{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":5,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":5,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"6ee0bfb9eebb","filters":{"venue":"2022 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)"}},"results":[{"id":"W4280625329","doi":"10.23919/date54114.2022.9774576","title":"Efficient Traveling Salesman Problem Solvers using the Ising Model with Simulated Bifurcation","year":2022,"lang":"en","type":"article","venue":"2022 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Travelling salesman problem; Solver; Computer science; Mathematical optimization; Simulated annealing; Benchmark (surveying); Ising model; Spins; Applied mathematics; Mathematics; Algorithm; Physics; Statistical physics","authors":[{"name":"Tingting Zhang","is_ca":true},{"name":"Jie Han","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0955018404612106,"gpt":0.3027928999542914,"spread":0.2072910594930808,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.003508424,0.000460369,0.0003969636,0.000775204,0.001361449,0.0009060677,0.001340793,0.00009759406,0.0006440004],"category_scores_gemma":[0.0008729772,0.0004141236,0.00007139197,0.00438033,0.0001850037,0.0006376707,0.0005638485,0.0008206472,0.0002044181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003867507,"about_ca_system_score_gemma":0.001091385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008504065,"about_ca_topic_score_gemma":0.00004997593,"domain_scores_codex":[0.9933775,0.001792179,0.001104262,0.001156126,0.001835773,0.0007341246],"domain_scores_gemma":[0.9957843,0.0007590704,0.0007017704,0.00130053,0.001260645,0.0001936646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002953132,0.0002804781,0.00008709844,0.00003377005,0.00001632549,0.000006937903,0.002956568,0.9758617,0.01667859,0.002190454,0.0003611337,0.001497368],"study_design_scores_gemma":[0.0008551935,0.00006906714,0.0002436935,0.0001112128,0.00002573524,0.00006596486,0.00009067688,0.9953138,0.0003107598,0.0004627587,0.00194646,0.000504636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04462636,0.00003411756,0.951534,0.000847152,0.0001660415,0.001572222,0.00004160254,0.0005437012,0.0006347959],"genre_scores_gemma":[0.5222749,0.00002742742,0.4752325,0.0002874652,0.00003830067,0.0001377947,0.0004805899,0.00007953697,0.001441555],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4776485,"threshold_uncertainty_score":0.9999387,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4280571518","doi":"10.23919/date54114.2022.9774699","title":"Deep Reinforcement Learning for Analog Circuit Structure Synthesis","year":2022,"lang":"en","type":"article","venue":"2022 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Computer science; Reinforcement learning; Construct (python library); Set (abstract data type); Reliability (semiconductor); Circuit extraction; Circuit design; Computer engineering; Artificial intelligence; Equivalent circuit; Engineering; Electrical engineering; Embedded system; Programming language; Voltage","authors":[{"name":"Zhenxin Zhao","is_ca":true},{"name":"Lihong Zhang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04201048525884097,"gpt":0.2475071451572473,"spread":0.2054966598984063,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001083737,0.0005025658,0.0004972705,0.0007100452,0.0005344978,0.0002523769,0.0005210989,0.0001741389,0.006495759],"category_scores_gemma":[0.001198612,0.000587519,0.0001180319,0.001222492,0.00006527184,0.0004973926,0.0001419464,0.0007468599,0.0002576052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003153876,"about_ca_system_score_gemma":0.0001284183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002978359,"about_ca_topic_score_gemma":0.00009941007,"domain_scores_codex":[0.996594,0.0005272751,0.0009604511,0.0006448484,0.0006368744,0.0006365891],"domain_scores_gemma":[0.9978743,0.0006928651,0.0003139492,0.0006359187,0.0003360278,0.0001469141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004698371,0.0001316583,0.0005407566,0.0003057933,0.00007184317,0.00001140733,0.001908128,0.6684227,0.2914398,0.002855493,0.01695202,0.01731341],"study_design_scores_gemma":[0.001689812,0.0004248298,0.003560565,0.0004152672,0.0001996408,0.0001565121,0.0003216848,0.5513273,0.02475148,0.005324404,0.4090486,0.002779817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01338558,0.0001302447,0.979427,0.00009847881,0.0002821382,0.001370847,0.00009960188,0.001945416,0.003260708],"genre_scores_gemma":[0.9754701,0.00018608,0.01856621,0.0001673717,0.0001009074,0.001096075,0.002252223,0.0001510252,0.002010034],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9620845,"threshold_uncertainty_score":0.9996576,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4280560843","doi":"10.23919/date54114.2022.9774530","title":"CR&amp;P: An Efficient Co-operation between Routing and Placement","year":2022,"lang":"en","type":"article","venue":"2022 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Routing (electronic design automation); Physical design; Electronic design automation; Placement; Design flow; CONTEST; Network routing; Place and route; Integer programming; Distributed computing; Embedded system; Circuit design; Algorithm","authors":[{"name":"Erfan Aghaeekiasaraee","is_ca":true},{"name":"Aysa Fakheri Tabrizi","is_ca":true},{"name":"Tiago Augusto Fontana","is_ca":false},{"name":"Renan Netto","is_ca":false},{"name":"Sheiny Fabre Almeida","is_ca":false},{"name":"Upma Gandhi","is_ca":true},{"name":"José Luís Güntzel","is_ca":false},{"name":"David T. Westwick","is_ca":true},{"name":"Laleh Behjat","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0573484131648651,"gpt":0.2814321515290119,"spread":0.2240837383641468,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002041027,0.0005139663,0.0004739344,0.0006071466,0.0006138369,0.0004358016,0.0003790775,0.0001569974,0.00241838],"category_scores_gemma":[0.0003260482,0.0005986565,0.00005848851,0.0007966098,0.00008773075,0.0004917633,0.0001731299,0.0006775669,0.0005351293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003039714,"about_ca_system_score_gemma":0.0001353665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006164372,"about_ca_topic_score_gemma":0.0001170469,"domain_scores_codex":[0.9959372,0.0008816629,0.001054863,0.0007712679,0.0007629264,0.0005920577],"domain_scores_gemma":[0.998243,0.0003679532,0.0002679785,0.0006899538,0.000216678,0.0002143831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009462949,0.0008898497,0.007630024,0.0003487584,0.00009417554,0.00002133976,0.01120181,0.3579178,0.5752754,0.002834431,0.02240789,0.02128389],"study_design_scores_gemma":[0.005394743,0.001155153,0.04503496,0.0007596525,0.0002916903,0.0002606686,0.001002907,0.4910298,0.03281133,0.001372829,0.4151267,0.005759592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3298905,0.00009222228,0.6645416,0.0001263161,0.0001898285,0.001172183,0.0002471959,0.001746646,0.001993529],"genre_scores_gemma":[0.9705552,0.0001169942,0.02334959,0.0001560334,0.000130193,0.0004041177,0.004238393,0.0001245761,0.0009248402],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.641192,"threshold_uncertainty_score":0.9996465,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4221156338","doi":"10.23919/date54114.2022.9774648","title":"Non-Volatile Phase Change Material based Nanophotonic Interconnect","year":2022,"lang":"en","type":"article","venue":"2022 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","topic":"Phase-change materials and chalcogenides","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; Agence Nationale de la Recherche","keywords":"Nanophotonics; Interconnection; Computer science; Optoelectronics; Phase change; Materials science; Telecommunications; Engineering physics; Physics","authors":[{"name":"Parya Zolfaghari","is_ca":true},{"name":"Joseph Ortiz","is_ca":false},{"name":"Cédric Killian","is_ca":false},{"name":"Sébastien Le Beux","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1016122851983024,"gpt":0.3064950413649614,"spread":0.204882756166659,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00248219,0.000706456,0.0007810405,0.0006992572,0.0007325955,0.0007331087,0.0009368808,0.0001768642,0.07458504],"category_scores_gemma":[0.0005639338,0.0007558654,0.0001382383,0.001218075,0.0001906986,0.001029215,0.0005283591,0.0003799234,0.003468695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000284691,"about_ca_system_score_gemma":0.0004278033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003748894,"about_ca_topic_score_gemma":0.0004013389,"domain_scores_codex":[0.9940022,0.001418367,0.001366683,0.001282945,0.0009752038,0.0009546517],"domain_scores_gemma":[0.9970144,0.0003672516,0.0008160232,0.001105516,0.0004339708,0.0002628306],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003777962,0.000894871,0.00005664381,0.0001204151,0.0000097127,0.00003682932,0.001562842,0.0002730519,0.9905465,0.0001380883,0.005253165,0.0007301425],"study_design_scores_gemma":[0.007204094,0.001141616,0.001125586,0.0005382539,0.0001259913,0.0002016194,0.0002661542,0.01498603,0.7764034,0.0009280217,0.1946032,0.002476028],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689077,0.0000793763,0.022283,0.000495184,0.002338079,0.001928845,0.002505335,0.0007694358,0.0006930258],"genre_scores_gemma":[0.9836259,0.00006836759,0.006719518,0.001012191,0.0003496346,0.001895729,0.004925374,0.0001456925,0.00125757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2141431,"threshold_uncertainty_score":0.9994892,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225885311","doi":"10.23919/date54114.2022.9774635","title":"FitAct: Error Resilient Deep Neural Networks via Fine-Grained Post-Trainable Activation Functions","year":2022,"lang":"en","type":"preprint","venue":"2022 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Fault tolerance; Inference; Redundancy (engineering); Resilience (materials science); Activation function; Deep neural networks; Artificial neural network; Latency (audio); Word error rate; Artificial intelligence; Distributed computing","authors":[{"name":"Behnam Ghavami","is_ca":true},{"name":"Mani Sadati","is_ca":true},{"name":"Zhenman Fang","is_ca":true},{"name":"Lesley Shannon","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04523905429616132,"gpt":0.2870918710591243,"spread":0.241852816762963,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002923349,0.001223944,0.001017708,0.00153252,0.001319769,0.001319124,0.002608144,0.0006228258,0.004583409],"category_scores_gemma":[0.005290717,0.001420909,0.0003042197,0.003403094,0.0002125279,0.00201748,0.003005093,0.003729871,0.0006493711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007648318,"about_ca_system_score_gemma":0.0008202291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004701947,"about_ca_topic_score_gemma":0.0007342504,"domain_scores_codex":[0.9892236,0.003208442,0.00201811,0.002616378,0.001666592,0.001266882],"domain_scores_gemma":[0.9913821,0.001763577,0.001961865,0.002878846,0.001655541,0.0003580609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001051324,0.0004672945,0.0004644037,0.0001526458,0.00005002105,0.00002913327,0.002146392,0.9728523,0.005140828,0.001933521,0.005525155,0.01113314],"study_design_scores_gemma":[0.001067627,0.0001839198,0.01216736,0.0002762103,0.00007511657,0.00006626532,0.0001124161,0.9539567,0.00006619617,0.001781527,0.02865667,0.001589954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0155415,0.0001005738,0.9727319,0.003130312,0.002397553,0.002342762,0.0001046692,0.001925432,0.001725281],"genre_scores_gemma":[0.8112643,0.00007467821,0.160725,0.001149835,0.0006408004,0.001409559,0.01431306,0.0002928713,0.01012999],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.812007,"threshold_uncertainty_score":0.9999804,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}