array processing; Focus (optics); Eigendecomposition of a matrix; Signal processing; Covariance matrix; SIGNAL (programming language); Mathematics; Eigenvalues and eigenvectors; Statistics; Geometry; Telecommunications; Physics; Optics","score_opus":0.015886758503165774,"score_gpt":0.2739155982210381,"score_spread":0.2580288397178723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978869461","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":[0.06775223,0.000009245004,0.92400014,0.000040573796,0.00008457247,0.00006896723,6.2722336e-7,0.00019860995,0.0078450525],"genre_scores_gemma":[0.67138267,0.0000029248424,0.3285166,0.000018938903,0.0000053968092,0.0000062515383,0.0000024676458,0.0000021513456,0.00006263434],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991766,0.000027433663,0.0002967027,0.00011572098,0.00024322365,0.00014027402],"domain_scores_gemma":[0.99918866,0.00006096585,0.00019949023,0.00037011973,0.0001337669,0.00004697939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039233433,0.00007265786,0.0001863585,0.00042199137,0.000034691504,0.000014493256,0.00031187758,0.000036286576,0.000096555326],"category_scores_gemma":[0.000041978543,0.00006421939,0.000080669335,0.0015034773,0.000031351363,0.001099061,0.000050958617,0.000035292356,0.000017362227],"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":[0.000017018156,0.0007081242,0.1506048,0.00020610225,0.0008365795,1.9024695e-7,0.0033405065,0.018143108,0.12802525,0.08852521,0.0004741435,0.609119],"study_design_scores_gemma":[0.000030548235,0.00002502876,0.04787165,0.0000063075313,0.00005587013,6.6731997e-7,0.0000026478185,0.77142406,0.18027346,0.0002195106,0.000028880837,0.00006135586],"about_ca_topic_score_codex":0.00005017575,"about_ca_topic_score_gemma":0.0000023376722,"teacher_disagreement_score":0.753281,"about_ca_system_score_codex":0.000023302451,"about_ca_system_score_gemma":0.000015927217,"threshold_uncertainty_score":0.2618791},"labels":[],"label_agreement":null},{"id":"W1978954881","doi":"10.1109/tvt.2012.2203327","title":"Joint Space-Time Parameter Estimation for Multicarrier CDMA Systems","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Smoothing; Subcarrier; Multipath propagation; Covariance matrix; Code division multiple access; Algorithm; Computer science; Decorrelation; Joint (building); Electronic engineering; Orthogonal frequency-division multiplexing; Engineering; Telecommunications","score_opus":0.01793113486942034,"score_gpt":0.2582527950253429,"score_spread":0.24032166015592255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978954881","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":[0.014258927,0.00007098126,0.98182285,0.00072010723,0.0007614873,0.000849356,0.000015148937,0.0014181946,0.00008294078],"genre_scores_gemma":[0.69910353,0.0000051188526,0.30026397,0.000026839884,0.000014192034,0.00045658014,0.0000017270146,0.000019668616,0.00010836156],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985219,0.00006381692,0.00044170438,0.0003412573,0.00024879313,0.0003824888],"domain_scores_gemma":[0.99852204,0.00017935579,0.00020124167,0.00079202786,0.00021383117,0.00009150839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038020324,0.0002129919,0.00033851853,0.00077748724,0.00015912658,0.00004725041,0.0004246003,0.00035297693,0.000013518146],"category_scores_gemma":[0.00008416747,0.00020945452,0.00016556389,0.0007149531,0.00014021272,0.00056449533,0.0000058477904,0.00023097437,0.00008962515],"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":[0.000080415215,0.0021557272,0.00009188582,0.0004720969,0.0006017877,0.0000073994765,0.0009136517,0.113033324,0.21559814,0.1916839,0.0014158445,0.47394583],"study_design_scores_gemma":[0.00024290654,0.00018085663,0.000021473352,0.00005265222,0.00003656961,0.00003884872,0.000013384613,0.51122385,0.48480445,0.0023490156,0.00085160433,0.00018440321],"about_ca_topic_score_codex":0.000017337814,"about_ca_topic_score_gemma":7.125773e-7,"teacher_disagreement_score":0.6848446,"about_ca_system_score_codex":0.00011690968,"about_ca_system_score_gemma":0.00003870588,"threshold_uncertainty_score":0.85413074},"labels":[],"label_agreement":null},{"id":"W1980617447","doi":"10.1109/array.2010.5613308","title":"DOA estimation using cross-correlation matrix","year":2010,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Subspace topology; Covariance matrix; Computer science; Algorithm; Narrowband; Direction of arrival; Correlation; Cross-correlation; Matrix (chemical analysis); Signal subspace; Pattern recognition (psychology); Mathematics; Artificial intelligence; Statistics; Noise (video); Geometry; Telecommunications; Image (mathematics)","score_opus":0.015622554328094297,"score_gpt":0.3430218920320629,"score_spread":0.3273993377039686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980617447","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":[0.11337429,0.000002057668,0.8799184,0.00005204253,0.00052386057,0.000105200874,4.415008e-7,0.0005102248,0.005513489],"genre_scores_gemma":[0.49189684,2.2340274e-7,0.507926,0.0000120790755,0.000012721993,0.000002701853,0.000001024869,0.0000033100823,0.0001451207],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992561,0.00001505218,0.00025151385,0.00017377798,0.00020569154,0.000097874334],"domain_scores_gemma":[0.9992259,0.000059937145,0.00014850449,0.0003521278,0.0001773756,0.00003616426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028222264,0.00007384813,0.0000825712,0.00015417203,0.00008234901,0.00015060026,0.0003024625,0.000076601325,0.00009382988],"category_scores_gemma":[0.00015056574,0.000071354734,0.00003757792,0.0003510321,0.000044569864,0.0013610778,0.00007445115,0.00010830224,0.000040904688],"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":[0.0000043340174,0.00007665434,0.006488508,0.000030983552,0.00000804093,0.0000010144623,0.00023354277,0.029416956,0.10450368,0.7479843,0.00034214533,0.110909864],"study_design_scores_gemma":[0.00006019258,0.000012537631,0.003466251,0.000006755528,0.000002048101,0.000011476446,8.7510045e-7,0.8765599,0.09987977,0.01982994,0.000097018776,0.000073241594],"about_ca_topic_score_codex":0.00010093251,"about_ca_topic_score_gemma":0.0000048682136,"teacher_disagreement_score":0.84714293,"about_ca_system_score_codex":0.000021858108,"about_ca_system_score_gemma":0.000048448295,"threshold_uncertainty_score":0.29097617},"labels":[],"label_agreement":null},{"id":"W1982907761","doi":"10.1109/camsap.2011.6135977","title":"A computationally efficient robust adaptive beamforming for general-rank signal model with positive semi-definite constraint","year":2011,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematical optimization; Adaptive beamformer; Constraint (computer-aided design); Rank (graph theory); Linearization; Convex optimization; Convergence (economics); Optimization problem; Beamforming; Mathematics; Computer science; Regular polygon; Nonlinear system","score_opus":0.045267194192322065,"score_gpt":0.24023475899820707,"score_spread":0.194967564805885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982907761","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":[0.004900849,0.0000047147014,0.9799075,0.000062940155,0.00003104987,0.00055526267,0.000030073348,0.00031069346,0.014196929],"genre_scores_gemma":[0.3849311,3.2436353e-7,0.61480975,0.00012228884,0.0000068060835,0.000054054133,0.0000059654167,0.000008186413,0.00006150786],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879026,0.000027405822,0.00031708126,0.00034746836,0.0003015164,0.00021627647],"domain_scores_gemma":[0.9987445,0.00017683423,0.00020346924,0.00018706082,0.00060637697,0.000081785125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025263635,0.00016950052,0.00020070911,0.00018112765,0.000119604156,0.00004273509,0.00033573303,0.00005199154,0.000014826383],"category_scores_gemma":[0.000015624051,0.0001423302,0.00007675988,0.0002632333,0.00013587822,0.0003123098,0.000083024584,0.00007559837,0.0000032647113],"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":[0.000046611207,0.00010879113,0.0000096529875,0.0000090720205,0.00003674043,0.0000014522094,0.0013281038,0.51377416,0.0005228308,0.47942954,0.00005639285,0.004676647],"study_design_scores_gemma":[0.00034439098,0.00038596964,0.0001293276,0.000055884484,0.000014072852,0.000021372025,0.0000511724,0.95394146,0.032084588,0.012778829,0.0000027501437,0.00019015661],"about_ca_topic_score_codex":0.0000629387,"about_ca_topic_score_gemma":0.0000065241106,"teacher_disagreement_score":0.46665072,"about_ca_system_score_codex":0.00006489062,"about_ca_system_score_gemma":0.00023592223,"threshold_uncertainty_score":0.5804057},"labels":[],"label_agreement":null},{"id":"W1984793157","doi":"10.1155/2011/490289","title":"Computationally Efficient DOA and Polarization Estimation of Coherent Sources with Linear Electromagnetic Vector-Sensor Array","year":2011,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Decorrelation; Algorithm; Computational complexity theory; Computer science; Polarization (electrochemistry); Preprocessor; Monte Carlo method; Direction of arrival; Stokes parameters; Mathematics; Physics; Optics; Telecommunications; Statistics; Artificial intelligence; Scattering","score_opus":0.012437371007973617,"score_gpt":0.2624894734558864,"score_spread":0.2500521024479128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984793157","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":[0.21744609,0.0004986624,0.7814916,0.000038364753,0.000033214004,0.00011724482,5.2382495e-7,0.000044959575,0.00032938487],"genre_scores_gemma":[0.6727043,0.000017739296,0.32723442,0.000016262751,0.000012910008,0.000002758508,7.1881846e-7,0.000007525463,0.0000033694964],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986358,0.000102337915,0.00049119024,0.0002090657,0.00041052088,0.00015106726],"domain_scores_gemma":[0.998745,0.000120093995,0.0006883138,0.00008442339,0.00030268883,0.000059484657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035728296,0.00014154939,0.0002084813,0.00033124757,0.000110377776,0.00006390708,0.0002282874,0.000035564255,0.00000803887],"category_scores_gemma":[0.00006307592,0.0001154543,0.000025495863,0.00053731323,0.000112466776,0.0007760087,0.000019407205,0.0002005273,7.0789105e-7],"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":[0.0003383994,0.00060476304,0.005109937,0.0003517244,0.00002165556,0.000016558399,0.0042412207,0.53923005,0.043812882,0.007012648,0.000001685194,0.39925846],"study_design_scores_gemma":[0.00070411374,0.0018304667,0.015695548,0.0011904376,0.000016238379,0.00018722001,0.000086585846,0.8134715,0.15837032,0.00817037,0.0000148875415,0.0002623221],"about_ca_topic_score_codex":0.0000035884102,"about_ca_topic_score_gemma":0.000001149942,"teacher_disagreement_score":0.45525822,"about_ca_system_score_codex":0.00004735964,"about_ca_system_score_gemma":0.000107062166,"threshold_uncertainty_score":0.47080895},"labels":[],"label_agreement":null},{"id":"W1985319438","doi":"10.1016/s0165-1684(00)00139-0","title":"Sensor array signal tracking using a data-driven window approach","year":2000,"lang":"en","type":"article","venue":"Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Window (computing); Sensor array; SIGNAL (programming language); Computer science; Tracking (education); Real-time computing; Artificial intelligence","score_opus":0.06725814964956589,"score_gpt":0.3071153046183793,"score_spread":0.23985715496881344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985319438","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":[0.014650257,0.00011705248,0.9779901,0.000045920635,0.000031468957,0.00019611462,0.000006390369,0.00052748545,0.00643519],"genre_scores_gemma":[0.57618296,0.0000015385492,0.42362934,0.00004866952,0.00007190102,0.00000423213,0.000007690066,0.000015070217,0.000038581067],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997976,0.00010205764,0.00044902667,0.0006262512,0.0005182566,0.00032841464],"domain_scores_gemma":[0.99887824,0.00006367903,0.0002507712,0.00054158905,0.00017297316,0.00009274354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004965586,0.00020797964,0.00027661046,0.00018201658,0.00027919916,0.00037446863,0.0012499449,0.0000902358,0.00009603185],"category_scores_gemma":[0.000022976872,0.00020519375,0.000057878253,0.000761707,0.00011154195,0.0025898563,0.0001251936,0.00022100934,0.000011801864],"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":[0.000017076673,0.00015692282,0.00019482322,0.00017659324,0.000022416789,0.000008230321,0.0011177986,0.018089877,0.0941791,0.00023905929,0.000051297586,0.8857468],"study_design_scores_gemma":[0.00016767907,0.000037756105,0.00010766434,0.00021059107,0.000019722707,0.00007916127,0.00004264398,0.9238605,0.07374302,0.0012113177,0.00024802808,0.00027193507],"about_ca_topic_score_codex":0.000037370402,"about_ca_topic_score_gemma":6.5659185e-7,"teacher_disagreement_score":0.9057706,"about_ca_system_score_codex":0.000057981382,"about_ca_system_score_gemma":0.00023899031,"threshold_uncertainty_score":0.8367558},"labels":[],"label_agreement":null},{"id":"W1987596210","doi":"10.1109/embc.2012.6347171","title":"Brain source localization based on fast fully adaptive approach","year":2012,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Adaptive beamformer; Computer science; Beamforming; Context (archaeology); Signal processing; Electroencephalography; Adaptive filter; Bootstrapping (finance); Array processing; Space-time adaptive processing; Degrees of freedom (physics and chemistry); Artificial intelligence; Pattern recognition (psychology); Radar; Speech recognition; Algorithm; Mathematics; Telecommunications; Radar engineering details; Neuroscience","score_opus":0.01937537654522364,"score_gpt":0.24669283133680767,"score_spread":0.22731745479158402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987596210","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":[0.0001147666,0.0000041836934,0.93743485,0.00022018913,0.000078632664,0.00015331012,6.1019216e-7,0.00052346726,0.061469972],"genre_scores_gemma":[0.6818618,1.4861943e-7,0.31697857,0.00066898455,0.000023342216,0.000017851647,0.0000031198615,0.000006725432,0.0004394498],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913085,0.00008443457,0.00016600464,0.00017849181,0.00027897197,0.00016123758],"domain_scores_gemma":[0.99930096,0.00010725958,0.00009313911,0.00033349716,0.000093880015,0.00007126892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035965574,0.00009478502,0.00009924759,0.00015463054,0.000056049685,0.000037177895,0.00030388453,0.000051593164,0.000028940163],"category_scores_gemma":[0.00008389332,0.00008421787,0.000039360075,0.0004422889,0.000034773882,0.00050262356,0.000056651133,0.00005711828,0.0000319113],"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":[0.000030685784,0.00091615756,0.0017231926,0.000048565802,0.000018158995,3.1477532e-7,0.002073902,0.05892914,0.0006330811,0.64568144,0.019207807,0.2707376],"study_design_scores_gemma":[0.000097414166,0.000096096905,0.0004598307,0.000012423191,0.0000018143967,0.000001382389,0.0000317701,0.9740464,0.022617118,0.00047375055,0.002056728,0.000105256084],"about_ca_topic_score_codex":0.000032803375,"about_ca_topic_score_gemma":7.2022686e-7,"teacher_disagreement_score":0.91511726,"about_ca_system_score_codex":0.000043382814,"about_ca_system_score_gemma":0.000031861247,"threshold_uncertainty_score":0.34343052},"labels":[],"label_agreement":null},{"id":"W1988838366","doi":"10.1016/j.sigpro.2006.11.001","title":"On the adaptive linear estimators, using biased Cramér–Rao bound","year":2006,"lang":"en","type":"article","venue":"Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Queen's University","funders":"","keywords":"Estimator; Cramér–Rao bound; Mathematics; Algorithm; Computer science; Statistics; Applied mathematics","score_opus":0.03617379225947152,"score_gpt":0.2838124885625061,"score_spread":0.24763869630303462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988838366","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":[0.032087613,0.000063736654,0.96355796,0.00018365905,0.00006130279,0.00016156062,0.0000015225172,0.00035010575,0.0035325577],"genre_scores_gemma":[0.82556355,3.1191706e-7,0.17420045,0.00012415319,0.000055498695,0.000008270655,9.552236e-7,0.000012678865,0.000034124205],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987689,0.00006979142,0.0002891255,0.00027512608,0.0003912835,0.00020574778],"domain_scores_gemma":[0.9990402,0.0002277827,0.0002546063,0.000238293,0.00020407552,0.000035057066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038340912,0.00014829742,0.00014911756,0.00013848217,0.00034423443,0.00022645062,0.00047131345,0.000056898054,0.000013452576],"category_scores_gemma":[0.000073275376,0.000111979745,0.000054893215,0.00063441566,0.00012810864,0.0005808703,0.000077014374,0.00015499373,0.000009968877],"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":[0.00012361466,0.0008343708,0.00058789714,0.0003131987,0.000063464846,0.000049433645,0.0016164675,0.10692758,0.09796018,0.42956042,0.0036124943,0.35835087],"study_design_scores_gemma":[0.00007680697,0.000064857384,0.00008379456,0.00021111575,0.0000064755172,0.000007731769,0.00001212853,0.82272345,0.117875926,0.058731765,0.00007292304,0.00013301196],"about_ca_topic_score_codex":0.00014542855,"about_ca_topic_score_gemma":0.000002663678,"teacher_disagreement_score":0.7934759,"about_ca_system_score_codex":0.00007007863,"about_ca_system_score_gemma":0.00020520928,"threshold_uncertainty_score":0.45664015},"labels":[],"label_agreement":null},{"id":"W1989097365","doi":"10.1109/icassp.2002.5745285","title":"On uniqueness of direction of arrival estimates using RAnk Reduction Estimator (RARE)","year":2002,"lang":"en","type":"article","venue":"IEEE International Conference on Acoustics Speech and Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Uniqueness; Identifiability; Direction of arrival; Estimator; Rank (graph theory); Reduction (mathematics); Equivalence (formal languages); Algorithm; SIGNAL (programming language); Mathematics; Computer science; Manifold (fluid mechanics); Applied mathematics; Statistics; Combinatorics; Mathematical analysis; Telecommunications; Engineering; Discrete mathematics; Geometry","score_opus":0.05940025821180401,"score_gpt":0.31681934530991007,"score_spread":0.25741908709810607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989097365","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":[0.19184688,0.000028918901,0.80507034,0.00008307871,0.00033447676,0.00012793089,0.00001129319,0.00010305709,0.0023940008],"genre_scores_gemma":[0.8663542,0.00003329935,0.1335094,0.000012497471,0.000039433144,0.0000049099813,0.0000021707438,0.000010875476,0.0000331942],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843067,0.00004125809,0.00051488966,0.000307672,0.00056747097,0.00013805424],"domain_scores_gemma":[0.9982074,0.00012754784,0.0005639397,0.00016295182,0.00087766076,0.000060512546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002325219,0.0001800167,0.0002734946,0.00040368622,0.00009337523,0.000094988696,0.00037016626,0.00009547503,0.00005147399],"category_scores_gemma":[0.00014965337,0.00017802266,0.000051894312,0.00029103537,0.00017134739,0.00052552123,0.000042394695,0.00015550198,0.0000013140159],"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":[0.00009679954,0.00032708576,0.00013141352,0.00024730113,0.00004233724,0.000006221391,0.00034555947,0.014727014,0.7830267,0.026766894,0.00006457437,0.1742181],"study_design_scores_gemma":[0.00015023652,0.00015824099,0.00008698329,0.0005238743,0.000013062991,0.00003352487,0.000021774156,0.6330253,0.35172388,0.014156221,0.0000015598214,0.00010534766],"about_ca_topic_score_codex":0.000042848824,"about_ca_topic_score_gemma":4.282181e-7,"teacher_disagreement_score":0.6745073,"about_ca_system_score_codex":0.000068589914,"about_ca_system_score_gemma":0.00009425599,"threshold_uncertainty_score":0.7259553},"labels":[],"label_agreement":null},{"id":"W1989219461","doi":"10.1109/bsc.2008.4563221","title":"Diversity combining and eigencombining performance and complexity comparison for estimated channels","year":2008,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Maximal-ratio combining; Fading; Algorithm; Subspace topology; Computer science; Diversity combining; Diversity gain; Covariance matrix; Antenna (radio); Channel (broadcasting); Mathematics; Signal-to-noise ratio (imaging); Statistics; Telecommunications; Artificial intelligence; Decoding methods","score_opus":0.1483716341711634,"score_gpt":0.31073754274364984,"score_spread":0.16236590857248645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989219461","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":[0.582817,0.000018440807,0.4160112,0.000050570252,0.00007615887,0.00014378756,8.937421e-7,0.00024357445,0.00063831743],"genre_scores_gemma":[0.78383404,0.000016566268,0.21607384,0.000030306177,0.0000037006205,0.0000064726364,0.000001555354,0.0000032253615,0.000030307701],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927175,0.000020044094,0.00020159286,0.00022414165,0.0001378401,0.00014462182],"domain_scores_gemma":[0.9994241,0.00012496301,0.00011558127,0.00015680623,0.00011272962,0.00006580478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022257505,0.00009879352,0.00021325624,0.00009934631,0.00086680765,0.00002957526,0.00023237431,0.00003835354,0.0000034883374],"category_scores_gemma":[0.00004052588,0.00009954696,0.000020057236,0.00017112576,0.00018501327,0.00054577406,0.0007119208,0.000058884343,7.428647e-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":[0.00005655284,0.0002794578,0.7570729,0.00031713082,0.000061001374,0.0000029395455,0.017560173,0.0005597898,0.0007816932,0.17152847,0.0018092253,0.049970634],"study_design_scores_gemma":[0.00037351047,0.00023187882,0.11098527,0.000040014704,0.0000049223927,0.000024330926,0.00003272244,0.87149763,0.011954693,0.0046761865,0.000036580484,0.00014228084],"about_ca_topic_score_codex":0.00010853361,"about_ca_topic_score_gemma":0.0000033557612,"teacher_disagreement_score":0.8709378,"about_ca_system_score_codex":0.000015227474,"about_ca_system_score_gemma":0.000017092254,"threshold_uncertainty_score":0.66668713},"labels":[],"label_agreement":null},{"id":"W1994419003","doi":"10.1109/taes.2012.6324673","title":"Effects of Mutual Coupling on the Accuracy of Adcock Direction Finding Systems","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; Royal Military College of Canada","funders":"","keywords":"Antenna (radio); Coupling (piping); Direction finding; Electronic engineering; Computer science; Range (aeronautics); Key (lock); Cover (algebra); Implementation; Antenna array; Topology (electrical circuits); Engineering; Electrical engineering; Telecommunications; Aerospace engineering","score_opus":0.013527015449574627,"score_gpt":0.25081541383349004,"score_spread":0.2372883983839154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994419003","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":[0.27823296,0.0010995006,0.7184333,0.000059024136,0.0011671266,0.00068548345,0.0000030933993,0.00013266172,0.00018682634],"genre_scores_gemma":[0.9991757,0.0003114427,0.00013620504,0.000006676163,0.000041147643,0.0001277709,2.7281283e-7,0.000015206511,0.00018554355],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99861044,0.00012926923,0.00036382483,0.00021174656,0.00035429437,0.00033043037],"domain_scores_gemma":[0.99793124,0.0011355946,0.00040505445,0.0003619414,0.000107333675,0.000058808153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006837057,0.0001732095,0.00032754798,0.00020114804,0.00016267486,0.00004578566,0.00025539208,0.00010244002,0.0000012641615],"category_scores_gemma":[0.00004207866,0.00013507919,0.00009408555,0.0005086037,0.000058121615,0.0003340676,0.0000032280068,0.00023036306,0.000004068783],"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":[0.000315702,0.0021478834,0.00078646734,0.0041372282,0.0010206242,0.0000016238288,0.008069972,0.12787382,0.63653827,0.18984723,0.0013043506,0.027956836],"study_design_scores_gemma":[0.00037137207,0.0007181283,0.00023773189,0.0008666964,0.00006488428,0.000026426067,0.00020908863,0.1063638,0.8905413,0.000036280275,0.0003494863,0.00021475705],"about_ca_topic_score_codex":0.00030323555,"about_ca_topic_score_gemma":0.000007867442,"teacher_disagreement_score":0.7209428,"about_ca_system_score_codex":0.00013254798,"about_ca_system_score_gemma":0.000068292604,"threshold_uncertainty_score":0.5508369},"labels":[],"label_agreement":null},{"id":"W1996199981","doi":"10.1109/iscas.2012.6271833","title":"Accurate DOA estimation via sparse sensor array","year":2012,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Direction of arrival; Rotational invariance; Property (philosophy); Algorithm; Sparse array; Null (SQL); Computer science; Sensor array; Ambiguity; Mathematics; Data mining; Telecommunications","score_opus":0.028714943126454905,"score_gpt":0.2933550869587069,"score_spread":0.264640143832252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996199981","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":[0.003275776,0.000010787703,0.9783139,0.00029412514,0.00035078125,0.00013605155,5.832535e-7,0.0006918215,0.016926153],"genre_scores_gemma":[0.51496375,0.0000015049864,0.48469466,0.00007543332,0.000021907776,0.000009158144,0.0000010988861,0.000004006617,0.00022847873],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99916774,0.000045037006,0.00023822176,0.00014739163,0.00021155889,0.00019007239],"domain_scores_gemma":[0.9992079,0.00007755901,0.00013488045,0.00039289502,0.00010156984,0.00008517567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032183868,0.00009634024,0.00011416314,0.000119651195,0.000050492457,0.000053345237,0.00030277862,0.0000469505,0.000083597115],"category_scores_gemma":[0.00009153539,0.00008487838,0.000041558083,0.00033406375,0.000028632494,0.0015791046,0.00005862352,0.000056688434,0.0002383261],"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":[0.000013814421,0.00055400806,0.0029326824,0.00010561206,0.00005503866,0.0000021446717,0.0024697797,0.003316761,0.102713004,0.36515832,0.009679255,0.5129996],"study_design_scores_gemma":[0.000104216415,0.000040254075,0.003610492,0.000018533494,0.0000063915722,0.00002290118,0.000009224934,0.32087916,0.6658464,0.0075081545,0.0017512838,0.00020300536],"about_ca_topic_score_codex":0.000044426077,"about_ca_topic_score_gemma":0.0000013409863,"teacher_disagreement_score":0.56313336,"about_ca_system_score_codex":0.00003103872,"about_ca_system_score_gemma":0.00002033514,"threshold_uncertainty_score":0.346124},"labels":[],"label_agreement":null},{"id":"W1996662010","doi":"10.1109/atc.2010.5672752","title":"A novel multi-dimensional spectrum estimation technique","year":2010,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Snapshot (computer storage); Computer science; Synthetic aperture radar; Sonar; Spectral density estimation; Radar; Synthetic aperture sonar; Radar imaging; Inverse synthetic aperture radar; Fourier transform; Algorithm; Electronic engineering; Computer vision; Telecommunications; Artificial intelligence; Mathematics; Engineering","score_opus":0.01426063530921575,"score_gpt":0.2750435584421159,"score_spread":0.2607829231329002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996662010","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":[0.0022698562,0.000001314854,0.99266404,0.00053526915,0.00027071856,0.00027541767,0.000001498679,0.0009331737,0.0030486854],"genre_scores_gemma":[0.3408728,1.7154522e-7,0.6588562,0.00006180268,0.0000097309885,0.000037284222,0.0000014313944,0.0000051908473,0.00015537009],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99912137,0.0000123202135,0.00024886048,0.00024434613,0.00023992814,0.00013318082],"domain_scores_gemma":[0.99918383,0.00006896059,0.000117186566,0.00046164644,0.00011022179,0.000058131543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003236777,0.00010410395,0.00011495008,0.00019980069,0.00005974941,0.000048551246,0.00045997743,0.00008649352,0.000079346544],"category_scores_gemma":[0.00014086417,0.00009490091,0.00004933859,0.0003612947,0.00005571517,0.00055390527,0.00014569223,0.00017093796,0.000036586163],"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":[0.0000018915887,0.00020860415,0.00008754344,0.000010245401,0.0000053706876,8.8552355e-7,0.00004548381,0.00020367664,0.6638915,0.3166276,0.0004412967,0.018475877],"study_design_scores_gemma":[0.00009631812,0.000028096558,0.001328585,0.000009568798,0.000001353633,0.000042910146,4.8980127e-7,0.4027682,0.58591694,0.009555584,0.00015940813,0.0000925414],"about_ca_topic_score_codex":0.00012409916,"about_ca_topic_score_gemma":0.00003568583,"teacher_disagreement_score":0.40256453,"about_ca_system_score_codex":0.000018112662,"about_ca_system_score_gemma":0.00007270826,"threshold_uncertainty_score":0.3869947},"labels":[],"label_agreement":null},{"id":"W1999104815","doi":"10.1109/tsp.2015.2422675","title":"Subspace Leakage Analysis and Improved DOA Estimation With Small Sample Size","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":95,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Subspace topology; Covariance matrix; Algorithm; Signal subspace; Mathematics; Computer science; Resampling; Noise (video); Pattern recognition (psychology); Statistics; Artificial intelligence","score_opus":0.027144516678505686,"score_gpt":0.2648219987545098,"score_spread":0.23767748207600412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999104815","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":[0.010893156,0.00002160253,0.98815733,0.00016810317,0.000034345398,0.00016581197,0.0000051330285,0.00038740822,0.00016707924],"genre_scores_gemma":[0.5739613,0.0000015742827,0.42594305,0.00002887596,0.0000043497757,0.000019631045,5.8544254e-7,0.000007821156,0.000032776195],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887073,0.000055659377,0.00026066072,0.00035576322,0.00028763217,0.00016956218],"domain_scores_gemma":[0.99884367,0.0002878437,0.00019552883,0.00024157487,0.00030131347,0.0001300588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032509328,0.00016532696,0.00023835839,0.00036213713,0.00017328134,0.00021131613,0.0002243653,0.00006617189,0.000008368012],"category_scores_gemma":[0.000030168165,0.00014729524,0.00005870955,0.001568596,0.000087495944,0.00087254884,0.0000029375688,0.00015192069,0.0000018003094],"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":[0.00011441511,0.0002317516,0.00015946505,0.00011742047,0.00018038422,0.0000029375628,0.002197354,0.0959572,0.007930048,0.00012648135,0.000009322899,0.89297324],"study_design_scores_gemma":[0.0003085707,0.0002396622,0.00017891584,0.000054358894,0.00015389863,0.000009415297,0.00006216189,0.8354387,0.16201468,0.0013440602,0.0000115874245,0.00018394688],"about_ca_topic_score_codex":0.00024327585,"about_ca_topic_score_gemma":0.00013501439,"teacher_disagreement_score":0.8927893,"about_ca_system_score_codex":0.00006414889,"about_ca_system_score_gemma":0.00015952406,"threshold_uncertainty_score":0.6006526},"labels":[],"label_agreement":null},{"id":"W2004316630","doi":"10.1049/iet-com.2008.0362","title":"Beamforming technique to solve the hidden beam problem in wireless communication systems","year":2009,"lang":"en","type":"article","venue":"IET Communications","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Null (SQL); Beamforming; Beam (structure); Throughput; Antenna (radio); Wireless; Computer science; Planar array; Acoustics; Topology (electrical circuits); Mathematics; Telecommunications; Physics; Optics; Data mining; Combinatorics","score_opus":0.022178894716724098,"score_gpt":0.2964406925399306,"score_spread":0.27426179782320653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004316630","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":[0.0023167876,0.0003683345,0.96076864,0.015096498,0.00005493452,0.0022569045,0.000005811705,0.00069756655,0.018434538],"genre_scores_gemma":[0.61374974,0.00012122226,0.38533604,0.00017217077,0.0000049558644,0.000570395,0.000008765121,0.000007082473,0.000029633125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985569,0.00020298107,0.0005930718,0.0001999212,0.0002472598,0.00019984275],"domain_scores_gemma":[0.9947001,0.00038290786,0.00027079252,0.0043303748,0.00025908332,0.00005675616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012094866,0.00013711044,0.00020809504,0.00029734013,0.00033332888,0.00015622184,0.005158789,0.000086102256,0.0000013193054],"category_scores_gemma":[0.00008901984,0.00012094224,0.000055769982,0.001365139,0.00010852612,0.0007610932,0.0007757732,0.00033326235,0.000012994808],"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":[0.0000034084,0.00028593215,0.00014410316,0.000016888936,0.000010940545,2.4428186e-7,0.0034540931,0.00051892636,0.008391821,0.9260941,0.0011035965,0.059975933],"study_design_scores_gemma":[0.0013052498,0.0011185823,0.018391384,0.0045580333,0.00007928006,0.00019726536,0.00234941,0.3490007,0.1501428,0.40522122,0.065094665,0.0025413837],"about_ca_topic_score_codex":0.00055575644,"about_ca_topic_score_gemma":0.000117867996,"teacher_disagreement_score":0.6114329,"about_ca_system_score_codex":0.00014531836,"about_ca_system_score_gemma":0.00009441041,"threshold_uncertainty_score":0.9586399},"labels":[],"label_agreement":null},{"id":"W2007409848","doi":"10.1007/bf02687975","title":"A matched filter bank based DOA estimation for asynchronous multipath CDMA channels","year":2005,"lang":"en","type":"article","venue":"Journal of Electronics (China)","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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 British Columbia","funders":"","keywords":"Multipath propagation; Computer science; Code division multiple access; Asynchronous communication; Algorithm; Direction of arrival; Telecommunications link; Matched filter; Antenna array; Antenna (radio); Filter (signal processing); Base station; Electronic engineering; Real-time computing; Telecommunications; Engineering; Channel (broadcasting)","score_opus":0.01116012219285591,"score_gpt":0.27175109594900904,"score_spread":0.26059097375615314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007409848","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":[0.030012783,0.00022347386,0.9660171,0.0029066585,0.00027850125,0.00030556702,0.0000033828837,0.00010518756,0.00014730946],"genre_scores_gemma":[0.5554869,0.00001686472,0.44422275,0.0000973308,0.00010694801,0.00001528179,0.0000022429804,0.000014397743,0.000037261274],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998301,0.00007456094,0.00063753163,0.00020720922,0.00042513726,0.00035454077],"domain_scores_gemma":[0.9981124,0.00015826477,0.00090297183,0.0003428871,0.0003816309,0.00010185347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009816996,0.00018790488,0.00036101195,0.00036534507,0.00010090246,0.00012659984,0.0007086179,0.00010306146,0.000021961816],"category_scores_gemma":[0.00026317808,0.00017288137,0.00023523242,0.0003367964,0.000029008945,0.001030785,0.000045002893,0.00028121105,0.000005267472],"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":[0.0003044536,0.0010998464,0.00009612994,0.000232899,0.00020024068,0.000011434628,0.0015933957,0.3852751,0.029852297,0.03781068,0.008109054,0.53541446],"study_design_scores_gemma":[0.0007776012,0.0008686732,0.00030446541,0.00008427892,0.000024546382,0.00005049299,0.0000021049436,0.85923433,0.1272721,0.009234587,0.001984983,0.00016184628],"about_ca_topic_score_codex":0.000007127061,"about_ca_topic_score_gemma":0.0000065425024,"teacher_disagreement_score":0.53525263,"about_ca_system_score_codex":0.00035285373,"about_ca_system_score_gemma":0.00044327244,"threshold_uncertainty_score":0.70498973},"labels":[],"label_agreement":null},{"id":"W2009647803","doi":"10.1109/bsc.2010.5472961","title":"On the lower performance bounds for DOA estimators from linearly-modulated signals","year":2010,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Estimator; Additive white Gaussian noise; Algorithm; Direction of arrival; Mathematics; Gaussian; Antenna array; Circular buffer; Computer science; Antenna (radio); White noise; Statistics; Telecommunications; Physics","score_opus":0.013476297905024824,"score_gpt":0.26011623239096715,"score_spread":0.24663993448594232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009647803","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":[0.4575962,0.0000017851172,0.5385955,0.0005404519,0.00047709365,0.00022503508,0.0000036423978,0.00035031943,0.0022099798],"genre_scores_gemma":[0.8060185,9.5352834e-7,0.19332604,0.00029659807,0.000032337077,0.000044865883,0.0000024216934,0.000008567189,0.00026974833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991294,0.000018462712,0.00023452919,0.00023875864,0.00022803049,0.00015082618],"domain_scores_gemma":[0.9985291,0.0005286426,0.00011371288,0.00060012634,0.00018220651,0.000046258727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035108294,0.00011598159,0.00012565777,0.000076358505,0.00013639193,0.00014867578,0.0007233643,0.00007692775,0.000175104],"category_scores_gemma":[0.00023464364,0.000075848,0.000066730056,0.00025645466,0.000069826885,0.0003980781,0.000075063,0.00014881483,0.000045754277],"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":[0.000115268864,0.00089705363,0.0018128607,0.000053705124,0.00013417326,0.0000023493424,0.0010555019,0.0030901511,0.14937639,0.5970617,0.03790251,0.20849834],"study_design_scores_gemma":[0.00010377078,0.00018736506,0.0013126539,0.000021268674,0.0000035667836,9.0117464e-7,0.0000014136247,0.6401774,0.33377352,0.022922035,0.001381383,0.000114681105],"about_ca_topic_score_codex":0.000077214005,"about_ca_topic_score_gemma":0.000008085933,"teacher_disagreement_score":0.6370873,"about_ca_system_score_codex":0.000012059783,"about_ca_system_score_gemma":0.000051178224,"threshold_uncertainty_score":0.30929917},"labels":[],"label_agreement":null},{"id":"W2010697455","doi":"10.1109/glocom.2011.6134249","title":"A Maximum Likelihood Time Delay Estimator Using Importance Sampling","year":2011,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Estimator; Initialization; Computer science; Algorithm; Convergence (economics); Likelihood function; Importance sampling; Maximum likelihood; Function (biology); Sampling (signal processing); Mathematical optimization; Estimation theory; Mathematics; Statistics; Monte Carlo method","score_opus":0.05436994656824419,"score_gpt":0.2830021809736514,"score_spread":0.2286322344054072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010697455","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":[0.020187827,0.0000236205,0.9633676,0.000026269285,0.00011928429,0.0001366756,0.0000011089431,0.0007981797,0.01533946],"genre_scores_gemma":[0.18629053,0.0000013573047,0.8135668,0.00006945234,0.000011407462,0.0000071609406,5.68983e-7,0.000010941222,0.000041757954],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989051,0.000022275113,0.0003485518,0.00029201907,0.0002079491,0.00022409578],"domain_scores_gemma":[0.9990259,0.000042867563,0.00018385211,0.0005151667,0.00014437808,0.00008787932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002801241,0.00012797762,0.00017313483,0.00014200683,0.000077203294,0.000048387214,0.00058529637,0.000058696027,0.00020791037],"category_scores_gemma":[0.00006707262,0.00012154775,0.00006284274,0.00039649493,0.000039685194,0.0007323297,0.00017230278,0.000071218055,0.00007636142],"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":[0.000059381044,0.0012208075,0.032067798,0.0002540696,0.00023966648,0.00009815033,0.0048720315,0.0003951828,0.11632156,0.40284166,0.0036917487,0.43793795],"study_design_scores_gemma":[0.00020789352,0.00012971346,0.0024103196,0.00009823904,0.000018032495,0.0001166805,0.000013531286,0.6259399,0.20142452,0.16889483,0.000272996,0.00047334714],"about_ca_topic_score_codex":0.00012723058,"about_ca_topic_score_gemma":0.0000032876205,"teacher_disagreement_score":0.6255447,"about_ca_system_score_codex":0.000043160508,"about_ca_system_score_gemma":0.00009097353,"threshold_uncertainty_score":0.49565735},"labels":[],"label_agreement":null},{"id":"W2019202918","doi":"10.1109/glocom.2009.5425799","title":"Cramer-Rao Bound for NDA DOA Estimates of Square QAM-Modulated Signals","year":2009,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Cramér–Rao bound; Quadrature amplitude modulation; QAM; Upper and lower bounds; Mathematics; Additive white Gaussian noise; Expression (computer science); Algorithm; Signal-to-noise ratio (imaging); Square (algebra); White noise; Fisher information; Modulation (music); Estimation theory; Computer science; Statistics; Physics; Mathematical analysis; Acoustics; Bit error rate; Decoding methods; Geometry","score_opus":0.01995357389513819,"score_gpt":0.30765742099299737,"score_spread":0.2877038470978592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019202918","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":[0.016464345,0.000044261087,0.9784804,0.0007324932,0.00009905404,0.0003941633,0.0000062528916,0.0006092629,0.0031697773],"genre_scores_gemma":[0.5996368,0.000002432304,0.4001221,0.00011227298,0.000008070323,0.000012895004,0.0000036249833,0.0000051403094,0.00009664099],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988713,0.00002190233,0.00041992476,0.00026339837,0.000237167,0.00018626935],"domain_scores_gemma":[0.9987131,0.00022424896,0.00021287095,0.0004250093,0.00036851992,0.00005629887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000254555,0.00013328536,0.0002611602,0.00017721289,0.000062984516,0.00008087249,0.00052072003,0.00007072261,0.000051010258],"category_scores_gemma":[0.00019158132,0.0001202871,0.00010233796,0.00043939857,0.00005620024,0.00050971843,0.00005021152,0.00004643721,0.0000067056358],"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":[0.00004982075,0.00068182906,0.0004506436,0.00024788908,0.00010221169,0.0000028800757,0.00080403,0.0039174855,0.2506395,0.24844828,0.014790101,0.47986534],"study_design_scores_gemma":[0.00017401541,0.00038698365,0.0012113034,0.00006400375,0.000008311704,0.0000031899551,0.0000064691744,0.23629116,0.6410726,0.120194994,0.00044464064,0.00014235187],"about_ca_topic_score_codex":0.00007069633,"about_ca_topic_score_gemma":0.0000024811638,"teacher_disagreement_score":0.5831725,"about_ca_system_score_codex":0.00002443711,"about_ca_system_score_gemma":0.000059363374,"threshold_uncertainty_score":0.49051657},"labels":[],"label_agreement":null},{"id":"W2019492706","doi":"10.1109/tsp.2011.2180902","title":"Efficient Application of MUSIC Algorithm Under the Coexistence of Far-Field and Near-Field Sources","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":215,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Narrowband; Algorithm; Field (mathematics); Multiple signal classification; Computer science; Mathematics; Telecommunications","score_opus":0.02923972409227907,"score_gpt":0.26218649138815076,"score_spread":0.2329467672958717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019492706","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":[0.023507861,0.00006644481,0.9756345,0.00007727387,0.000044684846,0.00016434432,0.00000160121,0.00007722363,0.0004260722],"genre_scores_gemma":[0.9160997,0.000004360057,0.08376601,0.000088443165,0.000004555634,0.000023044813,8.0809336e-8,0.000005658254,0.000008125466],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99911624,0.00003701944,0.00030328537,0.00019742764,0.0002485115,0.00009751494],"domain_scores_gemma":[0.9991242,0.00019705099,0.00024592757,0.00022155808,0.00018079093,0.000030468926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002321436,0.00009427876,0.00014157472,0.00010170923,0.00015968582,0.00002956027,0.00031069104,0.00005957075,0.000012028207],"category_scores_gemma":[0.0000046452446,0.00007500058,0.000049494312,0.00043954924,0.00015266694,0.0001518447,0.0000047878366,0.00012578943,8.750551e-7],"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":[0.000020548021,0.00017798226,0.000013228705,0.00009106645,0.000014343704,1.7740108e-7,0.0032942276,0.0062155705,0.010696595,0.00077161094,0.0000037215448,0.97870094],"study_design_scores_gemma":[0.00006973361,0.00016526441,0.00009269075,0.000071997885,0.000015362315,0.00000486172,0.00018366624,0.4270816,0.5712388,0.001006543,0.000006872079,0.000062575025],"about_ca_topic_score_codex":0.00017958821,"about_ca_topic_score_gemma":0.000006657792,"teacher_disagreement_score":0.97863835,"about_ca_system_score_codex":0.0000105913905,"about_ca_system_score_gemma":0.000060367096,"threshold_uncertainty_score":0.30584347},"labels":[],"label_agreement":null},{"id":"W2021856733","doi":"10.1109/glocom.2005.1578050","title":"A vector-hydrophone~s minimal composition for finite estimation-variance in direction-finding near a rigid reflecting boundary","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Hydrophone; Acoustics; Underwater; Boundary (topology); Underwater acoustics; Sound pressure; Geology; Mathematics; Physics; Mathematical analysis","score_opus":0.03939539621145125,"score_gpt":0.33711664004476477,"score_spread":0.2977212438333135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021856733","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":[0.021876602,0.00031435722,0.958881,0.0036926237,0.00075520703,0.0013158126,0.00015615045,0.0009839134,0.012024306],"genre_scores_gemma":[0.55570984,0.000076382006,0.44357663,0.00015004977,0.000048111902,0.00028193896,0.00007253728,0.000016449338,0.00006806333],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99645346,0.0003422068,0.0013351786,0.0007269922,0.00043792682,0.0007042387],"domain_scores_gemma":[0.99616677,0.00069376035,0.00078293256,0.0016117899,0.000560186,0.00018456313],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000912706,0.00043127057,0.0005891,0.00041311726,0.0009259888,0.000653633,0.0020253232,0.0002576451,0.00005002037],"category_scores_gemma":[0.00035738834,0.00052248384,0.00021121417,0.001875154,0.00027281212,0.0017932131,0.00028988597,0.00042628634,0.000075149415],"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":[0.00035901656,0.0038250156,0.0032264236,0.00038589883,0.00040745866,0.000013340286,0.0040656175,0.107556425,0.012087557,0.20903794,0.022771707,0.6362636],"study_design_scores_gemma":[0.0010904594,0.00018940587,0.0036473037,0.00035020977,0.000034363886,0.0000761551,0.000038505586,0.9595549,0.006355031,0.009775674,0.018242327,0.0006456688],"about_ca_topic_score_codex":0.00068125495,"about_ca_topic_score_gemma":0.0012143817,"teacher_disagreement_score":0.85199845,"about_ca_system_score_codex":0.0010337337,"about_ca_system_score_gemma":0.00084838946,"threshold_uncertainty_score":0.99972266},"labels":[],"label_agreement":null},{"id":"W2025396508","doi":"10.1049/el.2010.2498","title":"Adaptive beamforming with joint robustness against covariance matrix uncertainty and signal steering vector mismatch","year":2010,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Adaptive beamformer; Covariance matrix; Robustness (evolution); Control theory (sociology); Diagonal; Beamforming; Covariance; Algorithm; Mathematics; Diagonal matrix; Computer science; Estimation of covariance matrices; Matrix (chemical analysis); Mathematical optimization; Statistics; Artificial intelligence","score_opus":0.007254560196589095,"score_gpt":0.21409262225561812,"score_spread":0.20683806205902902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025396508","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":[0.28790706,0.000040678413,0.71054626,0.00095558853,0.00008849833,0.00017741471,0.0000013672972,0.0002119385,0.00007117944],"genre_scores_gemma":[0.7258908,0.000008382646,0.2737807,0.00023027569,0.000033180942,0.000026459815,0.0000018453223,0.000015897953,0.000012440249],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872017,0.00003296339,0.00024144034,0.0003532518,0.00028319744,0.00036899443],"domain_scores_gemma":[0.9992203,0.000079066565,0.00019471065,0.00033362964,0.00009802442,0.00007427857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031780027,0.00018401633,0.0002173047,0.00012565702,0.00012541964,0.000108104854,0.00038148192,0.000061894934,0.0000040079644],"category_scores_gemma":[0.000021464597,0.00017095596,0.000038757873,0.000342919,0.00009394658,0.0005346606,0.00009153174,0.00041012946,0.0000012596471],"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":[0.00005934427,0.00006315745,0.00011163543,0.00008037454,0.000093573304,0.000019848438,0.00082550413,0.12210771,0.7884426,0.05575112,0.00027843833,0.032166716],"study_design_scores_gemma":[0.000481014,0.0002841877,0.00029684842,0.00010956716,0.000016197284,0.000077870136,0.000023399285,0.74040556,0.25654143,0.00056460063,0.00073361135,0.00046571236],"about_ca_topic_score_codex":0.000042553034,"about_ca_topic_score_gemma":0.00004786768,"teacher_disagreement_score":0.6182979,"about_ca_system_score_codex":0.00010992869,"about_ca_system_score_gemma":0.00014176096,"threshold_uncertainty_score":0.6971382},"labels":[],"label_agreement":null},{"id":"W2027607884","doi":"10.1109/camsap.2013.6714005","title":"Iterative root-MUSIC algorithm for DOA estimation","year":2013,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Covariance matrix; Algorithm; Sample mean and sample covariance; Mean squared error; Subspace topology; Direction of arrival; Computer science; Iterative method; Matrix (chemical analysis); Estimation of covariance matrices; Sample (material); Covariance; Mathematics; Statistics; Artificial intelligence","score_opus":0.016928170291453635,"score_gpt":0.2750173859254941,"score_spread":0.2580892156340404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027607884","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":[0.0006075937,0.000005885578,0.99293894,0.00037649635,0.00017145576,0.0005361945,0.0000018759147,0.00045808815,0.004903466],"genre_scores_gemma":[0.082130484,4.2335532e-7,0.91690326,0.00011691145,0.000019156229,0.00022933542,0.000004496809,0.000005418316,0.0005905463],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993103,0.00002102282,0.00021624991,0.00019197403,0.00014477786,0.000115650306],"domain_scores_gemma":[0.9991673,0.0001224799,0.00010175996,0.00025476498,0.00031309738,0.00004054897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013242844,0.000084577536,0.000110145025,0.00011644803,0.00005956688,0.00013892996,0.00029711807,0.00003887077,0.00010338479],"category_scores_gemma":[0.00006341032,0.00007312601,0.00004706848,0.00024634422,0.000024374514,0.0012858192,0.00006077408,0.000033823002,0.000067349145],"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":[3.111383e-7,0.000029985307,0.000012302368,0.00000894165,0.00000629605,7.8097536e-8,0.00023504502,0.00010568033,0.00050446205,0.056261938,0.0076653073,0.93516964],"study_design_scores_gemma":[0.00009452515,0.00007645989,0.0004903076,0.000012253327,0.000001925305,0.0000019729473,0.000005536019,0.871934,0.070526324,0.05641397,0.0003592487,0.00008346303],"about_ca_topic_score_codex":0.00007846316,"about_ca_topic_score_gemma":0.0000037952902,"teacher_disagreement_score":0.9350862,"about_ca_system_score_codex":0.000028844197,"about_ca_system_score_gemma":0.00002961511,"threshold_uncertainty_score":0.2981992},"labels":[],"label_agreement":null},{"id":"W2032643202","doi":"10.1109/comnet.2010.5699831","title":"Closed form expression for the Cramér-Rao lower bound for the DOA estimates from spatially and temporally correlated narrowband signals considering noncircular sources","year":2010,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Narrowband; Cramér–Rao bound; Upper and lower bounds; Expression (computer science); Correlation; Signal-to-noise ratio (imaging); Physics; Merge (version control); Mathematics; Algorithm; Statistics; Computer science; Mathematical analysis; Optics; Geometry","score_opus":0.023358284895738782,"score_gpt":0.27532831862227236,"score_spread":0.2519700337265336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032643202","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":[0.18876527,0.00016340354,0.80794555,0.00091462536,0.00053686247,0.0012395895,0.00001616054,0.0003066661,0.00011186464],"genre_scores_gemma":[0.67836666,0.000010480639,0.32106835,0.00017399347,0.00005319241,0.00020467349,0.000008186073,0.000020821579,0.000093682786],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985369,0.000028095705,0.0004666223,0.00040943318,0.00029564748,0.00026329423],"domain_scores_gemma":[0.9948858,0.003697246,0.0003281441,0.0006722101,0.00034042544,0.000076162585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075315003,0.00023367452,0.00027289093,0.00007523138,0.0006249205,0.00053946854,0.0007338224,0.00015435825,0.000059539518],"category_scores_gemma":[0.0007126467,0.00013582426,0.00012867844,0.00014900192,0.00024323462,0.0005805231,0.0001869455,0.00018200888,0.0000026211583],"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":[0.00019037857,0.00018447863,0.0027670604,0.000124764,0.00025062857,0.000002129606,0.004739887,0.001945221,0.92911243,0.007990655,0.005865629,0.04682673],"study_design_scores_gemma":[0.0008070652,0.00016259585,0.0010917828,0.00011627925,0.0000687031,0.000010115506,0.0000818875,0.48909009,0.4479758,0.053369876,0.0068984036,0.0003273786],"about_ca_topic_score_codex":0.0004936007,"about_ca_topic_score_gemma":0.00026624862,"teacher_disagreement_score":0.48960137,"about_ca_system_score_codex":0.000014649252,"about_ca_system_score_gemma":0.00011162994,"threshold_uncertainty_score":0.55387527},"labels":[],"label_agreement":null},{"id":"W2041043425","doi":"10.1109/ctit.2013.6749497","title":"Enhanced DOA estimation algorithms using MVDR and MUSIC","year":2013,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Multiple signal classification; Direction of arrival; Computer science; Algorithm; Smart antenna; Estimation; Speech recognition; Minimum-variance unbiased estimator; SIGNAL (programming language); Antenna (radio); Directional antenna; Mathematics; Telecommunications; Statistics; Engineering; Mean squared error","score_opus":0.024513871839680967,"score_gpt":0.27716265574255994,"score_spread":0.252648783902879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041043425","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":[0.049463954,0.0000102323165,0.94651383,0.000096853466,0.00010392423,0.00017444536,1.7562074e-7,0.0003223098,0.0033142555],"genre_scores_gemma":[0.45278844,0.0000015124475,0.54708785,0.00004023444,0.0000063123543,0.000009935402,3.191577e-7,0.0000026271566,0.00006275758],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939173,0.00001999983,0.00017596617,0.00017534845,0.00014031191,0.00009663853],"domain_scores_gemma":[0.9994865,0.000045629153,0.00008460908,0.0002173218,0.0001239197,0.000042034935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010592837,0.000071632225,0.0000971497,0.00010747395,0.000051099134,0.00010748411,0.00017478447,0.00003485561,0.00006190223],"category_scores_gemma":[0.000044379325,0.00006484877,0.000022719809,0.00024649774,0.00003543526,0.0008547364,0.00009220709,0.000035957833,0.000020355401],"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":[4.874184e-7,0.00003097977,0.000024173556,0.000023723629,0.000008921183,2.603059e-7,0.00042658686,0.0005729313,0.057391886,0.026161395,0.0003145483,0.9150441],"study_design_scores_gemma":[0.00005109499,0.000021573811,0.00060907897,0.000015459376,0.0000020979953,0.000005687061,0.000006655893,0.7821507,0.20342755,0.013630095,0.000010752891,0.00006926431],"about_ca_topic_score_codex":0.00032588415,"about_ca_topic_score_gemma":0.0000025196025,"teacher_disagreement_score":0.91497487,"about_ca_system_score_codex":0.000021009731,"about_ca_system_score_gemma":0.000021345268,"threshold_uncertainty_score":0.26444563},"labels":[],"label_agreement":null},{"id":"W2042391992","doi":"10.1109/wsa.2011.5741916","title":"Calibration for single-carrier preFDE transceivers based on property mapping principles","year":2011,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ryerson University","keywords":"Telecommunications link; Computer science; Transceiver; MIMO; Base station; Duplex (building); Channel (broadcasting); Calibration; Equalization (audio); Electronic engineering; Frequency domain; Transmission (telecommunications); Space-division multiple access; SIGNAL (programming language); Algorithm; Wireless; Telecommunications; Engineering; Mathematics","score_opus":0.12416597890199026,"score_gpt":0.24775882639685354,"score_spread":0.12359284749486328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042391992","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":[0.0011420813,0.0000010851073,0.9461083,0.00016958574,0.0000989418,0.0004969973,0.0000035058886,0.0004907024,0.051488843],"genre_scores_gemma":[0.6172778,2.474489e-7,0.3821863,0.00013601639,0.000007750738,0.00006274995,0.0000022375727,0.0000066806124,0.00032023384],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999232,0.000033644974,0.00021428341,0.00023462731,0.00016554428,0.00011988625],"domain_scores_gemma":[0.9994206,0.000055192824,0.00008823812,0.0002886174,0.00010309257,0.00004426457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019196421,0.00009229155,0.0001008521,0.00013345745,0.00006185534,0.000037539052,0.0003161606,0.000048350208,0.00003920666],"category_scores_gemma":[0.0000651453,0.00006493435,0.00006398527,0.00019006895,0.00003279777,0.0005222601,0.000012457002,0.00003564891,0.0000018279029],"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":[0.0002961186,0.0017070547,0.0025697488,0.00066258054,0.00009462132,0.0000041138233,0.0123403855,0.00420863,0.29097158,0.422406,0.0025007417,0.26223847],"study_design_scores_gemma":[0.00015602497,0.00022467317,0.00036547895,0.00004159491,0.000002988223,5.488853e-7,0.000011508352,0.42418525,0.57250744,0.001083404,0.0013241475,0.000096961216],"about_ca_topic_score_codex":0.00003808635,"about_ca_topic_score_gemma":0.0000061745973,"teacher_disagreement_score":0.6161357,"about_ca_system_score_codex":0.00003660499,"about_ca_system_score_gemma":0.00006158392,"threshold_uncertainty_score":0.2647946},"labels":[],"label_agreement":null},{"id":"W2044000385","doi":"10.1016/j.sigpro.2012.10.021","title":"Principles of minimum variance robust adaptive beamforming design","year":2012,"lang":"en","type":"article","venue":"Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":294,"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 Alberta","funders":"","keywords":"Robustness (evolution); Minimum-variance unbiased estimator; Beamforming; Adaptive beamformer; Computer science; Imperfect; Variance (accounting); Range (aeronautics); Electronic engineering; Engineering; Telecommunications; Mathematics; Statistics; Mean squared error","score_opus":0.07905418114954706,"score_gpt":0.2786842532869124,"score_spread":0.19963007213736533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044000385","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":[0.0012457254,0.00028558317,0.9936683,0.00002598906,0.00006546903,0.00014650518,7.568171e-7,0.0001761308,0.0043855384],"genre_scores_gemma":[0.52238876,0.0000012201832,0.47752038,0.000011782147,0.000024814208,0.000008717621,2.1358073e-7,0.000005616659,0.00003848604],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99886775,0.000059324542,0.0003644915,0.00017828314,0.000294028,0.00023609486],"domain_scores_gemma":[0.99898684,0.00013531333,0.000411479,0.00017738169,0.00022373535,0.000065243345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000729196,0.00011565125,0.00018361946,0.00013325474,0.000096334974,0.00004018606,0.00043514094,0.00005515981,0.000008681727],"category_scores_gemma":[0.000077302735,0.00010998765,0.000040637144,0.00047037585,0.00007862407,0.0017112587,0.000116809264,0.00008767646,0.0000030999288],"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":[0.00007268867,0.0004925766,0.001238192,0.0006041207,0.0000540851,0.0000026574776,0.008636423,0.03265603,0.09782701,0.14333406,0.00008536444,0.7149968],"study_design_scores_gemma":[0.00011051105,0.00011397569,0.00038324573,0.00038192194,0.00001194269,0.000012281191,0.000070338545,0.44395643,0.5505788,0.0040305313,0.00016161737,0.00018841593],"about_ca_topic_score_codex":0.000009840627,"about_ca_topic_score_gemma":2.3663058e-7,"teacher_disagreement_score":0.7148084,"about_ca_system_score_codex":0.000039541283,"about_ca_system_score_gemma":0.0001607947,"threshold_uncertainty_score":0.44851664},"labels":[],"label_agreement":null},{"id":"W2047530045","doi":"10.1155/2007/45194","title":"Recursive and Fast Recursive Capon Spectral Estimators","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Capon; Algorithm; Signal processing; Estimator; Recursive least squares filter; Statistical signal processing; Computer science; Spectral density estimation; Computational complexity theory; Adaptive filter; Mathematics; Digital signal processing; Beamforming; Statistics; Telecommunications; Fourier transform","score_opus":0.010060365212122056,"score_gpt":0.30398275454411977,"score_spread":0.2939223893319977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047530045","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":[0.04527662,0.0025641578,0.945607,0.0002464369,0.00032461982,0.00013990527,7.984226e-7,0.000107709726,0.005732756],"genre_scores_gemma":[0.7823209,0.00021854599,0.21722776,0.00010683481,0.000091662594,0.0000021205929,3.3137982e-7,0.000013596305,0.00001825296],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981714,0.00008193307,0.0005901075,0.00032027104,0.00048350167,0.0003528043],"domain_scores_gemma":[0.9986117,0.00026607697,0.00060547306,0.00012968978,0.00023005414,0.00015702395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010452624,0.00019951035,0.00026684706,0.0005331892,0.00019469681,0.00017946766,0.0004527211,0.00006529591,0.000008903779],"category_scores_gemma":[0.00021418415,0.0001819332,0.000051321676,0.0007424183,0.00014799753,0.002488747,0.00005721965,0.0005281978,0.0000029854614],"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":[0.0001070319,0.00010384637,0.0022658438,0.000061770275,0.000006564012,0.00015978425,0.00154221,0.0012713104,0.0012706064,0.011730107,0.000037050933,0.9814439],"study_design_scores_gemma":[0.0025767554,0.003165608,0.020023026,0.006612601,0.00003837204,0.0037930955,0.0016567168,0.036897734,0.39989364,0.5193027,0.0042735585,0.0017661965],"about_ca_topic_score_codex":0.000002200654,"about_ca_topic_score_gemma":0.0000048870384,"teacher_disagreement_score":0.9796777,"about_ca_system_score_codex":0.00016637552,"about_ca_system_score_gemma":0.000108169304,"threshold_uncertainty_score":0.74190205},"labels":[],"label_agreement":null},{"id":"W2050328357","doi":"10.1186/1687-6180-2014-133","title":"Joint mean angle of arrival, angular and Doppler spreads estimation in macrocell environments","year":2014,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Macrocell; Non-line-of-sight propagation; Estimator; Angle of arrival; Computer science; Doppler effect; Algorithm; Joint (building); Orthogonality; Channel (broadcasting); Direction of arrival; Cramér–Rao bound; Minimum mean square error; Time of arrival; Wireless; Telecommunications; Estimation theory; Mathematics; Statistics; Physics; Base station; Antenna (radio); Geometry; Engineering","score_opus":0.011800634351273653,"score_gpt":0.26937291122214674,"score_spread":0.2575722768708731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050328357","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":[0.14276697,0.00085322873,0.85517883,0.0000772251,0.00006471627,0.00010317449,5.586421e-7,0.000027890392,0.0009273962],"genre_scores_gemma":[0.861868,0.00013235518,0.13791342,0.000047006404,0.000017532439,0.0000035318446,4.917682e-7,0.000009628926,0.00000800029],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984144,0.00013075637,0.00061818666,0.00023888663,0.00041875357,0.0001790267],"domain_scores_gemma":[0.999079,0.000094617266,0.0005742471,0.0001379962,0.000047729038,0.00006640486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008701179,0.00014499498,0.0002674065,0.00039983753,0.000063974905,0.00007435106,0.0002936963,0.000046948233,0.000009335187],"category_scores_gemma":[0.0001033537,0.0001336464,0.0000346299,0.0003658963,0.000095698306,0.0016371418,0.000063758496,0.00024469392,0.0000015189476],"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":[0.000043075004,0.00023826258,0.005301466,0.00019409612,0.0000046217488,0.00001678024,0.0011324869,0.037559573,0.03152779,0.001460894,0.000011219687,0.92250973],"study_design_scores_gemma":[0.0010287832,0.0006039339,0.01298593,0.0018259804,0.000008301255,0.00018199398,0.00008305038,0.5794222,0.34181553,0.061215308,0.00047261993,0.00035641185],"about_ca_topic_score_codex":0.0000034606135,"about_ca_topic_score_gemma":0.000002683206,"teacher_disagreement_score":0.9221533,"about_ca_system_score_codex":0.00007595014,"about_ca_system_score_gemma":0.000032926284,"threshold_uncertainty_score":0.54499424},"labels":[],"label_agreement":null},{"id":"W2050507001","doi":"10.3390/s140609669","title":"Precise Calibration of a GNSS Antenna Array for Adaptive Beamforming Applications","year":2014,"lang":"en","type":"article","venue":"Sensors","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Calibration; Beamforming; Computer science; Antenna (radio); Antenna array; Electronic engineering; Interference (communication); Global Positioning System; GPS signals; Noise (video); Engineering; Telecommunications; Assisted GPS; Channel (broadcasting); Artificial intelligence; Physics","score_opus":0.01696874679609427,"score_gpt":0.261891165710614,"score_spread":0.2449224189145197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050507001","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":[0.0026920915,0.0000063279294,0.9951209,0.0001234294,0.00005476824,0.00038959473,0.000009631447,0.00015944884,0.0014438439],"genre_scores_gemma":[0.48090777,0.0000022378933,0.5188597,0.000016470824,0.000017622606,0.000080769896,0.0000034298628,0.0000058582345,0.000106129955],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993203,0.00003311059,0.0002457914,0.00017773347,0.00013058702,0.000092436814],"domain_scores_gemma":[0.99900407,0.00019349506,0.00020337295,0.0003180237,0.00024900117,0.000032055734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019320074,0.00006721854,0.00012926217,0.000096506286,0.000049685477,0.000015639464,0.00021275252,0.000040372346,0.0000016218078],"category_scores_gemma":[0.0001277481,0.00006735238,0.000056826906,0.0002741201,0.000040705916,0.0002450584,0.000027283308,0.00003294666,0.0000019059976],"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":[0.00004235316,0.00023151656,0.0001808098,0.00020259513,0.000047968835,1.8450127e-7,0.002243703,0.0039152936,0.28873304,0.5326436,0.0003837395,0.17137519],"study_design_scores_gemma":[0.000090608104,0.00007531306,0.000057457648,0.000026225813,0.000005958823,0.000001993493,0.000023759849,0.38811168,0.5844335,0.025846977,0.001256568,0.0000699779],"about_ca_topic_score_codex":0.000014978277,"about_ca_topic_score_gemma":0.0000048411634,"teacher_disagreement_score":0.50679666,"about_ca_system_score_codex":0.000016438398,"about_ca_system_score_gemma":0.00003706812,"threshold_uncertainty_score":0.27465504},"labels":[],"label_agreement":null},{"id":"W2050978411","doi":"10.1121/1.4874224","title":"An eigenvector-based test for local stationarity applied to array processing","year":2014,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Office of Naval Research","keywords":"Sonar; Eigenvalues and eigenvectors; Covariance matrix; Computation; Computer science; Covariance; Algorithm; Data processing; Array processing; Sample mean and sample covariance; Matrix (chemical analysis); Interval (graph theory); Data Matrix; Mathematics; Signal processing; Statistics; Artificial intelligence; Digital signal processing","score_opus":0.012336612499693084,"score_gpt":0.2782046923048999,"score_spread":0.2658680798052068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050978411","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":[0.0010654719,0.000007177295,0.9955904,0.0029824951,0.000061597006,0.00018571346,0.000004138106,0.00003303,0.00006997378],"genre_scores_gemma":[0.52962196,0.0000012107269,0.46949992,0.00083109457,0.000035860623,0.0000028901122,1.7366943e-7,0.0000047734857,0.000002097346],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988239,0.000082434424,0.00039063033,0.00009951639,0.00045766364,0.00014589024],"domain_scores_gemma":[0.9975983,0.0010171918,0.0005305908,0.00031652927,0.00045081117,0.00008656905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000992725,0.00009355264,0.00022584689,0.000024704614,0.0001688003,0.000029969566,0.0010619186,0.00003898707,0.000003882706],"category_scores_gemma":[0.00041914452,0.000054912827,0.00015913519,0.00036828744,0.0003393786,0.00014722253,0.00005584276,0.00015996544,6.6706235e-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":[0.00014383547,0.0007014155,0.00015448414,0.00020147309,0.000060150072,5.98818e-8,0.0023731615,0.30004027,0.2001523,0.00057734933,0.0085387165,0.4870568],"study_design_scores_gemma":[0.00017879462,0.0005404462,0.00085942424,0.00004919239,0.000042966552,0.000003163811,0.00018560627,0.9303643,0.060756586,0.006523192,0.00041621993,0.000080106656],"about_ca_topic_score_codex":0.000014975072,"about_ca_topic_score_gemma":2.8903202e-7,"teacher_disagreement_score":0.63032407,"about_ca_system_score_codex":0.000057635385,"about_ca_system_score_gemma":0.0001750176,"threshold_uncertainty_score":0.223928},"labels":[],"label_agreement":null},{"id":"W2053948140","doi":"10.1109/iscas.2013.6572309","title":"Sparse linear arrays for estimating and tracking DOAs of signals with known waveforms","year":2013,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Waveform; Computer science; Direction of arrival; SIGNAL (programming language); Algorithm; Sensor array; Antenna array; Filter (signal processing); Smart antenna; Antenna (radio); Computer vision; Telecommunications; Radar; Directional antenna","score_opus":0.02599578083782897,"score_gpt":0.27323990550258986,"score_spread":0.2472441246647609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053948140","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":[0.021498334,0.000007214588,0.9760997,0.0001622941,0.000040202813,0.00038306759,9.380709e-7,0.00018100867,0.0016272215],"genre_scores_gemma":[0.36072704,8.3520564e-7,0.6391344,0.000022571374,0.000012216411,0.000031461845,5.0551495e-7,0.0000051066622,0.00006583532],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992653,0.000010753278,0.00027578967,0.00017561858,0.0001472105,0.00012532125],"domain_scores_gemma":[0.99914575,0.00013334575,0.00019143532,0.0002093059,0.00027417278,0.000045973527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023626006,0.00009104063,0.0001755503,0.000095218275,0.000048203612,0.000056268305,0.00020906431,0.000033999087,0.000020822947],"category_scores_gemma":[0.00009611863,0.00006247628,0.000029022214,0.00018200139,0.000056257188,0.0008078149,0.00005320501,0.000039782808,0.000002414074],"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":[0.000019060908,0.00020351022,0.00097399607,0.0005646205,0.00007061008,9.250537e-7,0.0025158846,0.009714765,0.04794554,0.06733664,0.0011592407,0.8694952],"study_design_scores_gemma":[0.00012690168,0.00018096306,0.00022543342,0.00008732111,0.0000039272327,0.000005371716,0.00002207305,0.73843807,0.25283083,0.007965244,0.000033448327,0.00008041823],"about_ca_topic_score_codex":0.00012388315,"about_ca_topic_score_gemma":0.0000047257377,"teacher_disagreement_score":0.8694148,"about_ca_system_score_codex":0.000009008508,"about_ca_system_score_gemma":0.000029881783,"threshold_uncertainty_score":0.2547709},"labels":[],"label_agreement":null},{"id":"W2056164473","doi":"10.1007/bf01201977","title":"Direction finding using data-supported optimization","year":2001,"lang":"en","type":"article","venue":"Circuits Systems and Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Maximum likelihood; Computer science; Likelihood function; Function (biology); Data point; Optimization problem; Mathematical optimization; Algorithm; Data mining; Mathematics; Estimation theory; Statistics","score_opus":0.08092773395973421,"score_gpt":0.30822431848341153,"score_spread":0.22729658452367732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056164473","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":[0.010705478,0.0005660865,0.9865498,0.000014640602,0.00017290258,0.00017314265,0.0000021746011,0.00030103824,0.0015147333],"genre_scores_gemma":[0.9779242,0.00001960024,0.021898774,0.000010731209,0.000069305606,0.0000061665646,0.000009323159,0.000011703622,0.000050182105],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878395,0.000060923285,0.00037698212,0.0003661232,0.00025065534,0.00016138326],"domain_scores_gemma":[0.99910545,0.000038125105,0.0003283183,0.00027397665,0.00019416858,0.000059953993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005495706,0.000115507326,0.00019195504,0.00021209111,0.00025482205,0.00036416203,0.00032780183,0.00007148228,0.0000055033674],"category_scores_gemma":[0.000041154883,0.000115964394,0.00001642436,0.00060986,0.000034123004,0.001994204,0.0001028981,0.000072185336,7.4091804e-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":[0.0000054955735,0.00010558138,0.004500323,0.0007684218,0.000040872772,0.000019542622,0.0011968224,0.13069536,0.040790983,0.0027177008,0.00011000434,0.8190489],"study_design_scores_gemma":[0.0000921835,0.000019565261,0.00021843148,0.00031552842,0.000012051888,0.00015282186,0.00004609401,0.9974549,0.0012532158,0.00013414002,0.00016764404,0.00013342634],"about_ca_topic_score_codex":0.00009800699,"about_ca_topic_score_gemma":7.489829e-7,"teacher_disagreement_score":0.96721876,"about_ca_system_score_codex":0.0000452783,"about_ca_system_score_gemma":0.000093455084,"threshold_uncertainty_score":0.47288907},"labels":[],"label_agreement":null},{"id":"W2056506919","doi":"10.1109/ccece.2008.4564699","title":"A hybrid approach involving artificial neural network and ant colony optimization for direction of arrival estimation","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Tarbiat Modares University; Iran Telecommunication Research Center","keywords":"Ant colony optimization algorithms; Computer science; Artificial neural network; Ant colony; Artificial intelligence; Mathematical optimization; Perceptron; Mathematics","score_opus":0.021758346707454673,"score_gpt":0.20772083747345998,"score_spread":0.18596249076600532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056506919","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":[0.07941401,0.000047696358,0.91962785,0.00012682631,0.00011720881,0.0003714215,0.0000037358066,0.0001538492,0.00013738497],"genre_scores_gemma":[0.8141409,0.00004440889,0.18565238,0.00003169258,0.000059364338,0.000050419956,0.000006152243,0.000010443823,0.000004247536],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870497,0.0000113754595,0.00036100953,0.00040201764,0.00017996438,0.00034064645],"domain_scores_gemma":[0.9990242,0.00008076414,0.00016664283,0.00009641714,0.0004094807,0.00022246256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001797948,0.00020443174,0.0003156194,0.00035799242,0.00016906744,0.00014127074,0.00023960434,0.00008782019,0.000001816033],"category_scores_gemma":[0.00010089675,0.0002190553,0.000038953247,0.00041884396,0.000068844216,0.000459979,0.00004845133,0.00016160325,1.5029852e-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":[0.000058339305,0.000107428816,0.0011608875,0.00037325115,0.000058695714,0.0000043863174,0.0012059758,0.17811398,0.0020611826,0.62608325,0.0003672082,0.1904054],"study_design_scores_gemma":[0.00013967615,0.00034715643,0.0013512283,0.00008920856,0.00000936452,0.00005128854,0.0000037285329,0.9935831,0.002074353,0.0021205547,0.000018770244,0.00021157513],"about_ca_topic_score_codex":0.0005207961,"about_ca_topic_score_gemma":0.000027901144,"teacher_disagreement_score":0.8154691,"about_ca_system_score_codex":0.000075781034,"about_ca_system_score_gemma":0.00021895897,"threshold_uncertainty_score":0.89328164},"labels":[],"label_agreement":null},{"id":"W2061903575","doi":"10.1007/s11760-014-0700-1","title":"Joint delay and direction of arrivals estimation in mobile communications","year":2014,"lang":"en","type":"article","venue":"Signal Image and Video Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Multilateration; Estimator; Computer science; Direction of arrival; Algorithm; Multipath propagation; Beamforming; Channel (broadcasting); Mathematics; Telecommunications; Statistics; Antenna (radio); Azimuth","score_opus":0.01856281537331634,"score_gpt":0.29714654241949073,"score_spread":0.2785837270461744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061903575","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":[0.04099928,0.00044836584,0.9569825,0.00011471473,0.000013941538,0.00013714151,6.617355e-7,0.00008636439,0.0012170416],"genre_scores_gemma":[0.75397676,0.000049499402,0.24591723,0.000018449346,0.0000036039323,0.000023616032,0.0000011883316,0.000003858697,0.0000057643088],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992397,0.000097291755,0.0003123068,0.00015967111,0.00011139635,0.00007967531],"domain_scores_gemma":[0.9992674,0.00012527978,0.00021182791,0.00022514329,0.00013989529,0.000030459016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065542123,0.000073771815,0.00015793256,0.00018639982,0.0000848843,0.00008413847,0.00016821937,0.000036075417,0.0000018817173],"category_scores_gemma":[0.00013192663,0.00007253777,0.00001660283,0.00028800024,0.00012851959,0.0010078179,0.0001241941,0.00007339977,4.6435764e-7],"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":[0.000003534213,0.0000551929,0.0005022051,0.00018116712,0.0000032289693,2.2707995e-7,0.0010121249,0.00012782433,0.07669774,0.0019095934,0.000016157726,0.919491],"study_design_scores_gemma":[0.00015302117,0.00008930365,0.002761424,0.00031282127,0.0000073965375,0.000012021431,0.000031330583,0.7690861,0.210111,0.01726006,0.00007680917,0.00009865804],"about_ca_topic_score_codex":0.00006737031,"about_ca_topic_score_gemma":0.000008257706,"teacher_disagreement_score":0.91939235,"about_ca_system_score_codex":0.000013862156,"about_ca_system_score_gemma":0.00002911861,"threshold_uncertainty_score":0.29580042},"labels":[],"label_agreement":null},{"id":"W2064709514","doi":"10.1109/icassp.2014.6854397","title":"A new importance-sampling ML estimator of time delays and angles of arrival in multipath environments","year":2014,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Multipath propagation; Estimator; Computer science; Arrival time; Sampling (signal processing); Time of arrival; Angle of arrival; Real-time computing; Statistics; Telecommunications; Mathematics; Engineering; Transport engineering; Wireless","score_opus":0.01057899823785429,"score_gpt":0.24047932333003894,"score_spread":0.22990032509218464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064709514","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":[0.21058053,0.000021755131,0.78846043,0.000022962513,0.00002143344,0.00010479989,0.0000016641238,0.000048082115,0.00073836924],"genre_scores_gemma":[0.51966465,0.0000056931867,0.48027998,0.000007848434,0.0000035156336,0.0000025923687,7.516118e-7,0.000003884617,0.000031088202],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991076,0.000026861158,0.00038455162,0.00019634563,0.00018143086,0.00010318529],"domain_scores_gemma":[0.9992902,0.00012593354,0.0002227906,0.0002889564,0.000017134766,0.000054928012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025918224,0.00008881923,0.00022148073,0.0001319267,0.0000136632825,0.000009854763,0.00026047288,0.00004390427,0.000024410214],"category_scores_gemma":[0.00008272455,0.00008382666,0.000027190965,0.00012885421,0.000050973304,0.00026843528,0.00012151689,0.00004099076,0.0000030085155],"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":[0.00004644787,0.00048120975,0.16303954,0.00023929065,0.00006750385,0.000003105655,0.0018100367,0.0035199989,0.28556713,0.055109497,0.00033090377,0.48978534],"study_design_scores_gemma":[0.0006058439,0.0002193556,0.061551817,0.00013504275,0.000009974004,0.000005698784,0.0000130294475,0.53533155,0.38932157,0.01241157,0.00018395112,0.00021060868],"about_ca_topic_score_codex":0.00020829763,"about_ca_topic_score_gemma":0.0000124923245,"teacher_disagreement_score":0.53181154,"about_ca_system_score_codex":0.000015649523,"about_ca_system_score_gemma":0.000026833664,"threshold_uncertainty_score":0.34183517},"labels":[],"label_agreement":null},{"id":"W2064713618","doi":"10.1049/ip-rsn:20020124","title":"Stochastic Cramer–Rao bound for direction estimation in unknown noise fields","year":2002,"lang":"en","type":"article","venue":"IEE Proceedings - Radar Sonar and Navigation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Stiftelsen för Strategisk Forskning","keywords":"Cramér–Rao bound; Noise (video); Upper and lower bounds; Algorithm; Applied mathematics; Computer science; Estimation; Mathematics; Estimation theory; Mathematical optimization; Mathematical analysis; Artificial intelligence; Engineering","score_opus":0.01542150011354054,"score_gpt":0.2579245318020412,"score_spread":0.24250303168850068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064713618","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":[0.22366108,0.00015393282,0.7740451,0.00056800136,0.00019313637,0.0005652621,0.0000030307283,0.00028064655,0.0005298061],"genre_scores_gemma":[0.90912753,0.000023358316,0.090557285,0.000034512163,0.000035856352,0.00010568586,0.000006836803,0.000010738936,0.00009819296],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896014,0.000009436299,0.00033008723,0.00031431642,0.00022011346,0.00016589492],"domain_scores_gemma":[0.9993666,0.000088698325,0.00020572031,0.0000864125,0.0002012679,0.000051326766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029943412,0.00013391535,0.0001708293,0.0002113498,0.00013541622,0.00013490893,0.00015845477,0.000111918045,0.000004591582],"category_scores_gemma":[0.00010914049,0.00014460193,0.000041402945,0.00048105657,0.000049923143,0.0012261597,0.000032967208,0.00011346323,0.0000029915084],"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":[0.000055590026,0.00031088517,0.00069554494,0.00054913264,0.000026064827,0.0000011495415,0.007558582,0.00074906356,0.01194054,0.0694462,0.0022180018,0.90644926],"study_design_scores_gemma":[0.0005036144,0.00024851758,0.0015138029,0.00026464972,0.000015471982,0.000024033146,0.00004103812,0.93402267,0.022646261,0.040000476,0.0004893507,0.00023014616],"about_ca_topic_score_codex":0.000058484966,"about_ca_topic_score_gemma":0.0000052943637,"teacher_disagreement_score":0.93327355,"about_ca_system_score_codex":0.00007494119,"about_ca_system_score_gemma":0.000015309442,"threshold_uncertainty_score":0.5896695},"labels":[],"label_agreement":null},{"id":"W2064727507","doi":"10.1109/icecs.2013.6815537","title":"Accurate detection and estimation of radio signals using a 2D novel smart antenna array","year":2013,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Narrowband; Antenna array; Sensor array; Smart antenna; Computer science; Direction of arrival; Antenna (radio); SIGNAL (programming language); Direction finding; Electronic engineering; Signal-to-noise ratio (imaging); Array gain; Acoustics; Algorithm; Telecommunications; Dipole antenna; Physics; Engineering","score_opus":0.029198375474493925,"score_gpt":0.2745048381744103,"score_spread":0.24530646269991638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064727507","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":[0.09627598,0.000013952329,0.9026982,0.000073523035,0.00008626314,0.00019438771,8.449624e-7,0.00017660635,0.00048020278],"genre_scores_gemma":[0.6314991,0.0000029925495,0.3684353,0.0000192896,0.0000044062695,0.000007947493,3.0962934e-7,0.000003838422,0.000026813537],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991819,0.00003307768,0.00031797425,0.00019526227,0.00016886616,0.00010288747],"domain_scores_gemma":[0.99912363,0.00009031109,0.00022958106,0.00023126313,0.00028249776,0.000042718304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021192679,0.00009048252,0.00015453373,0.0001680838,0.000050042538,0.00007876667,0.00015164222,0.00004987375,0.000021628875],"category_scores_gemma":[0.00013367952,0.00008402455,0.000032936907,0.00039137833,0.000048970407,0.0012661605,0.00005158295,0.000046801397,0.0000054370194],"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":[0.0000019482077,0.00003410722,0.00006443535,0.000031967473,0.000009260697,1.1730648e-7,0.00013440882,0.0008891291,0.95889884,0.0014402217,0.0000136815215,0.038481876],"study_design_scores_gemma":[0.00007029019,0.000029743473,0.0014929448,0.000025615525,0.000003647323,0.000014526796,0.0000064891747,0.5336707,0.46196002,0.0026696997,0.0000040069867,0.000052279902],"about_ca_topic_score_codex":0.00038686633,"about_ca_topic_score_gemma":0.0000068451063,"teacher_disagreement_score":0.5352231,"about_ca_system_score_codex":0.00002611323,"about_ca_system_score_gemma":0.000040935134,"threshold_uncertainty_score":0.3426422},"labels":[],"label_agreement":null},{"id":"W2071032643","doi":"10.1109/msna.2012.6324523","title":"Design and simulation of a variable bit load adaptive OFDM transceiver for frequency selective channel","year":2012,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Channel (broadcasting); Transceiver; Adaptive beamformer; Electronic engineering; Beamforming; Least mean squares filter; Phase-shift keying; Bit error rate; Signal-to-noise ratio (imaging); Interference (communication); Modulation (music); Mean squared error; Algorithm; Adaptive filter; Engineering; Telecommunications; Mathematics; Wireless; Acoustics; Statistics","score_opus":0.03723823595802756,"score_gpt":0.27657661151588814,"score_spread":0.23933837555786058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071032643","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":[0.00074498914,0.000055017306,0.9961929,0.0000206904,0.000056622222,0.00055026193,0.0000028636337,0.00012335432,0.0022533014],"genre_scores_gemma":[0.5592533,0.0000016551588,0.44065434,0.000013473636,0.0000071298514,0.00002978404,3.2007517e-7,0.000003523452,0.00003651932],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993213,0.000049662234,0.00018974529,0.00015118427,0.0001479358,0.00014018462],"domain_scores_gemma":[0.9989868,0.00031781793,0.00011655256,0.0001303261,0.00040567757,0.000042828095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044325672,0.00008345596,0.00014325787,0.00010065693,0.00004067536,0.000011106541,0.00013450204,0.000056376823,0.000009050063],"category_scores_gemma":[0.00007688187,0.000077291275,0.000028781833,0.00031900383,0.00003537332,0.0009011365,0.000015407679,0.000033496806,9.4728085e-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":[0.00027357016,0.00089968997,0.0005757534,0.00028559525,0.0002643983,2.9198867e-7,0.021271216,0.16556266,0.09614661,0.66176057,0.00068129407,0.05227833],"study_design_scores_gemma":[0.00021650635,0.0002718772,0.00037901753,0.000021755084,0.00001312779,0.0000010781135,0.000013762079,0.7633249,0.18950301,0.046147477,0.0000149422,0.00009250444],"about_ca_topic_score_codex":0.000121207755,"about_ca_topic_score_gemma":0.0000010905245,"teacher_disagreement_score":0.6156131,"about_ca_system_score_codex":0.00004665575,"about_ca_system_score_gemma":0.000077470046,"threshold_uncertainty_score":0.31518468},"labels":[],"label_agreement":null},{"id":"W2074557689","doi":"10.1155/2011/283020","title":"Improvement on EVESPA for Beamforming and Direction of Arrival Estimation","year":2011,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Beamforming; Direction of arrival; Computer science; Computational complexity theory; Algorithm; Signal subspace; Matrix (chemical analysis); Reduction (mathematics); Subspace topology; Covariance matrix; Adaptive beamformer; Estimation; SIGNAL (programming language); Mathematical optimization; Mathematics; Telecommunications; Artificial intelligence; Noise (video); Engineering","score_opus":0.02383832453633264,"score_gpt":0.30426548861623987,"score_spread":0.2804271640799072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074557689","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":[0.038479015,0.00028812294,0.95932513,0.000039405528,0.0001815151,0.00020041759,8.795274e-7,0.00005119338,0.0014343349],"genre_scores_gemma":[0.73350424,0.00005607909,0.26635537,0.000030538475,0.000024910134,0.000012727934,2.7978956e-7,0.000007607039,0.000008245308],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987964,0.00003655617,0.0005203355,0.00019991529,0.00029541773,0.00015135329],"domain_scores_gemma":[0.99888265,0.0001275276,0.00066737126,0.0000948734,0.00017667052,0.000050884766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065742596,0.00012548706,0.000195759,0.00035634974,0.00012299651,0.00005152974,0.00022547877,0.000037382088,0.0000033296487],"category_scores_gemma":[0.00013569776,0.00011031732,0.00004402138,0.00028254255,0.0000531695,0.0018033121,0.000029408477,0.00016358713,3.0617082e-7],"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":[0.000103615916,0.00010531361,0.0002567951,0.0001176143,0.0000037562324,0.0000012194773,0.0006163747,0.0021492115,0.00600692,0.002829706,0.0000030624449,0.98780644],"study_design_scores_gemma":[0.0008536295,0.0028474398,0.0019704858,0.0017771766,0.000013039623,0.00005813064,0.0001164625,0.2556182,0.64981794,0.08639371,0.00025176155,0.00028202595],"about_ca_topic_score_codex":0.000002486343,"about_ca_topic_score_gemma":0.000001031835,"teacher_disagreement_score":0.9875244,"about_ca_system_score_codex":0.00007504774,"about_ca_system_score_gemma":0.00005466453,"threshold_uncertainty_score":0.44986096},"labels":[],"label_agreement":null},{"id":"W2074853220","doi":"10.1109/tsp.2004.838934","title":"Wideband array signal processing using MCMC methods","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Narrowband; Wideband; Reversible-jump Markov chain Monte Carlo; Markov chain Monte Carlo; Algorithm; Maximum a posteriori estimation; Computer science; Robustness (evolution); Array processing; Signal processing; Interpolation (computer graphics); Monte Carlo method; Bayesian probability; Direction of arrival; Mathematics; Statistics; Artificial intelligence; Electronic engineering; Maximum likelihood; Telecommunications; Engineering; Radar","score_opus":0.0448059475000119,"score_gpt":0.3486716157430472,"score_spread":0.30386566824303535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074853220","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":[0.0011690829,0.00023002437,0.99596447,0.00021913214,0.00012303903,0.0002388527,0.00000283533,0.00076499424,0.001287566],"genre_scores_gemma":[0.5230333,0.0000032682865,0.47669196,0.00011372184,0.000052271724,0.000019636469,2.9469456e-7,0.00002312406,0.00006240283],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99747944,0.00019990491,0.00070424087,0.0006147687,0.0005857541,0.0004158845],"domain_scores_gemma":[0.9985614,0.00018054078,0.00039971576,0.00031200904,0.00039123523,0.0001550992],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008479481,0.0003294231,0.00038172593,0.00055813015,0.00063467637,0.000368142,0.0006343264,0.00016007914,0.00008315047],"category_scores_gemma":[0.000008395823,0.00032961796,0.00016175532,0.0013068558,0.00015715288,0.0026418506,0.000004779056,0.0004257256,0.0000115931],"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":[0.000018631528,0.00015548077,0.00000317916,0.00009294504,0.00001419328,0.0000013234484,0.00063808233,0.03559781,0.16381595,0.00004112729,0.000010331663,0.799611],"study_design_scores_gemma":[0.00016611104,0.00006620271,0.0000043663026,0.00026917644,0.000028419649,0.000037924485,0.0000273932,0.41654846,0.58151263,0.000791381,0.00031113808,0.00023680588],"about_ca_topic_score_codex":0.000023156095,"about_ca_topic_score_gemma":0.000004918981,"teacher_disagreement_score":0.79937416,"about_ca_system_score_codex":0.00019746994,"about_ca_system_score_gemma":0.00041225032,"threshold_uncertainty_score":0.9999156},"labels":[],"label_agreement":null},{"id":"W2077709167","doi":"10.1016/j.sigpro.2007.11.006","title":"Experimental antenna array calibration with artificial neural networks","year":2007,"lang":"en","type":"article","venue":"Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Université Laval","funders":"","keywords":"Artificial neural network; Computer science; Perceptron; Calibration; Antenna (radio); Antenna array; Context (archaeology); Network topology; Algorithm; Electronic engineering; Artificial intelligence; Engineering; Mathematics; Telecommunications","score_opus":0.019065685617639164,"score_gpt":0.2754845854648529,"score_spread":0.2564188998472137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077709167","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":[0.015612899,0.00013159306,0.98286307,0.00006708984,0.00007280049,0.000083229585,2.1915478e-7,0.00031715594,0.000851947],"genre_scores_gemma":[0.91723263,2.388701e-7,0.08256561,0.00008995719,0.000082240724,0.000004496717,0.0000019915694,0.000009165856,0.000013681453],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99905425,0.00002477466,0.0002502027,0.00022733319,0.00025475523,0.00018866136],"domain_scores_gemma":[0.999511,0.000033266617,0.0001598204,0.00012204581,0.00011884977,0.00005503566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024058884,0.00010140497,0.00010585807,0.0000866546,0.00013417732,0.00015434012,0.00019920612,0.000046129528,0.000008698008],"category_scores_gemma":[0.0000075380253,0.00008927869,0.000025131165,0.0004309799,0.00006670273,0.0010138075,0.000031739186,0.000098968405,9.734728e-7],"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":[0.00010349592,0.00019790074,0.00054375036,0.000039129754,0.000009938243,0.000029916087,0.0011958313,0.004318931,0.64769334,0.005016682,0.00005649652,0.34079456],"study_design_scores_gemma":[0.000046899,0.000071091985,0.00009178994,0.00002984994,0.0000018394876,0.000018346362,0.000052248066,0.47472823,0.52430075,0.0005721217,0.000008062092,0.00007876277],"about_ca_topic_score_codex":0.0000076661145,"about_ca_topic_score_gemma":0.000002955462,"teacher_disagreement_score":0.90161973,"about_ca_system_score_codex":0.00003017038,"about_ca_system_score_gemma":0.00006423892,"threshold_uncertainty_score":0.36406794},"labels":[],"label_agreement":null},{"id":"W2079475265","doi":"10.1109/vetecs.2012.6240336","title":"Stochastic NDA CRLB for DOA Estimation over SIMO Systems","year":2012,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Cramér–Rao bound; Distortion (music); Additive white Gaussian noise; Algorithm; Direction of arrival; Constant (computer programming); Channel (broadcasting); Gaussian; Mathematics; Circular buffer; Gaussian noise; Signal-to-noise ratio (imaging); Computer science; Upper and lower bounds; Complex normal distribution; Estimation theory; Telecommunications; Physics; Mathematical analysis; Bandwidth (computing)","score_opus":0.02224639162321665,"score_gpt":0.3007901257696325,"score_spread":0.27854373414641587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079475265","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":[0.0014357157,0.00004059313,0.9945854,0.000069412396,0.0007425694,0.00044669394,0.0000028316097,0.00052917807,0.0021476294],"genre_scores_gemma":[0.7309526,3.529652e-7,0.268575,0.000035508012,0.000045401503,0.0000898463,0.0000024452975,0.0000066343255,0.00029218657],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916947,0.000024541052,0.0002556241,0.00014763273,0.00021392922,0.0001888317],"domain_scores_gemma":[0.9991191,0.00021602749,0.00013824335,0.0003217361,0.00013390572,0.00007100437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037284897,0.00009285291,0.00013444634,0.00012312492,0.000059223425,0.00008073729,0.00028409497,0.000051162857,0.00001574691],"category_scores_gemma":[0.00018215294,0.000082689505,0.000047718702,0.00021628987,0.00002131512,0.0010933816,0.000061243976,0.00003569995,0.000027450542],"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":[0.0000075706703,0.00015116506,0.0002499909,0.00017343074,0.000024522371,1.0748631e-7,0.0004916046,0.02510943,0.0013857657,0.92919457,0.009698126,0.033513695],"study_design_scores_gemma":[0.0001293049,0.0000554813,0.0006499423,0.000036728496,0.00000743269,0.000004462105,0.000008014982,0.9856261,0.008308149,0.0043278723,0.0007228182,0.00012371207],"about_ca_topic_score_codex":0.00007065197,"about_ca_topic_score_gemma":9.569786e-7,"teacher_disagreement_score":0.96051663,"about_ca_system_score_codex":0.00005206166,"about_ca_system_score_gemma":0.000030099822,"threshold_uncertainty_score":0.337198},"labels":[],"label_agreement":null},{"id":"W2080927857","doi":"10.1155/s1110865704404028","title":"Gaussian Channel Model for Mobile Multipath Environment","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Angle of arrival; Multipath propagation; Gaussian; Computer science; Channel (broadcasting); Probability density function; Base station; Gaussian process; Algorithm; Statistical physics; Physics; Optics; Telecommunications; Mathematics; Statistics","score_opus":0.020933222228818348,"score_gpt":0.3046314250766167,"score_spread":0.2836982028477984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080927857","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":[0.0026791275,0.0011385065,0.9951565,0.00017347805,0.000101261416,0.0002642282,0.0000020180855,0.00008068279,0.00040417345],"genre_scores_gemma":[0.69196194,0.00017689605,0.30763084,0.00010329776,0.000043066855,0.000051253646,4.6351204e-7,0.000012860798,0.000019355899],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99852973,0.000031313866,0.0004953719,0.00028591303,0.0003897761,0.00026790987],"domain_scores_gemma":[0.9991824,0.00006401038,0.00043301526,0.00014830817,0.000075732336,0.0000965055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047261248,0.00016953703,0.00021726142,0.00026412707,0.00018209354,0.00011077531,0.00051757897,0.000065692315,0.000003605223],"category_scores_gemma":[0.0000386199,0.00014997803,0.00007831103,0.00023082014,0.00006104489,0.0019236942,0.000049793965,0.00033550212,0.0000031596003],"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":[0.000027384702,0.00016006734,0.0000188495,0.000043727247,0.0000020789607,0.000006484063,0.00070131733,0.71350956,0.0010255404,0.0013831955,0.000003801091,0.283118],"study_design_scores_gemma":[0.0007538781,0.0004178025,0.000039103303,0.0005152145,0.0000035236935,0.000051777188,0.000052567953,0.8718394,0.031741615,0.09399162,0.00038170096,0.00021180429],"about_ca_topic_score_codex":6.799614e-7,"about_ca_topic_score_gemma":7.2236054e-7,"teacher_disagreement_score":0.68928283,"about_ca_system_score_codex":0.00021273881,"about_ca_system_score_gemma":0.00012070572,"threshold_uncertainty_score":0.6115927},"labels":[],"label_agreement":null},{"id":"W2081344000","doi":"10.1049/iet-spr.2011.0328","title":"Gaussian mixture model approximation of total spatial power spectral density for multiple incoherently distributed sources","year":2013,"lang":"en","type":"article","venue":"IET Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"Gaussian; Spectral density; Covariance; Mixture model; Algorithm; Gaussian process; Mixture distribution; Probability density function; Mathematics; Computer science; Pattern recognition (psychology); Statistics; Artificial intelligence; Physics","score_opus":0.011848888785694432,"score_gpt":0.23961381886696337,"score_spread":0.22776493008126894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081344000","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":[0.1750408,0.000017015394,0.82407045,0.00011950441,0.0000387445,0.0004040836,0.00001555728,0.00017452704,0.00011931379],"genre_scores_gemma":[0.78018975,1.7419629e-7,0.21968782,0.000015903603,0.000023367134,0.000042750606,0.000018564444,0.000009273907,0.000012404389],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988104,0.00002980865,0.00038540576,0.00027417982,0.00029888735,0.00020129624],"domain_scores_gemma":[0.9989178,0.00006559003,0.00038396125,0.0001755937,0.00039375224,0.000063305684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017363417,0.00014974311,0.00022713852,0.00010141548,0.000121967765,0.00013306663,0.00029379138,0.00012607768,0.000012284068],"category_scores_gemma":[0.0000752443,0.00013741475,0.00008493573,0.00024978188,0.000073594776,0.0010116219,0.00007931042,0.00012889464,0.0000017896618],"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":[0.00021853957,0.0011711244,0.0063459435,0.0016641726,0.00010844598,0.0000021091857,0.0075326283,0.06665672,0.5630472,0.008021654,0.0016747103,0.34355676],"study_design_scores_gemma":[0.00018550942,0.00007112045,0.0012759794,0.00006861357,0.000006389117,0.0000031421619,0.000020161817,0.7137063,0.27000767,0.014541625,0.0000021470967,0.00011133725],"about_ca_topic_score_codex":0.00013815874,"about_ca_topic_score_gemma":0.000007810336,"teacher_disagreement_score":0.64704955,"about_ca_system_score_codex":0.000043856086,"about_ca_system_score_gemma":0.000107941174,"threshold_uncertainty_score":0.56036115},"labels":[],"label_agreement":null},{"id":"W2083835430","doi":"10.1109/taslp.2015.2410139","title":"Combined Beamformers for Robust Broadband Regularized Superdirective Beamforming","year":2015,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Audio Speech and Language Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Academia Româna; Israel Science Foundation","keywords":"Directivity; Beamforming; Broadband; Adaptive beamformer; White noise; Computer science; Noise (video); Acoustics; Array gain; Telecommunications; Physics; Antenna array; Antenna (radio); Artificial intelligence","score_opus":0.027156774610238375,"score_gpt":0.2808212654049863,"score_spread":0.25366449079474795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083835430","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":[0.021125793,0.00021191704,0.97639024,0.00029888185,0.00025612084,0.0004862506,0.0000140612565,0.00050097477,0.0007157335],"genre_scores_gemma":[0.36418802,0.000013828792,0.63517964,0.00009585685,0.000031193682,0.00008460309,0.000005127083,0.000023082888,0.0003786782],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99858725,0.000040949286,0.00034444567,0.00041549167,0.00031651027,0.00029535688],"domain_scores_gemma":[0.9988192,0.00013682009,0.00017419716,0.00039956128,0.000294543,0.0001756772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004783583,0.00022160812,0.00031759,0.00032930681,0.0002876946,0.00017358657,0.00040475064,0.00011643014,0.0000071247036],"category_scores_gemma":[0.00013608724,0.00021196595,0.00009862614,0.0005531316,0.000101522186,0.0010164188,0.000012201197,0.00018174629,0.0000022005165],"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":[0.00017290519,0.00017686671,0.000025083333,0.00017526002,0.00005209001,0.0000049608634,0.0060593877,0.0009551445,0.011209622,0.00009448288,0.00011984561,0.98095435],"study_design_scores_gemma":[0.0029585364,0.0007906708,0.00006930843,0.00040185114,0.00009342225,0.00009609008,0.0020202245,0.124840125,0.8634727,0.0042022415,0.00042411537,0.00063070224],"about_ca_topic_score_codex":0.00009532358,"about_ca_topic_score_gemma":0.000027145086,"teacher_disagreement_score":0.9803237,"about_ca_system_score_codex":0.00010582735,"about_ca_system_score_gemma":0.00018586912,"threshold_uncertainty_score":0.8643721},"labels":[],"label_agreement":null},{"id":"W2084638580","doi":"10.4028/www.scientific.net/amm.543-547.2201","title":"A Review of Super-Resolution Methods for Nonorthogonal Analysis of Highly Correlated Signals in Noise","year":2014,"lang":"en","type":"review","venue":"Applied Mechanics and Materials","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; Central University of Technology","keywords":"Noise (video); Resolution (logic); Computer science; SIGNAL (programming language); High resolution; Electronic engineering; Algorithm; Artificial intelligence; Engineering; Remote sensing; Geology; Image (mathematics)","score_opus":0.03641907020040838,"score_gpt":0.3730551877931088,"score_spread":0.3366361175927004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084638580","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000016985472,0.4099347,0.5888963,0.0000039056945,0.000097149714,0.0009308216,0.00008683915,0.000025114403,0.000023475048],"genre_scores_gemma":[0.00003811323,0.70073164,0.29873914,0.000024225135,0.0000071015534,0.00032211875,0.00012143178,0.000013679601,0.0000025339068],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99719495,0.0003150396,0.0017619466,0.00041310565,0.00015668018,0.00015829617],"domain_scores_gemma":[0.99708676,0.0004975487,0.0016472375,0.0005061865,0.00021785233,0.000044419292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003788591,0.00026707628,0.003214865,0.00070014247,0.000020239702,0.000020992558,0.00045843757,0.00024675427,0.000018796602],"category_scores_gemma":[0.00017948324,0.0002310057,0.00032479127,0.0011844967,0.000018707375,0.00007004232,0.00018676952,0.00006194169,6.232212e-7],"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":[0.000007968627,0.00005057445,1.6801856e-8,0.07436674,0.00033628056,9.112896e-8,0.000019022451,0.000004602746,0.0041153845,0.33576497,0.000049133552,0.5852852],"study_design_scores_gemma":[0.0011503621,0.00075949624,0.0000031060433,0.19045821,0.021016736,0.000014807947,0.0000059101367,0.02916698,0.097683415,0.10841519,0.5491906,0.0021352072],"about_ca_topic_score_codex":0.000037771457,"about_ca_topic_score_gemma":0.0000020696932,"teacher_disagreement_score":0.58314997,"about_ca_system_score_codex":0.00003156059,"about_ca_system_score_gemma":0.00012214266,"threshold_uncertainty_score":0.9420139},"labels":[],"label_agreement":null},{"id":"W2086201587","doi":"10.1007/s00034-007-9009-4","title":"A Class of Adaptive Cyclostationary Beamforming Algorithms","year":2008,"lang":"en","type":"article","venue":"Circuits Systems and Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Cyclostationary process; Algorithm; Adaptive beamformer; Computer science; Autocorrelation; Computational complexity theory; Beamforming; Interference (communication); Adaptive algorithm; Adaptive filter; Channel (broadcasting); Telecommunications; Mathematics; Statistics","score_opus":0.034326280615326325,"score_gpt":0.2541103741956896,"score_spread":0.21978409358036327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086201587","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":[0.02244744,0.00092705985,0.97300947,0.000013370803,0.00006672218,0.00017011503,0.000003055779,0.00011886146,0.003243896],"genre_scores_gemma":[0.979327,0.000012344633,0.02054694,0.00001038994,0.00003008576,0.000016175818,0.0000011689103,0.000007345034,0.000048533766],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894553,0.00003832505,0.00038602366,0.0002106758,0.00029625054,0.00012317271],"domain_scores_gemma":[0.9991142,0.00007680682,0.0003335357,0.00011239219,0.0003116212,0.000051439183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024093564,0.0000985783,0.00022286664,0.00016091716,0.00016190564,0.000037341884,0.00019171661,0.000053787633,0.0000010605597],"category_scores_gemma":[0.000019619203,0.00009375194,0.00003082638,0.00034156392,0.0001011516,0.00080148637,0.000045112392,0.000068097084,6.8325267e-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":[0.000010496189,0.00018892897,0.0030720679,0.0015026913,0.00006329984,0.000034242374,0.013102221,0.002770106,0.030669581,0.042573635,0.00017509388,0.90583766],"study_design_scores_gemma":[0.0003092774,0.00024515885,0.0028289289,0.0010097466,0.00001207133,0.00041427783,0.00043045773,0.964921,0.025817689,0.003520653,0.00018874554,0.0003019935],"about_ca_topic_score_codex":0.000060451483,"about_ca_topic_score_gemma":2.779486e-7,"teacher_disagreement_score":0.9621509,"about_ca_system_score_codex":0.000026021886,"about_ca_system_score_gemma":0.0001515776,"threshold_uncertainty_score":0.38230935},"labels":[],"label_agreement":null},{"id":"W2091252063","doi":"10.1007/bf01196158","title":"Robust mixed-order root-music","year":2000,"lang":"en","type":"article","venue":"Circuits Systems and Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Robustness (evolution); Computer science; Order (exchange); Covariance; Algorithm; Root (linguistics); Mathematical optimization; Mathematics; Statistics","score_opus":0.032196228173983384,"score_gpt":0.23659832710594925,"score_spread":0.20440209893196587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091252063","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":[0.04196843,0.0019058909,0.9383244,0.00004142295,0.00014757886,0.00020814655,0.0000013732421,0.00040122168,0.017001532],"genre_scores_gemma":[0.9960235,0.0000066972516,0.003392037,0.000028165183,0.00006913043,0.000019676803,9.863604e-7,0.000011623139,0.00044823534],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882805,0.000054650845,0.00034267677,0.0003173712,0.00026637013,0.0001909046],"domain_scores_gemma":[0.99935436,0.000039515497,0.0001443595,0.0001903865,0.00019248178,0.00007887247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033402917,0.00013160842,0.0002193777,0.00011467904,0.00018856955,0.00033847598,0.00029667953,0.0000737558,0.000037415648],"category_scores_gemma":[0.000014300528,0.00012208981,0.000028674662,0.0004960978,0.000055343302,0.0008052074,0.000033213288,0.00009002498,0.000011511218],"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":[0.0000011066728,0.00003449316,0.00033029003,0.00032842255,0.000008275221,0.000004259185,0.0006084989,0.002309325,0.0014244224,0.0040129777,0.00031164844,0.9906263],"study_design_scores_gemma":[0.0005835382,0.0002065031,0.0043998878,0.0017827548,0.000030130708,0.00032786635,0.00017025707,0.96999735,0.009969189,0.0047538523,0.006931166,0.00084749574],"about_ca_topic_score_codex":0.00006157023,"about_ca_topic_score_gemma":0.0000032176858,"teacher_disagreement_score":0.98977876,"about_ca_system_score_codex":0.000023154327,"about_ca_system_score_gemma":0.00009154763,"threshold_uncertainty_score":0.49786782},"labels":[],"label_agreement":null},{"id":"W2092755517","doi":"10.1109/icmtma.2010.689","title":"Wideband DOA Estimation Using Two Sensors","year":2010,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Concordia University","funders":"","keywords":"Wideband; Narrowband; Bin; Toeplitz matrix; Computer science; Algorithm; Covariance matrix; Direction of arrival; SIGNAL (programming language); Wideband audio; Electronic engineering; Speech recognition; Mathematics; Telecommunications; Engineering","score_opus":0.018617385665353616,"score_gpt":0.3068880790755198,"score_spread":0.2882706934101662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092755517","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":[0.14115192,0.0000011536355,0.850454,0.0001337974,0.00029686978,0.000079701924,2.7245346e-7,0.0004114792,0.007470816],"genre_scores_gemma":[0.49160594,2.231417e-7,0.50827765,0.00002784178,0.000010424999,0.0000016004219,3.070276e-7,0.0000028366878,0.000073184754],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936956,0.000019195246,0.00018377304,0.0001592032,0.00017219776,0.000096070944],"domain_scores_gemma":[0.9993486,0.000065350774,0.00009330972,0.00033774375,0.00011355604,0.000041433483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021622125,0.00006927687,0.00008666649,0.00012460844,0.0000568282,0.000074469666,0.00026078793,0.00003662881,0.00005121679],"category_scores_gemma":[0.0001167093,0.00006330687,0.000030265832,0.0002792493,0.000038846454,0.00066242495,0.00006489615,0.00008462593,0.000018883768],"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":[0.0000036583197,0.00008710179,0.0011510771,0.0000276088,0.000013855326,0.000003126197,0.00044959708,0.010288466,0.38241464,0.41249627,0.000889429,0.19217518],"study_design_scores_gemma":[0.0000577591,0.000009460515,0.00022413161,0.0000064470214,0.0000018669589,0.000014558401,0.0000014514906,0.6660032,0.3221574,0.011329203,0.00013320967,0.000061312625],"about_ca_topic_score_codex":0.00019657063,"about_ca_topic_score_gemma":0.000017232378,"teacher_disagreement_score":0.65571475,"about_ca_system_score_codex":0.0000130862245,"about_ca_system_score_gemma":0.00003726988,"threshold_uncertainty_score":0.2581579},"labels":[],"label_agreement":null},{"id":"W2095441115","doi":"10.1109/icuwb.2015.7324433","title":"Cramer-Rao Lower Bounds for Angular Parameters Estimates from Incoherently Distributed Signals Generated by Noncircular Sources","year":2015,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Cramér–Rao bound; Physics; Upper and lower bounds; Angular velocity; Point (geometry); Phase (matter); Optics; Computational physics; Mathematics; Mathematical analysis; Geometry","score_opus":0.028343599996232607,"score_gpt":0.27197816250765106,"score_spread":0.24363456251141846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095441115","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":[0.12539649,0.00020486159,0.87236196,0.00028348164,0.000254653,0.00041237145,0.00018622311,0.0007336148,0.00016635955],"genre_scores_gemma":[0.57135975,0.0000024347976,0.4278722,0.0002122532,0.000022067486,0.00011531767,0.0003162059,0.000020891923,0.00007884847],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99820304,0.00007479805,0.00048049638,0.00049949484,0.0004299967,0.00031219432],"domain_scores_gemma":[0.998195,0.00025906888,0.00025871993,0.00058171526,0.000489635,0.00021584867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037106252,0.0002504848,0.00036688897,0.000113945986,0.000096782,0.00036377442,0.0008050868,0.00013224881,0.0000373796],"category_scores_gemma":[0.00039475682,0.00022830826,0.00012692383,0.0004950781,0.00014918183,0.0006618489,0.00014475684,0.0000823371,0.00001867323],"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":[0.00022580761,0.002074445,0.0089256065,0.00014585668,0.0010986016,0.0000311508,0.0021485977,0.023929788,0.35510764,0.01116185,0.5212366,0.07391405],"study_design_scores_gemma":[0.00047378187,0.00026437905,0.00009711547,0.000031257747,0.000026339007,0.0000022304225,0.000031641688,0.37412542,0.5979344,0.02271543,0.00396574,0.0003322614],"about_ca_topic_score_codex":0.0011457648,"about_ca_topic_score_gemma":0.0000102056665,"teacher_disagreement_score":0.51727086,"about_ca_system_score_codex":0.000097679804,"about_ca_system_score_gemma":0.00012880204,"threshold_uncertainty_score":0.93101406},"labels":[],"label_agreement":null},{"id":"W2096220875","doi":"10.1109/aps.2009.5172377","title":"Impact of experimental calibration on direction of arrival estimation","year":2009,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Calibration; Direction of arrival; Computer science; Multiple signal classification; Coupling (piping); SIGNAL (programming language); Direction finding; Electronic engineering; Sensor array; Acoustics; Telecommunications; Engineering; Statistics; Machine learning; Mathematics; Physics; Antenna (radio)","score_opus":0.014840903846471808,"score_gpt":0.32419346042720043,"score_spread":0.30935255658072863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096220875","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":[0.3349512,0.000007862801,0.6588981,0.00004279484,0.00007347962,0.00013950426,0.0000014220947,0.00017786374,0.005707734],"genre_scores_gemma":[0.910609,0.0000014585241,0.08933537,0.000010991644,0.000007805439,0.0000037970692,0.0000033357683,0.0000030503845,0.000025185207],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991435,0.000041303105,0.0003352142,0.0001472815,0.00025968975,0.00007300257],"domain_scores_gemma":[0.9993123,0.000042185235,0.0002571594,0.00026231847,0.00009546961,0.000030574567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013380157,0.00008688026,0.00015451973,0.00021081477,0.000022558588,0.000016038084,0.00018221968,0.000044751247,0.000030689847],"category_scores_gemma":[0.00005484455,0.000075357435,0.00009429321,0.00034684475,0.00002670058,0.00066760037,0.000018546096,0.00003533878,0.0000015334199],"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":[0.00007307169,0.0009495982,0.0007853375,0.000017120146,0.000027305576,4.6590912e-7,0.00079858606,0.01100022,0.72326666,0.11049891,0.00064394355,0.1519388],"study_design_scores_gemma":[0.000100772915,0.0008864144,0.016307846,0.000022868777,0.0000018364074,0.0000018995879,0.000004265691,0.25437328,0.7258289,0.0024209605,0.0000011014661,0.00004987806],"about_ca_topic_score_codex":0.00012737348,"about_ca_topic_score_gemma":6.215859e-7,"teacher_disagreement_score":0.5756578,"about_ca_system_score_codex":0.000066974484,"about_ca_system_score_gemma":0.000043392487,"threshold_uncertainty_score":0.30729872},"labels":[],"label_agreement":null},{"id":"W2097513256","doi":"10.1109/ccece.1996.548245","title":"Adaptive beamforming with near-instantaneous convergence for matched filter processing","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Technical University of Nova Scotia","funders":"","keywords":"Adaptive filter; Beamforming; Adaptive beamformer; Computer science; Sonar signal processing; Array processing; Marine mammals and sonar; Filter (signal processing); Covariance matrix; Convergence (economics); Algorithm; Signal processing; Matched filter; Space-time adaptive processing; Broadband; Coherence (philosophical gambling strategy); Sonar; Mathematics; Digital signal processing; Artificial intelligence; Telecommunications; Computer vision","score_opus":0.02898321400461711,"score_gpt":0.241530739916424,"score_spread":0.21254752591180687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097513256","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":[0.0036442468,0.000022196284,0.98807395,0.00014148504,0.00005203345,0.00030484918,0.0000017266789,0.00045515364,0.007304349],"genre_scores_gemma":[0.4849109,0.0000018745009,0.5145384,0.000073410614,0.000005688186,0.000032632706,3.1574967e-7,0.000006061379,0.00043073663],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991839,0.000009640907,0.00019961334,0.00023721314,0.00019572918,0.00017393808],"domain_scores_gemma":[0.99932766,0.000066448185,0.0001310883,0.0002233937,0.00020549569,0.000045899713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000095914285,0.00010661936,0.00014164108,0.000055207933,0.000118220756,0.0000937338,0.0003405416,0.00003523897,0.00006901966],"category_scores_gemma":[0.000024086714,0.00008485707,0.000031880183,0.0002990852,0.000067525805,0.00071559957,0.000050116207,0.000047555408,0.000010136187],"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":[0.00010854776,0.0003278854,0.00053381285,0.0003507294,0.00007003451,0.000031252985,0.008852666,0.0014953627,0.0047755837,0.060390994,0.0037237506,0.91933936],"study_design_scores_gemma":[0.00016506706,0.0002870673,0.000032921907,0.00007865451,0.0000058049727,0.000059576825,0.00006193274,0.925942,0.07093844,0.0016139916,0.0006460353,0.00016851988],"about_ca_topic_score_codex":0.00002359521,"about_ca_topic_score_gemma":0.0000074226173,"teacher_disagreement_score":0.92444664,"about_ca_system_score_codex":0.000033029108,"about_ca_system_score_gemma":0.00003781706,"threshold_uncertainty_score":0.3460371},"labels":[],"label_agreement":null},{"id":"W2098637377","doi":"10.1109/tap.2007.891852","title":"Fast Adaptive Microwave Beamforming Using Array Signal Estimation","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Antennas and Propagation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Adaptive beamformer; Beamforming; Estimator; Antenna array; Weight; Signal-to-interference-plus-noise ratio; Computer science; Algorithm; Quantization (signal processing); Mathematics; Control theory (sociology); Antenna (radio); Acoustics; Physics; Telecommunications; Statistics; Power (physics)","score_opus":0.023379159782482208,"score_gpt":0.2654175166013979,"score_spread":0.2420383568189157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098637377","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":[0.016982073,0.000012961438,0.9818971,0.0000576,0.00020245757,0.00027956333,0.000003698574,0.00018576325,0.00037875594],"genre_scores_gemma":[0.69372827,0.0000068253926,0.30618185,0.00003135186,0.000011775092,0.000006190121,0.0000010672458,0.000007355514,0.0000253152],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989805,0.000036711903,0.0003359136,0.00025097386,0.00022874758,0.00016710628],"domain_scores_gemma":[0.99932176,0.00008139038,0.00018535186,0.00016285645,0.00018482962,0.000063807274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044115543,0.00013566844,0.00013780141,0.00031866026,0.00022488504,0.000066329274,0.00012267337,0.0000763243,0.000006792219],"category_scores_gemma":[0.0000060444418,0.00013317677,0.000054599182,0.0004322216,0.00007172006,0.0008573836,0.0000016828765,0.00013811886,0.0000038849766],"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":[0.000050907816,0.00009330678,0.000007978792,0.000028381974,0.000018384488,0.0000016333164,0.00081681483,0.005777911,0.38194773,0.002110189,0.0000026084833,0.60914415],"study_design_scores_gemma":[0.00011858655,0.00014619507,0.00009076806,0.000081314305,0.000010658487,0.000026207026,0.000055715132,0.4034971,0.5947547,0.0011093707,0.000006101892,0.00010329073],"about_ca_topic_score_codex":0.000059982347,"about_ca_topic_score_gemma":0.000021070884,"teacher_disagreement_score":0.6767462,"about_ca_system_score_codex":0.00007450246,"about_ca_system_score_gemma":0.000046773046,"threshold_uncertainty_score":0.54307914},"labels":[],"label_agreement":null},{"id":"W2099862052","doi":"10.1109/78.902109","title":"Direction-of-arrival estimation of an amplitude-distorted wavefront","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Wavefront; Array processing; Distortion (music); Direction of arrival; Estimator; Amplitude; Robustness (evolution); Algorithm; Mathematics; Estimation theory; Parameterized complexity; Signal processing; Computer science; Physics; Statistics; Optics; Telecommunications","score_opus":0.021424995449398108,"score_gpt":0.2852116709079119,"score_spread":0.26378667545851375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099862052","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":[0.043795925,0.000035215293,0.9545343,0.000039870072,0.00019539444,0.00020562444,0.0000062949593,0.00037469104,0.0008127201],"genre_scores_gemma":[0.86675805,0.000007591688,0.1331128,0.000014028339,0.000013852509,0.000027149921,0.0000019917736,0.000016585014,0.000047926653],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981571,0.00009057375,0.00068602414,0.00035544366,0.0005250806,0.00018579133],"domain_scores_gemma":[0.99858576,0.00010246059,0.0004623896,0.00037359915,0.00038529406,0.00009050875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003457236,0.00018842508,0.00031917458,0.00047037596,0.00017755345,0.00005210845,0.00042601745,0.000103767765,0.00004306072],"category_scores_gemma":[0.000012939387,0.00019598842,0.00012002023,0.0009694904,0.00013541587,0.0013986484,0.0000031517936,0.00016967481,0.0000033647007],"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":[0.00006916237,0.0005839034,0.000021452503,0.00013427198,0.000029165547,0.0000019239951,0.0007675723,0.08118624,0.037109263,0.000323446,0.0000073418933,0.8797662],"study_design_scores_gemma":[0.00023229778,0.00030071172,0.00044886113,0.0001970578,0.00003036993,0.000023805718,0.000030796764,0.54890776,0.44772327,0.0018987957,0.00003424625,0.00017206265],"about_ca_topic_score_codex":0.0001354988,"about_ca_topic_score_gemma":0.000014211313,"teacher_disagreement_score":0.8795942,"about_ca_system_score_codex":0.000094763054,"about_ca_system_score_gemma":0.00016940536,"threshold_uncertainty_score":0.7992176},"labels":[],"label_agreement":null},{"id":"W2100629768","doi":"10.1109/vetecf.2003.1285216","title":"Antenna array training and adaptation techniques in an unpredictable and uncontrolled interference environment","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Interference (communication); Channel (broadcasting); Wireless; Network packet; Real-time computing; Sample matrix inversion; Electronic engineering; Algorithm; Telecommunications; Covariance matrix; Computer network; Engineering","score_opus":0.02847387309904573,"score_gpt":0.24485814286703514,"score_spread":0.2163842697679894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100629768","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":[0.021583911,0.00006598662,0.9743235,0.00007055669,0.000022540673,0.00016744253,6.313643e-7,0.00018263042,0.0035827882],"genre_scores_gemma":[0.6391576,0.000058715224,0.360693,0.000031510197,0.0000017495432,0.0000201748,4.2555558e-7,0.0000029385749,0.00003392318],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991879,0.00009300385,0.0002511833,0.0002531196,0.00010385342,0.00011094709],"domain_scores_gemma":[0.9995945,0.00006646596,0.000078883226,0.0001795331,0.000030479998,0.000050099203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004153864,0.0000883503,0.00015622244,0.00013517967,0.00003148145,0.00005788303,0.0001097461,0.00004221349,0.000010053733],"category_scores_gemma":[0.00007468307,0.00008249888,0.000010591122,0.00013562253,0.00005268376,0.0006828292,0.000030079515,0.000062089326,4.903119e-7],"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":[0.000029349047,0.00025618388,0.009887531,0.000046125315,0.000018961047,0.000007954901,0.009819403,0.00008142279,0.18441841,0.15774323,0.000024516543,0.63766694],"study_design_scores_gemma":[0.0012005615,0.0009463556,0.0049974555,0.00019110159,0.000012136876,0.00006072788,0.0014313643,0.420052,0.47130883,0.098619916,0.00068727817,0.0004922868],"about_ca_topic_score_codex":0.000034728255,"about_ca_topic_score_gemma":0.000039665934,"teacher_disagreement_score":0.6371746,"about_ca_system_score_codex":0.000024531928,"about_ca_system_score_gemma":0.000035414214,"threshold_uncertainty_score":0.33642066},"labels":[],"label_agreement":null},{"id":"W2102871601","doi":"10.1109/aps.2009.5171463","title":"Single-port direction of arrival estimation using adaptive null-forming","year":2009,"lang":"en","type":"article","venue":"Digest - IEEE Antennas and Propagation Society. International Symposium","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Direction of arrival; Multiple signal classification; Null (SQL); Computer science; Bandwidth (computing); Port (circuit theory); Electronic engineering; Algorithm; Telecommunications; Antenna (radio); Engineering; Data mining","score_opus":0.02329416445402963,"score_gpt":0.27358896854338166,"score_spread":0.250294804089352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102871601","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":[0.1567468,0.00004363977,0.83835566,0.0007518878,0.00069360906,0.00032498207,0.000010795402,0.00021328381,0.0028593554],"genre_scores_gemma":[0.9200745,0.00007820687,0.0795228,0.00011302687,0.00009072173,0.00001086704,0.000019409528,0.000011076443,0.00007934402],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982553,0.000046089408,0.0006183655,0.00035697792,0.0005514625,0.00017179394],"domain_scores_gemma":[0.9982947,0.0000730377,0.00065804017,0.0002113365,0.0006995654,0.00006332377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041109114,0.00019137845,0.00024332447,0.00013621098,0.00015265762,0.00011718998,0.00032206223,0.000112701695,0.000005894779],"category_scores_gemma":[0.000053395244,0.00019310933,0.00015548452,0.00040060224,0.00010542722,0.0016388044,0.000052012114,0.00012185488,0.000001603434],"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":[0.00006703347,0.0004555986,0.0016846447,0.000065434535,0.00013560182,0.0000028105928,0.003374593,0.0030920946,0.8764268,0.033574015,0.00019010501,0.08093125],"study_design_scores_gemma":[0.00031568186,0.0003290156,0.0031729012,0.00022796931,0.000025900714,0.000048317474,0.00010118152,0.61180454,0.38004184,0.003489651,0.00019685451,0.00024614073],"about_ca_topic_score_codex":0.00008784508,"about_ca_topic_score_gemma":0.0000017804977,"teacher_disagreement_score":0.7633277,"about_ca_system_score_codex":0.00015055329,"about_ca_system_score_gemma":0.00006776385,"threshold_uncertainty_score":0.78747696},"labels":[],"label_agreement":null},{"id":"W2103156253","doi":"10.1109/wcnc.2011.5779388","title":"A new importance-sampling-based non-data-aided maximum likelihood time delay estimator","year":2011,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Estimator; Additive white Gaussian noise; Algorithm; Computer science; Convergence (economics); Mathematical optimization; Sampling (signal processing); Estimation theory; Mathematics; Gaussian noise; Interval (graph theory); Likelihood function; Gaussian; White noise; Statistics; Telecommunications","score_opus":0.05330853665553672,"score_gpt":0.2853298887002611,"score_spread":0.23202135204472438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103156253","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":[0.000833902,0.000019407546,0.9817602,0.00020483605,0.0001942249,0.0003017079,0.00000893551,0.001163602,0.01551321],"genre_scores_gemma":[0.057156514,0.0000015543814,0.94221634,0.0002868598,0.000031145257,0.000019564362,0.000019688487,0.000022846087,0.0002455053],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980679,0.000031081698,0.0005686469,0.00061599666,0.00038099714,0.0003353331],"domain_scores_gemma":[0.99724454,0.00011092041,0.00029272985,0.0019232631,0.00019095217,0.00023759958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047084282,0.000229357,0.00031345122,0.00021803833,0.000078351346,0.00009038018,0.0021082244,0.00010542891,0.0007664495],"category_scores_gemma":[0.00016255796,0.00021017077,0.00008988665,0.00058935245,0.000046080593,0.0010767977,0.00040560213,0.000121152465,0.0003942617],"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":[0.00016558249,0.0015822635,0.012751655,0.00026390824,0.00034247752,0.00011941402,0.0016944928,0.0002880867,0.012065833,0.058646385,0.22407936,0.68800056],"study_design_scores_gemma":[0.00085902686,0.00037729432,0.0032311496,0.00010774585,0.00004777503,0.00003154468,0.0000072643966,0.7583584,0.14126131,0.09279936,0.002166071,0.00075301627],"about_ca_topic_score_codex":0.00047834622,"about_ca_topic_score_gemma":0.00003082623,"teacher_disagreement_score":0.75807035,"about_ca_system_score_codex":0.00004370689,"about_ca_system_score_gemma":0.0004864724,"threshold_uncertainty_score":0.8570515},"labels":[],"label_agreement":null},{"id":"W2103255537","doi":"10.1109/pacrim.1991.160698","title":"Detection of the number of signals in the presence of noise with an unknown, banded structured covariance matrix","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Covariance matrix; Noise (video); Range (aeronautics); Covariance; Scheme (mathematics); Algorithm; Computer science; Process (computing); Matrix (chemical analysis); Canonical correlation; Mathematics; Artificial intelligence; Image (mathematics); Statistics; Engineering","score_opus":0.014968516863291847,"score_gpt":0.26848964584518037,"score_spread":0.2535211289818885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103255537","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":[0.39516935,0.000019662455,0.60110676,0.00017460392,0.00006985002,0.00045347257,0.0000032543508,0.000059600916,0.0029434455],"genre_scores_gemma":[0.95321643,0.0000036250149,0.046663254,0.000015666395,0.000004086409,0.0000102661525,1.1454571e-7,0.000003405376,0.000083121544],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989302,0.00017075268,0.00031939265,0.00014639819,0.0003533289,0.00007988636],"domain_scores_gemma":[0.9987575,0.0001263391,0.0003279091,0.0005673748,0.00020661115,0.000014255259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031712037,0.00007569865,0.00015448443,0.000058495614,0.000024908382,0.000013621943,0.0007396982,0.000041476647,0.00004241777],"category_scores_gemma":[0.00008573433,0.00004133866,0.000035211415,0.0008371389,0.00012329042,0.00035820698,0.000054180946,0.00007121921,5.0221416e-7],"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":[0.00025022822,0.0011853444,0.025105929,0.0005291975,0.00009772378,0.0000029047517,0.012907674,0.026565941,0.6752619,0.16115804,0.0005015875,0.096433505],"study_design_scores_gemma":[0.00019872609,0.0001256452,0.018650789,0.000062693325,0.000006197729,0.0000110733035,0.000035275505,0.08773406,0.88662183,0.006472921,0.000018393162,0.000062416686],"about_ca_topic_score_codex":0.00029583235,"about_ca_topic_score_gemma":0.00012287522,"teacher_disagreement_score":0.5580471,"about_ca_system_score_codex":0.000010680889,"about_ca_system_score_gemma":0.00002406213,"threshold_uncertainty_score":0.16857415},"labels":[],"label_agreement":null},{"id":"W2104845454","doi":"10.1109/wcnc.2011.5779403","title":"DOA estimation from temporally and spatially correlated narrowband signals with noncircular sources","year":2011,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Narrowband; Subspace topology; Correlation; Variance (accounting); Signal subspace; Algorithm; SIGNAL (programming language); Estimation theory; Expression (computer science); Computer science; Signal-to-noise ratio (imaging); Mathematics; Random variable; Signal processing; Spatial correlation; Cramér–Rao bound; Stochastic process; Statistics; Noise (video); Artificial intelligence; Telecommunications","score_opus":0.017000348860972778,"score_gpt":0.21589815801016946,"score_spread":0.1988978091491967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104845454","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":[0.20436242,0.000033194035,0.79128736,0.000052180072,0.000042149815,0.00016753672,0.0000015623234,0.00038823034,0.0036653425],"genre_scores_gemma":[0.62081206,0.000002814109,0.379084,0.000043464297,0.000004005326,0.000007964948,0.0000034444574,0.0000060712227,0.000036172132],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903697,0.000048808088,0.00026788338,0.00028471102,0.00025026232,0.00011136673],"domain_scores_gemma":[0.9991726,0.00008544206,0.000206363,0.0003043984,0.0001609253,0.00007023003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019223757,0.00012952427,0.0001740696,0.00012015465,0.000065617605,0.00007837073,0.00029488307,0.000068530855,0.00009475293],"category_scores_gemma":[0.00004876675,0.00010293663,0.000023775534,0.00025013078,0.000083006285,0.0007334042,0.000066868226,0.000064622196,0.0000112540265],"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":[0.0005087456,0.0016233173,0.2656321,0.00039273934,0.0009537352,0.00018728177,0.05939121,0.012994534,0.094523266,0.11995913,0.002774729,0.44105923],"study_design_scores_gemma":[0.00063199585,0.0005652872,0.030862397,0.00020072635,0.000037976923,0.000027479797,0.000048015394,0.59184283,0.3463426,0.028943716,0.000058060577,0.00043888227],"about_ca_topic_score_codex":0.0016464898,"about_ca_topic_score_gemma":0.000071485316,"teacher_disagreement_score":0.5788483,"about_ca_system_score_codex":0.00001337634,"about_ca_system_score_gemma":0.0000772994,"threshold_uncertainty_score":0.4197634},"labels":[],"label_agreement":null},{"id":"W2105319844","doi":"10.1109/pacrim.1991.160866","title":"Parallel implementation of high-resolution direction-finding algorithms with circular arrays","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Multiple signal classification; Algorithm; Sensor array; Circular buffer; Calibration; SIGNAL (programming language); Array processing; Direction finding; Resolution (logic); Coupling (piping); Signal processing; Mathematics; Artificial intelligence; Computer hardware; Engineering; Telecommunications; Digital signal processing; Antenna (radio); Machine learning","score_opus":0.02531525862273632,"score_gpt":0.2758765985661906,"score_spread":0.2505613399434543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105319844","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":[0.012912024,0.000025972415,0.98366326,0.00015847181,0.00012815102,0.00021584384,0.000001721818,0.00032938298,0.0025652002],"genre_scores_gemma":[0.6202538,0.000011645091,0.37962386,0.0000121334215,0.000012712821,0.000016520784,0.000002458628,0.000005445959,0.00006142878],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988665,0.000038108203,0.0003516532,0.00023936502,0.0003440828,0.00016031084],"domain_scores_gemma":[0.99917006,0.0000511313,0.00026781874,0.0002997784,0.00016766564,0.00004351635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026890627,0.0001050141,0.00015913734,0.00021770065,0.000078659694,0.0000324509,0.0002470466,0.000040027837,0.00011563403],"category_scores_gemma":[0.000014568666,0.00009473211,0.000044266206,0.00057380134,0.000040882685,0.0006407559,0.00004163131,0.000052167536,0.000007001677],"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":[0.000019437997,0.00048384717,0.009434575,0.00016867765,0.00021660392,0.000008199054,0.0032067832,0.0063697095,0.028441515,0.33244154,0.0029562716,0.61625284],"study_design_scores_gemma":[0.0013648428,0.0007320065,0.05054135,0.00010341962,0.000044881715,0.000049834336,0.0003402802,0.2631912,0.6728227,0.00959942,0.0006489644,0.00056112144],"about_ca_topic_score_codex":0.0008775011,"about_ca_topic_score_gemma":0.00005394103,"teacher_disagreement_score":0.64438117,"about_ca_system_score_codex":0.000069065114,"about_ca_system_score_gemma":0.000018522487,"threshold_uncertainty_score":0.38630635},"labels":[],"label_agreement":null},{"id":"W2106343541","doi":"10.1109/tsp.2011.2157499","title":"DOA Estimation of Temporally and Spatially Correlated Narrowband Noncircular Sources in Spatially Correlated White Noise","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Narrowband; Subspace topology; White noise; Mathematics; Correlation; Cramér–Rao bound; Algorithm; Signal-to-noise ratio (imaging); Signal subspace; Signal processing; Estimation theory; Noise (video); Statistics; Computer science; Mathematical analysis; Telecommunications; Artificial intelligence","score_opus":0.01899203473198949,"score_gpt":0.23804827560051584,"score_spread":0.21905624086852635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106343541","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":[0.14883517,0.000058347498,0.85000014,0.000034054912,0.000111347355,0.00028865327,0.000004058337,0.00023009187,0.000438153],"genre_scores_gemma":[0.9194601,0.000010166309,0.08042727,0.000025629775,0.000004729336,0.00002363718,0.0000022075762,0.000020924956,0.000025299352],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812007,0.000109289365,0.00075420935,0.00040461525,0.0004042471,0.00020758685],"domain_scores_gemma":[0.99878585,0.00009323427,0.0004899915,0.00024638503,0.00029719013,0.00008733069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042756528,0.00023187135,0.00034257307,0.0006022328,0.00014748955,0.000072947594,0.00033461937,0.00017916126,0.000040494604],"category_scores_gemma":[0.000019569077,0.00023923111,0.00007124043,0.00094981166,0.00016245796,0.0011319804,0.000005528448,0.00028646458,0.00000407035],"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":[0.00036740367,0.0010766309,0.0031997699,0.0006430969,0.00008607698,0.00003085645,0.019045517,0.4183802,0.039849892,0.00020292719,0.00001000718,0.5171076],"study_design_scores_gemma":[0.00057180645,0.0003020769,0.0019536125,0.0006657062,0.000035591584,0.000024305797,0.00003870331,0.77881545,0.21632493,0.0010231221,0.0000016849526,0.00024302649],"about_ca_topic_score_codex":0.00033663513,"about_ca_topic_score_gemma":0.00008299748,"teacher_disagreement_score":0.770625,"about_ca_system_score_codex":0.000055691897,"about_ca_system_score_gemma":0.00027747202,"threshold_uncertainty_score":0.9755562},"labels":[],"label_agreement":null},{"id":"W2108258804","doi":"10.1109/sam.2004.1503020","title":"A generalized esprit direction-of-arrival estimator","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Direction of arrival; Estimator; Algorithm; Rank (graph theory); Computer science; Reduction (mathematics); Class (philosophy); Mathematical optimization; Mathematics; Statistics; Artificial intelligence; Telecommunications; Combinatorics","score_opus":0.013814205485008287,"score_gpt":0.275449399204187,"score_spread":0.2616351937191787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108258804","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":[0.018634805,0.00007885863,0.9562133,0.0011394189,0.0002969384,0.00020105425,0.0000023221253,0.00092967023,0.02250363],"genre_scores_gemma":[0.3768481,0.000012152132,0.62237537,0.00007558481,0.000041401443,0.000020296058,9.242678e-7,0.000008479185,0.00061769225],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986807,0.000054257478,0.00047506645,0.00027757985,0.00033853872,0.00017381941],"domain_scores_gemma":[0.9988458,0.00009821783,0.00020829555,0.0005527107,0.00021212836,0.00008280414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027983668,0.00013630473,0.00025321107,0.00023694294,0.000062086496,0.000043510685,0.0006191165,0.00006760165,0.00018435603],"category_scores_gemma":[0.00013203929,0.00012730742,0.00011455548,0.0005638597,0.00006665153,0.0006770743,0.00014385076,0.00007137254,0.000045418798],"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":[0.000015486517,0.000299684,0.001134588,0.000048519578,0.000050489132,0.0000015842407,0.00033277035,0.0009773015,0.02469718,0.67204326,0.0101693,0.29022986],"study_design_scores_gemma":[0.00038851795,0.000095765376,0.0018421459,0.000037620805,0.000010378231,0.000020807372,0.0000049244236,0.21746688,0.7506979,0.0066670617,0.022519138,0.00024882943],"about_ca_topic_score_codex":0.00013818563,"about_ca_topic_score_gemma":0.000012509024,"teacher_disagreement_score":0.7260007,"about_ca_system_score_codex":0.00004738324,"about_ca_system_score_gemma":0.000083186795,"threshold_uncertainty_score":0.5191446},"labels":[],"label_agreement":null},{"id":"W2108354294","doi":"10.1109/mwscas.2007.4488760","title":"A spatial exploration based blind DOA estimation algorithm for closely spaced sources","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Extrapolation; Algorithm; Computer science; Correlation coefficient; Block (permutation group theory); Mean squared error; Coefficient matrix; Computational complexity theory; Mathematics; Statistics; Geometry","score_opus":0.04322867996489723,"score_gpt":0.3015852059163894,"score_spread":0.25835652595149217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108354294","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":[0.009382175,0.0000065188697,0.9877754,0.000554963,0.00017666136,0.0006734774,0.000003663077,0.00053465494,0.00089248153],"genre_scores_gemma":[0.5100042,0.0000013821691,0.48978716,0.000042087784,0.000040327894,0.00007827625,0.000007195018,0.000007939877,0.00003139541],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985819,0.0000073014594,0.0004236133,0.0003757194,0.0003605246,0.00025092735],"domain_scores_gemma":[0.9981623,0.00011769582,0.00039838644,0.0001482753,0.0010832081,0.000090080845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000813288,0.00017192548,0.00020202801,0.00033876332,0.00013144867,0.0002855996,0.00046462697,0.00011519281,0.000010062532],"category_scores_gemma":[0.00032699015,0.00017562557,0.00006610463,0.00046602715,0.00007072842,0.0015760519,0.00006069682,0.00009540083,0.0000074797495],"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":[0.000047529298,0.00009315256,0.00021758022,0.00009641883,0.000010146694,3.990379e-7,0.0020920807,0.000041436888,0.0087907575,0.039225515,0.00030164258,0.9490833],"study_design_scores_gemma":[0.000414074,0.00018660254,0.00028154557,0.0000668179,0.000008336785,0.0000016789697,0.0000758025,0.70035684,0.2814906,0.016664548,0.00030175113,0.00015140127],"about_ca_topic_score_codex":0.000044562817,"about_ca_topic_score_gemma":0.000008212944,"teacher_disagreement_score":0.94893193,"about_ca_system_score_codex":0.00005622369,"about_ca_system_score_gemma":0.00014917625,"threshold_uncertainty_score":0.71618026},"labels":[],"label_agreement":null},{"id":"W2109078395","doi":"10.1109/vetec.1994.345406","title":"Spatial channel simulator for phased arrays","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Base station; Computer science; Channel (broadcasting); Phased array; Interference (communication); Antenna (radio); Rayleigh fading; Angle of arrival; Fading; Antenna diversity; Weighting; Antenna array; Simulation; Beamforming; Electronic engineering; Algorithm; Telecommunications; Engineering; Acoustics; Physics","score_opus":0.03569344701866523,"score_gpt":0.2733347293587165,"score_spread":0.23764128234005127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109078395","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":[0.0004719069,0.000009611232,0.99023074,0.00038015185,0.00021583737,0.0002353291,0.0000023366324,0.0005072057,0.00794691],"genre_scores_gemma":[0.80765045,0.0000012832307,0.19167487,0.00012102408,0.000038983697,0.000030597963,6.217474e-7,0.0000051487295,0.00047702107],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940336,0.000010688505,0.00016607872,0.00017017951,0.00013279243,0.000116907504],"domain_scores_gemma":[0.99942714,0.00009318443,0.00006803794,0.00026315375,0.00010514815,0.000043312288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009578862,0.00006941057,0.00010131385,0.00008511195,0.000045846362,0.000035276167,0.00031827224,0.000034456683,0.00010512747],"category_scores_gemma":[0.00007947725,0.00006399158,0.000057231427,0.00015975484,0.000018489049,0.00027812886,0.000025005615,0.000025709065,0.00002300986],"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":[0.000025635181,0.0010149507,0.0001060797,0.0001372424,0.000065307904,0.0000022559557,0.0017471579,0.0042006695,0.02753358,0.23781686,0.043031972,0.6843183],"study_design_scores_gemma":[0.00021579025,0.00009686095,0.000017858512,0.0000057244447,0.0000017666202,8.0219286e-7,0.0000015862634,0.77633613,0.21423143,0.0059413994,0.003075477,0.00007518074],"about_ca_topic_score_codex":0.000031772677,"about_ca_topic_score_gemma":0.000003031257,"teacher_disagreement_score":0.80717856,"about_ca_system_score_codex":0.000015080144,"about_ca_system_score_gemma":0.000008728257,"threshold_uncertainty_score":0.2609501},"labels":[],"label_agreement":null},{"id":"W2111484900","doi":"10.1109/tcomm.2011.050211.100036a","title":"Cramer-Rao Lower Bounds of DOA Estimates from Square QAM-Modulated Signals","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Quadrature amplitude modulation; Cramér–Rao bound; QAM; Mathematics; Algorithm; Additive white Gaussian noise; Fisher information; Estimation theory; Statistics; White noise; Bit error rate; Decoding methods","score_opus":0.05889292817463917,"score_gpt":0.2964461860052343,"score_spread":0.23755325783059514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111484900","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":[0.007841808,0.000096683514,0.9859688,0.00037064494,0.0002819843,0.00029368198,0.00009314686,0.0005909037,0.0044622896],"genre_scores_gemma":[0.7086796,0.00009608968,0.2910144,0.00004082186,0.00000334978,0.00008159267,0.000008616758,0.000016105372,0.0000594195],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99841726,0.00015946309,0.00064214796,0.00029245554,0.00028623588,0.0002024407],"domain_scores_gemma":[0.9955251,0.0005828572,0.00031755434,0.0030707293,0.00041518768,0.00008853964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023515482,0.0001991271,0.00030758648,0.00035946094,0.0003191383,0.000051914278,0.0021825375,0.00012833394,0.0002563884],"category_scores_gemma":[0.000028523265,0.00021176993,0.00018661012,0.00088691927,0.00033846806,0.0006508112,0.000027468648,0.00028497967,0.00005144218],"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":[0.00032538795,0.020199655,0.0007200723,0.00027097584,0.0018763505,0.0000095919595,0.031627994,0.024795355,0.2568356,0.083380975,0.0026606473,0.5772974],"study_design_scores_gemma":[0.00039825108,0.0003874801,0.0015795466,0.00028349142,0.00010320738,0.000005679837,0.00010203369,0.18909208,0.77653253,0.030474905,0.000621576,0.00041922007],"about_ca_topic_score_codex":0.0012736663,"about_ca_topic_score_gemma":0.00011107221,"teacher_disagreement_score":0.7008378,"about_ca_system_score_codex":0.00005530101,"about_ca_system_score_gemma":0.000102161626,"threshold_uncertainty_score":0.8635727},"labels":[],"label_agreement":null},{"id":"W2112620443","doi":"10.1109/icassp.2003.1199945","title":"Robust adaptive beamforming using worst-case SINR optimization: a new diagonal loading-type solution for general-rank signal models","year":2004,"lang":"en","type":"article","venue":"2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Diagonal; Rank (graph theory); Adaptive beamformer; Beamforming; Mathematical optimization; Computer science; SIGNAL (programming language); Type (biology); Control theory (sociology); Mathematics; Telecommunications; Combinatorics; Artificial intelligence","score_opus":0.10537580720602725,"score_gpt":0.3062916911590948,"score_spread":0.2009158839530676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112620443","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":[0.0034094255,0.000091037,0.99136955,0.00017107723,0.00069306936,0.000776646,0.000045078294,0.00032350735,0.003120624],"genre_scores_gemma":[0.33072314,0.00007119413,0.668146,0.00022300558,0.0004130225,0.000036182624,0.000022433594,0.000042786258,0.00032222446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99647033,0.00002235336,0.00094790227,0.0009951483,0.00097111316,0.00059312995],"domain_scores_gemma":[0.99118006,0.00003053444,0.00089615,0.00016971628,0.007389758,0.00033378566],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00053016946,0.0005608605,0.0005200016,0.0005931897,0.0005423796,0.00083186006,0.00076855574,0.00032375904,0.000085806845],"category_scores_gemma":[0.000333422,0.00058393436,0.00009136599,0.0011210094,0.00025579042,0.0026286696,0.00013355032,0.00043046707,0.000007076671],"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":[0.00049074943,0.00059431157,0.000043762055,0.0002639737,0.00018481702,0.00009105803,0.0013357752,0.62134606,0.01954846,0.32992375,0.0024147558,0.023762556],"study_design_scores_gemma":[0.0010404491,0.0005356313,0.00000406486,0.0005696004,0.00007282894,0.00054842234,0.00013386818,0.9669477,0.016261732,0.013196402,0.0000718472,0.0006175014],"about_ca_topic_score_codex":0.00015599115,"about_ca_topic_score_gemma":0.000008018743,"teacher_disagreement_score":0.34560162,"about_ca_system_score_codex":0.00049863744,"about_ca_system_score_gemma":0.0016527518,"threshold_uncertainty_score":0.9996612},"labels":[],"label_agreement":null},{"id":"W2112920874","doi":"10.1109/iscas.2011.5937922","title":"Compressed sensing for DOA estimation with fewer receivers than sensors","year":2011,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Compressed sensing; Preprocessor; Algorithm; Computer science; Norm (philosophy); Direction of arrival; Domain (mathematical analysis); Mathematical optimization; Mathematics; Artificial intelligence; Telecommunications","score_opus":0.03399987484798808,"score_gpt":0.25504688464278163,"score_spread":0.22104700979479355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112920874","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":[0.010832291,0.000001289109,0.97505265,0.00009762928,0.000106281856,0.00029950117,0.000001169976,0.0005681815,0.013041026],"genre_scores_gemma":[0.40349314,5.112878e-7,0.59633946,0.000027542463,0.0000041544936,0.000004314279,0.0000013286244,0.0000055217865,0.0001240496],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999301,0.000027880775,0.0001706491,0.0002116537,0.0001620567,0.00012676301],"domain_scores_gemma":[0.9991848,0.00009123945,0.00013281111,0.00030942858,0.0002383799,0.00004334102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016021966,0.000096489755,0.00012562929,0.00012293686,0.00007031357,0.00003980618,0.00021509801,0.00003942653,0.0000144409305],"category_scores_gemma":[0.000046277255,0.000079543934,0.000036288056,0.00023091138,0.000049927447,0.0005443201,0.00003605678,0.00003892024,0.0000066764087],"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":[0.00039689674,0.00046176382,0.002191823,0.00033892124,0.00023715015,0.000015819609,0.013889816,0.010655422,0.015009491,0.30001482,0.008979542,0.64780855],"study_design_scores_gemma":[0.00021788104,0.00014768713,0.0012581005,0.000043682347,0.00000863741,0.00000979265,0.000035514353,0.6767345,0.31508908,0.006175323,0.00014402029,0.00013579114],"about_ca_topic_score_codex":0.00018187914,"about_ca_topic_score_gemma":0.000014102164,"teacher_disagreement_score":0.66607904,"about_ca_system_score_codex":0.000024029407,"about_ca_system_score_gemma":0.00003064086,"threshold_uncertainty_score":0.32437074},"labels":[],"label_agreement":null},{"id":"W2113168978","doi":"10.1109/tsp.2002.806865","title":"Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1485,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Adaptive beamformer; Beamforming; Diagonal; Control theory (sociology); SIGNAL (programming language); Computer science; Convex optimization; Optimization problem; Antenna array; Mathematical optimization; Algorithm; Mathematics; Antenna (radio); Regular polygon; Telecommunications","score_opus":0.05056948937366794,"score_gpt":0.25946602533642976,"score_spread":0.2088965359627618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113168978","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":[0.002272981,0.000034020573,0.9955979,0.00014579862,0.00013352624,0.0005248845,0.000003071586,0.0003135703,0.0009742239],"genre_scores_gemma":[0.5556334,0.0000023260259,0.44417572,0.00006639786,0.000015964788,0.000053354335,2.4896477e-7,0.00001460421,0.000037950813],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981766,0.00012579911,0.00048766992,0.00042479162,0.00045265222,0.000332514],"domain_scores_gemma":[0.99887604,0.00009351068,0.00025249136,0.00027569558,0.0003923267,0.000109962726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063281716,0.00023776003,0.00020536743,0.00032909898,0.001090385,0.00022512407,0.0003738783,0.000093394345,0.000038887407],"category_scores_gemma":[0.000006280553,0.00020612532,0.00008822486,0.0015488466,0.00007721341,0.0015930762,0.0000053222902,0.00028955945,0.000007630157],"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":[0.000020006282,0.0000852471,0.0000016698392,0.00004323177,0.0000122826095,0.000005539049,0.000994783,0.9017516,0.0008110519,0.00008810404,0.000015237014,0.0961713],"study_design_scores_gemma":[0.00015229482,0.00017195138,8.1568606e-7,0.0002944908,0.000027635333,0.00045630467,0.00014166618,0.906196,0.092176944,0.00009010708,0.00006997997,0.00022181163],"about_ca_topic_score_codex":0.000035741272,"about_ca_topic_score_gemma":0.000009899383,"teacher_disagreement_score":0.55336046,"about_ca_system_score_codex":0.00019233754,"about_ca_system_score_gemma":0.0002860244,"threshold_uncertainty_score":0.84055465},"labels":[],"label_agreement":null},{"id":"W2113509911","doi":"10.1109/icassp.2012.6288674","title":"Correlogram for undersampled data: Bias and variance analysis","year":2012,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Correlogram; Estimator; Variance (accounting); Mathematics; Statistics; Minimum-variance unbiased estimator; Computer science; Bias of an estimator; Algorithm","score_opus":0.1676091129324707,"score_gpt":0.36037032998111324,"score_spread":0.19276121704864255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113509911","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":[0.00056656206,0.000040473504,0.9976334,0.00019603784,0.00012534231,0.00013303204,0.000008114502,0.00022518875,0.0010718361],"genre_scores_gemma":[0.47494072,0.000006134031,0.5248396,0.00006486166,0.000011726686,0.000009532917,0.000012124265,0.000002021723,0.00011328212],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994093,0.000027547938,0.0001509243,0.00018815952,0.00009707649,0.00012695756],"domain_scores_gemma":[0.99888235,0.0003124459,0.00008549209,0.00059990695,0.000065422,0.000054404332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005620292,0.000057598132,0.00013328955,0.00014317561,0.000044060802,0.000059231283,0.00044066415,0.00003225566,0.000010163567],"category_scores_gemma":[0.00021067102,0.00005016744,0.0000325718,0.00066032726,0.00003067654,0.00092950015,0.00020047075,0.00002552873,0.0000018753425],"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":[0.000008069676,0.00021611602,0.037210952,0.000050510647,0.00046323086,1.7083521e-7,0.00050678477,0.00009768192,0.00029190374,0.77828324,0.012581553,0.17028977],"study_design_scores_gemma":[0.00022179684,0.000066698216,0.02576038,0.000007341909,0.00020823763,0.0000038362273,0.00003273671,0.94393706,0.004612727,0.014366634,0.0105603235,0.00022220248],"about_ca_topic_score_codex":0.00012860996,"about_ca_topic_score_gemma":0.000024276764,"teacher_disagreement_score":0.94383943,"about_ca_system_score_codex":0.00000899844,"about_ca_system_score_gemma":0.000016310702,"threshold_uncertainty_score":0.20457688},"labels":[],"label_agreement":null},{"id":"W2116377224","doi":"10.1109/aps.2007.4396383","title":"Effect of temporal correlation on the adaptive beamforming performance","year":2007,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Correlation; Interference (communication); SIGNAL (programming language); Noise (video); Null (SQL); Signal-to-noise ratio (imaging); Adaptive beamformer; Beamforming; Computer science; Algorithm; Statistics; Electronic engineering; Mathematics; Telecommunications; Engineering; Artificial intelligence; Channel (broadcasting); Data mining","score_opus":0.011415489833535306,"score_gpt":0.2604822405350971,"score_spread":0.2490667507015618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116377224","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":[0.2391175,0.0000023092286,0.7431486,0.00004822821,0.00008874453,0.00016139801,1.4826445e-7,0.000104021645,0.017328994],"genre_scores_gemma":[0.9628002,8.034188e-7,0.03704253,0.000033595745,0.000007639655,0.000004905953,3.6281875e-7,0.0000026386,0.00010730052],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99939466,0.000033114073,0.00018629758,0.00009233135,0.00021356106,0.0000800423],"domain_scores_gemma":[0.9990535,0.0005085449,0.0001424905,0.00021487361,0.00006491109,0.000015729875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011804132,0.000060425074,0.00008367283,0.00009229338,0.000050070288,0.000008676962,0.00024692138,0.000028600594,0.000007822665],"category_scores_gemma":[0.00007769697,0.000036751375,0.000033438893,0.00028996685,0.000041692154,0.0003114086,0.000043177435,0.00006481942,0.000007426621],"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":[0.00013949825,0.00006991533,0.014119066,0.000058920326,0.000020342632,7.0019377e-7,0.0012167419,0.0017508926,0.0022912556,0.23958614,0.00045899785,0.74028754],"study_design_scores_gemma":[0.000076597076,0.00083163846,0.0053879274,0.000053022253,0.0000024412868,0.0000019197253,0.00001217189,0.27224424,0.72097975,0.00028464725,0.00007386162,0.000051782612],"about_ca_topic_score_codex":0.000035482826,"about_ca_topic_score_gemma":0.0000016935094,"teacher_disagreement_score":0.74023575,"about_ca_system_score_codex":0.000024668023,"about_ca_system_score_gemma":0.000013812829,"threshold_uncertainty_score":0.14986776},"labels":[],"label_agreement":null},{"id":"W2117133262","doi":"10.1109/icassp.2003.1199950","title":"Adaptive beamforming with joint robustness against signal steering vector errors and interference nonstationarity","year":2004,"lang":"en","type":"article","venue":"2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Adaptive beamformer; Robustness (evolution); Beamforming; Computer science; Interference (communication); Algorithm; Joint (building); Control theory (sociology); SIGNAL (programming language); Artificial intelligence; Telecommunications; Engineering","score_opus":0.043482661346346735,"score_gpt":0.27411817898227736,"score_spread":0.23063551763593063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117133262","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":[0.052988876,0.000043741136,0.937217,0.00018690964,0.00030557372,0.00049676123,0.000035434183,0.00031364945,0.008412075],"genre_scores_gemma":[0.71692765,0.00006756114,0.28257418,0.00014594026,0.00008388183,0.00004450904,0.000008780199,0.000026721189,0.00012078775],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99693644,0.000021619844,0.000733377,0.0008946618,0.00096456433,0.00044932181],"domain_scores_gemma":[0.993871,0.000023238672,0.0007215523,0.00015134277,0.004979151,0.00025375857],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00044316988,0.0005048523,0.0004850978,0.0004826031,0.00032508487,0.00067815743,0.0006996064,0.00019569787,0.00004125582],"category_scores_gemma":[0.00024333694,0.0004633388,0.00003979075,0.0007681957,0.0004703759,0.0018180858,0.00016699676,0.00057290005,0.0000073354827],"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":[0.0008757702,0.0015217538,0.0016325926,0.0011611542,0.00043465022,0.00015907353,0.0068367766,0.019909192,0.07346828,0.7695973,0.00092389825,0.12347956],"study_design_scores_gemma":[0.0010731206,0.0009414073,0.00079611025,0.0017160036,0.000042703065,0.00017549016,0.00096608576,0.94321615,0.047114413,0.003099729,0.00005302794,0.00080577855],"about_ca_topic_score_codex":0.00006187114,"about_ca_topic_score_gemma":0.000014339736,"teacher_disagreement_score":0.92330694,"about_ca_system_score_codex":0.00028575247,"about_ca_system_score_gemma":0.0008044233,"threshold_uncertainty_score":0.99978185},"labels":[],"label_agreement":null},{"id":"W2117330767","doi":"10.1109/ccece.2006.277823","title":"SVM Classifier Approach to Enumerate Directional Signals Impinging on an Array of Sensors","year":2006,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Support vector machine; Pattern recognition (psychology); Computer science; Classifier (UML); Generative model; A priori and a posteriori; Sensor array; Artificial intelligence; Signal processing; Enumeration; Statistical model; Machine learning; Algorithm; Generative grammar; Mathematics","score_opus":0.02180116494730534,"score_gpt":0.26952532460875134,"score_spread":0.247724159661446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117330767","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":[0.037168328,0.0000028570482,0.8576515,0.00013309019,0.000111301255,0.00015348554,0.0000023773434,0.00035596677,0.10442111],"genre_scores_gemma":[0.69310546,3.4702524e-7,0.30610725,0.00007528298,0.000035684545,0.000016011267,0.0000024558494,0.000007196278,0.00065027864],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99878544,0.000076857,0.00032560097,0.0003175256,0.00033637887,0.00015820545],"domain_scores_gemma":[0.999215,0.00008151219,0.00013144079,0.00033633166,0.00017341656,0.00006231318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003555351,0.000117662166,0.00017586471,0.00030088905,0.0000623525,0.000054903096,0.00031485435,0.000050148894,0.000022738386],"category_scores_gemma":[0.000035702542,0.00010766079,0.0000605349,0.0005727791,0.00003138984,0.00037635394,0.000037918027,0.00006954405,0.000011928697],"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":[0.000030725554,0.00096738455,0.0012898186,0.000056973367,0.000038838403,0.0000012923911,0.00066743477,0.068939514,0.476091,0.4165047,0.0042615035,0.031150784],"study_design_scores_gemma":[0.000079749756,0.00013009708,0.0038479168,0.00002654182,0.0000029396172,0.0000051914917,0.000015547092,0.062466476,0.9282839,0.0044065635,0.0005721102,0.00016298224],"about_ca_topic_score_codex":0.00020280472,"about_ca_topic_score_gemma":0.0000035924245,"teacher_disagreement_score":0.65593714,"about_ca_system_score_codex":0.000040069186,"about_ca_system_score_gemma":0.000038176084,"threshold_uncertainty_score":0.43902797},"labels":[],"label_agreement":null},{"id":"W2121165908","doi":"10.1109/tsp.2004.838966","title":"Maximum likelihood direction-of-arrival estimation in unknown noise fields using sparse sensor arrays","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":101,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Direction of arrival; Estimator; Algorithm; Noise (video); Mathematics; Covariance matrix; Identifiability; Sensor array; Covariance; Computer science; Statistics; Artificial intelligence; Telecommunications","score_opus":0.022860702600461316,"score_gpt":0.2763915560202189,"score_spread":0.2535308534197576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121165908","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":[0.05734338,0.00003376206,0.9412546,0.00013657649,0.00028306304,0.0002642753,0.00000389335,0.0003181631,0.00036225907],"genre_scores_gemma":[0.7402826,0.0000066611096,0.25961548,0.000031678035,0.000015836818,0.000020465082,7.127362e-7,0.00001778397,0.000008770389],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99803674,0.00007531564,0.000694939,0.00043126292,0.0004669935,0.00029473295],"domain_scores_gemma":[0.9989108,0.00009598988,0.00033753988,0.00031194248,0.00025140433,0.000092341696],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003463918,0.00024183201,0.0003321607,0.0006972953,0.00020344571,0.00009347207,0.0003508805,0.00016746623,0.000017661145],"category_scores_gemma":[0.000017479937,0.00026127254,0.00012929906,0.00138405,0.0000992198,0.001265958,0.0000047516296,0.00033291924,0.000006241378],"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":[0.000038431404,0.00040235528,0.000019695168,0.00014278981,0.000015719539,0.000005731133,0.0009647764,0.6874492,0.032407705,0.00018922193,0.0000016978536,0.27836266],"study_design_scores_gemma":[0.0004508638,0.0001361163,0.000064050655,0.0005157239,0.000022158396,0.000028845672,0.000031832053,0.4569517,0.53238875,0.009186428,0.000006534573,0.00021699099],"about_ca_topic_score_codex":0.00023349407,"about_ca_topic_score_gemma":0.00004335464,"teacher_disagreement_score":0.68293923,"about_ca_system_score_codex":0.00021683358,"about_ca_system_score_gemma":0.0003473914,"threshold_uncertainty_score":0.99998397},"labels":[],"label_agreement":null},{"id":"W2121951709","doi":"10.1109/isspa.2005.1580279","title":"Colored loading for robust adaptive beamforming with low sample support","year":2006,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Diagonal; Signal-to-interference-plus-noise ratio; Covariance matrix; Identity matrix; Colored; Algorithm; Colors of noise; Adaptive beamformer; Beamforming; Toeplitz matrix; Matrix (chemical analysis); Hermitian matrix; Computer science; Mathematics; Interference (communication); Control theory (sociology); Applied mathematics; Mathematical optimization; White noise; Telecommunications; Physics; Geometry; Materials science; Artificial intelligence","score_opus":0.016376980972717035,"score_gpt":0.23635049013113138,"score_spread":0.21997350915841435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121951709","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":[0.002079742,0.0000019464896,0.9884728,0.00007764643,0.000057642763,0.00034132565,0.000006643207,0.0004484183,0.008513801],"genre_scores_gemma":[0.28503343,2.3640807e-7,0.7145603,0.000039636463,0.00001637235,0.00005285814,0.0000061250316,0.000006947797,0.00028409122],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992125,0.000008707873,0.00021034406,0.00021843126,0.00017027569,0.00017975326],"domain_scores_gemma":[0.99921286,0.00023130393,0.00012581833,0.00020974044,0.00018673507,0.00003352056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017693923,0.00009585845,0.00013925537,0.00011490321,0.00008665376,0.00005730103,0.0002882767,0.000035661604,0.000021267879],"category_scores_gemma":[0.00004481305,0.00008049803,0.000041171927,0.00028945022,0.00003979735,0.0006016404,0.000052949574,0.00003594543,0.0000029863847],"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":[0.00010323355,0.0002888981,0.0017277285,0.0001018888,0.000053344032,0.0000044133367,0.00056573964,0.018024936,0.004221886,0.9102302,0.012739423,0.051938273],"study_design_scores_gemma":[0.00049532845,0.0007906736,0.0005438653,0.000062119216,0.000012079013,0.000016373584,0.00006797814,0.5724811,0.4034081,0.020088844,0.0017214052,0.00031210447],"about_ca_topic_score_codex":0.0004413317,"about_ca_topic_score_gemma":0.00010275702,"teacher_disagreement_score":0.89014137,"about_ca_system_score_codex":0.000053712254,"about_ca_system_score_gemma":0.00007946814,"threshold_uncertainty_score":0.32826144},"labels":[],"label_agreement":null},{"id":"W2123109827","doi":"10.1109/aps.1998.690784","title":"Smart antenna calibration for beamforming","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Beamforming; Smart antenna; Computer science; Calibration; Antenna array; Antenna (radio); Electronic engineering; Direction of arrival; Sensor array; Coupling (piping); Acoustics; Directional antenna; Telecommunications; Engineering; Mathematics; Physics; Statistics","score_opus":0.032103485681111855,"score_gpt":0.2560533611305458,"score_spread":0.22394987544943393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123109827","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":[0.0005011765,0.000009793342,0.9902454,0.0005058601,0.00011783723,0.00015376716,7.1833733e-7,0.00039740565,0.008068031],"genre_scores_gemma":[0.34916553,0.0000038610756,0.64954525,0.00014989071,0.000014742333,0.000028267901,9.972348e-7,0.0000038576627,0.001087586],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995445,0.0000075510184,0.0001541837,0.00011713865,0.00009390648,0.000082728504],"domain_scores_gemma":[0.9996151,0.00005467621,0.000057396806,0.00018138473,0.00006756078,0.000023879327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010818098,0.000045828456,0.00006494266,0.000076771496,0.000046575315,0.000043039276,0.00020742875,0.000024947336,0.0000409117],"category_scores_gemma":[0.00005635722,0.00004158308,0.00003513295,0.00017650379,0.000012630035,0.00071944343,0.0000337409,0.000019210225,0.000006702508],"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":[0.0000031334007,0.00012828628,0.0004597985,0.00005706924,0.000014003093,5.331991e-7,0.00072334195,0.000052865027,0.017701508,0.6572757,0.016433064,0.30715072],"study_design_scores_gemma":[0.00006455723,0.00005313961,0.000058114765,0.0000088128,0.000001246791,0.0000026432838,0.0000039958845,0.8994917,0.09025497,0.00727707,0.0027254976,0.000058222526],"about_ca_topic_score_codex":0.00001760519,"about_ca_topic_score_gemma":0.0000030828846,"teacher_disagreement_score":0.89943886,"about_ca_system_score_codex":0.00001206771,"about_ca_system_score_gemma":0.0000061246024,"threshold_uncertainty_score":0.16957088},"labels":[],"label_agreement":null},{"id":"W2124166795","doi":"10.1109/ccece.2007.193","title":"Short Data Record DoA and Timing Estimation in Multipath DS/CDMA Systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Multipath propagation; Computer science; Smoothing; Code division multiple access; Direction of arrival; Antenna (radio); Algorithm; Joint (building); Smart antenna; Antenna array; Real-time computing; Electronic engineering; Telecommunications; Directional antenna; Engineering","score_opus":0.07215820564118244,"score_gpt":0.34323039715765546,"score_spread":0.271072191516473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124166795","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":[0.02458517,0.000028286287,0.97141415,0.000047579728,0.00021088724,0.00022022991,0.0000023922228,0.00028849245,0.0032028258],"genre_scores_gemma":[0.5952188,0.000005941183,0.4046969,0.000012696269,0.0000077811765,0.000004448322,0.0000058716323,0.0000037163945,0.000043841374],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998956,0.00003061918,0.00037287455,0.00030972328,0.00019122806,0.00013955246],"domain_scores_gemma":[0.9990221,0.00016047593,0.00007875362,0.0006313886,0.000059558042,0.000047724017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012107322,0.00008415295,0.00013642453,0.00023755657,0.000034851288,0.00008936894,0.0005183129,0.00005262886,0.0000024755786],"category_scores_gemma":[0.00016169256,0.00008031619,0.000009699848,0.00034931322,0.000024936888,0.0011442727,0.0002913475,0.000068156,0.000003339577],"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":[0.000005780798,0.000059161688,0.012219823,0.00007180074,0.0000063499233,0.00000767956,0.00032659582,0.00062538404,0.000784319,0.01475838,0.00057147205,0.97056323],"study_design_scores_gemma":[0.00007144182,0.000023952829,0.012121794,0.000078044795,0.0000020586858,0.000012519616,0.000025255897,0.9831263,0.003778184,0.00040487017,0.00025656266,0.000099012694],"about_ca_topic_score_codex":0.0006784842,"about_ca_topic_score_gemma":0.00012320824,"teacher_disagreement_score":0.9825009,"about_ca_system_score_codex":0.000040191695,"about_ca_system_score_gemma":0.00002013883,"threshold_uncertainty_score":0.32751992},"labels":[],"label_agreement":null},{"id":"W2125505169","doi":"10.1109/aps.2009.5171465","title":"Elimination of direction of arrival estimation ambiguities through the use of non-square coupling matrices","year":2009,"lang":"en","type":"article","venue":"Digest - IEEE Antennas and Propagation Society. International Symposium","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Beamforming; Square (algebra); Direction of arrival; Smart antenna; Coupling (piping); Matrix (chemical analysis); Computer science; Antenna (radio); Antenna array; Electronic engineering; Acoustics; Algorithm; Topology (electrical circuits); Mathematics; Physics; Directional antenna; Telecommunications; Engineering; Electrical engineering; Geometry; Materials science","score_opus":0.02582866485452834,"score_gpt":0.2811989106564506,"score_spread":0.25537024580192225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125505169","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":[0.24796562,0.00008440717,0.74856967,0.0017892844,0.00050838024,0.00044151803,0.00003132501,0.00009011724,0.00051968376],"genre_scores_gemma":[0.9689707,0.0005939025,0.030207822,0.00006223661,0.00004834623,0.000018283172,0.000029324017,0.000008377325,0.000060968567],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99824804,0.000042578533,0.0007497689,0.00023948569,0.00060787,0.00011228161],"domain_scores_gemma":[0.9972863,0.00023995095,0.0010721928,0.00023962745,0.0011389633,0.000022938608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040286817,0.00015280055,0.0002516668,0.00010377308,0.000111408,0.000085445055,0.0003574651,0.00009292096,0.000003625055],"category_scores_gemma":[0.00009683285,0.00012750622,0.0001585225,0.00043989028,0.00018208157,0.0016542592,0.00004928273,0.00009588287,4.779779e-7],"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":[0.00018254748,0.0009478704,0.0052406457,0.0007958138,0.00036935476,0.0000011041966,0.024546335,0.05614766,0.73591197,0.10999222,0.0012615409,0.064602956],"study_design_scores_gemma":[0.0002793018,0.0003025544,0.015657557,0.00037206645,0.000036462076,0.0000075184203,0.00027080427,0.56520945,0.4152716,0.0022469943,0.00019261215,0.00015304158],"about_ca_topic_score_codex":0.00024525207,"about_ca_topic_score_gemma":0.0000028967331,"teacher_disagreement_score":0.72100514,"about_ca_system_score_codex":0.00004966608,"about_ca_system_score_gemma":0.000049216564,"threshold_uncertainty_score":0.5199553},"labels":[],"label_agreement":null},{"id":"W2126344571","doi":"10.1109/tsp.2003.820089","title":"A Generalized Capon Estimator for Localization of Multiple Spread Sources","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":114,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Capon; Estimator; Algorithm; Mathematics; Estimation theory; Computer science; Statistics; Beamforming","score_opus":0.024488961679666566,"score_gpt":0.279672682163631,"score_spread":0.2551837204839644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126344571","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":[0.0072785774,0.000046240315,0.9917964,0.000070622234,0.0000999415,0.0003312673,0.000011691333,0.00030939924,0.000055913584],"genre_scores_gemma":[0.7265551,0.0000028042912,0.2733033,0.000031810923,0.000010242547,0.00006382533,0.0000014198959,0.000012993383,0.000018522267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988729,0.000028509028,0.00040836414,0.000264741,0.00027118772,0.00015431765],"domain_scores_gemma":[0.9990938,0.000103842845,0.00025823197,0.00018392214,0.00030657256,0.000053674416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018219219,0.0001402453,0.00021541172,0.00026187938,0.0002086234,0.000060309136,0.0002770262,0.00007896691,0.000006286546],"category_scores_gemma":[0.000016455297,0.00014004663,0.000103778824,0.00048344626,0.000078320605,0.0006215373,0.0000018140674,0.00007506035,0.0000017560188],"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":[0.00008297922,0.00038972782,0.000017057662,0.0003324778,0.000025208265,6.2336983e-7,0.001003654,0.73474896,0.057994187,0.0013373255,0.000009801995,0.20405799],"study_design_scores_gemma":[0.00043588734,0.00011186667,0.000004481763,0.00015430889,0.000013866831,0.000003601715,0.000013268867,0.40875134,0.5876244,0.002765612,0.000032165924,0.0000892057],"about_ca_topic_score_codex":0.000091951566,"about_ca_topic_score_gemma":0.000013238806,"teacher_disagreement_score":0.7192765,"about_ca_system_score_codex":0.00006359459,"about_ca_system_score_gemma":0.000171954,"threshold_uncertainty_score":0.57109356},"labels":[],"label_agreement":null},{"id":"W2127389695","doi":"10.1109/lcomm.2012.12.121706","title":"True ML Estimator for the Location Parameter of the Generalized Gaussian Distribution with p = 4","year":2013,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Estimator; Mathematics; Efficient estimator; Mean squared error; Trimmed estimator; Minimax estimator; Consistent estimator; Bias of an estimator; Cramér–Rao bound; Minimum-variance unbiased estimator; Estimation theory; Statistics; Moment (physics); Stein's unbiased risk estimate; Applied mathematics; Upper and lower bounds; Maximum likelihood sequence estimation; Mathematical analysis; Physics","score_opus":0.024065932969750216,"score_gpt":0.26869135593065163,"score_spread":0.24462542296090142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127389695","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":[0.019799706,0.000044846598,0.9449932,0.034043223,0.00010800325,0.00085407833,0.000010837097,0.000092023256,0.00005409784],"genre_scores_gemma":[0.7978046,0.000011122275,0.20108362,0.00047252505,0.000008101795,0.00058541744,0.000012843993,0.00000726154,0.0000145348795],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913394,0.00014595257,0.00029944326,0.00013231156,0.00017525975,0.00011309244],"domain_scores_gemma":[0.9962566,0.0006070205,0.0003210682,0.0025054337,0.00028659726,0.000023286504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024109338,0.00009510442,0.00011865295,0.00004340681,0.00029178648,0.00007464855,0.0021084284,0.000033243727,0.000003074355],"category_scores_gemma":[0.00013729821,0.000056075307,0.00006869428,0.00051469903,0.00033576103,0.00037355203,0.0001369703,0.00009756415,0.0000038512894],"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":[0.000060460232,0.0008655227,0.005653745,0.0002919707,0.0005012498,1.730686e-7,0.003530603,0.021702632,0.1509178,0.52090985,0.11366149,0.18190454],"study_design_scores_gemma":[0.0006755478,0.000100035504,0.033629123,0.00019098743,0.00008936958,0.000010349317,0.000052223466,0.7857879,0.16631559,0.0071562883,0.0056760837,0.00031652808],"about_ca_topic_score_codex":0.0002778396,"about_ca_topic_score_gemma":0.0000213401,"teacher_disagreement_score":0.7780049,"about_ca_system_score_codex":0.00005105586,"about_ca_system_score_gemma":0.000052869702,"threshold_uncertainty_score":0.39180195},"labels":[],"label_agreement":null},{"id":"W2127439636","doi":"10.1109/ccece.2005.1557190","title":"A deterministic direction finding approach using a single snapshot of array measurement","year":2006,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Snapshot (computer storage); Computer science; Direction of arrival; Sonar; Algorithm; Radar; Direction finding; Radar signal processing; Main lobe; Signal processing; Telecommunications; Artificial intelligence; Antenna (radio)","score_opus":0.07928707772033869,"score_gpt":0.27297997027974846,"score_spread":0.19369289255940977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127439636","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":[0.0137905795,0.000016476162,0.94617456,0.00001033847,0.00012943211,0.00015173286,5.280026e-7,0.00018465373,0.039541725],"genre_scores_gemma":[0.63001424,2.2687541e-7,0.36993402,0.000004532573,0.000013278099,0.0000069561024,8.979584e-7,0.000004292581,0.000021543212],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987698,0.00006297029,0.00037077608,0.00022607874,0.00043594203,0.00013440113],"domain_scores_gemma":[0.9992016,0.00004275576,0.00023756064,0.00028067618,0.00021190067,0.000025486446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005518229,0.00010087818,0.00017302194,0.00022298885,0.000060086815,0.000046054953,0.00024866263,0.000042960848,0.000010890849],"category_scores_gemma":[0.00009347369,0.00009734913,0.0000637064,0.0004785846,0.000041124422,0.00029665872,0.00004436666,0.000043066928,7.519202e-7],"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":[0.0000059293993,0.0004945055,0.000693568,0.00011827112,0.000017507236,7.3999627e-7,0.00021407122,0.0019186173,0.96101385,0.015759852,0.00017662175,0.019586444],"study_design_scores_gemma":[0.00009846398,0.00007631592,0.00084619666,0.00006575195,0.000011498741,0.000014610635,0.000010307778,0.17024925,0.82565624,0.0027702313,0.00007510086,0.00012600861],"about_ca_topic_score_codex":0.0002991455,"about_ca_topic_score_gemma":0.000011259861,"teacher_disagreement_score":0.6162237,"about_ca_system_score_codex":0.00013673598,"about_ca_system_score_gemma":0.000054248536,"threshold_uncertainty_score":0.39697826},"labels":[],"label_agreement":null},{"id":"W2127902187","doi":"10.1109/glocom.2004.1378462","title":"Joint domain localized adaptive processing with zero forcing for multi-cell CDMA systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Beamforming; Convergence (economics); Joint (building); Telecommunications link; Signal processing; Algorithm; Rate of convergence; Forcing (mathematics); Code division multiple access; Digital signal processing; Channel (broadcasting); Mathematics; Telecommunications; Engineering; Computer hardware","score_opus":0.04068026331602576,"score_gpt":0.2750256171898768,"score_spread":0.23434535387385103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127902187","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":[0.0010388908,0.00008995286,0.99428254,0.00009836982,0.00005968592,0.00074613345,0.0000013797836,0.000611231,0.0030717833],"genre_scores_gemma":[0.4307922,6.7356115e-7,0.56867236,0.000039227085,0.0000143230645,0.0000973849,5.6257073e-7,0.000009548399,0.00037372552],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988705,0.000034547713,0.0003429396,0.00030788884,0.00023291037,0.00021121289],"domain_scores_gemma":[0.99908805,0.000054881923,0.00024339618,0.0002632027,0.00028635096,0.00006412735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036609697,0.0001424479,0.0002313176,0.00013415459,0.00011166048,0.00013199847,0.00030107785,0.000052442127,0.0000019341007],"category_scores_gemma":[0.00002176667,0.00010941869,0.0000498408,0.00027855678,0.000042958396,0.0007479873,0.000062342995,0.000058124537,0.0000040544282],"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":[0.00034380495,0.0016050412,0.00035472188,0.0019411166,0.00013512083,0.000010662745,0.010028108,0.058782876,0.030150712,0.3179652,0.005423573,0.57325906],"study_design_scores_gemma":[0.0007648481,0.00017950516,0.000012995626,0.00017223656,0.0000047525023,0.000009393041,0.000099613404,0.8848432,0.11233011,0.0006264139,0.0007982877,0.00015870007],"about_ca_topic_score_codex":0.00008809947,"about_ca_topic_score_gemma":0.000017573446,"teacher_disagreement_score":0.82606024,"about_ca_system_score_codex":0.00009398539,"about_ca_system_score_gemma":0.000100974285,"threshold_uncertainty_score":0.44619647},"labels":[],"label_agreement":null},{"id":"W2128590775","doi":"10.1049/ip-rsn:20000419","title":"Complexity-reduced direction-of-arrival estimation method for highly correlated sources","year":2000,"lang":"en","type":"article","venue":"IEE Proceedings - Radar Sonar and Navigation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Smoothing; Snapshot (computer storage); Subspace topology; Preprocessor; Computational complexity theory; Algorithm; Signal subspace; Computer science; Covariance matrix; Correlation; Mathematical optimization; Artificial intelligence; Mathematics; Noise (video); Computer vision; Image (mathematics)","score_opus":0.016973784788041228,"score_gpt":0.2879251491084966,"score_spread":0.27095136432045536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128590775","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":[0.409561,0.000091309186,0.5879159,0.00043232064,0.00016964074,0.00059992936,0.000015131428,0.00047711455,0.0007376513],"genre_scores_gemma":[0.5188239,0.000018162718,0.48094133,0.000017989194,0.00003085316,0.000044988203,0.000021469572,0.000012791294,0.00008847092],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853355,0.00002896323,0.00053088844,0.00039213398,0.0003293866,0.00018509736],"domain_scores_gemma":[0.9988256,0.00015647225,0.00039917222,0.00012311443,0.00041860738,0.000077031655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005820263,0.00018594223,0.00030511522,0.0001927843,0.00022818027,0.00009900757,0.00027504365,0.0001297949,0.000014355133],"category_scores_gemma":[0.00006924165,0.0001921519,0.00008747648,0.0006383417,0.000114278155,0.0010575161,0.000033939137,0.00011670221,0.00000310914],"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":[0.00013329802,0.00016359444,0.00039742328,0.00039391365,0.00006414586,3.4933905e-7,0.0044291257,0.00023592495,0.06250736,0.072455935,0.00065722934,0.8585617],"study_design_scores_gemma":[0.0006436351,0.00035305042,0.0025738166,0.0002737668,0.000052554104,0.000045486777,0.00006904084,0.5083316,0.41484544,0.071369454,0.0011521222,0.0002900693],"about_ca_topic_score_codex":0.00014001511,"about_ca_topic_score_gemma":0.0000011680895,"teacher_disagreement_score":0.8582716,"about_ca_system_score_codex":0.000049690167,"about_ca_system_score_gemma":0.000048181835,"threshold_uncertainty_score":0.78357273},"labels":[],"label_agreement":null},{"id":"W2128746719","doi":"10.1109/icics.2003.1292616","title":"Cramer-Rao bounds for estimation of pure-tone signals' Azimuth-elevation arrival angles & polarization parameters & frequencies using a dipole-triad or a loop-triad","year":2004,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Azimuth; Dipole; Cramér–Rao bound; Amplitude; Polarization (electrochemistry); Direction of arrival; Triad (sociology); Physics; Multiple signal classification; Computational physics; Antenna (radio); Acoustics; Estimation theory; Optics; Algorithm; Computer science; Telecommunications; Chemistry","score_opus":0.0607132256543674,"score_gpt":0.339721564844196,"score_spread":0.2790083391898286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128746719","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":[0.29802027,0.000038320526,0.700174,0.00023314607,0.00021503758,0.0008144434,0.000023775345,0.0004091656,0.00007185221],"genre_scores_gemma":[0.4579274,0.000005764128,0.541711,0.00006230779,0.000025130059,0.00005499675,0.00006199711,0.000021063248,0.00013033945],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9971114,0.00012304042,0.0011263462,0.00056193117,0.0007016022,0.00037567483],"domain_scores_gemma":[0.9969883,0.0004672241,0.0009785909,0.00070943445,0.00074545655,0.00011097732],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008804386,0.00033034317,0.00052417174,0.00073906523,0.000233532,0.00026267834,0.0006336003,0.00021748335,0.000028996346],"category_scores_gemma":[0.0017734305,0.00030364713,0.00020363048,0.0016205149,0.00021026595,0.0020250753,0.00011304093,0.00013142927,0.00001053045],"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":[0.00036686694,0.00096229726,0.0010270136,0.0006387354,0.0002597778,0.0000018073911,0.0035352977,0.25363627,0.5739199,0.109295785,0.0003608171,0.055995457],"study_design_scores_gemma":[0.001965777,0.00059149106,0.0007271518,0.00051919615,0.00014735034,0.00003463509,0.00009505485,0.37628004,0.4780938,0.14059718,0.00018345755,0.00076485024],"about_ca_topic_score_codex":0.0010849874,"about_ca_topic_score_gemma":0.00017527107,"teacher_disagreement_score":0.15990713,"about_ca_system_score_codex":0.00029742697,"about_ca_system_score_gemma":0.00042839866,"threshold_uncertainty_score":0.9999416},"labels":[],"label_agreement":null},{"id":"W2129146546","doi":"10.1109/7.976956","title":"Direction finding with a four-element Adcock-Butler matrix antenna array","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nortel (Canada); Royal Military College of Canada","funders":"","keywords":"Estimator; Antenna (radio); Direction finding; Algorithm; Antenna array; Antenna measurement; Radiation pattern; Antenna noise temperature; Electronic engineering; Discrete Fourier transform (general); Computer science; Fourier transform; Mathematics; Engineering; Antenna factor; Telecommunications; Mathematical analysis; Fourier analysis; Fractional Fourier transform; Statistics","score_opus":0.014443364427687528,"score_gpt":0.2516337031443645,"score_spread":0.23719033871667697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129146546","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":[0.025601061,0.00027282143,0.9719836,0.00039358824,0.0004025131,0.00038000816,0.0000032789435,0.00038234022,0.00058080093],"genre_scores_gemma":[0.9933955,0.00051163073,0.003413264,0.000028229028,0.000032585645,0.0001345604,6.587209e-7,0.000021974283,0.0024615717],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984129,0.00009004869,0.00030140864,0.0004240003,0.00035042738,0.00042123493],"domain_scores_gemma":[0.9991181,0.000075514945,0.00017353051,0.00040325333,0.00013975575,0.00008982744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029702974,0.00021416468,0.00026968215,0.00022791018,0.0002486092,0.00016756415,0.00019422326,0.000088738656,0.000012506629],"category_scores_gemma":[0.000003773311,0.00019056755,0.0000705375,0.0007238995,0.00004036418,0.0003807684,0.0000019173197,0.00023625928,0.000016236945],"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":[0.0011126961,0.0025040037,0.0027811658,0.0010552609,0.0018600622,0.00011897475,0.005532433,0.05277299,0.70975167,0.046914533,0.00215407,0.17344217],"study_design_scores_gemma":[0.004571018,0.006077587,0.0010238263,0.0017513172,0.00034216527,0.0036406626,0.000862464,0.2350707,0.71300316,0.0014753556,0.02975966,0.0024220815],"about_ca_topic_score_codex":0.0002614024,"about_ca_topic_score_gemma":0.00017264372,"teacher_disagreement_score":0.96857035,"about_ca_system_score_codex":0.00022738565,"about_ca_system_score_gemma":0.0001345606,"threshold_uncertainty_score":0.7771119},"labels":[],"label_agreement":null},{"id":"W2130786571","doi":"10.1109/icassp.2004.1326239","title":"Improving the robustness of the RARE algorithm against subarray orientation errors","year":2004,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Robustness (evolution); Estimator; Algorithm; Computer science; Orientation (vector space); Calibration; Cramér–Rao bound; Estimation theory; Mathematics; Statistics","score_opus":0.009953524335768961,"score_gpt":0.23639928121273443,"score_spread":0.22644575687696547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130786571","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":[0.028321568,0.0000092324035,0.9691448,0.0005886022,0.00042047602,0.0002322716,0.0000013366113,0.00016881162,0.0011128555],"genre_scores_gemma":[0.7201271,0.0000020261264,0.27965853,0.000091717426,0.000018147195,0.000016307995,8.753366e-7,0.0000053185454,0.00007995489],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991389,0.000049665912,0.00024705412,0.00016275015,0.00029861648,0.000103026265],"domain_scores_gemma":[0.99901366,0.000050833238,0.0002164392,0.00050518324,0.00019314857,0.000020750136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028792993,0.000078643476,0.00008950052,0.00005611386,0.00012121461,0.000039893323,0.00077213475,0.000035784466,0.00000549102],"category_scores_gemma":[0.000091210466,0.00004430769,0.000065188535,0.00060956494,0.00008897616,0.0004361841,0.00014469314,0.0000757879,0.0000014443268],"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":[0.0000041450994,0.00015350296,0.000432828,0.000071029135,0.000026940637,0.000001045144,0.0036864232,0.06584149,0.01595546,0.08295488,0.00034144096,0.8305308],"study_design_scores_gemma":[0.00024215136,0.000043337168,0.0024784377,0.000051659506,0.000007453575,0.0000060364705,0.00027397915,0.27962938,0.71396536,0.003103222,0.00007294591,0.00012601887],"about_ca_topic_score_codex":0.00020616397,"about_ca_topic_score_gemma":0.000022306338,"teacher_disagreement_score":0.8304048,"about_ca_system_score_codex":0.000050658484,"about_ca_system_score_gemma":0.00011154577,"threshold_uncertainty_score":0.18068151},"labels":[],"label_agreement":null},{"id":"W2131513837","doi":"10.1109/ccece.1997.614829","title":"A new complexity reduced direction-of-arrival estimation method for highly correlated wave fronts","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Smoothing; Algorithm; Preprocessor; Computational complexity theory; Eigendecomposition of a matrix; Eigenvalues and eigenvectors; Dimension (graph theory); Direction of arrival; Covariance matrix; Computer science; Matrix (chemical analysis); Multiple signal classification; Mathematical optimization; Mathematics; Antenna (radio); Artificial intelligence; Physics","score_opus":0.06338241862634918,"score_gpt":0.31239217705791605,"score_spread":0.24900975843156686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131513837","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":[0.00094897987,0.00003113289,0.98825276,0.0007718967,0.00068779296,0.0006055836,0.000007938251,0.00084918726,0.007844742],"genre_scores_gemma":[0.15742917,0.0000049199816,0.8409077,0.000042441898,0.000026793403,0.000036199628,0.000008301116,0.0000143632915,0.0015301076],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982351,0.00011498357,0.00066309265,0.00041229936,0.00035218592,0.00022232922],"domain_scores_gemma":[0.99813384,0.00038848078,0.00043773477,0.00055222755,0.00036356144,0.00012415803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004113646,0.00019334337,0.0003826158,0.00028994711,0.00011047065,0.00005871959,0.000463614,0.00012748296,0.00020011097],"category_scores_gemma":[0.00040740008,0.0001896814,0.00015741604,0.00071855343,0.000054509055,0.00071609986,0.000098813645,0.000105142004,0.000018696153],"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":[0.000039772585,0.0002902647,0.00004486528,0.00008073598,0.000096875905,9.499304e-7,0.0010667188,0.0012595304,0.014496856,0.19200502,0.031684287,0.75893414],"study_design_scores_gemma":[0.000415466,0.00016188102,0.00069220486,0.00004389319,0.000019898778,0.000011620566,0.0000050649114,0.78874743,0.16726187,0.042063106,0.0004137383,0.00016379652],"about_ca_topic_score_codex":0.00064537034,"about_ca_topic_score_gemma":0.0000165408,"teacher_disagreement_score":0.7874879,"about_ca_system_score_codex":0.00009075414,"about_ca_system_score_gemma":0.00006645421,"threshold_uncertainty_score":0.7734983},"labels":[],"label_agreement":null},{"id":"W2131776754","doi":"10.1109/vetecf.2008.83","title":"Impact of the Angular Velocity on the Signals Spectrum and Performance of Antenna-Array Receivers","year":2008,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Wideband; Antenna (radio); Doppler effect; Context (archaeology); Antenna array; Acoustics; Transmission (telecommunications); Computer science; Angular velocity; Physics; Telecommunications; Electronic engineering; Optics; Engineering; Geology","score_opus":0.01982592268077929,"score_gpt":0.2472721436161403,"score_spread":0.22744622093536102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131776754","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":[0.9706156,0.000014389124,0.025153337,0.00038034597,0.00003860702,0.00012036062,0.0000024908625,0.0000436991,0.003631169],"genre_scores_gemma":[0.9941182,0.00006178117,0.005662743,0.000042783926,0.0000040530263,0.00000163262,9.825694e-8,0.0000026998366,0.0001059944],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99932855,0.00007452511,0.00017432033,0.00011680431,0.0002206892,0.00008510848],"domain_scores_gemma":[0.99918634,0.0001296638,0.00016428909,0.00039806103,0.00010163968,0.00002001534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027791373,0.00006995306,0.0001245935,0.000049296043,0.00008968654,0.000007286538,0.00039963875,0.000026082373,0.0000381287],"category_scores_gemma":[0.00009304613,0.00003608022,0.0000762539,0.00038174624,0.00018320685,0.00017775799,0.00006524963,0.00007453242,0.0000014463508],"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":[0.0002184839,0.00078153843,0.32999623,0.00019463994,0.00035671523,0.000005569941,0.010019482,0.001397305,0.56753576,0.046622206,0.008430401,0.03444164],"study_design_scores_gemma":[0.0000584073,0.00023811498,0.27875784,0.000032441967,0.0000025837746,0.000011034273,0.000009387325,0.011636381,0.7080868,0.0011109492,0.000010354384,0.000045735058],"about_ca_topic_score_codex":0.0001165604,"about_ca_topic_score_gemma":0.0000026785513,"teacher_disagreement_score":0.14055099,"about_ca_system_score_codex":0.000022294344,"about_ca_system_score_gemma":0.000078237776,"threshold_uncertainty_score":0.14713086},"labels":[],"label_agreement":null},{"id":"W2131853781","doi":"10.1109/vetecf.2002.1040393","title":"Combined CDMA and matrix pencil direction of arrival estimation","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Direction of arrival; Algorithm; Code division multiple access; Matrix pencil; Computer science; Snapshot (computer storage); Pencil (optics); Angle of arrival; Mean squared error; Computational complexity theory; Speech recognition; Mathematics; Telecommunications; Statistics; Physics; Optics","score_opus":0.011100650908360443,"score_gpt":0.26477666475744627,"score_spread":0.25367601384908584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131853781","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":[0.06473893,0.000024526165,0.9169199,0.00009439723,0.00017796007,0.00016930932,6.7791046e-7,0.0003089674,0.017565325],"genre_scores_gemma":[0.69558173,0.000007681407,0.3041464,0.000009541894,0.0000022954323,0.000006924941,6.404637e-7,0.0000034747936,0.00024128683],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99917036,0.00006383485,0.00028249025,0.00017491524,0.0002213168,0.00008705015],"domain_scores_gemma":[0.99930227,0.0000884408,0.00016380734,0.00025123713,0.0001542167,0.000040057155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035804533,0.00008219707,0.00014829138,0.00014885757,0.00004401909,0.00003187338,0.00015365331,0.000045225413,0.00003099775],"category_scores_gemma":[0.00024054342,0.00007846505,0.00003226976,0.0003644149,0.000049271937,0.0005074427,0.000040002364,0.00004264294,0.000004816178],"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":[0.000010829358,0.00014921093,0.0024489784,0.00009617416,0.000018612842,7.148869e-7,0.00038138076,0.00047545112,0.015462889,0.91101897,0.00074089714,0.06919589],"study_design_scores_gemma":[0.0004362228,0.00029748539,0.010889864,0.000048778158,0.000012418222,0.00002057779,0.000019491166,0.2860974,0.6396725,0.061959624,0.00034695351,0.00019866225],"about_ca_topic_score_codex":0.00007247963,"about_ca_topic_score_gemma":0.000002748904,"teacher_disagreement_score":0.84905934,"about_ca_system_score_codex":0.000025425848,"about_ca_system_score_gemma":0.000044654724,"threshold_uncertainty_score":0.31997117},"labels":[],"label_agreement":null},{"id":"W2132731975","doi":"10.1109/twc.2004.828022","title":"Maximal-Ratio Combining Architectures and Performance With Channel Estimation Based on a Training Sequence","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Training (meteorology); Sequence (biology); Channel (broadcasting); Maximal-ratio combining; Signal-to-noise ratio (imaging); Estimation; Algorithm; Speech recognition; Artificial intelligence; Pattern recognition (psychology); Telecommunications; Fading; Engineering","score_opus":0.04189403111970468,"score_gpt":0.2767665662630302,"score_spread":0.2348725351433255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132731975","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":[0.05713636,0.000009816233,0.93978167,0.0016239855,0.000055128367,0.00033760833,0.000011572831,0.00046554103,0.0005782964],"genre_scores_gemma":[0.78398836,0.00003292852,0.21559049,0.00015883773,0.0000027380358,0.0001972751,0.0000048728266,0.000016550774,0.0000079335005],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875236,0.00010276151,0.0003271807,0.0003061675,0.0003158896,0.00019562045],"domain_scores_gemma":[0.99792284,0.00031498176,0.00019235094,0.0013458334,0.00013930965,0.000084714404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024117866,0.00020591744,0.00021413868,0.0004178392,0.00055421604,0.00010069198,0.00085053133,0.00007151455,0.000002762719],"category_scores_gemma":[0.000011363357,0.0001986663,0.000048630765,0.00069465395,0.00030382126,0.00041554065,0.000008908857,0.00037750654,0.0000047556255],"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":[0.00004520328,0.0003337214,0.000012854925,0.000045554174,0.00002388309,9.1913097e-7,0.0030618377,0.80045056,0.0011426149,0.01198556,0.0000013480648,0.18289591],"study_design_scores_gemma":[0.00053224753,0.0005930463,0.0004024385,0.00046075383,0.000016922513,0.000025215057,0.000057718356,0.9463517,0.049740896,0.0015902838,0.000006675002,0.00022208376],"about_ca_topic_score_codex":0.00007971203,"about_ca_topic_score_gemma":0.00006448605,"teacher_disagreement_score":0.726852,"about_ca_system_score_codex":0.00010183901,"about_ca_system_score_gemma":0.00020070116,"threshold_uncertainty_score":0.8101376},"labels":[],"label_agreement":null},{"id":"W2134223162","doi":"10.1049/ip-rsn:20020553","title":"Minimal sample support space–time adaptive processing with fast subspace techniques","year":2002,"lang":"en","type":"article","venue":"IEE Proceedings - Radar Sonar and Navigation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Subspace topology; Clutter; Projection (relational algebra); Dimension (graph theory); Estimator; Computer science; Space-time adaptive processing; Algorithm; Rank (graph theory); Eigenvalues and eigenvectors; Linear subspace; Mathematical optimization; Mathematics; Radar; Artificial intelligence; Statistics","score_opus":0.012662886740699575,"score_gpt":0.2255104268102163,"score_spread":0.21284754006951673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134223162","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":[0.2623882,0.00032231267,0.7209449,0.0020329931,0.00007210264,0.0013852555,0.000029858285,0.0027546,0.010069811],"genre_scores_gemma":[0.59069574,0.000017238013,0.40902296,0.000028937653,0.000036014506,0.000038754555,0.0000050682456,0.000017256236,0.00013803506],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99859107,0.000011275069,0.00027768294,0.0004465648,0.000431891,0.00024151702],"domain_scores_gemma":[0.9989962,0.00004032509,0.00032625836,0.00011211171,0.0004277154,0.00009738475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027058605,0.0002161742,0.00024140018,0.00018048935,0.0001957237,0.0001895776,0.0002692422,0.00010347928,0.000017699678],"category_scores_gemma":[0.000028311204,0.0001986671,0.00003772521,0.0006608496,0.00014570358,0.0018229306,0.00007272567,0.0001533622,0.0000062666936],"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":[0.00013932485,0.00037253962,0.00523993,0.0005263744,0.000059960454,0.000013047964,0.0237806,0.0000027673027,0.061240885,0.019649912,0.0050639184,0.8839107],"study_design_scores_gemma":[0.0007657371,0.0025285864,0.0020598967,0.0011194925,0.00007147772,0.00040015133,0.0007203378,0.10872386,0.8688857,0.007864963,0.005783525,0.0010762878],"about_ca_topic_score_codex":0.000039877195,"about_ca_topic_score_gemma":0.0000017265033,"teacher_disagreement_score":0.88283443,"about_ca_system_score_codex":0.00006209228,"about_ca_system_score_gemma":0.000037383645,"threshold_uncertainty_score":0.8101409},"labels":[],"label_agreement":null},{"id":"W2134583306","doi":"10.1109/icassp.2002.5745255","title":"Robust adaptive beamforming using worst-case performance optimization via Second-Order Cone programming","year":2002,"lang":"en","type":"article","venue":"IEEE International Conference on Acoustics Speech and Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Adaptive beamformer; Robustness (evolution); Beamforming; Computer science; Second-order cone programming; SIGNAL (programming language); Control theory (sociology); Algorithm; Signal processing; Mathematics; Convex optimization; Artificial intelligence; Telecommunications; Radar","score_opus":0.08281570535449398,"score_gpt":0.28719483191906825,"score_spread":0.20437912656457427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134583306","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":[0.025161555,0.00003290832,0.9712899,0.000064403175,0.00021027343,0.00020454147,0.0000056687986,0.00017269613,0.0028580949],"genre_scores_gemma":[0.5681973,0.000017622062,0.43159676,0.000047923524,0.00004806267,0.00000809347,0.0000022731153,0.00001010728,0.00007186327],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984061,0.000031213753,0.00044472935,0.00039239202,0.0004808492,0.00024470792],"domain_scores_gemma":[0.9983046,0.00006795987,0.00038812135,0.00014650292,0.0009945745,0.00009824863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025551036,0.00022094705,0.00020837021,0.0003190404,0.00027028285,0.00038640495,0.00036523523,0.000102575024,0.00016306645],"category_scores_gemma":[0.00004661924,0.00022581102,0.0000344055,0.00037535912,0.00012392056,0.0013519807,0.00008077617,0.00024717432,0.000003429548],"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":[0.000037565405,0.00019231201,0.00007298923,0.00012763256,0.000041819487,0.000102096485,0.00071712834,0.34969535,0.012226698,0.0016922264,0.000024634572,0.63506955],"study_design_scores_gemma":[0.00023188598,0.00017091604,0.0000059508975,0.00032528286,0.000014359213,0.0005834774,0.00009234363,0.9866634,0.01120148,0.00045459325,0.0000135632,0.0002427251],"about_ca_topic_score_codex":0.0000171974,"about_ca_topic_score_gemma":0.0000024870994,"teacher_disagreement_score":0.6369681,"about_ca_system_score_codex":0.00009948953,"about_ca_system_score_gemma":0.000087904766,"threshold_uncertainty_score":0.9208306},"labels":[],"label_agreement":null},{"id":"W2135090566","doi":"10.1109/lsp.2006.871715","title":"Improved structured least squares for the application of unitary ESPRIT to cross arrays","year":2006,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Unitary state; Algorithm; Least-squares function approximation; Minification; Rotational invariance; Total least squares; Set (abstract data type); Unitary transformation; Non-linear least squares; Mathematics; Computer science; Mathematical optimization; Estimation theory; Statistics; Physics","score_opus":0.010858717955748885,"score_gpt":0.27006486049824974,"score_spread":0.25920614254250085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135090566","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":[0.035349905,0.000032109205,0.96211183,0.0017467173,0.00009051755,0.00046526396,0.000008090535,0.00016673049,0.000028806797],"genre_scores_gemma":[0.86232,1.50839e-7,0.1370013,0.00047610377,0.000082550374,0.000098098506,0.0000030308993,0.000011374268,0.000007369783],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989982,0.000022022434,0.00032694582,0.00025747152,0.00022868367,0.00016667183],"domain_scores_gemma":[0.999048,0.0001281246,0.00026028973,0.00027886615,0.0002560745,0.000028670065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021535842,0.00011991637,0.00013999741,0.00011539234,0.00016663766,0.00012213488,0.0006692313,0.000042726693,0.0000010452324],"category_scores_gemma":[0.000020841875,0.00009719502,0.00006061084,0.00043221182,0.000113041824,0.00036396546,0.00003432757,0.00007476332,6.97576e-7],"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":[0.000023417162,0.000023099188,0.00013843057,0.000115312694,0.0000072501753,1.4023665e-7,0.0002102751,0.029961728,0.8629345,0.00074083376,0.00066931034,0.10517567],"study_design_scores_gemma":[0.00015170123,0.00005386436,0.0012421599,0.000040086412,0.000009253571,0.0000021970852,0.000009492973,0.3531042,0.6424837,0.0024710689,0.00030481128,0.00012745307],"about_ca_topic_score_codex":0.0001935555,"about_ca_topic_score_gemma":0.00001245344,"teacher_disagreement_score":0.8269701,"about_ca_system_score_codex":0.000034500263,"about_ca_system_score_gemma":0.00005646244,"threshold_uncertainty_score":0.3963498},"labels":[],"label_agreement":null},{"id":"W2135418529","doi":"10.1023/a:1026095707656","title":"The Feasibility of Neutron Moderation Imaging for Land Mine Detection","year":2003,"lang":"en","type":"article","venue":"Subsurface Sensing Technologies and Applications","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Department of National Defence; Atomic Energy (Canada); Defence Research and Development Canada","funders":"","keywords":"Detector; Neutron detection; Neutron; Neutron source; Neutron imaging; Bonner sphere; Monte Carlo method; Remote sensing; Neutron temperature; Optics; Physics; Environmental science; Neutron cross section; Nuclear physics; Geology; Mathematics","score_opus":0.021384296932153178,"score_gpt":0.2802933225788894,"score_spread":0.25890902564673623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135418529","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":[0.07496828,0.00030353497,0.9228629,0.00068084686,0.000029704657,0.0005539427,0.0000026235095,0.00048893224,0.00010926074],"genre_scores_gemma":[0.838588,0.00005911657,0.16130544,0.000003398217,0.0000021064275,0.000029845489,7.9921847e-7,0.0000039454826,0.000007323272],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99939144,0.000022267148,0.00020849984,0.0001993479,0.00007525264,0.000103168946],"domain_scores_gemma":[0.9989964,0.00019519281,0.00016346034,0.00044294776,0.00019212639,0.000009911272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031035065,0.00007197166,0.00009819714,0.00005701131,0.00027959107,0.0000495637,0.00015840172,0.000047588972,6.4782945e-8],"category_scores_gemma":[0.0001852956,0.000058333946,0.00003013301,0.00030162267,0.00015409976,0.00013775079,0.00004697069,0.000056204724,1.5338033e-7],"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":[0.0000073672913,0.000040293682,0.0014227452,0.0000449655,0.000010360708,4.819294e-8,0.000059943126,0.00056234916,0.13128261,0.20844355,0.000039612263,0.6580861],"study_design_scores_gemma":[0.00012521652,0.000039732353,0.0006116204,0.000012307625,0.000008657461,0.000007508243,0.00018360859,0.1391366,0.7239506,0.13477612,0.0010576899,0.00009033213],"about_ca_topic_score_codex":0.000026291606,"about_ca_topic_score_gemma":0.00004771304,"teacher_disagreement_score":0.7636197,"about_ca_system_score_codex":0.000023254272,"about_ca_system_score_gemma":0.000019343672,"threshold_uncertainty_score":0.23787893},"labels":[],"label_agreement":null},{"id":"W2137738638","doi":"10.1109/acssc.1992.269204","title":"The steered pattern averaging technique (SPAT) for direction finding in a multiple coherent signal environment","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Smoothing; Preprocessor; SIGNAL (programming language); Algorithm; Computer science; Deconvolution; Direction finding; Artificial intelligence; Computer vision; Telecommunications","score_opus":0.02317922644849458,"score_gpt":0.24969047239072004,"score_spread":0.22651124594222546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137738638","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":[0.00224126,0.00002220968,0.99510705,0.00009892699,0.00008924142,0.0009142164,0.0000015142954,0.00019587729,0.0013296921],"genre_scores_gemma":[0.8907912,0.00001259167,0.108171195,0.000023834466,0.00000678624,0.00070368976,0.0000012807311,0.0000092888595,0.00028014352],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998947,0.000103839004,0.00031031968,0.00025128553,0.00019163519,0.00019592472],"domain_scores_gemma":[0.9991598,0.00037251864,0.00012736687,0.00027903973,0.000029957022,0.00003130943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007346018,0.000110407505,0.00011841901,0.000118281634,0.00015181513,0.00007315743,0.0002846681,0.00004750103,0.000033423246],"category_scores_gemma":[0.0000851672,0.00008770257,0.000057166904,0.00017118831,0.000028632052,0.00022422786,0.000060806287,0.000085238724,0.0000060347006],"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":[0.00002069653,0.0003582276,0.013974571,0.000072995805,0.000036219106,0.0000026104592,0.0007998409,0.0028220678,0.060872357,0.022722088,0.00093263865,0.8973857],"study_design_scores_gemma":[0.00044416427,0.00013631835,0.0015788636,0.00007440048,0.000003818001,0.000007836252,0.00004152512,0.22118394,0.75646955,0.0060666148,0.013761461,0.00023151744],"about_ca_topic_score_codex":0.0000917713,"about_ca_topic_score_gemma":0.000034586144,"teacher_disagreement_score":0.89715415,"about_ca_system_score_codex":0.00016269361,"about_ca_system_score_gemma":0.000026917345,"threshold_uncertainty_score":0.3576407},"labels":[],"label_agreement":null},{"id":"W2138364821","doi":"10.1109/icassp.1996.547981","title":"A new family of EVD tracking algorithms using Givens rotations","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Orthonormality; Algorithm; Eigenvalues and eigenvectors; Computer science; Covariance matrix; Convergence (economics); Tracking (education); QR decomposition; Eigendecomposition of a matrix; Orthonormal basis","score_opus":0.08301519700287781,"score_gpt":0.3019909743894675,"score_spread":0.2189757773865897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138364821","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":[0.004187361,0.000044506625,0.9853713,0.00011511508,0.000105867235,0.00010184271,0.0000010147952,0.00024062343,0.009832403],"genre_scores_gemma":[0.27985483,0.0000050442013,0.719806,0.000031722288,0.000012504891,0.0000018754321,1.9729073e-7,0.000004165764,0.00028364334],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999262,0.000023420464,0.00026147827,0.00014665385,0.00020797637,0.00009850629],"domain_scores_gemma":[0.9993538,0.000064563894,0.00013289975,0.00025077854,0.00015292842,0.000045021836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009799621,0.00006674307,0.000118978765,0.00016350542,0.000043249158,0.000036102458,0.0002951774,0.00003171245,0.000078198806],"category_scores_gemma":[0.000051066658,0.00006683797,0.000053710373,0.00053746806,0.000023266344,0.0005399473,0.000051524625,0.000044513272,0.00000839696],"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":[9.5200306e-7,0.00013220671,0.00029075518,0.000028509792,0.000027046359,0.0000024025796,0.0023940392,0.0022527939,0.049966235,0.062463254,0.0028530997,0.8795887],"study_design_scores_gemma":[0.00011944861,0.000051518156,0.0018838339,0.000051600826,0.0000068860427,0.000007985149,0.00003220643,0.89038455,0.10152394,0.0055170637,0.00031183273,0.00010912615],"about_ca_topic_score_codex":0.00037777526,"about_ca_topic_score_gemma":0.000004451006,"teacher_disagreement_score":0.88813174,"about_ca_system_score_codex":0.000024691257,"about_ca_system_score_gemma":0.000035395697,"threshold_uncertainty_score":0.27255735},"labels":[],"label_agreement":null},{"id":"W2140494646","doi":"10.1109/acssc.1996.599176","title":"SVD-updating via constrained perturbations with application to subspace tracking","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Singular value decomposition; Subspace topology; Singular value; Ode; Orthonormality; Algorithm; Mathematics; Signal subspace; Ordinary differential equation; Singular perturbation; Matrix decomposition; Computer science; Applied mathematics; Noise (video); Differential equation; Orthonormal basis; Artificial intelligence; Mathematical analysis; Eigenvalues and eigenvectors","score_opus":0.015247644218825842,"score_gpt":0.24798988896191457,"score_spread":0.23274224474308872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140494646","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":[0.002127116,0.0000049327855,0.97025126,0.001927968,0.00002507621,0.00028611755,7.407713e-7,0.0006322427,0.024744544],"genre_scores_gemma":[0.590008,6.632071e-7,0.40960735,0.00014027642,0.000008279579,0.000039302926,0.0000011029176,0.0000045807374,0.00019040583],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920964,0.00002199771,0.00019750326,0.00024103482,0.00020475016,0.00012508723],"domain_scores_gemma":[0.99916154,0.00012046899,0.000106193096,0.00034935377,0.00019653792,0.00006593057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001322493,0.00008819875,0.00010104545,0.0001382159,0.00009658794,0.00007697694,0.00031047408,0.0000299894,0.000068096124],"category_scores_gemma":[0.00009028202,0.00007779759,0.000022533131,0.00068844954,0.000033888802,0.0004976433,0.000041525793,0.000054203934,0.00004145138],"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":[0.000003011331,0.00014484576,0.0008099435,0.000020682923,0.000018322598,0.0000011790187,0.00246663,0.0013108241,0.02887392,0.3142919,0.0016764782,0.6503823],"study_design_scores_gemma":[0.00021773587,0.00018422246,0.0020916634,0.000066298155,0.000008718809,0.000037928603,0.00010755144,0.8778433,0.11509542,0.002226114,0.0017985138,0.00032253342],"about_ca_topic_score_codex":0.000049758284,"about_ca_topic_score_gemma":0.000023717748,"teacher_disagreement_score":0.8765325,"about_ca_system_score_codex":0.00003380314,"about_ca_system_score_gemma":0.000014402304,"threshold_uncertainty_score":0.31724936},"labels":[],"label_agreement":null},{"id":"W2140648934","doi":"10.1121/1.4930568","title":"Eigenvector pruning method for high resolution beamforming","year":2015,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Naval Sea Systems Command; Office of Naval Research","keywords":"Beamforming; Estimator; Eigenvalues and eigenvectors; Algorithm; Computer science; Subspace topology; Signal subspace; Array processing; Noise (video); Signal processing; Mathematics; Artificial intelligence; Statistics; Telecommunications; Radar","score_opus":0.02970779828873279,"score_gpt":0.3109321804441727,"score_spread":0.28122438215543993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140648934","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":[0.00075050304,0.000072420764,0.9953994,0.0032760925,0.0002560736,0.00014312242,0.0000022959628,0.000027804423,0.00007226311],"genre_scores_gemma":[0.11494733,0.000025332807,0.88459074,0.00031936684,0.000080895596,0.000001973446,1.16885126e-7,0.0000066525968,0.000027590688],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986756,0.00016855788,0.00044635026,0.000074521566,0.00048221636,0.00015275442],"domain_scores_gemma":[0.9974991,0.0008140813,0.0008019314,0.00030365543,0.0005126194,0.00006863226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002027962,0.00008449361,0.00024471973,0.000026166877,0.00012567017,0.000017455275,0.0010053823,0.00004705257,0.0000024030767],"category_scores_gemma":[0.0008663997,0.000047440568,0.00024720622,0.00036437,0.00021052235,0.00024838184,0.00021738527,0.00019838256,4.5084093e-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":[0.00040101176,0.00051367504,0.00009873108,0.00025728758,0.00066035084,6.322957e-7,0.013612942,0.19931486,0.15330553,0.006399654,0.12942988,0.49600545],"study_design_scores_gemma":[0.00023892055,0.00042693308,0.00012625105,0.00008047832,0.00009849975,0.000032159085,0.00043801765,0.93638563,0.03793561,0.022854822,0.0013068003,0.00007589429],"about_ca_topic_score_codex":0.00008386785,"about_ca_topic_score_gemma":1.5954392e-7,"teacher_disagreement_score":0.73707074,"about_ca_system_score_codex":0.000096737436,"about_ca_system_score_gemma":0.0001610979,"threshold_uncertainty_score":0.19345702},"labels":[],"label_agreement":null},{"id":"W2141310001","doi":"10.1109/tsp.2011.2161293","title":"A Non-Data-Aided Maximum Likelihood Time Delay Estimator Using Importance Sampling","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Estimator; Mathematics; Additive white Gaussian noise; Algorithm; Estimation theory; Mathematical optimization; Gaussian noise; White noise; Convergence (economics); Sampling (signal processing); Likelihood function; Statistics; Computer science","score_opus":0.07906014994916653,"score_gpt":0.3064905066795563,"score_spread":0.22743035673038975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141310001","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":[0.008521342,0.00004849788,0.98962164,0.000026840933,0.00015684192,0.00025818506,0.000015905298,0.0006286548,0.0007220962],"genre_scores_gemma":[0.5524081,0.0000021239027,0.4474717,0.000048606533,0.000016583896,0.000015475378,0.0000016836793,0.000024261934,0.000011432713],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99780166,0.0000424868,0.0006502843,0.00067186146,0.0004525976,0.0003810993],"domain_scores_gemma":[0.99832684,0.00007816858,0.00038925454,0.000777833,0.00027919014,0.00014870417],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00051319425,0.0002793563,0.00033745088,0.00036297177,0.00040639506,0.00015990146,0.0011351726,0.00012747994,0.000107471904],"category_scores_gemma":[0.000010096561,0.00028783127,0.000102370446,0.00089439075,0.00010000343,0.002316297,0.000015338026,0.00029622397,0.000043324617],"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":[0.00012674031,0.0009964973,0.00014501934,0.00039148214,0.00014790276,0.00004208128,0.0024459988,0.009389522,0.09736964,0.0001405739,0.00009868878,0.88870585],"study_design_scores_gemma":[0.000219772,0.000104748506,0.000044609813,0.00030878247,0.000054600292,0.00007295134,0.000020428182,0.7659769,0.22800095,0.00485429,0.000017044391,0.0003249079],"about_ca_topic_score_codex":0.000068042566,"about_ca_topic_score_gemma":0.0000054341913,"teacher_disagreement_score":0.88838094,"about_ca_system_score_codex":0.000098873454,"about_ca_system_score_gemma":0.00035887756,"threshold_uncertainty_score":0.9999574},"labels":[],"label_agreement":null},{"id":"W2143006940","doi":"10.1109/icassp.1996.550162","title":"Direction finding for point and dispersed sources: VEC-MUSIC and its performance","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Point (geometry); Radar; Linear subspace; Computer science; Multiple signal classification; Property (philosophy); Noise (video); Prime (order theory); Speech recognition; Telecommunications; Mathematics; Artificial intelligence; Antenna (radio); Combinatorics; Pure mathematics","score_opus":0.03686821394495207,"score_gpt":0.242427638531962,"score_spread":0.20555942458700993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143006940","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":[0.6166518,0.00019030026,0.3761862,0.00034288212,0.00016065755,0.0003249944,0.0000011477874,0.0004213481,0.0057206615],"genre_scores_gemma":[0.9615853,0.00007687543,0.03765796,0.00005524394,0.000015777066,0.000025166944,2.95127e-7,0.000004821471,0.0005785809],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948615,0.000011170802,0.00013075494,0.00018472446,0.00008670872,0.000100515565],"domain_scores_gemma":[0.9996703,0.000072348776,0.00006194963,0.00010900412,0.000048889546,0.000037458576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014617544,0.00007041629,0.00009205102,0.000102097365,0.00011246152,0.00006457963,0.000098266704,0.000030658535,0.000022664119],"category_scores_gemma":[0.00004903702,0.00006297167,0.000018483926,0.00015676828,0.000022637429,0.00061665406,0.00005472043,0.000032530195,0.0000027465362],"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":[0.000019097673,0.00016412635,0.0051077195,0.0005720012,0.000042297605,8.7335786e-7,0.0076638614,0.0001196902,0.02373664,0.07634953,0.0031367037,0.88308746],"study_design_scores_gemma":[0.00021475881,0.00014845027,0.0044706054,0.000054668926,0.0000052109513,0.000013127036,0.000028034974,0.9211829,0.072237626,0.00059569464,0.00092157215,0.00012736696],"about_ca_topic_score_codex":0.000008196175,"about_ca_topic_score_gemma":0.0000027483275,"teacher_disagreement_score":0.9210632,"about_ca_system_score_codex":0.000015257949,"about_ca_system_score_gemma":0.0000034822976,"threshold_uncertainty_score":0.25679103},"labels":[],"label_agreement":null},{"id":"W2143309866","doi":"10.1109/97.988716","title":"Robust array interpolation using second-order cone programming","year":2002,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Interpolation (computer graphics); Robustness (evolution); Mathematical optimization; Second-order cone programming; Computer science; Multivariate interpolation; Convex optimization; Algorithm; Stairstep interpolation; Mathematics; Bilinear interpolation; Nearest-neighbor interpolation; Regular polygon; Artificial intelligence; Computer vision; Geometry","score_opus":0.04750596592998896,"score_gpt":0.2604011387072404,"score_spread":0.21289517277725145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143309866","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":[0.028038934,0.00006679893,0.96994233,0.0005459571,0.00020073495,0.00017659696,6.9930974e-7,0.00047435777,0.0005535998],"genre_scores_gemma":[0.61191785,3.5495594e-7,0.3874908,0.00047796476,0.00005838954,0.0000099707595,7.2148123e-7,0.000013837164,0.000030112691],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985992,0.000058547826,0.00038968748,0.0003587617,0.00032778247,0.00026606806],"domain_scores_gemma":[0.9991421,0.000050209146,0.00033559368,0.00021741686,0.00019264828,0.00006202635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025335007,0.00017320334,0.00019082565,0.00025464487,0.00017223261,0.00028921486,0.00042663177,0.000064591935,0.0000772042],"category_scores_gemma":[0.000024878174,0.00018076762,0.00005716094,0.0007191909,0.00011032312,0.0014201015,0.000033279084,0.00017735986,0.00001090707],"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":[0.0000048910415,0.00009062317,0.00021935943,0.00017495829,0.000021346126,0.0000065462646,0.0016763734,0.005736986,0.727703,0.00009751074,0.0011225464,0.26314592],"study_design_scores_gemma":[0.00017283595,0.00004609965,0.00004239621,0.00026088292,0.000011363188,0.000033242017,0.000018909901,0.8358731,0.16251475,0.00018974688,0.0005630379,0.00027363867],"about_ca_topic_score_codex":0.000017667284,"about_ca_topic_score_gemma":0.000001667354,"teacher_disagreement_score":0.8301361,"about_ca_system_score_codex":0.000071998904,"about_ca_system_score_gemma":0.000034706492,"threshold_uncertainty_score":0.73714894},"labels":[],"label_agreement":null},{"id":"W2143635038","doi":"10.1109/vtcf.2006.57","title":"Spatial-Smoothing-Based Direction-of-Arrival, Propagation Delay and Channel Estimation for Antenna-Array DS/CDMA Systems","year":2006,"lang":"en","type":"article","venue":"IEEE Vehicular Technology Conference","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Multipath propagation; Direction of arrival; Computer science; Estimator; Delay spread; Smoothing; Angle of arrival; Antenna array; Algorithm; Channel (broadcasting); Fading; Code division multiple access; Antenna (radio); Electronic engineering; Narrowband; Smart antenna; Signal subspace; Telecommunications; Noise (video); Directional antenna; Engineering; Mathematics; Statistics; Artificial intelligence","score_opus":0.0126007460322561,"score_gpt":0.2399693766888388,"score_spread":0.2273686306565827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143635038","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":[0.043711722,0.00020778613,0.95282316,0.0008013047,0.00048100206,0.0008837132,0.000016101381,0.00096777955,0.0001074011],"genre_scores_gemma":[0.9010352,0.0000139948115,0.09853831,0.000016943832,0.000023157894,0.0003029717,0.000016996308,0.000019506544,0.00003294165],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998048,0.00008915653,0.00069481856,0.00057522475,0.0003187032,0.0002740792],"domain_scores_gemma":[0.99733084,0.00015519845,0.00067461707,0.0006493941,0.0011457108,0.00004422278],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004614595,0.00025440412,0.00043805107,0.00071830145,0.00017059653,0.000095491705,0.0005211296,0.0003783101,0.0000015799599],"category_scores_gemma":[0.0003018937,0.00025909202,0.00008115288,0.0008499938,0.00030762766,0.00044177324,0.000053354215,0.00017548654,0.000002997852],"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":[0.000058156016,0.0005157595,0.0026780667,0.0011775865,0.000112587426,0.000017038603,0.00022015716,0.019848479,0.7087796,0.2057219,0.0003075801,0.060563117],"study_design_scores_gemma":[0.00027718788,0.00015326444,0.00033907444,0.00018601325,0.000021423526,0.000026494126,0.000008459151,0.5529624,0.4308542,0.014891726,0.00011160634,0.00016814058],"about_ca_topic_score_codex":0.00045581485,"about_ca_topic_score_gemma":0.00006321301,"teacher_disagreement_score":0.85732347,"about_ca_system_score_codex":0.00006709644,"about_ca_system_score_gemma":0.00023665592,"threshold_uncertainty_score":0.9999861},"labels":[],"label_agreement":null},{"id":"W2144376566","doi":"10.1109/icassp.1994.389745","title":"A computationally efficient self-calibrating direction-of-arrival estimator","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Direction of arrival; Estimator; Calibration; Computer science; Algorithm; Array processing; Noise (video); Sensor array; Covariance; Direction finding; Sensitivity (control systems); Signal processing; Mathematics; Artificial intelligence; Statistics; Electronic engineering; Telecommunications; Engineering; Machine learning; Image (mathematics)","score_opus":0.013335280390297426,"score_gpt":0.2334550217966583,"score_spread":0.22011974140636087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144376566","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":[0.0166732,0.00003786061,0.95732725,0.00029819304,0.00025574895,0.00021298628,0.0000023133823,0.0011720966,0.024020346],"genre_scores_gemma":[0.5181969,0.0000019038698,0.48164785,0.0000361224,0.000014188591,0.000011678709,8.2431404e-7,0.000007263547,0.00008326943],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984006,0.00007123397,0.00055517926,0.00030660874,0.0004922291,0.00017412238],"domain_scores_gemma":[0.9986722,0.00031107682,0.00029758245,0.0003580973,0.00027900055,0.00008206977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026025885,0.00014506331,0.00023341444,0.00024630883,0.00011070934,0.00006679907,0.0005076357,0.00005797822,0.00013684797],"category_scores_gemma":[0.00015365107,0.00013929207,0.00009960999,0.00080005825,0.000058878104,0.0003743119,0.0001457287,0.00008381383,0.000037039186],"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":[0.000008042814,0.0016428069,0.0030585944,0.00025599543,0.00014643268,0.000008137514,0.0031804433,0.06865306,0.0072194193,0.8001745,0.006284097,0.10936848],"study_design_scores_gemma":[0.00015803303,0.0000749072,0.0019187317,0.000039860883,0.0000062618556,0.000016487795,0.0000101832,0.96264356,0.032951985,0.0017969346,0.0002396101,0.00014345451],"about_ca_topic_score_codex":0.000029033174,"about_ca_topic_score_gemma":9.758232e-7,"teacher_disagreement_score":0.89399046,"about_ca_system_score_codex":0.000043710254,"about_ca_system_score_gemma":0.000047543563,"threshold_uncertainty_score":0.5680165},"labels":[],"label_agreement":null},{"id":"W2144903671","doi":"10.1109/issse.2007.4294512","title":"Adaptive Microwave Beamforming with Low Weighting Rate Requirement","year":2007,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Beamforming; Weighting; Adaptive beamformer; Bandwidth (computing); Computer science; Microwave; SIGNAL (programming language); Signal-to-interference-plus-noise ratio; Interference (communication); Algorithm; Electronic engineering; Control theory (sociology); Acoustics; Telecommunications; Physics; Engineering; Power (physics); Artificial intelligence","score_opus":0.01438802016012575,"score_gpt":0.25134578556024645,"score_spread":0.2369577654001207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144903671","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":[0.011930741,0.0000073035844,0.9459648,0.00008369519,0.00007400018,0.00015421587,1.9230215e-7,0.00034899137,0.041436043],"genre_scores_gemma":[0.48569584,9.690389e-7,0.51400965,0.00008067473,0.000011650973,0.000003579309,3.2003362e-7,0.0000044474377,0.00019287635],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990673,0.000018881767,0.00026733737,0.00022372523,0.00021396812,0.00020878449],"domain_scores_gemma":[0.9992407,0.00009530339,0.00016692113,0.0002719346,0.00016991659,0.000055238506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077780953,0.00010148424,0.0001152228,0.00013756567,0.000073575786,0.000044036835,0.00030929793,0.000030330059,0.000011102957],"category_scores_gemma":[0.00002413837,0.00007982953,0.000029566243,0.00038745953,0.000041689997,0.0006322096,0.00010503624,0.00006449103,0.000010788963],"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":[0.000061180006,0.00016125516,0.0006477932,0.000051194478,0.000063231826,0.000028847018,0.0018267992,0.00019731853,0.1407127,0.3862486,0.00051233516,0.46948874],"study_design_scores_gemma":[0.00013036634,0.00017162442,0.0004571677,0.00008988346,0.0000031926957,0.000011086898,0.0000623451,0.01880659,0.976774,0.003112733,0.00024527623,0.0001357567],"about_ca_topic_score_codex":0.0000580239,"about_ca_topic_score_gemma":0.00003363515,"teacher_disagreement_score":0.8360613,"about_ca_system_score_codex":0.00007158125,"about_ca_system_score_gemma":0.00005308468,"threshold_uncertainty_score":0.32553536},"labels":[],"label_agreement":null},{"id":"W2147679520","doi":"10.1109/sam.2004.1502957","title":"A robust state-space approach for localizing wideband sources in sensor arrays","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Wideband; Computer science; Direction of arrival; Noise (video); Algorithm; Robustness (evolution); Sensor array; Electronic engineering; Artificial intelligence; Engineering; Antenna (radio); Telecommunications; Machine learning","score_opus":0.03322975108881241,"score_gpt":0.2559746846704072,"score_spread":0.22274493358159478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147679520","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":[0.004079815,0.000027648362,0.9886691,0.00050762895,0.000030172963,0.00031144576,0.0000010465111,0.00035374952,0.006019373],"genre_scores_gemma":[0.23543103,0.0000038348026,0.76390636,0.00009443516,0.000016308599,0.000041347397,0.0000011639756,0.000007386853,0.0004981584],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990779,0.00003222191,0.0002582353,0.00027422808,0.00016242077,0.0001949681],"domain_scores_gemma":[0.9993955,0.00012037892,0.00009424249,0.0002614232,0.00008190401,0.0000465575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035861152,0.00010334945,0.0001611239,0.0001838582,0.000044541695,0.0000811522,0.00032691794,0.000041768253,0.000006212191],"category_scores_gemma":[0.000074878284,0.00009358145,0.00004516108,0.00035522555,0.000037110512,0.0005034732,0.0000624945,0.0000614651,0.0000031988297],"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":[0.000042684565,0.0005125166,0.003626097,0.00022877485,0.000033127202,0.0000019297045,0.0056502135,0.7602671,0.0061502387,0.058831826,0.007193818,0.15746172],"study_design_scores_gemma":[0.00022489611,0.00004380803,0.00012576098,0.000019821819,0.0000017177558,0.000003835578,0.00007128616,0.8604642,0.13590282,0.0011865858,0.0018186263,0.00013662617],"about_ca_topic_score_codex":0.00012465102,"about_ca_topic_score_gemma":0.000045833483,"teacher_disagreement_score":0.23135121,"about_ca_system_score_codex":0.000048648733,"about_ca_system_score_gemma":0.00003484722,"threshold_uncertainty_score":0.3816141},"labels":[],"label_agreement":null},{"id":"W2148167464","doi":"10.1109/icassp.1988.197225","title":"A new criterion for the determination of the number of signals in high-resolution array processing","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Term (time); Function (biology); Set (abstract data type); Maximum likelihood; Computer science; Algorithm; Likelihood function; Resolution (logic); Minimum description length; Estimation theory; High resolution; Mathematics; Statistics; Artificial intelligence","score_opus":0.02033413283683864,"score_gpt":0.3037368127193476,"score_spread":0.28340267988250895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148167464","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":[0.008294721,0.00001946259,0.98994726,0.00029484308,0.00007872325,0.00028170407,5.0596435e-7,0.000029730718,0.0010530668],"genre_scores_gemma":[0.6906482,0.0000013797091,0.30920357,0.000020054995,0.0000039008996,0.000016456144,1.2560288e-7,0.0000023143043,0.000103987484],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99934226,0.000060364095,0.0002684709,0.000098437275,0.00016289891,0.00006758139],"domain_scores_gemma":[0.9992821,0.00012616171,0.00022338888,0.00019345888,0.00016509487,0.000009759905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042003184,0.00004970807,0.0000905579,0.000052087165,0.00003634594,0.000019631967,0.00027205367,0.000031591506,0.000012500778],"category_scores_gemma":[0.00020862898,0.00003042091,0.000039360006,0.000389944,0.00003164819,0.0003273496,0.00002164986,0.000030050232,3.0603144e-7],"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":[0.000020774072,0.00016831417,0.002785976,0.0002679728,0.000008121712,8.287472e-8,0.0025284218,0.000706359,0.17580687,0.17238754,0.000604412,0.6447152],"study_design_scores_gemma":[0.00015385644,0.000029480992,0.0041674334,0.00011855311,0.0000052396235,0.0000023526354,0.000022104417,0.06983514,0.88688874,0.03858708,0.00014042581,0.00004962024],"about_ca_topic_score_codex":0.00015972272,"about_ca_topic_score_gemma":0.000021690994,"teacher_disagreement_score":0.71108186,"about_ca_system_score_codex":0.000022674376,"about_ca_system_score_gemma":0.000087411645,"threshold_uncertainty_score":0.124052875},"labels":[],"label_agreement":null},{"id":"W2150835235","doi":"10.1109/tsp.2003.815395","title":"Robust adaptive beamforming for general-rank signal models","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":515,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Adaptive beamformer; Beamforming; Robustness (evolution); Signal subspace; Computer science; Covariance matrix; Computational complexity theory; Sensor array; Signal processing; Algorithm; Adaptive filter; SIGNAL (programming language); Array processing; Control theory (sociology); Rank (graph theory); Subspace topology; Antenna array; Mathematics; Artificial intelligence; Noise (video); Machine learning; Digital signal processing; Telecommunications; Antenna (radio)","score_opus":0.06330710987030926,"score_gpt":0.27389654098516714,"score_spread":0.2105894311148579,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150835235","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":[0.00046393467,0.00005507816,0.99658996,0.000051251078,0.00014162001,0.00039565362,0.000009668215,0.00041278772,0.0018800718],"genre_scores_gemma":[0.54442567,0.0000033448061,0.4552523,0.000062983745,0.000015678652,0.000101262776,4.9350507e-7,0.00001726625,0.00012099194],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983812,0.000062271916,0.00043433649,0.000440117,0.00037100632,0.00031107356],"domain_scores_gemma":[0.99896497,0.0001532767,0.00020724541,0.00022199634,0.00035461003,0.00009792173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039763213,0.0002235745,0.00025140733,0.00032237885,0.00043664355,0.00013584702,0.0003709348,0.00010898699,0.000025000827],"category_scores_gemma":[0.0000051300317,0.00022791073,0.0001584727,0.0006098363,0.00007182741,0.0017136219,0.000001821008,0.00019996995,0.0000037377295],"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":[0.000035709247,0.00016717565,3.843037e-7,0.00006681985,0.000026131278,9.98511e-7,0.00046671278,0.7180094,0.007787767,0.009076317,0.00003612298,0.26432648],"study_design_scores_gemma":[0.00021538178,0.00015515689,3.7171324e-7,0.000091598944,0.000017806635,0.000011380519,0.000027256603,0.6369011,0.34727177,0.015066256,0.00006908797,0.00017286371],"about_ca_topic_score_codex":0.000013891186,"about_ca_topic_score_gemma":0.0000031579964,"teacher_disagreement_score":0.54396176,"about_ca_system_score_codex":0.00010213184,"about_ca_system_score_gemma":0.00024864537,"threshold_uncertainty_score":0.929393},"labels":[],"label_agreement":null},{"id":"W2151766157","doi":"10.1109/tap.2009.2015814","title":"On Proper Antenna Pattern for a Simple Source Detection and Localization System","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Antennas and Propagation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Simple (philosophy); Computer science; Antenna (radio); Envelope (radar); Directional antenna; Slot antenna; SIGNAL (programming language); Radiation pattern; Set (abstract data type); Range (aeronautics); Signal processing; Smart antenna; Acoustics; Electronic engineering; Telecommunications; Physics; Engineering; Radar","score_opus":0.012069290556538928,"score_gpt":0.23716540206577416,"score_spread":0.22509611150923522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151766157","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":[0.013031572,0.000014388957,0.98551697,0.00019127115,0.00014000923,0.0007063673,0.000006430014,0.00034267936,0.00005032337],"genre_scores_gemma":[0.9973287,0.000022396154,0.0023252803,0.00017256281,0.000016392265,0.000074436124,0.0000023699015,0.000010919793,0.00004692194],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990552,0.000057373913,0.0002688043,0.00031638637,0.00017192193,0.00013027713],"domain_scores_gemma":[0.99937546,0.00006097135,0.0001343652,0.00018927714,0.00018513556,0.00005477108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022386515,0.00014055634,0.00015251532,0.00023428726,0.00025817213,0.00010143157,0.00008750313,0.000079001176,0.0000014758243],"category_scores_gemma":[0.000012577453,0.00012294881,0.000044436278,0.00026289083,0.00003584146,0.00041259563,0.0000012032491,0.00008370763,0.0000018916636],"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":[0.00009186577,0.00012236214,0.000012293543,0.00014330102,0.000012544559,5.3147255e-7,0.0003963402,0.0010514375,0.023260096,0.0016880323,0.000013218494,0.97320795],"study_design_scores_gemma":[0.0003796394,0.0010710463,0.0003026209,0.00016175667,0.000016531956,0.000022007669,0.00004535786,0.88066727,0.116085924,0.001027296,0.00007472634,0.00014582986],"about_ca_topic_score_codex":0.00003522168,"about_ca_topic_score_gemma":0.000014052866,"teacher_disagreement_score":0.98429716,"about_ca_system_score_codex":0.00004666749,"about_ca_system_score_gemma":0.000016739357,"threshold_uncertainty_score":0.5013707},"labels":[],"label_agreement":null},{"id":"W2152988895","doi":"10.1109/ccece.2009.5090300","title":"Impact of a finite ground plane on the accuracy of conventional wideband direction finding systems for signals of unknown polarization","year":2009,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; Royal Military College of Canada","funders":"","keywords":"Wideband; Direction finding; Ground plane; Polarization (electrochemistry); Acoustics; Physics; Computer science; Optics; Algorithm; Telecommunications","score_opus":0.03696195137168532,"score_gpt":0.32028209590127943,"score_spread":0.2833201445295941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152988895","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":[0.14681317,0.000032094256,0.8515669,0.00007578966,0.00011194083,0.00048220958,0.00002493966,0.00005893974,0.0008339913],"genre_scores_gemma":[0.99612117,0.000007972642,0.003699918,0.000010672109,0.000012982592,0.000011867225,0.000013636414,0.0000038058465,0.00011795833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989428,0.00007780526,0.0004916456,0.00013391631,0.00026728457,0.000086567175],"domain_scores_gemma":[0.9974943,0.0012457732,0.0006844784,0.00021526263,0.00033968227,0.000020498328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052917417,0.00008849151,0.00021507316,0.00021495938,0.000046067813,0.000027660095,0.0002404391,0.000051496707,0.00001847494],"category_scores_gemma":[0.0005305255,0.00006203557,0.00012416266,0.00039823065,0.000036079196,0.00037618622,0.000017458337,0.000039789666,4.3872464e-7],"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":[0.00023104933,0.0007994756,0.0038326548,0.00033790735,0.00021293398,2.7028963e-7,0.00071243907,0.025844531,0.38414696,0.5667554,0.0013800696,0.015746312],"study_design_scores_gemma":[0.0007000651,0.0024419557,0.04901822,0.00070337654,0.000035645535,0.0000075138987,0.000026422511,0.29741496,0.63448936,0.014876554,0.000080682104,0.00020525568],"about_ca_topic_score_codex":0.00029763475,"about_ca_topic_score_gemma":0.0000019423064,"teacher_disagreement_score":0.849308,"about_ca_system_score_codex":0.00003878667,"about_ca_system_score_gemma":0.000070499416,"threshold_uncertainty_score":0.2529737},"labels":[],"label_agreement":null},{"id":"W2154354807","doi":"10.1109/tsp.2012.2189389","title":"Robust Adaptive Beamforming Based on Steering Vector Estimation With as Little as Possible Prior Information","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":280,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Adaptive beamformer; Robustness (evolution); Mathematical optimization; Beamforming; Quadratic programming; Minimum-variance unbiased estimator; Computer science; Convex optimization; Control theory (sociology); Mathematics; Algorithm; Regular polygon; Artificial intelligence; Estimator; Statistics; Telecommunications","score_opus":0.02117742417983207,"score_gpt":0.2502864510795929,"score_spread":0.22910902689976084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154354807","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":[0.0054931785,0.000012711929,0.990671,0.0000830216,0.00013401452,0.00034330194,0.0000036523918,0.0005250473,0.002734106],"genre_scores_gemma":[0.74258894,8.197666e-7,0.25717908,0.00010474716,0.000016629938,0.00006443533,0.0000020807138,0.000014149486,0.000029133818],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984987,0.000042961965,0.00037153356,0.00021067983,0.0005905929,0.00028554525],"domain_scores_gemma":[0.9989637,0.00013392419,0.00029219038,0.00023741774,0.00025118253,0.00012158025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033604063,0.00021360362,0.0001830028,0.00048585475,0.0003819646,0.0002075982,0.00025608105,0.00009021543,0.000032500546],"category_scores_gemma":[0.00001576471,0.00019568988,0.000060344995,0.0008035714,0.00005184308,0.0054254103,0.0000027418046,0.00024246659,0.000055450313],"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":[0.00011971466,0.00017775755,0.000011057369,0.00012251362,0.0000130580265,5.4612593e-7,0.0013257215,0.5243687,0.00068488263,0.00038904473,0.0000047752933,0.4727822],"study_design_scores_gemma":[0.0002564448,0.00047202047,0.00008937141,0.0004300531,0.000018500905,0.00001519134,0.00006918715,0.71829957,0.28000444,0.00013383376,0.000022795291,0.00018863379],"about_ca_topic_score_codex":0.000056354573,"about_ca_topic_score_gemma":0.0000017092233,"teacher_disagreement_score":0.7370957,"about_ca_system_score_codex":0.00019604349,"about_ca_system_score_gemma":0.00027096592,"threshold_uncertainty_score":0.79800016},"labels":[],"label_agreement":null},{"id":"W2154620976","doi":"10.1109/icassp.2003.1199900","title":"Wideband array signal processing using MCMC methods","year":2004,"lang":"en","type":"article","venue":"2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Maximum a posteriori estimation; Markov chain Monte Carlo; Reversible-jump Markov chain Monte Carlo; Robustness (evolution); Computer science; Wideband; Cramér–Rao bound; Algorithm; Bayesian probability; Monte Carlo method; Array processing; A priori and a posteriori; Signal processing; Estimation theory; Maximum likelihood; Mathematics; Artificial intelligence; Statistics; Electronic engineering; Engineering; Telecommunications","score_opus":0.06492847587096034,"score_gpt":0.3522771052444602,"score_spread":0.28734862937349986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154620976","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":[0.0052500507,0.00016593319,0.9702568,0.00022298645,0.0006287121,0.0005118184,0.000021103788,0.000505388,0.022437185],"genre_scores_gemma":[0.46763492,0.00006954956,0.531311,0.0003328874,0.0002422232,0.000030241636,0.0000067478404,0.000043270953,0.0003291688],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954668,0.00005858013,0.001168776,0.0012189192,0.0013937394,0.0006931392],"domain_scores_gemma":[0.99084055,0.000033203327,0.0011582841,0.00023253915,0.0073890435,0.0003463861],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0011495877,0.00068089674,0.00069756596,0.0007225736,0.00050433335,0.0013553762,0.0013946097,0.0003670285,0.00015421085],"category_scores_gemma":[0.0005555652,0.00066083856,0.00009301204,0.0014964752,0.000499007,0.002291126,0.00015636277,0.0007390673,0.000025506002],"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":[0.00027077633,0.0011767044,0.0006641986,0.0009615806,0.00020753035,0.00006580647,0.0027558445,0.0019098707,0.55037177,0.19531071,0.0020454656,0.24425972],"study_design_scores_gemma":[0.0010497534,0.00046403,0.00013508495,0.0013922844,0.00008212498,0.00027525448,0.00034019526,0.6676769,0.30858025,0.017959658,0.0010232019,0.0010212339],"about_ca_topic_score_codex":0.00007756804,"about_ca_topic_score_gemma":0.000003486075,"teacher_disagreement_score":0.6657671,"about_ca_system_score_codex":0.00039959015,"about_ca_system_score_gemma":0.0015175741,"threshold_uncertainty_score":0.9996813},"labels":[],"label_agreement":null},{"id":"W2155250989","doi":"10.1109/pacrim.1991.160696","title":"Adaptive signal-subspace processing based on first-order perturbation analysis","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Subspace topology; Array processing; Covariance matrix; Algorithm; Orthonormal basis; Signal processing; Perturbation (astronomy); Nonlinear system; Applied mathematics; Recursion (computer science); Mathematics; Narrowband; Curse of dimensionality; Signal subspace; Covariance; Computer science; Digital signal processing; Mathematical analysis; Artificial intelligence; Physics; Statistics","score_opus":0.022989601279716415,"score_gpt":0.2409420675193456,"score_spread":0.2179524662396292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155250989","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":[0.00020169403,0.000019316452,0.9556543,0.001095375,0.000022757538,0.000116142925,5.727142e-7,0.0004484588,0.042441342],"genre_scores_gemma":[0.72654104,0.0000017028474,0.2723914,0.00018377969,0.0000075640714,0.000017527645,0.0000010917656,0.000004632577,0.00085125654],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898994,0.000044013366,0.0001961011,0.000291988,0.00035584025,0.0001221228],"domain_scores_gemma":[0.99906343,0.00013786931,0.00014756582,0.00031273387,0.0002929912,0.000045436296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001562681,0.00011048475,0.00015570047,0.00044843357,0.00012587236,0.000088518114,0.0002984652,0.000048912454,0.00035613144],"category_scores_gemma":[0.00007408836,0.0000968576,0.00008196163,0.0023429345,0.00002889526,0.0005049409,0.000030370202,0.000064070024,0.000025975176],"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":[0.00004211315,0.0013715997,0.003171229,0.0001220749,0.00029648343,0.0000086956015,0.0045170174,0.36144313,0.0008375787,0.0721123,0.008335148,0.5477426],"study_design_scores_gemma":[0.000079511956,0.00010497169,0.0005746414,0.000022508948,0.000030839237,3.017851e-7,0.000011322559,0.9875626,0.010651526,0.0006527561,0.00019396223,0.00011507772],"about_ca_topic_score_codex":0.00003762114,"about_ca_topic_score_gemma":0.000022795233,"teacher_disagreement_score":0.72633934,"about_ca_system_score_codex":0.000057520032,"about_ca_system_score_gemma":0.000018463295,"threshold_uncertainty_score":0.3949738},"labels":[],"label_agreement":null},{"id":"W2155835781","doi":"10.1109/78.863054","title":"Approximate maximum likelihood estimators for array processing in multiplicative noise environments","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":120,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Estimator; Multiplicative noise; Multiplicative function; Mathematics; Applied mathematics; Noise (video); Signal-to-noise ratio (imaging); Algorithm; Estimation theory; Mathematical optimization; Statistics; Computer science; Mathematical analysis; Telecommunications","score_opus":0.015599099106712082,"score_gpt":0.2656172499997385,"score_spread":0.2500181508930264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155835781","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":[0.0061746184,0.000056463356,0.9921187,0.00010874041,0.00004490809,0.00065696886,0.000010402917,0.00032965597,0.00049950735],"genre_scores_gemma":[0.7403074,0.000009076905,0.25917575,0.000059924034,0.000010708376,0.0003491511,0.0000013291047,0.000026936805,0.000059723745],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980844,0.000051015508,0.00054611906,0.0005875981,0.00035520087,0.00037561313],"domain_scores_gemma":[0.99924207,0.00008044167,0.00022258708,0.00028063153,0.00007027137,0.00010398604],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003095171,0.0002656054,0.00029264425,0.00033865977,0.00028820772,0.0001396849,0.0004984829,0.000116904506,0.000035164016],"category_scores_gemma":[0.0000055151077,0.00027324856,0.000102014295,0.00070365274,0.000113145215,0.0013148066,0.0000022303443,0.00023689473,0.000015958494],"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":[0.00006222268,0.00038998754,0.000018052568,0.00014373059,0.00000709846,0.0000010417244,0.0011390069,0.013147531,0.02686478,0.000013552698,0.000003912014,0.9582091],"study_design_scores_gemma":[0.0005592345,0.0001291866,0.00009704385,0.00034095006,0.000015928388,0.000008013977,0.000037027832,0.45230195,0.54167575,0.004441488,0.0001103215,0.00028313635],"about_ca_topic_score_codex":0.000014318412,"about_ca_topic_score_gemma":0.0000031913853,"teacher_disagreement_score":0.957926,"about_ca_system_score_codex":0.00014243927,"about_ca_system_score_gemma":0.00013087342,"threshold_uncertainty_score":0.999972},"labels":[],"label_agreement":null},{"id":"W2157006365","doi":"10.1109/icassp.1994.389847","title":"Adaptive beamforming of cyclic signal and fast implementation","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Beamforming; Adaptive beamformer; Computer science; Sonar; Channel (broadcasting); SIGNAL (programming language); Interference (communication); Radar; Signal processing; Electronic engineering; Real-time computing; Telecommunications; Artificial intelligence; Engineering","score_opus":0.02351093694845345,"score_gpt":0.2710456078590393,"score_spread":0.24753467091058584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157006365","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":[0.02551889,0.000014844077,0.9644448,0.00006517124,0.000021139322,0.00009882755,0.0000011590735,0.00009541967,0.009739705],"genre_scores_gemma":[0.7745033,0.000005331666,0.22540356,0.00001878548,0.00000347314,0.000004531237,3.1473718e-7,0.0000015895334,0.000059146532],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995454,0.000013079969,0.00016711005,0.00009567412,0.00011831548,0.000060447885],"domain_scores_gemma":[0.99970067,0.000037635687,0.00009624705,0.000091003734,0.000054014625,0.000020442316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008416388,0.000042355572,0.00007220992,0.0000880959,0.000025169917,0.000013612892,0.00011129641,0.000014360989,0.00013809936],"category_scores_gemma":[0.0000052455625,0.0000394908,0.00001631868,0.00015898581,0.000025936495,0.0004386058,0.000054384705,0.00002067303,0.0000025894444],"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":[0.0000017930731,0.000046668632,0.0011349507,0.000017205319,0.000014989693,3.5855768e-7,0.0018082402,0.000037720125,0.018763965,0.09960796,0.00062578125,0.87794036],"study_design_scores_gemma":[0.00019725644,0.00025822312,0.0036741262,0.000020879736,0.0000053609756,0.000006199827,0.00025062048,0.18474744,0.8054468,0.005150831,0.00013584977,0.00010642367],"about_ca_topic_score_codex":0.00011594851,"about_ca_topic_score_gemma":0.000010142711,"teacher_disagreement_score":0.87783396,"about_ca_system_score_codex":0.000010575253,"about_ca_system_score_gemma":0.000005240791,"threshold_uncertainty_score":0.1610388},"labels":[],"label_agreement":null},{"id":"W2157084855","doi":"10.1109/taes.2004.1337475","title":"Array shape estimation and tracking using active sonar reverberation","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Toronto; Concordia University","keywords":"Reverberation; Beamforming; Marine mammals and sonar; Sonar; Multipath propagation; Doppler effect; Acoustics; Computer science; Sensor array; Underwater acoustics; Direction of arrival; Underwater; Geology; Physics; Antenna (radio); Channel (broadcasting); Telecommunications","score_opus":0.01601925585487397,"score_gpt":0.25814291995346006,"score_spread":0.2421236640985861,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157084855","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":[0.13268007,0.00016900263,0.86628914,0.00017830523,0.0001638625,0.00030548286,0.0000024817666,0.00015841813,0.00005322338],"genre_scores_gemma":[0.9753911,0.00013487783,0.024353834,0.000022257485,0.000016987888,0.00003487776,7.012382e-7,0.000012935795,0.00003242994],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99893504,0.00005716901,0.00024576992,0.0003154381,0.00021389913,0.00023269314],"domain_scores_gemma":[0.9994448,0.00005551691,0.00015621129,0.00019443003,0.00009045479,0.000058603975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002230187,0.00015486153,0.00019930102,0.00016501613,0.00025473593,0.00013933223,0.000107469794,0.000093991686,0.0000017937745],"category_scores_gemma":[0.0000053951985,0.00016080469,0.00003936573,0.00032858815,0.000047293935,0.00081006234,0.000001339706,0.00018107951,0.0000022063164],"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":[0.00007554353,0.00028067312,0.000025569414,0.00026540557,0.00015476243,0.0000027771514,0.0043758745,0.23633902,0.45947203,0.024995565,0.000014614966,0.27399817],"study_design_scores_gemma":[0.0006534993,0.00043496795,0.000118364,0.00035975743,0.00004248659,0.00016970825,0.00014383443,0.35998777,0.6354454,0.0022831003,0.000055935223,0.00030515908],"about_ca_topic_score_codex":0.00028012437,"about_ca_topic_score_gemma":0.00004711032,"teacher_disagreement_score":0.84271103,"about_ca_system_score_codex":0.00025706686,"about_ca_system_score_gemma":0.00012628677,"threshold_uncertainty_score":0.65574247},"labels":[],"label_agreement":null},{"id":"W2157902093","doi":"10.1109/taes.2010.5461642","title":"Spacial Extrapolation-Based Blind DOA Estimation Approach for Closely Spaced Sources","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Extrapolation; Direction of arrival; Algorithm; Autoregressive model; Rotational invariance; Mean squared error; Snapshot (computer storage); Mathematics; Estimation theory; Computational complexity theory; Computer science; Statistics; Antenna (radio); Telecommunications","score_opus":0.013116546107509869,"score_gpt":0.25580732529832867,"score_spread":0.2426907791908188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157902093","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":[0.033059783,0.000053422686,0.9645495,0.00027266474,0.00053811946,0.00097142474,0.000011339341,0.00033691616,0.00020683698],"genre_scores_gemma":[0.92320865,0.000010834384,0.076146275,0.00002484261,0.00005468679,0.00033803994,0.00000547973,0.000022020618,0.00018914843],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984851,0.00006259378,0.00035291482,0.00043166673,0.0003057337,0.00036202327],"domain_scores_gemma":[0.9988591,0.00021499024,0.00024317359,0.000418184,0.0001677983,0.00009675141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051185134,0.00022409843,0.00027935603,0.00029934116,0.00031018126,0.00021377094,0.00027881804,0.00019386149,0.000004121153],"category_scores_gemma":[0.00001869848,0.00022008696,0.000118533135,0.00045929634,0.00008322547,0.0003661746,0.0000014447468,0.00031791636,0.0000031404443],"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":[0.000750599,0.0016500945,0.00024014499,0.0010168515,0.00036846937,0.0000010214467,0.0028001806,0.511511,0.2211439,0.13757925,0.0007920625,0.1221464],"study_design_scores_gemma":[0.0008812036,0.00036390085,0.000034570963,0.000031210384,0.000032255735,0.000012662553,0.00003574632,0.88607657,0.111423686,0.0004554057,0.00041659948,0.0002361866],"about_ca_topic_score_codex":0.00016342432,"about_ca_topic_score_gemma":0.0000972079,"teacher_disagreement_score":0.8901489,"about_ca_system_score_codex":0.00007135929,"about_ca_system_score_gemma":0.00023004833,"threshold_uncertainty_score":0.8974886},"labels":[],"label_agreement":null},{"id":"W2158016691","doi":"10.1109/ccece.2007.263","title":"MUSIC-Based Joint DoA Estimation and Signal Enumeration","year":2007,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Dimension (graph theory); Subspace topology; Covariance matrix; Noise (video); Enumeration; Eigenvalues and eigenvectors; Algorithm; Mathematics; Covariance; Applied mathematics; Spectrum (functional analysis); Detection theory; Computer science; Signal subspace; SIGNAL (programming language); Matrix (chemical analysis); Speech recognition; Statistics; Discrete mathematics; Combinatorics; Mathematical analysis; Artificial intelligence; Telecommunications; Physics","score_opus":0.021803130807092452,"score_gpt":0.2633371951717538,"score_spread":0.24153406436466135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158016691","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":[0.011167961,0.0000063610382,0.9833888,0.00022061956,0.00007110694,0.00012796075,2.9447187e-7,0.00034135507,0.0046755704],"genre_scores_gemma":[0.56120634,3.0664484e-7,0.43864256,0.00011318493,0.0000074734526,0.0000032280338,0.0000014272711,0.0000020883513,0.000023411947],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931216,0.00002004404,0.0002303278,0.0001572659,0.00018906633,0.000091155154],"domain_scores_gemma":[0.9995101,0.00007729643,0.00009567737,0.00016572412,0.00010764775,0.000043551645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005169961,0.00006632175,0.000079235695,0.00016796176,0.000055034016,0.00006440784,0.000104609346,0.000038213922,0.000040155664],"category_scores_gemma":[0.000048397673,0.000062343606,0.000021439248,0.00023230228,0.00002968038,0.00048591773,0.000031905354,0.000040932693,0.000007860705],"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":[0.000007346747,0.00007856833,0.00025076157,0.00003476736,0.000005768425,0.0000020074149,0.0003174468,0.0019137438,0.037231337,0.1577557,0.00085175014,0.8015508],"study_design_scores_gemma":[0.00008322824,0.00005225693,0.0024734312,0.0000115227,0.0000016718351,0.0000026171285,0.0000028522286,0.5949108,0.39674085,0.005588147,0.0000741313,0.00005850849],"about_ca_topic_score_codex":0.000051489205,"about_ca_topic_score_gemma":0.000012634885,"teacher_disagreement_score":0.8014923,"about_ca_system_score_codex":0.000025524432,"about_ca_system_score_gemma":0.000033488872,"threshold_uncertainty_score":0.25422987},"labels":[],"label_agreement":null},{"id":"W2158365388","doi":"10.1109/mcise.2003.1238705","title":"The direction-of-arrival problem: coming at you","year":2003,"lang":"en","type":"article","venue":"Computing in Science & Engineering","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Submarine; Direction of arrival; Computer science; Computation; Navy; SIGNAL (programming language); Eigenvalues and eigenvectors; Transmitter; Algorithm; Real-time computing; Telecommunications; Engineering; Physics; Marine engineering","score_opus":0.008856306417097795,"score_gpt":0.24439006973270433,"score_spread":0.23553376331560655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158365388","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":[0.27685055,0.00013181701,0.71850413,0.00005001913,0.00089006114,0.00019744386,2.0787694e-7,0.00030996295,0.0030658056],"genre_scores_gemma":[0.8201341,0.0000059037707,0.17980969,0.0000049571204,0.00001052928,0.000005459245,6.819895e-8,0.000006971497,0.000022312603],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99831045,0.000040621675,0.00047293873,0.00033497365,0.00046739582,0.00037364732],"domain_scores_gemma":[0.99870807,0.00039129792,0.00019489907,0.0004741344,0.00016649335,0.000065120024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024141106,0.00012872793,0.00017739442,0.00033122927,0.00030270254,0.00010816943,0.0011152402,0.00003402511,0.0000012233337],"category_scores_gemma":[0.00089147384,0.00011244007,0.00004919602,0.0021986514,0.00022135892,0.00044750897,0.0003277733,0.00014320992,0.0000021166227],"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":[0.0000029618893,0.00006671775,0.014136598,0.00006402651,0.000009478846,0.000003290003,0.00248452,0.3061972,0.1413592,0.499331,0.00005583035,0.03628915],"study_design_scores_gemma":[0.000120815326,0.000034271427,0.0069434275,0.0001649345,0.0000017659441,0.000024534538,0.000022242313,0.68281287,0.30718893,0.0009586149,0.0015473561,0.00018028216],"about_ca_topic_score_codex":0.000021370113,"about_ca_topic_score_gemma":0.0000033317235,"teacher_disagreement_score":0.5432836,"about_ca_system_score_codex":0.0001959047,"about_ca_system_score_gemma":0.00012437483,"threshold_uncertainty_score":0.4585173},"labels":[],"label_agreement":null},{"id":"W2158386631","doi":"10.1109/lsp.2008.2008482","title":"A Robust Adaptive Dimension Reduction Technique With Application to Array Processing","year":2008,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Robustness (evolution); Orthogonality; Algorithm; Computer science; Preprocessor; Adaptive filter; Dimension (graph theory); Matrix (chemical analysis); Reduction (mathematics); Signal processing; Noise reduction; Dimensionality reduction; Mathematics; Digital signal processing; Artificial intelligence; Computer hardware","score_opus":0.022742001599102276,"score_gpt":0.2385570505773691,"score_spread":0.2158150489782668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158386631","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":[0.019472443,0.000021873195,0.97777325,0.0009981372,0.000045141882,0.0006596532,6.1718276e-7,0.0007751046,0.00025378822],"genre_scores_gemma":[0.5986897,6.973918e-7,0.40077174,0.00025624354,0.00004673245,0.00020598329,0.0000012119816,0.000017420429,0.00001032269],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99826777,0.000054972188,0.00034051627,0.000573605,0.0005081502,0.0002550055],"domain_scores_gemma":[0.99887747,0.000022016136,0.00035045922,0.00029424424,0.00035875736,0.0000970571],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002710734,0.00021830692,0.00021884328,0.00035522468,0.00034361694,0.00008382694,0.0004327714,0.00007448327,0.0000012836102],"category_scores_gemma":[0.000010112045,0.00019915432,0.000039345,0.0012720542,0.00015354216,0.0012144531,0.000033158525,0.00019336859,0.0000070288365],"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":[0.0000446105,0.00006262967,0.000031817992,0.00006194392,0.000005670444,0.000004748191,0.0011394285,0.013546253,0.90230554,0.00005704265,0.0004113936,0.08232893],"study_design_scores_gemma":[0.00013324669,0.00021506714,0.00015770251,0.00043529028,0.000010515283,0.0002451987,0.000028378621,0.042618167,0.9554592,0.00028377151,0.00009257383,0.0003209314],"about_ca_topic_score_codex":0.000036951318,"about_ca_topic_score_gemma":0.0000010469872,"teacher_disagreement_score":0.5792172,"about_ca_system_score_codex":0.00014352454,"about_ca_system_score_gemma":0.00017577996,"threshold_uncertainty_score":0.81212777},"labels":[],"label_agreement":null},{"id":"W2158835216","doi":"10.1109/tsp.2007.893977","title":"Information Theoretic Enumeration and Tracking of Multiple Sources","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Clutter; Computer science; Algorithm; Tracking (education); A priori and a posteriori; Noise (video); Wideband; Artificial intelligence; Radar; Electronic engineering; Telecommunications","score_opus":0.013194962004283339,"score_gpt":0.2555405531673103,"score_spread":0.24234559116302695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158835216","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":[0.057947747,0.00002653876,0.94134074,0.000030322513,0.000051017007,0.00011373024,0.0000015832536,0.00014442837,0.000343861],"genre_scores_gemma":[0.95746535,0.0000052851715,0.04247678,0.000030131858,0.0000070971305,0.0000057036914,5.7310484e-7,0.000004613416,0.0000044570943],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991609,0.000025197547,0.00036989822,0.00009880857,0.00024009428,0.00010513937],"domain_scores_gemma":[0.99927974,0.00015949807,0.00022606358,0.00010006908,0.00019927928,0.000035366487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004612252,0.00008666988,0.00011228398,0.00030441093,0.00014784026,0.00008634371,0.00013515569,0.000055397344,0.00000602462],"category_scores_gemma":[0.000012892779,0.00008469458,0.000034375927,0.00036867577,0.00008183388,0.0018293043,0.0000014800133,0.00010024096,0.0000013864867],"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":[0.000024737614,0.000050953913,0.00006689121,0.00012162432,0.0000061323994,1.7253635e-7,0.003644893,0.0041684275,0.017365595,0.0009779441,0.0000011650003,0.9735715],"study_design_scores_gemma":[0.00016092438,0.000087875116,0.00036078732,0.0001242408,0.000008872104,0.0000075194703,0.0001507878,0.16434106,0.833074,0.0015764984,0.000021244532,0.00008623909],"about_ca_topic_score_codex":0.000016218268,"about_ca_topic_score_gemma":0.0000041922426,"teacher_disagreement_score":0.97348523,"about_ca_system_score_codex":0.00002155356,"about_ca_system_score_gemma":0.000040150622,"threshold_uncertainty_score":0.34537446},"labels":[],"label_agreement":null},{"id":"W2159693415","doi":"10.1109/lsp.2003.817852","title":"Adaptive beamforming with sidelobe control: a second-order cone programming approach","year":2003,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":126,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Adaptive beamformer; Beamforming; Second-order cone programming; Minimum-variance unbiased estimator; Control theory (sociology); Cone (formal languages); Computer science; Mathematics; Convex optimization; Mathematical optimization; Regular polygon; Algorithm; Control (management); Telecommunications; Statistics","score_opus":0.014256741831875482,"score_gpt":0.22759183949744605,"score_spread":0.21333509766557057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159693415","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":[0.0076156664,0.00006321951,0.98898536,0.00020869428,0.000059307735,0.00042071787,0.0000012672035,0.00048732918,0.0021584544],"genre_scores_gemma":[0.5639712,1.8195504e-7,0.4352356,0.0006705657,0.000018272329,0.0000664907,7.232377e-7,0.000016915137,0.000020054067],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998166,0.00009726685,0.00038479912,0.00048635478,0.00046741005,0.00039817166],"domain_scores_gemma":[0.998877,0.00009041034,0.00038241205,0.0002528269,0.00030214514,0.00009522027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004866942,0.00025247532,0.00031562627,0.00021040719,0.00020870668,0.00023398879,0.00043541103,0.0000688912,0.000007795089],"category_scores_gemma":[0.000031385152,0.00022031521,0.000057841582,0.0008255095,0.0001959726,0.0012264999,0.00002187326,0.00023589566,0.0000030675328],"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":[0.00026089477,0.0008994343,0.0011473512,0.0011356659,0.0004265787,0.00009305041,0.0076867524,0.046958707,0.2065954,0.016096083,0.0014663169,0.7172338],"study_design_scores_gemma":[0.0035441432,0.0009860588,0.00016649177,0.0009102346,0.00012353202,0.0004719215,0.0004994688,0.5991449,0.38612813,0.0024938146,0.0036241028,0.0019072437],"about_ca_topic_score_codex":0.000018704446,"about_ca_topic_score_gemma":0.0000023068342,"teacher_disagreement_score":0.7153265,"about_ca_system_score_codex":0.000071750874,"about_ca_system_score_gemma":0.00021913991,"threshold_uncertainty_score":0.8984193},"labels":[],"label_agreement":null},{"id":"W2161879122","doi":"10.1109/aps.1993.385572","title":"Performance analysis of broadband adaptive digital beamforming","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Wideband; Bandwidth (computing); Adaptive beamformer; Broadband; Computer science; Beamforming; Interference (communication); Narrowband; Electronic engineering; Telecommunications; Engineering","score_opus":0.02125075284190264,"score_gpt":0.2284124586797433,"score_spread":0.20716170583784066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161879122","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":[0.16064863,0.000013916672,0.776624,0.000021368332,0.000026833493,0.000051279654,0.0000024265091,0.00014989101,0.062461633],"genre_scores_gemma":[0.91901726,0.000009303033,0.08046074,0.000010685556,0.0000029310897,0.0000028380693,7.451757e-7,0.0000020158682,0.00049349805],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993682,0.0000059433455,0.00022196717,0.00012951174,0.00019173844,0.000082665],"domain_scores_gemma":[0.9994444,0.00004732226,0.00012234117,0.0002515379,0.000107727894,0.000026636539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007313411,0.000059002126,0.00015837682,0.00033251062,0.000031111078,0.000031209034,0.00029460274,0.00002236775,0.00007395367],"category_scores_gemma":[0.000023213086,0.00005183783,0.00007997661,0.0012528286,0.000037668324,0.0010638648,0.000072916104,0.000029624955,0.000007461022],"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":[0.000006790353,0.0002456436,0.033952206,0.000036492816,0.0005498054,9.4647527e-7,0.002788809,0.005508209,0.0007826299,0.026777377,0.00058710016,0.928764],"study_design_scores_gemma":[0.00004289862,0.000083036146,0.004508943,0.000011127182,0.000030517815,0.0000015663683,0.0000112682665,0.9668612,0.028099034,0.00014811492,0.00013371113,0.00006859213],"about_ca_topic_score_codex":0.000021596308,"about_ca_topic_score_gemma":0.0000020802795,"teacher_disagreement_score":0.961353,"about_ca_system_score_codex":0.00001570075,"about_ca_system_score_gemma":0.0000064092237,"threshold_uncertainty_score":0.21138853},"labels":[],"label_agreement":null},{"id":"W2161887073","doi":"10.1109/tsp.2007.909223","title":"A Two-Stage Approach to Estimate the Angles of Arrival and the Angular Spreads of Locally Scattered Sources","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Estimator; Algorithm; Channel (broadcasting); Angle of arrival; Direction of arrival; Covariance; Computer science; Preprocessor; Mathematics; Statistics; Telecommunications","score_opus":0.022200631189151578,"score_gpt":0.28254859265716037,"score_spread":0.2603479614680088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161887073","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":[0.068867564,0.000103758524,0.92984474,0.00016041171,0.000028169852,0.0002973522,0.0000054154993,0.000098466364,0.0005941079],"genre_scores_gemma":[0.89631766,0.000005061511,0.103524566,0.000060073708,0.000008441484,0.00003724778,2.3950005e-7,0.000010531757,0.000036162783],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987129,0.000114003364,0.00039384866,0.00024531313,0.00038797458,0.00014595884],"domain_scores_gemma":[0.999017,0.00018685758,0.00024472384,0.00031134326,0.00019146672,0.000048626116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004624457,0.0001443754,0.00026289374,0.00017451684,0.0002902668,0.000052785264,0.00053971465,0.00004115541,0.000003520738],"category_scores_gemma":[0.000011326142,0.00009209243,0.00008900031,0.00062140386,0.0005911219,0.00033859388,0.000008669303,0.00014158196,6.483353e-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":[0.00058877235,0.0010198199,0.00022940863,0.0009043688,0.0001917202,0.00000515679,0.038134407,0.3967344,0.08422467,0.0048725563,0.00004264926,0.47305208],"study_design_scores_gemma":[0.0006600161,0.00015635263,0.00033931923,0.00022336103,0.00004157962,0.00005668416,0.0002609011,0.39083624,0.60620433,0.0010430786,0.000015932392,0.00016220822],"about_ca_topic_score_codex":0.00009833819,"about_ca_topic_score_gemma":0.0000043685845,"teacher_disagreement_score":0.8274501,"about_ca_system_score_codex":0.000014357812,"about_ca_system_score_gemma":0.0000980384,"threshold_uncertainty_score":0.375542},"labels":[],"label_agreement":null},{"id":"W2162194155","doi":"10.1109/radar.2006.1631785","title":"Building a Confidence Interval for the Number of Signals in Noise using Likelihood Ratio Test Statistics","year":2006,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Confidence interval; Statistics; Noise (video); CDF-based nonparametric confidence interval; Mathematics; Percentile; Interval (graph theory); Signal-to-noise ratio (imaging); Credible interval; Likelihood-ratio test; Population; Algorithm; Computer science; Artificial intelligence","score_opus":0.022789616787549496,"score_gpt":0.3255521427564812,"score_spread":0.3027625259689317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162194155","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":[0.008734701,0.000011797624,0.99037045,0.00010038678,0.00007051219,0.0002672614,0.000014316346,0.00006227604,0.00036831058],"genre_scores_gemma":[0.5048411,8.372273e-7,0.49508694,0.00002286014,0.000008785566,0.000012190036,3.8220594e-7,0.0000032302619,0.00002370017],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912894,0.000028614673,0.00040705744,0.00014535288,0.00016903166,0.000120988276],"domain_scores_gemma":[0.9982871,0.0010337812,0.00019889389,0.00021513105,0.00024963787,0.000015482248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004195403,0.00007553225,0.00014089524,0.000071089176,0.000037573413,0.000058665944,0.00038004637,0.000028051434,0.000019109044],"category_scores_gemma":[0.00033724113,0.00005969454,0.000034273333,0.0002939813,0.000056859528,0.0003023103,0.00008088295,0.000046022997,0.0000011919801],"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":[0.000010184976,0.00023581185,0.008687644,0.00011047814,0.00001337803,0.0000018031808,0.00031781162,0.0064237397,0.13066691,0.8283195,0.001691711,0.023521041],"study_design_scores_gemma":[0.00011136775,0.000031461772,0.0015247405,0.00007363165,0.000005289883,0.0000046430023,0.0000134027105,0.6966699,0.22829488,0.07317641,0.000026324382,0.00006797284],"about_ca_topic_score_codex":0.0012451223,"about_ca_topic_score_gemma":0.000079144804,"teacher_disagreement_score":0.75514305,"about_ca_system_score_codex":0.000032913133,"about_ca_system_score_gemma":0.00008263903,"threshold_uncertainty_score":0.24342728},"labels":[],"label_agreement":null},{"id":"W2163940726","doi":"","title":"Direction of Arrival Estimation and Tracking with Sparse Arrays","year":2013,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Electronic Science and Technology of China; University of Hong Kong; Concordia University","keywords":"Redundancy (engineering); Computer science; Direction of arrival; Algorithm; Tracking (education); Sparse array; Sensor array; Maximum a posteriori estimation; Mathematics; Telecommunications; Maximum likelihood","score_opus":0.023909062210471666,"score_gpt":0.27668653631913415,"score_spread":0.25277747410866247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163940726","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":[0.8857175,0.00008158021,0.051927857,0.000077121826,0.00050990604,0.0008443262,0.000003928837,0.00032550597,0.06051228],"genre_scores_gemma":[0.98707247,0.00008592452,0.007125803,9.58246e-7,0.000047353173,0.000008056438,0.000020532512,0.00002783899,0.005611087],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974453,0.00034682846,0.0003656994,0.00062241865,0.0008751559,0.00034459712],"domain_scores_gemma":[0.9976326,0.0002592319,0.0005512533,0.00063074013,0.0007641636,0.00016201343],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004800955,0.00025082976,0.00043279474,0.0016951654,0.0003221571,0.00016974754,0.0007393812,0.0002480578,0.000010145946],"category_scores_gemma":[0.00011448055,0.00026540656,0.000097058124,0.0014849873,0.0002699312,0.0013200687,0.00011793234,0.00056564977,0.0000040994323],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002183632,0.0013644836,0.041884303,0.0056429394,0.0014551873,0.0006825623,0.011599105,0.001736971,0.40840068,0.25391757,0.0018472428,0.26928532],"study_design_scores_gemma":[0.00061300566,0.0011933388,0.10069494,0.0010000961,0.00008815262,0.00005964513,0.0008933094,0.023579078,0.8667394,0.003895089,0.0006563089,0.00058762013],"about_ca_topic_score_codex":0.006663069,"about_ca_topic_score_gemma":0.0011247122,"teacher_disagreement_score":0.45833874,"about_ca_system_score_codex":0.0002895747,"about_ca_system_score_gemma":0.0006004957,"threshold_uncertainty_score":0.9999798},"labels":[],"label_agreement":null},{"id":"W2165224060","doi":"10.1109/tsp.2007.906764","title":"Design and Analysis of Supervised and Decision-Directed Estimators of the MMSE/LCMV Filter in Data Limited Environments","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Estimator; Minimum mean square error; Fading; Computer science; Algorithm; Filter (signal processing); Multipath propagation; Context (archaeology); Minimum-variance unbiased estimator; Upper and lower bounds; Mean squared error; Control theory (sociology); Filter design; Mathematics; Adaptive filter; Statistics; Artificial intelligence; Decoding methods","score_opus":0.050381240299691786,"score_gpt":0.2750907678134825,"score_spread":0.22470952751379072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165224060","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":[0.18026519,0.000054651402,0.8194454,0.00002053408,0.000017949682,0.00013856131,0.000011085121,0.000038277267,0.000008391386],"genre_scores_gemma":[0.78835565,0.000034501663,0.21157654,0.000013604625,9.050037e-7,0.000006980139,0.0000012234507,0.000005931158,0.000004656064],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873585,0.00009714208,0.00042379857,0.00031475187,0.00032550315,0.00010293173],"domain_scores_gemma":[0.99890375,0.00037591567,0.00019004519,0.0004382416,0.00005297906,0.000039090763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030142895,0.00011785477,0.0002768463,0.0005339255,0.000118004245,0.000021882586,0.0004591639,0.000060192586,0.000010472577],"category_scores_gemma":[0.000019105835,0.000095781645,0.00004276301,0.0016044305,0.00019417201,0.00059376116,0.000015493328,0.000109677785,1.9457613e-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":[0.00017451437,0.0007572589,0.004483493,0.00013710423,0.00033277358,0.0000052139935,0.0033336538,0.1648654,0.06705255,0.000013486117,0.000028208688,0.75881636],"study_design_scores_gemma":[0.00021198468,0.000038658734,0.008994947,0.00012274276,0.00009505946,0.000005671581,0.0000100155485,0.84765226,0.14261402,0.00017334231,0.0000017861277,0.00007953423],"about_ca_topic_score_codex":0.000034805285,"about_ca_topic_score_gemma":0.000006982791,"teacher_disagreement_score":0.7587368,"about_ca_system_score_codex":0.000020343221,"about_ca_system_score_gemma":0.00006435709,"threshold_uncertainty_score":0.39058623},"labels":[],"label_agreement":null},{"id":"W2165555792","doi":"10.1109/vetecs.2005.1543241","title":"High Resolution Estimation of Directions of Arrival","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Matching pursuit; A priori and a posteriori; Computer science; Convergence (economics); Algorithm; Direction of arrival; Matching (statistics); Estimation; Resolution (logic); Tree (set theory); High resolution; Artificial intelligence; Mathematics; Engineering; Statistics; Telecommunications; Remote sensing; Geography; Compressed sensing","score_opus":0.011798746745625874,"score_gpt":0.265292562987906,"score_spread":0.2534938162422801,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165555792","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":[0.02140106,0.000025937048,0.969973,0.00034215092,0.00013872515,0.00011984446,0.0000028916174,0.00027942707,0.0077169463],"genre_scores_gemma":[0.561303,0.00000795724,0.4385527,0.0000073803462,0.000009899867,0.0000054839434,0.0000013695003,0.0000024624148,0.00010974328],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99905884,0.00004058105,0.00042323768,0.00014378739,0.00025043302,0.000083130326],"domain_scores_gemma":[0.9990558,0.000081713624,0.00026996955,0.0003498599,0.00021442532,0.000028225655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025216123,0.00006858711,0.00015663293,0.00023952089,0.000033662276,0.000009508176,0.0002706888,0.000047108082,0.000041961535],"category_scores_gemma":[0.0001392452,0.00006716509,0.00005819977,0.00052636163,0.00006382316,0.0005933078,0.00006332848,0.000043358166,0.000006934629],"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":[0.000008871241,0.00023875687,0.00014014432,0.000049583443,0.000020133099,1.0359599e-7,0.00031043155,0.02919199,0.016152605,0.57122105,0.0014970336,0.3811693],"study_design_scores_gemma":[0.000104647355,0.000082193474,0.0032129155,0.000040553234,0.0000065106096,0.0000026378254,0.000004587894,0.3624805,0.62517685,0.008476274,0.00034710066,0.00006524544],"about_ca_topic_score_codex":0.0002897506,"about_ca_topic_score_gemma":0.000017456296,"teacher_disagreement_score":0.6090242,"about_ca_system_score_codex":0.000040337978,"about_ca_system_score_gemma":0.00004521211,"threshold_uncertainty_score":0.2738913},"labels":[],"label_agreement":null},{"id":"W2167339465","doi":"10.1109/pimrc.2011.6139850","title":"Second-order moment-based direction finding of a single source for ULA systems","year":2011,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Direction of arrival; Estimator; Computer science; Algorithm; Covariance matrix; Moment (physics); Range (aeronautics); Eigendecomposition of a matrix; Matrix (chemical analysis); SIGNAL (programming language); Noise (video); Simple (philosophy); White noise; Mathematics; Eigenvalues and eigenvectors; Telecommunications; Artificial intelligence; Statistics; Engineering","score_opus":0.05183151416455932,"score_gpt":0.2618286494006942,"score_spread":0.2099971352361349,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167339465","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":[0.011566438,0.000014658423,0.9749506,0.000018047982,0.0002972403,0.00032294283,0.000002292087,0.00036700038,0.01246079],"genre_scores_gemma":[0.7541912,2.833036e-7,0.24459304,0.000019114292,0.000009859679,0.00006137147,0.0000013077968,0.000008140753,0.0011156651],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99921393,0.00003315649,0.00029845178,0.00018667524,0.00014765757,0.00012010385],"domain_scores_gemma":[0.9991428,0.00009728187,0.0002288427,0.0002734103,0.00022499321,0.000032639055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028886824,0.0000829083,0.00015662669,0.00020532566,0.00004500791,0.000029405703,0.0002534954,0.000049344908,0.00004760256],"category_scores_gemma":[0.0000540251,0.00007879813,0.000058773705,0.00033654203,0.000026608219,0.00029012034,0.000036688118,0.000027798354,0.0000026433952],"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":[0.00014176387,0.0023893511,0.0046291584,0.0023918888,0.00024649382,0.0000017354589,0.007094201,0.004211397,0.4130363,0.34948447,0.009033172,0.20734006],"study_design_scores_gemma":[0.00022360405,0.00025411914,0.00026018164,0.00007468254,0.000006872667,0.0000022196496,0.00003668049,0.1945604,0.80140513,0.0006633696,0.0023938676,0.000118857686],"about_ca_topic_score_codex":0.00017151382,"about_ca_topic_score_gemma":0.000010060109,"teacher_disagreement_score":0.74262476,"about_ca_system_score_codex":0.000042917985,"about_ca_system_score_gemma":0.000037742513,"threshold_uncertainty_score":0.32132947},"labels":[],"label_agreement":null},{"id":"W2167599467","doi":"10.1109/iscas.2011.5937584","title":"Minimum redundancy linear sparse subarrays for direction of arrival estimation without ambiguity","year":2011,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Redundancy (engineering); Algorithm; Kronecker delta; Ambiguity; Computer science; Direction of arrival; Multiple signal classification; Mathematics; Telecommunications","score_opus":0.05360478227637365,"score_gpt":0.29665901988898197,"score_spread":0.2430542376126083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167599467","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":[0.037939068,0.000008594941,0.95037085,0.000054110853,0.00040898347,0.00044243594,0.0000047028234,0.00052198797,0.0102492925],"genre_scores_gemma":[0.5137238,0.0000028974948,0.48601443,0.000010181962,0.000016190037,0.000036453264,0.0000027318983,0.000007939741,0.00018538094],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99869955,0.000051047835,0.00051944307,0.00030782432,0.00025294602,0.0001691894],"domain_scores_gemma":[0.99858016,0.00007298426,0.00037392403,0.0005132775,0.00039305523,0.00006660441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049424684,0.00014110732,0.00025833008,0.0002118719,0.00007066901,0.00002001049,0.0004331184,0.00008946118,0.00003377561],"category_scores_gemma":[0.00030509045,0.00013619724,0.00011186551,0.00037933973,0.00008552897,0.0007162693,0.00007513353,0.00006250215,0.000007768746],"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":[0.00045481877,0.0019845564,0.011535195,0.0009676067,0.0001998761,0.0000024769995,0.008250214,0.0010021481,0.10976034,0.39276424,0.0048780316,0.4682005],"study_design_scores_gemma":[0.00025557177,0.00029182786,0.004480014,0.00005067394,0.000016094655,0.0000049425025,0.000012691645,0.28684363,0.68702996,0.020709964,0.00015288319,0.00015176607],"about_ca_topic_score_codex":0.00028925875,"about_ca_topic_score_gemma":0.000017952736,"teacher_disagreement_score":0.5772696,"about_ca_system_score_codex":0.000038032027,"about_ca_system_score_gemma":0.00007633231,"threshold_uncertainty_score":0.55539626},"labels":[],"label_agreement":null},{"id":"W2167754229","doi":"10.1109/ccece.2010.5575147","title":"A spatio-temporal stacking approach for estimating two-dimensional direction-of-arrival","year":2010,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Azimuth; Stacking; Computer science; Algorithm; Singular value decomposition; Block matrix; Direction of arrival; Matrix (chemical analysis); Block (permutation group theory); Matching (statistics); Face (sociological concept); Mathematics; Telecommunications; Geometry; Statistics; Antenna (radio); Physics","score_opus":0.020932144755841826,"score_gpt":0.293578499594771,"score_spread":0.2726463548389292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167754229","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":[0.035375565,0.000004776077,0.95818585,0.00007046811,0.00073736376,0.00042590144,0.000005702314,0.00051889446,0.0046754475],"genre_scores_gemma":[0.4454399,5.781737e-8,0.5543541,0.00001791191,0.00005223714,0.000046813824,0.0000110234,0.000009506815,0.000068489826],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984305,0.000039474136,0.00054581475,0.0003801716,0.00039060967,0.00021342549],"domain_scores_gemma":[0.99831504,0.00029865603,0.00038677058,0.000473738,0.00044647686,0.00007931111],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073869055,0.00016404247,0.00027221144,0.00024157963,0.00014214552,0.00006819539,0.00052184256,0.0000797835,0.000031809635],"category_scores_gemma":[0.00039046374,0.00015437635,0.00012863835,0.00043936414,0.00009065428,0.0006662203,0.00016236823,0.00016364247,0.0000020867697],"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":[0.000095372394,0.0010866476,0.014369414,0.00055744644,0.0001604397,0.0000020334896,0.0014254926,0.044236913,0.09489324,0.49610925,0.0040213857,0.34304237],"study_design_scores_gemma":[0.00027550117,0.00007663821,0.00034401543,0.000022378974,0.0000072941643,0.000012031492,0.000006389468,0.87194425,0.11967995,0.0073329294,0.00014030945,0.00015829293],"about_ca_topic_score_codex":0.00027077217,"about_ca_topic_score_gemma":0.00003034105,"teacher_disagreement_score":0.82770735,"about_ca_system_score_codex":0.000023993447,"about_ca_system_score_gemma":0.00013844662,"threshold_uncertainty_score":0.6295285},"labels":[],"label_agreement":null},{"id":"W2167937813","doi":"10.1109/icassp.1994.389827","title":"Array signal number detection for coherent and incoherent signals in unknown noise environments","year":2002,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Detector; SIGNAL (programming language); Noise (video); White noise; Detection theory; Computer science; Parametric statistics; Signal processing; Signal-to-noise ratio (imaging); Array processing; Algorithm; Speech recognition; Artificial intelligence; Telecommunications; Mathematics; Statistics","score_opus":0.0193658158160032,"score_gpt":0.2487743229906159,"score_spread":0.2294085071746127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167937813","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":[0.048071265,0.000021886535,0.94766015,0.00009641691,0.00007798974,0.00048650824,0.0000013483739,0.00010967555,0.0034747408],"genre_scores_gemma":[0.94936174,0.000016915918,0.049905747,0.00005025933,0.000013056885,0.00014765769,6.488431e-7,0.0000073438205,0.00049662293],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990764,0.0000454107,0.00028407545,0.00026469128,0.00018282373,0.0001465833],"domain_scores_gemma":[0.9995369,0.000101678655,0.00010429293,0.00018112568,0.000019683086,0.000056361845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018862555,0.00011121886,0.00014409624,0.000096160446,0.000043358865,0.000043972992,0.00018122222,0.000057557863,0.00023744872],"category_scores_gemma":[0.000018584173,0.00010425174,0.000037830046,0.00014029935,0.000037331127,0.00036566396,0.00005361203,0.000058931368,0.000023356533],"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":[0.000021072681,0.00063448894,0.0033080142,0.00006781342,0.000029059316,0.0000014772806,0.00059172587,0.0004802819,0.275975,0.004030807,0.0008333552,0.7140269],"study_design_scores_gemma":[0.00043046646,0.00015791251,0.002185383,0.000030808038,0.000004521032,0.000005103725,0.000007889395,0.09404891,0.8953266,0.00484812,0.0027874876,0.00016678152],"about_ca_topic_score_codex":0.000047756257,"about_ca_topic_score_gemma":0.000029145514,"teacher_disagreement_score":0.9012905,"about_ca_system_score_codex":0.00006699604,"about_ca_system_score_gemma":0.0000053384542,"threshold_uncertainty_score":0.42512625},"labels":[],"label_agreement":null},{"id":"W2168375507","doi":"10.1109/lsp.2011.2152393","title":"Joint DOD and DOA Estimation for MIMO Array With Velocity Receive Sensors","year":2011,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"MIMO; Direction of arrival; Joint (building); Computer science; Sensor array; Constraint (computer-aided design); Algorithm; Pairing; Key (lock); Mathematics; Telecommunications; Engineering; Channel (broadcasting); Antenna (radio); Physics","score_opus":0.032979630456559494,"score_gpt":0.2480927040236721,"score_spread":0.2151130735671126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168375507","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":[0.07704622,0.000010861432,0.9214452,0.00063548196,0.0000644375,0.00025336642,0.0000017115206,0.00026267505,0.00028003266],"genre_scores_gemma":[0.53363156,5.612135e-7,0.4660488,0.00025968446,0.000015742298,0.000028025257,7.857558e-7,0.000008699409,0.0000061482515],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989996,0.000035910016,0.00024549544,0.00032438867,0.00021531034,0.00017931669],"domain_scores_gemma":[0.99927825,0.000057572674,0.00026838406,0.00016122629,0.00017589369,0.00005868701],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002910314,0.00014584379,0.00017576355,0.00014734182,0.00015161639,0.000101041485,0.00020655035,0.000047549882,0.00000284378],"category_scores_gemma":[0.000029510124,0.0001263801,0.000032612545,0.00025085072,0.00014637996,0.0007991704,0.000016168435,0.00009244785,0.0000017055031],"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":[0.00018128895,0.00017583116,0.0003232348,0.00088852627,0.00007737833,0.0000116090105,0.013457125,0.0037112175,0.4313105,0.0012106664,0.002071467,0.54658115],"study_design_scores_gemma":[0.0003122992,0.00021003542,0.0009326924,0.00028279182,0.000021857282,0.000029717106,0.000027935974,0.18159312,0.8118108,0.004463932,0.00004212637,0.00027270257],"about_ca_topic_score_codex":0.000034941557,"about_ca_topic_score_gemma":0.000001516851,"teacher_disagreement_score":0.54630846,"about_ca_system_score_codex":0.00003815758,"about_ca_system_score_gemma":0.00005954439,"threshold_uncertainty_score":0.5153631},"labels":[],"label_agreement":null},{"id":"W2168896363","doi":"10.1109/iscas.2005.1464869","title":"Pilot-Aided DOA Estimation for CDMA Communication Systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Direction of arrival; Computer science; Beamforming; Interference (communication); Code division multiple access; Algorithm; Subspace topology; Eigendecomposition of a matrix; Computation; Electronic engineering; Telecommunications; Eigenvalues and eigenvectors; Engineering; Artificial intelligence","score_opus":0.033627548050709895,"score_gpt":0.30686232492754245,"score_spread":0.27323477687683256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168896363","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":[0.000971225,0.00006144954,0.9876013,0.0009845793,0.0001347214,0.00050091144,0.0000016083867,0.00072313775,0.009021064],"genre_scores_gemma":[0.4932178,0.000005732942,0.50629497,0.000048857903,0.000012771891,0.00009574314,0.0000054362636,0.0000043444397,0.0003143721],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916995,0.000053609023,0.00034029403,0.00015872436,0.0001713259,0.00010610415],"domain_scores_gemma":[0.9986643,0.00023486237,0.00018883216,0.00064145256,0.00023508725,0.000035465022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046130805,0.000080962236,0.00012464394,0.00013145349,0.00009250077,0.00011224524,0.0005936085,0.000029999417,0.000008212612],"category_scores_gemma":[0.00014128863,0.000077394405,0.000038069284,0.00024031813,0.00002732806,0.00097185513,0.000080592814,0.00004270249,0.000028304314],"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":[0.0000064995584,0.00010386289,0.000029662559,0.000045091238,0.00001019237,3.39712e-8,0.0001925993,0.0103602875,0.0015057548,0.86163104,0.008583147,0.11753184],"study_design_scores_gemma":[0.00017894662,0.00009763848,0.00015860952,0.000044197583,0.000003859818,0.000003515019,0.0000072016214,0.96241146,0.026380295,0.0075520924,0.0030698287,0.000092353184],"about_ca_topic_score_codex":0.00014334137,"about_ca_topic_score_gemma":0.000017458508,"teacher_disagreement_score":0.95205116,"about_ca_system_score_codex":0.00006777231,"about_ca_system_score_gemma":0.000035303623,"threshold_uncertainty_score":0.31560522},"labels":[],"label_agreement":null},{"id":"W2169081015","doi":"10.1109/78.815500","title":"Matrix filter design using semi-infinite programming with application to DOA estimation","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McMaster University","funders":"","keywords":"Stopband; Filter design; Passband; Elliptic filter; Convex optimization; Control theory (sociology); Filter (signal processing); Mathematics; Matrix (chemical analysis); Butterworth filter; Linear matrix inequality; Prototype filter; Computer science; Mathematical optimization; Algorithm; Electronic engineering; Band-pass filter; Regular polygon; Engineering","score_opus":0.02371013390922769,"score_gpt":0.2946813301141164,"score_spread":0.2709711962048887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169081015","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":[0.0037710627,0.000012135624,0.9946133,0.00009879432,0.000029274026,0.0006711335,0.0000022378279,0.000650438,0.00015165728],"genre_scores_gemma":[0.51864815,9.718883e-7,0.48113054,0.000047274578,0.000009906813,0.00010094332,7.1325127e-7,0.000015548258,0.000045929573],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984199,0.00006833827,0.00039114492,0.0004350793,0.00043358497,0.00025195006],"domain_scores_gemma":[0.99912614,0.000088664034,0.00016637974,0.00030217564,0.0002101001,0.00010656757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030574278,0.00021011144,0.00019571935,0.0003600818,0.00033123823,0.00024873536,0.00033988542,0.00008185487,0.000045460598],"category_scores_gemma":[0.000002891873,0.00019978707,0.00005273172,0.0013405619,0.000051124993,0.0012321527,0.0000019079969,0.00017103525,0.00003387626],"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":[0.000035634373,0.000063547915,0.0000013432145,0.000033056134,0.0000060746956,7.126605e-7,0.000328715,0.4546101,0.005114322,0.00001839571,0.0000031808602,0.5397849],"study_design_scores_gemma":[0.00014520095,0.00018849972,0.00000782956,0.00023049995,0.000022972687,0.000029359506,0.000009567212,0.78494805,0.21376798,0.0003341192,0.00011669516,0.00019922035],"about_ca_topic_score_codex":0.00003608139,"about_ca_topic_score_gemma":0.000002536399,"teacher_disagreement_score":0.53958565,"about_ca_system_score_codex":0.000113951966,"about_ca_system_score_gemma":0.0001453198,"threshold_uncertainty_score":0.81470805},"labels":[],"label_agreement":null},{"id":"W2170097251","doi":"10.1109/tsp.2006.877653","title":"A new DOA estimation technique based on subarray beamforming","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Huazhong University of Science and Technology; University of Victoria","keywords":"Beamforming; Interference (communication); SIGNAL (programming language); Computer science; Direction of arrival; Algorithm; Phase (matter); Computation; Antenna (radio); Electronic engineering; Telecommunications; Engineering; Physics","score_opus":0.011946119289156945,"score_gpt":0.25715204350177845,"score_spread":0.2452059242126215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170097251","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":[0.00017968885,0.0000094829165,0.9958158,0.00022873639,0.00010059143,0.00035741628,0.0000027197154,0.0009763031,0.002329242],"genre_scores_gemma":[0.56862205,2.8711852e-7,0.43113726,0.00006507422,0.000018668614,0.00006004583,0.0000011952252,0.000014322721,0.00008107349],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983744,0.000050180275,0.00044458252,0.0003870228,0.0005107103,0.00023309105],"domain_scores_gemma":[0.9990968,0.00012837033,0.00023189094,0.00031161835,0.00015172071,0.00007956061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031452562,0.00021914755,0.0002035056,0.00058816496,0.0002972942,0.00017567346,0.0003934491,0.000121928584,0.000038348782],"category_scores_gemma":[0.0000063815946,0.00022145489,0.000109400295,0.0009852198,0.00004520747,0.001014149,0.0000016742745,0.00025655163,0.000014129308],"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":[0.000027813687,0.00017983808,0.0000031445898,0.000076057484,0.0000039297947,0.000002140023,0.00008132974,0.365243,0.032695774,0.000596777,0.000096251264,0.60099393],"study_design_scores_gemma":[0.00013432544,0.00011803849,0.000010407251,0.00021650745,0.000007919768,0.000006794568,0.0000024557914,0.48034367,0.51568633,0.0032849468,0.00005204325,0.00013656446],"about_ca_topic_score_codex":0.00012079466,"about_ca_topic_score_gemma":0.0000065519985,"teacher_disagreement_score":0.6008574,"about_ca_system_score_codex":0.00014202943,"about_ca_system_score_gemma":0.00030547843,"threshold_uncertainty_score":0.9030668},"labels":[],"label_agreement":null},{"id":"W2170619594","doi":"10.1109/sam.2002.1191055","title":"Parametric localization of multiple incoherently distributed sources using covariance fitting","year":2003,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McMaster University","funders":"","keywords":"Covariance matrix; Parametric statistics; Covariance; Moment (physics); Method of moments (probability theory); Algorithm; Computer science; Power (physics); Mathematics; Mathematical optimization; Physics; Statistics","score_opus":0.028080482176225566,"score_gpt":0.2708055657913634,"score_spread":0.24272508361513784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170619594","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":[0.0188162,0.00002838433,0.979941,0.000008805797,0.000068573005,0.00013643419,0.0000030418785,0.0001881433,0.0008094253],"genre_scores_gemma":[0.665477,0.0000013753031,0.3344824,0.000009967344,0.000002666991,0.0000029308087,0.0000022282943,0.000003524454,0.000017949673],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903595,0.00008976047,0.0003638114,0.00018014737,0.00021612518,0.00011420604],"domain_scores_gemma":[0.99894524,0.0002206309,0.00030525782,0.0002643626,0.00023183947,0.000032684107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031839372,0.00008115583,0.00015269867,0.00018145563,0.00006120967,0.000038566086,0.00025666572,0.000048942133,0.000032402655],"category_scores_gemma":[0.0010609603,0.000078936326,0.00003851253,0.0016210056,0.000043069635,0.00037357004,0.000054777207,0.0000424767,0.0000029871721],"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":[0.000016904074,0.0007334723,0.16849835,0.0003579299,0.0000918553,0.000002929735,0.0007295001,0.51537275,0.012493555,0.23186095,0.0005633908,0.06927843],"study_design_scores_gemma":[0.00012465622,0.000024866253,0.00055709464,0.000037037888,0.0000037675766,0.0000026353794,0.000013474173,0.7466581,0.2500592,0.0021199086,0.00032168036,0.00007759223],"about_ca_topic_score_codex":0.00019708215,"about_ca_topic_score_gemma":0.0000030570566,"teacher_disagreement_score":0.64666075,"about_ca_system_score_codex":0.000039533505,"about_ca_system_score_gemma":0.000054879154,"threshold_uncertainty_score":0.321893},"labels":[],"label_agreement":null},{"id":"W2181562192","doi":"10.21553/rev-jec.25","title":"A Novel Multi-Dimensional Spectrum Estimation Technique using Antenna Array Displacement","year":2011,"lang":"en","type":"article","venue":"REV Journal on Electronics and Communications","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Université Laval; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Computer science; Snapshot (computer storage); Antenna array; Antenna (radio); Antenna aperture; Synthetic aperture radar; Acoustics; Electronic engineering; Optics; Dipole antenna; Telecommunications; Physics; Computer vision; Engineering","score_opus":0.06328501059830022,"score_gpt":0.3128028075551181,"score_spread":0.24951779695681786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2181562192","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":[0.001690172,0.00074762746,0.99620974,0.000627777,0.000043457985,0.00019280754,0.0000027690296,0.00007613341,0.00040950454],"genre_scores_gemma":[0.32983032,0.00069299614,0.66936535,0.000057371282,0.0000053882495,0.000016187028,0.0000021634717,0.000008896327,0.000021314945],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989048,0.00010838483,0.0004108723,0.00016648865,0.00020734692,0.00020208102],"domain_scores_gemma":[0.99839896,0.00008024917,0.0003791252,0.0008609717,0.0001971206,0.000083584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005673952,0.00012878058,0.0001674761,0.00020789364,0.00037802942,0.000070575086,0.00075010036,0.00005740987,0.0000073592687],"category_scores_gemma":[0.000060022892,0.0001213208,0.00006951439,0.0003493821,0.00007537388,0.0003731409,0.00017984911,0.00040497567,0.000002378535],"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":[0.000031431264,0.0016251141,0.00012753617,0.000028075454,0.00011688313,0.000003657522,0.00060715876,0.00039929722,0.27117026,0.7044862,0.000044738073,0.021359682],"study_design_scores_gemma":[0.0004898491,0.0004829361,0.0007478548,0.0003232732,0.000043960514,0.0013752969,0.00001526518,0.82200176,0.11843536,0.054880764,0.00088993524,0.00031377774],"about_ca_topic_score_codex":0.000021326758,"about_ca_topic_score_gemma":0.000011292702,"teacher_disagreement_score":0.8216024,"about_ca_system_score_codex":0.00016089257,"about_ca_system_score_gemma":0.0002534091,"threshold_uncertainty_score":0.49473184},"labels":[],"label_agreement":null},{"id":"W2196292687","doi":"10.1016/b978-0-12-411597-2.00012-6","title":"Adaptive and Robust Beamforming","year":2014,"lang":"en","type":"book-chapter","venue":"Academic press library in signal processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":34,"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 Alberta","funders":"","keywords":"Adaptive beamformer; Beamforming; WSDMA; Computer science; Algorithm; Adaptive filter; Sample matrix inversion; Covariance matrix; Control theory (sociology); Precoding; Artificial intelligence; Telecommunications; MIMO","score_opus":0.03439249069938835,"score_gpt":0.2444656379628306,"score_spread":0.21007314726344226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2196292687","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":[0.000024951934,0.0056118607,0.71068925,0.00013635893,0.00006733744,0.00031865443,0.000006906613,0.0006030448,0.28254163],"genre_scores_gemma":[0.16807714,0.00371787,0.7138073,0.0014338788,0.00078791106,0.00014557762,0.000045506684,0.00036206527,0.111622795],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998109,0.000037096703,0.000670542,0.00057736214,0.00036053415,0.000245508],"domain_scores_gemma":[0.9987411,0.00021981038,0.0006528916,0.00024677665,0.000044547116,0.000094899944],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002668757,0.0003296048,0.00045879962,0.00036951678,0.00007675934,0.00011969963,0.0010429207,0.0005747174,0.000018369641],"category_scores_gemma":[0.00002042911,0.00033864382,0.0000544127,0.000101738595,0.00017577817,0.0033855103,0.0006963836,0.0010926111,0.0000026429248],"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":[0.000021357493,0.000008150151,0.000053296193,0.0005894334,0.00001910675,0.000008908567,0.0006864904,0.0007393773,0.00012944294,0.32032195,0.0009952263,0.67642725],"study_design_scores_gemma":[0.00040773122,0.0001952865,0.000038800852,0.010092785,0.000045740984,0.00008102645,0.000016767348,0.44601107,0.016880743,0.4926071,0.032320622,0.0013023344],"about_ca_topic_score_codex":0.0000063551124,"about_ca_topic_score_gemma":1.4231397e-7,"teacher_disagreement_score":0.67512494,"about_ca_system_score_codex":0.000027834998,"about_ca_system_score_gemma":0.00015408934,"threshold_uncertainty_score":0.99990654},"labels":[],"label_agreement":null},{"id":"W2200561009","doi":"10.1007/978-3-662-05592-2_6","title":"Sidelobe Control Using Optimization Methods in Adaptive Beamforming","year":2004,"lang":"en","type":"book-chapter","venue":"Signals and communication technology","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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 Victoria","funders":"","keywords":"Beamforming; Adaptive beamformer; Clutter; Sonar; Radar; Computer science; Marine mammals and sonar; Beam pattern; Electronic engineering; Wireless; Acoustics; Engineering; Telecommunications; Artificial intelligence; Antenna (radio); Physics","score_opus":0.033981866631340736,"score_gpt":0.3260193453829988,"score_spread":0.2920374787516581,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2200561009","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":[0.000010406483,0.0022163333,0.9725532,0.00048872887,0.000030991087,0.000424781,0.0000042490815,0.00035434696,0.023916971],"genre_scores_gemma":[0.03683962,0.00079168007,0.96179557,0.00007282275,0.0000046317086,0.000042532713,0.0000064318992,0.000025182522,0.0004215325],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986079,0.00009460668,0.0006654575,0.00033278286,0.00014415664,0.00015514667],"domain_scores_gemma":[0.99771816,0.00021573245,0.00073282374,0.0010183412,0.00028375108,0.000031202697],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00062186917,0.00023214797,0.00048359865,0.0010450245,0.00011289096,0.00003786707,0.0009827305,0.00054596167,0.000028173135],"category_scores_gemma":[0.000086606335,0.00025787976,0.00006124424,0.0002840787,0.00027701966,0.00034199655,0.00045318523,0.00044099652,0.0000013407985],"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":[0.0000048788074,0.00001795461,0.0000048114807,0.000016174405,0.000026872236,7.737148e-7,0.0000801278,0.015045642,0.000624881,0.8719191,0.0000028007698,0.11225596],"study_design_scores_gemma":[0.00032851388,0.00013142443,0.0000029000264,0.0005267221,0.000025632076,0.000019284022,0.000025204483,0.27649766,0.0066011758,0.715111,0.00046097886,0.0002694821],"about_ca_topic_score_codex":0.00007745568,"about_ca_topic_score_gemma":0.000010440625,"teacher_disagreement_score":0.26145202,"about_ca_system_score_codex":0.00016961106,"about_ca_system_score_gemma":0.0001556366,"threshold_uncertainty_score":0.99998736},"labels":[],"label_agreement":null},{"id":"W2243812048","doi":"10.1109/camsap.2015.7383805","title":"Asymptotically optimal narrowband signal detection using uniform linear array antenna","year":2015,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Narrowband; Estimator; Algorithm; Mathematics; Likelihood-ratio test; Direction of arrival; Outlier; Estimation theory; Statistics; Gaussian noise; Detection theory; Detector; Computer science; Antenna (radio); Telecommunications","score_opus":0.03968816526032651,"score_gpt":0.2853541979610899,"score_spread":0.2456660327007634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2243812048","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":[0.03855706,0.000007320892,0.9561243,0.00009813043,0.00021221394,0.00012068508,6.0564275e-7,0.000521518,0.004358149],"genre_scores_gemma":[0.5445765,5.891731e-7,0.4552804,0.00003624108,0.000031581974,0.0000024424833,4.036636e-7,0.000005898832,0.00006594729],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998846,0.000046928577,0.00030385365,0.00024818734,0.0003656068,0.00018945083],"domain_scores_gemma":[0.9989795,0.000047238587,0.00011801702,0.00029233051,0.00041699625,0.0001458933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004941299,0.00012190064,0.00015561162,0.00018058055,0.00007002488,0.00007991264,0.00037830515,0.00008181911,0.00002074436],"category_scores_gemma":[0.00011268153,0.00010983804,0.00005603231,0.0004890688,0.00006619682,0.0008614306,0.00008452809,0.00010978104,0.000020849222],"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":[0.0001489046,0.0005656794,0.0014402522,0.00008763193,0.00011224113,0.000023542858,0.0023058935,0.029365387,0.819516,0.050549228,0.00033236973,0.09555285],"study_design_scores_gemma":[0.00013643004,0.00017890154,0.0000627127,0.00001646784,0.000004264004,0.000035155095,0.000021974298,0.6492851,0.34839842,0.0016175397,0.0001332854,0.000109752815],"about_ca_topic_score_codex":0.00009712641,"about_ca_topic_score_gemma":0.000007722658,"teacher_disagreement_score":0.6199197,"about_ca_system_score_codex":0.0000881681,"about_ca_system_score_gemma":0.00014635782,"threshold_uncertainty_score":0.44790652},"labels":[],"label_agreement":null},{"id":"W2244144132","doi":"10.1049/iet-rsn.2015.0401","title":"Multiple targets direction‐of‐arrival estimation in frequency scanning array antennas","year":2015,"lang":"en","type":"article","venue":"IET Radar Sonar & Navigation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Direction of arrival; Estimation; Computer science; Acoustics; Telecommunications; Physics; Engineering; Antenna (radio)","score_opus":0.021053408939478515,"score_gpt":0.27697204289979477,"score_spread":0.2559186339603163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2244144132","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":[0.19319189,0.00018212623,0.80421215,0.0002306762,0.0004985545,0.00035023535,0.000008042865,0.00036965884,0.00095665053],"genre_scores_gemma":[0.61863345,0.0000047290555,0.3812553,0.000010866577,0.000021656604,0.000022689346,0.000027130913,0.000010635642,0.000013509341],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980716,0.00015188074,0.00064365636,0.0003542121,0.00056639384,0.00021223363],"domain_scores_gemma":[0.99852824,0.00011870437,0.00046377545,0.00037960318,0.00041124423,0.00009843323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084582006,0.00017357334,0.0002763686,0.0003199894,0.00006905706,0.000048502265,0.0004067708,0.00011351863,0.0000043210525],"category_scores_gemma":[0.00031954487,0.00019088884,0.00007270537,0.0010409637,0.00008105909,0.0014941758,0.00005391682,0.0001671063,0.000011966745],"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":[0.00014615186,0.0011360997,0.12663323,0.00047051255,0.00011082696,0.000045717683,0.029855855,0.010729582,0.34560648,0.052428916,0.0018809179,0.43095574],"study_design_scores_gemma":[0.001439153,0.00039372384,0.042320695,0.00081824133,0.000020314852,0.000058718764,0.0002654086,0.3533324,0.5127618,0.08752829,0.0004456164,0.0006156433],"about_ca_topic_score_codex":0.0010128112,"about_ca_topic_score_gemma":0.00004428095,"teacher_disagreement_score":0.43034008,"about_ca_system_score_codex":0.00022831211,"about_ca_system_score_gemma":0.00018970293,"threshold_uncertainty_score":0.77842206},"labels":[],"label_agreement":null},{"id":"W2255848753","doi":"10.1016/j.acha.2016.02.001","title":"Finite-length and asymptotic analysis of averaged correlogram for undersampled data","year":2016,"lang":"en","type":"article","venue":"Applied and Computational Harmonic Analysis","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Correlogram; Mathematical analysis; Applied mathematics; Statistics","score_opus":0.035839945968615915,"score_gpt":0.2853665673918079,"score_spread":0.24952662142319196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2255848753","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":[0.015502959,0.00005503293,0.98375344,0.00022890819,0.000015801817,0.00015929146,0.00010781145,0.00007096912,0.00010576109],"genre_scores_gemma":[0.8560239,0.000038547547,0.14366922,0.000055026216,0.000005162189,0.000019410596,0.00016919296,0.000004760149,0.000014783309],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986444,0.000039456507,0.0004320354,0.00048569046,0.00026627572,0.00013211563],"domain_scores_gemma":[0.9971847,0.001784478,0.0003163732,0.00046768284,0.0001808536,0.00006593745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042513336,0.00012982031,0.000469644,0.00079404475,0.00009101934,0.00004553592,0.0004569898,0.00004960974,0.000017249049],"category_scores_gemma":[0.00009090399,0.00010351391,0.00013541071,0.0020275982,0.00013110471,0.00021266004,0.00023178496,0.000036553203,7.5401397e-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":[0.000082647275,0.0002981239,0.010943967,0.000089957386,0.018339107,8.641698e-7,0.0005725672,0.071528785,0.0008083468,0.5778898,0.0002407777,0.31920505],"study_design_scores_gemma":[0.00039092597,0.000037430098,0.02749039,0.000007116029,0.0024976414,4.1339214e-7,0.000022190881,0.9322601,0.00027816236,0.03684331,0.000039925042,0.0001323806],"about_ca_topic_score_codex":0.000039487477,"about_ca_topic_score_gemma":0.000016441398,"teacher_disagreement_score":0.8607313,"about_ca_system_score_codex":0.000019351606,"about_ca_system_score_gemma":0.000057417947,"threshold_uncertainty_score":0.42211747},"labels":[],"label_agreement":null},{"id":"W2296426763","doi":"10.1109/cjece.2015.2436054","title":"Feasible Generalized Least Squares Estimation of Channel and Noise Covariance Matrices for MIMO Systems","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Covariance matrix; Mathematics; Estimator; Estimation of covariance matrices; Cramér–Rao bound; Covariance; Algorithm; Noise (video); Least-squares function approximation; Statistics; Estimation theory; Applied mathematics; Computer science; Artificial intelligence","score_opus":0.009729116961973728,"score_gpt":0.20650239202565301,"score_spread":0.19677327506367928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2296426763","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":[0.028768536,0.0011946739,0.96953344,0.00017370019,0.00020344602,0.00009968501,0.000003829007,0.00001804221,0.0000046279843],"genre_scores_gemma":[0.8766433,0.000042432726,0.12322398,0.000010054257,0.00006278393,0.0000043107284,2.0763135e-7,0.0000056279036,0.0000072931048],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934477,0.000015300331,0.00030182416,0.00009956511,0.00009186381,0.00014669048],"domain_scores_gemma":[0.9992244,0.00015913104,0.00017630337,0.00007745478,0.00017822835,0.00018446417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017514697,0.00008302733,0.00021337261,0.00034455367,0.000033890225,0.000060033548,0.00018056744,0.00003958119,4.2751384e-7],"category_scores_gemma":[0.0000735021,0.00006409986,0.000037301168,0.00023816747,0.000018570901,0.0003097276,0.000012841523,0.000043455297,8.698407e-8],"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":[0.00006705201,0.00006946532,0.0013532144,0.0010614323,0.00023675495,0.000035568155,0.0006583576,0.23106942,0.012953964,0.28157738,0.0021344128,0.468783],"study_design_scores_gemma":[0.00032987056,0.00024436275,0.0013539456,0.00024817899,0.000009583682,0.00011485642,6.7002463e-7,0.99242806,0.0041307597,0.0008077765,0.00024093935,0.00009099634],"about_ca_topic_score_codex":0.00021077282,"about_ca_topic_score_gemma":0.000011248473,"teacher_disagreement_score":0.84787476,"about_ca_system_score_codex":0.000040684004,"about_ca_system_score_gemma":0.0001207088,"threshold_uncertainty_score":0.26139164},"labels":[],"label_agreement":null},{"id":"W2340413290","doi":"10.1109/tvt.2015.2436060","title":"Bayesian Information Criterion for Source Enumeration in Large-Scale Adaptive Antenna Array","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"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":"Subspace topology; False alarm; Algorithm; Bayesian information criterion; Mathematics; Bayesian probability; Antenna array; A priori and a posteriori; Maximum a posteriori estimation; Detector; Detection theory; Enumeration; Expression (computer science); Computer science; Antenna (radio); Statistics; Discrete mathematics; Maximum likelihood; Artificial intelligence","score_opus":0.013331434477261086,"score_gpt":0.2511511021309986,"score_spread":0.23781966765373752,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2340413290","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":[0.003825265,0.00001759596,0.99323183,0.0012718027,0.00034055125,0.00047429302,0.000017902787,0.0006943054,0.00012645537],"genre_scores_gemma":[0.8078962,0.000008309724,0.19169612,0.000111508234,0.000007106845,0.00022928526,0.0000061266887,0.000010045291,0.000035308105],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879926,0.000057953144,0.0004296525,0.00026112108,0.00021829693,0.00023372579],"domain_scores_gemma":[0.9988758,0.000043972228,0.0001616056,0.0004434462,0.00042043944,0.000054729135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034529684,0.00015057501,0.00021844069,0.0009475544,0.00009690671,0.000044068405,0.0003329532,0.00027488972,0.0000032237147],"category_scores_gemma":[0.000044512024,0.00016529938,0.0000803436,0.0010469278,0.00006274902,0.001120855,0.0000042503075,0.00023280161,0.000019038609],"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":[0.00043219235,0.001984944,0.000295744,0.00020922995,0.00014804042,0.000013537483,0.0100123035,0.070671976,0.10190185,0.03477995,0.00069593545,0.7788543],"study_design_scores_gemma":[0.00078533473,0.00042633744,0.00003395165,0.00005645474,0.000011246534,0.000029422477,0.00031842795,0.4977447,0.48790777,0.009875253,0.0026202204,0.00019087538],"about_ca_topic_score_codex":0.000024014691,"about_ca_topic_score_gemma":0.000081136175,"teacher_disagreement_score":0.8040709,"about_ca_system_score_codex":0.00016009767,"about_ca_system_score_gemma":0.00011149993,"threshold_uncertainty_score":0.6740713},"labels":[],"label_agreement":null},{"id":"W2345529816","doi":"10.1007/s00034-016-0327-2","title":"DOA Estimation Using Second-Order Differential of Invariant Noise MUSIC (SODIN-MUSIC)","year":2016,"lang":"en","type":"article","venue":"Circuits Systems and Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Royal Military College of Canada; Queen's University","funders":"","keywords":"Multiple signal classification; Computer science; Invariant (physics); Direction of arrival; Noise (video); Speech recognition; Differential (mechanical device); Acoustics; Subspace topology; Algorithm; Signal subspace; Mathematics; Artificial intelligence; Telecommunications; Engineering; Physics","score_opus":0.036919087260112074,"score_gpt":0.25502797153874657,"score_spread":0.2181088842786345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345529816","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":[0.16062729,0.00018623848,0.8381276,0.000013717572,0.00017974678,0.00020553841,0.0000044434637,0.00011070482,0.0005447233],"genre_scores_gemma":[0.9908773,0.0000016364711,0.008960702,0.000012026301,0.000071620336,0.0000126773875,9.887658e-7,0.000013681737,0.000049390783],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851805,0.00007979985,0.00056399975,0.00032945123,0.00032194497,0.00018676235],"domain_scores_gemma":[0.99870944,0.00009581495,0.0005364788,0.00021731043,0.0003665848,0.000074364965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034796514,0.00016100748,0.00032441353,0.00023052651,0.00014337491,0.00017957983,0.0002692814,0.00009261003,0.000032679236],"category_scores_gemma":[0.000055734392,0.00012141748,0.00004096014,0.00038376576,0.000094082294,0.0011101837,0.00008782368,0.00006203377,0.0000015929006],"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":[0.0000050507115,0.00007018175,0.00033616895,0.0011628614,0.00002435203,0.0000029545351,0.0012422046,0.00048581304,0.55842316,0.0087782815,0.000047932186,0.429421],"study_design_scores_gemma":[0.00059539307,0.00010553997,0.0012818484,0.0025625874,0.000033781987,0.00008265803,0.000056418165,0.8964847,0.09479702,0.0035909205,0.000048457296,0.0003606728],"about_ca_topic_score_codex":0.0000625814,"about_ca_topic_score_gemma":0.0000028193986,"teacher_disagreement_score":0.8959989,"about_ca_system_score_codex":0.00004679825,"about_ca_system_score_gemma":0.00016961225,"threshold_uncertainty_score":0.4951261},"labels":[],"label_agreement":null},{"id":"W2377009302","doi":"10.1109/acssc.2003.1292208","title":"Robust adaptive beamforming using worst-case performance optimization","year":2004,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Beamforming; Adaptive beamformer; Robustness (evolution); Computer science; Microphone array; Array processing; Sonar; Wireless; Radar; Sensor array; Antenna array; Electronic engineering; Microphone; Antenna (radio); Signal processing; Telecommunications; Engineering; Artificial intelligence; Machine learning","score_opus":0.05544136726692359,"score_gpt":0.25431834202977904,"score_spread":0.19887697476285546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2377009302","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":[0.023446549,0.000007029243,0.9711917,0.00003936003,0.000110786204,0.00013722459,3.8588468e-7,0.00039128002,0.004675705],"genre_scores_gemma":[0.42838502,0.0000033010133,0.5715484,0.000025668556,0.000009000611,0.0000036802996,4.017033e-7,0.000004273733,0.00002025663],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926496,0.000013407976,0.0002270971,0.00019115061,0.00016776788,0.00013561221],"domain_scores_gemma":[0.99940467,0.000021808566,0.000126522,0.0002501294,0.00015297886,0.00004386544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017457567,0.000092660004,0.00010140613,0.00017033973,0.00013375455,0.0000548112,0.0002328192,0.000042698844,0.00001565598],"category_scores_gemma":[0.00002721357,0.000089566034,0.00003230752,0.00054072926,0.0000340497,0.0015589184,0.0000999336,0.000061549974,0.0000044323738],"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":[0.0000019648576,0.000023029314,0.000029070194,0.0000070344363,0.0000036215695,0.000007914794,0.000197672,0.9784792,0.00009044645,0.013006795,0.000004394232,0.008148822],"study_design_scores_gemma":[0.00012073255,0.00006274613,0.000016347592,0.00005344925,0.0000036181236,0.00028796223,0.000029982268,0.96056587,0.038201068,0.00054480805,0.000006967601,0.00010642907],"about_ca_topic_score_codex":0.00016264823,"about_ca_topic_score_gemma":0.000005918725,"teacher_disagreement_score":0.40493846,"about_ca_system_score_codex":0.00011721575,"about_ca_system_score_gemma":0.00007928964,"threshold_uncertainty_score":0.36523968},"labels":[],"label_agreement":null},{"id":"W2521692127","doi":"10.3390/s16091549","title":"Underdetermined DOA Estimation Using MVDR-Weighted LASSO","year":2016,"lang":"en","type":"article","venue":"Sensors","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Underdetermined system; Algorithm; Singular value decomposition; Lasso (programming language); Orthogonality; Direction of arrival; Mathematics; Noise (video); Computer science; Compressed sensing; Antenna (radio); Artificial intelligence","score_opus":0.023463364070389632,"score_gpt":0.28322431485317,"score_spread":0.2597609507827804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2521692127","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":[0.26020056,0.0000038529647,0.737354,0.0003566472,0.00019789762,0.00010537764,0.0000019816898,0.00045602815,0.0013236607],"genre_scores_gemma":[0.6716527,0.0000027437018,0.32807845,0.000022523951,0.000016310594,0.0000027205285,5.4498406e-7,0.000007865832,0.00021615891],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906385,0.00006345935,0.00025408485,0.00022874222,0.0002336104,0.00015628106],"domain_scores_gemma":[0.9990971,0.00014957902,0.00017258755,0.00039903814,0.00012995652,0.000051719104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001690235,0.00010480655,0.00013529538,0.00018291926,0.000059772374,0.000041542084,0.00028949874,0.000060146413,0.00001681999],"category_scores_gemma":[0.00014234055,0.00007830194,0.000050132756,0.00033645402,0.000055751923,0.0003552669,0.000075529526,0.000035942267,0.000035895737],"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":[0.0000209648,0.00013654755,0.0008351969,0.00006602183,0.000052007897,0.00001789034,0.0007073231,0.0022681386,0.1975353,0.079724185,0.00060318067,0.71803325],"study_design_scores_gemma":[0.0002144168,0.00004719545,0.00067918736,0.00009693259,0.000006744371,0.000019576099,0.0000036979422,0.64576995,0.33145154,0.021244615,0.00030545137,0.00016069064],"about_ca_topic_score_codex":0.000036536887,"about_ca_topic_score_gemma":0.000003177956,"teacher_disagreement_score":0.71787256,"about_ca_system_score_codex":0.000083856845,"about_ca_system_score_gemma":0.000045544948,"threshold_uncertainty_score":0.31930605},"labels":[],"label_agreement":null},{"id":"W2534732770","doi":"10.1109/acssc.2006.355175","title":"Robust Minimum Variance Beamforming with Dual Response Constraints","year":2006,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Robustness (evolution); Control theory (sociology); Beamforming; Adaptive beamformer; Computer science; Constraint (computer-aided design); Diagonal; Filter (signal processing); Mathematical optimization; Mathematics; Algorithm; Telecommunications","score_opus":0.015343076773743018,"score_gpt":0.22886365793160532,"score_spread":0.2135205811578623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2534732770","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":[0.02254696,0.0000054685574,0.95340586,0.0003531895,0.00007202117,0.00012304788,0.0000017348234,0.0004844691,0.023007272],"genre_scores_gemma":[0.46928188,3.3988215e-7,0.52984226,0.000050549592,0.000011606946,0.000008263197,6.5445136e-7,0.00000439217,0.0008000757],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99908876,0.000051944233,0.00023012597,0.00022957956,0.00023817706,0.00016143653],"domain_scores_gemma":[0.99920654,0.00018322055,0.00011553419,0.00033104734,0.00012614903,0.000037504677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041897307,0.00009837372,0.00012056285,0.00012368408,0.000063568536,0.00006745153,0.00028377163,0.000040681745,0.00004218694],"category_scores_gemma":[0.00006148127,0.00008227085,0.000025857144,0.00038716482,0.00014327132,0.0005479125,0.00006572682,0.00005862054,0.000013233718],"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":[0.0003582583,0.00041504853,0.0016787401,0.000054407687,0.00004283345,0.00009256382,0.00055093,0.006690497,0.039915197,0.86526346,0.008464568,0.0764735],"study_design_scores_gemma":[0.0017007448,0.0010765794,0.022946863,0.00030849353,0.000023226195,0.0006928931,0.0001093878,0.21207255,0.7300928,0.022734998,0.007109151,0.0011323125],"about_ca_topic_score_codex":0.000085436746,"about_ca_topic_score_gemma":0.000013282908,"teacher_disagreement_score":0.84252846,"about_ca_system_score_codex":0.000031936026,"about_ca_system_score_gemma":0.0001222383,"threshold_uncertainty_score":0.3354908},"labels":[],"label_agreement":null},{"id":"W2541809568","doi":"10.1109/acssc.2011.6190076","title":"Maximum likelihood time delay estimation for Direct-Spread CDMA multipath transmissions using importance sampling","year":2011,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Multipath propagation; Computer science; Estimator; Algorithm; Delay spread; Cramér–Rao bound; Code division multiple access; Maximum likelihood; Antenna array; Upper and lower bounds; Maximum likelihood sequence estimation; Estimation theory; Electronic engineering; Antenna (radio); Statistics; Telecommunications; Mathematics; Engineering","score_opus":0.06225893573434387,"score_gpt":0.30258446788941734,"score_spread":0.24032553215507346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2541809568","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":[0.00788902,0.000030155572,0.98497677,0.00003902218,0.00014452428,0.0005358141,0.000010190529,0.0008574284,0.005517103],"genre_scores_gemma":[0.2314253,0.0000036220324,0.7683846,0.0000414447,0.000012991272,0.000049608418,0.0000058206924,0.000017656674,0.000058988637],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855584,0.000033017343,0.00050192914,0.00040415564,0.00021980287,0.0002852311],"domain_scores_gemma":[0.9987521,0.0001663135,0.00024271579,0.0004902107,0.00022733166,0.00012131418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035976476,0.00018482142,0.00024695016,0.00019193809,0.00016669503,0.000054340187,0.0005078246,0.00009853123,0.00007849635],"category_scores_gemma":[0.00014625274,0.00017241393,0.00012527738,0.00038038014,0.000039159513,0.00091774436,0.000063641346,0.00007303222,0.000013506371],"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":[0.000066810586,0.00067503017,0.0013512723,0.00019733641,0.000096390526,0.0000053394792,0.004321741,0.0019553448,0.08165689,0.022610359,0.0007204375,0.88634306],"study_design_scores_gemma":[0.00021007675,0.0000903288,0.00038347533,0.000087204404,0.000019992862,0.000010627453,0.000007704294,0.81003237,0.1604589,0.028269213,0.00020750561,0.00022262594],"about_ca_topic_score_codex":0.00013847604,"about_ca_topic_score_gemma":0.000008087505,"teacher_disagreement_score":0.88612044,"about_ca_system_score_codex":0.000058549806,"about_ca_system_score_gemma":0.0001009218,"threshold_uncertainty_score":0.7030836},"labels":[],"label_agreement":null},{"id":"W2542249827","doi":"10.1109/ssp.2003.1289459","title":"A bayesian approach to tracking wideband targets using sensor arrays and particle filters","year":2004,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Particle filter; Robustness (evolution); Wideband; Computer science; Estimator; Bayesian probability; Tracking (education); Direction of arrival; Smart antenna; Electronic engineering; Antenna (radio); Engineering; Artificial intelligence; Kalman filter; Telecommunications; Mathematics; Directional antenna; Statistics","score_opus":0.030643845539128856,"score_gpt":0.26967073194336905,"score_spread":0.2390268864042402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2542249827","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":[0.052019194,0.000011026018,0.94528025,0.00030268813,0.00005264185,0.00016674068,4.72404e-7,0.00025347524,0.0019135035],"genre_scores_gemma":[0.52165514,5.337387e-7,0.47820407,0.000114082875,0.0000062355666,0.0000040384894,1.3409365e-7,0.0000038222965,0.000011969341],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99922603,0.000022116528,0.00018120685,0.0002523242,0.00015212606,0.00016619374],"domain_scores_gemma":[0.9995404,0.000027092989,0.000050265844,0.00022516423,0.00005464597,0.00010241776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017042992,0.00008841147,0.00011954969,0.000078972706,0.00007589505,0.00010682493,0.00017377794,0.000028872942,0.0000036032118],"category_scores_gemma":[0.000054848428,0.00008230297,0.000026690677,0.00032263555,0.000026675734,0.00050826615,0.00006723724,0.000041974876,0.0000024124593],"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":[0.00003574755,0.0007390199,0.0042534964,0.00020834962,0.000081854305,0.000019380108,0.018164624,0.10225018,0.56219333,0.19352347,0.0004699778,0.11806059],"study_design_scores_gemma":[0.00023150598,0.00006627073,0.0007037981,0.000040089544,0.0000052864784,0.000029271141,0.00007844437,0.286654,0.7055999,0.006333791,0.00006963131,0.00018801549],"about_ca_topic_score_codex":0.00013008928,"about_ca_topic_score_gemma":0.0000040924983,"teacher_disagreement_score":0.46963593,"about_ca_system_score_codex":0.000036941346,"about_ca_system_score_gemma":0.000027300757,"threshold_uncertainty_score":0.33562177},"labels":[],"label_agreement":null},{"id":"W2544544579","doi":"10.1002/9780470487068.ch4","title":"Robustness Issues in Sensor Array Processing","year":2010,"lang":"en","type":"other","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Robustness (evolution); Computer science; Array processing; Real-time computing; Signal processing; Computer hardware; Digital signal processing; Biology","score_opus":0.013130256152049678,"score_gpt":0.28677460960662426,"score_spread":0.2736443534545746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2544544579","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":[0.0000037468228,0.000074485615,0.57514346,0.00014076912,0.00017740073,0.00012661425,6.393581e-7,0.00082767004,0.42350522],"genre_scores_gemma":[0.0002207077,0.000016036256,0.66961324,0.000026147898,0.0000611139,0.000017301167,0.0000013730139,0.000076836746,0.32996723],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99907804,0.000028538803,0.00022174114,0.0003139652,0.00021902716,0.00013866785],"domain_scores_gemma":[0.9992335,0.000019913517,0.0002083894,0.00044620765,0.000060048544,0.000031971274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015864542,0.00016192863,0.00025971216,0.00048555314,0.0000149218995,0.00008095814,0.0006219462,0.00025640117,0.00043727792],"category_scores_gemma":[0.000045710607,0.00014440967,0.000033896173,0.00040207474,0.000049736536,0.00019135293,0.00006578936,0.00020443765,0.0000166975],"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":[0.0000034224595,0.00029691216,0.0003229893,0.0009536591,0.000025373734,0.000017742108,0.00058894034,0.00027220818,0.005125052,0.01745483,0.3951658,0.57977307],"study_design_scores_gemma":[0.00038647678,0.000077016586,0.00022885192,0.0023756798,0.000013425868,0.000032599895,0.00003865205,0.06648609,0.17877121,0.0023958143,0.7477367,0.0014574856],"about_ca_topic_score_codex":0.00044097926,"about_ca_topic_score_gemma":0.00031474355,"teacher_disagreement_score":0.57831556,"about_ca_system_score_codex":0.000016633023,"about_ca_system_score_gemma":0.00007314058,"threshold_uncertainty_score":0.58888555},"labels":[],"label_agreement":null},{"id":"W2545819561","doi":"10.1109/acssc.2007.4487639","title":"Semi-Blind Adaptive Beamforming for Cyclostationary Signals: A Kalman Filtering Approach","year":2007,"lang":"en","type":"article","venue":"Conference record/Conference record - Asilomar Conference on Signals, Systems, & Computers","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Cyclostationary process; Beamforming; Kalman filter; Adaptive beamformer; Computer science; Extended Kalman filter; Algorithm; Autoencoder; Control theory (sociology); Mathematical optimization; Mathematics; Artificial intelligence; Telecommunications; Channel (broadcasting); Artificial neural network","score_opus":0.0937800095394437,"score_gpt":0.3137663560487998,"score_spread":0.2199863465093561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2545819561","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":[0.010130706,0.00010752647,0.96625763,0.0002920185,0.002587896,0.0038725731,0.00014886065,0.0012833319,0.015319426],"genre_scores_gemma":[0.65940124,0.00012981548,0.3388272,0.00014662613,0.00029888787,0.0005992241,0.0001268393,0.00010184877,0.00036834602],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98946255,0.0007290881,0.0033981141,0.0027379352,0.001708904,0.001963407],"domain_scores_gemma":[0.9884703,0.0023861744,0.0028586525,0.002022358,0.0033697349,0.00089275755],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0035337496,0.0015645698,0.0022910319,0.0018924297,0.00069849874,0.0013199915,0.0039546588,0.00072938506,0.000120006975],"category_scores_gemma":[0.00041021395,0.001632801,0.0006319385,0.0016285648,0.0004825187,0.0026307881,0.00073889317,0.0009988351,0.00008535905],"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":[0.0009096623,0.0008295106,0.0005548696,0.001062213,0.0005127576,0.00005440462,0.0024055117,0.0016795584,0.008315478,0.251658,0.0022372454,0.7297808],"study_design_scores_gemma":[0.002145343,0.0026863217,0.00039860484,0.0034958282,0.00010812205,0.00014267344,0.0018620021,0.95625365,0.0077482876,0.015966104,0.0067591425,0.002433898],"about_ca_topic_score_codex":0.0007644847,"about_ca_topic_score_gemma":0.000094368406,"teacher_disagreement_score":0.9545741,"about_ca_system_score_codex":0.0006174238,"about_ca_system_score_gemma":0.00167558,"threshold_uncertainty_score":0.99971676},"labels":[],"label_agreement":null},{"id":"W2545965423","doi":"10.1109/acssc.2010.5757574","title":"Robust adaptive beamforming via estimating steering vector based on semidefinite relaxation","year":2010,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Adaptive beamformer; Beamforming; Mathematical optimization; Covariance matrix; Computer science; Robustness (evolution); Quadratic programming; Control theory (sociology); Covariance; Algorithm; Mathematics; Artificial intelligence","score_opus":0.023034231488922273,"score_gpt":0.2395688154998602,"score_spread":0.21653458401093792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2545965423","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":[0.00774867,8.329774e-7,0.97854435,0.0001219428,0.0005220477,0.00017409181,9.994832e-7,0.00069457834,0.012192512],"genre_scores_gemma":[0.45367745,5.6412357e-8,0.5461854,0.00005696171,0.000022937611,0.0000149066345,0.0000014883268,0.0000075820367,0.000033239256],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987479,0.000036643043,0.00038212328,0.00030124738,0.00036448907,0.00016760896],"domain_scores_gemma":[0.9985793,0.000369752,0.0003105964,0.0005020673,0.00017715937,0.000061072795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006224912,0.00013948098,0.00015946467,0.0002357936,0.00011843324,0.0000878379,0.00040308942,0.000079179365,0.00006235578],"category_scores_gemma":[0.00047869456,0.0001305418,0.00006127036,0.00042689216,0.000030748997,0.0007337387,0.00008102617,0.00024123957,0.000027194528],"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":[0.000024180008,0.00018755057,0.00088765466,0.000072317656,0.000021404267,0.000004560105,0.00073568075,0.3440227,0.07805388,0.22830991,0.00034387852,0.3473363],"study_design_scores_gemma":[0.00009102929,0.00010135571,0.00089958863,0.00005819887,0.0000026682653,0.000003514398,0.0000048130805,0.8995773,0.09750682,0.0015733666,0.000052479576,0.00012884199],"about_ca_topic_score_codex":0.00008895021,"about_ca_topic_score_gemma":0.000017681268,"teacher_disagreement_score":0.5555546,"about_ca_system_score_codex":0.00004972803,"about_ca_system_score_gemma":0.000055500866,"threshold_uncertainty_score":0.532334},"labels":[],"label_agreement":null},{"id":"W2548913830","doi":"10.1109/acssc.2012.6488947","title":"Threshold performance for conditional and unconditional direction of arrival estimation","year":2012,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Estimation; Computer science; Statistics; Econometrics; Algorithm; Mathematics; Engineering","score_opus":0.01865755257547675,"score_gpt":0.2755922569886188,"score_spread":0.25693470441314203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2548913830","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":[0.10680894,0.000020693913,0.8896644,0.000106222855,0.00016862509,0.00019895552,0.00002055824,0.00013736422,0.0028742603],"genre_scores_gemma":[0.7686612,0.0000035033238,0.23111553,0.000030287507,0.000028783852,0.000044822827,0.000047980255,0.000003546853,0.000064330765],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993055,0.000011451677,0.00024233601,0.000120014236,0.00020782751,0.00011291286],"domain_scores_gemma":[0.99939555,0.00010731474,0.00015915076,0.00012807449,0.00017045514,0.00003947888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029560426,0.00007516796,0.00011393522,0.00013536963,0.000069679416,0.000016281812,0.000117273106,0.00004262716,0.000031278236],"category_scores_gemma":[0.000055574088,0.00007206411,0.000036715166,0.00015629479,0.00007149571,0.0013235116,0.000038751066,0.00003447815,0.000002484634],"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":[0.00001811892,0.00016665984,0.01804937,0.00015722458,0.000028015755,3.319503e-8,0.0002034309,0.00086485804,0.0039129443,0.9397614,0.0032278846,0.033610046],"study_design_scores_gemma":[0.0004119802,0.00021134947,0.14118183,0.000042157793,0.000015173782,0.000026261057,0.000009776848,0.44119897,0.3665238,0.049495496,0.00069565745,0.00018752924],"about_ca_topic_score_codex":0.0000060074517,"about_ca_topic_score_gemma":5.370659e-7,"teacher_disagreement_score":0.89026594,"about_ca_system_score_codex":0.000024475426,"about_ca_system_score_gemma":0.00003192457,"threshold_uncertainty_score":0.29386893},"labels":[],"label_agreement":null},{"id":"W2558353860","doi":"10.1109/iemcon.2016.7746238","title":"Direction of Arrival algorithms for user identification in cellular networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Algorithm; Direction of arrival; Computer science; Angle of arrival; SIGNAL (programming language); Transmitter; Interference (communication); Identification (biology); Multiple signal classification; Projection (relational algebra); Telecommunications; Antenna (radio)","score_opus":0.01748276120721316,"score_gpt":0.2711198178736047,"score_spread":0.2536370566663915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2558353860","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":[0.0075628217,0.000015552141,0.9909989,0.00017793512,0.00034665846,0.00026217368,0.0000014528998,0.00016508148,0.00046942968],"genre_scores_gemma":[0.85284257,0.000013314059,0.14644037,0.000009212551,0.000025615167,0.000058424954,0.0000012687947,0.00000609431,0.0006031251],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99914026,0.00003685968,0.00037198063,0.00020475729,0.0001407483,0.00010537339],"domain_scores_gemma":[0.99917036,0.00014117445,0.00018855432,0.00030692725,0.00016983156,0.000023141378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047082052,0.000065783024,0.00012246425,0.00017770678,0.00002033535,0.000018352186,0.00028642514,0.000056883786,0.000010485391],"category_scores_gemma":[0.00009337963,0.000050450577,0.000052270516,0.00033908855,0.00003226326,0.0005272822,0.000043668846,0.000024322559,0.0000025705197],"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":[0.00001712091,0.00017281866,0.0023164426,0.000042237305,0.0000164774,3.4289127e-7,0.00015145267,0.00054469594,0.2611502,0.12470814,0.0011357279,0.6097443],"study_design_scores_gemma":[0.00022714755,0.000055475004,0.0067927684,0.00005027162,0.000003179554,7.048248e-7,0.0000038577787,0.17428064,0.8084319,0.009557178,0.0005064297,0.00009039279],"about_ca_topic_score_codex":0.00005951908,"about_ca_topic_score_gemma":0.000009392854,"teacher_disagreement_score":0.84527975,"about_ca_system_score_codex":0.00004097617,"about_ca_system_score_gemma":0.000019831816,"threshold_uncertainty_score":0.20573148},"labels":[],"label_agreement":null},{"id":"W2566194199","doi":"10.1109/oceans.2016.7761145","title":"Compression-Aided Kalman Filter for recursive Bayesian estimation of sparse wideband channels in OFDM systems","year":2016,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ultra Electronics (Canada)","funders":"","keywords":"Kalman filter; Computer science; Orthogonal frequency-division multiplexing; Bayesian probability; Recursive Bayesian estimation; Compression (physics); Wideband; Data compression; Algorithm; Electronic engineering; Artificial intelligence; Channel (broadcasting); Telecommunications; Engineering","score_opus":0.02397331628498245,"score_gpt":0.2807376276157015,"score_spread":0.25676431133071903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2566194199","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":[0.0061338693,0.000021373367,0.99095935,0.0005080551,0.00036827635,0.00067381095,0.000008211399,0.00014456952,0.0011825153],"genre_scores_gemma":[0.85549337,0.0000046486207,0.14396724,0.000026043992,0.000015494126,0.000110053894,0.0000025866182,0.000008143142,0.00037240464],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878114,0.00007429555,0.0005094485,0.0002604686,0.00021516663,0.00015950057],"domain_scores_gemma":[0.9986335,0.00040270147,0.00030636074,0.00040013014,0.00020635784,0.00005093582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003749381,0.00011676815,0.00026874078,0.00028049288,0.00003001018,0.000029823945,0.00040288467,0.00007315351,0.000017371998],"category_scores_gemma":[0.00023821347,0.00008169638,0.00005592282,0.00026392256,0.00005117031,0.0006983095,0.00007582936,0.00003171119,0.000004205312],"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":[0.00020043891,0.00069026666,0.0023032995,0.0010526001,0.00009288246,0.000006121929,0.0030035865,0.018106906,0.059902687,0.58918154,0.03488756,0.29057214],"study_design_scores_gemma":[0.00068727846,0.0002069001,0.00047556104,0.0010667605,0.0000055023984,0.0000052813266,0.000019163133,0.5346303,0.42899287,0.033469055,0.00026086366,0.00018043889],"about_ca_topic_score_codex":0.00014757834,"about_ca_topic_score_gemma":0.000008539066,"teacher_disagreement_score":0.8493595,"about_ca_system_score_codex":0.00004942877,"about_ca_system_score_gemma":0.000041565523,"threshold_uncertainty_score":0.33314818},"labels":[],"label_agreement":null},{"id":"W2574838513","doi":"10.1109/icces.2016.7822052","title":"Analysis of different GNSS array processing methods utilizing new experimental approach using a Spirent simulator and single frontend receiver","year":2016,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada; Queen's University","funders":"","keywords":"GNSS applications; Beamforming; Computer science; Antenna array; GPS signals; Emulation; Planar array; Satellite system; Electronic engineering; Global Positioning System; Satellite navigation; Antenna (radio); Engineering; Assisted GPS; Telecommunications","score_opus":0.08447133779353946,"score_gpt":0.3654432949848952,"score_spread":0.2809719571913557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2574838513","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":[0.12042191,0.00014584333,0.8781417,0.000024454614,0.000047732836,0.0001247312,8.182821e-7,0.00012996721,0.00096281414],"genre_scores_gemma":[0.53831303,0.0000015365586,0.46162838,0.000008032409,0.0000060086118,0.0000025113436,3.00496e-7,0.0000050190674,0.000035171546],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99867755,0.00012644038,0.00039922452,0.00038871903,0.00024831312,0.00015973274],"domain_scores_gemma":[0.99908686,0.0001258949,0.00027627262,0.0003174769,0.00009630618,0.00009716992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029671393,0.00015698525,0.00039957493,0.00038862214,0.000058167992,0.00006485411,0.00027256168,0.000052458345,0.000025364938],"category_scores_gemma":[0.00007065287,0.00010467491,0.00011108537,0.0006078281,0.00008287578,0.00057681167,0.00014438825,0.00003590907,1.5494223e-7],"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":[0.000008542065,0.00020484938,0.0016393078,0.00002607905,0.00014433877,1.8949252e-7,0.0010561111,0.00015151461,0.7202346,0.0012700576,0.00000633337,0.2752581],"study_design_scores_gemma":[0.00014304514,0.00004698252,0.0007479112,0.000058849673,0.000078232464,0.0000014623487,0.00008999664,0.32964167,0.66876817,0.00029992286,0.00001251792,0.00011122481],"about_ca_topic_score_codex":0.0001035731,"about_ca_topic_score_gemma":0.0000026351163,"teacher_disagreement_score":0.41789114,"about_ca_system_score_codex":0.00010158448,"about_ca_system_score_gemma":0.00004003048,"threshold_uncertainty_score":0.4268519},"labels":[],"label_agreement":null},{"id":"W2594179527","doi":"","title":"Penalty function based 2D adaptive digital beamforming for satellite communications","year":2002,"lang":"en","type":"article","venue":"International Symposium on Antenna Technology and Applied Electromagnetics","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Communications Research Centre Canada; University of Calgary","funders":"","keywords":"Beamforming; Adaptive beamformer; Computer science; Smart antenna; Jitter; Communications satellite; WSDMA; Antenna (radio); Algorithm; Electronic engineering; Adaptive filter; Satellite; Telecommunications; Directional antenna; Engineering; MIMO; Precoding","score_opus":0.015473796181896442,"score_gpt":0.2354576154054519,"score_spread":0.21998381922355545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594179527","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":[0.0059982953,0.0002327207,0.96623445,0.008219377,0.00014930427,0.00051598524,0.00002405773,0.0007014064,0.017924406],"genre_scores_gemma":[0.9062943,0.00023514782,0.09287657,0.0002456178,0.000016521604,0.0001392937,0.000018706252,0.000011775054,0.00016206068],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901533,0.00000925443,0.00029898123,0.00030354477,0.00017913624,0.00019374647],"domain_scores_gemma":[0.9989472,0.00017028823,0.00018725429,0.0004618214,0.00019658623,0.000036854377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009942588,0.00015222089,0.00015579662,0.00041219074,0.0001509369,0.00008019162,0.00081623124,0.00014550422,0.000007126191],"category_scores_gemma":[0.000040660667,0.0001574973,0.000052983927,0.00043658746,0.00021814967,0.00020990527,0.00014289664,0.00018944839,0.000010705151],"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":[0.00005050405,0.00021970924,0.000104107035,0.000008227674,0.0000366155,3.7334112e-7,0.00004396912,0.00001490073,0.06436164,0.8082451,0.0000642177,0.1268506],"study_design_scores_gemma":[0.0015271908,0.0036923655,0.00049840385,0.00010900608,0.000049708568,0.000052496696,0.00006522692,0.6590558,0.17103842,0.13184582,0.03142311,0.0006424046],"about_ca_topic_score_codex":0.0000012784026,"about_ca_topic_score_gemma":0.0000017981283,"teacher_disagreement_score":0.90029603,"about_ca_system_score_codex":0.000052434083,"about_ca_system_score_gemma":0.000013603929,"threshold_uncertainty_score":0.64225537},"labels":[],"label_agreement":null},{"id":"W2594400359","doi":"10.1109/antem.2004.7860594","title":"Adaptive array algorithm performance: Case studies in different environments","year":2004,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","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":"Communications Research Centre Canada","funders":"Defence Research and Development Canada","keywords":"Computer science; Algorithm; Channel (broadcasting); Least mean squares filter; Inversion (geology); Performance improvement; Algorithm design; Recursive least squares filter; Adaptive filter; Telecommunications; Engineering","score_opus":0.03727462493961454,"score_gpt":0.2937347893287155,"score_spread":0.25646016438910096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594400359","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":[0.15927418,0.000035135003,0.83927524,0.00006243518,0.00013430524,0.00014968593,7.898306e-7,0.000111156696,0.00095706026],"genre_scores_gemma":[0.76382005,0.00005594974,0.23595767,0.000027081127,0.000009086931,0.00003011178,2.6191827e-7,0.0000032950618,0.00009651589],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99926084,0.000022213926,0.0002107111,0.00019840445,0.0001804602,0.0001273465],"domain_scores_gemma":[0.99962205,0.000034192704,0.00006579445,0.0002286251,0.00001698967,0.0000323433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010882665,0.00010584446,0.00015278142,0.00012631055,0.000045036846,0.000012371528,0.00019741975,0.000028075749,0.000006517421],"category_scores_gemma":[0.000011325111,0.00008190108,0.000027723512,0.00014378352,0.00007210421,0.00040765412,0.000103848804,0.00006898395,0.0000136700455],"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":[0.000012290596,0.0010204274,0.0014771532,0.00007361184,0.00012270406,0.0005504265,0.009454331,0.0030112967,0.0027706465,0.016956512,0.00017858266,0.96437204],"study_design_scores_gemma":[0.00080842536,0.0005332604,0.004890468,0.00014013519,0.000007899624,0.00048114063,0.00052464154,0.03862443,0.94096,0.012584561,0.00009650381,0.00034854963],"about_ca_topic_score_codex":0.000054302713,"about_ca_topic_score_gemma":0.000009218988,"teacher_disagreement_score":0.9640235,"about_ca_system_score_codex":0.0001689756,"about_ca_system_score_gemma":0.000014388488,"threshold_uncertainty_score":0.3339829},"labels":[],"label_agreement":null},{"id":"W2596829020","doi":"10.1109/twc.2017.2669026","title":"Code-Aided DOA Estimation From Turbo-Coded QAM Transmissions: Analytical CRLBs and Maximum Likelihood Estimator","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Canada Research Chairs","keywords":"Turbo code; Computer science; Estimator; Algorithm; Beamforming; Turbo; QAM; Direction of arrival; Turbo equalizer; Cramér–Rao bound; Quadrature amplitude modulation; Estimation theory; Decoding methods; Statistics; Mathematics; Bit error rate; Concatenated error correction code; Telecommunications; Block code; Engineering","score_opus":0.03465749232128381,"score_gpt":0.31537831630717666,"score_spread":0.2807208239858929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2596829020","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":[0.009924381,0.00008733412,0.98025596,0.0074558114,0.0002504987,0.00049542246,0.00019690563,0.0006609514,0.0006727443],"genre_scores_gemma":[0.69684845,0.0003242183,0.3025128,0.00006665635,0.000008478713,0.00014997464,0.000014248002,0.000025399184,0.000049808845],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99771154,0.00022526897,0.00074663176,0.00056308636,0.00044515837,0.00030830974],"domain_scores_gemma":[0.99349964,0.0007511025,0.00044828327,0.0047415732,0.00029067582,0.00026872125],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00038052798,0.00032471147,0.00046249054,0.0003524231,0.0018038613,0.00039214065,0.003008609,0.0002219342,0.000037174508],"category_scores_gemma":[0.000088092005,0.00033652713,0.00018216946,0.00035222652,0.0005170674,0.0014835228,0.000051685576,0.000538512,0.000035553745],"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":[0.00007167456,0.0014532254,0.000107451895,0.000073873816,0.00024098097,0.0000042166935,0.0013843755,0.0035892292,0.0057000304,0.020875493,0.00039540243,0.96610403],"study_design_scores_gemma":[0.00069509743,0.00010328321,0.0013233704,0.00028919464,0.00010720232,0.000011688253,0.000033321285,0.9186924,0.05339063,0.024707468,0.00027782796,0.0003684893],"about_ca_topic_score_codex":0.000634641,"about_ca_topic_score_gemma":0.00024855233,"teacher_disagreement_score":0.96573555,"about_ca_system_score_codex":0.00012324263,"about_ca_system_score_gemma":0.00018033538,"threshold_uncertainty_score":0.9999087},"labels":[],"label_agreement":null},{"id":"W2606059557","doi":"10.1016/j.jfranklin.2017.04.004","title":"Direction of arrival tracking for signals with known waveforms based on block least squares techniques","year":2017,"lang":"en","type":"article","venue":"Journal of the Franklin Institute","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Concordia University","funders":"","keywords":"Least-squares function approximation; Algorithm; Block (permutation group theory); Waveform; Sensor array; Computer science; Direction of arrival; QR decomposition; Total least squares; Tracking (education); Antenna array; Non-linear least squares; Mathematics; Estimation theory; Antenna (radio); Estimator; Statistics; Singular value decomposition; Telecommunications","score_opus":0.024631157177232358,"score_gpt":0.2896053300689138,"score_spread":0.26497417289168146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606059557","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":[0.051249266,0.000031589894,0.9431528,0.0013208261,0.0013378029,0.0006271296,0.00000909859,0.00010375172,0.002167734],"genre_scores_gemma":[0.88657534,0.0000095762425,0.11314661,0.000050623625,0.00014360718,0.000018102788,2.1940073e-7,0.000011077636,0.00004487051],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985228,0.00004735629,0.00059710426,0.0001541821,0.0005345355,0.00014399202],"domain_scores_gemma":[0.99664795,0.00011424444,0.0018347172,0.0006788041,0.00067112653,0.000053137897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094973645,0.00015450947,0.0003451065,0.00025701185,0.00035321142,0.00014015152,0.001426423,0.00008291778,0.0000025454083],"category_scores_gemma":[0.0004956676,0.00009186465,0.00025439434,0.00017078556,0.0002240399,0.0011876062,0.00007787139,0.0002179704,4.067577e-7],"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":[0.0016248398,0.0015595432,0.0065613263,0.0007624839,0.00047283492,0.000026070342,0.0011821447,0.054967433,0.12445741,0.024701647,0.002504698,0.78117955],"study_design_scores_gemma":[0.00068666553,0.0011230168,0.0060729356,0.0016063097,0.000054850476,0.00006009255,0.000008355238,0.029285401,0.9524991,0.004667453,0.0037578945,0.00017790812],"about_ca_topic_score_codex":0.00004563,"about_ca_topic_score_gemma":0.000016338834,"teacher_disagreement_score":0.8353261,"about_ca_system_score_codex":0.000068121255,"about_ca_system_score_gemma":0.00020598853,"threshold_uncertainty_score":0.37461317},"labels":[],"label_agreement":null},{"id":"W2606620875","doi":"10.1109/isivc.2016.7893998","title":"Performance analysis of 2-D DOA estimation using L-shaped array in scattered channel","year":2016,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Azimuth; Direction of arrival; Channel (broadcasting); Computer science; Context (archaeology); Algorithm; Constant (computer programming); Elevation (ballistics); Electronic engineering; Telecommunications; Physics; Mathematics; Optics; Engineering; Antenna (radio); Geology; Geometry","score_opus":0.0290757926262251,"score_gpt":0.2857080625180693,"score_spread":0.2566322698918442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606620875","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":[0.27529493,0.0000022427698,0.7238699,0.00009985557,0.00003523878,0.00006648304,0.0000010114686,0.00007886397,0.00055144745],"genre_scores_gemma":[0.79788715,0.000004162941,0.2020467,0.00001706951,0.0000028342083,0.000005620898,7.726806e-7,0.0000028578304,0.00003280054],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990934,0.000032987224,0.00036327806,0.00018805762,0.00019928672,0.00012299725],"domain_scores_gemma":[0.99923724,0.00006614933,0.00021294793,0.00033712748,0.000121482124,0.00002504034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033392315,0.00007672672,0.0002116275,0.0008145026,0.000023196186,0.000014701122,0.0003182364,0.00003730426,0.00003515605],"category_scores_gemma":[0.00005685394,0.000056662004,0.000060958104,0.0016359778,0.000039283044,0.0007962598,0.000055787372,0.000023624347,0.0000040704476],"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":[0.000030098496,0.00032960722,0.05062785,0.0001505619,0.0003163715,0.0000010139423,0.0016723403,0.057250667,0.5811091,0.009191655,0.000045716555,0.29927504],"study_design_scores_gemma":[0.00008748048,0.000020388086,0.024650963,0.00005569713,0.000019669735,5.3703565e-7,0.0000029156545,0.776997,0.19764943,0.00045285124,0.0000011188239,0.00006189845],"about_ca_topic_score_codex":0.00011696073,"about_ca_topic_score_gemma":0.000012614688,"teacher_disagreement_score":0.71974635,"about_ca_system_score_codex":0.00005464644,"about_ca_system_score_gemma":0.000032369888,"threshold_uncertainty_score":0.23106094},"labels":[],"label_agreement":null},{"id":"W2625740259","doi":"10.1109/radar.2017.7944342","title":"Low-complexity 2D root-MUSIC pairing for an L-shaped array","year":2017,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Pairing; Algorithm; Computer science; Computational complexity theory; Maxima and minima; Direction of arrival; SIGNAL (programming language); Statistic; Multiple signal classification; Noise (video); Key (lock); Polynomial; Colors of noise; Speech recognition; Mathematics; Artificial intelligence; Statistics; Telecommunications; Mathematical analysis; Image (mathematics); Physics; Noise reduction","score_opus":0.10644468647200771,"score_gpt":0.337415981795783,"score_spread":0.2309712953237753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2625740259","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":[0.025772544,0.000002195019,0.9588057,0.00029504125,0.00029072643,0.00027528923,0.000002210319,0.00065901055,0.013897322],"genre_scores_gemma":[0.6772637,2.8733788e-7,0.32243255,0.00006145269,0.00004113877,0.000029129307,0.0000013062614,0.0000065414074,0.00016393146],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999097,0.000024801151,0.00021801027,0.00030556234,0.00017345329,0.00018120735],"domain_scores_gemma":[0.9983738,0.000060486243,0.0002111221,0.0011144412,0.00016266333,0.00007750623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038470092,0.0001061457,0.00015861662,0.000077469274,0.00035400272,0.000306249,0.0013134279,0.000046043413,0.00003720042],"category_scores_gemma":[0.00018546579,0.00009904816,0.00007279263,0.00006522435,0.000089576555,0.0014293736,0.00014908085,0.000052604508,0.000013971036],"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":[0.000022683053,0.00038646272,0.0029609108,0.00018715629,0.000029074276,0.0000015564806,0.0009699724,0.000046137993,0.0807028,0.60662365,0.003468274,0.30460134],"study_design_scores_gemma":[0.00040157256,0.00027182957,0.032018192,0.00006566026,0.0000075235057,0.000004607763,0.00001538045,0.20629027,0.5841831,0.17513578,0.0012419609,0.0003641363],"about_ca_topic_score_codex":0.00015175575,"about_ca_topic_score_gemma":0.00021176573,"teacher_disagreement_score":0.6514911,"about_ca_system_score_codex":0.000025995727,"about_ca_system_score_gemma":0.000042086216,"threshold_uncertainty_score":0.40390667},"labels":[],"label_agreement":null},{"id":"W2627024661","doi":"10.1109/radar.2017.7944160","title":"Joint diagonalization based 2D DOA estimation for mixed circular and strictly noncircular sources","year":2017,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Joint (building); Direction of arrival; Algorithm; Ambiguity; Computer science; Mathematics; Telecommunications; Engineering; Antenna (radio)","score_opus":0.028718910384298014,"score_gpt":0.27814836901032663,"score_spread":0.2494294586260286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2627024661","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":[0.020371258,0.000030187723,0.9777209,0.00047569894,0.00013728299,0.0004151554,0.0000037400782,0.00026681102,0.0005789391],"genre_scores_gemma":[0.66411656,0.0000034714662,0.3357016,0.000074264484,0.000012848924,0.000054913748,0.00000838165,0.0000070664723,0.000020896228],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990298,0.000035216122,0.0002727327,0.00028640474,0.00024753925,0.00012828855],"domain_scores_gemma":[0.998657,0.00009813602,0.00033471943,0.0006027431,0.00024715293,0.000060276136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044330556,0.000114115224,0.0001676654,0.00015504472,0.00032714286,0.0003579209,0.00040837805,0.00006670252,0.000008212987],"category_scores_gemma":[0.0005783008,0.000109984416,0.00006508589,0.00010168986,0.00007158534,0.00087923685,0.00008844325,0.00003517951,0.0000025095242],"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":[0.000023615747,0.0003933513,0.008230777,0.00092874205,0.000117929994,0.0000053859103,0.00089433,0.023724684,0.035638,0.41721335,0.0022007297,0.5106291],"study_design_scores_gemma":[0.00027585914,0.000053261774,0.010687978,0.00003547165,0.000012105055,0.0000021467351,0.000004501232,0.83734924,0.13923533,0.011897833,0.00032190103,0.00012435099],"about_ca_topic_score_codex":0.000077443525,"about_ca_topic_score_gemma":0.000004627741,"teacher_disagreement_score":0.81362456,"about_ca_system_score_codex":0.00003318297,"about_ca_system_score_gemma":0.000067705056,"threshold_uncertainty_score":0.44850343},"labels":[],"label_agreement":null},{"id":"W2740579037","doi":"10.1121/1.4995993","title":"Beamforming using subspace estimation from a diagonally averaged sample covariance","year":2017,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Naval Sea Systems Command; Office of Naval Research","keywords":"Covariance matrix; Beamforming; Estimator; Algorithm; Mathematics; Covariance; Toeplitz matrix; Signal subspace; Projector; Subspace topology; Computer science; Covariance intersection; Estimation of covariance matrices; Noise (video); Statistics; Artificial intelligence; Mathematical analysis","score_opus":0.023704831646235505,"score_gpt":0.2912815630912919,"score_spread":0.2675767314450564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2740579037","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":[0.016755892,0.000038408267,0.980276,0.002551988,0.0002223842,0.00009159109,0.0000081521675,0.00001955147,0.000036021927],"genre_scores_gemma":[0.4145741,0.000039142367,0.58516854,0.0001678139,0.000040042487,4.117205e-7,1.365347e-7,0.000004687721,0.000005130001],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986604,0.00011672261,0.00043569945,0.00009315523,0.00054835354,0.00014569578],"domain_scores_gemma":[0.99621886,0.0011103677,0.0016438158,0.0006797736,0.00029438475,0.000052824947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008151612,0.00010496573,0.0002846519,0.000017972838,0.0004789565,0.000084261665,0.0018575605,0.000049704653,0.000010894957],"category_scores_gemma":[0.0015660146,0.00006408099,0.00025483622,0.00015895304,0.00047545644,0.00057978526,0.0003810858,0.00027752935,7.907737e-7],"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":[0.00020632615,0.00046680385,0.0014684905,0.00013843362,0.00070809,0.0000025112436,0.010291032,0.48744214,0.19791399,0.0010785783,0.0067018117,0.2935818],"study_design_scores_gemma":[0.00015795519,0.000068258414,0.0029131346,0.00014766496,0.00008074248,0.000015596897,0.000084296415,0.96615195,0.014503987,0.015718725,0.000084207764,0.000073504125],"about_ca_topic_score_codex":0.000636639,"about_ca_topic_score_gemma":0.0000010074691,"teacher_disagreement_score":0.47870982,"about_ca_system_score_codex":0.000077174474,"about_ca_system_score_gemma":0.00015396385,"threshold_uncertainty_score":0.36837947},"labels":[],"label_agreement":null},{"id":"W2756554878","doi":"10.1109/mwscas.2017.8053059","title":"Compressive sensing-based DOA estimation using the Dantzig selector","year":2017,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Lasso (programming language); Compressed sensing; Constraint (computer-aided design); Direction of arrival; Algorithm; A priori and a posteriori; Computer science; Scheme (mathematics); Computational complexity theory; Mathematical optimization; Mathematics; Telecommunications","score_opus":0.03810606477218101,"score_gpt":0.324761516132251,"score_spread":0.28665545136007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756554878","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":[0.011382907,0.0000047175636,0.98436415,0.00066586083,0.00021173377,0.000173857,9.134501e-7,0.00029759426,0.002898237],"genre_scores_gemma":[0.5882096,2.3599556e-7,0.4116623,0.000079196805,0.000012460493,0.0000014793168,5.3752075e-7,0.00000389285,0.000030261297],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999214,0.00005706478,0.0001844215,0.00018487942,0.0002377147,0.000121928846],"domain_scores_gemma":[0.99835765,0.00013345941,0.00033777094,0.0009173859,0.00022206517,0.000031647764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023645858,0.00009343308,0.00011578133,0.0000670564,0.0005156676,0.0003631352,0.00078570825,0.000037429312,0.000009680994],"category_scores_gemma":[0.00023572157,0.00006633857,0.000045094792,0.00011266462,0.00011993551,0.0006207576,0.0001414246,0.000072052775,0.000006734516],"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":[0.00005381351,0.00031438452,0.0025468045,0.00019551549,0.00012772516,0.000022987324,0.0017177776,0.14615797,0.11403583,0.18554181,0.007332442,0.54195297],"study_design_scores_gemma":[0.0000681086,0.00001512993,0.00090378424,0.000033780037,0.0000043439145,0.0000051589845,0.000002193568,0.7445612,0.2520157,0.0022634754,0.000063694264,0.00006343314],"about_ca_topic_score_codex":0.00038104408,"about_ca_topic_score_gemma":0.000017443353,"teacher_disagreement_score":0.5984032,"about_ca_system_score_codex":0.00003615908,"about_ca_system_score_gemma":0.00009299926,"threshold_uncertainty_score":0.39661503},"labels":[],"label_agreement":null},{"id":"W2762131880","doi":"10.1155/2017/3265236","title":"Adaptive Antenna Null Broadening Beamforming against Array Calibration Error Based on Adaptive Variable Diagonal Loading","year":2017,"lang":"en","type":"article","venue":"International Journal of Antennas and Propagation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Fundamental Research Funds for the Central Universities","keywords":"Covariance matrix; Diagonal; Robustness (evolution); Beamforming; Sample mean and sample covariance; Null (SQL); Algorithm; Adaptive beamformer; Computer science; Mathematics; Control theory (sociology); Statistics; Artificial intelligence; Data mining; Chemistry; Estimator","score_opus":0.026266750911277177,"score_gpt":0.2818437774938255,"score_spread":0.25557702658254833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762131880","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":[0.0128823025,0.000036242738,0.98394156,0.0009612373,0.0007863932,0.00013912005,0.0000096445165,0.00003762541,0.0012058576],"genre_scores_gemma":[0.8792763,0.000030311348,0.1203194,0.00015367265,0.00017703259,0.0000050602707,0.0000045858305,0.00000990273,0.000023739212],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983372,0.00007295712,0.0005628873,0.00021407566,0.00067377015,0.0001390785],"domain_scores_gemma":[0.9971452,0.00015668203,0.0014614299,0.00020584793,0.0009505631,0.00008027806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071708916,0.00015288126,0.0002191002,0.00038164845,0.0002618379,0.00037985417,0.00071620796,0.000071991315,0.000008096285],"category_scores_gemma":[0.00044625715,0.00013410237,0.00009052743,0.00010325653,0.000093911374,0.002605989,0.0000781414,0.00022044845,0.0000012033869],"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":[0.0025841042,0.0009496647,0.01377371,0.00011482417,0.00071610336,0.00021269912,0.0042528645,0.01564939,0.45543295,0.16374715,0.0005650768,0.34200147],"study_design_scores_gemma":[0.00065394165,0.00053997344,0.003571442,0.0008934644,0.000015043289,0.000063542364,0.00007769781,0.93562025,0.052355144,0.005928656,0.00010561837,0.00017524463],"about_ca_topic_score_codex":0.000039167706,"about_ca_topic_score_gemma":0.000002989319,"teacher_disagreement_score":0.91997087,"about_ca_system_score_codex":0.00011113927,"about_ca_system_score_gemma":0.00017759147,"threshold_uncertainty_score":0.5468536},"labels":[],"label_agreement":null},{"id":"W2774730835","doi":"10.1109/iemcon.2017.8117125","title":"Optimum scheduling based on beamforming for the fifth generation of mobile communication systems","year":2017,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Beamforming; Scheduling (production processes); Smart antenna; Algorithm; Wireless; Real-time computing; Mobile telephony; Exploit; Rate of convergence; Mathematical optimization; Computer engineering; Mobile radio; Telecommunications; Directional antenna; Mathematics","score_opus":0.06570484625657469,"score_gpt":0.33054914288558074,"score_spread":0.26484429662900605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2774730835","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":[0.00448912,0.00003996321,0.9930587,0.0002417844,0.00017304928,0.00053854735,0.0000019230831,0.00008938496,0.0013675325],"genre_scores_gemma":[0.6234914,0.000006168186,0.3762978,0.000018081499,0.00001376888,0.00013266722,0.0000024471028,0.0000031619566,0.00003448418],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939483,0.000031318912,0.00024011848,0.00011081853,0.00015616452,0.00006673854],"domain_scores_gemma":[0.99791545,0.0002756218,0.0003782241,0.0011990641,0.00021707472,0.000014575405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007065379,0.000058107573,0.000100981124,0.00006051088,0.00038529167,0.00015898976,0.00091769465,0.000034570705,0.0000025504996],"category_scores_gemma":[0.00017466527,0.000042124517,0.00004490578,0.000055562476,0.000045879602,0.00044692837,0.00008331898,0.00004048255,0.0000010852281],"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":[0.000009984588,0.00010473231,0.00013402173,0.00008685574,0.00001946462,4.124818e-8,0.0004461231,0.69875735,0.01005236,0.22309655,0.00032965184,0.066962875],"study_design_scores_gemma":[0.00009745173,0.00007638825,0.00006170192,0.000056887242,0.0000039179977,2.574126e-7,0.000018458051,0.91604435,0.08303641,0.00023722812,0.00032454834,0.000042378197],"about_ca_topic_score_codex":0.00014804583,"about_ca_topic_score_gemma":0.0000056802974,"teacher_disagreement_score":0.6190023,"about_ca_system_score_codex":0.00002385964,"about_ca_system_score_gemma":0.000040860028,"threshold_uncertainty_score":0.2963391},"labels":[],"label_agreement":null},{"id":"W2785535958","doi":"10.1109/pimrc.2017.8292640","title":"ML time delay estimation for 5G links with DSSS multi-carrier multipath MIMO radio access","year":2017,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Multipath propagation; MIMO; Cramér–Rao bound; Delay spread; Algorithm; Initialization; Electronic engineering; Channel (broadcasting); Estimation theory; Telecommunications; Engineering","score_opus":0.03704503892336109,"score_gpt":0.3347330389934566,"score_spread":0.2976880000700955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785535958","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":[0.0043330956,0.000008506538,0.991028,0.00040554607,0.00019112806,0.00073693076,0.000009973298,0.0006068381,0.0026799776],"genre_scores_gemma":[0.36494768,0.0000018762455,0.6339494,0.00006815955,0.000024823183,0.000120724406,0.0000064178644,0.000016431579,0.0008644827],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987149,0.00002671896,0.0003175661,0.00042961523,0.000279011,0.00023214756],"domain_scores_gemma":[0.997791,0.00013939707,0.0004208924,0.0011474262,0.00039585168,0.000105445295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003903893,0.00018877129,0.00024784458,0.00014705848,0.00038646773,0.00063109875,0.0016750211,0.00015647824,0.000030430376],"category_scores_gemma":[0.00035053844,0.00015296745,0.000076504715,0.00012844175,0.00011256346,0.0025506814,0.00015477919,0.00013150815,0.000021723818],"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":[0.00042110926,0.00095069467,0.008079557,0.00043802365,0.00028811942,0.000021233056,0.0021053206,0.014349742,0.005303564,0.040446866,0.018013922,0.90958184],"study_design_scores_gemma":[0.0006902874,0.00023793991,0.0041989675,0.000064726526,0.000012758484,0.000009543133,0.0000016631087,0.89978707,0.0933623,0.000944382,0.0004707747,0.0002195661],"about_ca_topic_score_codex":0.00022772719,"about_ca_topic_score_gemma":0.000058414847,"teacher_disagreement_score":0.90936226,"about_ca_system_score_codex":0.00005094097,"about_ca_system_score_gemma":0.000104962644,"threshold_uncertainty_score":0.6237832},"labels":[],"label_agreement":null},{"id":"W2792713580","doi":"10.1016/j.dsp.2018.03.012","title":"Computationally efficient direction of arrival estimation with unknown number of signals","year":2018,"lang":"en","type":"article","venue":"Digital Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":10,"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":"Fundamental Research Funds for the Central Universities; University of Waterloo; Harbin Institute of Technology; National Natural Science Foundation of China","keywords":"Capon; Beamforming; Estimator; Algorithm; Covariance matrix; Rank (graph theory); Direction of arrival; Computer science; SIGNAL (programming language); Minimum-variance unbiased estimator; Covariance; Mathematics; Inverse; Mathematical optimization; Statistics; Telecommunications; Combinatorics","score_opus":0.01028088772318838,"score_gpt":0.27237466713724534,"score_spread":0.262093779414057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792713580","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":[0.09693323,0.00001350808,0.8942374,0.000027182512,0.000032748216,0.00013542874,0.000005055732,0.0001514668,0.0084639955],"genre_scores_gemma":[0.90852976,1.8794572e-7,0.09138828,0.00000913992,0.000021935053,0.0000061376236,0.0000071762965,0.000010261492,0.000027136706],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854374,0.000025987069,0.00048526193,0.0002460087,0.0005658079,0.00013318974],"domain_scores_gemma":[0.99812806,0.00009799252,0.00059222244,0.00014198106,0.0009925088,0.000047220125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021361418,0.00013235582,0.0002278518,0.00015596254,0.000075938755,0.00011339814,0.00027596398,0.000045666424,0.000014560751],"category_scores_gemma":[0.000064046464,0.00011638986,0.000050937102,0.0007829823,0.00026251748,0.0010350025,0.00006688368,0.000054915516,0.0000060477314],"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":[0.000073846706,0.00037835242,0.0012799583,0.00028436282,0.00003483915,0.0000011098224,0.0010316558,0.034444254,0.008547354,0.0077843745,0.000038794235,0.94610107],"study_design_scores_gemma":[0.00018401182,0.00024965577,0.0016634486,0.00038920005,0.000009322251,0.00001863581,0.000015204474,0.84054345,0.15044954,0.006316464,0.000025388399,0.00013567053],"about_ca_topic_score_codex":0.000010670826,"about_ca_topic_score_gemma":5.4727604e-7,"teacher_disagreement_score":0.9459654,"about_ca_system_score_codex":0.000035520785,"about_ca_system_score_gemma":0.00017324903,"threshold_uncertainty_score":0.4746241},"labels":[],"label_agreement":null},{"id":"W2804575066","doi":"10.1109/tsp.2018.2847692","title":"Joint Detection and Localization of an Unknown Number of Sources Using the Algebraic Structure of the Noise Subspace","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"King Abdullah University of Science and Technology; Academy of Finland; Natural Sciences and Engineering Research Council of Canada; Technische Universiteit Delft; Massachusetts Institute of Technology","keywords":"Subspace topology; Orthogonality; Noise (video); Algorithm; Linear subspace; Greatest common divisor; Computer science; Mathematics; Signal subspace; A priori and a posteriori; Noise measurement; Pattern recognition (psychology); Artificial intelligence; Noise reduction","score_opus":0.016648775591504125,"score_gpt":0.26859820962020897,"score_spread":0.25194943402870484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804575066","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":[0.39225793,0.000011865089,0.6075134,0.000014559746,0.000056836376,0.000093801034,0.0000021929686,0.000028363556,0.000021043612],"genre_scores_gemma":[0.9865303,0.0000019123247,0.013420151,0.00001574313,0.000015412345,0.0000020885072,1.16142765e-7,0.00000930341,0.000004974726],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990017,0.00011047085,0.00033313563,0.00017206935,0.00029652196,0.000086112865],"domain_scores_gemma":[0.9988584,0.000047427468,0.00043303162,0.0002356306,0.00040133958,0.000024185545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018906218,0.00010241815,0.00015578742,0.00011272804,0.00024279169,0.000034075805,0.00023612706,0.00006818527,0.000010125543],"category_scores_gemma":[0.000009105047,0.00006952397,0.000051440704,0.0007487511,0.00037334807,0.00051057467,0.0000050683757,0.0001071326,1.0559745e-7],"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":[0.00004116761,0.00011129688,0.00017895465,0.00024988744,0.000026364522,7.5416814e-8,0.004386145,0.040048495,0.774259,0.00022246223,9.2399273e-7,0.18047523],"study_design_scores_gemma":[0.00006935034,0.00006599039,0.0002026495,0.00013411426,0.00002222484,0.000010996087,0.00007220909,0.3223801,0.67565084,0.0013436672,0.0000022561358,0.000045594104],"about_ca_topic_score_codex":0.000114710034,"about_ca_topic_score_gemma":0.000061756225,"teacher_disagreement_score":0.5942724,"about_ca_system_score_codex":0.000022745402,"about_ca_system_score_gemma":0.0000830007,"threshold_uncertainty_score":0.2835105},"labels":[],"label_agreement":null},{"id":"W2830158513","doi":"10.1007/s00034-018-0892-7","title":"An $$\\ell _p$$ ℓ p -norm Based Method for Off-grid DOA Estimation","year":2018,"lang":"en","type":"article","venue":"Circuits Systems and Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Concordia University","funders":"National Natural Science Foundation of China","keywords":"Norm (philosophy); Regularization (linguistics); Mathematics; Interior point method; Sparse approximation; Compressed sensing; Algorithm; Minification; Direction of arrival; Mathematical optimization; Applied mathematics; Computer science; Artificial intelligence","score_opus":0.02919417994894662,"score_gpt":0.320058498260105,"score_spread":0.2908643183111584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2830158513","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":[0.0016912944,0.0003204358,0.9960384,0.000036544083,0.00022435482,0.0004126631,0.000005533584,0.0003251701,0.0009456067],"genre_scores_gemma":[0.76141065,8.7523443e-7,0.23829071,0.000048675898,0.00015396354,0.000054768465,0.0000050691438,0.000012547229,0.000022757067],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867606,0.000090009315,0.00040464217,0.00038280964,0.00025238108,0.00019410558],"domain_scores_gemma":[0.99866277,0.00013695857,0.00032584948,0.00024291973,0.00053514313,0.000096368945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010578955,0.00014462977,0.00024569474,0.00018966671,0.00028386974,0.00040346826,0.0003224889,0.00009037496,0.0000037196364],"category_scores_gemma":[0.000057688576,0.00013479065,0.000037781625,0.00033685638,0.00006674882,0.0011233604,0.00002398723,0.000059484148,0.0000020850553],"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":[0.000005508596,0.000052504296,0.00008274613,0.0006561892,0.0000072409402,5.735777e-7,0.0006456245,0.0014860623,0.021201223,0.0057972306,0.00015759323,0.9699075],"study_design_scores_gemma":[0.0001949916,0.00025714017,0.00013515902,0.0003025799,0.0000112682965,0.000015618398,0.000028451259,0.9515612,0.044683516,0.0021816813,0.00046611586,0.00016226128],"about_ca_topic_score_codex":0.000039460556,"about_ca_topic_score_gemma":0.0000022912163,"teacher_disagreement_score":0.9697452,"about_ca_system_score_codex":0.00003674829,"about_ca_system_score_gemma":0.00015745382,"threshold_uncertainty_score":0.5496603},"labels":[],"label_agreement":null},{"id":"W2892367793","doi":"10.1109/tsp.2018.2870357","title":"Number of Source Signal Estimation by the Mean Squared Eigenvalue Error","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Mean squared error; Eigenvalues and eigenvectors; Robustness (evolution); Mathematics; Algorithm; Statistics; Signal-to-noise ratio (imaging); Noise (video); Probabilistic logic; Applied mathematics; Mathematical optimization; Computer science; Artificial intelligence","score_opus":0.021999457757364383,"score_gpt":0.2979845168372073,"score_spread":0.2759850590798429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892367793","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":[0.010994647,0.00001992081,0.98713815,0.00017660735,0.00011408378,0.00021575556,0.000007329119,0.00031468584,0.0010188328],"genre_scores_gemma":[0.9256237,0.0000011005383,0.074042365,0.00008255456,0.000026840207,0.000032406362,0.000001094962,0.000018562292,0.00017135726],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99834585,0.00011810875,0.00047429133,0.00031302994,0.0005465403,0.00020217511],"domain_scores_gemma":[0.99873453,0.00015802485,0.0003333321,0.00031777905,0.00039548954,0.000060852628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004479049,0.00017647941,0.00020099168,0.00014058505,0.00040473635,0.000106020634,0.00057456316,0.00008955568,0.0001359021],"category_scores_gemma":[0.000007827608,0.00014541364,0.00010185676,0.000790477,0.00029503825,0.000790248,0.000004358032,0.00019160582,0.00003265295],"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":[0.00005089037,0.0002897505,0.00001710106,0.000100006284,0.000036761863,4.190374e-7,0.0036106776,0.016609574,0.031875942,0.0003150771,0.0003862279,0.94670755],"study_design_scores_gemma":[0.00012475396,0.000116752744,0.00001268082,0.000105898514,0.000019942541,0.000013821962,0.000055838234,0.46354988,0.53438264,0.001435628,0.00007026016,0.00011187582],"about_ca_topic_score_codex":0.00007450586,"about_ca_topic_score_gemma":0.000006701717,"teacher_disagreement_score":0.94659567,"about_ca_system_score_codex":0.000057053432,"about_ca_system_score_gemma":0.0001408659,"threshold_uncertainty_score":0.5929796},"labels":[],"label_agreement":null},{"id":"W2909860276","doi":"10.1016/j.jfranklin.2019.01.019","title":"Mixed rectilinear sources localization under unknown mutual coupling","year":2019,"lang":"en","type":"article","venue":"Journal of the Franklin Institute","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Science Foundation of Ningbo Municipality; National Natural Science Foundation of China","keywords":"Coupling (piping); Range (aeronautics); Mutual information; Cramér–Rao bound; Computer science; Algorithm; Field (mathematics); Mathematics; Topology (electrical circuits); Estimation theory; Artificial intelligence; Engineering; Combinatorics","score_opus":0.019506729722482283,"score_gpt":0.24940449232402387,"score_spread":0.2298977626015416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909860276","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":[0.21593927,0.00011221342,0.7795148,0.00046513084,0.0031555602,0.00015767563,5.77379e-7,0.00006080239,0.0005939876],"genre_scores_gemma":[0.9598607,0.000035380395,0.039413065,0.00017895616,0.0001533427,0.0000019217462,3.868533e-7,0.000009755003,0.00034652778],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863774,0.000053102198,0.00056495564,0.00013209105,0.0004899845,0.00012213767],"domain_scores_gemma":[0.9983692,0.00009506846,0.00070380536,0.00038119478,0.00040103812,0.00004965985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072244153,0.00010983904,0.00022824612,0.0001752597,0.00010926199,0.000082839346,0.00096751726,0.00008098933,0.000016599815],"category_scores_gemma":[0.00021143226,0.00007657723,0.00015905,0.0005445934,0.00009151299,0.0009078946,0.00015033544,0.00023891512,0.000020558653],"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":[0.00006351647,0.00020827903,0.00615787,0.00009788826,0.00015953575,0.000005471217,0.00088091753,0.8775151,0.007097192,0.09014756,0.0031045966,0.0145620955],"study_design_scores_gemma":[0.0008649817,0.00023862804,0.0027222773,0.0005573663,0.000051643798,0.00014908084,0.000060813283,0.7677693,0.16449867,0.013857138,0.048962954,0.00026719196],"about_ca_topic_score_codex":0.000020738295,"about_ca_topic_score_gemma":0.000008813261,"teacher_disagreement_score":0.7439214,"about_ca_system_score_codex":0.00007111464,"about_ca_system_score_gemma":0.00019004903,"threshold_uncertainty_score":0.31227288},"labels":[],"label_agreement":null},{"id":"W2936104239","doi":"10.1139/juvs-2018-0011","title":"A harmonic spectral beamformer for the enhanced localization of propeller-driven aircraft","year":2019,"lang":"en","type":"article","venue":"Journal of Unmanned Vehicle Systems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Capon; Beamforming; Narrowband; Computer science; Propeller; Frequency domain; Harmonic; Harmonic analysis; Acoustics; Algorithm; Electronic engineering; Engineering; Telecommunications; Physics; Computer vision","score_opus":0.01419673642786231,"score_gpt":0.2546080176044907,"score_spread":0.24041128117662838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2936104239","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":[0.058637634,0.00022704827,0.9389463,0.00027617344,0.0008063683,0.00073199056,0.000002358182,0.000037058115,0.00033506597],"genre_scores_gemma":[0.98777866,0.000028124148,0.011810455,0.00002112772,0.00008953246,0.000013565353,4.6666398e-7,0.000012022913,0.00024602844],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983903,0.00008085569,0.00080417685,0.00013181737,0.00043218458,0.00016063328],"domain_scores_gemma":[0.9975843,0.00018397684,0.0011593333,0.00032154864,0.0007038773,0.000046969886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007694652,0.00010712002,0.00032980173,0.00017295206,0.000055578457,0.00005820745,0.0006849247,0.000062596715,0.0000069908656],"category_scores_gemma":[0.000078290235,0.00007155757,0.00017129123,0.0003687069,0.000041431693,0.0005958995,0.000048107686,0.00011418221,0.000008954902],"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":[0.00066332787,0.00087764097,0.0047440557,0.0024518652,0.000921089,0.0000047838757,0.007175042,0.29341325,0.58616745,0.04948827,0.006453169,0.047640055],"study_design_scores_gemma":[0.000881164,0.0011356605,0.0005916172,0.00054249226,0.00003442249,0.0000391792,0.00017795352,0.6200402,0.3731442,0.0008193044,0.0024532648,0.0001405744],"about_ca_topic_score_codex":0.000029204695,"about_ca_topic_score_gemma":0.0000019377144,"teacher_disagreement_score":0.92914104,"about_ca_system_score_codex":0.00007351969,"about_ca_system_score_gemma":0.0001433678,"threshold_uncertainty_score":0.2918033},"labels":[],"label_agreement":null},{"id":"W2949108189","doi":"","title":"Subspace Leakage Analysis and Improved DOA Estimation with Small Sample Size","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Subspace topology; Covariance matrix; Algorithm; Signal subspace; Mathematics; Resampling; Computer science; Noise (video); Covariance; Pattern recognition (psychology); Statistics; Artificial intelligence","score_opus":0.05396357390245824,"score_gpt":0.19909900877219508,"score_spread":0.14513543486973685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949108189","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":[0.14919975,0.000012055625,0.8494514,0.000054144824,0.000062561754,0.0002561413,0.000017283028,0.00037712549,0.0005695206],"genre_scores_gemma":[0.7032353,0.000022267193,0.29648265,0.000013334037,0.0000070219476,0.0000015532457,0.000011807665,0.000009670931,0.00021636662],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857146,0.000109079374,0.00020473966,0.00081557455,0.00010613273,0.00019303564],"domain_scores_gemma":[0.99759614,0.00035694198,0.00046097054,0.0010054774,0.00042728853,0.00015316889],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036226213,0.00026005364,0.00042787485,0.0005023777,0.00008076892,0.0001321757,0.00079654274,0.00018890566,0.000010009891],"category_scores_gemma":[0.0002605344,0.00027405127,0.00012212478,0.0015290577,0.00013349703,0.00043970975,0.0008119862,0.00026074788,0.000003156936],"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":[0.0002314647,0.0003953278,0.03612085,0.0005860046,0.0022060652,0.00010458499,0.0021638072,0.839131,0.0005609317,0.09748937,0.00024718774,0.020763421],"study_design_scores_gemma":[0.00026746286,0.000094578936,0.0038826484,0.000046030367,0.00040652408,0.0000020444409,0.000028948129,0.9576978,0.0015799575,0.03565031,0.000025871554,0.0003178249],"about_ca_topic_score_codex":0.0019455777,"about_ca_topic_score_gemma":0.0006029096,"teacher_disagreement_score":0.55403554,"about_ca_system_score_codex":0.00016021437,"about_ca_system_score_gemma":0.00020482813,"threshold_uncertainty_score":0.99997115},"labels":[],"label_agreement":null},{"id":"W2977357260","doi":"","title":"A Bayesian approach to tracking wideband targets using sensor arrays and particle filters","year":2003,"lang":"en","type":"article","venue":"IEEE Signal Processing Workshop on Statistical Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Particle filter; Robustness (evolution); Wideband; Computer science; Estimator; Bayesian probability; Electronic engineering; Tracking (education); Direction of arrival; Smart antenna; Antenna (radio); Kalman filter; Engineering; Artificial intelligence; Telecommunications; Mathematics; Directional antenna; Statistics","score_opus":0.042080177449275606,"score_gpt":0.30456316731261096,"score_spread":0.26248298986333535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977357260","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":[0.004002636,0.00023261015,0.99334973,0.00010535113,0.00007848696,0.00040281285,0.000008342409,0.0003720211,0.0014480378],"genre_scores_gemma":[0.5844044,0.0000016597246,0.41524678,0.00022792695,0.000039826205,0.0000237454,0.0000016329597,0.00003532057,0.000018693834],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961908,0.00026483292,0.00083486363,0.0010577991,0.00087267935,0.0007790677],"domain_scores_gemma":[0.9979191,0.00057127693,0.00037320977,0.00027006265,0.00037650872,0.00048987794],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00090486265,0.00047033204,0.0005699649,0.00027398363,0.0006461932,0.0009516318,0.00044678978,0.00016795885,0.000025986068],"category_scores_gemma":[0.00028874548,0.0004499874,0.00006934232,0.0013000042,0.0002491869,0.0011968425,0.000065620094,0.00044554818,0.0000053795766],"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":[0.00014297338,0.0006153908,0.00016666927,0.0007032099,0.00003609654,0.00004034902,0.0024309317,0.033314556,0.05450744,0.0077207456,0.00018571338,0.90013593],"study_design_scores_gemma":[0.00040605007,0.00019315915,0.000054670905,0.0009550121,0.000044251297,0.000068318535,0.00021357318,0.8922331,0.09479048,0.010279242,0.00010192274,0.0006602273],"about_ca_topic_score_codex":0.000011058167,"about_ca_topic_score_gemma":9.020254e-7,"teacher_disagreement_score":0.8994757,"about_ca_system_score_codex":0.00012889307,"about_ca_system_score_gemma":0.0002978037,"threshold_uncertainty_score":0.9997952},"labels":[],"label_agreement":null},{"id":"W2982349564","doi":"10.1109/apusncursinrsm.2019.8888325","title":"Direction-of-Arrival (DOA) Estimation based on Spacetime-Modulated Metasurface","year":2019,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Spacetime; Waveform; Direction of arrival; Estimator; Antenna (radio); Computer science; Row; SIGNAL (programming language); Algorithm; Acoustics; Electronic engineering; Physics; Telecommunications; Mathematics; Engineering","score_opus":0.009879092754806128,"score_gpt":0.2599094568707715,"score_spread":0.25003036411596535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982349564","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":[0.053988595,0.000010337738,0.91579837,0.0004293662,0.0005050195,0.00044106808,0.000003089222,0.0008184045,0.02800578],"genre_scores_gemma":[0.6733771,0.0000013959071,0.32599556,0.000058712092,0.000004812906,0.000009503817,0.0000038515877,0.000011072684,0.0005379712],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983117,0.000114518174,0.00043146597,0.0003931421,0.0005689573,0.00018021463],"domain_scores_gemma":[0.9982254,0.00026770608,0.00032240173,0.0008446866,0.0002718392,0.00006794933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051434414,0.00018287143,0.00031918572,0.00037029875,0.000046346202,0.000048831796,0.0005086625,0.00009518678,0.0002122569],"category_scores_gemma":[0.00018693198,0.00016986365,0.00012444556,0.0009368564,0.0000444646,0.00055564544,0.00007158541,0.0001092064,0.0001536395],"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":[0.00010511399,0.00082598167,0.0041655917,0.00026870705,0.00012747778,0.0000025258482,0.0003435936,0.6363163,0.13723294,0.10418531,0.0028061762,0.1136203],"study_design_scores_gemma":[0.0002059562,0.00017599572,0.0031817995,0.0000528934,0.000007336356,0.0000013135322,0.000002414473,0.69070727,0.30399987,0.0013424221,0.00019522868,0.00012751356],"about_ca_topic_score_codex":0.00012538083,"about_ca_topic_score_gemma":0.000002016192,"teacher_disagreement_score":0.6193885,"about_ca_system_score_codex":0.000065958455,"about_ca_system_score_gemma":0.00009373209,"threshold_uncertainty_score":0.6926838},"labels":[],"label_agreement":null},{"id":"W2985074536","doi":"10.1049/iet-map.2019.0326","title":"Patch and monopole antennas in linear coprime arrays for direction of arrival estimation using compressed sensing","year":2019,"lang":"en","type":"article","venue":"IET Microwaves Antennas & Propagation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Deanship of Scientific Research, King Saud University","keywords":"Coprime integers; Direction of arrival; Multiple signal classification; Antenna (radio); Algorithm; Computer science; Mean squared error; Compressed sensing; Isotropy; Antenna array; Acoustics; Directional antenna; Mathematics; Electronic engineering; Telecommunications; Physics; Engineering; Optics; Statistics","score_opus":0.016347300454766817,"score_gpt":0.2720644922036911,"score_spread":0.25571719174892427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2985074536","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":[0.44177037,0.000042379983,0.5572466,0.000058913414,0.00019978567,0.000564489,0.0000045037104,0.00008110914,0.000031838783],"genre_scores_gemma":[0.66714513,0.000014263893,0.33275917,0.000014298489,0.000017024193,0.0000052354712,0.000012739334,0.000014390387,0.00001774368],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847645,0.000093196446,0.0006156017,0.00039559952,0.00021201489,0.00020711898],"domain_scores_gemma":[0.99859744,0.00012599479,0.0005303466,0.00031584073,0.0003907515,0.000039641443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005009696,0.00018076025,0.00035207337,0.0003387513,0.00007158422,0.00006324862,0.00017690817,0.00010831282,0.0000017266527],"category_scores_gemma":[0.00011754614,0.00018975142,0.00006916376,0.00047439864,0.00008277272,0.00085011136,0.00007714248,0.00010393795,0.0000017932315],"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":[0.00005350645,0.00007787248,0.0013700345,0.00021736676,0.000012734928,5.0080143e-7,0.0006524687,0.0015923606,0.97770786,0.00079222757,0.0000087671915,0.017514285],"study_design_scores_gemma":[0.00031489405,0.00011698354,0.0013632937,0.00025005994,0.000007897108,0.000010390692,0.00003978915,0.56555986,0.43061563,0.00159942,0.00001165427,0.00011008166],"about_ca_topic_score_codex":0.00040181473,"about_ca_topic_score_gemma":0.000020580652,"teacher_disagreement_score":0.5639675,"about_ca_system_score_codex":0.00007908643,"about_ca_system_score_gemma":0.00007621935,"threshold_uncertainty_score":0.7737838},"labels":[],"label_agreement":null},{"id":"W2990066212","doi":"10.23919/eumc.2019.8910916","title":"Evaluation of Antenna Calibration and DOA Estimation Algorithms for FMCW Radars","year":2019,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Calibration; Computer science; Subspace topology; Antenna (radio); Radar; Algorithm; Direction of arrival; Remote sensing; Antenna array; Electronic engineering; Telecommunications; Engineering; Mathematics; Artificial intelligence; Geology","score_opus":0.03748051387163361,"score_gpt":0.3237691773840559,"score_spread":0.2862886635124223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990066212","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":[0.023751983,0.000025300342,0.9743502,0.00017963516,0.00014751856,0.0006930568,0.0000027729138,0.00011626696,0.00073324004],"genre_scores_gemma":[0.5376511,0.0000028624413,0.46225175,0.000015629996,0.0000046862933,0.00002356401,0.000005369102,0.000003308053,0.00004167177],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898005,0.000061589264,0.00026693748,0.00018135093,0.0004411289,0.00006896447],"domain_scores_gemma":[0.99891675,0.00010860506,0.00018753874,0.0002257565,0.00053932756,0.000022048825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012564884,0.00006588124,0.00012225896,0.00013718025,0.000025712687,0.00003522602,0.00014025958,0.000043788332,0.000018602534],"category_scores_gemma":[0.00018745598,0.000061118575,0.000029360386,0.00021014387,0.000024235527,0.00089782494,0.000036958718,0.000022232894,0.0000013824508],"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":[0.000010984278,0.00007727037,0.00044655672,0.00012266941,0.000026731876,3.6535003e-8,0.00052113313,0.0030390983,0.027716225,0.098272726,0.00031815082,0.8694484],"study_design_scores_gemma":[0.00028171387,0.000107039574,0.0009257525,0.000024369818,0.000014654418,0.0000014627392,0.000010948666,0.87385935,0.09830618,0.026396625,0.000014518184,0.00005739546],"about_ca_topic_score_codex":0.000045769197,"about_ca_topic_score_gemma":0.0000030101123,"teacher_disagreement_score":0.8708202,"about_ca_system_score_codex":0.000031460262,"about_ca_system_score_gemma":0.0000843886,"threshold_uncertainty_score":0.2492343},"labels":[],"label_agreement":null},{"id":"W3010992090","doi":"10.1109/camsap45676.2019.9022674","title":"Blind Maximum Likelihood Jade in Multipath Environement Using Importance Sampling","year":2019,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Cramér–Rao bound; Computer science; Maximum likelihood; Multipath propagation; Algorithm; Maximization; Sampling (signal processing); Upper and lower bounds; Joint (building); Estimation theory; Expectation–maximization algorithm; Importance sampling; Signal-to-noise ratio (imaging); SIGNAL (programming language); Mathematical optimization; Iterative method; Statistics; Mathematics; Telecommunications; Monte Carlo method; Detector; Channel (broadcasting); Engineering","score_opus":0.03499129999447652,"score_gpt":0.29734860513635836,"score_spread":0.2623573051418818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010992090","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":[0.39797142,0.000022837386,0.59981436,0.000053948443,0.000116716,0.00022905463,5.688704e-7,0.00012526965,0.0016658],"genre_scores_gemma":[0.55858654,0.000004721371,0.44130155,0.000057270063,0.0000066612774,0.000006341208,6.824957e-7,0.000005391111,0.00003081981],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885213,0.000024854004,0.0003645184,0.00031275605,0.00023915016,0.00020656968],"domain_scores_gemma":[0.9992642,0.000050836865,0.00014872754,0.00045625563,0.000035590445,0.00004441117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003381017,0.00010756099,0.00016028366,0.00019302742,0.000025603471,0.000044459022,0.00040384938,0.00005188168,0.00008427168],"category_scores_gemma":[0.000027522121,0.00010624591,0.000040243816,0.00033562534,0.000017182865,0.0004925958,0.00017212806,0.000091571674,0.000034009066],"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":[0.000041052393,0.0008353828,0.4154786,0.0001919567,0.000042360694,0.000012664461,0.0023229693,0.009391242,0.27397802,0.037932616,0.00011659211,0.25965658],"study_design_scores_gemma":[0.0012638759,0.00014334229,0.05712894,0.00018099636,0.0000059278455,0.000011607287,0.00009011848,0.7327869,0.18481559,0.022429649,0.0006252553,0.00051783636],"about_ca_topic_score_codex":0.00019127411,"about_ca_topic_score_gemma":0.000025086569,"teacher_disagreement_score":0.72339565,"about_ca_system_score_codex":0.0000941524,"about_ca_system_score_gemma":0.000050945244,"threshold_uncertainty_score":0.43325827},"labels":[],"label_agreement":null},{"id":"W3012983481","doi":"10.1186/s13638-020-1637-4","title":"Channel estimation based on the PSS-MUSIC for millimeter-wave MIMO systems equipped with co-prime arrays","year":2020,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Computer science; Channel (broadcasting); Prime (order theory); Path (computing); Algorithm; Aperture (computer memory); MIMO; Direction of arrival; Extremely high frequency; Computational complexity theory; Telecommunications; Acoustics; Mathematics; Physics; Antenna (radio)","score_opus":0.10567937032291205,"score_gpt":0.29110046736083406,"score_spread":0.185421097037922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012983481","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":[0.0036721488,0.00031752806,0.9881729,0.0062897285,0.00016677409,0.0005209402,0.000005070185,0.00013410408,0.0007208313],"genre_scores_gemma":[0.95533675,0.00021911916,0.04343432,0.00078264094,0.000116387746,0.00007532173,0.000008545704,0.000021900225,0.0000050282124],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847335,0.00035191362,0.00044630765,0.00021334694,0.00031060772,0.00020445409],"domain_scores_gemma":[0.99687934,0.0013397611,0.00060542463,0.0008489426,0.00021060042,0.000115912546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083455304,0.00018236197,0.00025727984,0.00013422224,0.00081093103,0.0003697209,0.0009844363,0.000054613778,0.0000018282346],"category_scores_gemma":[0.00005089787,0.00012873467,0.00007725375,0.0004642293,0.00011234092,0.00026725634,0.00010181295,0.00036554312,0.0000019069198],"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":[0.00063612446,0.0008095868,0.0006084063,0.00030195358,0.00043656107,0.000016061276,0.0066963946,0.19016814,0.0044005224,0.096150056,0.00489964,0.69487655],"study_design_scores_gemma":[0.00033957433,0.00059967267,0.00008674277,0.00056182215,0.00001866428,0.000025083877,0.000049215905,0.99456275,0.0016009668,0.00049338856,0.0015095293,0.00015257437],"about_ca_topic_score_codex":0.0000050132962,"about_ca_topic_score_gemma":0.0000017033456,"teacher_disagreement_score":0.95166457,"about_ca_system_score_codex":0.00004767581,"about_ca_system_score_gemma":0.00006796233,"threshold_uncertainty_score":0.6237108},"labels":[],"label_agreement":null},{"id":"W3019597002","doi":"10.1109/taes.2020.2988424","title":"DOA Elevation and Azimuth Angles Estimation of GPS Jamming Signals Using Fast Orthogonal Search","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Royal Military College of Canada","funders":"","keywords":"Jamming; Azimuth; Direction of arrival; Interference (communication); Global Positioning System; Computer science; GPS signals; Elevation (ballistics); SIGNAL (programming language); Telecommunications; Assisted GPS; Engineering; Mathematics; Antenna (radio); Physics","score_opus":0.02635567342748359,"score_gpt":0.26811899717912313,"score_spread":0.24176332375163953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3019597002","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":[0.29343876,0.00014169724,0.70586264,0.00016486307,0.000056351393,0.00022581637,0.000004832794,0.000082404644,0.000022613027],"genre_scores_gemma":[0.9923341,0.00009023767,0.007489302,0.000022810966,0.000017166927,0.000017221442,0.0000011957785,0.000011825062,0.000016133148],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874693,0.00010010595,0.00033157365,0.000293912,0.00030866681,0.0002187982],"domain_scores_gemma":[0.99934286,0.000113235335,0.00017270795,0.00016099644,0.00013059733,0.00007960737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032868175,0.00013922149,0.0002447602,0.0001651957,0.00014090318,0.0000834756,0.00013290065,0.00007766912,0.0000030215817],"category_scores_gemma":[0.000010864107,0.00014196867,0.000045121204,0.00052886957,0.000061194,0.0004211741,0.0000037131758,0.0001662176,0.0000012613575],"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":[0.000092019276,0.00017476303,0.0001637717,0.0007192659,0.0001512323,0.000001630521,0.0051513067,0.49270475,0.38047627,0.01257785,0.00003129473,0.10775585],"study_design_scores_gemma":[0.00020296473,0.00036755495,0.00005026974,0.00012575228,0.000020676722,0.000018854063,0.00017550886,0.7842891,0.2145113,0.00010882387,0.000010827455,0.00011831084],"about_ca_topic_score_codex":0.0001554667,"about_ca_topic_score_gemma":0.000011635056,"teacher_disagreement_score":0.69889534,"about_ca_system_score_codex":0.00006761902,"about_ca_system_score_gemma":0.00013011615,"threshold_uncertainty_score":0.57893145},"labels":[],"label_agreement":null},{"id":"W3022426739","doi":"10.1049/el.2019.4030","title":"Low‐complexity architecture for AR(1) inference","year":2020,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Estimator; Inference; Monte Carlo method; Reduction (mathematics); Power (physics); Architecture","score_opus":0.026089559352522294,"score_gpt":0.27185239471598266,"score_spread":0.24576283536346036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022426739","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":[0.009501662,0.00004145943,0.9609398,0.02855441,0.00006804513,0.0002653269,0.000004059694,0.0004148465,0.0002103518],"genre_scores_gemma":[0.68508744,0.000008117654,0.30629483,0.008464099,0.00006671972,0.00004975752,0.00000696574,0.000014087404,0.000007966833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989707,0.000037383168,0.00020794003,0.00030438224,0.00019063256,0.00028899318],"domain_scores_gemma":[0.9993038,0.0001356182,0.00012068386,0.0003019591,0.00006291007,0.00007503566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012612452,0.00012483496,0.00016302204,0.00006626702,0.00006379198,0.000058550777,0.00076466973,0.000038564547,0.000008190345],"category_scores_gemma":[0.00016753697,0.00012751397,0.00008682297,0.00034719025,0.000059376405,0.00020694721,0.000099678204,0.00018809152,0.0000073593083],"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":[0.000051272455,0.00009404445,0.00015915574,0.0002422071,0.000056671444,0.0000031523457,0.0016456718,0.002994863,0.29873422,0.54000926,0.022430614,0.13357884],"study_design_scores_gemma":[0.00048446172,0.0005881548,0.0002882025,0.00003957738,0.000013673749,0.000006729776,0.0000038894386,0.082956046,0.797756,0.081214964,0.036164246,0.00048405887],"about_ca_topic_score_codex":0.000006109811,"about_ca_topic_score_gemma":0.000008165511,"teacher_disagreement_score":0.6755858,"about_ca_system_score_codex":0.000051853644,"about_ca_system_score_gemma":0.000093165916,"threshold_uncertainty_score":0.51998687},"labels":[],"label_agreement":null},{"id":"W3035267179","doi":"10.1109/radar42522.2020.9114700","title":"Improved Covariance Matrix Estimation using Riemannian Geometry for Beamforming Applications","year":2020,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; Carleton University","funders":"","keywords":"Estimation of covariance matrices; Covariance matrix; Mathematics; Covariance; Algorithm; Signal-to-interference-plus-noise ratio; Beamforming; Riemannian manifold; Applied mathematics; Statistics; Mathematical analysis; Physics","score_opus":0.030615637524414704,"score_gpt":0.32021839656960244,"score_spread":0.28960275904518773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035267179","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":[0.0003940362,0.000017262324,0.9970389,0.00079097797,0.000056363355,0.00077140843,0.000007314327,0.00059660437,0.00032714292],"genre_scores_gemma":[0.13119331,0.0000012141998,0.86837876,0.00020720612,0.00003552474,0.00013176183,0.000005842023,0.000009504958,0.0000369103],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909806,0.000011248517,0.000330728,0.00027746474,0.00013804223,0.00014447996],"domain_scores_gemma":[0.99913436,0.00009844262,0.00021247247,0.00029252816,0.00018384475,0.00007837275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001853209,0.00010000456,0.00014974631,0.000112125905,0.00012951311,0.00008816863,0.00044897117,0.00005255912,0.000008397692],"category_scores_gemma":[0.0001462414,0.000104596584,0.00006130661,0.0007733055,0.000027000404,0.0007924766,0.00009869511,0.000053464348,0.0000060391612],"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":[0.000020700361,0.00011188348,0.00008647771,0.0005113459,0.00004576176,3.6319693e-7,0.0007212853,0.025495201,0.11084026,0.59462017,0.0005910167,0.26695552],"study_design_scores_gemma":[0.00012205604,0.00004750414,0.000018871924,0.000011360236,0.00000771292,0.0000025560266,0.000010024261,0.9154609,0.077058814,0.0058995667,0.0012535498,0.000107115186],"about_ca_topic_score_codex":0.000030796855,"about_ca_topic_score_gemma":7.683096e-7,"teacher_disagreement_score":0.88996565,"about_ca_system_score_codex":0.000043536143,"about_ca_system_score_gemma":0.00007571098,"threshold_uncertainty_score":0.42653248},"labels":[],"label_agreement":null},{"id":"W3036645861","doi":"10.11159/mhci20.104","title":"Mathematical Tools for Processing Broadband Multi-Sensor Signals","year":2020,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Broadband; Signal processing; Telecommunications; Radar","score_opus":0.025109796118492247,"score_gpt":0.2508735084354703,"score_spread":0.22576371231697806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036645861","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":[0.049503956,0.00025403264,0.94807076,0.0007452054,0.0003301177,0.00069462723,0.0000019092647,0.0002482827,0.00015112832],"genre_scores_gemma":[0.9311767,0.000004122607,0.06862685,0.00005950138,0.000050115712,0.000029028295,3.2727865e-8,0.000006790209,0.000046833175],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988524,0.0000041455537,0.00030103684,0.00032895195,0.0003087021,0.00020476195],"domain_scores_gemma":[0.9991753,0.00018178458,0.00017166026,0.000081291,0.00027336337,0.00011657985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036893509,0.00012770825,0.00026616876,0.00014931858,0.0001231573,0.00043217713,0.0005989845,0.00002829857,1.3213626e-7],"category_scores_gemma":[0.00025406913,0.00009002265,0.00003947947,0.00091263273,0.00011879741,0.0004994374,0.0001578814,0.0001011712,1.36546e-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":[0.00005374662,0.00021350574,0.0006305435,0.0034301903,0.00005257792,0.0000010846627,0.0012914618,0.0069206217,0.12504141,0.68436444,0.00081293326,0.17718746],"study_design_scores_gemma":[0.00015390126,0.0001413281,0.00023239167,0.0003128948,0.0000051172974,0.000010085065,0.000003831611,0.9597223,0.038969465,0.00013813598,0.00020446027,0.00010610103],"about_ca_topic_score_codex":0.0000014053988,"about_ca_topic_score_gemma":2.8200713e-8,"teacher_disagreement_score":0.95280164,"about_ca_system_score_codex":0.00001522081,"about_ca_system_score_gemma":0.00003166472,"threshold_uncertainty_score":0.4167494},"labels":[],"label_agreement":null},{"id":"W3046897407","doi":"10.1109/tsp.2020.3013389","title":"Padded Coprime Arrays for Improved DOA Estimation: Exploiting Hole Representation and Filling Strategies","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":141,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fundamental Research Funds for the Central Universities; State Key Laboratory of Millimeter Waves; Southeast University; China Scholarship Council","keywords":"Coprime integers; Algorithm; Degrees of freedom (physics and chemistry); Representation (politics); Coupling (piping); Mathematics; Displacement (psychology); Computer science; Sensor array; Sparse array; Topology (electrical circuits); Combinatorics; Physics; Engineering","score_opus":0.046784536910230025,"score_gpt":0.30503231201494135,"score_spread":0.2582477751047113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046897407","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":[0.0021458603,0.000031786796,0.99601686,0.0006798352,0.00007718692,0.00036582872,0.000007548876,0.00052191893,0.00015318574],"genre_scores_gemma":[0.6526297,0.0000033684157,0.34715155,0.000101000915,0.000025137739,0.00006889909,0.0000021456624,0.000011690337,0.000006510878],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884254,0.000037089656,0.0003796948,0.00039218922,0.00018665499,0.00016182166],"domain_scores_gemma":[0.99912757,0.00019544149,0.0002346329,0.00013496824,0.00022357849,0.000083804734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017878984,0.00015132432,0.00019821001,0.00012452599,0.0003320383,0.0003503813,0.00020383982,0.00006496341,0.0000072474404],"category_scores_gemma":[0.000023388302,0.00016116102,0.00006575405,0.00045914282,0.000061323466,0.0018675763,0.0000030937995,0.00013955713,0.0000016858021],"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":[0.00006173207,0.000060958755,0.0000011926537,0.00028645035,0.00002309576,8.518156e-7,0.002889455,0.14737049,0.17052677,0.0006427415,0.000027626671,0.67810863],"study_design_scores_gemma":[0.00019875966,0.00011191555,0.0000023803955,0.00007616956,0.000012470432,0.000002397471,0.000237078,0.60628086,0.39063424,0.0023308755,0.000010501847,0.00010234388],"about_ca_topic_score_codex":0.000009320765,"about_ca_topic_score_gemma":0.0000011052415,"teacher_disagreement_score":0.6780063,"about_ca_system_score_codex":0.000026744605,"about_ca_system_score_gemma":0.00012220645,"threshold_uncertainty_score":0.65719557},"labels":[],"label_agreement":null},{"id":"W3082485027","doi":"10.1155/2020/9651650","title":"Nonuniformly Spaced Array with the Direct Data Domain Method for 2D Angle-of-Arrival Measurement in Electronic Support Measures Application from 6 to 18 GHz","year":2020,"lang":"en","type":"article","venue":"International Journal of Antennas and Propagation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"Defence Research and Development Canada","keywords":"Estimator; Angle of arrival; Algorithm; Mean squared error; Frequency domain; Computer science; Direction of arrival; Transformation (genetics); Electronic engineering; Mathematics; Statistics; Engineering; Telecommunications; Antenna (radio)","score_opus":0.04473327753809468,"score_gpt":0.3102350867470661,"score_spread":0.26550180920897143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082485027","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":[0.010042939,0.00007243222,0.9803966,0.008821638,0.000082552506,0.00041750097,0.000026704147,0.000017631537,0.00012198848],"genre_scores_gemma":[0.80430067,0.000027916245,0.19533043,0.00021486261,0.000085359745,0.000017831217,0.000013557855,0.000007261234,0.0000021193728],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99831545,0.000102998674,0.00047979664,0.00022165204,0.0007700227,0.00011009869],"domain_scores_gemma":[0.99798536,0.00013081782,0.00061756046,0.0002162542,0.0009915842,0.00005840549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017745029,0.00010514837,0.00021091507,0.00016168578,0.000034424036,0.00007246013,0.00091368594,0.00003238534,0.000003577785],"category_scores_gemma":[0.00026346964,0.00007224553,0.000045012595,0.00026292418,0.000030191497,0.00058931817,0.00008113594,0.000114245,4.5321048e-7],"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":[0.0019601858,0.00025382885,0.0027825246,0.00006554498,0.00048803736,0.0000063276134,0.0053967517,0.0013015014,0.6537949,0.010572181,0.0015961679,0.32178208],"study_design_scores_gemma":[0.0034808272,0.003707771,0.012835977,0.0006034871,0.0001395848,0.000103795865,0.0006373806,0.18981434,0.74349874,0.023174264,0.021440247,0.00056356954],"about_ca_topic_score_codex":0.00009299071,"about_ca_topic_score_gemma":0.000115564864,"teacher_disagreement_score":0.7942577,"about_ca_system_score_codex":0.00008669275,"about_ca_system_score_gemma":0.00023157276,"threshold_uncertainty_score":0.2946087},"labels":[],"label_agreement":null},{"id":"W3092233937","doi":"10.1109/jsen.2020.3029934","title":"Sparse DOA Estimation for Directional Antenna Arrays: An Experimental Validation","year":2020,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"King Fahd University of Petroleum and Minerals","keywords":"Direction of arrival; Directivity; Radiation pattern; Antenna (radio); Acoustics; Mean squared error; Computer science; Multipath propagation; Antenna array; Algorithm; Electronic engineering; Physics; Mathematics; Telecommunications; Engineering; Statistics","score_opus":0.05493039373258703,"score_gpt":0.31590045824867663,"score_spread":0.2609700645160896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092233937","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":[0.11082156,0.000016282956,0.8871056,0.00063013914,0.00075915764,0.00019770501,0.0000054895963,0.00024804572,0.00021601641],"genre_scores_gemma":[0.6297064,0.000004931327,0.36985224,0.00013053109,0.00025772865,0.000011254958,0.000006641232,0.000012035533,0.000018262139],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986435,0.00010425594,0.00043555346,0.00025396526,0.00039047305,0.00017225336],"domain_scores_gemma":[0.9989163,0.000077899545,0.00033977177,0.000168408,0.0003086021,0.00018898128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034379048,0.00013852303,0.00017837562,0.00015639109,0.00021073966,0.00021097955,0.00034366437,0.000060270148,0.000031950716],"category_scores_gemma":[0.00016483445,0.00013893668,0.00011331429,0.00027901158,0.000042107582,0.0015566933,0.000021343563,0.0001453478,0.000012016391],"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":[0.00015435654,0.00037363032,0.00017388556,0.000040480776,0.00006176198,0.000012513409,0.003908339,0.049232703,0.9118835,0.0048722527,0.0042661154,0.025020473],"study_design_scores_gemma":[0.0002568881,0.00028084725,0.00011213633,0.000019559264,0.000006385303,0.00011343558,0.000046542646,0.47459242,0.52272075,0.0014388842,0.00029950019,0.00011267152],"about_ca_topic_score_codex":0.000005442083,"about_ca_topic_score_gemma":2.513853e-7,"teacher_disagreement_score":0.5188848,"about_ca_system_score_codex":0.00007745582,"about_ca_system_score_gemma":0.00007774584,"threshold_uncertainty_score":0.56656736},"labels":[],"label_agreement":null},{"id":"W3093324473","doi":"10.1186/s13638-020-01830-1","title":"Robust widely linear beamforming using estimation of extended covariance matrix and steering vector","year":2020,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"China Scholarship Council","keywords":"Covariance matrix; Computer science; Beamforming; Algorithm; Covariance; Noise (video); Computational complexity theory; Estimation of covariance matrices; Matrix (chemical analysis); Adaptive beamformer; Convex optimization; Array processing; Mathematical optimization; Signal processing; Mathematics; Regular polygon; Artificial intelligence; Radar; Telecommunications; Statistics","score_opus":0.08387111226946407,"score_gpt":0.3141854374430649,"score_spread":0.2303143251736008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093324473","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":[0.06139731,0.0014654644,0.9360627,0.00071874936,0.0000952258,0.0001129906,0.0000012540843,0.00007180433,0.00007452399],"genre_scores_gemma":[0.61812806,0.00093902776,0.3808494,0.000034663724,0.000036859725,0.000001696056,7.8112316e-7,0.000008218079,0.0000012673001],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988738,0.00013308741,0.0005175226,0.00015148956,0.0001930482,0.0001310647],"domain_scores_gemma":[0.99848443,0.0002953714,0.00058019155,0.00040351748,0.00014040164,0.00009605813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048672842,0.0001195037,0.00024063079,0.00011848829,0.0003483666,0.00011525859,0.0005735148,0.000046327736,0.0000010965015],"category_scores_gemma":[0.000051990395,0.00012065684,0.000041670224,0.00043587538,0.000091033595,0.00057729817,0.00030614279,0.0002943315,2.5566396e-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":[0.000048980943,0.000109115615,0.0010145691,0.0001578397,0.00008407698,0.0000051791485,0.0027470733,0.21417552,0.010417784,0.051796664,0.000020603613,0.7194226],"study_design_scores_gemma":[0.00017480513,0.00010729048,0.00043119318,0.00050094,0.000014295913,0.000066315195,0.000032614793,0.99627286,0.0015991153,0.0004681403,0.0002236292,0.00010880986],"about_ca_topic_score_codex":0.00001145464,"about_ca_topic_score_gemma":0.0000012580562,"teacher_disagreement_score":0.78209734,"about_ca_system_score_codex":0.00003211976,"about_ca_system_score_gemma":0.000048184153,"threshold_uncertainty_score":0.49202433},"labels":[],"label_agreement":null},{"id":"W3110308674","doi":"10.1109/ccece47787.2020.9255751","title":"Implementation and Evaluation of LS-SVM Optimization Methods for Estimating DoAs","year":2020,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Beamforming; Computer science; Direction of arrival; Algorithm; Waveform; Antenna array; Support vector machine; Power (physics); Channel (broadcasting); Least-squares function approximation; Antenna (radio); Computer engineering; Artificial intelligence; Mathematics; Telecommunications; Radar","score_opus":0.1149314300856014,"score_gpt":0.4880341300795623,"score_spread":0.3731026999939609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110308674","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":[0.0006534463,0.00002630305,0.997303,0.00040860445,0.00007559358,0.0005846069,0.0000014781859,0.00012846486,0.00081849354],"genre_scores_gemma":[0.075001,0.0000021975106,0.9248075,0.00009220454,0.0000128794945,0.00006953298,0.000007648267,0.000004548804,0.0000024750866],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913067,0.00012678074,0.0003138589,0.00017130964,0.00019850521,0.000058867132],"domain_scores_gemma":[0.9989419,0.000148641,0.00023823034,0.00011257715,0.00052524655,0.00003341595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011890765,0.000059805927,0.00011336663,0.00007579783,0.0000374508,0.000033547443,0.00013057009,0.000025722686,0.000029432165],"category_scores_gemma":[0.00038205262,0.000059495997,0.000025615998,0.00026472087,0.000016177733,0.0005096663,0.000059858587,0.00001939367,1.9334128e-7],"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":[0.0000027534404,0.000011890206,0.000071032555,0.000059013903,0.000007681842,4.5433377e-9,0.0004458934,0.02535054,0.0033019546,0.023355287,0.00013728156,0.9472567],"study_design_scores_gemma":[0.00020500695,0.000089187306,0.00007454595,0.000010376527,0.00002007704,4.8535816e-7,0.00005512927,0.8510579,0.14213516,0.0062790406,0.000025575964,0.000047543166],"about_ca_topic_score_codex":0.0000320902,"about_ca_topic_score_gemma":0.0000012691271,"teacher_disagreement_score":0.9472091,"about_ca_system_score_codex":0.000020520765,"about_ca_system_score_gemma":0.000099648794,"threshold_uncertainty_score":0.24261764},"labels":[],"label_agreement":null},{"id":"W3131547648","doi":"10.1109/taes.2021.3059094","title":"A Maximum Likelihood Method for Joint DOA and Polarization Estimation Based on Manifold Separation","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"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":"Direction of arrival; Antenna array; Azimuth; Polarization (electrochemistry); Algorithm; Computer science; Radar; Mathematics; Antenna (radio); Physics; Optics; Telecommunications","score_opus":0.012333185537603035,"score_gpt":0.27845061724476455,"score_spread":0.2661174317071615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3131547648","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":[0.0015152056,0.00013164442,0.9964397,0.00072815723,0.00027750104,0.0005949896,0.000010792854,0.00019393879,0.00010808232],"genre_scores_gemma":[0.87249553,0.00005559113,0.12692489,0.00010923778,0.000015287096,0.00020396538,0.00000835632,0.000018217093,0.00016891342],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986563,0.0001353773,0.0003060267,0.0004141188,0.0002386259,0.00024957277],"domain_scores_gemma":[0.99911445,0.00015322103,0.00016419338,0.00031324071,0.00018698993,0.00006789812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047540705,0.00017158751,0.00023909094,0.00020478165,0.00020767047,0.00018451917,0.00008790658,0.00011856032,0.0000028265608],"category_scores_gemma":[0.000019079635,0.0001779395,0.00006796492,0.00039982083,0.000014953548,0.00031383274,0.00000181375,0.00013997343,0.0000023645086],"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":[0.00024618028,0.0009577378,0.00003923369,0.001116557,0.0002449341,0.000004369617,0.0012089014,0.28777617,0.23049976,0.10588076,0.0004467195,0.37157866],"study_design_scores_gemma":[0.00044440417,0.00046367207,0.000029825082,0.000106203166,0.000030555933,0.000025108478,0.0000247949,0.8095234,0.18720944,0.0018314422,0.00016949052,0.00014166164],"about_ca_topic_score_codex":0.00011794694,"about_ca_topic_score_gemma":0.00004456502,"teacher_disagreement_score":0.8709803,"about_ca_system_score_codex":0.00013940473,"about_ca_system_score_gemma":0.00018119834,"threshold_uncertainty_score":0.7256162},"labels":[],"label_agreement":null},{"id":"W3141713161","doi":"10.1007/s00034-021-01708-7","title":"Atomic Norm-Based DOA Estimation with Sum and Difference Co-arrays in Coexistence of Circular and Non-circular Signals","year":2021,"lang":"en","type":"article","venue":"Circuits Systems and Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Concordia University","funders":"Key Laboratory of Intelligent Perception and Advanced Control of State Ethnic Affairs Commission; National Natural Science Foundation of China","keywords":"Circular buffer; Norm (philosophy); Algorithm; Minification; Direction of arrival; Computer science; Set (abstract data type); Aperture (computer memory); Mathematics; Mathematical optimization; Acoustics; Physics; Telecommunications","score_opus":0.020290754848345107,"score_gpt":0.256773390192085,"score_spread":0.2364826353437399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3141713161","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":[0.37185648,0.0013640615,0.6263942,0.00001763595,0.000015889958,0.00019440726,0.000002787635,0.000039756476,0.00011478887],"genre_scores_gemma":[0.99247956,0.000017036995,0.007423173,0.000023111837,0.000008047933,0.000028306586,0.000003952517,0.000011554589,0.000005258129],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984401,0.00009852914,0.00048000147,0.00045300942,0.0003436513,0.00018471868],"domain_scores_gemma":[0.99890447,0.00013371065,0.0003558271,0.00020721155,0.0003089017,0.00008990301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047900563,0.00017999501,0.00043459274,0.00020319724,0.00011829609,0.00024701623,0.00016431394,0.000090006826,0.0000011481147],"category_scores_gemma":[0.000045882978,0.00016658472,0.000021741414,0.00048026978,0.0001778747,0.00053089904,0.000041299627,0.00011085786,2.0409769e-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":[0.000030218931,0.00032002648,0.087733366,0.01706584,0.00007525238,0.00013557739,0.0067007155,0.013120031,0.69216776,0.0037594212,0.0000089439545,0.17888287],"study_design_scores_gemma":[0.0005770291,0.0001160414,0.017014218,0.002669725,0.000019621799,0.00013166772,0.00018516755,0.90069866,0.07727928,0.0010389823,0.0000031597958,0.00026641818],"about_ca_topic_score_codex":0.00010039859,"about_ca_topic_score_gemma":0.0000038734775,"teacher_disagreement_score":0.88757867,"about_ca_system_score_codex":0.0000355686,"about_ca_system_score_gemma":0.00027121554,"threshold_uncertainty_score":0.6793128},"labels":[],"label_agreement":null},{"id":"W3149904770","doi":"10.18280/mmep.080116","title":"Hybrid Reweighted Optimization Method for Gridless Direction of Arrival Estimation in Heteroscedastic Noise Environment","year":2021,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Heteroscedasticity; Computer science; Maxima and minima; Algorithm; Noise (video); Mathematical optimization; Covariance; Relaxation (psychology); Optimization problem; Global optimization; Minification; Mathematics; Artificial intelligence; Machine learning","score_opus":0.01751370679589677,"score_gpt":0.23621838697400094,"score_spread":0.21870468017810418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3149904770","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":[0.004639745,0.00005446158,0.99483556,0.00004033589,0.000054050222,0.0002314308,0.0000024970761,0.00011356154,0.000028335475],"genre_scores_gemma":[0.25569427,0.000025951433,0.74419194,0.0000017123052,0.0000040561517,0.000059196784,0.0000051171783,0.000010270856,0.000007467173],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906516,0.000025828338,0.00042860818,0.00022523517,0.00013222183,0.00012292308],"domain_scores_gemma":[0.9993883,0.00022557295,0.00010293262,0.00018618793,0.000057922847,0.00003909351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037268276,0.00011050086,0.00023935073,0.0001308464,0.00002346269,0.000031029547,0.00009237167,0.000047037578,0.0000023612529],"category_scores_gemma":[0.000106978274,0.000114015915,0.00004229052,0.00014355443,0.000013201601,0.00019222814,0.000042345102,0.000065160864,3.501537e-7],"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":[0.000002210292,0.000065285785,0.0000018979817,0.00057249336,0.0000074622944,2.5971477e-7,0.00018214431,0.9799232,0.003499803,0.013227953,8.2144703e-7,0.0025164767],"study_design_scores_gemma":[0.00014874183,0.000036441597,0.0000046444816,0.0003137392,0.000010438023,0.000009306527,0.0000018348567,0.9225697,0.052176327,0.024627866,0.0000047340704,0.00009622852],"about_ca_topic_score_codex":0.000005354428,"about_ca_topic_score_gemma":7.0024434e-8,"teacher_disagreement_score":0.25105453,"about_ca_system_score_codex":0.000034319637,"about_ca_system_score_gemma":0.00001241146,"threshold_uncertainty_score":0.4649434},"labels":[],"label_agreement":null},{"id":"W3157878946","doi":"10.1109/lcomm.2021.3074890","title":"Harmonic Retrieval Joint Multiple Regression: Robust DOA Estimation for FMCW Radar in the Presence of Unknown Spatially Colored Noise","year":2021,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Colors of noise; Robustness (evolution); Direction of arrival; Computer science; Noise (video); Algorithm; White noise; Radar; Colored; Gaussian noise; Mathematics; Artificial intelligence; Telecommunications","score_opus":0.06117261001555043,"score_gpt":0.30143712307621157,"score_spread":0.24026451306066113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157878946","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":[0.042406935,0.00018863386,0.93025154,0.025875967,0.00021712073,0.000794751,0.000017401479,0.00011901729,0.00012862243],"genre_scores_gemma":[0.54582196,0.000059463066,0.45366353,0.0003030941,0.000008790756,0.000095788084,0.000028553195,0.0000073916667,0.000011396246],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998093,0.0004937089,0.00063720986,0.00025851408,0.0003509326,0.00016660294],"domain_scores_gemma":[0.99508554,0.0014775831,0.0004681828,0.002547498,0.00038784693,0.000033334938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009113751,0.00013440769,0.0002419295,0.0001820944,0.0001953168,0.000078505764,0.0021744198,0.00006819324,0.0000028663096],"category_scores_gemma":[0.001232526,0.0001167809,0.000110942216,0.0009851067,0.00023569106,0.0004919907,0.00030675903,0.00021738681,0.0000024007752],"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":[0.00011341785,0.0011205785,0.00064771896,0.00030100177,0.00008005348,0.00000824383,0.007296199,0.042686068,0.8706665,0.026120806,0.015784,0.03517541],"study_design_scores_gemma":[0.00056700537,0.000062029496,0.0023077114,0.00028512467,0.00001859353,0.000012184346,0.000056836227,0.6017458,0.39228672,0.0014093366,0.0010807177,0.0001679596],"about_ca_topic_score_codex":0.000092680864,"about_ca_topic_score_gemma":0.00010334132,"teacher_disagreement_score":0.55905974,"about_ca_system_score_codex":0.00008660536,"about_ca_system_score_gemma":0.00019304201,"threshold_uncertainty_score":0.4762187},"labels":[],"label_agreement":null},{"id":"W3165395996","doi":"10.1109/tsp.2021.3083988","title":"Dilated Arrays: A Family of Sparse Arrays With Increased Uniform Degrees of Freedom and Reduced Mutual Coupling on a Moving Platform","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sparse array; Robustness (evolution); Degrees of freedom (physics and chemistry); Redundancy (engineering); Coupling (piping); Computer science; Algorithm; Sensor array; Array gain; Topology (electrical circuits); Mathematics; Antenna array; Physics; Telecommunications; Engineering; Combinatorics","score_opus":0.029255073480383788,"score_gpt":0.2506038047519542,"score_spread":0.22134873127157043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165395996","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":[0.3536979,0.000031286323,0.64576066,0.000013271385,0.00003484097,0.00011447444,0.000008703204,0.00011678425,0.0002220852],"genre_scores_gemma":[0.86683416,0.000012769627,0.13308829,0.0000130973785,0.000008908937,0.000014920912,0.0000019590125,0.000017516948,0.000008354429],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984437,0.00002475591,0.0005114883,0.00036043074,0.00046992445,0.00018969923],"domain_scores_gemma":[0.9985997,0.00020418066,0.00038108687,0.00026936136,0.0004609874,0.00008470174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025910485,0.00020530583,0.00036199339,0.0003525602,0.00017378211,0.00007044784,0.00024107205,0.000096328156,0.0000071865343],"category_scores_gemma":[0.000016694126,0.00018896826,0.00006848445,0.00096633995,0.0001715499,0.00075032626,0.0000049050236,0.00023678836,5.641593e-7],"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":[0.0003005702,0.00047781918,0.000042670858,0.00035171123,0.00009222702,0.000012948333,0.0018155453,0.34808525,0.5782634,0.00037066595,0.0000032854518,0.07018387],"study_design_scores_gemma":[0.00036932397,0.00028861107,0.00014542227,0.00084148796,0.00003027731,0.000018373657,0.00022133262,0.4611859,0.5366369,0.00013345227,0.0000012934562,0.00012759528],"about_ca_topic_score_codex":0.00014902651,"about_ca_topic_score_gemma":0.000032903743,"teacher_disagreement_score":0.51313627,"about_ca_system_score_codex":0.000056633606,"about_ca_system_score_gemma":0.00039633134,"threshold_uncertainty_score":0.77059025},"labels":[],"label_agreement":null},{"id":"W3167377032","doi":"10.1109/lgrs.2023.3238334","title":"How to Determine an Optimal Noise Subspace?","year":2023,"lang":"en","type":"article","venue":"IEEE Geoscience and Remote Sensing Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Subspace topology; Noise (video); Eigenvalues and eigenvectors; Signal subspace; Random subspace method; Orthogonality; Algorithm; Computer science; Mathematics; Covariance matrix; Pattern recognition (psychology); Speech recognition; Artificial intelligence; Physics","score_opus":0.02395594318138885,"score_gpt":0.2616533215347389,"score_spread":0.23769737835335006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3167377032","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":[0.46890017,0.0000018483122,0.5232637,0.0070596226,0.00035263703,0.00007857349,5.9056345e-7,0.00031680992,0.000026013744],"genre_scores_gemma":[0.40917408,0.000007782672,0.5889166,0.0016399848,0.00006233415,1.6427857e-7,6.9278093e-7,0.000009492658,0.00018888796],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986642,0.00004697776,0.00014982384,0.0004712971,0.0003370904,0.0003305855],"domain_scores_gemma":[0.9991711,0.00006284568,0.00008150394,0.00044567604,0.00007551693,0.00016336571],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041727792,0.00013083099,0.00015145949,0.00039669557,0.00018516202,0.00032935504,0.00039924658,0.000039628216,2.486358e-7],"category_scores_gemma":[0.000093988965,0.00012140989,0.000036090198,0.001256615,0.00017069836,0.00079857383,0.00011816592,0.00007889971,0.000009229263],"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":[0.0000031243642,0.0000045295037,0.000012852545,0.0000103467055,0.0000019042039,0.0000387532,0.00092334056,0.00036152708,0.4320957,0.000026742586,0.0008632709,0.5656579],"study_design_scores_gemma":[0.000086925225,0.00011677019,0.0017971476,0.00006986936,0.0000037309858,0.00008814374,0.00004745167,0.80004865,0.19643034,0.00017147709,0.00089766516,0.00024184278],"about_ca_topic_score_codex":0.00014383603,"about_ca_topic_score_gemma":0.000014674357,"teacher_disagreement_score":0.7996871,"about_ca_system_score_codex":0.000022749626,"about_ca_system_score_gemma":0.000029448584,"threshold_uncertainty_score":0.49509516},"labels":[],"label_agreement":null},{"id":"W3193636205","doi":"10.1109/lsp.2021.3104503","title":"Sparse Bayesian Learning Using Generalized Double Pareto Prior for DOA Estimation","year":2021,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; Guangzhou Municipal Science and Technology Bureau; National Natural Science Foundation of China; Ministry of Natural Resources","keywords":"Hyperparameter; Prior probability; Convergence (economics); Computer science; Bayesian probability; Algorithm; Pareto principle; Bayesian inference; Direction of arrival; Hyperparameter optimization; Mathematical optimization; Artificial intelligence; Pattern recognition (psychology); Mathematics; Support vector machine","score_opus":0.037807666731298525,"score_gpt":0.30254015479877117,"score_spread":0.2647324880674726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193636205","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":[0.05396175,0.000053849024,0.94418883,0.00087596965,0.00019849245,0.00022891226,0.000001017456,0.0003985252,0.000092627735],"genre_scores_gemma":[0.51190394,8.097771e-7,0.4876703,0.00029914142,0.000054166692,0.0000272743,0.0000050048743,0.000016351729,0.000023017394],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845916,0.00007794186,0.0004108738,0.00043240693,0.00033890863,0.00028071026],"domain_scores_gemma":[0.9989779,0.00008260968,0.00034825396,0.00022094735,0.00029954294,0.00007072627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037450754,0.00017688233,0.00024603461,0.00017025445,0.00031911168,0.0003556538,0.00033135043,0.00007078788,0.00000890419],"category_scores_gemma":[0.00005447631,0.00019343282,0.000098510616,0.000559871,0.000058466896,0.0010245527,0.000050509447,0.00014402613,0.0000023439063],"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":[0.0000392501,0.000055802022,0.00014855163,0.00031451468,0.000025292302,0.000013850515,0.00071537105,0.2228307,0.62290055,0.0009068272,0.00041125107,0.15163803],"study_design_scores_gemma":[0.0003566789,0.000020783014,0.000021947017,0.00014984139,0.000015621883,0.000018423792,0.000009833517,0.6342287,0.36401063,0.0008702479,0.00013990245,0.00015736741],"about_ca_topic_score_codex":0.000027634698,"about_ca_topic_score_gemma":0.000001961903,"teacher_disagreement_score":0.4579422,"about_ca_system_score_codex":0.00010139179,"about_ca_system_score_gemma":0.00023832184,"threshold_uncertainty_score":0.7887961},"labels":[],"label_agreement":null},{"id":"W3200738832","doi":"","title":"A Null Broadening Beamforming Approach Based on Covariance Matrix Expansion","year":2017,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Covariance matrix; Kronecker product; Beamforming; Estimation of covariance matrices; Covariance; Mathematics; Algorithm; Matrix (chemical analysis); Null (SQL); Applied mathematics; Mathematical optimization; Computer science; Kronecker delta; Statistics; Physics","score_opus":0.024150446319206518,"score_gpt":0.3065111529370001,"score_spread":0.28236070661779356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200738832","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":[0.0012136118,0.000004425883,0.95005745,0.00033794765,0.00015463197,0.00015963809,6.0885895e-7,0.00044395818,0.047627717],"genre_scores_gemma":[0.43193144,7.649841e-7,0.56761765,0.000090119065,0.000014295608,0.0000154662,7.4087865e-7,0.000005339729,0.00032422025],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989671,0.000024900679,0.00022278188,0.000303496,0.0003224464,0.00015925408],"domain_scores_gemma":[0.99842405,0.00006345801,0.0002532052,0.001090758,0.000115752606,0.000052744555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003732307,0.00011155738,0.0001487356,0.00013106642,0.00032173697,0.00025793994,0.0010731966,0.000060144997,0.000014731247],"category_scores_gemma":[0.00024471205,0.00010006138,0.000057914986,0.00012031766,0.00004628858,0.0008853688,0.00016887372,0.000096533964,0.000018221757],"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":[0.00006352906,0.0005562344,0.0011256369,0.00023223765,0.000025451627,0.000013414774,0.00087964744,0.019955266,0.020391252,0.5084588,0.0040915473,0.444207],"study_design_scores_gemma":[0.00020415036,0.00006961083,0.00078716886,0.000080667305,0.000002361925,0.0000049009423,0.000007513945,0.91620827,0.08033806,0.0016640321,0.0004988611,0.00013440473],"about_ca_topic_score_codex":0.00012040579,"about_ca_topic_score_gemma":0.0000010812462,"teacher_disagreement_score":0.896253,"about_ca_system_score_codex":0.000036456848,"about_ca_system_score_gemma":0.00006162588,"threshold_uncertainty_score":0.40803847},"labels":[],"label_agreement":null},{"id":"W3215663949","doi":"10.3390/electronics10232964","title":"Application of Differential Geometry to the Array Manifolds of Linear Arrays in Antenna Array Processing","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Taif University","keywords":"Algorithm; Direction of arrival; Antenna (radio); Intersection (aeronautics); Antenna array; MATLAB; Genetic algorithm; Set (abstract data type); Mathematics; Differential (mechanical device); Direction finding; Null (SQL); Computer science; Geometry; Topology (electrical circuits); Mathematical optimization; Physics; Combinatorics; Engineering; Telecommunications","score_opus":0.0088708483257693,"score_gpt":0.26003762795391555,"score_spread":0.25116677962814626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215663949","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":[0.03188927,0.00046683822,0.96659595,0.00044224117,0.00005499068,0.00015615024,0.0000022306324,0.000057291916,0.00033504554],"genre_scores_gemma":[0.91985315,0.00006549707,0.07993986,0.00004120012,0.00002522728,0.000023256816,0.000004708076,0.000008831661,0.00003828624],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99884623,0.000057553334,0.00037719533,0.00024555883,0.0002841108,0.00018932406],"domain_scores_gemma":[0.9989036,0.000053447868,0.0002312376,0.00047189492,0.00031286498,0.000026973574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024977874,0.0000933084,0.00020041595,0.0001427333,0.000039083774,0.000020930815,0.00047390687,0.000056546192,0.0000050020576],"category_scores_gemma":[0.00010743339,0.00008216603,0.00005486891,0.001387035,0.000027390399,0.00015131258,0.000065242086,0.00014407939,0.000002550594],"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":[0.000010517421,0.00020490465,0.00045573484,0.00011233989,0.000014356999,5.9482625e-7,0.00068301306,0.0005351439,0.9186016,0.016013287,0.00003048872,0.06333804],"study_design_scores_gemma":[0.000094039715,0.00007040084,0.0012791156,0.000051670613,0.0000064978394,0.0000057678567,0.000021770693,0.027966695,0.9652651,0.00426672,0.0008913076,0.00008091704],"about_ca_topic_score_codex":0.000012253567,"about_ca_topic_score_gemma":0.000051668932,"teacher_disagreement_score":0.8879639,"about_ca_system_score_codex":0.00006244059,"about_ca_system_score_gemma":0.000277395,"threshold_uncertainty_score":0.33506334},"labels":[],"label_agreement":null},{"id":"W4206664160","doi":"10.22215/etd/2021-14672","title":"Signal Processing Methods in Riemannian Geometry with Application to Drone Detection","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"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":"Riemannian geometry; Mathematics; Algorithm; Riemannian manifold; Covariance matrix; Information geometry; Computer science; Mathematical analysis; Geometry","score_opus":0.010255421059346008,"score_gpt":0.3441728962431909,"score_spread":0.3339174751838449,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206664160","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":[0.0042117587,0.000074517666,0.9886666,0.000048201062,0.0000940923,0.0005424728,6.3474016e-7,0.000376332,0.0059854183],"genre_scores_gemma":[0.21537177,0.000003831523,0.78310186,0.00004200327,0.000023389577,0.00035665484,0.00004850759,0.000025611678,0.0010263674],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99818224,0.00011256982,0.00048781707,0.0006283543,0.00040171496,0.00018729281],"domain_scores_gemma":[0.9986088,0.00007460347,0.00035895978,0.0004141157,0.00046920744,0.000074267766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005778367,0.00022805281,0.0003470977,0.0009515759,0.00007131685,0.00014723546,0.00046120345,0.00021195672,0.000020002599],"category_scores_gemma":[0.000059197748,0.00022278416,0.000048860464,0.00291678,0.000014269849,0.00051064923,0.00004974781,0.0002442805,0.0000060019474],"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":[0.000018888457,0.000063747844,0.000042395175,0.00021826336,0.000009053147,0.0000013865072,0.0006850755,0.00026491817,0.033949174,0.0008461561,0.000011669872,0.9638893],"study_design_scores_gemma":[0.00013206904,0.00016737246,0.004806948,0.00044995133,0.000017625098,0.000009370185,0.00030566409,0.06785575,0.92369133,0.0017541727,0.0004112424,0.00039850897],"about_ca_topic_score_codex":0.0003075595,"about_ca_topic_score_gemma":0.0009900475,"teacher_disagreement_score":0.9634908,"about_ca_system_score_codex":0.00015385676,"about_ca_system_score_gemma":0.00023515952,"threshold_uncertainty_score":0.90848744},"labels":[],"label_agreement":null},{"id":"W4206866472","doi":"10.1109/lwc.2022.3153927","title":"A Gridless Fourth-Order Cumulant-Based DOA Estimation Method Under Unknown Colored Noise","year":2022,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Algorithm; Redundancy (engineering); Computer science; Colors of noise; Gaussian noise; Minification; Direction of arrival; Rotational invariance; Gaussian; Colored; Noise (video); Mathematical optimization; Mathematics; Noise reduction; Artificial intelligence; Telecommunications","score_opus":0.03150678632848905,"score_gpt":0.31368492653889773,"score_spread":0.28217814021040866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206866472","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":[0.017884865,0.000031010703,0.961913,0.018260414,0.00035218717,0.000531542,0.000024294219,0.00071373495,0.00028893343],"genre_scores_gemma":[0.42700848,0.000008492802,0.57089907,0.0014937428,0.000009324707,0.00048450526,0.000052678773,0.000022557426,0.000021134316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970013,0.0010514123,0.0006291915,0.00042582676,0.00059862505,0.00029367438],"domain_scores_gemma":[0.9950737,0.00092428166,0.0005108385,0.0031343747,0.0002685233,0.000088311535],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009540473,0.00023971534,0.00033239962,0.0005233599,0.0008094739,0.00013399775,0.0036158676,0.000064924294,0.000027757405],"category_scores_gemma":[0.00006371713,0.0002783456,0.0001385852,0.0017295667,0.0002119177,0.00054893544,0.0007378662,0.00046480141,0.000014972421],"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":[0.000023028942,0.000481486,0.00009481756,0.000042557444,0.00006829892,0.000003476423,0.0009970831,0.8642604,0.050710607,0.044462018,0.0030886033,0.03576765],"study_design_scores_gemma":[0.0004432865,0.000052960557,0.00019934378,0.000035471356,0.000025618143,0.000017839133,0.000048899405,0.97315115,0.023011163,0.001072594,0.001645185,0.00029649597],"about_ca_topic_score_codex":0.00034479794,"about_ca_topic_score_gemma":0.000041244148,"teacher_disagreement_score":0.4091236,"about_ca_system_score_codex":0.00032072232,"about_ca_system_score_gemma":0.0002325823,"threshold_uncertainty_score":0.99996686},"labels":[],"label_agreement":null},{"id":"W4214488878","doi":"10.1109/access.2022.3153358","title":"Visibility Domain Direction-of-Arrival Optimization for Arbitrary 2-D Arrays","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Air Force Office of Scientific Research; Air Force Research Laboratory; Office of Naval Research; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Visibility; Azimuth; Computer science; Subspace topology; Antenna (radio); Elevation angle; Angle of arrival; Direction of arrival; Multiple signal classification; Algorithm; Direction finding; Elevation (ballistics); Antenna array; SIGNAL (programming language); Artificial intelligence; Optics; Mathematics; Telecommunications; Physics; Geometry","score_opus":0.026480248701957115,"score_gpt":0.31399518561264556,"score_spread":0.2875149369106884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214488878","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":[0.040993232,0.000020162955,0.95519924,0.0001794714,0.0011220743,0.00055830274,0.000030655377,0.00036320923,0.0015336722],"genre_scores_gemma":[0.698092,0.000004599627,0.30142426,0.00008814873,0.000044139008,0.00029193383,0.000010972772,0.000014077101,0.000029857958],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842346,0.00014017659,0.00047778364,0.00039109343,0.00039771557,0.00016978636],"domain_scores_gemma":[0.99852973,0.00023391616,0.00038002388,0.0005880905,0.00021760611,0.000050653125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007157334,0.00012619224,0.00023556102,0.00025254657,0.00023816682,0.000078752695,0.0012638659,0.000042850443,0.000079490135],"category_scores_gemma":[0.000101798316,0.0001401343,0.00012854132,0.0009068273,0.00005867657,0.0011396734,0.00025691182,0.00011802744,6.503368e-7],"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":[0.00032360674,0.0020222971,0.006860056,0.0007257442,0.00020881052,0.0000065327717,0.0033239867,0.7608326,0.023061657,0.08558558,0.011344489,0.10570463],"study_design_scores_gemma":[0.00066930574,0.00038101914,0.0018350771,0.00003287187,0.000020543579,0.000013265441,0.00005235553,0.57648873,0.32377765,0.09505573,0.0012763115,0.00039714453],"about_ca_topic_score_codex":0.00009913677,"about_ca_topic_score_gemma":0.0000034659831,"teacher_disagreement_score":0.65709877,"about_ca_system_score_codex":0.000101191676,"about_ca_system_score_gemma":0.00013147699,"threshold_uncertainty_score":0.5714511},"labels":[],"label_agreement":null},{"id":"W4226458335","doi":"10.1109/access.2022.3165038","title":"Large Direction-of-Arrival Mismatch Correction for Adaptive Beamforming","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Taishan University; Marine S&T Fund of Shandong Province; Polit National Laboratory for Marine Science and Technology; National Natural Science Foundation of China","keywords":"Beamforming; Adaptive beamformer; Direction of arrival; Computer science; Algorithm; Covariance matrix; Signal-to-noise ratio (imaging); Noise (video); Control theory (sociology); Telecommunications; Artificial intelligence; Antenna (radio)","score_opus":0.032084423369176475,"score_gpt":0.3192598056479817,"score_spread":0.2871753822788052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226458335","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":[0.026161622,0.000028092902,0.96685386,0.00008122843,0.004178079,0.0004925204,0.000030733623,0.00037713425,0.0017967115],"genre_scores_gemma":[0.965291,0.0000049889554,0.03381628,0.0000704816,0.000067822766,0.00039759133,0.000006688922,0.000017523607,0.00032761545],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99858844,0.000078420955,0.00040469773,0.00032077215,0.00038907267,0.00021857844],"domain_scores_gemma":[0.9986425,0.000261594,0.00041613617,0.000373277,0.00026040024,0.000046083922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056089554,0.0001282558,0.00023504179,0.00029887122,0.00034622327,0.00006152189,0.0010059011,0.000042847823,0.0000373093],"category_scores_gemma":[0.00009580865,0.00014395222,0.00012980103,0.0008603277,0.000031276486,0.001116742,0.00029349377,0.00011076547,0.0000015086721],"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":[0.00083104597,0.0032476063,0.009746893,0.0006889645,0.0005625969,0.000013150448,0.014694998,0.06044059,0.053798124,0.1375695,0.11077996,0.60762656],"study_design_scores_gemma":[0.00062305137,0.0005442228,0.0010969329,0.000054462278,0.000028549586,0.000030564246,0.00022251258,0.37276807,0.5978772,0.014253647,0.012134868,0.00036593055],"about_ca_topic_score_codex":0.00023588719,"about_ca_topic_score_gemma":0.00001938953,"teacher_disagreement_score":0.9391294,"about_ca_system_score_codex":0.00012856815,"about_ca_system_score_gemma":0.000105888765,"threshold_uncertainty_score":0.5870201},"labels":[],"label_agreement":null},{"id":"W4241079900","doi":"10.21203/rs.2.24042/v2","title":"Robust widely linear beamforming using estimation of extended covariance matrix and steering vector","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Queen's University","funders":"China Scholarship Council","keywords":"Covariance matrix; Estimation of covariance matrices; Covariance; Beamforming; Estimation; Computer science; Matrix (chemical analysis); Mathematics; Algorithm; Statistics; Engineering; Chemistry","score_opus":0.15044934530392814,"score_gpt":0.4209648531069188,"score_spread":0.2705155078029906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241079900","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":[0.020061454,0.00036337908,0.97798187,0.0002690185,0.00014908718,0.0007714582,0.000027608818,0.00026048752,0.00011567016],"genre_scores_gemma":[0.4436731,0.000049765975,0.55616724,0.0000024095089,0.00003722523,0.0000291923,0.000008873294,0.000018142271,0.000014055055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971555,0.00023715365,0.00060069276,0.000605602,0.001084073,0.00031701228],"domain_scores_gemma":[0.9975996,0.00036531014,0.0003753632,0.00071257877,0.0008117861,0.0001353327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015011604,0.00020644254,0.00043811894,0.0005374847,0.00014158996,0.00017484656,0.00084999914,0.00020397666,0.000007712012],"category_scores_gemma":[0.0012108549,0.00022571514,0.000089411245,0.000860357,0.00015024516,0.00055960956,0.001962313,0.0007323233,0.0000028776483],"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":[0.000079408055,0.00016659047,0.00025860575,0.011103127,0.00011757341,0.000030617502,0.002780411,0.8166838,0.024536658,0.06599544,0.000117936106,0.07812983],"study_design_scores_gemma":[0.000115497176,0.00011770913,0.000698269,0.0016399195,0.000008089555,0.0000081551725,0.000035099827,0.957503,0.032348767,0.0073259273,0.00003016091,0.00016937603],"about_ca_topic_score_codex":0.00043125823,"about_ca_topic_score_gemma":0.000004019451,"teacher_disagreement_score":0.42361164,"about_ca_system_score_codex":0.00020050337,"about_ca_system_score_gemma":0.0005179081,"threshold_uncertainty_score":0.9204396},"labels":[],"label_agreement":null},{"id":"W4242657727","doi":"10.21203/rs.2.24042/v1","title":"Robust widely linear beamforming using estimation of extended covariance matrix and steering vector","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Queen's University","funders":"","keywords":"Covariance matrix; Beamforming; Estimation of covariance matrices; Covariance; Estimation; Computer science; Matrix (chemical analysis); Mathematics; Algorithm; Statistics; Engineering; Chemistry","score_opus":0.15044934530392814,"score_gpt":0.4209648531069188,"score_spread":0.2705155078029906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242657727","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":[0.020061454,0.00036337908,0.97798187,0.0002690185,0.00014908718,0.0007714582,0.000027608818,0.00026048752,0.00011567016],"genre_scores_gemma":[0.4436731,0.000049765975,0.55616724,0.0000024095089,0.00003722523,0.0000291923,0.000008873294,0.000018142271,0.000014055055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971555,0.00023715365,0.00060069276,0.000605602,0.001084073,0.00031701228],"domain_scores_gemma":[0.9975996,0.00036531014,0.0003753632,0.00071257877,0.0008117861,0.0001353327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015011604,0.00020644254,0.00043811894,0.0005374847,0.00014158996,0.00017484656,0.00084999914,0.00020397666,0.000007712012],"category_scores_gemma":[0.0012108549,0.00022571514,0.000089411245,0.000860357,0.00015024516,0.00055960956,0.001962313,0.0007323233,0.0000028776483],"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":[0.000079408055,0.00016659047,0.00025860575,0.011103127,0.00011757341,0.000030617502,0.002780411,0.8166838,0.024536658,0.06599544,0.000117936106,0.07812983],"study_design_scores_gemma":[0.000115497176,0.00011770913,0.000698269,0.0016399195,0.000008089555,0.0000081551725,0.000035099827,0.957503,0.032348767,0.0073259273,0.00003016091,0.00016937603],"about_ca_topic_score_codex":0.00043125823,"about_ca_topic_score_gemma":0.000004019451,"teacher_disagreement_score":0.42361164,"about_ca_system_score_codex":0.00020050337,"about_ca_system_score_gemma":0.0005179081,"threshold_uncertainty_score":0.9204396},"labels":[],"label_agreement":null},{"id":"W4245461059","doi":"10.22215/etd/2014-10412","title":"Sinusoidal Parameter Estimation and Application to Eddy Current NDT Data Records","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Waveform; Interference (communication); Eddy current; Noise (video); Nondestructive testing; Algorithm; Power (physics); Harmonic; Process (computing); Estimation theory; Computer science; Acoustics; Engineering; Artificial intelligence; Physics; Electrical engineering; Telecommunications","score_opus":0.02299825523455791,"score_gpt":0.3415485090813148,"score_spread":0.3185502538467569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245461059","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":[0.0019168485,0.00005824399,0.99368584,0.00013742344,0.0006584225,0.0007412278,0.000017484896,0.00045757764,0.0023269064],"genre_scores_gemma":[0.098111875,0.00004407915,0.8985628,0.000088569795,0.00009202472,0.00026609492,0.0020121112,0.000034466844,0.0007879939],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979852,0.000064245745,0.00054892607,0.0008276575,0.0004091984,0.00016480219],"domain_scores_gemma":[0.9974243,0.00018426776,0.00040946933,0.0016027599,0.0002682863,0.0001109369],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00048315868,0.00025213827,0.00031617197,0.00037206948,0.00007642663,0.00020519759,0.0012767737,0.00016494836,0.000012100723],"category_scores_gemma":[0.00040841365,0.00025086297,0.000037853337,0.00042054133,0.000020598862,0.00079453323,0.00026214815,0.00017493598,0.000056384335],"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":[0.000008162223,0.00004311987,0.000029174273,0.00017008698,0.000008489158,7.459588e-8,0.00015596638,0.00008104579,0.00016572073,0.0105954725,0.004843909,0.98389876],"study_design_scores_gemma":[0.00012817951,0.00013719681,0.0023610613,0.00031808458,0.000037168193,0.000003846953,0.0000139962585,0.95612276,0.011416123,0.017613994,0.011344093,0.00050350133],"about_ca_topic_score_codex":0.00018998439,"about_ca_topic_score_gemma":0.00017322172,"teacher_disagreement_score":0.9833953,"about_ca_system_score_codex":0.000049417493,"about_ca_system_score_gemma":0.000096617914,"threshold_uncertainty_score":0.99999434},"labels":[],"label_agreement":null},{"id":"W4251398499","doi":"10.22215/etd/2020-14180","title":"Semi-Parametric Inference with Density Ratio Model Fitted to Distributed Data using Alternating Direction Method of Multipliers","year":2020,"lang":"en","type":"dissertation","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Inference; Statistical inference; Quantile; Parametric statistics; Computer science; Parametric model; Empirical likelihood; Sampling distribution; Sample (material); Algorithm; Mathematics; Data mining; Statistics; Artificial intelligence","score_opus":0.0726198242290373,"score_gpt":0.3769970332824413,"score_spread":0.304377209053404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251398499","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":[0.025902526,0.0000075246194,0.9722877,0.000033134667,0.00018466878,0.00057263183,0.00008355202,0.00043455942,0.00049371284],"genre_scores_gemma":[0.36451143,0.000004441729,0.63472044,0.000020253692,0.000010267075,0.000014043756,0.00064753444,0.000017721586,0.000053862168],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973993,0.00012811784,0.00072366686,0.0008616988,0.0006873646,0.00019990209],"domain_scores_gemma":[0.99658555,0.00037628767,0.0009373573,0.0011054532,0.00086643064,0.00012892371],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004730534,0.00031509876,0.00058249704,0.0006062983,0.00010577134,0.00012305644,0.0014321185,0.00017773958,0.0000042998026],"category_scores_gemma":[0.001640093,0.00030329297,0.000061064726,0.0026769736,0.000022214543,0.00090290117,0.00036221545,0.00027552142,0.0000015193228],"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":[0.00028332684,0.00031313836,0.0017315557,0.0010073753,0.00042761394,0.000007977578,0.0030897951,0.74972475,0.107481316,0.008630631,0.00052801636,0.12677453],"study_design_scores_gemma":[0.00010894633,0.00005764015,0.00048157788,0.00019451398,0.000049047023,0.0000025828724,0.00005409165,0.7684207,0.23007436,0.0003172337,0.000005458549,0.00023384685],"about_ca_topic_score_codex":0.0013227239,"about_ca_topic_score_gemma":0.00021645986,"teacher_disagreement_score":0.3386089,"about_ca_system_score_codex":0.00014668964,"about_ca_system_score_gemma":0.00040628464,"threshold_uncertainty_score":0.99994195},"labels":[],"label_agreement":null},{"id":"W4254780092","doi":"10.1002/9780470827253.ch4","title":"Farfield Array Signal Processing Algorithms","year":2013,"lang":"en","type":"other","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Beamforming; Robustness (evolution); Array processing; Signal processing; Sensor array; Computer science; Algorithm; High resolution; Adaptive beamformer; SIGNAL (programming language); Noise (video); Electronic engineering; Engineering; Artificial intelligence; Telecommunications; Digital signal processing; Computer hardware; Remote sensing; Machine learning","score_opus":0.015119152523529286,"score_gpt":0.2638128787557232,"score_spread":0.24869372623219388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254780092","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":[5.4380973e-8,0.0000715708,0.5192374,0.00005861204,0.00009008979,0.00011556687,6.792334e-7,0.0009030485,0.47952297],"genre_scores_gemma":[0.00013588007,0.000009610481,0.5351388,0.0000914283,0.00007496177,0.000029455157,0.0000015744743,0.00006574587,0.46445253],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990362,0.000021512133,0.00021147114,0.00030792618,0.0002760446,0.00014688083],"domain_scores_gemma":[0.999242,0.000024077617,0.00024237325,0.0003620643,0.00007847029,0.000051032162],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000088397006,0.00017218197,0.00022189373,0.00027804784,0.000025179175,0.000120995835,0.0007265982,0.00019804458,0.0024324837],"category_scores_gemma":[0.000010149373,0.00014639396,0.000055328266,0.0002637712,0.00004129901,0.00023951617,0.00008252344,0.00012477789,0.00017871855],"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":[1.4557418e-7,0.000025069427,0.0000036517115,0.000070975926,0.0000107069645,6.599782e-7,0.000043727487,0.0000010701003,0.00017427941,0.009110829,0.43829817,0.5522607],"study_design_scores_gemma":[0.000154778,0.00012280067,0.000014253511,0.0007415225,0.000014886506,0.0000149852685,0.000014167699,0.059414756,0.06672314,0.0069143316,0.8650656,0.0008047913],"about_ca_topic_score_codex":0.00035962297,"about_ca_topic_score_gemma":0.0000053870426,"teacher_disagreement_score":0.5514559,"about_ca_system_score_codex":0.000016136937,"about_ca_system_score_gemma":0.00008003139,"threshold_uncertainty_score":0.9984794},"labels":[],"label_agreement":null},{"id":"W4297268591","doi":"10.3390/app12199726","title":"An Efficient FPGA Implementation of MUSIC Processor Using Cyclic Jacobi Method: LiDAR Applications","year":2022,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Singular value decomposition; Field-programmable gate array; Eigenvalues and eigenvectors; Singular value; Lidar; Position (finance); Algorithm; Jacobian matrix and determinant; Jacobi method; Jacobi eigenvalue algorithm; Mathematical optimization; Mathematics; Computer hardware; Applied mathematics","score_opus":0.04063495712668336,"score_gpt":0.37728068449618035,"score_spread":0.336645727369497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297268591","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":[0.13200244,0.000015844942,0.86584234,0.0000541061,0.0000660618,0.0005950869,0.0000082771785,0.00016354275,0.0012523264],"genre_scores_gemma":[0.6572017,4.6086436e-7,0.34245208,0.0000464282,0.00000934776,0.00028191687,0.0000021532799,0.000003886772,0.000002029831],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99819,0.00009068271,0.00039487588,0.0004462997,0.00068529433,0.00019286826],"domain_scores_gemma":[0.99895144,0.00009970968,0.00042981666,0.00037146691,0.00009641553,0.000051176175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014865471,0.000101217935,0.00016038175,0.00035295013,0.000580012,0.00006783758,0.0012188863,0.000019235458,0.000056068297],"category_scores_gemma":[0.000008611666,0.00010161806,0.00003828957,0.002365596,0.00016941287,0.0002879497,0.00025953827,0.00007496548,0.0000016404981],"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":[0.0000066695266,0.0003988857,0.00039708943,0.00006690593,0.000014155847,3.0525266e-7,0.005321734,0.08878272,0.29536328,0.24045987,0.000050670664,0.36913773],"study_design_scores_gemma":[0.00016782478,0.00023763158,0.0011291072,0.0000059221143,0.000015173473,0.000007863796,0.0024197078,0.16450341,0.8165901,0.014355453,0.00034954998,0.00021825865],"about_ca_topic_score_codex":0.00017147756,"about_ca_topic_score_gemma":0.000008547391,"teacher_disagreement_score":0.52519923,"about_ca_system_score_codex":0.000063801264,"about_ca_system_score_gemma":0.0002521468,"threshold_uncertainty_score":0.4461042},"labels":[],"label_agreement":null},{"id":"W4311238878","doi":"10.18280/mmep.090534","title":"Off-Grid Based DOA Estimation Algorithm Using Auto-Regression (1) Sparse Bayesian Learning with Linear Interpolation Model","year":2022,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Algorithm; Grid; Computer science; Interpolation (computer graphics); Bayesian inference; Bayesian probability; Hyperparameter optimization; Pattern recognition (psychology); Mathematical optimization; Mathematics; Artificial intelligence; Support vector machine; Image (mathematics)","score_opus":0.023900499223152634,"score_gpt":0.24032086635344266,"score_spread":0.21642036713029003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311238878","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":[0.0034862678,0.00003565616,0.9955791,0.000049564638,0.000050002727,0.00021278614,0.0000031725006,0.0005401047,0.00004334297],"genre_scores_gemma":[0.3392108,0.000002216459,0.6607023,0.0000049306846,0.000007931123,0.00003494287,0.0000052687637,0.000019309398,0.0000122893525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877065,0.000038107886,0.00035580492,0.00028084652,0.00036117158,0.00019342982],"domain_scores_gemma":[0.9993869,0.000096064716,0.00015173969,0.00022217745,0.00006856719,0.00007453151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048086356,0.00017874563,0.00023042517,0.00023750064,0.00019129024,0.000062986066,0.00019928232,0.000048964495,0.0000063433213],"category_scores_gemma":[0.000030546642,0.00015997865,0.000040194886,0.00031834238,0.000022860266,0.00036101614,0.000121045894,0.0002829803,7.2162004e-7],"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":[0.0000034787522,0.00004408954,0.0000029369787,0.00017153,0.000007345944,8.8765165e-7,0.0005795536,0.9884423,0.00044825018,0.0035457648,0.0000018479309,0.0067520225],"study_design_scores_gemma":[0.00015227405,0.00010082649,5.0551745e-7,0.00039194955,0.000014193313,0.000020326286,0.000011914262,0.9920542,0.0007646762,0.0062896167,0.0000145848935,0.00018492404],"about_ca_topic_score_codex":0.0000109311795,"about_ca_topic_score_gemma":6.44806e-8,"teacher_disagreement_score":0.33572453,"about_ca_system_score_codex":0.000063663734,"about_ca_system_score_gemma":0.000042050313,"threshold_uncertainty_score":0.652374},"labels":[],"label_agreement":null},{"id":"W4317419696","doi":"10.1109/vtc2022-fall57202.2022.10012869","title":"A Low-Complexity DNN-Based DoA Estimation Method for EHF and THF Cell-Free Massive MIMO","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"MIMO; Computer science; Algorithm; Snapshot (computer storage); Array processing; Computational complexity theory; Quantization (signal processing); Direction of arrival; Artificial neural network; Wireless; Channel (broadcasting); Antenna (radio); Artificial intelligence; Signal processing; Telecommunications","score_opus":0.021892675571993495,"score_gpt":0.2802801848746755,"score_spread":0.258387509302682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317419696","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":[0.030442568,0.00015448662,0.9597561,0.005613094,0.00049796765,0.0014971878,0.00014190732,0.0014770385,0.00041966318],"genre_scores_gemma":[0.43167138,0.000014234898,0.5663346,0.0003343039,0.000017572665,0.001433737,0.00005043583,0.000037496116,0.00010623982],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99624133,0.00033886262,0.0007922892,0.0012350722,0.00076460047,0.0006278388],"domain_scores_gemma":[0.9963251,0.00044348897,0.000742393,0.0018421711,0.0005135164,0.00013336285],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012862318,0.00047511316,0.0007149998,0.0011127455,0.00072923646,0.00014601034,0.002735457,0.000347257,0.000096055395],"category_scores_gemma":[0.00052664673,0.0005302749,0.00021048951,0.0019005004,0.0004624673,0.00045070605,0.0011122694,0.00082111615,0.000008264978],"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":[0.000181214,0.0013214727,0.0009357303,0.0008168673,0.00021701155,0.0001095644,0.00084989355,0.019142183,0.09328805,0.69273263,0.0067811674,0.18362421],"study_design_scores_gemma":[0.0010988121,0.0005827401,0.0001157736,0.00004499216,0.000055608074,0.00003742892,0.00015451014,0.6728455,0.14704952,0.17612177,0.0014061662,0.00048720292],"about_ca_topic_score_codex":0.00019640799,"about_ca_topic_score_gemma":0.00008502122,"teacher_disagreement_score":0.6537033,"about_ca_system_score_codex":0.00030328732,"about_ca_system_score_gemma":0.0005420069,"threshold_uncertainty_score":0.99971485},"labels":[],"label_agreement":null},{"id":"W4320005477","doi":"10.1109/lsp.2023.3242808","title":"Off-Grid DOA Estimation for Noncircular Signals via Block Sparse Representation Using Extended Transformed Nested Array","year":2023,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Natural Science Foundation of China","keywords":"Block (permutation group theory); Computer science; Grid; Representation (politics); Algorithm; Interpolation (computer graphics); Direction of arrival; SIGNAL (programming language); Displacement (psychology); Computer vision; Mathematics; Antenna (radio); Telecommunications; Motion (physics)","score_opus":0.04545425219593095,"score_gpt":0.318474727682301,"score_spread":0.27302047548637004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320005477","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":[0.10356185,0.00002551141,0.89363366,0.000707567,0.00030443745,0.00082533294,0.000005554581,0.0009091113,0.000026967158],"genre_scores_gemma":[0.80926627,0.0000026896926,0.19004439,0.00036233952,0.00011732288,0.00013717481,0.000025756459,0.00003575188,0.000008291124],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99762404,0.00010571556,0.00068607286,0.00057177234,0.00061605347,0.00039637592],"domain_scores_gemma":[0.9985764,0.00023010885,0.00046439553,0.00032044016,0.00031484518,0.00009378576],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007000616,0.0002517246,0.00033705268,0.00053136615,0.0002914926,0.0002406878,0.00049123744,0.00010426236,0.000004608056],"category_scores_gemma":[0.00007969838,0.0002689648,0.00015778509,0.0015713007,0.00010410511,0.0015831261,0.000020457805,0.0001305121,0.000009499363],"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":[0.00002146482,0.000037976577,0.000017659728,0.00027434554,0.000019362345,0.0000057258285,0.0006235242,0.1196228,0.7985046,0.000020151216,0.00023559757,0.08061678],"study_design_scores_gemma":[0.00024255257,0.00003475585,0.00010848975,0.0002953998,0.000025251187,0.000016624717,0.00001103097,0.5523139,0.44578502,0.00097154564,0.000013936642,0.00018146675],"about_ca_topic_score_codex":0.000029285586,"about_ca_topic_score_gemma":0.0000015413232,"teacher_disagreement_score":0.70570445,"about_ca_system_score_codex":0.000110841574,"about_ca_system_score_gemma":0.00018239129,"threshold_uncertainty_score":0.9999763},"labels":[],"label_agreement":null},{"id":"W4376132931","doi":"10.1371/journal.pone.0285459","title":"Multiple co-frequency sources DOA estimation for coprime vector sensor arrays","year":2023,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Polit National Laboratory for Marine Science and Technology; National Natural Science Foundation of China; Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Coprime integers; Computer science; Beamforming; Direction of arrival; Algorithm; Hydrophone; Acoustics; Antenna (radio); Physics; Telecommunications","score_opus":0.058433826649611775,"score_gpt":0.2804281283620042,"score_spread":0.22199430171239243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376132931","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":[0.17013748,0.000014986818,0.8255324,0.0006486751,0.00010267718,0.0007243878,0.000034097946,0.0020599382,0.00074537925],"genre_scores_gemma":[0.4266546,0.0000066308476,0.572855,0.0000370877,0.0000407351,0.0001617423,0.000029085331,0.00001534358,0.00019977865],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99880725,0.00003831427,0.00029290924,0.00028113244,0.00037291177,0.00020745725],"domain_scores_gemma":[0.9987016,0.00042696745,0.0001755159,0.00041144132,0.0002232976,0.00006121427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029595656,0.00011805514,0.00021570866,0.00022085522,0.00011784991,0.000074313626,0.00040888443,0.000065386404,0.000014460985],"category_scores_gemma":[0.0007929791,0.00012378,0.00006126058,0.00052626344,0.00004598348,0.00042434095,0.00005590452,0.000067234454,0.00015225128],"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":[0.000035244477,0.0013706775,0.00544505,0.0008822309,0.0002654387,0.000004913552,0.0026511925,0.0016071534,0.93598545,0.028843781,0.0038130002,0.019095879],"study_design_scores_gemma":[0.00019057043,0.00010248927,0.0013986442,0.000087395296,0.000014878609,7.152051e-7,0.00000860289,0.40032694,0.59123236,0.006468927,0.000046631758,0.00012186946],"about_ca_topic_score_codex":0.000039594423,"about_ca_topic_score_gemma":0.000003028547,"teacher_disagreement_score":0.3987198,"about_ca_system_score_codex":0.000046290777,"about_ca_system_score_gemma":0.00005027746,"threshold_uncertainty_score":0.5047602},"labels":[],"label_agreement":null},{"id":"W4376456276","doi":"10.1109/tgrs.2023.3274182","title":"Direction-of-Arrival Estimation for Nested Acoustic Vector-Sensor Arrays Using Quaternions","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Quaternion; Direction of arrival; Computer science; Smoothing; Algorithm; Covariance matrix; Noise (video); Computational complexity theory; Underwater; Artificial intelligence; Mathematics; Computer vision; Telecommunications","score_opus":0.033419566558927076,"score_gpt":0.2973973767507486,"score_spread":0.26397781019182154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376456276","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":[0.08843589,0.000004586966,0.90955085,0.00015807558,0.0010346412,0.00032205012,0.000010824298,0.0004516079,0.00003146177],"genre_scores_gemma":[0.58656764,0.000017176668,0.4133094,0.000014777968,0.000014719501,7.238149e-7,9.359092e-7,0.000010974013,0.00006364413],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848795,0.000066451124,0.0004101629,0.0004215399,0.0003359607,0.00027794365],"domain_scores_gemma":[0.99873364,0.00038249587,0.00021571408,0.00034164827,0.0002393631,0.00008714897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044329627,0.00017080219,0.00024565976,0.0006344865,0.00049714284,0.00008383012,0.00019860527,0.0000912928,0.0000011323882],"category_scores_gemma":[0.00008220841,0.00016867756,0.00010796411,0.0016186289,0.0002029866,0.0005297669,0.000005515353,0.00011636107,0.0000033547635],"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":[0.000019976987,0.00004456072,0.0000021793892,0.00011293332,0.000019832647,0.0000026830041,0.00086296105,0.09736306,0.23747815,0.0001429544,0.000010214999,0.6639405],"study_design_scores_gemma":[0.00013653302,0.00010210897,0.00026189277,0.00017141693,0.000024603185,0.000030413057,0.00006288866,0.82905114,0.16906402,0.00094193465,0.000011494261,0.00014154724],"about_ca_topic_score_codex":0.00042010285,"about_ca_topic_score_gemma":0.000027218439,"teacher_disagreement_score":0.7316881,"about_ca_system_score_codex":0.00005720455,"about_ca_system_score_gemma":0.00010851323,"threshold_uncertainty_score":0.68784714},"labels":[],"label_agreement":null},{"id":"W4376464607","doi":"10.1109/jsen.2023.3273401","title":"Two-Dimensional Minimum Sensor Array: A New Perspective to Array Design","year":2023,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Planar array; Sensor array; Binary number; Planar; Computer science; Algorithm; Nonlinear programming; Sparse array; Linear programming; Optimization problem; Mathematical optimization; Nonlinear system; Mathematics; Telecommunications; Physics","score_opus":0.040852421971739585,"score_gpt":0.31421720459507596,"score_spread":0.27336478262333636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376464607","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":[0.049806215,0.000022940587,0.94044554,0.004806016,0.0017826435,0.0003195928,0.0000038454755,0.00070577784,0.0021074486],"genre_scores_gemma":[0.18278857,0.000010109445,0.81332487,0.0005023178,0.0006674105,0.000008435672,5.606486e-7,0.00004190227,0.002655811],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975889,0.00026554696,0.00049337134,0.00041976952,0.0007855287,0.0004469203],"domain_scores_gemma":[0.9979075,0.0003791089,0.00028004046,0.00041697477,0.0005637446,0.00045259175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008792731,0.00023412144,0.0003162947,0.00078030693,0.00023548244,0.00020417255,0.0006376818,0.00007728773,0.00005888398],"category_scores_gemma":[0.00041683836,0.00022052763,0.00018081204,0.0014665885,0.000056707922,0.00050437363,0.000052106574,0.00035501723,0.00041875604],"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":[0.00011355903,0.00012005617,0.00005172871,0.000009812066,0.00014620814,0.00024219575,0.007284715,0.12403232,0.714219,0.003373951,0.14306433,0.007342141],"study_design_scores_gemma":[0.0008223657,0.000535329,0.00044849026,0.00018424129,0.000026671963,0.0014974385,0.00047166276,0.028379615,0.9267717,0.038891375,0.0013863031,0.000584832],"about_ca_topic_score_codex":0.00006377789,"about_ca_topic_score_gemma":0.000002888824,"teacher_disagreement_score":0.2125527,"about_ca_system_score_codex":0.00021557654,"about_ca_system_score_gemma":0.00041413435,"threshold_uncertainty_score":0.89928555},"labels":[],"label_agreement":null},{"id":"W4384575251","doi":"10.23952/jnva.7.2023.4.02","title":"Sparse broadband beamformer design via proximal optimization Techniques","year":2023,"lang":"en","type":"article","venue":"Journal of Nonlinear and Variational Analysis","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Robustness (evolution); Adaptive beamformer; Beamforming; Computer science; Term (time); Optimization problem; Algorithm; Recursive least squares filter; Mathematical optimization; Regularization (linguistics); Least-squares function approximation; Adaptive filter; Mathematics; Telecommunications; Artificial intelligence","score_opus":0.0208525109966032,"score_gpt":0.274930023273085,"score_spread":0.25407751227648184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384575251","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":[0.0010432386,0.000022221315,0.9981171,0.000503034,0.000048809394,0.000079392055,0.000004787392,0.00007948891,0.00010196492],"genre_scores_gemma":[0.051968012,0.00009599382,0.9477165,0.000045516936,0.00008979256,0.000004264629,0.000012859092,0.0000057105613,0.000061370236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987086,0.000080264064,0.0005460932,0.00013597292,0.00042949908,0.000099555684],"domain_scores_gemma":[0.99848026,0.00016788971,0.00054531195,0.00013007964,0.0006128522,0.00006361099],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001027435,0.000093750714,0.00026864835,0.0010342764,0.00007834727,0.0000756581,0.00024222094,0.000060322833,0.00003057262],"category_scores_gemma":[0.00013859727,0.00007821744,0.00015902433,0.0021168643,0.000028117467,0.00070861966,0.000055569042,0.00009259247,0.0000020474874],"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":[0.00015542154,0.00052379677,0.0066198693,0.000064606524,0.002530709,0.000017431961,0.0008390114,0.90258956,0.0071894326,0.010237797,0.0012430476,0.067989305],"study_design_scores_gemma":[0.00011989372,0.00015149522,0.0038935537,0.000014895291,0.00022319403,0.000021740327,0.000004953151,0.9857092,0.0062124655,0.0033604214,0.00020092493,0.000087300774],"about_ca_topic_score_codex":0.000015047151,"about_ca_topic_score_gemma":9.884617e-7,"teacher_disagreement_score":0.083119586,"about_ca_system_score_codex":0.000028891265,"about_ca_system_score_gemma":0.00010099478,"threshold_uncertainty_score":0.31896144},"labels":[],"label_agreement":null},{"id":"W4388126712","doi":"10.3390/electronics12214501","title":"Robust Adaptive Beamforming for Interference Suppression Based on SNR","year":2023,"lang":"en","type":"article","venue":"Electronics","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China; Qingdao Agricultural University","keywords":"Adaptive beamformer; Covariance matrix; Beamforming; Interference (communication); Signal-to-interference-plus-noise ratio; Algorithm; Control theory (sociology); Noise (video); Noise power; Subspace topology; Zero-forcing precoding; Quadratic programming; Computer science; Mathematics; Power (physics); Mathematical optimization; Telecommunications; MIMO; Precoding; Artificial intelligence","score_opus":0.04036966231173403,"score_gpt":0.2828123081585482,"score_spread":0.24244264584681416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388126712","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":[0.0013649183,0.000030270941,0.9962065,0.00030149694,0.00017005122,0.00025240734,0.0000047131407,0.0005965712,0.0010730627],"genre_scores_gemma":[0.70054483,0.000029622799,0.2988076,0.0001356608,0.000029684234,0.00013904595,0.000018047602,0.000018959312,0.00027656945],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910045,0.00002817083,0.00017399223,0.00024578453,0.00018445375,0.00026717156],"domain_scores_gemma":[0.99917483,0.00026219012,0.00010197514,0.00031858776,0.00010750386,0.000034905785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030753558,0.0000990719,0.00011860687,0.00020071336,0.00008610631,0.000036117104,0.00047696827,0.000052062667,0.000005510345],"category_scores_gemma":[0.00014162065,0.0000938413,0.000059560174,0.00052222336,0.000018994724,0.00024616998,0.0000751715,0.000117410345,0.000013390654],"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":[0.00021873486,0.0002561126,0.00007551283,0.00012991358,0.000039136296,0.000003372203,0.00083987985,0.11013834,0.02269308,0.30661827,0.023980822,0.5350068],"study_design_scores_gemma":[0.000118906035,0.0005315827,0.0000305833,0.00006580542,0.0000023731166,5.8486586e-7,0.000005149368,0.76694816,0.22234578,0.007162953,0.0027017626,0.00008634659],"about_ca_topic_score_codex":0.0000033912706,"about_ca_topic_score_gemma":0.0000058117403,"teacher_disagreement_score":0.6991799,"about_ca_system_score_codex":0.00010339104,"about_ca_system_score_gemma":0.0001464225,"threshold_uncertainty_score":0.3826737},"labels":[],"label_agreement":null},{"id":"W4390666312","doi":"10.3389/fmars.2023.1329898","title":"Broadband high-resolution direction of arrival estimation using the generalized weighted Radon transform","year":2024,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"Azimuth; Robustness (evolution); Algorithm; Radon transform; Wavenumber; Computer science; Direction of arrival; Beamforming; Deconvolution; Broadband; Energy (signal processing); Frequency domain; Time domain; Mathematics; Telecommunications; Statistics; Optics; Physics; Antenna (radio); Artificial intelligence; Computer vision","score_opus":0.010127460366925443,"score_gpt":0.26093300794087987,"score_spread":0.2508055475739544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390666312","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":[0.10506669,0.00007758698,0.89159226,0.00043091286,0.0018734427,0.0002769987,0.0000018841686,0.00018960793,0.00049061544],"genre_scores_gemma":[0.49843594,0.000023571065,0.50146854,0.000010022642,0.000016053731,0.000009769693,0.0000016341703,0.00000461939,0.000029812065],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983407,0.00007665691,0.0004178715,0.00037063184,0.0005760582,0.00021803117],"domain_scores_gemma":[0.9992832,0.00004614018,0.00013226006,0.0003628846,0.0001350952,0.000040431307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012819059,0.00012299279,0.000190682,0.0007293369,0.0001511429,0.00013880168,0.00072705327,0.00004960055,0.0000060553],"category_scores_gemma":[0.00009501846,0.000096992684,0.00005881576,0.0030529913,0.0004359643,0.0014878557,0.0001583234,0.00013180403,5.8936786e-7],"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":[0.000036933783,0.00008220082,0.0025292146,0.0001593115,0.000018526274,0.0000031960965,0.0012036609,0.017346425,0.04164048,0.042422056,0.0006956467,0.89386237],"study_design_scores_gemma":[0.00012573451,0.000041007705,0.0040685167,0.00006920205,0.000009411441,0.000007827807,0.000011940643,0.8398571,0.1173862,0.03820116,0.00012908413,0.0000928288],"about_ca_topic_score_codex":0.0005179066,"about_ca_topic_score_gemma":0.000008187798,"teacher_disagreement_score":0.8937695,"about_ca_system_score_codex":0.00025297308,"about_ca_system_score_gemma":0.00018399197,"threshold_uncertainty_score":0.3955247},"labels":[],"label_agreement":null},{"id":"W4391895194","doi":"10.1109/csrswtc60855.2023.10427537","title":"A Fast MUSIC Algorithm for High-Quality Real-Time Point Clouds Acquisition","year":2023,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Science Foundation of Fujian Province; National Key Research and Development Program of China; Fujian Provincial Department of Science and Technology; Fuzhou Science and Technology Bureau","keywords":"Computer science; Point cloud; Quality (philosophy); Algorithm; Point (geometry); Artificial intelligence; Mathematics","score_opus":0.02562648061626548,"score_gpt":0.3045049962278212,"score_spread":0.2788785156115557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391895194","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":[0.0061015845,0.000001191164,0.98616123,0.0005851136,0.00027574465,0.00035337472,0.000021625163,0.0024060286,0.0040941215],"genre_scores_gemma":[0.068608075,0.000007150762,0.928576,0.0001882876,0.000086499465,0.00014379683,0.000047380727,0.000015856984,0.0023269588],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987786,0.000068140514,0.00035811326,0.00032095774,0.00027200475,0.00020222377],"domain_scores_gemma":[0.9988864,0.00021748526,0.00014738906,0.00046596996,0.00022375863,0.00005897568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008332893,0.00011036458,0.00019262689,0.00018098552,0.0000854859,0.00006545619,0.0004032684,0.000064821215,0.000100514284],"category_scores_gemma":[0.000058129306,0.000105735715,0.000086336375,0.00076156703,0.00003543046,0.00046901967,0.00017140314,0.00003968533,0.00017210431],"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":[0.000007290483,0.00009881949,0.000013341906,0.00005159502,0.000024698658,0.0000021953576,0.00042597114,0.00006371288,0.033401486,0.3060424,0.023867005,0.63600147],"study_design_scores_gemma":[0.00043078844,0.00026568843,0.005888435,0.000041245577,0.00000894346,0.0000051334832,0.000032968062,0.62494826,0.22840573,0.13940234,0.0002620622,0.00030841792],"about_ca_topic_score_codex":0.00029559588,"about_ca_topic_score_gemma":0.000003583702,"teacher_disagreement_score":0.6356931,"about_ca_system_score_codex":0.000055398454,"about_ca_system_score_gemma":0.000049626833,"threshold_uncertainty_score":0.4311777},"labels":[],"label_agreement":null},{"id":"W4392745501","doi":"10.1109/access.2024.3377246","title":"Direct One-Bit DOA Estimation Robust in Presence of Unequal Power Signals","year":2024,"lang":"en","type":"article","venue":"IEEE Access","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast; Leverhulme Trust; National Aeronautics and Space Administration","keywords":"Covariance matrix; Computer science; Beamforming; Algorithm; Smoothing; Quantization (signal processing); Covariance; Radar; Antenna array; Antenna (radio); Mathematics; Telecommunications; Statistics; Computer vision","score_opus":0.05034519567925337,"score_gpt":0.34108749796992577,"score_spread":0.2907423022906724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392745501","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":[0.059170794,0.00014702653,0.933854,0.00018402608,0.00056743115,0.00025166123,0.0000060760267,0.00038900145,0.0054300185],"genre_scores_gemma":[0.95890504,0.000012867324,0.040932126,0.000027819264,0.000015387286,0.0000374594,0.0000013667477,0.000009731066,0.00005820132],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99862593,0.000083092214,0.0004325285,0.00031755195,0.0003893528,0.00015156418],"domain_scores_gemma":[0.9989318,0.00036951856,0.00013845379,0.0003879329,0.00013468668,0.00003760869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005125645,0.000110660134,0.00021088844,0.00040343255,0.00002281579,0.00021178536,0.00096405396,0.000065982684,0.000043182663],"category_scores_gemma":[0.0001807168,0.0001097232,0.0000535906,0.0012256711,0.00005545785,0.0021425153,0.0001494744,0.0001056311,0.0000129295095],"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":[0.000048146896,0.00074281,0.0028785565,0.0013322408,0.00011202225,0.000056568737,0.0038211262,0.5772203,0.06674575,0.06691346,0.008478044,0.27165094],"study_design_scores_gemma":[0.000068695896,0.000057528167,0.0022323322,0.00046417722,0.0000054779084,0.0000016770902,0.0000030142062,0.4931896,0.49554247,0.008242111,0.00006226092,0.00013065845],"about_ca_topic_score_codex":0.0004257178,"about_ca_topic_score_gemma":0.00003326148,"teacher_disagreement_score":0.89973426,"about_ca_system_score_codex":0.00004823139,"about_ca_system_score_gemma":0.0001015642,"threshold_uncertainty_score":0.4474382},"labels":[],"label_agreement":null},{"id":"W4402158785","doi":"10.1109/icc51166.2024.10623125","title":"High-Resolution Wideband DOA Estimation Based on Multi-Frequency Cyclic Rank-Minimization","year":2024,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Natural Science Foundation of China","keywords":"Wideband; Minification; Computer science; Rank (graph theory); Resolution (logic); Algorithm; Estimation; Electronic engineering; Mathematics; Artificial intelligence; Engineering","score_opus":0.017245346282945606,"score_gpt":0.27659608307300176,"score_spread":0.25935073679005616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402158785","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":[0.0008437801,0.0000383561,0.9926852,0.0010627208,0.0006596694,0.0003165286,0.000004055901,0.0018254159,0.0025642875],"genre_scores_gemma":[0.50528336,0.0000054711245,0.49437833,0.00010785953,0.000017505618,0.0000354679,0.000018983175,0.000010280905,0.00014273215],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855095,0.00009026074,0.00040154293,0.00040864857,0.00038593644,0.0001626546],"domain_scores_gemma":[0.9990251,0.0002176164,0.00010501626,0.00045872742,0.00013574916,0.000057757632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032967242,0.00016174883,0.0001579159,0.0004915782,0.00008937347,0.0002052858,0.0003366778,0.00009790138,0.000072193434],"category_scores_gemma":[0.00023396767,0.0001465651,0.00007327468,0.0008955588,0.0000441722,0.0010240378,0.000038393748,0.000106867876,0.00009294654],"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":[0.000021541875,0.0003309168,0.00015637367,0.00025166894,0.000030032681,0.000010216132,0.0003436866,0.23492652,0.010041691,0.5040934,0.004859093,0.24493484],"study_design_scores_gemma":[0.00022692881,0.0001059259,0.0007004245,0.0001556284,0.000009175001,0.0000025484542,0.0000014177546,0.93571603,0.05360975,0.009202072,0.00012309273,0.00014702162],"about_ca_topic_score_codex":0.00018725036,"about_ca_topic_score_gemma":0.000011975255,"teacher_disagreement_score":0.7007895,"about_ca_system_score_codex":0.00013067161,"about_ca_system_score_gemma":0.000103966275,"threshold_uncertainty_score":0.59767514},"labels":[],"label_agreement":null},{"id":"W4402356135","doi":"10.3390/s24175821","title":"Data-Aided Maximum Likelihood Joint Angle and Delay Estimator Over Orthogonal Frequency Division Multiplex Single-Input Multiple-Output Channels Based on New Gray Wolf Optimization Embedding Importance Sampling","year":2024,"lang":"en","type":"article","venue":"Sensors","topic":"Direction-of-Arrival Estimation Techniques","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":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cramér–Rao bound; Initialization; Estimator; Algorithm; Embedding; Computer science; Convergence (economics); Mathematical optimization; Mathematics; Control theory (sociology); Statistics","score_opus":0.05427382651610916,"score_gpt":0.3031959870810878,"score_spread":0.24892216056497865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402356135","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":[0.08677617,0.0001531613,0.91026515,0.00032686655,0.0007239779,0.00046874682,0.00008803106,0.0010748548,0.00012303816],"genre_scores_gemma":[0.51385146,0.000008583862,0.48582307,0.00007964942,0.000078489786,0.000009666852,0.000093951276,0.00003794115,0.000017156122],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99698955,0.000105751074,0.0007404271,0.0011006293,0.00064020813,0.00042345948],"domain_scores_gemma":[0.9977254,0.000527401,0.00030324867,0.0010415175,0.00016106044,0.00024132451],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00062727556,0.00038020013,0.00038838488,0.00053135195,0.0001987512,0.00047841063,0.0005729953,0.00016298259,0.000032672502],"category_scores_gemma":[0.00092468696,0.0003630084,0.00011052751,0.00068300264,0.000070983726,0.0012051514,0.00030518082,0.00026437154,0.000011128686],"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":[0.000038533944,0.00026851395,0.0036904216,0.00029570184,0.00008277598,0.000094571595,0.00078318553,0.8858191,0.010606158,0.0019356551,0.0008893224,0.09549605],"study_design_scores_gemma":[0.0003861002,0.0001498747,0.0010277998,0.00058266876,0.000022989032,0.00002052431,0.000010969307,0.98711526,0.0072072954,0.0029706361,0.00012866216,0.00037721585],"about_ca_topic_score_codex":0.00011705263,"about_ca_topic_score_gemma":0.000022666587,"teacher_disagreement_score":0.42707533,"about_ca_system_score_codex":0.0001383852,"about_ca_system_score_gemma":0.00018261948,"threshold_uncertainty_score":0.99988216},"labels":[],"label_agreement":null},{"id":"W4404919737","doi":"10.1016/j.sigpro.2024.109820","title":"Automatic regularization for linear MMSE filters","year":2024,"lang":"en","type":"article","venue":"Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"Institut National de la Recherche Scientifique","funders":"","keywords":"Regularization (linguistics); Mathematics; Linear filter; Computer science; Algorithm; Artificial intelligence; Computer vision; Filter (signal processing)","score_opus":0.01977431075990281,"score_gpt":0.29802524475652226,"score_spread":0.27825093399661943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404919737","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":[0.00071593816,0.00018395546,0.99687153,0.00031291883,0.00011695548,0.00017406525,0.0000015085812,0.000999613,0.0006235151],"genre_scores_gemma":[0.5688843,9.577595e-7,0.43081614,0.000044234315,0.000042564272,0.000031314306,0.0000039058555,0.000010275318,0.00016629524],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992861,0.000017335893,0.00021369739,0.00020435192,0.00017053928,0.00010795722],"domain_scores_gemma":[0.99958086,0.00008016273,0.000072181625,0.00011730971,0.00012153365,0.000027929726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026828103,0.00007542562,0.00009159685,0.00015926726,0.00007966764,0.00020438388,0.0002360124,0.000040038845,0.000011865874],"category_scores_gemma":[0.000052920655,0.00007072419,0.000044409495,0.0004832329,0.00002845063,0.00084036926,0.000036684574,0.000049846945,0.0000060181155],"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":[0.0000016504642,0.00001612347,0.000004500947,0.00081478443,0.0000074640016,0.0000013078896,0.0005886201,0.00037563604,0.009580585,0.013518233,0.00049894693,0.97459215],"study_design_scores_gemma":[0.00003732473,0.000040002375,0.00001015313,0.0003782742,0.0000066821126,0.000004570712,0.0000058760597,0.8775975,0.087793514,0.03351742,0.00053591427,0.00007276829],"about_ca_topic_score_codex":0.0000019396396,"about_ca_topic_score_gemma":1.4655929e-7,"teacher_disagreement_score":0.9745194,"about_ca_system_score_codex":0.000031791336,"about_ca_system_score_gemma":0.00013466256,"threshold_uncertainty_score":0.28840488},"labels":[],"label_agreement":null},{"id":"W4405699004","doi":"10.1049/rsn2.12685","title":"High sensitivity multi‐channel digital receiver for wideband very weak signal direction‐finding classified by machine learning","year":2024,"lang":"en","type":"article","venue":"IET Radar Sonar & Navigation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"Ministère de la Défense Nationale","keywords":"Computer science; SIGNAL (programming language); Direction of arrival; Sensitivity (control systems); Wideband; Acoustics; Radar; Algorithm; Frequency band; Direction finding; Bandwidth (computing); Cluster analysis; Signal-to-noise ratio (imaging); Noise (video); Electronic engineering; Physics; Telecommunications; Antenna (radio); Artificial intelligence; Engineering","score_opus":0.01790810657129642,"score_gpt":0.2621195970922104,"score_spread":0.24421149052091395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405699004","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":[0.032126684,0.00018207057,0.964833,0.00041615823,0.0007164657,0.0003764124,0.00010630856,0.0011018782,0.00014101621],"genre_scores_gemma":[0.9517265,0.000020355796,0.04695318,0.00001879654,0.00009687311,0.00004070233,0.00027380005,0.000031711323,0.0008381069],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984443,0.00011150634,0.00035561807,0.00049816025,0.00036066544,0.0002297536],"domain_scores_gemma":[0.9989125,0.0004927044,0.00017799842,0.00017893409,0.00016541229,0.00007245973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005798569,0.0002063516,0.00023154437,0.00017209208,0.000250428,0.0003796416,0.00016850694,0.00012832765,0.000006466086],"category_scores_gemma":[0.000092318296,0.000216827,0.00013265293,0.0005318742,0.000061998544,0.001789571,0.00007007034,0.00026613838,0.000016080758],"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":[0.00012865971,0.00032820448,0.0006844989,0.00047175368,0.00022457246,0.000033486183,0.0030017218,0.0037798854,0.1559238,0.0070682857,0.012897137,0.815458],"study_design_scores_gemma":[0.00043301334,0.00019773445,0.0004119342,0.00040401705,0.000027460166,0.000047781577,0.0000463716,0.7758417,0.20696574,0.0035625407,0.01168657,0.00037511557],"about_ca_topic_score_codex":0.00022074275,"about_ca_topic_score_gemma":0.000011247703,"teacher_disagreement_score":0.9195998,"about_ca_system_score_codex":0.00019295888,"about_ca_system_score_gemma":0.00007204316,"threshold_uncertainty_score":0.88419485},"labels":[],"label_agreement":null},{"id":"W4412425365","doi":"10.1016/j.sigpro.2025.110179","title":"Performance analysis of Quaternion-MUSIC: Unification, simplification, and evaluation","year":2025,"lang":"en","type":"article","venue":"Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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, Okanagan Campus; University of British Columbia","funders":"Taishan Scholar Project of Shandong Province","keywords":"Unification; Quaternion; Algebra over a field; Computer science; Mathematics; Speech recognition; Algorithm; Applied mathematics; Arithmetic; Calculus (dental); Pure mathematics; Programming language; Geometry","score_opus":0.02585280732697223,"score_gpt":0.3139844720401824,"score_spread":0.2881316647132102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412425365","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":[0.2021368,0.00011949907,0.7957171,0.00018651881,0.000020700714,0.00013267012,8.8834764e-7,0.00008020192,0.0016056256],"genre_scores_gemma":[0.97836363,0.000010626784,0.021524794,0.000026858725,0.0000042151337,0.000021743544,0.000008360497,0.0000025331817,0.000037246005],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900407,0.000058316495,0.00036460563,0.00022197359,0.00027937262,0.000071663555],"domain_scores_gemma":[0.9985416,0.000066098735,0.0003031192,0.00022905167,0.000841044,0.000019093733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078592775,0.000070233116,0.00015490505,0.00059500104,0.00009970191,0.00005571353,0.00025725635,0.00003668723,0.000010394475],"category_scores_gemma":[0.00006180979,0.00006954597,0.000030251711,0.0023243017,0.00006510122,0.0005810219,0.000046099285,0.00004026087,5.748394e-7],"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":[0.0000058112996,0.00005035622,0.015981626,0.0001985222,0.00008271853,2.6928365e-8,0.0007985527,0.004629809,0.017605243,0.009245155,0.000049222555,0.95135295],"study_design_scores_gemma":[0.00006263684,0.00001472653,0.08921896,0.000074187315,0.00013992983,2.3643172e-7,0.00002247392,0.85862213,0.048784863,0.0029631287,0.0000401573,0.00005653522],"about_ca_topic_score_codex":0.000021212654,"about_ca_topic_score_gemma":0.0000027419217,"teacher_disagreement_score":0.95129645,"about_ca_system_score_codex":0.000038317106,"about_ca_system_score_gemma":0.00016784777,"threshold_uncertainty_score":0.28360024},"labels":[],"label_agreement":null},{"id":"W4413384000","doi":"10.1049/rsn2.70066","title":"Deep Neural Network Model of Ultrafast 2D Direction‐of‐Arrival Estimation Using Planar Arrays for Multi‐Octave‐Band Digital Receiver Applications","year":2025,"lang":"en","type":"article","venue":"IET Radar Sonar & Navigation","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"Ministère de la Défense Nationale; Government of Canada","keywords":"Planar; Computer science; Artificial neural network; Acoustics; Octave (electronics); Direction of arrival; Ultrashort pulse; Algorithm; Artificial intelligence; Physics; Telecommunications; Optics; Computer graphics (images)","score_opus":0.027338039376452388,"score_gpt":0.29801987555259296,"score_spread":0.27068183617614056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413384000","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":[0.030089723,0.000053388394,0.9681917,0.000074705764,0.00020544212,0.0008937754,0.00006404928,0.00021486483,0.00021237387],"genre_scores_gemma":[0.5329459,0.0000048071547,0.46681818,0.000011043318,0.000029292383,0.000066828616,0.00008698783,0.000010971954,0.000026009906],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99840206,0.0000460436,0.00068574084,0.00036364133,0.00030540643,0.0001971377],"domain_scores_gemma":[0.998333,0.00019623949,0.0005791274,0.00038888943,0.00045299702,0.000049774666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002775711,0.00018429094,0.00030632628,0.00019480288,0.000192156,0.00006755431,0.00039076942,0.00012262694,0.0000012472102],"category_scores_gemma":[0.000061115556,0.00020695731,0.00013993192,0.00085198606,0.00011643176,0.0010318191,0.000036989222,0.00011018294,8.4632353e-7],"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":[0.00006408535,0.00023578526,0.00075422483,0.00030434603,0.000075098724,2.39912e-7,0.0009255417,0.74558586,0.032588825,0.02163013,0.00016652109,0.19766934],"study_design_scores_gemma":[0.00033501186,0.000049759292,0.0003754007,0.00015267052,0.000037765512,0.000004001884,0.000025517375,0.91248614,0.07198837,0.014315384,0.00008580688,0.00014418861],"about_ca_topic_score_codex":0.000050388437,"about_ca_topic_score_gemma":0.0000073562665,"teacher_disagreement_score":0.50285614,"about_ca_system_score_codex":0.00011469407,"about_ca_system_score_gemma":0.00012234201,"threshold_uncertainty_score":0.8439474},"labels":[],"label_agreement":null},{"id":"W4415707568","doi":"10.1109/jiot.2025.3626821","title":"Integrated Sensing and Communication Beamforming Design With Target Model Aware Antenna Selection","year":2025,"lang":"","type":"article","venue":"IEEE Internet of Things Journal","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Beamforming; Latency (audio); Efficient energy use; Software deployment; Antenna (radio); Communications system; Low latency (capital markets); Energy (signal processing)","score_opus":0.021351516259490555,"score_gpt":0.26884376426376805,"score_spread":0.2474922480042775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415707568","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":[0.021567121,0.0002992713,0.97664595,0.00039315593,0.0003768523,0.00027629218,0.0000014594301,0.00011200077,0.00032792124],"genre_scores_gemma":[0.54368556,0.00013448646,0.4558844,0.00007862206,0.000009424427,0.0000013434418,6.7177183e-7,0.000012318867,0.00019318658],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974279,0.00035829388,0.0011390033,0.0003361682,0.00045368215,0.00028494338],"domain_scores_gemma":[0.99606425,0.00023355911,0.0014830554,0.000364459,0.0017510327,0.00010363649],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0018514012,0.00031138904,0.0005213075,0.00086065085,0.0002691834,0.00046849868,0.00082955824,0.00018499806,0.000007323984],"category_scores_gemma":[0.00022184747,0.00028218687,0.00010959826,0.0008557192,0.0002944953,0.0024199367,0.00019478396,0.0009661275,5.4906326e-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":[0.0019240914,0.0007942871,0.002103064,0.0011252639,0.0016889672,0.000028856108,0.049965456,0.20480226,0.17037652,0.006452082,0.005398343,0.5553408],"study_design_scores_gemma":[0.00031219493,0.00032657527,0.000020947155,0.004008714,0.00006345029,0.00040844068,0.00015948243,0.7633879,0.22207712,0.009041939,0.0000213867,0.00017180835],"about_ca_topic_score_codex":0.0005112821,"about_ca_topic_score_gemma":0.000011800735,"teacher_disagreement_score":0.5585857,"about_ca_system_score_codex":0.00028185427,"about_ca_system_score_gemma":0.0005484683,"threshold_uncertainty_score":0.99996305},"labels":[],"label_agreement":null},{"id":"W654790286","doi":"10.1049/iet-spr.2014.0173","title":"Mean angle of arrival, angular and Doppler spreads estimation in multiple‐input multiple‐output system","year":2015,"lang":"en","type":"article","venue":"IET Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Estimator; Transmitter; Algorithm; Angle of arrival; MIMO; Direction of arrival; Mathematics; Gaussian; Rayleigh fading; Doppler effect; Computer science; Channel (broadcasting); Statistics; Control theory (sociology); Fading; Telecommunications; Physics; Decoding methods","score_opus":0.03512724157525543,"score_gpt":0.2685694669163852,"score_spread":0.2334422253411298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W654790286","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":[0.15655941,0.00030053593,0.84185547,0.000048252026,0.000071151975,0.00027897005,0.000003828107,0.0003076056,0.00057479815],"genre_scores_gemma":[0.79561794,0.0000012359873,0.20430335,0.000012585196,0.000017619808,0.000019671132,0.000003638376,0.000013299095,0.000010636615],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983149,0.0001039909,0.0005547759,0.0003549602,0.0004664484,0.00020491821],"domain_scores_gemma":[0.99873513,0.00014201958,0.00039096345,0.0002674676,0.00035121493,0.00011321884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000785749,0.00017564523,0.00032241433,0.0003218285,0.00006577965,0.000108423745,0.00036975773,0.00010106428,0.0000011626473],"category_scores_gemma":[0.00021910563,0.00017252236,0.00004033044,0.000598938,0.000109450295,0.0011539527,0.00013720113,0.0001164597,0.0000023952714],"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":[0.00021819294,0.0007500685,0.059277333,0.0044049774,0.00007467292,0.00005766733,0.029618226,0.05514958,0.073135935,0.0090870075,0.00077371276,0.7674526],"study_design_scores_gemma":[0.0005515191,0.00009684932,0.0019492178,0.0006240361,0.000009047059,0.000029408613,0.00021534332,0.9078103,0.08726633,0.0012471884,0.000025853986,0.00017494704],"about_ca_topic_score_codex":0.00023945533,"about_ca_topic_score_gemma":0.000020837018,"teacher_disagreement_score":0.85266066,"about_ca_system_score_codex":0.00010290299,"about_ca_system_score_gemma":0.0001537636,"threshold_uncertainty_score":0.7035257},"labels":[],"label_agreement":null},{"id":"W6887857238","doi":"10.17863/cam.82516","title":"Prevalence, and Predictors, of Vascular Cognitive Impairment in CADASIL","year":2022,"lang":"en","type":"article","venue":"Apollo (University of Cambridge)","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"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":"Medical Research Council; University College London Hospitals NHS Foundation Trust; Cambridge University Hospitals; University College London; University of Cambridge","keywords":"CADASIL; Stroke (engine); Cohort; Cognitive impairment; Cognition; Leukoencephalopathy; Montreal Cognitive Assessment; Cohort study","score_opus":0.006000635929904089,"score_gpt":0.19629662962459007,"score_spread":0.19029599369468597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6887857238","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":[0.9670936,0.00012364713,0.03125708,0.00007560258,0.00006315664,0.00024740217,0.000043366035,0.000050121642,0.0010460551],"genre_scores_gemma":[0.99505496,0.00006901111,0.0046650264,0.000009580012,0.0000022593106,0.0000011026655,0.0000024812468,0.0000027843735,0.00019282303],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999187,0.00009985217,0.0001274303,0.00018265852,0.000311629,0.00009142173],"domain_scores_gemma":[0.9994585,0.000066741995,0.00017236623,0.00018110908,0.00008447591,0.000036817793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030547922,0.000063228086,0.00016698994,0.00025751666,0.000068031724,0.0000036484985,0.0003511684,0.000023326524,0.000018559314],"category_scores_gemma":[0.000019981522,0.0000856805,0.00005837265,0.0004417485,0.00012340711,0.00029558202,0.00042185432,0.00007727297,4.1454265e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003241847,0.0019493079,0.82264394,0.0015790666,0.0004979123,0.000091803304,0.023533966,0.0005634142,0.0048459442,0.09837735,0.0062553673,0.03933775],"study_design_scores_gemma":[0.0012935186,0.0007184537,0.97863996,0.00015826682,0.000057458776,0.000012072968,0.0014190227,0.009182458,0.0074624433,0.00029635016,0.000559833,0.00020013368],"about_ca_topic_score_codex":0.0008272456,"about_ca_topic_score_gemma":0.000012863897,"teacher_disagreement_score":0.15599605,"about_ca_system_score_codex":0.000053874202,"about_ca_system_score_gemma":0.00008642266,"threshold_uncertainty_score":0.34939495},"labels":[],"label_agreement":null},{"id":"W6901715310","doi":"10.60692/xdd60-kyd46","title":"A new low-complexity angular spread estimator in the presence of line-of-sight with angular distribution selection","year":2011,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada); Institut National de la Recherche Scientifique","funders":"","keywords":"Estimator; Antenna (radio); Antenna array; Angle of arrival; Mean squared error; Bias of an estimator; Nonlinear system; Minimum-variance unbiased estimator; Estimation theory","score_opus":0.03974138137354698,"score_gpt":0.22543048849942962,"score_spread":0.18568910712588266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901715310","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":[0.18161759,0.0000024544108,0.8170265,0.000013577359,0.00007249525,0.0004519322,0.000025168225,0.0001421253,0.00064817804],"genre_scores_gemma":[0.94192874,9.116578e-8,0.057994574,0.0000072174284,0.00001103588,0.000036445195,0.000011276734,0.0000040659843,0.0000065314903],"study_design_codex":"qualitative","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99837816,0.00012106787,0.00074398,0.00014516804,0.00046014853,0.00015146051],"domain_scores_gemma":[0.99831766,0.000019697196,0.0007354418,0.0004936189,0.00038877278,0.00004480964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005670629,0.00014546809,0.00025154345,0.000244818,0.0000537443,0.000050109604,0.00055765006,0.00007869404,0.0000069247826],"category_scores_gemma":[0.000055117125,0.000101499194,0.00005600676,0.0009506201,0.00006894657,0.001460961,0.0000616342,0.000084781714,0.00000958584],"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":[0.0006111308,0.00014330608,0.3637859,0.0049277847,0.0001586193,0.000009716853,0.4150545,0.002754579,0.00037490993,0.19577232,0.00047515266,0.01593209],"study_design_scores_gemma":[0.0015715815,0.0007858701,0.33278766,0.0017233457,0.000060954506,0.0001595664,0.0032122803,0.23285083,0.42564708,0.00060521567,0.000059134578,0.00053646736],"about_ca_topic_score_codex":0.00030893757,"about_ca_topic_score_gemma":0.0000027862693,"teacher_disagreement_score":0.7603112,"about_ca_system_score_codex":0.0000610963,"about_ca_system_score_gemma":0.000101404556,"threshold_uncertainty_score":0.4139017},"labels":[],"label_agreement":null},{"id":"W6958057523","doi":"10.6084/m9.figshare.19069810","title":"Additional file 1 of AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens","year":2022,"lang":"en","type":"article","venue":"Open MIND","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver General Hospital; University of Victoria; University of British Columbia; BC Centre for Disease Control; BC Cancer Agency","funders":"","keywords":"Deep learning; Workflow; Set (abstract data type); Test set; Plot (graphics); Pattern recognition (psychology); Sequence (biology); Identification (biology)","score_opus":0.024958413623433238,"score_gpt":0.28017853911917046,"score_spread":0.2552201254957372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958057523","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":[0.03234021,0.0000022581658,0.7607448,0.000016781536,0.000053805794,0.0009794125,0.20420162,0.000009703848,0.0016514182],"genre_scores_gemma":[0.29513806,9.2541904e-7,0.6967367,0.00001812365,0.000015053702,0.0006235194,0.0066749863,0.000014213908,0.0007784067],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989465,0.000090542555,0.0002973405,0.00030936152,0.000229779,0.00012650034],"domain_scores_gemma":[0.99806523,0.0010129197,0.00046960145,0.00021041081,0.00021787011,0.000023968076],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00032251325,0.00010409431,0.00026503275,0.000111845744,0.00016790637,0.00005993574,0.00063805137,0.00003466831,0.004559232],"category_scores_gemma":[0.00043002208,0.00011520753,0.00011208815,0.0002596897,0.00008242853,0.00069902645,0.0007574287,0.00012856924,0.0000023690955],"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":[0.00038947404,0.0025331606,0.00012544157,0.0002508997,0.00034677162,0.0000043649993,0.01921478,0.14206417,0.1792591,0.0022508325,0.2273649,0.4261961],"study_design_scores_gemma":[0.00053984055,0.00032247545,0.0006712655,0.00022139867,0.000019248451,0.0000053941017,0.00030151816,0.9291569,0.061239894,0.0004083182,0.0068633,0.00025047772],"about_ca_topic_score_codex":0.00001851195,"about_ca_topic_score_gemma":0.0000097489365,"teacher_disagreement_score":0.7870927,"about_ca_system_score_codex":0.000066630746,"about_ca_system_score_gemma":0.00017549307,"threshold_uncertainty_score":0.99635077},"labels":[],"label_agreement":null},{"id":"W6977167807","doi":"10.60692/e9tp8-w8s11","title":"Joint mean angle of arrival, angular and Doppler spreads estimation in macrocell environments","year":2014,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Macrocell; Estimator; Doppler effect; Joint (building); Channel (broadcasting); Minimum mean square error; Angular displacement; Wireless; Computational complexity theory","score_opus":0.017177323486332483,"score_gpt":0.1993745820811579,"score_spread":0.18219725859482544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6977167807","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":[0.31708896,0.0000017325453,0.68121886,0.000014982022,0.00007381776,0.00022141608,0.0000073281117,0.00010030345,0.0012725623],"genre_scores_gemma":[0.95994127,2.429895e-7,0.039974816,0.000024976076,0.0000060091074,0.000025961692,0.0000058751575,0.000005314428,0.000015526834],"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99858946,0.00007622361,0.0007296021,0.00014836757,0.00032243496,0.00013388865],"domain_scores_gemma":[0.9989767,0.000011356543,0.0004951702,0.00040440104,0.0000592781,0.00005309008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005920539,0.00013132406,0.0002450607,0.00040362118,0.00003674887,0.00006959744,0.0002246123,0.000076152886,0.0000047119993],"category_scores_gemma":[0.00003127779,0.00012234098,0.000038133552,0.00024751513,0.000041956126,0.001246276,0.00010909876,0.00005307343,0.000036760382],"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":[0.00014347766,0.000119608994,0.34925398,0.0072206543,0.00019337868,0.000007631724,0.4373611,0.025302872,0.0037617304,0.070349805,0.00053131155,0.105754465],"study_design_scores_gemma":[0.0009885537,0.00014805475,0.11280719,0.00042941613,0.000014535206,0.000044315388,0.0008109818,0.73662615,0.1474948,0.00021312179,0.00011777588,0.0003051418],"about_ca_topic_score_codex":0.000025917265,"about_ca_topic_score_gemma":2.8248454e-7,"teacher_disagreement_score":0.71132326,"about_ca_system_score_codex":0.00006521947,"about_ca_system_score_gemma":0.00001327154,"threshold_uncertainty_score":0.49889207},"labels":[],"label_agreement":null},{"id":"W7020833390","doi":"","title":"Multiple-antenna wireless communications: detection and estimation with smart antennas, and space-time code design considerations","year":2009,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Smoothing; Covariance matrix; Estimator; Multipath propagation; Subspace topology; Wireless; Antenna array; Array processing; Channel (broadcasting); Signal subspace","score_opus":0.023101246664073198,"score_gpt":0.25360839561300147,"score_spread":0.23050714894892826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7020833390","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":[0.800346,0.0029889927,0.15129048,0.0009244402,0.0015325443,0.013341104,0.0013233732,0.008156554,0.020096522],"genre_scores_gemma":[0.7532811,0.000458671,0.24544242,0.00008441354,0.000006555437,0.00020956963,0.00015783442,0.00007185809,0.00028757725],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962926,0.00065602234,0.0009781187,0.0010316832,0.0006338122,0.0004077667],"domain_scores_gemma":[0.994963,0.0012233813,0.001071911,0.0014912877,0.0010068483,0.00024355526],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0010510577,0.0006688919,0.00077380467,0.0007874934,0.0014562155,0.0003681326,0.0007258283,0.0005237594,0.00000874863],"category_scores_gemma":[0.0011710675,0.0006983557,0.00010463461,0.0008014519,0.00023198596,0.0022897902,0.00019240768,0.00083780097,0.000020482626],"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":[0.000360384,0.00047980575,0.00006285495,0.00045527006,0.0003146876,0.000027096154,0.00012092817,0.00017201147,0.22245029,0.1054292,0.000011079476,0.6701164],"study_design_scores_gemma":[0.0020846657,0.0012586989,0.006968565,0.002299373,0.00043928658,0.00051011465,0.00015756623,0.49474588,0.39115185,0.09732016,0.0008204621,0.0022433754],"about_ca_topic_score_codex":0.0003313224,"about_ca_topic_score_gemma":0.0017068849,"teacher_disagreement_score":0.667873,"about_ca_system_score_codex":0.00026738492,"about_ca_system_score_gemma":0.00011411117,"threshold_uncertainty_score":0.9998438},"labels":[],"label_agreement":null},{"id":"W7097811722","doi":"","title":"University of Alberta ROBUST SIGNAL DETECTION IN NON-GAUSSIAN NOISE USING THRESHOLD SYSTEM AND BISTABLE SYSTEM","year":2016,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"","keywords":"Permission; Detection theory; Noise (video); SIGNAL (programming language); Bistability; Signal processing","score_opus":0.013234530269164732,"score_gpt":0.2023047100378665,"score_spread":0.18907017976870175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097811722","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":[0.15615828,0.000004653626,0.83860004,0.000017789149,0.00006456905,0.00014261533,9.577677e-7,0.000113532886,0.0048975702],"genre_scores_gemma":[0.97115004,0.000001397679,0.028660405,0.0000013046001,0.000004958264,7.247129e-7,9.174176e-8,0.0000042887978,0.00017678001],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930054,0.00004015114,0.00019684245,0.000211995,0.00013840699,0.00011208784],"domain_scores_gemma":[0.999422,0.000064967215,0.00015003841,0.00023480336,0.00008346651,0.00004469355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024348989,0.000078784324,0.0001683752,0.00022027257,0.00005343806,0.000020572867,0.00022056192,0.00005952961,0.000004861092],"category_scores_gemma":[0.000007756611,0.00006435911,0.00002712968,0.0003582775,0.000043808075,0.00058765494,0.00010741136,0.000032231306,0.0000022754562],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019088444,0.0003033962,0.03561103,0.0036361548,0.00011587493,0.00005296361,0.0030257648,0.008568924,0.66278005,0.20860524,0.0001472174,0.076962486],"study_design_scores_gemma":[0.00038791954,0.00006699011,0.002388944,0.0008503601,0.000009525898,0.000028362309,0.00029463394,0.803966,0.19178931,0.00006464523,0.000013597822,0.00013969913],"about_ca_topic_score_codex":0.006628768,"about_ca_topic_score_gemma":0.0007164625,"teacher_disagreement_score":0.8149918,"about_ca_system_score_codex":0.00019207386,"about_ca_system_score_gemma":0.00004018786,"threshold_uncertainty_score":0.9999862},"labels":[],"label_agreement":null},{"id":"W7125606233","doi":"10.1109/iciteics64870.2025.11341606","title":"Adaptive Beamforming of Smart Antenna Array for Space-Time Signal Processing with GA-PSO Using Novel Adaptive Equalizer on Rayleighfading Channels","year":2025,"lang":"","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Multipath propagation; Beamforming; Smart antenna; Antenna array; Wireless; Beam steering; Adaptive beamformer; Antenna (radio); Signal processing; Adaptive equalizer","score_opus":0.04857403178558096,"score_gpt":0.3009993145209583,"score_spread":0.25242528273537734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7125606233","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":[0.0016859319,0.00013036541,0.98875344,0.0002245582,0.00034283713,0.0017423732,0.000044291985,0.00029587734,0.0067803008],"genre_scores_gemma":[0.4922956,0.000004262511,0.5065022,0.000099193116,0.000048892576,0.000054857537,0.0000021306741,0.00004002978,0.00095283706],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954392,0.00013809367,0.0014026623,0.0012739067,0.00090119935,0.0008449893],"domain_scores_gemma":[0.994339,0.00084547297,0.0015514217,0.00061705033,0.002475886,0.0001711793],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012382257,0.00072966487,0.0012254766,0.0011845786,0.00057108887,0.00027597524,0.00082823756,0.00028270605,0.000055812707],"category_scores_gemma":[0.0002055086,0.0006754078,0.0003137332,0.002683292,0.00045905224,0.0019855131,0.00028948658,0.00035279867,0.0000039586535],"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":[0.0034615458,0.0017307774,0.00007579742,0.0016065211,0.00090391154,0.000007554093,0.008076876,0.030404443,0.6956403,0.1653741,0.00009903667,0.09261912],"study_design_scores_gemma":[0.000774634,0.0012437392,0.0000069680586,0.004254684,0.0001182573,0.000012094808,0.00039247554,0.5371611,0.45248133,0.0031078937,0.000043486456,0.00040333043],"about_ca_topic_score_codex":0.00014878358,"about_ca_topic_score_gemma":0.000009845278,"teacher_disagreement_score":0.50675666,"about_ca_system_score_codex":0.00041806366,"about_ca_system_score_gemma":0.001656286,"threshold_uncertainty_score":0.9995697},"labels":[],"label_agreement":null},{"id":"W7139051077","doi":"10.1109/globecom59602.2025.11431916","title":"CRLB Analysis for Matrix Pencil DoA Estimation in Hybrid Receivers Under Snapshot Constraints","year":2025,"lang":"","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ericsson (Canada); Carleton University","funders":"","keywords":"Snapshot (computer storage); Cramér–Rao bound; Upper and lower bounds; Exploit; Matrix pencil; Signal processing","score_opus":0.02481931202570799,"score_gpt":0.3296956457970149,"score_spread":0.3048763337713069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7139051077","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":[0.0052631604,0.00006571037,0.9724743,0.0015180872,0.00056475966,0.0011136254,0.00003943391,0.00020956811,0.0187514],"genre_scores_gemma":[0.6830099,0.0000369426,0.31566566,0.00017537737,0.000006378171,0.000073528805,0.000038899656,0.0000075452967,0.000985739],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966102,0.00018917475,0.0013377881,0.00089757034,0.00051597616,0.00044924632],"domain_scores_gemma":[0.99706906,0.0007510438,0.0005129007,0.00082976994,0.0007269889,0.000110263754],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014339752,0.0003519542,0.00074663654,0.0024379687,0.00018032792,0.00030194028,0.00094877783,0.00017236067,0.0009673842],"category_scores_gemma":[0.0006518199,0.0003943389,0.00043316348,0.0051077106,0.00039571978,0.001101825,0.00021787517,0.00020341751,0.00001537051],"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":[0.00013783683,0.0007213728,0.0053427834,0.00057983596,0.0015419823,0.000007941024,0.00081277266,0.25225994,0.0009431189,0.46138316,0.0075783967,0.26869085],"study_design_scores_gemma":[0.00063977874,0.00010384423,0.005360746,0.0001759421,0.00038569092,0.0000030440378,0.0001194216,0.9215064,0.027285447,0.04396752,0.00012501463,0.0003271207],"about_ca_topic_score_codex":0.00049885525,"about_ca_topic_score_gemma":0.00017853816,"teacher_disagreement_score":0.6777468,"about_ca_system_score_codex":0.0005363899,"about_ca_system_score_gemma":0.0008401033,"threshold_uncertainty_score":0.9999459},"labels":[],"label_agreement":null},{"id":"W7139052319","doi":"10.1109/globecom59602.2025.11432111","title":"Linear Receive Beamforming for Continuous-Aperture Array (CAPA) Systems","year":2025,"lang":"","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Beamforming; Maximization; WSDMA; Telecommunications link; Channel (broadcasting); Rayleigh quotient","score_opus":0.016039584585729953,"score_gpt":0.2923467551176155,"score_spread":0.2763071705318855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7139052319","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":[0.00017263823,0.0005974401,0.94284225,0.0017371285,0.0035220203,0.0020461152,0.00003390649,0.00067051797,0.04837797],"genre_scores_gemma":[0.17901286,0.00018626443,0.7816685,0.0010248553,0.0002647039,0.00048134144,0.00001838182,0.000046957775,0.037296135],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99688876,0.00012257737,0.0012340953,0.00081186707,0.00042518578,0.0005174987],"domain_scores_gemma":[0.9958518,0.0011864632,0.00058184494,0.0009885941,0.001262278,0.00012898508],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010462512,0.00040419045,0.0008016124,0.00051024085,0.00033366142,0.00035052726,0.0012495358,0.00037146968,0.000038714992],"category_scores_gemma":[0.0012251724,0.00038458421,0.0003178203,0.0012555149,0.0001631926,0.0009389239,0.00020201936,0.00027114426,0.000024521269],"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":[0.00014351374,0.00057518214,0.0003114241,0.0029841992,0.0005270501,0.0000028984532,0.0023178272,0.0017834915,0.03431973,0.6715557,0.046620663,0.23885834],"study_design_scores_gemma":[0.0006187598,0.0004208581,0.000028401222,0.001655872,0.00007828529,0.00001035149,0.0003262619,0.6625458,0.16174531,0.0044188765,0.16765378,0.0004974293],"about_ca_topic_score_codex":0.00023708261,"about_ca_topic_score_gemma":0.000012879659,"teacher_disagreement_score":0.6671368,"about_ca_system_score_codex":0.00017450978,"about_ca_system_score_gemma":0.0004513401,"threshold_uncertainty_score":0.9998606},"labels":[],"label_agreement":null},{"id":"W7143282180","doi":"10.5281/zenodo.19334136","title":"A Novel Approach to Electromagnetic Source Direction of Arrival Estimation Using Virtual Antenna Arrays","year":2024,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Troubleshooting; Antenna (radio); Antenna array; Radiation pattern; Direction of arrival; Position (finance); Multiple signal classification; Antenna measurement","score_opus":0.03744744733112851,"score_gpt":0.26371587827098425,"score_spread":0.22626843093985574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7143282180","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":[0.0108817145,0.00017124813,0.9720911,0.00019521316,0.00039925234,0.0009454486,0.000095155476,0.0016350519,0.013585826],"genre_scores_gemma":[0.8742893,0.000056404468,0.123740666,0.00003427967,0.00014352372,2.4852537e-7,0.0001775692,0.0011168858,0.0004411253],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9960129,0.0004667806,0.0009350721,0.0010136194,0.0010162567,0.00055536104],"domain_scores_gemma":[0.99719477,0.00007829868,0.00035943172,0.00083338073,0.0012582137,0.00027591805],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0015830379,0.0003493124,0.0004216982,0.0013891169,0.0011841445,0.0015205026,0.0017004366,0.00015956334,0.000616757],"category_scores_gemma":[0.001193639,0.00040998528,0.00016952983,0.003918478,0.00031348495,0.0011379381,0.0013674749,0.0004498238,0.00049507467],"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":[0.00008909779,0.00061721733,4.151663e-7,0.00060560176,0.00011451449,0.0000027122924,0.005082797,0.014118265,0.5019802,0.02014425,0.0038977244,0.45334724],"study_design_scores_gemma":[0.0002816944,0.001338328,0.000093092014,0.00052357704,0.00007010257,0.00035576356,0.00014155057,0.9359105,0.02890749,0.00034885088,0.031646997,0.00038203766],"about_ca_topic_score_codex":0.00009584061,"about_ca_topic_score_gemma":1.5156004e-7,"teacher_disagreement_score":0.92179227,"about_ca_system_score_codex":0.00043548315,"about_ca_system_score_gemma":0.000043557033,"threshold_uncertainty_score":0.9998352},"labels":[],"label_agreement":null},{"id":"W7143297364","doi":"10.5281/zenodo.19334137","title":"A Novel Approach to Electromagnetic Source Direction of Arrival Estimation Using Virtual Antenna Arrays","year":2024,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Troubleshooting; Antenna (radio); Antenna array; Radiation pattern; Direction of arrival; Position (finance); Multiple signal classification; Antenna measurement","score_opus":0.03744744733112851,"score_gpt":0.26371587827098425,"score_spread":0.22626843093985574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7143297364","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":[0.0108817145,0.00017124813,0.9720911,0.00019521316,0.00039925234,0.0009454486,0.000095155476,0.0016350519,0.013585826],"genre_scores_gemma":[0.8742893,0.000056404468,0.123740666,0.00003427967,0.00014352372,2.4852537e-7,0.0001775692,0.0011168858,0.0004411253],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9960129,0.0004667806,0.0009350721,0.0010136194,0.0010162567,0.00055536104],"domain_scores_gemma":[0.99719477,0.00007829868,0.00035943172,0.00083338073,0.0012582137,0.00027591805],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0015830379,0.0003493124,0.0004216982,0.0013891169,0.0011841445,0.0015205026,0.0017004366,0.00015956334,0.000616757],"category_scores_gemma":[0.001193639,0.00040998528,0.00016952983,0.003918478,0.00031348495,0.0011379381,0.0013674749,0.0004498238,0.00049507467],"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":[0.00008909779,0.00061721733,4.151663e-7,0.00060560176,0.00011451449,0.0000027122924,0.005082797,0.014118265,0.5019802,0.02014425,0.0038977244,0.45334724],"study_design_scores_gemma":[0.0002816944,0.001338328,0.000093092014,0.00052357704,0.00007010257,0.00035576356,0.00014155057,0.9359105,0.02890749,0.00034885088,0.031646997,0.00038203766],"about_ca_topic_score_codex":0.00009584061,"about_ca_topic_score_gemma":1.5156004e-7,"teacher_disagreement_score":0.92179227,"about_ca_system_score_codex":0.00043548315,"about_ca_system_score_gemma":0.000043557033,"threshold_uncertainty_score":0.9998352},"labels":[],"label_agreement":null},{"id":"W7147280012","doi":"10.5281/zenodo.19343957","title":"A Novel Approach to Electromagnetic Source Direction of Arrival Estimation Using Virtual Antenna Arrays","year":2022,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Troubleshooting; Antenna (radio); Antenna array; Radiation pattern; Direction of arrival; Position (finance); Multiple signal classification; Antenna measurement","score_opus":0.03725511827124546,"score_gpt":0.25133594839957674,"score_spread":0.2140808301283313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7147280012","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":[0.023334933,0.00005329652,0.96355134,0.00016823251,0.00028729544,0.0011082354,0.00014877196,0.00088874117,0.010459178],"genre_scores_gemma":[0.8989264,0.000017625249,0.09936937,0.00006189514,0.0000760873,5.6301764e-7,0.00026024715,0.0009364066,0.00035145122],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99526817,0.0008967706,0.00095053593,0.0009347072,0.0013773753,0.00057244353],"domain_scores_gemma":[0.9967829,0.000060221657,0.00074177113,0.0009512867,0.0012051942,0.00025864886],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019721321,0.00032026033,0.00043966903,0.0012391969,0.0030692173,0.00062375615,0.0023646601,0.00008973507,0.0014457512],"category_scores_gemma":[0.0011159354,0.0004187181,0.00015456365,0.003880331,0.00026766644,0.0007436582,0.0032231177,0.00053598837,0.00014413183],"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":[0.00025030575,0.0017220055,0.0000016580135,0.0002416151,0.00010618145,0.0000021080887,0.007424678,0.09890368,0.5678437,0.012767693,0.004476021,0.30626035],"study_design_scores_gemma":[0.00063511106,0.002671365,0.0001932729,0.00009551459,0.00005767776,0.00045588342,0.0004634571,0.9411075,0.017541794,0.00026141526,0.036067624,0.00044939228],"about_ca_topic_score_codex":0.00013295536,"about_ca_topic_score_gemma":1.2386916e-7,"teacher_disagreement_score":0.8755914,"about_ca_system_score_codex":0.0006447558,"about_ca_system_score_gemma":0.000041230043,"threshold_uncertainty_score":0.9998265},"labels":[],"label_agreement":null},{"id":"W7147728038","doi":"10.5281/zenodo.19343958","title":"A Novel Approach to Electromagnetic Source Direction of Arrival Estimation Using Virtual Antenna Arrays","year":2022,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Troubleshooting; Antenna (radio); Antenna array; Radiation pattern; Direction of arrival; Position (finance); Multiple signal classification; Antenna measurement","score_opus":0.03725511827124546,"score_gpt":0.25133594839957674,"score_spread":0.2140808301283313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7147728038","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":[0.023334933,0.00005329652,0.96355134,0.00016823251,0.00028729544,0.0011082354,0.00014877196,0.00088874117,0.010459178],"genre_scores_gemma":[0.8989264,0.000017625249,0.09936937,0.00006189514,0.0000760873,5.6301764e-7,0.00026024715,0.0009364066,0.00035145122],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99526817,0.0008967706,0.00095053593,0.0009347072,0.0013773753,0.00057244353],"domain_scores_gemma":[0.9967829,0.000060221657,0.00074177113,0.0009512867,0.0012051942,0.00025864886],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019721321,0.00032026033,0.00043966903,0.0012391969,0.0030692173,0.00062375615,0.0023646601,0.00008973507,0.0014457512],"category_scores_gemma":[0.0011159354,0.0004187181,0.00015456365,0.003880331,0.00026766644,0.0007436582,0.0032231177,0.00053598837,0.00014413183],"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":[0.00025030575,0.0017220055,0.0000016580135,0.0002416151,0.00010618145,0.0000021080887,0.007424678,0.09890368,0.5678437,0.012767693,0.004476021,0.30626035],"study_design_scores_gemma":[0.00063511106,0.002671365,0.0001932729,0.00009551459,0.00005767776,0.00045588342,0.0004634571,0.9411075,0.017541794,0.00026141526,0.036067624,0.00044939228],"about_ca_topic_score_codex":0.00013295536,"about_ca_topic_score_gemma":1.2386916e-7,"teacher_disagreement_score":0.8755914,"about_ca_system_score_codex":0.0006447558,"about_ca_system_score_gemma":0.000041230043,"threshold_uncertainty_score":0.9998265},"labels":[],"label_agreement":null},{"id":"W7160933639","doi":"10.1121/10.0040617","title":"Advances in real-time estimation of multiple acoustic waveforms","year":2025,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","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":"","keywords":"Waveform; Kalman filter; SIGNAL (programming language); Basis (linear algebra); Signal processing; Fourier transform; Fourier series; Frequency domain; Filter (signal processing)","score_opus":0.007154281387265935,"score_gpt":0.27455869842547004,"score_spread":0.2674044170382041,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7160933639","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":[0.0072286045,0.00011124864,0.9906863,0.0011612519,0.00012890191,0.000137855,0.0000024291614,0.000022398757,0.0005210326],"genre_scores_gemma":[0.68710536,0.0005571726,0.3121942,0.000097332544,0.000010312217,0.000001331653,1.3519113e-7,0.0000038414664,0.000030303136],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985388,0.00011731472,0.00069466385,0.00008203291,0.00043108754,0.00013611256],"domain_scores_gemma":[0.9973993,0.0010903247,0.0008538181,0.00035642507,0.00027060494,0.000029530378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079381233,0.00009879261,0.00034367375,0.000063928266,0.0000627842,0.000010004639,0.0010404679,0.000052071446,0.0000069769876],"category_scores_gemma":[0.0007919172,0.000054982494,0.00022448502,0.00080971624,0.0004370862,0.00036267086,0.00022235414,0.00021542286,8.1394097e-7],"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":[0.00012480347,0.00041215608,0.00036430487,0.0003190587,0.00010030156,4.5936085e-7,0.0017392118,0.55317897,0.09439272,0.00035697457,0.0037062077,0.34530485],"study_design_scores_gemma":[0.00021170577,0.0001492845,0.001841982,0.00029144812,0.00005018853,0.000006446749,0.00017697812,0.96331024,0.02315773,0.010705765,0.00004479903,0.0000534553],"about_ca_topic_score_codex":0.00007458949,"about_ca_topic_score_gemma":7.445875e-7,"teacher_disagreement_score":0.6798768,"about_ca_system_score_codex":0.0000795119,"about_ca_system_score_gemma":0.00014206173,"threshold_uncertainty_score":0.22421211},"labels":[],"label_agreement":null},{"id":"W749873514","doi":"10.21236/ada617680","title":"Analysis of Eigenspace Dynamics with Applications to Array Processing","year":2014,"lang":"en","type":"report","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Dynamics (music); Array processing; Computer science; Signal processing; Physics; Computer hardware; Acoustics; Digital signal processing","score_opus":0.02144294265344315,"score_gpt":0.32162157158701166,"score_spread":0.3001786289335685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W749873514","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":[0.000028202241,0.00001895511,0.90485376,0.00011442978,0.000031636344,0.00036236248,0.0000144086625,0.00031586245,0.09426036],"genre_scores_gemma":[0.1170371,0.000025826013,0.87979573,0.0000352603,0.00002639762,0.00022115941,0.000060107173,0.000023179156,0.0027752335],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980636,0.000024446528,0.00050697,0.00046087944,0.0008091737,0.00013489922],"domain_scores_gemma":[0.9963314,0.00006414791,0.0007836135,0.001020964,0.0017210561,0.00007881582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050342875,0.00018462639,0.00060095714,0.0011227619,0.000050504015,0.00006322676,0.0007946941,0.00012496255,0.000010202945],"category_scores_gemma":[0.00007043058,0.00015362342,0.00013330278,0.003623024,0.000052386247,0.00015205442,0.00009400438,0.000107266984,0.0000032106652],"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":[0.000008843768,0.00034132053,0.010527063,0.0016470287,0.0020375543,0.0000013224552,0.0006376181,0.012520625,0.00055332284,0.05763883,0.0030687542,0.9110177],"study_design_scores_gemma":[0.0002125426,0.0006404513,0.012669552,0.0013496251,0.004572395,0.00004631955,0.00011443399,0.83129776,0.04802561,0.0030236484,0.09562669,0.0024209816],"about_ca_topic_score_codex":0.00044523267,"about_ca_topic_score_gemma":0.00086765824,"teacher_disagreement_score":0.90859675,"about_ca_system_score_codex":0.00019264831,"about_ca_system_score_gemma":0.0007034639,"threshold_uncertainty_score":0.6264581},"labels":[],"label_agreement":null}]}