{"meta":{"query_hash":"a13ef10df191","filters":{"venue":"IEEE Journal on Selected Areas in Information Theory"},"cohort_total":20,"direct_labels_cover":0,"predictions_cover":20,"exported":20,"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/a13ef10df191","api":"https://metacan.xera.ac/api/v1/cohort?venue=IEEE+Journal+on+Selected+Areas+in+Information+Theory"},"results":[{"id":"W2982682504","doi":"10.1109/jsait.2020.3017054","title":"Erasable Bit Commitment From Temporary Quantum Trust","year":2020,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Cryptography and Data Security","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 de Sherbrooke; Université de Montréal; Perimeter Institute; University of Waterloo","funders":"Industry Canada; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Communication source; Commit; Commitment scheme; Computer science; Computer security; Protocol (science); Third party; Trusted third party; Cryptography; Cryptographic protocol; Node (physics); Adversarial system; Bit (key); Computer network; Internet privacy","score_opus":0.015256136464743468,"score_gpt":0.22594976497196748,"score_spread":0.210693628507224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982682504","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":[0.32425046,0.00019428301,0.6656477,0.002670807,0.001266001,0.00034978762,0.0001373411,0.00032230737,0.0051613315],"genre_scores_gemma":[0.99032426,0.0000931222,0.0032260078,0.006053196,0.00020715695,0.000008227767,0.00007893162,0.0000070259753,0.000002055102],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981794,0.00028958058,0.0006547126,0.00015338811,0.0004527745,0.00027016844],"domain_scores_gemma":[0.99866825,0.00026466022,0.00035309524,0.00030613254,0.00016539276,0.00024247337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063893525,0.00018035312,0.00021519263,0.00032677007,0.00020944302,0.0004612117,0.0008611595,0.000092711525,0.00014738124],"category_scores_gemma":[0.00018565157,0.00015616171,0.00008323181,0.001184503,0.000030121018,0.0037019418,0.00006925673,0.000698178,0.00021754326],"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":[0.0013109612,0.00053380587,0.012172787,0.00005369989,0.00020769492,0.00010720644,0.020133248,0.0027785068,0.000532922,0.83249915,0.08632907,0.04334097],"study_design_scores_gemma":[0.008342291,0.0018656397,0.039622318,0.00049278914,0.000044750046,0.00023404279,0.0024113336,0.19074824,0.012886073,0.5788125,0.16271907,0.0018209463],"about_ca_topic_score_codex":0.000017398439,"about_ca_topic_score_gemma":0.0000024656488,"teacher_disagreement_score":0.6660738,"about_ca_system_score_codex":0.00007642392,"about_ca_system_score_gemma":0.0001606012,"threshold_uncertainty_score":0.636809},"labels":[],"label_agreement":null},{"id":"W3161297530","doi":"10.1109/jsait.2021.3079856","title":"Asynchronous Delayed Optimization With Time-Varying Minibatches","year":2021,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":4,"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 Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Huawei Technologies","keywords":"Asynchronous communication; Regret; Computer science; Variable (mathematics); Mathematical optimization; Process (computing); Mathematics","score_opus":0.006218310357429007,"score_gpt":0.21096753306189617,"score_spread":0.20474922270446716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161297530","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":[0.0043043755,0.00002863608,0.99001116,0.00022337574,0.0002477939,0.00017191056,0.0000028587485,0.00024559762,0.0047643124],"genre_scores_gemma":[0.3581567,0.00008661558,0.639573,0.0017853269,0.00012396637,0.00004512704,0.00007605751,0.00003191156,0.00012133243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982017,0.00024317001,0.00060479215,0.00017021573,0.0004814793,0.00029861895],"domain_scores_gemma":[0.99789226,0.00029946602,0.0004357223,0.00031267767,0.00094060204,0.00011927079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006273478,0.00019746528,0.00020667791,0.0005962812,0.00020846575,0.00044198014,0.00043766882,0.000106013715,0.00012023917],"category_scores_gemma":[0.00040646695,0.00017326426,0.000043821467,0.0015688359,0.000037526926,0.0026691288,0.000037572292,0.00039100312,0.000053346295],"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":[0.00015944884,0.00009983509,0.000052431868,0.00000927477,0.000051040868,0.000039669478,0.0019008465,0.96250886,0.00010392316,0.023793358,0.00048478023,0.010796561],"study_design_scores_gemma":[0.001651795,0.0005340225,0.00021249782,0.0002977465,0.000020197285,0.0016357539,0.00015760266,0.9698656,0.01631114,0.0086649945,0.00016578297,0.00048284855],"about_ca_topic_score_codex":9.905759e-7,"about_ca_topic_score_gemma":5.778083e-7,"teacher_disagreement_score":0.35385233,"about_ca_system_score_codex":0.00026686545,"about_ca_system_score_gemma":0.00046074906,"threshold_uncertainty_score":0.7065511},"labels":[],"label_agreement":null},{"id":"W3189399213","doi":"10.1109/jsait.2021.3102853","title":"Sequential Gradient Coding for Packet-Loss Networks","year":2021,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Cooperative Communication and Network Coding","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":"Notation; Mathematics; Algorithm; Discrete mathematics; Combinatorics; Arithmetic","score_opus":0.024068254098254048,"score_gpt":0.2722622865215812,"score_spread":0.24819403242332713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3189399213","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":[0.015758485,0.0001866742,0.9797641,0.0007066203,0.001311243,0.00017718514,0.0000026732712,0.000079617814,0.0020133937],"genre_scores_gemma":[0.9927566,0.0010557674,0.0038904527,0.0019059483,0.00023308973,0.000026921844,0.000027617652,0.000008349267,0.0000952379],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982615,0.00045932754,0.00059060624,0.00012509373,0.00024304226,0.00032039743],"domain_scores_gemma":[0.99791616,0.00047788682,0.00029553633,0.000343211,0.00085145223,0.00011577125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013562344,0.00014686293,0.0001806087,0.00027034924,0.000430147,0.000504415,0.0005856784,0.00007965216,0.00004336553],"category_scores_gemma":[0.00039937824,0.00013730265,0.00008976788,0.000960119,0.00003097496,0.0015086572,0.000079229016,0.0005248928,0.000018685632],"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":[0.00016345932,0.00011751724,0.0002236098,0.00001655118,0.00007056977,0.000022498341,0.0032796361,0.031438857,0.00030830686,0.7831456,0.004819007,0.17639439],"study_design_scores_gemma":[0.0049501145,0.00040460963,0.0038086234,0.0007218082,0.000027941884,0.0011996633,0.00047850228,0.8727567,0.012582971,0.0409057,0.061174497,0.0009888682],"about_ca_topic_score_codex":2.5863264e-7,"about_ca_topic_score_gemma":0.0000067830033,"teacher_disagreement_score":0.97699815,"about_ca_system_score_codex":0.00023020532,"about_ca_system_score_gemma":0.00023404972,"threshold_uncertainty_score":0.5599039},"labels":[],"label_agreement":null},{"id":"W3189787503","doi":"10.1109/jsait.2021.3103494","title":"Compressing Gradients by Exploiting Temporal Correlation in Momentum-SGD","year":2021,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Stochastic Gradient Optimization 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":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Huawei Technologies","keywords":"Bottleneck; Computer science; Computation; Rate of convergence; Convergence (economics); Algorithm; Momentum (technical analysis); Mathematical optimization; Information bottleneck method; Compression (physics); Exploit; Norm (philosophy); Mathematics; Artificial intelligence; Telecommunications","score_opus":0.009529290614629546,"score_gpt":0.23181319729259658,"score_spread":0.22228390667796705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3189787503","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":[0.058906097,0.000046424717,0.93798405,0.00017416068,0.0006981412,0.00016470173,0.000003606049,0.00014734169,0.0018754893],"genre_scores_gemma":[0.9829719,0.00003171093,0.01615382,0.0006655114,0.000037416437,0.000021799924,0.000052150623,0.000010818593,0.000054850145],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997796,0.00034513813,0.0008812094,0.00016460152,0.00049241795,0.00032063134],"domain_scores_gemma":[0.9983969,0.00033162514,0.00053187273,0.00022134025,0.00041834998,0.000099912584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009373337,0.00017230783,0.00020055419,0.00077133905,0.00017425901,0.00040022892,0.00039561352,0.00010080653,0.000024294208],"category_scores_gemma":[0.0006619653,0.00017727856,0.00004371789,0.001487435,0.00002869854,0.0032630635,0.00004965105,0.0005661909,0.00001958586],"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":[0.00044563392,0.0013282791,0.025735917,0.000108795146,0.00011673702,0.00020529993,0.028804801,0.41863927,0.0033837466,0.36028305,0.016831888,0.14411658],"study_design_scores_gemma":[0.0034905074,0.0002735909,0.0052255597,0.0010975507,0.00000990922,0.00048624864,0.0011141984,0.895459,0.021816295,0.069066495,0.001188775,0.00077184377],"about_ca_topic_score_codex":0.0000034671457,"about_ca_topic_score_gemma":0.0000012405876,"teacher_disagreement_score":0.9240658,"about_ca_system_score_codex":0.00040486295,"about_ca_system_score_gemma":0.00015675137,"threshold_uncertainty_score":0.722921},"labels":[],"label_agreement":null},{"id":"W3193529446","doi":"10.1109/jsait.2021.3104970","title":"Coded Sequential Matrix Multiplication for Straggler Mitigation","year":2021,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Cooperative Communication and Network Coding","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":"University of Toronto","funders":"","keywords":"Notation; Mathematics; Computer science; Arithmetic","score_opus":0.022187923574703377,"score_gpt":0.2947377955343279,"score_spread":0.2725498719596245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193529446","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":[0.039010324,0.00010242889,0.95786566,0.00095525803,0.00056062115,0.00027768943,0.00000674406,0.000091722235,0.0011295852],"genre_scores_gemma":[0.98141354,0.0003177818,0.016785853,0.0010284042,0.00014596857,0.000051020263,0.00008499564,0.000008127119,0.00016430032],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984286,0.00039303536,0.0005894301,0.00012386875,0.00025634526,0.00020870999],"domain_scores_gemma":[0.9976763,0.00036513832,0.0003359089,0.00033963975,0.0012006615,0.00008232393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009751496,0.00012553956,0.00014023515,0.00028138096,0.0003076207,0.00041203032,0.00045445593,0.00008390554,0.00004825911],"category_scores_gemma":[0.00047510787,0.00012291924,0.00006903205,0.0008110151,0.000022302664,0.0019296104,0.000040460553,0.00035161775,0.0000431819],"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":[0.00030999977,0.00022547232,0.00017268458,0.000036466045,0.000078192934,0.0000057377374,0.005705968,0.01980561,0.01711701,0.68531907,0.004511812,0.266712],"study_design_scores_gemma":[0.0078269765,0.00038466495,0.011441082,0.00055628817,0.00003454004,0.0005835732,0.00072203774,0.7019239,0.16329958,0.066573925,0.045570225,0.0010832311],"about_ca_topic_score_codex":3.178863e-7,"about_ca_topic_score_gemma":0.0000063305324,"teacher_disagreement_score":0.9424032,"about_ca_system_score_codex":0.00020663207,"about_ca_system_score_gemma":0.00028953227,"threshold_uncertainty_score":0.5012501},"labels":[],"label_agreement":null},{"id":"W3214381038","doi":"10.1109/jsait.2021.3126687","title":"On Streaming Codes With Unequal Error Protection","year":2021,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Cooperative Communication and Network Coding","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":"University of Toronto","funders":"","keywords":"Computer science; Network packet; Converse; Coding (social sciences); Packet loss; Forward error correction; Computer network; Algorithm; Theoretical computer science; Decoding methods; Mathematics","score_opus":0.02265578548945043,"score_gpt":0.25782235971382145,"score_spread":0.235166574224371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214381038","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":[0.22177903,0.000053338143,0.76908785,0.0008224147,0.00038054716,0.00021453922,0.0000018759977,0.00013193914,0.007528437],"genre_scores_gemma":[0.99705976,0.00009189261,0.001805439,0.0008768193,0.000049974853,0.00001689445,0.0000068158965,0.000005784168,0.00008664509],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984348,0.00054687576,0.00038096725,0.00010916739,0.0003331259,0.00019508667],"domain_scores_gemma":[0.9984812,0.00026582548,0.000256654,0.0003087659,0.0006137023,0.00007381383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073242723,0.00013308809,0.00013729445,0.0003319664,0.00032885978,0.0003527591,0.00035863105,0.00005592152,0.000046189016],"category_scores_gemma":[0.00033409832,0.000105963205,0.00003108556,0.0011423096,0.00002448019,0.0014523823,0.00003569615,0.00064567564,0.000047903],"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":[0.000501721,0.0002742052,0.0001438121,0.000019289162,0.00007166483,0.000040441973,0.0065638865,0.073921174,0.0013202666,0.47499207,0.00061658357,0.44153488],"study_design_scores_gemma":[0.012481634,0.0048438287,0.028427478,0.0047407397,0.00004910913,0.0026866274,0.00402864,0.73474026,0.119046904,0.06500158,0.021222455,0.0027307523],"about_ca_topic_score_codex":7.4179184e-7,"about_ca_topic_score_gemma":0.000017862896,"teacher_disagreement_score":0.7752807,"about_ca_system_score_codex":0.00019923842,"about_ca_system_score_gemma":0.00026025932,"threshold_uncertainty_score":0.4321054},"labels":[],"label_agreement":null},{"id":"W4285230246","doi":"10.1109/jsait.2022.3182943","title":"Soft BIBD and Product Gradient Codes","year":2022,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Adversarial Robustness in Machine Learning","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 British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Probabilistic logic; Coding (social sciences); Code (set theory); Algorithm; Mathematics; Artificial intelligence; Statistics","score_opus":0.007631716982751596,"score_gpt":0.23078160945333973,"score_spread":0.22314989247058814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285230246","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":[0.21333618,0.00017137555,0.7792045,0.0014361513,0.0026888277,0.0003056214,0.0000060179314,0.0002306565,0.002620674],"genre_scores_gemma":[0.9960144,0.00002035421,0.0031194305,0.0006622598,0.00010510358,0.000017689525,0.000003911067,0.0000073723236,0.000049462673],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980187,0.00061333494,0.00044454227,0.00014398873,0.0005122369,0.00026721938],"domain_scores_gemma":[0.9987639,0.00039828432,0.00036450961,0.00022058403,0.00016513185,0.00008759227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002171746,0.00013827228,0.00015527345,0.00075057306,0.0006687466,0.00025750024,0.0005806196,0.000027168417,0.00005852523],"category_scores_gemma":[0.00090205105,0.00012682228,0.000032334236,0.0011015006,0.00004622422,0.0019711824,0.00015625829,0.00101824,0.000014717255],"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":[0.0003467757,0.00011252834,0.0026756967,0.00003076591,0.000048398968,0.000044830915,0.019886663,0.54069793,0.00015975078,0.24328814,0.0020213819,0.19068712],"study_design_scores_gemma":[0.0052530365,0.0019585832,0.03479577,0.00026002873,0.000043920954,0.0065009007,0.004515142,0.6706004,0.0020511819,0.215023,0.057154264,0.0018437492],"about_ca_topic_score_codex":0.0000037220907,"about_ca_topic_score_gemma":8.564666e-7,"teacher_disagreement_score":0.78267825,"about_ca_system_score_codex":0.00022650862,"about_ca_system_score_gemma":0.00015524346,"threshold_uncertainty_score":0.5171663},"labels":[],"label_agreement":null},{"id":"W4285507276","doi":"10.1109/jsait.2022.3190859","title":"Successive Approximation Coding for Distributed Matrix Multiplication","year":2022,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":13,"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 Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computation; Computer science; Coding (social sciences); Matrix multiplication; Algorithm; Parallel computing; Multiplication (music); Theoretical computer science; Distributed computing; Mathematics","score_opus":0.010413482430253475,"score_gpt":0.25895779948335734,"score_spread":0.24854431705310387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285507276","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":[0.0035067734,0.000010415726,0.99443364,0.0003444865,0.0004929923,0.0007030302,0.00005231981,0.0002485474,0.00020780817],"genre_scores_gemma":[0.9583608,0.000008141237,0.04043365,0.00037125914,0.000059085625,0.0004967032,0.00023534927,0.000011370002,0.000023679308],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982218,0.00023983192,0.0006767771,0.00014689019,0.00046085604,0.00025385333],"domain_scores_gemma":[0.9975579,0.00058699347,0.0009880266,0.00023945658,0.0005551892,0.00007244692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013907474,0.00014410123,0.00015527011,0.00079200434,0.0005776695,0.0002615311,0.00067425333,0.00005467069,0.000026643054],"category_scores_gemma":[0.0010739629,0.00014606716,0.000060161175,0.0012942437,0.000020635938,0.0019920485,0.00006350097,0.000386559,0.0000075050384],"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":[0.0002863519,0.00014115791,0.000097443095,0.00002558053,0.00002489576,0.0000016146213,0.0027030911,0.23046823,0.00035214485,0.7473645,0.001918262,0.016616708],"study_design_scores_gemma":[0.0015313898,0.00031141532,0.0005114102,0.00004395937,0.000008545783,0.00012040099,0.00035217145,0.92836475,0.004038246,0.06349031,0.00095782237,0.00026958977],"about_ca_topic_score_codex":0.0000011633958,"about_ca_topic_score_gemma":2.0332259e-7,"teacher_disagreement_score":0.954854,"about_ca_system_score_codex":0.00060751307,"about_ca_system_score_gemma":0.00014348379,"threshold_uncertainty_score":0.5956446},"labels":[],"label_agreement":null},{"id":"W4312777148","doi":"10.1109/jsait.2022.3231820","title":"On the Rate-Distortion-Perception Function","year":2022,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":43,"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); McMaster University","funders":"","keywords":"Perception; Distortion function; Randomness; Distortion (music); Constraint (computer-aided design); Mathematics; Coding (social sciences); Rate distortion; Decoding methods; Function (biology); Information theory; Theoretical computer science; Algorithm; Mathematical optimization; Computer science; Statistics; Psychology; Telecommunications","score_opus":0.008935774984870014,"score_gpt":0.23274199312170699,"score_spread":0.22380621813683696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312777148","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":[0.042906832,0.0000093752005,0.95203185,0.0006716469,0.001200064,0.0002689042,0.000009925852,0.0002682954,0.0026331344],"genre_scores_gemma":[0.9938745,0.000020188189,0.0010008528,0.004788229,0.00007225096,0.00010959473,0.000026394962,0.000008483582,0.0000995391],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99761677,0.0009246872,0.0005142145,0.0001355754,0.00059356954,0.00021519192],"domain_scores_gemma":[0.9983303,0.00052009115,0.00045368797,0.0004363423,0.00019936876,0.000060234244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020897717,0.00014445251,0.00011425556,0.00055060035,0.0008135969,0.00019788182,0.0008403228,0.00004272998,0.00048762158],"category_scores_gemma":[0.0003775007,0.000105119645,0.000053286076,0.0009834566,0.000027482107,0.002326742,0.00009806847,0.0010133571,0.00012353642],"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":[0.0010018313,0.00024189983,0.000055226523,0.000007286118,0.00002766335,0.000009894878,0.0023752018,0.05131926,0.0022024338,0.6963533,0.07148478,0.17492121],"study_design_scores_gemma":[0.0018006312,0.0021424533,0.012483693,0.00017292176,0.000014845854,0.00045454604,0.0013548991,0.052761357,0.008035014,0.83121836,0.08873815,0.00082310196],"about_ca_topic_score_codex":0.0000014939803,"about_ca_topic_score_gemma":4.7528715e-7,"teacher_disagreement_score":0.95103097,"about_ca_system_score_codex":0.0005516108,"about_ca_system_score_gemma":0.00010705261,"threshold_uncertainty_score":0.62576115},"labels":[],"label_agreement":null},{"id":"W4313147713","doi":"10.1109/jsait.2022.3219807","title":"Sparsity-Free Compressed Sensing With Applications to Generative Priors","year":2022,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","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":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Notation; Combinatorics; Mathematics; Discrete mathematics; Algebra over a field; Pure mathematics; Arithmetic","score_opus":0.009189985625825691,"score_gpt":0.21449835616617585,"score_spread":0.20530837054035017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313147713","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":[0.22152294,0.000034412424,0.7692604,0.00015441538,0.00027044324,0.00060490856,0.000027696768,0.0005486411,0.007576106],"genre_scores_gemma":[0.9870403,0.000012362562,0.0119242035,0.0008234481,0.00009630858,0.00003955021,0.000018483968,0.000022656022,0.000022705344],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989001,0.00014366527,0.000329264,0.00007972424,0.00032807104,0.00021914659],"domain_scores_gemma":[0.99923664,0.0001013323,0.00011722401,0.00025400185,0.0002016303,0.00008917071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030365505,0.00015349066,0.00016355494,0.00054872304,0.0003361255,0.000100303936,0.0002677465,0.000036529113,0.000038921004],"category_scores_gemma":[0.00003288601,0.00014579356,0.000029105893,0.0007600057,0.000020466958,0.00035694256,0.00004020027,0.0006251712,0.000016007105],"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":[0.0002486376,0.000035968034,0.00004860638,0.0000071604054,0.00006257303,0.00001553774,0.0026489727,0.96672046,0.0037291858,0.0046468065,0.008556001,0.013280085],"study_design_scores_gemma":[0.007003956,0.0021833358,0.0055101183,0.0007694656,0.00016228431,0.0036167165,0.0076269987,0.33796257,0.35805428,0.06402195,0.20977022,0.003318108],"about_ca_topic_score_codex":0.000002971835,"about_ca_topic_score_gemma":0.000005127458,"teacher_disagreement_score":0.76551735,"about_ca_system_score_codex":0.00029144395,"about_ca_system_score_gemma":0.000057415273,"threshold_uncertainty_score":0.59452885},"labels":[],"label_agreement":null},{"id":"W4376607544","doi":"10.1109/jsait.2023.3276296","title":"Active Sensing for Two-Sided Beam Alignment and Reflection Design Using Ping-Pong Pilots","year":2023,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Huawei Technologies","keywords":"Ping pong; Reflection (computer programming); Optics; Beam (structure); Physics; Computer science; Engineering; Artificial intelligence","score_opus":0.026215546889704275,"score_gpt":0.26892948282244683,"score_spread":0.24271393593274254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376607544","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":[0.38336724,0.000015037966,0.6148302,0.000031639593,0.00059054815,0.00034697386,0.000005722715,0.0005333734,0.0002792669],"genre_scores_gemma":[0.99752593,0.00007969602,0.002144162,0.00009710029,0.000091714915,0.000011153037,0.000015847323,0.000024556835,0.00000982589],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989043,0.00008408366,0.00044591972,0.000080623475,0.00019013789,0.0002949668],"domain_scores_gemma":[0.9991722,0.00034246143,0.00014918538,0.00008710782,0.0001996577,0.000049382812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076578447,0.00016412987,0.00017069188,0.00090957235,0.00023336773,0.00012468838,0.00007329537,0.00011740162,0.000005553327],"category_scores_gemma":[0.0004377318,0.00015893705,0.00003443687,0.00082100555,0.000029242485,0.0008328141,0.000010305563,0.00029780873,0.000012370443],"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":[0.00032361873,0.000009120117,0.000025629597,0.000042311414,0.000064767744,0.0000045494644,0.0025301357,0.9449447,0.016245766,0.0010335397,0.00047528112,0.03430061],"study_design_scores_gemma":[0.0016063304,0.0001798728,0.0004368197,0.00031329732,0.000027939996,0.00018384944,0.0022437223,0.6315021,0.35050234,0.012466319,0.00020894258,0.0003284911],"about_ca_topic_score_codex":0.0000023410853,"about_ca_topic_score_gemma":0.0000016528522,"teacher_disagreement_score":0.6141587,"about_ca_system_score_codex":0.00040982518,"about_ca_system_score_gemma":0.000046909106,"threshold_uncertainty_score":0.6481265},"labels":[],"label_agreement":null},{"id":"W4391528179","doi":"10.1109/jsait.2023.3338326","title":"Dimensions of Channel Coding: From Theory to Algorithms to Applications","year":2023,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Cellular Automata and Applications","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":"Center for Advanced Study, University of Illinois at Urbana-Champaign; University of California, San Diego; University of Illinois at Urbana-Champaign; Centre National de la Recherche Scientifique; Nanyang Technological University; National University of Singapore","keywords":"Algorithm; Computer science; Coding (social sciences); Channel (broadcasting); Coding theory; Theoretical computer science; Mathematics; Telecommunications; Statistics","score_opus":0.013560731427355685,"score_gpt":0.2555760877282448,"score_spread":0.2420153563008891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391528179","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":[0.018142788,0.000011248743,0.9788173,0.00088131434,0.00026452492,0.0004981311,0.000054312033,0.00022504915,0.0011053391],"genre_scores_gemma":[0.98097146,0.000058570946,0.015962819,0.002153884,0.00017814442,0.00034429602,0.00008966149,0.00002018612,0.00022099528],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983851,0.00015292491,0.00062622037,0.00016692241,0.0003867051,0.00028214807],"domain_scores_gemma":[0.9981295,0.0005693001,0.00023950094,0.00048559014,0.00034577327,0.00023035787],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010524224,0.0001448456,0.00019305023,0.0010132729,0.0002318094,0.00013570332,0.00082140625,0.00007053824,0.000025241918],"category_scores_gemma":[0.00020815317,0.000121215744,0.000062780964,0.0031919614,0.000024183733,0.00067563955,0.000108434106,0.0002733649,0.0009509335],"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":[0.00011005929,0.00023590353,0.00004075114,0.000017628387,0.000079871475,0.000006492789,0.013643053,0.030229488,0.011201226,0.72864074,0.009938793,0.205856],"study_design_scores_gemma":[0.0018867712,0.0004781704,0.015735943,0.0004634768,0.00004504975,0.00011354189,0.002219073,0.11171739,0.07061059,0.71319497,0.08238203,0.001152989],"about_ca_topic_score_codex":0.0000059504127,"about_ca_topic_score_gemma":0.0000021584244,"teacher_disagreement_score":0.96285444,"about_ca_system_score_codex":0.00009606118,"about_ca_system_score_gemma":0.00012534372,"threshold_uncertainty_score":0.99982697},"labels":[],"label_agreement":null},{"id":"W4396680742","doi":"10.1109/jsait.2024.3396787","title":"Noisy Computing of the OR and MAX Functions","year":2024,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Machine Learning and Algorithms","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; University of British Columbia","funders":"","keywords":"Divergence (linguistics); Pairwise comparison; Mathematics; Function (biology); Computation; Combinatorics; Upper and lower bounds; Probability distribution; Kullback–Leibler divergence; Probability of error; Discrete mathematics; Algorithm; Statistics; Mathematical analysis","score_opus":0.006234505061312398,"score_gpt":0.23775144553921707,"score_spread":0.23151694047790466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396680742","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":[0.16549852,0.00013037797,0.8248388,0.0009936879,0.002928041,0.00012870105,0.0000040146297,0.00014843702,0.005329405],"genre_scores_gemma":[0.9978103,0.00001631534,0.0013362726,0.0003173058,0.00011012816,0.0000010777093,7.889565e-7,0.0000037443356,0.00040404507],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990917,0.00018152075,0.00032489793,0.000063773354,0.00021550352,0.00012264402],"domain_scores_gemma":[0.999251,0.00034156733,0.00013822925,0.00012384991,0.00010642826,0.000038913782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008430685,0.00007698852,0.0000884834,0.00027131682,0.00016960716,0.00025622462,0.00026789051,0.000036769947,0.000028910763],"category_scores_gemma":[0.00022084324,0.00004402331,0.000035051176,0.0008381592,0.000030386213,0.0007180323,0.000040134797,0.00053910987,0.000019051175],"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":[0.00008427488,0.000049680566,0.0009191245,0.000102335565,0.00006487167,0.00001336513,0.010467689,0.026046356,0.00013318648,0.11120313,0.002796306,0.8481197],"study_design_scores_gemma":[0.00070826965,0.00029603744,0.02146811,0.0009019572,0.000015865811,0.0015266273,0.0004946146,0.939936,0.00063298637,0.013431092,0.020335656,0.00025282663],"about_ca_topic_score_codex":0.000003094159,"about_ca_topic_score_gemma":0.0000011373911,"teacher_disagreement_score":0.9138896,"about_ca_system_score_codex":0.00003938223,"about_ca_system_score_gemma":0.00013012293,"threshold_uncertainty_score":0.24707799},"labels":[],"label_agreement":null},{"id":"W4396782890","doi":"10.1109/jsait.2024.3397305","title":"Contraction of Locally Differentially Private Mechanisms","year":2024,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Adhesion, Friction, and Surface Interactions","field":"Engineering","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":"Contraction (grammar); Medicine; Internal medicine","score_opus":0.004835886490959991,"score_gpt":0.21113994578124862,"score_spread":0.20630405929028864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396782890","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":[0.3802797,0.00007903613,0.6116611,0.000037818954,0.0034890217,0.00013893089,0.000013217462,0.00027426108,0.0040269285],"genre_scores_gemma":[0.99910957,0.00031238567,0.00031729072,0.000038827897,0.00009888921,0.0000073916153,0.000012794437,0.000017754131,0.00008507902],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987816,0.00008184276,0.0006413833,0.000058929785,0.00026067914,0.00017551675],"domain_scores_gemma":[0.99931437,0.00021752613,0.0001073799,0.00009430002,0.00020040644,0.00006601912],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039266472,0.00014399254,0.00016309251,0.0005982234,0.00007919419,0.00012431094,0.00010244528,0.000111293906,0.00025707338],"category_scores_gemma":[0.00009217312,0.00012547002,0.00007753626,0.00044533535,0.000016167303,0.0013863688,0.0000037867514,0.00056927575,0.0001108352],"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":[0.000934854,0.00025203847,0.00023387194,0.00051415764,0.0007390589,0.000039964485,0.007446299,0.50581986,0.11222313,0.26311398,0.00703653,0.10164626],"study_design_scores_gemma":[0.0027661365,0.00088982127,0.017620057,0.0029960326,0.00019718756,0.0012351469,0.0018475628,0.4557818,0.31203052,0.16509125,0.03822377,0.0013207265],"about_ca_topic_score_codex":0.0000024490716,"about_ca_topic_score_gemma":0.0000059961567,"teacher_disagreement_score":0.6188299,"about_ca_system_score_codex":0.00021674839,"about_ca_system_score_gemma":0.00006588596,"threshold_uncertainty_score":0.5116519},"labels":[],"label_agreement":null},{"id":"W4399766639","doi":"10.1109/jsait.2024.3416089","title":"Controlled Privacy Leakage Propagation Throughout Overlapping Grouped Learning","year":2024,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Network Security and Intrusion Detection","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":"Vector Institute; University of Toronto","funders":"","keywords":"Leakage (economics); Computer science; Internet privacy; Computer security; Economics","score_opus":0.008281932575904052,"score_gpt":0.2421834919386542,"score_spread":0.23390155936275014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399766639","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":[0.1430277,0.00020485817,0.84637564,0.000440292,0.0025573564,0.0004568243,6.181175e-7,0.0005437076,0.0063930396],"genre_scores_gemma":[0.9981742,0.0001787576,0.0006264596,0.00045802072,0.00039211634,0.000026008474,0.000007088166,0.000011220673,0.00012611973],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975204,0.0006116843,0.0008215483,0.00017546843,0.000543554,0.00032736216],"domain_scores_gemma":[0.99867487,0.00048715415,0.00034639225,0.0001864182,0.00021680848,0.00008835099],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0023625926,0.00019830375,0.00026577234,0.00081126235,0.00038363336,0.00146202,0.0004160762,0.00013809037,0.000053633208],"category_scores_gemma":[0.00063647184,0.00016267513,0.000118390046,0.0014228625,0.000028850807,0.0072161276,0.000043040516,0.0013134432,0.00021833809],"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":[0.001576852,0.00015460666,0.00008661095,0.00013484854,0.00020254667,0.00007506562,0.025336856,0.039524496,0.0039951787,0.44441888,0.0016567755,0.4828373],"study_design_scores_gemma":[0.0039556143,0.00064567156,0.0010032298,0.00083135994,0.000023309367,0.000584193,0.00034894008,0.91515535,0.004134359,0.050661482,0.022152642,0.00050386926],"about_ca_topic_score_codex":0.0000026756302,"about_ca_topic_score_gemma":0.0000012421334,"teacher_disagreement_score":0.87563086,"about_ca_system_score_codex":0.00030645233,"about_ca_system_score_gemma":0.00019095352,"threshold_uncertainty_score":0.99957454},"labels":[],"label_agreement":null},{"id":"W4400314741","doi":"10.1109/jsait.2024.3422011","title":"JPEG Compliant Compression for DNN Vision","year":2024,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":4,"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 Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; JPEG; Compression (physics); Computer vision; JPEG 2000; Artificial intelligence; Image compression; Data compression; Image processing; Materials science; Image (mathematics); Composite material","score_opus":0.012691720190788503,"score_gpt":0.30502544438548407,"score_spread":0.29233372419469555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400314741","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":[0.001764907,0.00017035293,0.9937348,0.00043307358,0.0013834891,0.00038884225,0.000027385395,0.0005990078,0.0014981463],"genre_scores_gemma":[0.8453033,0.00033123555,0.15102628,0.0023196402,0.00043923198,0.00015108309,0.00012642541,0.000048243328,0.00025455517],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99799305,0.00021102444,0.0007623964,0.00021381993,0.00048054627,0.00033916175],"domain_scores_gemma":[0.99797463,0.00085748325,0.00026807538,0.0004151599,0.00034896508,0.00013569093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011706132,0.00021712197,0.00022739856,0.0008905982,0.00025257413,0.00069724175,0.0009548102,0.00011807032,0.000039480685],"category_scores_gemma":[0.00027505786,0.00016648226,0.00009084415,0.0008246368,0.00003777293,0.005230452,0.00010713059,0.00066025974,0.0001091269],"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":[0.00036536192,0.00013087178,0.000012514416,0.00012659353,0.000031603442,0.000030363806,0.0012408306,0.004060506,0.004571709,0.32504082,0.08119724,0.5831916],"study_design_scores_gemma":[0.001278522,0.00073423097,0.00054412824,0.002811317,0.000010949119,0.00054104027,0.00008553925,0.3794203,0.04392299,0.30786237,0.2621743,0.00061431236],"about_ca_topic_score_codex":7.305569e-7,"about_ca_topic_score_gemma":4.5515114e-7,"teacher_disagreement_score":0.8435384,"about_ca_system_score_codex":0.00024579672,"about_ca_system_score_gemma":0.0001591406,"threshold_uncertainty_score":0.678895},"labels":[],"label_agreement":null},{"id":"W4401942877","doi":"10.1109/jsait.2024.3451240","title":"Low-Complexity Coding Techniques for Cloud Radio Access Networks","year":2024,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Cooperative Communication and Network Coding","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":"University of British Columbia; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cloud computing; Computer science; Coding (social sciences); Telecommunications; Operating system; Mathematics","score_opus":0.03720281742026299,"score_gpt":0.31269150711664156,"score_spread":0.2754886896963786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401942877","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":[0.0022349257,0.00027440453,0.99172956,0.0006775307,0.001447954,0.00034794287,0.0000032083162,0.0003849202,0.002899535],"genre_scores_gemma":[0.9910668,0.0013403415,0.005439368,0.0014525888,0.00054328627,0.00006451244,0.00001687677,0.000013928123,0.000062275925],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983493,0.0003345557,0.0006326446,0.00014254283,0.00023336703,0.00030756785],"domain_scores_gemma":[0.99822545,0.0007252626,0.00020492243,0.00032924383,0.00041791936,0.000097223165],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0020781353,0.00017603907,0.00019308373,0.0005898765,0.00038626674,0.0015710134,0.0012415816,0.00009683786,0.000035176283],"category_scores_gemma":[0.00023753151,0.00015240267,0.00008911881,0.0013017673,0.000050664643,0.003565227,0.00010756555,0.00074684975,0.000017277558],"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":[0.00009261644,0.000040819898,0.00002254339,0.00004256376,0.000030610063,0.0000043731875,0.0013581073,0.0041901693,0.00009481985,0.6346492,0.010383521,0.34909067],"study_design_scores_gemma":[0.0006802445,0.00021648439,0.00066459714,0.0012490388,0.000011925484,0.00022271444,0.000060947816,0.88764834,0.0073407916,0.062688045,0.038696013,0.00052088464],"about_ca_topic_score_codex":5.344729e-7,"about_ca_topic_score_gemma":0.000003647241,"teacher_disagreement_score":0.9888319,"about_ca_system_score_codex":0.00029284327,"about_ca_system_score_gemma":0.00018075843,"threshold_uncertainty_score":0.99946547},"labels":[],"label_agreement":null},{"id":"W4404840318","doi":"10.1109/jsait.2024.3509420","title":"Rate-Distortion-Perception Tradeoff for Gaussian Vector Sources","year":2024,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Distributed Sensor Networks and Detection Algorithms","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":"Huawei Technologies (Canada); University of Toronto; McMaster University","funders":"Huawei Technologies","keywords":"Distortion (music); Gaussian; Perception; Mathematics; Statistics; Computer science; Artificial intelligence; Pattern recognition (psychology); Mathematical optimization; Biology; Physics; Telecommunications","score_opus":0.00844123741768463,"score_gpt":0.2342088729274421,"score_spread":0.22576763550975748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404840318","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":[0.021233782,0.000085541746,0.9731306,0.0005938464,0.0032917345,0.0002470262,0.00002184978,0.00033577863,0.0010598274],"genre_scores_gemma":[0.99669605,0.00006295895,0.0018147562,0.0005801603,0.00055520755,0.000036186815,0.000038873175,0.000013696218,0.00020210592],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998396,0.00019887,0.0006175577,0.00016829719,0.00030010063,0.00031921972],"domain_scores_gemma":[0.99894947,0.0003199056,0.00018849288,0.00017551356,0.00022991275,0.0001366933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011325368,0.00018075314,0.00016714953,0.00061398983,0.00026993643,0.0010044496,0.00033707666,0.000127453,0.00007514661],"category_scores_gemma":[0.00015584109,0.00015158454,0.00012447916,0.0010646732,0.000029714432,0.0023780642,0.000010807481,0.00050028996,0.00014088704],"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":[0.00061415456,0.00019666384,0.000040874806,0.00013351341,0.00016912646,0.000038117596,0.00739574,0.044472557,0.0010547488,0.17269857,0.032869946,0.740316],"study_design_scores_gemma":[0.0019178808,0.0009544718,0.006601261,0.0005491953,0.000037796854,0.00077365024,0.00079873914,0.79341245,0.0036128575,0.048155874,0.14232291,0.000862928],"about_ca_topic_score_codex":0.0000019512486,"about_ca_topic_score_gemma":0.0000021849482,"teacher_disagreement_score":0.97546226,"about_ca_system_score_codex":0.00032540248,"about_ca_system_score_gemma":0.000152248,"threshold_uncertainty_score":0.968593},"labels":[],"label_agreement":null},{"id":"W4406089983","doi":"10.1109/jsait.2024.3499012","title":"Editorial Data, Physics, and Life Through the Lens of Information Theory","year":2024,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Computability, Logic, AI Algorithms","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":"Lens (geology); Through-the-lens metering; Data science; Physics; Computer science; Optics","score_opus":0.016638114248038748,"score_gpt":0.256696536806175,"score_spread":0.24005842255813625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406089983","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":[0.006447155,0.00019796856,0.95731795,0.0006262286,0.032574803,0.0003450066,0.000049907896,0.0001745018,0.0022664831],"genre_scores_gemma":[0.97447526,0.00024639253,0.005770225,0.0015504747,0.017837055,0.000017820468,0.000071874136,0.000016938884,0.0000139686745],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99737686,0.00053810957,0.0009161343,0.00015525722,0.0007441381,0.00026951928],"domain_scores_gemma":[0.99685377,0.001505476,0.00040759105,0.00065099075,0.00050844334,0.00007370192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003504303,0.00020269178,0.00023175307,0.0002701576,0.00020100456,0.0008923708,0.0012712207,0.00012183249,0.000016263446],"category_scores_gemma":[0.0011697373,0.00013777688,0.000059780996,0.0010286369,0.00014540902,0.012825872,0.00025743726,0.0008472146,0.000056725137],"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":[0.00018342178,0.00006946255,0.000035994985,0.000102047205,0.00009704525,0.0000014623903,0.017561758,0.00610397,0.000020820034,0.7864941,0.030541474,0.15878847],"study_design_scores_gemma":[0.0013388816,0.00043792574,0.0015422106,0.00033584918,0.000045185952,0.00015524372,0.0011244802,0.18621306,0.0005056204,0.69535655,0.112426735,0.0005182389],"about_ca_topic_score_codex":0.000008790115,"about_ca_topic_score_gemma":0.000001420976,"teacher_disagreement_score":0.96802807,"about_ca_system_score_codex":0.00011931969,"about_ca_system_score_gemma":0.0004940587,"threshold_uncertainty_score":0.9298448},"labels":[],"label_agreement":null},{"id":"W4406137362","doi":"10.1109/jsait.2024.3508492","title":"JSAIT Issue on Information-Theoretic Methods for Trustworthy and Reliable Machine Learning","year":2024,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Information Theory","topic":"Adversarial Robustness in Machine Learning","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":"University of British Columbia","funders":"","keywords":"Trustworthiness; Computer science; Artificial intelligence; Data science; Machine learning; Computer security","score_opus":0.007238332404877398,"score_gpt":0.2908124293006692,"score_spread":0.28357409689579177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406137362","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":[0.00187304,0.00022102597,0.98927116,0.0009162941,0.0016356999,0.00034179568,0.000004276712,0.00029950193,0.005437177],"genre_scores_gemma":[0.67856467,0.0006541318,0.31399664,0.00460518,0.0010612237,0.00014576018,0.00010330706,0.000079247046,0.0007898461],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976244,0.00058851554,0.00083668146,0.00017753088,0.00037331547,0.00039957685],"domain_scores_gemma":[0.99695075,0.0020004644,0.00037564774,0.00023418154,0.00030001422,0.00013894154],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004667459,0.00026910653,0.000285867,0.0012172211,0.0004038276,0.0010735617,0.0005165744,0.00015637248,0.000079674726],"category_scores_gemma":[0.0024023105,0.00022654643,0.000085297506,0.0011111886,0.000056862915,0.00515332,0.00006701832,0.0015012685,0.000120850294],"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":[0.00028417382,0.000017037757,0.000057906745,0.0001119669,0.0000452339,0.0000045973857,0.006788636,0.17541334,0.000014256728,0.31282967,0.0006792831,0.5037539],"study_design_scores_gemma":[0.0009372893,0.00042862934,0.000111839334,0.00033535177,0.000018197037,0.00019578006,0.0002149986,0.8137536,0.00044281912,0.06865012,0.11460765,0.0003037076],"about_ca_topic_score_codex":0.0000034133425,"about_ca_topic_score_gemma":4.365216e-7,"teacher_disagreement_score":0.6766916,"about_ca_system_score_codex":0.00022720944,"about_ca_system_score_gemma":0.00018133303,"threshold_uncertainty_score":0.9999634},"labels":[],"label_agreement":null}]}