{"meta":{"query_hash":"914f64678312","filters":{"topic":"Advanced Wireless Network Optimization"},"cohort_total":897,"direct_labels_cover":0,"predictions_cover":897,"exported":897,"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/914f64678312","api":"https://metacan.xera.ac/api/v1/cohort?topic=Advanced+Wireless+Network+Optimization"},"results":[{"id":"W1002864269","doi":"10.24138/jcomss.v10i1.140","title":"Impact of Uncertain Channel Estimation and Outdated Feedback on the Adaptive M-PSK Modulation","year":2014,"lang":"en","type":"article","venue":"Journal of Communications Software and Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"Rayleigh fading; Computer science; Modulation (music); Channel (broadcasting); Link adaptation; Channel state information; Phase-shift keying; Bit error rate; Fading; SIGNAL (programming language); Algorithm; Pilot signal; Telecommunications; Statistics; Mathematics; Wireless; Physics; Acoustics","score_opus":0.032014765851061444,"score_gpt":0.2704092291916796,"score_spread":0.23839446334061815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1002864269","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":[0.18462946,0.001282244,0.8135827,0.00009502438,0.00007962566,0.0001819775,0.000007901863,0.00003139655,0.000109642926],"genre_scores_gemma":[0.99239933,0.0006407004,0.006886323,0.0000045736037,0.000033134904,0.000005629192,0.000010384982,0.000013598964,0.000006307491],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926853,0.0001465016,0.00036075854,0.000042637163,0.00011189224,0.00006968166],"domain_scores_gemma":[0.99859434,0.0005286939,0.00029082864,0.0003361242,0.00021365799,0.000036351783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003587389,0.000088009685,0.00018790584,0.0000929496,0.00009941005,0.000029074434,0.00015988546,0.000050302264,8.6350354e-7],"category_scores_gemma":[0.00013022823,0.00006079709,0.000036685207,0.0001470786,0.00005240907,0.00019219403,0.000024907818,0.00014600944,5.5033445e-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":[0.000013650106,0.000012475823,0.0005342865,0.000018439514,0.00004979993,5.2084577e-8,0.0003996343,0.98905367,0.0000555081,0.00074479415,0.00010929765,0.009008391],"study_design_scores_gemma":[0.00020701038,0.00013210572,0.007693873,0.00020895149,0.000018014514,0.000013997301,0.0001302018,0.99091345,0.000009653449,0.0005745598,0.000039957675,0.000058214],"about_ca_topic_score_codex":0.00001606678,"about_ca_topic_score_gemma":0.000002949099,"teacher_disagreement_score":0.8077699,"about_ca_system_score_codex":0.00005507421,"about_ca_system_score_gemma":0.000012647253,"threshold_uncertainty_score":0.24792334},"labels":[],"label_agreement":null},{"id":"W103958510","doi":"","title":"Effect of Subchannelization in Uplink in OFDM PHY of IEEE 802.16d.","year":2008,"lang":"en","type":"article","venue":"High Performance Computing, Networking and Communication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Orthogonal frequency-division multiplexing; Telecommunications link; PHY; IEEE 802; Computer science; Computer network; Electronic engineering; Telecommunications; Wireless; Physical layer; Channel (broadcasting); Engineering","score_opus":0.007690530218839273,"score_gpt":0.20790984661737918,"score_spread":0.2002193163985399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W103958510","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":[0.9638038,0.004731817,0.030567223,0.0000029328098,0.00027601357,0.00029260232,4.3960281e-7,0.00008762663,0.00023750108],"genre_scores_gemma":[0.99280447,0.0064320615,0.00059278274,0.0000023929144,0.00008488288,0.0000151423,0.00003958044,0.000024488554,0.000004197212],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986908,0.00018530688,0.0006568879,0.00013666434,0.00013024628,0.00020008314],"domain_scores_gemma":[0.99906844,0.00020870398,0.00025935817,0.00037967472,0.000059234237,0.000024598668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060730585,0.00016000181,0.00041394774,0.00021465405,0.00007587132,0.000008469691,0.00021267004,0.000109127686,3.8217948e-7],"category_scores_gemma":[0.00000609937,0.00017177811,0.00002087153,0.00066283933,0.000060998424,0.00013617538,0.000042477128,0.00020566882,5.7717943e-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":[0.000022811257,0.000014043033,0.063044354,0.00023710179,0.000005656175,3.1639743e-7,0.0005655774,0.9276764,0.000107039006,0.00006980596,0.000014562108,0.008242373],"study_design_scores_gemma":[0.0006486477,0.000095270574,0.021658318,0.0013179781,0.000004337974,0.0000069950206,0.000018672135,0.97554606,0.00051537144,0.000004972629,0.00004779868,0.0001355692],"about_ca_topic_score_codex":0.000053124953,"about_ca_topic_score_gemma":0.000008068593,"teacher_disagreement_score":0.04786971,"about_ca_system_score_codex":0.00005908053,"about_ca_system_score_gemma":0.0000100910465,"threshold_uncertainty_score":0.70049083},"labels":[],"label_agreement":null},{"id":"W112136115","doi":"10.1007/978-3-642-12242-2_4","title":"WiMAX Network Planning Using Adaptive-Population-Size Genetic Algorithm","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"WiMAX; Computer science; Wireless broadband; Genetic algorithm; Population; Software deployment; Population size; Wireless network; Wireless; Distributed computing; Computer network; Mathematical optimization; Telecommunications; Machine learning; Mathematics","score_opus":0.012525902762142905,"score_gpt":0.22716529680596725,"score_spread":0.21463939404382434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W112136115","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":[0.00022761131,0.0010904606,0.99506,0.00000654493,0.0026264156,0.00028506725,0.0000044554736,0.00026626358,0.00043316124],"genre_scores_gemma":[0.051239148,0.000045720117,0.94657093,0.00009461483,0.0018992965,0.000004417548,0.000011861377,0.0001077386,0.00002624981],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978468,0.000011750303,0.00042072445,0.0006717261,0.0004488033,0.0006002124],"domain_scores_gemma":[0.998835,0.0003069067,0.00015038902,0.0005009253,0.00009640114,0.00011032516],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001813214,0.0004718846,0.00041660864,0.00024143688,0.00023506989,0.00012900797,0.0005521211,0.00042634484,0.000028778846],"category_scores_gemma":[0.000022949718,0.00051728665,0.00006507211,0.0004051088,0.00024370737,0.00025766582,0.00018696902,0.0010042087,0.000006056247],"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":[0.0000014192163,0.0000014465891,0.00007911473,0.000009201558,0.000006157335,0.000018368908,0.000056989953,0.76551896,0.000035708275,0.00005402851,0.0000018251086,0.2342168],"study_design_scores_gemma":[0.000109896326,0.00002171916,0.00040036652,0.0003979589,0.00001176256,0.0000339359,5.3677866e-8,0.97948956,0.00007184181,0.018750696,0.00018181874,0.0005303816],"about_ca_topic_score_codex":0.000009210907,"about_ca_topic_score_gemma":0.000020161673,"teacher_disagreement_score":0.23368642,"about_ca_system_score_codex":0.00029298206,"about_ca_system_score_gemma":0.00007138222,"threshold_uncertainty_score":0.99972785},"labels":[],"label_agreement":null},{"id":"W125084465","doi":"10.1007/978-94-017-0502-8_11","title":"Packet Re-Transmission Options for the SS-OFDM-F/TA System","year":2004,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Alberta","funders":"","keywords":"Asynchronous communication; Computer science; Network packet; Transmission delay; Orthogonal frequency-division multiplexing; Computer network; Transmission (telecommunications); Scheduling (production processes); Throughput; Packet loss; Real-time computing; Wireless; Telecommunications; Channel (broadcasting); Mathematics; Mathematical optimization","score_opus":0.014731654348430066,"score_gpt":0.21516414619084637,"score_spread":0.2004324918424163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W125084465","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.7742147e-7,0.0020600527,0.72628975,0.00008946006,0.00066951266,0.0007941497,0.000043485812,0.00077182666,0.26928157],"genre_scores_gemma":[0.009709797,0.0119708115,0.16915283,0.000103985054,0.0018786448,0.00044047827,0.00085340434,0.000909063,0.804981],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893075,0.00000441582,0.00036077038,0.00026340183,0.00018248789,0.00025817967],"domain_scores_gemma":[0.99915844,0.00015050151,0.00007180372,0.00046141518,0.00008133114,0.00007649916],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000087378416,0.0003657979,0.00030236354,0.000079260695,0.0001752186,0.00003967093,0.00022083432,0.00038196935,0.00030748922],"category_scores_gemma":[0.000003393543,0.0002720373,0.00018114527,0.000040782405,0.00003583502,0.00009676765,0.000020573165,0.00028915887,0.000063977976],"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":[0.0000057870607,0.0000017298605,6.017928e-8,0.00023663751,0.00005823841,0.0000014467785,0.000022044565,0.7453364,0.000011787405,0.24654448,0.00249289,0.0052884896],"study_design_scores_gemma":[0.0005114081,0.000035819005,0.0000011152981,0.0013863059,0.00020116035,0.000010523842,0.000048839687,0.6104341,0.000094931405,0.007580128,0.37902606,0.00066960556],"about_ca_topic_score_codex":0.000002169974,"about_ca_topic_score_gemma":0.000009492399,"teacher_disagreement_score":0.55713695,"about_ca_system_score_codex":0.00031469733,"about_ca_system_score_gemma":0.000030023279,"threshold_uncertainty_score":0.9999732},"labels":[],"label_agreement":null},{"id":"W1423609206","doi":"10.1007/978-3-642-29222-4_9","title":"Channel Aware and Queue Aware Scheduling in LTE Uplink","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Telecommunications link; Orthogonal frequency-division multiple access; Queue; Scheduling (production processes); Computer network; Orthogonal frequency-division multiplexing; Channel (broadcasting); Real-time computing; Mathematical optimization; Mathematics","score_opus":0.018607537348527613,"score_gpt":0.22573897933752676,"score_spread":0.20713144198899916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1423609206","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":[0.0003235919,0.0018984566,0.99638927,0.00015884504,0.00045028713,0.0003949332,0.00003006681,0.0000844292,0.00027009335],"genre_scores_gemma":[0.10265664,0.0016125338,0.89526224,0.00005540599,0.00023439042,0.000033479577,0.000080165744,0.000048730093,0.000016414264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990748,0.0000042761244,0.0004738574,0.00009715852,0.00011599489,0.00023391237],"domain_scores_gemma":[0.99922025,0.00015136214,0.00017426138,0.00034366245,0.0000673697,0.000043067143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018677932,0.0002567849,0.00031913552,0.0001982418,0.00034389496,0.000070348004,0.00060319,0.00023376143,5.896408e-7],"category_scores_gemma":[0.000022842243,0.00023559983,0.00007323005,0.00016794838,0.00020383616,0.00033416407,0.00036087082,0.00042998133,2.400873e-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":[6.2354e-7,0.0000028729448,0.0000043868445,0.00023443603,0.00002511833,3.0118603e-8,0.00072848384,0.9893691,0.000001525158,0.0021252134,0.0000070365236,0.0075011626],"study_design_scores_gemma":[0.00014203375,0.000011360003,0.000025244723,0.0003481275,0.000022544524,0.0000045135653,0.000005600935,0.99671,0.00002130198,0.0004226826,0.0020382865,0.0002483187],"about_ca_topic_score_codex":0.0000093104745,"about_ca_topic_score_gemma":0.000068393725,"teacher_disagreement_score":0.10233305,"about_ca_system_score_codex":0.00007437967,"about_ca_system_score_gemma":0.000038744907,"threshold_uncertainty_score":0.9607482},"labels":[],"label_agreement":null},{"id":"W1487367993","doi":"10.1109/wowmom.2006.94","title":"Rate Scheduling of Multimedia Streams over ParallelWireless Data Channels with Heterogeneous Reliability","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Scheduling (production processes); Quality of service; Wireless; Computer network; Reliability (semiconductor); Distributed computing; Real-time computing; Multimedia; Mathematical optimization; Telecommunications","score_opus":0.010244639995126882,"score_gpt":0.21869445075926408,"score_spread":0.2084498107641372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1487367993","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":[0.53659487,0.00016561295,0.46232736,0.00000757959,0.0001356921,0.00019236295,0.000026915523,0.0002727983,0.0002768021],"genre_scores_gemma":[0.90234286,0.00007910085,0.097062945,0.0000068217346,0.00011004232,0.000011480459,0.00028799358,0.00005172263,0.00004703934],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989224,0.000023972872,0.00031725867,0.0003158213,0.00014948368,0.00027103565],"domain_scores_gemma":[0.99897,0.00008696033,0.00006688855,0.00076436874,0.000060681417,0.00005111124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000119000164,0.00019643093,0.00024745407,0.00004401742,0.000030870182,0.000017491624,0.0002609867,0.000081732316,0.000061948405],"category_scores_gemma":[0.00001424036,0.00016936626,0.00002370739,0.0002085306,0.000058637863,0.00030514385,0.00007526123,0.00010686669,0.000005419057],"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":[0.000024127301,0.000034950535,0.001435773,0.000045882425,0.000020752008,0.000004331572,0.00001605728,0.9954333,0.0007131011,0.000032454853,0.00009385819,0.0021454692],"study_design_scores_gemma":[0.00047483345,0.00002131752,0.0006413265,0.00003820171,0.000014243715,0.0000025188458,0.000009933522,0.98881716,0.009643798,0.000066392044,0.00006489283,0.00020536278],"about_ca_topic_score_codex":0.00011021036,"about_ca_topic_score_gemma":0.00011542568,"teacher_disagreement_score":0.365748,"about_ca_system_score_codex":0.00003894022,"about_ca_system_score_gemma":0.000012393152,"threshold_uncertainty_score":0.6906556},"labels":[],"label_agreement":null},{"id":"W1492268059","doi":"10.1109/vtcspring.2015.7146148","title":"Uplink Load Balancing over Multipath Heterogeneous Wireless Networks","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"McGill University","funders":"","keywords":"Computer science; Computer network; Load balancing (electrical power); Telecommunications link; Network packet; Multipath propagation; Wireless; Real-time computing; Channel (broadcasting); Distributed computing; Telecommunications","score_opus":0.01006446607871579,"score_gpt":0.21348147530102102,"score_spread":0.20341700922230524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1492268059","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":[0.10828308,0.00078392273,0.8864737,0.0000060445836,0.0007467313,0.00015117282,0.0000010612702,0.00097446423,0.0025797992],"genre_scores_gemma":[0.98651475,0.00014435129,0.012597985,0.00008729637,0.0003337837,0.000019496314,0.000019367992,0.000085001586,0.00019798217],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989482,0.000014276345,0.00023791949,0.00021226182,0.00019641359,0.0003908909],"domain_scores_gemma":[0.99938357,0.000032787462,0.000026386339,0.0002788056,0.00008498675,0.0001934387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000106075335,0.00021102541,0.0001998708,0.00003719753,0.00003821174,0.000035904493,0.00013112518,0.00013385498,0.0000445991],"category_scores_gemma":[0.000010077073,0.0002127942,0.00004496941,0.00020132009,0.000019542522,0.0001944756,0.000045626697,0.00016982174,0.00004735096],"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":[0.000008600726,0.000008436447,0.0005925614,0.0000074341283,0.000017145503,0.00001246507,0.000093733164,0.9889892,0.00008650848,0.00011657115,0.0010401868,0.009027178],"study_design_scores_gemma":[0.00050679233,0.00001519193,0.00005038979,0.000020998097,0.0000071244895,0.000014882317,0.000017985496,0.9976467,0.00054835016,0.000045093333,0.0008591895,0.00026734214],"about_ca_topic_score_codex":0.000021387343,"about_ca_topic_score_gemma":0.00005085946,"teacher_disagreement_score":0.87823164,"about_ca_system_score_codex":0.00027255522,"about_ca_system_score_gemma":0.000021183218,"threshold_uncertainty_score":0.8677496},"labels":[],"label_agreement":null},{"id":"W1492523644","doi":"10.1007/978-90-481-2530-2_26","title":"Limited-Feedback Multiuser MIMO-OFDM Downlink with Spatial Multiplexing and Per-Chunk/Per-Antenna User Scheduling","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in electrical engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Alberta","funders":"","keywords":"Telecommunications link; Orthogonal frequency-division multiplexing; Computer science; Scheduling (production processes); Spatial multiplexing; MIMO; Multiplexing; Throughput; MIMO-OFDM; Real-time computing; Electronic engineering; Computer network; Telecommunications; Mathematics; Wireless; Engineering; Mathematical optimization","score_opus":0.005399695172143725,"score_gpt":0.18573932471775748,"score_spread":0.18033962954561375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1492523644","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":[0.0014831396,0.0066548614,0.9887756,0.000076101,0.00027479584,0.0007194894,0.000014163172,0.0010681752,0.0009336428],"genre_scores_gemma":[0.73445916,0.0028917661,0.25930822,0.00018134233,0.0014222102,0.000060423194,0.00022226223,0.0008718379,0.0005827595],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99683535,0.000016456741,0.0007329481,0.00089317333,0.00044771552,0.001074347],"domain_scores_gemma":[0.99845797,0.00055629265,0.00013184802,0.00048640431,0.00011490937,0.0002525861],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00011449917,0.0012027083,0.0010550484,0.00073453545,0.000093755465,0.00011449256,0.00029804916,0.0011529576,0.000041448897],"category_scores_gemma":[0.00018868844,0.0011926945,0.0001525848,0.0003455114,0.000059951457,0.0002547934,0.00006717097,0.0026834498,0.000016002767],"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":[0.000068729605,0.000016019365,0.00006969166,0.0001389463,0.00010961383,0.00006161817,0.00011450672,0.9398041,0.0026335407,0.0002569127,0.0000031705429,0.05672315],"study_design_scores_gemma":[0.0010880388,0.00014398314,0.00017712211,0.0008398915,0.000081506514,0.000068104804,8.3574474e-7,0.992554,0.00081410445,0.00021813529,0.0025903487,0.0014238935],"about_ca_topic_score_codex":0.000016698932,"about_ca_topic_score_gemma":0.000107009,"teacher_disagreement_score":0.732976,"about_ca_system_score_codex":0.0004972876,"about_ca_system_score_gemma":0.000041162508,"threshold_uncertainty_score":0.9996174},"labels":[],"label_agreement":null},{"id":"W1493712935","doi":"10.1109/icc.2003.1204158","title":"Optimal radio channel allocation for fair queuing in wireless data networks","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Manitoba","funders":"","keywords":"Computer science; Computer network; Queueing theory; Radio channel; Channel (broadcasting); Radio networks; Wireless; Channel allocation schemes; Wireless network; Radio resource management; Fair queuing; Telecommunications; Quality of service; Dynamic priority scheduling; Round-robin scheduling","score_opus":0.017546736778315628,"score_gpt":0.23814638130675622,"score_spread":0.2205996445284406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1493712935","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":[0.010724191,0.00023986302,0.98759305,0.00008884955,0.0002976445,0.0004190878,0.000006862235,0.00040008372,0.00023038831],"genre_scores_gemma":[0.91727495,0.0002682477,0.08148006,0.000032446744,0.00024669222,0.00007408859,0.00053041853,0.00006300552,0.00003010444],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905056,0.0000077796285,0.0002554202,0.00027579014,0.0000802793,0.0003301868],"domain_scores_gemma":[0.9994411,0.00004662444,0.000030831718,0.00040075628,0.00003065397,0.000050030783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014963951,0.00015620317,0.00016741245,0.00008309366,0.000043579075,0.000028855902,0.00028027777,0.00010784981,0.0000046428354],"category_scores_gemma":[0.000014538764,0.0001758535,0.000020389267,0.00028923538,0.000015974478,0.0005711895,0.000055036035,0.00012697285,0.0000031597842],"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":[0.000010618538,0.000014225768,0.000017863927,0.000022225231,0.00001001033,0.000001183482,0.00007247136,0.99349076,0.00008530295,0.0014190205,0.00021026169,0.0046460712],"study_design_scores_gemma":[0.0007626902,0.000013535418,0.00006908743,0.000059143025,0.0000058469222,0.0000024944027,0.00005870835,0.998113,0.0004198542,0.00014522085,0.00014223655,0.00020822855],"about_ca_topic_score_codex":0.000020328542,"about_ca_topic_score_gemma":0.00019683194,"teacher_disagreement_score":0.90655077,"about_ca_system_score_codex":0.00016977302,"about_ca_system_score_gemma":0.000016613401,"threshold_uncertainty_score":0.7171098},"labels":[],"label_agreement":null},{"id":"W1494933589","doi":"10.1109/glocom.2003.1258786","title":"Downlink resource management for packet transmission in OFDM wireless communication systems","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":23,"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","keywords":"Orthogonal frequency-division multiplexing; Subcarrier; Computer science; Computer network; Telecommunications link; Resource allocation; Scheduling (production processes); Wireless; Network packet; Real-time computing; Engineering; Telecommunications; Channel (broadcasting)","score_opus":0.007183917711695535,"score_gpt":0.21265069055458233,"score_spread":0.20546677284288678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1494933589","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":[0.0080779735,0.00088235416,0.98329186,0.00012829684,0.000056451197,0.0007786076,0.00000284722,0.00034527064,0.0064363354],"genre_scores_gemma":[0.93207866,0.0009622855,0.06632743,0.000024938387,0.000026309486,0.00019834799,0.00012061977,0.000045593573,0.00021581652],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993086,0.000018333127,0.00025813273,0.00013109644,0.000092763315,0.0001911118],"domain_scores_gemma":[0.9995958,0.00003728334,0.000026031985,0.0002833784,0.000018244693,0.000039240127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012917767,0.00011647428,0.00013585018,0.00009463801,0.00004785697,0.000022132308,0.00014891932,0.00007516281,0.0000043603814],"category_scores_gemma":[0.0000012994923,0.000117740354,0.000027343149,0.00022323418,0.000012775021,0.00012690583,0.00001482829,0.00008685613,0.0000047618146],"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":[0.000013456753,0.000019427382,0.00001548432,0.00013277699,0.000010033816,8.368183e-7,0.00016286035,0.9701153,0.00006716521,0.011118923,0.00023909475,0.018104626],"study_design_scores_gemma":[0.0015759539,0.000018099558,0.00013475746,0.00038465334,0.000011543973,0.0000015608607,0.00040017357,0.9826595,0.0006334736,0.00083888025,0.013118649,0.00022273212],"about_ca_topic_score_codex":0.000012480979,"about_ca_topic_score_gemma":0.000018777555,"teacher_disagreement_score":0.9240007,"about_ca_system_score_codex":0.0001732307,"about_ca_system_score_gemma":0.0000034039033,"threshold_uncertainty_score":0.48013124},"labels":[],"label_agreement":null},{"id":"W1496380983","doi":"10.1109/glocom.2004.1379086","title":"Effects of imperfect subcarrier SNR information on adaptive bit loading algorithms for multicarrier systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Subcarrier; Computer science; Quantization (signal processing); Algorithm; Robustness (evolution); Bit error rate; Signal-to-noise ratio (imaging); Imperfect; Orthogonal frequency-division multiplexing; Channel (broadcasting); Telecommunications; Decoding methods","score_opus":0.006188941788311987,"score_gpt":0.21228062524741045,"score_spread":0.20609168345909848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1496380983","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":[0.020363081,0.0001855845,0.9766534,0.000006366538,0.00041078436,0.00097232935,0.000015756745,0.00027980658,0.0011128802],"genre_scores_gemma":[0.9727139,0.00003961709,0.026769567,0.000023494576,0.00018046772,0.00016139564,0.000025958203,0.000035744742,0.00004989249],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991909,0.000015064605,0.00031068252,0.00010219941,0.00014366544,0.00023743212],"domain_scores_gemma":[0.9993556,0.00027734588,0.000067589324,0.00013262953,0.00010316114,0.00006367242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009233031,0.00016826144,0.0002150608,0.00013427547,0.000043498807,0.000020637022,0.000072385716,0.00010374045,0.000006789646],"category_scores_gemma":[0.000054260498,0.00015771051,0.00005915252,0.0001759215,0.000016757727,0.00062870263,0.0000106189755,0.00008504638,0.000018570643],"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":[0.000029639952,0.0000076156257,0.000010740234,0.00016954108,0.000039946182,1.6162566e-7,0.00024578598,0.9793096,0.0012871115,0.0014086447,0.00030306942,0.017188096],"study_design_scores_gemma":[0.00074011646,0.00010193959,0.00004602825,0.000091898895,0.000020526026,9.3267187e-7,0.00006379298,0.9419741,0.055363756,0.000009565129,0.0014196327,0.00016767798],"about_ca_topic_score_codex":0.0000047685903,"about_ca_topic_score_gemma":0.0000013384291,"teacher_disagreement_score":0.9523508,"about_ca_system_score_codex":0.00014611117,"about_ca_system_score_gemma":0.000008481166,"threshold_uncertainty_score":0.64312476},"labels":[],"label_agreement":null},{"id":"W1498905612","doi":"10.1109/pacrim.2005.1517336","title":"On the performance of a practical OFDM adaptive modulation scheme using a feedback channel","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Orthogonal frequency-division multiplexing; Computer science; Channel (broadcasting); Electronic engineering; Multipath propagation; Modulation (music); Transceiver; Link adaptation; Wireless; Scheme (mathematics); Telecommunications; Fading; Engineering; Mathematics; Acoustics; Physics","score_opus":0.028302489833727816,"score_gpt":0.2472898680612775,"score_spread":0.21898737822754968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1498905612","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":[0.54068804,0.000014033059,0.4573326,0.00009819434,0.000035776655,0.00012358515,6.261468e-7,0.00007192772,0.0016352057],"genre_scores_gemma":[0.90511465,0.000025254601,0.094682455,0.000037080477,0.000077552875,0.000006244618,0.0000017782844,0.000018769906,0.000036227135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995166,0.000011924296,0.00014124087,0.00008199759,0.00012180949,0.00012644375],"domain_scores_gemma":[0.99968415,0.00008163197,0.00004018244,0.00012810054,0.000045736266,0.000020208567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000068833535,0.00008600892,0.00008246666,0.000034486427,0.000040003015,0.0000061037003,0.00004221527,0.00004440883,0.00005249449],"category_scores_gemma":[0.000021196369,0.00006563557,0.000019954789,0.0001673057,0.000021912048,0.00027525588,0.000012563978,0.000107817104,0.000015673484],"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":[0.000020725063,0.000013432699,0.000014490507,0.000006093379,0.000010215519,8.81319e-8,0.0000719382,0.99351865,0.0016573329,0.0037981549,0.00007452151,0.00081433274],"study_design_scores_gemma":[0.00012081734,0.000028948542,0.00015737856,0.00003376205,0.000003896436,0.00000206422,0.00003405669,0.99411327,0.0053458433,0.000057787038,0.000026714873,0.00007547685],"about_ca_topic_score_codex":0.0000012019219,"about_ca_topic_score_gemma":0.0000019812521,"teacher_disagreement_score":0.36442658,"about_ca_system_score_codex":0.000069771246,"about_ca_system_score_gemma":0.000008305789,"threshold_uncertainty_score":0.26765406},"labels":[],"label_agreement":null},{"id":"W1507309343","doi":"10.1109/milcom.2005.1606152","title":"Analysis of downlink capacity for an OFDM based cellular system","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"","keywords":"Orthogonal frequency-division multiplexing; Telecommunications link; Resource allocation; Computer science; Channel allocation schemes; Bandwidth (computing); Channel capacity; Frequency reuse; Outage probability; Bandwidth allocation; Multiplexing; Channel (broadcasting); Computer network; Mathematical optimization; Telecommunications; Wireless; Mathematics; Base station; Fading","score_opus":0.013530690575203293,"score_gpt":0.20962312413488315,"score_spread":0.19609243355967987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1507309343","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":[0.072158776,0.000032461143,0.9262417,0.0000058297396,0.000040148192,0.00014368439,0.00002470391,0.00027199215,0.0010807154],"genre_scores_gemma":[0.80604863,0.0000018256504,0.19374137,0.000009106766,0.000052663996,0.00001561184,0.00008939492,0.000015930664,0.000025444955],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945396,0.000011330312,0.00021617523,0.00011139636,0.00007851529,0.00012864948],"domain_scores_gemma":[0.99959266,0.000039451752,0.000036321453,0.000223931,0.000062812236,0.00004483234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008807988,0.000087026136,0.00021439262,0.00015242372,0.00002103227,0.000006214237,0.000072772564,0.00005629253,0.000032091535],"category_scores_gemma":[0.0000044013013,0.00008656967,0.00008782541,0.0004315396,0.0000100951665,0.00012052799,0.000003334742,0.000032576187,0.0000018967477],"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":[0.000003899556,0.000011992922,0.00014028687,0.00006203472,0.00011319824,6.060985e-8,0.000022451915,0.9935141,0.0031481672,0.00066558336,0.000034935936,0.0022832507],"study_design_scores_gemma":[0.00017390368,0.000013453518,0.00006757157,0.000007418925,0.00020625822,5.2104177e-8,0.000019942447,0.9761508,0.022779623,0.0000021597914,0.00048482398,0.00009400707],"about_ca_topic_score_codex":0.000008381769,"about_ca_topic_score_gemma":0.0000865498,"teacher_disagreement_score":0.7338899,"about_ca_system_score_codex":0.0000756211,"about_ca_system_score_gemma":0.000004103291,"threshold_uncertainty_score":0.35302088},"labels":[],"label_agreement":null},{"id":"W1512193556","doi":"10.5772/7687","title":"Downlink Resource Scheduling in an LTE System","year":2010,"lang":"en","type":"book-chapter","venue":"InTech eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":8,"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":"Telecommunications link; Computer science; Scheduling (production processes); Computational complexity theory; Computer network; Distributed computing; Scheme (mathematics); Mathematical optimization; Algorithm; Mathematics","score_opus":0.010824792380106281,"score_gpt":0.21248588169229315,"score_spread":0.20166108931218688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1512193556","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011639989,0.0004980938,0.229414,0.0000069687176,0.0008769234,0.00066837703,0.000024874074,0.0022554062,0.76509136],"genre_scores_gemma":[0.8006362,0.000064193344,0.08763049,0.000091396694,0.0022615858,0.00016708093,0.00027298642,0.0012160944,0.107659996],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985931,0.000011056471,0.0005024411,0.0003764804,0.00019876384,0.0003181888],"domain_scores_gemma":[0.9990557,0.00004589205,0.00011229689,0.00061591674,0.00006554353,0.000104685816],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013883165,0.00042510996,0.0004319798,0.00033261106,0.00004837233,0.0000495411,0.00033059268,0.00089358055,0.000026639793],"category_scores_gemma":[0.000008455959,0.0004881074,0.000081026985,0.00002271744,0.00006483367,0.00007428498,0.00006851305,0.0016294507,0.00007150873],"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":[0.00007903416,0.000014042208,0.000022527181,0.0011436397,0.00014797272,0.00037307802,0.00093111495,0.8008004,0.04379141,0.050980926,0.00004568727,0.10167016],"study_design_scores_gemma":[0.001550216,0.00018386125,0.000006041619,0.010844032,0.00014560488,0.00016794346,0.00024353908,0.60292315,0.07354476,0.00941503,0.29677653,0.0041993014],"about_ca_topic_score_codex":0.0000029748503,"about_ca_topic_score_gemma":0.000100546305,"teacher_disagreement_score":0.79947215,"about_ca_system_score_codex":0.0002733332,"about_ca_system_score_gemma":0.000023421628,"threshold_uncertainty_score":0.99975705},"labels":[],"label_agreement":null},{"id":"W1523368156","doi":"10.1049/iet-com.2009.0827","title":"Spectral efficiency analysis of rate-adaptive user selection diversity in orthogonal space time block coding multiple-input multiple-output systems with antenna selection","year":2011,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Université du Québec à Montréal; Polytechnique Montréal","funders":"","keywords":"Spectral efficiency; MIMO; Diversity gain; Block code; Computer science; Selection (genetic algorithm); Space–time block code; Algorithm; Coding (social sciences); Mathematics; Control theory (sociology); Telecommunications; Channel (broadcasting); Statistics; Decoding methods; Artificial intelligence","score_opus":0.028204509582647537,"score_gpt":0.2204212143652008,"score_spread":0.19221670478255326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1523368156","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":[0.5522492,0.00012264174,0.44626275,0.000012317044,0.00005056914,0.000442524,0.00003072393,0.00027583417,0.0005534685],"genre_scores_gemma":[0.9811574,0.00016445038,0.018454937,0.0000029368819,0.000014766025,0.00003465446,0.00007814822,0.000031437317,0.00006124145],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987555,0.00019111637,0.00036763688,0.00023476346,0.00017178436,0.0002791985],"domain_scores_gemma":[0.9986558,0.00030635396,0.0001859753,0.00053827977,0.00025170663,0.000061873936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002403847,0.00020537687,0.00036091878,0.0005689028,0.00030455342,0.00001849422,0.0003941034,0.00010765758,0.000011897325],"category_scores_gemma":[0.000047497793,0.00022101121,0.00008266987,0.002753973,0.00010566125,0.00031979493,0.0001524505,0.00032290796,0.000006370277],"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":[0.000065675784,0.00012275376,0.15448858,0.000011574497,0.00030313272,5.87019e-7,0.0011804955,0.841588,0.001946166,0.00025446876,0.000009985184,0.000028598743],"study_design_scores_gemma":[0.00044248207,0.000060233164,0.09941033,0.000059049264,0.00024600074,0.0000036236527,0.0002282416,0.89882666,0.00050355063,0.000004176189,0.000009918776,0.00020572831],"about_ca_topic_score_codex":0.0005787691,"about_ca_topic_score_gemma":0.0037035965,"teacher_disagreement_score":0.42890826,"about_ca_system_score_codex":0.00027507177,"about_ca_system_score_gemma":0.000029334455,"threshold_uncertainty_score":0.9012576},"labels":[],"label_agreement":null},{"id":"W1527503965","doi":"10.1002/wcm.2559","title":"A coordinated multi‐point‐based quality of service provision resource allocation scheme with inter‐cell interference mitigation","year":2014,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Resource allocation; Subcarrier; Quality of service; Heuristic; Scheme (mathematics); Interference (communication); Power control; Resource management (computing); Computer network; Distributed computing; Power (physics); Orthogonal frequency-division multiplexing","score_opus":0.01614289682181826,"score_gpt":0.2592517032378952,"score_spread":0.24310880641607693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1527503965","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":[0.3340695,0.0001725292,0.6649465,0.00007408333,0.00001592267,0.00030959552,0.000002988358,0.00018859025,0.00022027634],"genre_scores_gemma":[0.9083085,0.00005153538,0.09131381,0.00005034245,0.000011291588,0.000054724012,0.00016776146,0.000036058867,0.000005989766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884397,0.0002040684,0.0004938316,0.0001951694,0.00009136019,0.00017160225],"domain_scores_gemma":[0.99812526,0.0003658349,0.00025998722,0.000874862,0.00031427416,0.000059809052],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037728297,0.00018259352,0.00025821134,0.0001029026,0.00017639078,0.000038309438,0.00039343027,0.00008233942,0.000002025118],"category_scores_gemma":[0.000023534014,0.00018523913,0.000025852252,0.00043716084,0.00011418759,0.00016734803,0.00018975245,0.00023190575,0.0000014396425],"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":[0.000037698443,0.00017834078,0.0025244933,0.0005553707,0.000023660497,7.094608e-8,0.00190983,0.874929,0.027164387,0.0008549927,0.000013610478,0.09180855],"study_design_scores_gemma":[0.00075163145,0.000078046374,0.00040369396,0.0004992071,0.000010471119,9.838958e-7,0.00054339407,0.9918643,0.0054548,0.000013271096,0.00017640063,0.00020378336],"about_ca_topic_score_codex":0.00006136583,"about_ca_topic_score_gemma":0.00009564806,"teacher_disagreement_score":0.57423896,"about_ca_system_score_codex":0.000054883487,"about_ca_system_score_gemma":0.000019697796,"threshold_uncertainty_score":0.75538325},"labels":[],"label_agreement":null},{"id":"W1536395336","doi":"10.1002/cpe.1892","title":"A performance evaluation framework for packet scheduling algorithms in wireless system","year":2011,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Maximum throughput scheduling; Network packet; Scheduling (production processes); Round-robin scheduling; Algorithm; Wireless; Fair-share scheduling; Distributed computing; Computer network; Mathematical optimization; Quality of service; Mathematics; Telecommunications","score_opus":0.04465426547914656,"score_gpt":0.31715499168889066,"score_spread":0.2725007262097441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1536395336","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":[0.4235855,0.00068619003,0.5749781,0.0000068418162,0.00022658582,0.00022766858,9.919413e-7,0.000059797538,0.0002282981],"genre_scores_gemma":[0.90680885,0.00059262465,0.09231745,0.000017667575,0.0000394419,0.00020235626,0.000009920237,0.000011125889,5.862484e-7],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992795,0.000040351526,0.00022170739,0.00019940983,0.00011152902,0.00014750549],"domain_scores_gemma":[0.99945915,0.00022543142,0.00008113369,0.00006602495,0.00012551014,0.00004275143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002681782,0.000109183784,0.00011730863,0.000056257544,0.00010240409,0.000033957207,0.000043022184,0.0000675386,0.0000027466135],"category_scores_gemma":[0.000105767846,0.00011959503,0.000009328587,0.0001812596,0.00004031327,0.00097178627,0.000013363399,0.000110247136,0.0000011164399],"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":[0.000072263625,0.000036254314,0.0020130237,0.00027416967,0.000014772909,0.0000021126532,0.028211655,0.2026118,0.000052832725,0.009941904,0.000004371277,0.7567648],"study_design_scores_gemma":[0.00034964102,0.00004657004,0.0009700646,0.00020292337,0.000014767359,0.000012201658,0.00572003,0.9919393,0.00021577443,0.00035155614,0.000029921073,0.00014722152],"about_ca_topic_score_codex":0.0000041304274,"about_ca_topic_score_gemma":7.679957e-7,"teacher_disagreement_score":0.7893275,"about_ca_system_score_codex":0.000037313457,"about_ca_system_score_gemma":0.000016997237,"threshold_uncertainty_score":0.48769438},"labels":[],"label_agreement":null},{"id":"W1538196338","doi":"10.1109/broadnets.2004.14","title":"A unified scheduling approach for guaranteed services over IEEE 802.11e wireless LANs","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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","funders":"","keywords":"Computer science; Round-robin scheduling; Weighted fair queueing; Computer network; Fair queuing; Fair-share scheduling; Scheduling (production processes); Dynamic priority scheduling; Generalized processor sharing; Maximum throughput scheduling; Fixed-priority pre-emptive scheduling; Distributed computing; Two-level scheduling; Earliest deadline first scheduling; Network packet; Rate-monotonic scheduling; Quality of service; Engineering","score_opus":0.008936968878924516,"score_gpt":0.2175557831836589,"score_spread":0.2086188143047344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1538196338","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":[0.1278391,0.000114829076,0.8678835,0.000012568455,0.00019333947,0.00038328063,0.0000099862855,0.00075495214,0.002808469],"genre_scores_gemma":[0.77715826,0.000029351864,0.22222476,0.000095606,0.00017448967,0.000071974864,0.00008526418,0.0000737387,0.00008658428],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904823,0.00000657624,0.00023291432,0.0002380752,0.00012508972,0.00034910775],"domain_scores_gemma":[0.99960077,0.00003103997,0.000037198904,0.00022417208,0.00004615323,0.000060655148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006767464,0.00021120496,0.00021540385,0.00007600157,0.00008106035,0.000042600033,0.0001719039,0.0001297301,0.000011394675],"category_scores_gemma":[0.0000021490878,0.00021034261,0.00006364186,0.00026919585,0.000018199367,0.00024448166,0.000014334436,0.00012113383,0.0000081379585],"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":[0.000017078375,0.000025879766,0.00007989206,0.00021074717,0.00003623867,8.390286e-7,0.00022850257,0.99187475,0.0035083704,0.003611166,0.000019434061,0.00038711712],"study_design_scores_gemma":[0.0012572326,0.000020869767,0.000038942253,0.00005291989,0.000018215314,0.0000029896273,0.00020036988,0.99042356,0.0071324944,0.00039044576,0.00017681773,0.0002851601],"about_ca_topic_score_codex":0.000020803329,"about_ca_topic_score_gemma":0.000049547903,"teacher_disagreement_score":0.6493191,"about_ca_system_score_codex":0.00008655516,"about_ca_system_score_gemma":0.00001347129,"threshold_uncertainty_score":0.85775226},"labels":[],"label_agreement":null},{"id":"W1539516986","doi":"10.1109/milcom.2003.1290182","title":"Optimum scheduling for smart antenna systems in Rayleigh fading channel","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Telecommunications link; Rayleigh fading; Scheduling (production processes); Computational complexity theory; Channel (broadcasting); Transmitter power output; Fading; Transmission (telecommunications); Mathematical optimization; Algorithm; Real-time computing; Computer network; Transmitter; Mathematics; Telecommunications","score_opus":0.01305201145241746,"score_gpt":0.2200478731319459,"score_spread":0.20699586167952844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1539516986","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":[0.023969624,0.00066738034,0.9731649,0.000028300281,0.00060913723,0.00042919183,0.0000023771438,0.00042201002,0.0007070796],"genre_scores_gemma":[0.9294758,0.0001179726,0.07001206,0.000016518055,0.00014233793,0.00010489907,0.000016162943,0.000057051184,0.00005717948],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999172,0.000005171382,0.00024906924,0.00016808468,0.0000726603,0.00033307172],"domain_scores_gemma":[0.9997269,0.00003979789,0.000022970444,0.00012599632,0.000034999553,0.0000493317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000107442065,0.0001430369,0.00018566732,0.00013068486,0.000043579923,0.000032206193,0.000086277636,0.00008543571,0.0000030017572],"category_scores_gemma":[0.00001853999,0.00015202377,0.000034667137,0.0002571347,0.00000942276,0.00024580266,0.000013569878,0.00009714344,0.000009049034],"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":[0.0000054444376,0.000007806491,0.00004707102,0.00007223911,0.000008597559,0.0000022927527,0.00009622487,0.9962444,0.0012938181,0.002057705,0.000008986597,0.00015546106],"study_design_scores_gemma":[0.0007801813,0.000014426795,0.00002589383,0.0001759991,0.000003483455,0.000004047866,0.00016942607,0.99733305,0.0008435069,0.00038700987,0.00007292739,0.0001900226],"about_ca_topic_score_codex":0.00001516879,"about_ca_topic_score_gemma":0.000015972128,"teacher_disagreement_score":0.9055062,"about_ca_system_score_codex":0.00017718425,"about_ca_system_score_gemma":0.000009405472,"threshold_uncertainty_score":0.619935},"labels":[],"label_agreement":null},{"id":"W1539925810","doi":"10.1109/icc.2015.7248914","title":"AppRAN: Application-oriented radio access network sharing in mobile networks","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 New Brunswick","funders":"","keywords":"Computer science; Radio access network; Computer network; Quality of service; Cellular network; Resource allocation; Shared resource; Radio resource management; Distributed computing; Resource management (computing); Telecommunications; Wireless network; Base station; Mobile station; Wireless","score_opus":0.011983683851981565,"score_gpt":0.2503302119371732,"score_spread":0.23834652808519163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1539925810","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":[0.004992952,0.0012403866,0.9814243,0.0000106477855,0.00036860871,0.0005206943,6.0716184e-7,0.00073575473,0.010706055],"genre_scores_gemma":[0.98412335,0.00024796568,0.014021654,0.00006649467,0.00064489606,0.00053131464,0.00012456361,0.00008982708,0.00014993845],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998819,0.000015204405,0.00032496947,0.00028376107,0.00013884559,0.00041822265],"domain_scores_gemma":[0.99936414,0.000045338373,0.000040713192,0.00036570756,0.00004314729,0.00014094329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019636798,0.00018252559,0.00021065348,0.00007514344,0.000036579622,0.000051513787,0.0003173613,0.000118026015,0.000023797707],"category_scores_gemma":[0.000008800932,0.00019939453,0.000027576738,0.0010057134,0.000019958716,0.0004751176,0.00010277042,0.00021351237,0.000018093306],"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":[0.000009380375,0.0000124856815,0.009439709,0.000007702162,0.000008658624,0.0000015957532,0.000042369044,0.978952,0.0000022283268,0.0012268414,0.0032637138,0.007033335],"study_design_scores_gemma":[0.0004405789,0.000008615006,0.0003215656,0.000020576363,0.0000040948858,0.00000207384,0.000034492674,0.9791052,0.000021115366,0.00028023496,0.019542092,0.00021937664],"about_ca_topic_score_codex":0.000011743489,"about_ca_topic_score_gemma":0.00007143136,"teacher_disagreement_score":0.9791304,"about_ca_system_score_codex":0.00016744739,"about_ca_system_score_gemma":0.000010760999,"threshold_uncertainty_score":0.8131073},"labels":[],"label_agreement":null},{"id":"W1541848105","doi":"10.1002/9780470747759.ch3","title":"Multimedia Traffic Model","year":2009,"lang":"en","type":"other","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo; University of Victoria","funders":"","keywords":"Computer science; Traffic model; Multimedia; Computer graphics (images); Computer network","score_opus":0.005422619840685488,"score_gpt":0.19523241230451344,"score_spread":0.18980979246382795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1541848105","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[5.186595e-7,0.00051884406,0.4442691,0.000002545729,0.00010731549,0.000086875276,0.0000040660557,0.0019910813,0.55301964],"genre_scores_gemma":[0.00028885662,0.000966927,0.25058272,0.000029484645,0.00026266053,0.000009131804,0.00007933027,0.0007151003,0.7470658],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995475,0.0000023548266,0.00009181905,0.00012406877,0.000075302756,0.00015895464],"domain_scores_gemma":[0.99975586,0.000005178312,0.000018016515,0.0001736418,0.0000045908705,0.00004273838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000008715818,0.00018389185,0.00016135024,0.00010244788,0.000005932991,0.0000065268887,0.00008269303,0.00022987927,0.00084458734],"category_scores_gemma":[0.0000015132285,0.00018763717,0.000030577285,0.00007591092,0.00000843545,0.000023763901,0.000004499723,0.000114817114,0.0001793209],"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":[1.6701702e-7,0.0000022903946,2.3344016e-8,0.000007888717,0.000005824491,5.437951e-7,0.0000051395123,0.5764877,0.0000017338929,0.00001730541,0.39369744,0.029773938],"study_design_scores_gemma":[0.0000920325,0.0000020698958,1.675008e-7,0.00003504313,0.000006131945,3.6289026e-7,7.6113355e-7,0.9178903,0.0000055322353,0.000013678516,0.08175974,0.00019414401],"about_ca_topic_score_codex":5.8138306e-7,"about_ca_topic_score_gemma":0.00002510011,"teacher_disagreement_score":0.34140262,"about_ca_system_score_codex":0.000028768349,"about_ca_system_score_gemma":0.0000051399124,"threshold_uncertainty_score":0.9247639},"labels":[],"label_agreement":null},{"id":"W1544015136","doi":"10.1002/0471643505.ch5","title":"Markov Chains: Application to Multiplexing and Access","year":2004,"lang":"en","type":"other","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Aloha; Markov chain; Asynchronous communication; Multiplexing; Statistical time division multiplexing; Computer science; Random access; Simple (philosophy); Time-division multiplexing; Poisson distribution; Markov process; Throughput; Algorithm; Computer network; Mathematics; Telecommunications; Statistics","score_opus":0.005429707492074638,"score_gpt":0.23438891493733757,"score_spread":0.22895920744526294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1544015136","genre_codex":"methods","genre_gemma":"other","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":[0.0000025356069,0.000458512,0.7588582,0.000016406715,0.00009038143,0.0004168317,0.0000069012112,0.0009117056,0.23923852],"genre_scores_gemma":[0.020379113,0.003182543,0.45331603,0.00046013983,0.0016167022,0.0007904842,0.0005725246,0.003165266,0.51651716],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994869,0.0000030631961,0.00010146501,0.00019807722,0.00006690408,0.00014354225],"domain_scores_gemma":[0.99971145,0.000008654007,0.000026532443,0.00018437223,0.00000803784,0.000060930022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000018217715,0.00017093505,0.00014423525,0.00014990196,0.000015300251,0.000030898118,0.00010992681,0.000147297,0.0001404057],"category_scores_gemma":[0.0000041481476,0.00018410369,0.000012202181,0.00015873401,0.000009005624,0.000059925176,0.000041154744,0.0000755969,0.000026285617],"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":[0.000001145316,0.0000030636434,0.000020794623,0.000107703294,0.000014974307,4.876044e-7,0.000018070597,0.9164983,0.000042701682,0.0004510675,0.035977174,0.04686452],"study_design_scores_gemma":[0.00036503238,0.0000074850554,0.000093573406,0.00033992733,0.000011384729,0.0000019585455,0.000009443258,0.5585802,0.00016155255,0.00010762068,0.4396893,0.00063249003],"about_ca_topic_score_codex":0.000034449942,"about_ca_topic_score_gemma":0.0002007223,"teacher_disagreement_score":0.40371215,"about_ca_system_score_codex":0.00006589952,"about_ca_system_score_gemma":0.0000043422842,"threshold_uncertainty_score":0.75075305},"labels":[],"label_agreement":null},{"id":"W1545157032","doi":"10.1007/11422778_102","title":"Load Balancing and Relaying Framework in TDD W-CDMA Multi-hop Cellular Networks","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Load balancing (electrical power); Computer network; Hotspot (geology); Network packet; Distributed computing; Cellular network; Code division multiple access","score_opus":0.0074160540446062285,"score_gpt":0.20965384100333864,"score_spread":0.2022377869587324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1545157032","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":[0.0004169178,0.0058378894,0.9916903,0.00003967665,0.0011441411,0.00028632712,0.000001250854,0.00020896444,0.00037455984],"genre_scores_gemma":[0.40774596,0.00091355725,0.5901312,0.0002444021,0.000805046,0.0000075316043,0.000006420491,0.00009950257,0.000046331606],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977411,0.000015067307,0.00045982012,0.0007787827,0.00038592325,0.0006192872],"domain_scores_gemma":[0.9988569,0.00037492136,0.00010909878,0.00048054688,0.00006735992,0.000111157126],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037359912,0.00047430975,0.00046156647,0.00038243335,0.000112073714,0.00013539245,0.00047331175,0.00057969557,0.00001348558],"category_scores_gemma":[0.000066017485,0.0005146884,0.00004651296,0.0004584568,0.00023969324,0.0003162766,0.00025119312,0.0014853294,0.0000056917147],"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":[0.0000022443594,0.0000036415854,0.00017143314,0.000025849275,0.0000036403824,0.000032283995,0.0002766825,0.81474733,0.00003785023,0.00018901804,0.0000021405103,0.18450786],"study_design_scores_gemma":[0.00020859328,0.00001498394,0.00009135627,0.0011051167,0.0000052509768,0.000011333998,2.5957755e-7,0.9944039,0.00010618634,0.0032477228,0.0002859402,0.0005193775],"about_ca_topic_score_codex":0.000005599706,"about_ca_topic_score_gemma":0.00010427257,"teacher_disagreement_score":0.40732905,"about_ca_system_score_codex":0.0005964768,"about_ca_system_score_gemma":0.00006347695,"threshold_uncertainty_score":0.99973047},"labels":[],"label_agreement":null},{"id":"W1547422865","doi":"10.5539/jmr.v7n3p208","title":"Optimization of Heterogeneous Network Performances Based on the Signal Interferences Noise Ration(SINR)","year":2015,"lang":"en","type":"article","venue":"Journal of Mathematics Research","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Blocking (statistics); Waypoint; Signal-to-interference-plus-noise ratio; Markov chain; Interference (communication); SIGNAL (programming language); Computer science; Noise (video); Markov process; Wireless; Wireless network; Mathematics; Computer network; Power (physics); Real-time computing; Telecommunications; Statistics","score_opus":0.09266344724103603,"score_gpt":0.32151546832634065,"score_spread":0.2288520210853046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1547422865","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":[0.050675478,0.00035029597,0.94674164,0.00017938501,0.00020824585,0.00021531818,0.0000016637238,0.000020546397,0.00160741],"genre_scores_gemma":[0.93634903,0.0001883256,0.06317397,0.000010086695,0.0002268938,0.0000067543233,0.0000019829556,0.000023756787,0.000019190202],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981802,0.0001449445,0.0005325209,0.000060792376,0.000866847,0.00021469384],"domain_scores_gemma":[0.9980617,0.00069541286,0.00021824645,0.00017712144,0.00076365366,0.00008382809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021363825,0.00010256372,0.00021175246,0.00019243755,0.00007861653,0.000057328896,0.00032539543,0.000056924626,0.00008530314],"category_scores_gemma":[0.0002360664,0.000066704124,0.00005555789,0.00042853708,0.00008937361,0.00017646964,0.000028640752,0.00035257774,0.0000056819476],"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":[0.000040587285,0.00005347304,0.000057267327,0.00006046815,0.00002314555,0.0000025044792,0.00037122244,0.9971646,0.000062443374,0.00019506854,0.0013756262,0.0005935813],"study_design_scores_gemma":[0.00023054285,0.00030080555,0.0000046007185,0.00029183752,0.000008018135,0.000010701979,0.00032033824,0.9954327,0.0021925217,0.0010850416,0.000061690385,0.00006125014],"about_ca_topic_score_codex":4.5585128e-7,"about_ca_topic_score_gemma":0.0000015533491,"teacher_disagreement_score":0.8856736,"about_ca_system_score_codex":0.00009361648,"about_ca_system_score_gemma":0.00009816776,"threshold_uncertainty_score":0.27201152},"labels":[],"label_agreement":null},{"id":"W1549995050","doi":"10.1109/ictel.2003.1191630","title":"Packet scheduling to support loss guarantee for video traffic","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Computer network; Packet loss; Scheduling (production processes); Router; Real-time computing; Network packet; Round-robin scheduling; Fair-share scheduling; Quality of service; Engineering","score_opus":0.011706789157427688,"score_gpt":0.23929307969230126,"score_spread":0.2275862905348736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1549995050","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":[0.10765101,0.00005170755,0.8889784,0.000030738738,0.00029492273,0.000333776,0.000004637853,0.0004431049,0.0022116965],"genre_scores_gemma":[0.766307,0.000021341446,0.23309477,0.00014544639,0.0000624862,0.00005901555,0.000012723991,0.00005269316,0.00024451193],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992657,0.000006688115,0.00018588256,0.00016274933,0.000076502896,0.0003024988],"domain_scores_gemma":[0.99967116,0.00005135263,0.000013644528,0.00016167655,0.000041110823,0.00006105209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000096205855,0.00013199725,0.00013836256,0.000060649738,0.000043660268,0.000020741358,0.00007189529,0.00004905022,0.00012593366],"category_scores_gemma":[0.000049440616,0.00013872515,0.000044525113,0.00020756458,0.000008388101,0.0001301942,0.00000539424,0.00005871136,0.00006822028],"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":[0.0000059731756,0.000007126636,0.000021292544,0.000019959365,0.000010215963,0.0000017703323,0.00005811534,0.9904049,0.00022138207,0.002421663,0.0016484233,0.005179157],"study_design_scores_gemma":[0.0005981651,0.000071757764,0.000009942732,0.000022330869,0.000011605407,0.000011154178,0.00007862599,0.9569404,0.0086387675,0.00036364523,0.032904338,0.00034924704],"about_ca_topic_score_codex":1.6750516e-7,"about_ca_topic_score_gemma":0.000008613849,"teacher_disagreement_score":0.658656,"about_ca_system_score_codex":0.00004714589,"about_ca_system_score_gemma":0.000012183527,"threshold_uncertainty_score":0.56570476},"labels":[],"label_agreement":null},{"id":"W1552048869","doi":"10.1109/vetecs.2006.1682920","title":"Joint Radio Resource Management over Very Tightly Coupled Heterogeneous Networks for Multimode Reconfigurable Terminals","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Calgary","funders":"","keywords":"Computer network; Computer science; Radio resource management; Wireless network; Heterogeneous wireless network; Quality of service; Bandwidth (computing); Wireless; Wireless WAN; Scheduling (production processes); Heterogeneous network; Wi-Fi array; Telecommunications; Engineering","score_opus":0.007758338942157876,"score_gpt":0.19990301191295867,"score_spread":0.1921446729708008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1552048869","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":[0.01057769,0.0006063066,0.97261715,0.00001906376,0.0002803126,0.0007827448,0.0000059728372,0.0006650491,0.014445698],"genre_scores_gemma":[0.9191787,0.00030094088,0.07348652,0.00014077661,0.00051222194,0.00031021456,0.00022454804,0.00017731082,0.0056687626],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987013,0.000014302949,0.00039089296,0.0002951158,0.00012516316,0.0004732457],"domain_scores_gemma":[0.9994553,0.0000637973,0.00006035228,0.00032675272,0.000029174016,0.00006467998],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010593786,0.00025201522,0.000267577,0.00009017636,0.00009473931,0.000056052442,0.0001237806,0.00011487673,0.000118913325],"category_scores_gemma":[0.000002545085,0.00026036784,0.00010353197,0.00014074183,0.000019972855,0.00013748009,0.000017684431,0.00009570834,0.000011806172],"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":[0.000028078093,0.00002096492,0.000020210246,0.000056136632,0.000047460053,0.000011782204,0.000007677212,0.9825632,0.00028707375,0.00026150054,0.011937257,0.004758673],"study_design_scores_gemma":[0.00079456856,0.000023824357,0.00015766567,0.000047563273,0.000030038336,0.000007893032,0.000006671893,0.9793463,0.0017168693,0.0001545334,0.017395716,0.00031838566],"about_ca_topic_score_codex":0.000019583773,"about_ca_topic_score_gemma":0.000030263962,"teacher_disagreement_score":0.908601,"about_ca_system_score_codex":0.00015033051,"about_ca_system_score_gemma":0.0000032333242,"threshold_uncertainty_score":0.99998486},"labels":[],"label_agreement":null},{"id":"W1555537460","doi":"10.1017/9781316212493","title":"Radio Resource Management in Wireless Networks","year":2017,"lang":"en","type":"book","venue":"Cambridge University Press eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":417,"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 du Québec à Montréal; University of Manitoba","funders":"","keywords":"Wireless network; Computer science; Radio resource management; Computer network; Wireless; Resource allocation; Cognitive radio; Relay; Multi-frequency network; Field (mathematics); Wi-Fi array; Telecommunications; Power (physics)","score_opus":0.008839422431138413,"score_gpt":0.17627982021501432,"score_spread":0.1674403977838759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1555537460","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000035974626,0.00035292667,0.053323112,0.0000019482125,0.00037377336,0.00061250397,0.000036844613,0.00045978848,0.9448031],"genre_scores_gemma":[0.0014621677,0.0012281347,0.0004687987,0.000013260051,0.0002671806,0.0000045465495,0.00023437616,0.00015208697,0.99616945],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984887,0.000044898232,0.00024061043,0.00049797504,0.00022015306,0.000507652],"domain_scores_gemma":[0.99863976,0.000046429785,0.0001661405,0.0009713973,0.000037309543,0.00013897616],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000913482,0.00047984134,0.00051487575,0.00028166937,0.00017046237,0.000066344626,0.0008770223,0.00051296625,0.0000011466482],"category_scores_gemma":[0.0000017587126,0.0006770237,0.00012920151,0.000023734694,0.0001453303,0.00014640045,0.0003396567,0.0007691929,0.000005462743],"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":[0.0000668823,0.000009312417,0.0000040395184,0.00030327347,0.0002234108,0.0011092146,0.000029467801,0.6416051,0.0000012840034,0.10344917,0.23922221,0.013976652],"study_design_scores_gemma":[0.0007829254,0.000009028105,0.000027544766,0.00050608127,0.00010391625,0.0000058045403,0.000014485904,0.18408817,0.000010677766,0.0000021185822,0.8138332,0.0006160834],"about_ca_topic_score_codex":0.000010669326,"about_ca_topic_score_gemma":0.0000043855016,"teacher_disagreement_score":0.57461095,"about_ca_system_score_codex":0.00096525677,"about_ca_system_score_gemma":0.000033759818,"threshold_uncertainty_score":0.9995681},"labels":[],"label_agreement":null},{"id":"W1555742514","doi":"10.20381/ruor-4409","title":"Sending Video Over WiMAX for Inter-Vehicle Communications","year":2011,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":2,"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":"WiMAX; Telecommunications; Computer science; Computer network; Engineering; Wireless","score_opus":0.004649799708401779,"score_gpt":0.16241156877662394,"score_spread":0.15776176906822215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1555742514","genre_codex":"other","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":[0.043213617,0.0040972787,0.03093351,0.0005536995,0.0025541175,0.0016643411,0.0013618458,0.00022904103,0.9153926],"genre_scores_gemma":[0.97603065,0.0013306753,0.01028958,0.00014801527,0.00007749264,0.00007086104,0.000500125,0.00010830132,0.0114443125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988919,0.000017649876,0.0002910751,0.0001657713,0.00041203765,0.00022156369],"domain_scores_gemma":[0.9992278,0.00019961329,0.0001368875,0.00032169773,7.7103607e-7,0.00011320354],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000050937874,0.00021391762,0.0002445355,0.0000291807,0.00013079881,0.00001526436,0.00029475623,0.00005395054,0.000021597389],"category_scores_gemma":[0.000001994491,0.0002479439,0.00003234833,0.00005656105,0.000027365979,0.00030463477,0.00005513779,0.00017085629,1.4136798e-9],"study_design_candidate":"simulation_or_modeling","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":[0.0027148244,0.00017221367,0.01168073,0.008768079,0.0019290177,0.000052857988,0.0025365914,0.11696004,0.06831575,0.45168644,0.02317999,0.31200346],"study_design_scores_gemma":[0.0010936743,0.00009264433,0.011151497,0.0014947557,0.00017860072,0.0000032787516,0.00462132,0.7081163,0.15498073,0.0050289724,0.111755244,0.0014830019],"about_ca_topic_score_codex":0.00055783713,"about_ca_topic_score_gemma":0.054564934,"teacher_disagreement_score":0.93281704,"about_ca_system_score_codex":0.000012390797,"about_ca_system_score_gemma":0.00030424102,"threshold_uncertainty_score":0.99999726},"labels":[],"label_agreement":null},{"id":"W1556521882","doi":"10.5772/27825","title":"Scheduling Mechanisms with Call Admission Control (CAC) and an Approach with Guaranteed Maximum Delay for","year":2012,"lang":"en","type":"book-chapter","venue":"InTech eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Cegep de Thetford","funders":"","keywords":"Computer science; Call Admission Control; Scheduling (production processes); Computer network; Distributed computing; Operations management; Telecommunications; Engineering","score_opus":0.01146153921552871,"score_gpt":0.2092939846230575,"score_spread":0.1978324454075288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1556521882","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":[0.00013064401,0.00055737444,0.97066885,0.00000359775,0.000075851065,0.0013431403,0.000036220124,0.0005403698,0.026643945],"genre_scores_gemma":[0.4939722,0.000045177418,0.49688715,0.00008719413,0.00033294625,0.00032283564,0.00011591425,0.0005832884,0.0076532606],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859875,0.000009367928,0.00030779626,0.0004356622,0.0002273072,0.00042111985],"domain_scores_gemma":[0.99908996,0.00004255168,0.00014656757,0.0003709833,0.00014057061,0.00020936398],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012926359,0.0005757134,0.0005504491,0.00015773946,0.00010209649,0.000049058654,0.00016707022,0.00047865795,0.000008588264],"category_scores_gemma":[0.0000050779427,0.0004625307,0.000053346812,0.000015608844,0.00008036887,0.00012242938,0.000026721116,0.00049230654,0.0000020007606],"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":[0.0055107507,0.00015820858,0.000031301053,0.0033412334,0.0027869027,0.000119176606,0.0018499848,0.58820873,0.043596976,0.1649614,0.000044566958,0.18939078],"study_design_scores_gemma":[0.00838058,0.001965442,0.000001832474,0.0043446776,0.0012840652,0.00046096442,0.00015572493,0.911388,0.024490379,0.033438407,0.010264521,0.0038254482],"about_ca_topic_score_codex":0.0000022864526,"about_ca_topic_score_gemma":0.000012453308,"teacher_disagreement_score":0.4938416,"about_ca_system_score_codex":0.000095373405,"about_ca_system_score_gemma":0.000036762693,"threshold_uncertainty_score":0.9997826},"labels":[],"label_agreement":null},{"id":"W1569594456","doi":"10.1007/978-3-540-79232-1_6","title":"Evaluation of VoIP Quality over WiBro","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"WiBro; Voice over IP; Computer network; Computer science; Quality of service; Telecommunications link; Handover; Throughput; Mobile telephony; Telecommunications; Mobile radio; Wireless network; Wireless; The Internet","score_opus":0.031315511870130666,"score_gpt":0.2827215142987769,"score_spread":0.25140600242864625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1569594456","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":[0.00088469737,0.0011645929,0.993001,0.0000101410515,0.0008005088,0.00027005843,0.000005205558,0.00009979044,0.0037640184],"genre_scores_gemma":[0.83156675,0.000449022,0.1672978,0.00008315706,0.00044834922,0.000009172733,0.000021407996,0.00007002912,0.000054284723],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99768734,0.000029990071,0.00040351544,0.0004103397,0.0012326193,0.00023619422],"domain_scores_gemma":[0.99879366,0.00018100192,0.00014512142,0.00048290307,0.00035094,0.000046374305],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00084028405,0.00025191988,0.00031889562,0.0002823999,0.000050699062,0.000021626549,0.00038199272,0.00021058785,0.00004188682],"category_scores_gemma":[0.00008656405,0.00026186017,0.0000570184,0.00027986334,0.00029197268,0.00021610416,0.00009511256,0.00032115728,0.000005286451],"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":[0.0000013095488,0.0000029716487,0.000018039218,0.000019560803,0.00000542827,9.1941376e-7,0.00012913583,0.7474643,0.000076687094,0.00011909245,0.000013715245,0.25214884],"study_design_scores_gemma":[0.00019047207,0.000018158318,0.0003993269,0.00019312707,0.000013597079,0.000004238677,3.3257596e-8,0.9860963,0.0009614989,0.011694664,0.00016337774,0.0002651811],"about_ca_topic_score_codex":0.000005245641,"about_ca_topic_score_gemma":0.000035459918,"teacher_disagreement_score":0.8306821,"about_ca_system_score_codex":0.00039096014,"about_ca_system_score_gemma":0.00016435176,"threshold_uncertainty_score":0.9999834},"labels":[],"label_agreement":null},{"id":"W1571428298","doi":"10.1109/twc.2010.04.081437","title":"Joint connection admission control and routing in IEEE 802.16-based mesh networks","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":40,"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; University of British Columbia","funders":"","keywords":"Admission control; Computer science; Computer network; Quality of service; Routing (electronic design automation); Handover; Wireless mesh network; Call Admission Control; Wireless network; Wireless; Telecommunications","score_opus":0.013535996593372504,"score_gpt":0.23585382457050275,"score_spread":0.22231782797713023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1571428298","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":[0.06586452,0.00008051261,0.9316104,0.00036773377,0.0007022747,0.0004949945,0.000018995737,0.00054481335,0.0003157743],"genre_scores_gemma":[0.99306434,0.00072965067,0.0056409375,0.00010980048,0.000053395812,0.00026433007,0.000028644945,0.0000846321,0.000024262092],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985422,0.00014200472,0.00052435714,0.00028191388,0.00015380784,0.00035570195],"domain_scores_gemma":[0.9980501,0.00048087927,0.00010156482,0.0011152796,0.00009226767,0.00015990977],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027551886,0.0002858773,0.00031804005,0.00030527601,0.00046616327,0.000063789346,0.00032961386,0.00027788492,0.000034896984],"category_scores_gemma":[0.000012422958,0.0003300652,0.000083604646,0.00057542283,0.00015126631,0.00029635412,0.0000033409024,0.0013093749,0.000007784254],"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":[0.000026707417,0.00013114008,0.00010516244,0.00001575571,0.000024112418,7.00627e-7,0.00009543798,0.9613413,0.009809084,0.00045248168,0.00003305571,0.02796504],"study_design_scores_gemma":[0.0012966958,0.000035300025,0.0003556887,0.0001304784,0.00003541381,0.000006898666,0.00006463219,0.99215996,0.0053906157,0.00005688195,0.00014800424,0.00031941562],"about_ca_topic_score_codex":0.00006060921,"about_ca_topic_score_gemma":0.001718678,"teacher_disagreement_score":0.92719984,"about_ca_system_score_codex":0.00017205144,"about_ca_system_score_gemma":0.00004007261,"threshold_uncertainty_score":0.9999151},"labels":[],"label_agreement":null},{"id":"W1571942004","doi":"10.1002/9780470986424.ch5","title":"MAC Layer Performance Limitations","year":2008,"lang":"en","type":"other","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Superframe; Computer network; Network packet; Computer science; Blocking (statistics); Telecommunications link","score_opus":0.020851947981912155,"score_gpt":0.19746820847578386,"score_spread":0.17661626049387172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1571942004","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000007907793,0.00070624123,0.13476431,0.000004912179,0.00030989372,0.000104481755,0.000004740937,0.0014631017,0.8626344],"genre_scores_gemma":[0.002562885,0.019269532,0.042171285,0.00003186234,0.00032811888,0.000031839594,0.000093239156,0.0007262832,0.93478495],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99957937,0.0000031035954,0.00009340893,0.00010326843,0.00007714988,0.0001437214],"domain_scores_gemma":[0.9997507,0.000013148645,0.000021670761,0.00017357728,0.000009895884,0.00003104191],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0000064782384,0.00015266391,0.00012110358,0.00011462994,0.000020880032,0.000005469302,0.000072975134,0.00014668076,0.0012934553],"category_scores_gemma":[0.0000024632611,0.00015758231,0.000023907447,0.00013129505,0.000015548781,0.000045637516,0.000008860856,0.00011051454,0.000615967],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[1.9501957e-7,0.00000201667,0.00001088338,0.000020551568,0.00001290151,7.7869373e-7,0.00000890629,0.42781156,0.0000031075583,0.00006258583,0.56672597,0.005340508],"study_design_scores_gemma":[0.00006546524,0.0000036746471,0.000019170799,0.000043557444,0.000005000988,0.0000027792462,0.0000020735674,0.21297924,0.000044612632,0.000002581721,0.7866458,0.00018598397],"about_ca_topic_score_codex":0.0000018868993,"about_ca_topic_score_gemma":0.00002503739,"teacher_disagreement_score":0.21991986,"about_ca_system_score_codex":0.000028450833,"about_ca_system_score_gemma":0.0000062177783,"threshold_uncertainty_score":0.9996195},"labels":[],"label_agreement":null},{"id":"W1571948099","doi":"10.1007/978-3-642-12630-7_15","title":"WiMAX TV: Possibilities and Challenges","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Communications Research Centre Canada","funders":"","keywords":"WiMAX; IPTV; Last mile (transportation); Computer network; Computer science; Key (lock); Telecommunications link; Video quality; Telecommunications; Wireless network; Multimedia; Wireless; Engineering; Mile; Computer security; Geography","score_opus":0.0232073657390348,"score_gpt":0.21764740923760853,"score_spread":0.19444004349857374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1571948099","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":[0.00051997014,0.0050195833,0.9898417,0.00039918048,0.0006432949,0.00044578884,0.00005771503,0.0001457277,0.0029270623],"genre_scores_gemma":[0.013444147,0.00425893,0.98195845,0.00003538363,0.00018224928,0.000019249785,0.000031243373,0.00003370105,0.000036652036],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992419,0.0000031511445,0.000378407,0.00009431645,0.00012038712,0.00016186868],"domain_scores_gemma":[0.9992161,0.00019521239,0.00015313984,0.00032396597,0.000077942575,0.00003366292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014226623,0.0002308471,0.00027591115,0.00011794001,0.00042046627,0.000077762044,0.00050215784,0.00023391772,8.8658817e-7],"category_scores_gemma":[0.000023942623,0.00019822273,0.000076033466,0.00006979566,0.00042935828,0.0002323566,0.000235547,0.0004022278,1.6589416e-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":[5.306447e-7,0.0000019966542,6.027849e-7,0.00030762624,0.000033057633,1.7048256e-8,0.0009809393,0.9561034,0.000009347923,0.020778028,0.0000069917237,0.021777498],"study_design_scores_gemma":[0.00013002541,0.000027992184,0.000022784749,0.00020827883,0.0000354472,0.0000083934265,0.000008163043,0.97102237,0.00009226157,0.002629942,0.025520258,0.00029405684],"about_ca_topic_score_codex":0.000004783705,"about_ca_topic_score_gemma":0.00007470166,"teacher_disagreement_score":0.025513267,"about_ca_system_score_codex":0.000032007003,"about_ca_system_score_gemma":0.000033499506,"threshold_uncertainty_score":0.8083288},"labels":[],"label_agreement":null},{"id":"W1575208491","doi":"10.1109/aps.2005.1551806","title":"New variable-rate variable-power adaptive modulation scheme for time-varying MIMO channels","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"MIMO; Variable (mathematics); Quantization (signal processing); Link adaptation; Computer science; 3G MIMO; Electronic engineering; Wireless; Control theory (sociology); Multi-user MIMO; Power (physics); Scheme (mathematics); Modulation (music); Quadrature amplitude modulation; Bit error rate; Telecommunications; Channel (broadcasting); Algorithm; Engineering; Mathematics; Fading; Artificial intelligence; Physics","score_opus":0.00993371416969436,"score_gpt":0.21075125196094083,"score_spread":0.20081753779124648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1575208491","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":[0.00029658483,0.00010181907,0.9820897,0.000065450055,0.0003666468,0.0005174916,0.000008773859,0.00074298726,0.015810534],"genre_scores_gemma":[0.12797198,0.000017685976,0.8664555,0.00010515252,0.00063607405,0.000063620406,0.00008593589,0.000101815785,0.0045622448],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886364,0.000015950118,0.0003015282,0.0002849641,0.000117416654,0.00041651167],"domain_scores_gemma":[0.99935716,0.00012553534,0.00005726466,0.00023046773,0.00011055182,0.0001189899],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015753564,0.0002456395,0.00022553104,0.00009660432,0.00009366022,0.00005144611,0.00012018751,0.00015950229,0.0006793252],"category_scores_gemma":[0.00003176592,0.0002701706,0.000043017953,0.00030956606,0.0000072647413,0.0007496362,0.000026815294,0.00012108673,0.00010412167],"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":[0.000031330394,0.000010443909,0.000002651063,0.000012323821,0.00004666842,1.800252e-7,0.00007564847,0.9751126,0.0073039904,0.009628589,0.004065535,0.0037100234],"study_design_scores_gemma":[0.0006961028,0.000030861294,0.000005703706,0.000043284672,0.000014846167,0.000001404414,0.000006299002,0.9858781,0.0021083916,0.0024441986,0.00844839,0.00032238604],"about_ca_topic_score_codex":0.000008918543,"about_ca_topic_score_gemma":0.0000020396624,"teacher_disagreement_score":0.1276754,"about_ca_system_score_codex":0.00016043286,"about_ca_system_score_gemma":0.00003511514,"threshold_uncertainty_score":0.999975},"labels":[],"label_agreement":null},{"id":"W1575827797","doi":"10.1109/tcomm.2010.03.080238","title":"Two-user opportunistic scheduling using hierarchical modulations in wireless networks with heterogenous average link gains","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":21,"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; Institut National de la Recherche Scientifique","funders":"","keywords":"Fading; Scheduling (production processes); Computer science; Spectral efficiency; Wireless; Algorithm; Computer network; Real-time computing; Mathematics; Channel (broadcasting); Telecommunications; Mathematical optimization","score_opus":0.02981871467635826,"score_gpt":0.2724712433676104,"score_spread":0.24265252869125215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1575827797","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":[0.08631775,0.000039362974,0.9118598,0.00017882649,0.00030792225,0.00040592047,0.000030277823,0.00042892477,0.00043122744],"genre_scores_gemma":[0.8681286,0.00034855085,0.13107891,0.000044927077,0.00006786296,0.00013384719,0.00006433071,0.00010858375,0.00002438561],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985583,0.00010219022,0.00046759265,0.00027459263,0.00017966499,0.00041768822],"domain_scores_gemma":[0.9977464,0.0003226591,0.00007254009,0.0015901075,0.00009762719,0.00017063586],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014633899,0.00028972578,0.00026802009,0.00032733014,0.00058685493,0.000075908894,0.0005531813,0.00019050433,0.000033578654],"category_scores_gemma":[0.00000474279,0.00032470012,0.00007698193,0.0008194064,0.00021455118,0.0003457256,0.0000076776705,0.0018545489,0.000008813106],"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":[0.000014697991,0.00014392279,0.00008715922,0.000008773034,0.00004152982,0.000004236083,0.00015906677,0.9891127,0.0029138217,0.0011014432,9.657903e-7,0.0064117196],"study_design_scores_gemma":[0.00059720234,0.000025424199,0.00009695883,0.00008832709,0.000039079307,0.00003075818,0.000029443758,0.9981873,0.0003712673,0.000114576425,0.00008096585,0.00033870887],"about_ca_topic_score_codex":0.000048217204,"about_ca_topic_score_gemma":0.0023319747,"teacher_disagreement_score":0.7818108,"about_ca_system_score_codex":0.00015785523,"about_ca_system_score_gemma":0.0000783662,"threshold_uncertainty_score":0.9999205},"labels":[],"label_agreement":null},{"id":"W1576016125","doi":"10.1109/pacrim.2005.1517297","title":"Fast optimal radio resource allocation in OFDMA system based on branch-and-bound method","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Lakehead University","funders":"","keywords":"Computer science; Orthogonal frequency-division multiple access; Quality of service; Base station; Frequency-division multiple access; Resource allocation; Throughput; Transmission (telecommunications); Channel (broadcasting); Computational complexity theory; Mathematical optimization; Orthogonal frequency-division multiplexing; Constraint (computer-aided design); Channel allocation schemes; Algorithm; Computer network; Wireless; Mathematics; Telecommunications","score_opus":0.005883136104817576,"score_gpt":0.221395465082969,"score_spread":0.21551232897815142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1576016125","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":[0.015292608,0.00018481187,0.97797567,0.00022960837,0.000056405566,0.00020775819,0.0000018618903,0.00042068725,0.0056305802],"genre_scores_gemma":[0.82022464,0.000023643437,0.17928891,0.00007359103,0.00012514806,0.000039637758,0.000015854048,0.00004179814,0.00016675492],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921507,0.000051559393,0.00022339459,0.00019187243,0.00012373361,0.00019439386],"domain_scores_gemma":[0.9996257,0.000107262014,0.00002774714,0.00017080587,0.00001674147,0.00005173268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018726022,0.0001426251,0.00016280769,0.00013576227,0.000035233403,0.000027918526,0.00006894117,0.00008557002,0.000025106667],"category_scores_gemma":[0.000009247407,0.00014786914,0.000021316255,0.00023581005,0.000011821388,0.00014944076,0.000009341779,0.0001223458,0.00001186182],"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":[0.000016929804,0.000010686935,0.00006225495,0.000046568417,0.000005414845,8.4150037e-7,0.0000823519,0.96392876,0.00050210766,0.0009607658,0.00014057696,0.03424272],"study_design_scores_gemma":[0.0005196345,0.00001450124,0.00039331475,0.00009568964,0.0000061465776,0.0000022089334,0.00005417936,0.9945833,0.0025630007,0.0000017719949,0.0016118953,0.00015436436],"about_ca_topic_score_codex":0.000006991277,"about_ca_topic_score_gemma":0.000023746867,"teacher_disagreement_score":0.80493206,"about_ca_system_score_codex":0.00021912217,"about_ca_system_score_gemma":0.0000074050154,"threshold_uncertainty_score":0.60299283},"labels":[],"label_agreement":null},{"id":"W1580440216","doi":"","title":"Upper and lower bounds for pilot coverage in UMTS networks","year":2009,"lang":"en","type":"article","venue":"ORCA Online Research @Cardiff","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"UMTS frequency bands; Upper and lower bounds; Computer science; Computer network; Mathematics","score_opus":0.029431207903812956,"score_gpt":0.33345040607042936,"score_spread":0.3040191981666164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1580440216","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":[0.36196932,0.008363087,0.6182211,0.0011215415,0.0006892001,0.00237064,0.00011866679,0.00058415986,0.0065622786],"genre_scores_gemma":[0.9878841,0.003920373,0.006900209,0.00006268485,0.0006139533,0.000050341943,0.00015369558,0.0000671557,0.00034747508],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983,0.00006852086,0.00025154947,0.0003092159,0.00031675055,0.0007539562],"domain_scores_gemma":[0.99917495,0.00024793987,0.000017697626,0.00029390372,0.00011847569,0.00014705361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004935811,0.0001865187,0.00027637192,0.0002317578,0.00011010741,0.000081417886,0.00015504748,0.00012309298,0.000016318952],"category_scores_gemma":[0.00011465621,0.00019344495,0.00005248745,0.0005420413,0.00006558619,0.00024979515,0.000071444316,0.0005214257,0.0000044687476],"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":[0.00013013542,0.000104880564,0.00037058396,0.000031921423,0.000018183575,0.00001665648,0.000030339872,0.90973955,0.00044181148,0.0003447971,0.0027638008,0.08600733],"study_design_scores_gemma":[0.0013414312,0.00041791773,0.0073495456,0.000101623096,0.0000051502616,0.000007166139,0.00001773305,0.97796696,0.00007023277,0.0020671138,0.010383739,0.0002713936],"about_ca_topic_score_codex":0.0000070012425,"about_ca_topic_score_gemma":0.000042192125,"teacher_disagreement_score":0.6259148,"about_ca_system_score_codex":0.00018742288,"about_ca_system_score_gemma":0.000029002915,"threshold_uncertainty_score":0.7888456},"labels":[],"label_agreement":null},{"id":"W1582415383","doi":"10.1007/978-3-540-27824-5_82","title":"Throughput Maximization of ARQ Transmission Protocol Employing Adaptive Modulation and Coding","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Computer science; Link adaptation; Automatic repeat request; Hybrid automatic repeat request; Selective Repeat ARQ; Throughput; Network packet; Computer network; Go-Back-N ARQ; Coding (social sciences); Linear network coding; Wireless; Channel (broadcasting); Fading; Telecommunications link; Telecommunications","score_opus":0.015527983320410084,"score_gpt":0.23864518623648084,"score_spread":0.22311720291607076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1582415383","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":[0.000032877186,0.00006759712,0.9910835,0.00001357079,0.00014026645,0.008055867,0.000002004556,0.00012128843,0.00048301995],"genre_scores_gemma":[0.31156033,0.00007244612,0.6874922,0.00002461789,0.00014396102,0.0006142345,0.000010919567,0.00006909116,0.0000121997855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866325,0.00000880552,0.0003590988,0.00042976154,0.00032350537,0.00021559554],"domain_scores_gemma":[0.99941653,0.00007869467,0.0001406665,0.00021075208,0.00010448626,0.000048881117],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013827303,0.00027525096,0.0002883122,0.0003024991,0.000087653534,0.000042614007,0.00018783195,0.00021098192,0.000009942818],"category_scores_gemma":[0.000010666502,0.0002773483,0.000032744065,0.000262509,0.0001935562,0.00037121624,0.00006091116,0.00028388115,5.932401e-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":[0.000007657826,0.000003036585,0.000010693236,0.00010302899,0.000003110603,0.0000016017808,0.00028612578,0.7436899,0.00033364352,0.0009604964,2.2936635e-7,0.25460047],"study_design_scores_gemma":[0.00030350283,0.000057064262,0.00005866,0.0011475646,0.0000052326727,0.000004902704,1.4251194e-7,0.9547828,0.0024311813,0.04092995,0.000026541868,0.00025246863],"about_ca_topic_score_codex":0.0000032698313,"about_ca_topic_score_gemma":0.000005221741,"teacher_disagreement_score":0.31152746,"about_ca_system_score_codex":0.00024342419,"about_ca_system_score_gemma":0.00006617188,"threshold_uncertainty_score":0.9999679},"labels":[],"label_agreement":null},{"id":"W1583129082","doi":"10.1109/wimob.2005.1512855","title":"Designing WLAN with minimum bandwidth guarantees","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Polytechnique Montréal","funders":"","keywords":"Tabu search; Computer science; Bandwidth (computing); Wi-Fi; Computer network; Wireless; Channel (broadcasting); Wireless network; Local area network; Wireless lan; Bandwidth allocation; Mathematical optimization; Algorithm; Telecommunications; Mathematics","score_opus":0.0030651637831894145,"score_gpt":0.1629259896294729,"score_spread":0.1598608258462835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1583129082","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":[0.022157889,0.00016486442,0.9556444,0.000011598404,0.000050511422,0.00007776706,5.573775e-7,0.00059203623,0.021300372],"genre_scores_gemma":[0.8662448,0.000014475762,0.13294975,0.000014341401,0.00009163353,0.000008680695,0.000012333211,0.00003379438,0.0006301978],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99955106,0.000005046847,0.000099840276,0.000094308925,0.00007583541,0.00017390771],"domain_scores_gemma":[0.9998281,0.000025223762,0.000012263889,0.00009818126,0.000017151548,0.000019088637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002289839,0.00010077173,0.00008712753,0.000038438066,0.00003335116,0.00001898875,0.000048424186,0.000031944808,0.00004991035],"category_scores_gemma":[0.0000012393247,0.000083318584,0.000012324322,0.00014403701,0.000014452944,0.00012326433,0.0000046592545,0.000050382696,0.000016099259],"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":[0.0000052787454,0.000004643513,0.0009746902,0.0000079925885,0.0000062458907,0.0000044481644,0.000017511224,0.9932134,0.0037273543,0.00039019887,0.0009690065,0.000679203],"study_design_scores_gemma":[0.00046646746,0.00003265492,0.0008775933,0.000040318857,0.000010297282,0.000010427607,0.00004106627,0.9802015,0.016626906,0.0003073986,0.0011025582,0.000282838],"about_ca_topic_score_codex":0.000007719348,"about_ca_topic_score_gemma":0.000038711467,"teacher_disagreement_score":0.8440869,"about_ca_system_score_codex":0.000021601343,"about_ca_system_score_gemma":0.000003601796,"threshold_uncertainty_score":0.3397633},"labels":[],"label_agreement":null},{"id":"W1587066713","doi":"10.1109/broadnets.2004.35","title":"Dynamic downlink OFDM resource allocation for broadband multimedia services in wireless cellular systems","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Subcarrier; Computer science; Telecommunications link; Fading; Orthogonal frequency-division multiplexing; Computer network; Link adaptation; Resource allocation; Network packet; Wireless; Bandwidth (computing); Broadband networks; Channel (broadcasting); Electronic engineering; Real-time computing; Broadband; Telecommunications; Engineering","score_opus":0.003951423752536098,"score_gpt":0.19778435804716193,"score_spread":0.19383293429462584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1587066713","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":[0.21991374,0.0004428681,0.7782975,0.000040168932,0.00014942646,0.00051756314,0.000006035526,0.00032600705,0.00030669337],"genre_scores_gemma":[0.97358006,0.000101546284,0.02577628,0.00002227401,0.00006313675,0.00008915461,0.0002071459,0.000054804525,0.0001055798],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991556,0.000013518823,0.00026678958,0.00018377049,0.00009750942,0.00028283187],"domain_scores_gemma":[0.9996372,0.0000508937,0.000039994553,0.00017958102,0.000036531434,0.000055818226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011920119,0.00014965488,0.00016753186,0.00010101646,0.000035175803,0.000032118816,0.00012464974,0.00013277763,0.0000031798807],"category_scores_gemma":[0.0000041015583,0.00016090003,0.000027131913,0.00021587704,0.000013479936,0.00017581314,0.000011740142,0.00009620423,0.000008046264],"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":[0.000009967081,0.00001632174,0.00008142469,0.0002571172,0.0000090043795,0.0000014951812,0.00036462478,0.98807704,0.008881722,0.0002971408,0.000012356251,0.001991807],"study_design_scores_gemma":[0.0009328147,0.000013323379,0.00013453052,0.00014581603,0.00000709969,0.0000016836669,0.00023580628,0.9943418,0.0035244545,0.000102561185,0.00037957067,0.00018054705],"about_ca_topic_score_codex":0.00007882263,"about_ca_topic_score_gemma":0.0002556753,"teacher_disagreement_score":0.75366634,"about_ca_system_score_codex":0.00030236613,"about_ca_system_score_gemma":0.000014136213,"threshold_uncertainty_score":0.65613127},"labels":[],"label_agreement":null},{"id":"W1589240109","doi":"10.1002/9780470403686.ch21","title":"Subchannel Allocation and Connection Admission Control in OFDMA‐Based IEEE 802.16/WiMAX‐Compliant Infrastructure Wireless Mesh Networks","year":2008,"lang":"en","type":"other","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"WiMAX; Computer network; Computer science; Wireless mesh network; Queueing theory; Admission control; IEEE 802.11s; Resource allocation; IEEE 802; Mesh networking; Service set; Radio resource management; Wireless network; Wireless; Wi-Fi; Telecommunications; Quality of service","score_opus":0.005786085698808544,"score_gpt":0.2009963793453844,"score_spread":0.19521029364657586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1589240109","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":[0.00045378687,0.0014878465,0.9834933,0.000058715217,0.0011264242,0.0009874178,0.000027593871,0.0010661248,0.011298786],"genre_scores_gemma":[0.9592184,0.014024415,0.0047045974,0.00037991535,0.0013588463,0.00032213074,0.000742661,0.001559702,0.017689323],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998323,0.000066748005,0.0004469649,0.0005050802,0.0002208978,0.00043727088],"domain_scores_gemma":[0.99919957,0.00007514119,0.00019365572,0.00031598445,0.00005591677,0.00015975145],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007597617,0.000573674,0.00062957406,0.00044242744,0.000066422675,0.000034010547,0.00014542292,0.00085299666,0.00047277435],"category_scores_gemma":[0.000010418768,0.00058204576,0.00006282157,0.00041233283,0.00006001044,0.00013353667,0.000016438022,0.0005232809,0.0000060779857],"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":[0.000040949988,0.000018422561,0.00027896574,0.00013352458,0.000046010653,0.0000067950605,0.00002176826,0.910337,0.00017061451,0.00009602171,0.08129747,0.0075524845],"study_design_scores_gemma":[0.0017354263,0.000028706636,0.00025204613,0.00059287145,0.000034751545,0.000010049599,0.000018499575,0.9888501,0.00013596716,0.000029336567,0.0077101835,0.00060203637],"about_ca_topic_score_codex":0.000102631515,"about_ca_topic_score_gemma":0.0004909889,"teacher_disagreement_score":0.97878873,"about_ca_system_score_codex":0.0002747175,"about_ca_system_score_gemma":0.000041674637,"threshold_uncertainty_score":0.9996631},"labels":[],"label_agreement":null},{"id":"W1593612435","doi":"10.1007/978-3-540-45076-4_31","title":"Base Station Joint Scheduling for Downlink Throughput Maximization in CDMA Packet Data Networks","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Telecommunications link; Network packet; Scheduling (production processes); Base station; Computer network; Power control; Cellular network; Optimization problem; Transmitter power output; W-CDMA; Throughput; Code division multiple access; Power (physics); Mathematical optimization; Wireless; Telecommunications","score_opus":0.03134926825858737,"score_gpt":0.24892862627122206,"score_spread":0.21757935801263467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1593612435","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":[0.00004382211,0.0008778179,0.99637187,0.00010005249,0.0014645533,0.00076343765,0.00004307136,0.0001620553,0.00017329965],"genre_scores_gemma":[0.04586071,0.0006174643,0.95148987,0.00040161173,0.00059306406,0.000026644708,0.0008704711,0.00012468653,0.000015457344],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974829,0.000027164224,0.0005923307,0.0009531537,0.0004195148,0.000524921],"domain_scores_gemma":[0.9983394,0.00026114393,0.00017870784,0.0009587706,0.00018674393,0.000075235876],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008490094,0.00042616506,0.0004166098,0.0004540483,0.00011138091,0.00015745683,0.0006842337,0.00035759003,0.000012287058],"category_scores_gemma":[0.00014573804,0.00046452542,0.000042672134,0.00052741653,0.00015172656,0.00072399684,0.00021266626,0.0005860761,0.0000027158076],"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":[0.000004660736,0.0000065085187,0.000014060649,0.000046999867,0.0000053811723,0.00000523198,0.00007817683,0.86355716,0.00001270524,0.00044601786,0.00002845814,0.13579462],"study_design_scores_gemma":[0.00041629813,0.000025206287,0.00001566327,0.00041770376,0.00001306164,0.000006700591,3.0406437e-7,0.97923714,0.00012428909,0.019058954,0.00022372915,0.00046097886],"about_ca_topic_score_codex":0.0000035634998,"about_ca_topic_score_gemma":0.00014569188,"teacher_disagreement_score":0.13533364,"about_ca_system_score_codex":0.00047069165,"about_ca_system_score_gemma":0.000110274996,"threshold_uncertainty_score":0.99978065},"labels":[],"label_agreement":null},{"id":"W15956924","doi":"","title":"Routing and Scheduling Using Column Generation in IEEE 802.16j Wireless Relay Networks","year":2011,"lang":"en","type":"dissertation","venue":"The Journal of Cardiovascular Surgery","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Concordia University","keywords":"WiMAX; Computer network; Scheduling (production processes); Computer science; Column generation; Wireless network; Wireless; Engineering; Telecommunications","score_opus":0.022511832663118878,"score_gpt":0.213042358867994,"score_spread":0.19053052620487512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W15956924","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":[0.70364463,0.04152933,0.2521913,0.0000010377252,0.002378396,0.0001608287,7.2151187e-7,0.000029811301,0.00006396711],"genre_scores_gemma":[0.9672425,0.028987903,0.0020892262,0.0000063747852,0.0014551831,0.00000487854,0.00004199834,0.0001543217,0.000017643704],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976334,0.00035621205,0.0010198834,0.00017475622,0.00046193393,0.0003538192],"domain_scores_gemma":[0.9985819,0.00024033427,0.00051365956,0.00034044712,0.0002460261,0.000077620476],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0028729436,0.00034371222,0.0010417822,0.00034726053,0.00013872473,0.000060944603,0.00016384262,0.0003851156,0.0000030345552],"category_scores_gemma":[0.00007186107,0.0003179731,0.0005943961,0.00043925422,0.000030629293,0.000384971,0.00001429177,0.0009481174,5.436269e-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":[0.00004300176,0.0000061232354,0.00021288366,0.000088454224,0.0008558328,0.000040657687,0.00036462254,0.9800009,0.00032079485,0.000004202152,0.000031865435,0.018030638],"study_design_scores_gemma":[0.00024658596,0.000007422211,0.00041633044,0.00091172743,0.0007407374,0.00017070958,0.00023115858,0.99589074,0.00093318895,0.000011547472,0.0000739855,0.00036585762],"about_ca_topic_score_codex":0.000037971462,"about_ca_topic_score_gemma":0.000055101304,"teacher_disagreement_score":0.26359785,"about_ca_system_score_codex":0.0001770921,"about_ca_system_score_gemma":0.00009358839,"threshold_uncertainty_score":0.9999272},"labels":[],"label_agreement":null},{"id":"W1596542638","doi":"10.1017/cbo9780511974366.004","title":"Adaptive modulation and coding for high-rate systems","year":2011,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Link adaptation; Orthogonal frequency-division multiplexing; Computer science; Electronic engineering; Wireless; Fading; Computer network; Spectral efficiency; Modulation (music); Coding (social sciences); Telecommunications; Engineering; Channel (broadcasting); Physics; Mathematics","score_opus":0.022339197581105117,"score_gpt":0.16899261004047,"score_spread":0.1466534124593649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596542638","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006360975,0.000197836,0.5155853,4.470603e-7,0.00033549248,0.0005991304,0.00019795865,0.00026146657,0.4827588],"genre_scores_gemma":[0.10408216,0.00056339,0.0021832453,0.000004714866,0.00022065558,0.000005644884,0.00017420435,0.0001433588,0.89262265],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992844,0.000012946235,0.00014939801,0.00028926678,0.00007487237,0.00018914249],"domain_scores_gemma":[0.99940926,0.000064223175,0.000119984325,0.0002075756,0.00011838817,0.00008056352],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005025736,0.00028591228,0.0003090081,0.00012311952,0.00011166968,0.000024665991,0.00011515547,0.00029544113,5.520465e-7],"category_scores_gemma":[0.0000026068326,0.00037828585,0.00005110311,0.000005668655,0.00006289785,0.00013739274,0.000063387364,0.00017818039,0.0000013874763],"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":[0.000059419635,0.0000010775982,3.1440845e-7,0.00018132172,0.000113500806,0.000011201077,0.000031671643,0.11324181,0.000046796045,0.88372725,0.0013940254,0.0011916213],"study_design_scores_gemma":[0.0010513805,0.000079503516,0.000020674112,0.0006020725,0.00031143753,0.0000068366508,0.000028801169,0.8650095,0.00022738382,0.00012045299,0.13159508,0.0009469169],"about_ca_topic_score_codex":0.000024618133,"about_ca_topic_score_gemma":9.2652e-7,"teacher_disagreement_score":0.8836068,"about_ca_system_score_codex":0.00018015911,"about_ca_system_score_gemma":0.000011756606,"threshold_uncertainty_score":0.9998669},"labels":[],"label_agreement":null},{"id":"W1596671267","doi":"10.1109/pacrim.2003.1235755","title":"Spectral efficiency of packet transmission with adaptive uncoded signaling compared to channel capacity","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Spectral efficiency; Transmission (telecommunications); Signalling; Channel capacity; Channel (broadcasting); Computer science; Throughput; Network packet; Block (permutation group theory); Electronic engineering; Channel spacing; Computer network; Telecommunications; Mathematics; Engineering; Physics; Wireless; Optoelectronics; Wavelength-division multiplexing","score_opus":0.014592691980181196,"score_gpt":0.1993951753503397,"score_spread":0.1848024833701585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596671267","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":[0.31648833,0.000018166655,0.68230224,0.000016577791,0.000028739556,0.00018273761,0.0000032446312,0.00016756874,0.00079243846],"genre_scores_gemma":[0.8587892,0.0000060419607,0.14112261,0.000011411358,0.000024144743,0.0000069656794,0.0000052983905,0.000025171154,0.000009166433],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925965,0.000009025217,0.00018415338,0.00015405177,0.00016217753,0.00023092146],"domain_scores_gemma":[0.999687,0.000019321646,0.000026442678,0.000113613125,0.000054402248,0.000099186196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000045469875,0.00014819855,0.00019921781,0.00007253957,0.00003773263,0.0000061284545,0.00008302075,0.000041742886,0.000022374887],"category_scores_gemma":[0.000002535674,0.00012508593,0.000028640417,0.00039813007,0.000028102162,0.00010390912,0.000005571449,0.00009102369,0.000003861276],"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":[0.000060887818,0.00003047595,0.000010405793,0.000018875055,0.0000125105535,0.0000016473359,0.0010130306,0.98151594,0.016724462,0.00038445555,0.000007783747,0.00021950435],"study_design_scores_gemma":[0.00083975634,0.00017478726,0.0000863419,0.0001659951,0.00001130416,0.0000029933713,0.00022181455,0.6804301,0.31740022,0.00043007717,0.000007675507,0.00022892327],"about_ca_topic_score_codex":0.000024686178,"about_ca_topic_score_gemma":0.000042691543,"teacher_disagreement_score":0.5423009,"about_ca_system_score_codex":0.000096549076,"about_ca_system_score_gemma":0.000015546511,"threshold_uncertainty_score":0.51008564},"labels":[],"label_agreement":null},{"id":"W1603858677","doi":"10.1109/iccw.2015.7247382","title":"Opportunistic Dual Metric Scheduling Algorithm for LTE uplink","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Ottawa","funders":"","keywords":"Computer science; Telecommunications link; Scheduling (production processes); Algorithm; Metric (unit); Dual (grammatical number); Distributed computing; Computer network; Mathematical optimization; Mathematics; Engineering","score_opus":0.03760158207506686,"score_gpt":0.2601939700120745,"score_spread":0.22259238793700764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1603858677","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":[0.00019942399,0.00026534998,0.9953407,0.000022008388,0.0005324762,0.00020058705,0.000006904764,0.0005655158,0.0028670558],"genre_scores_gemma":[0.057766635,0.00005773472,0.94102174,0.00003561781,0.00031377655,0.000045041736,0.000091096495,0.00006029754,0.0006080861],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993383,0.000004956342,0.00018306973,0.00013402806,0.000104854334,0.00023475745],"domain_scores_gemma":[0.9995136,0.0000734303,0.000023623197,0.0001359264,0.00010229067,0.00015110394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001346842,0.00011987083,0.00013737362,0.000119589364,0.00003394427,0.000024361778,0.00006428986,0.000067207046,0.000019379397],"category_scores_gemma":[0.00006870093,0.00012333163,0.000032297525,0.0003442969,0.0000115281455,0.00015700016,0.000018819914,0.00007365305,0.00002674298],"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":[0.0000015303623,0.0000057643306,0.0000065300605,0.000008648996,0.000014865486,0.0000021616465,0.000015397425,0.87476647,0.00002411253,0.0009852087,0.00084937,0.123319924],"study_design_scores_gemma":[0.00040476007,0.00002501855,0.0000028072527,0.0000066698626,0.000014820438,0.000004163179,0.000038422913,0.9956698,0.0002476717,0.0005951208,0.0028284749,0.00016231107],"about_ca_topic_score_codex":0.0000012610686,"about_ca_topic_score_gemma":7.514398e-7,"teacher_disagreement_score":0.12315761,"about_ca_system_score_codex":0.00008127946,"about_ca_system_score_gemma":0.000024154293,"threshold_uncertainty_score":0.5029318},"labels":[],"label_agreement":null},{"id":"W1605741195","doi":"10.1109/icscn.2015.7219903","title":"Integrated approach towards bandwidth aggregation (BAG) in multi-homed devices","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"BC Research (Canada)","funders":"","keywords":"Computer science; Computer network; Bandwidth (computing); Software deployment; Protocol (science); Protocol stack; Distributed computing; Application layer; Cellular network; Wireless sensor network; Operating system","score_opus":0.03852502138655105,"score_gpt":0.2468858183720017,"score_spread":0.20836079698545062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1605741195","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":[0.044277795,0.00035026326,0.9454687,0.000016900187,0.00018866232,0.0002348507,0.0000020549053,0.0005761423,0.0088845985],"genre_scores_gemma":[0.7851815,0.000043937336,0.21431918,0.000021599699,0.000030232326,0.000037404134,0.00010775677,0.00003064856,0.00022768986],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927443,0.000026172984,0.00021449119,0.00015890348,0.0001271406,0.00019886642],"domain_scores_gemma":[0.9996721,0.000014163728,0.000025753607,0.00013717699,0.00007000754,0.000080773905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013291792,0.000143794,0.0001571852,0.00017903537,0.0000137424195,0.00002709451,0.00010154716,0.00009461766,0.000016440736],"category_scores_gemma":[0.000040642855,0.0001287801,0.000017949646,0.0007113264,0.000015688402,0.00033488986,0.000017246211,0.00013149156,0.000018394636],"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":[0.000006834239,0.000025215597,0.001325426,0.000016957083,0.0000067541046,0.0000011293745,0.00028454865,0.96334994,0.00004500459,0.00010149356,0.00020538703,0.034631334],"study_design_scores_gemma":[0.00073739735,0.000009656598,0.0010177459,0.000023879173,0.0000030351737,0.0000015900613,0.00026267167,0.99579096,0.00083295617,0.00004585879,0.0011098494,0.00016441301],"about_ca_topic_score_codex":0.00005916397,"about_ca_topic_score_gemma":0.0002724533,"teacher_disagreement_score":0.74090374,"about_ca_system_score_codex":0.00017417627,"about_ca_system_score_gemma":0.00002488773,"threshold_uncertainty_score":0.52515},"labels":[],"label_agreement":null},{"id":"W1678876464","doi":"10.1109/iwcmc.2015.7289100","title":"On sharing resources performance analysis in 3GPP-LTE systems framework","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Computer science; Computer network; Cellular network; Node (physics); Mobile telephony; Next-generation network; Radio access network; Distributed computing; Mobile radio; Mobile station; Base station; Engineering; Operating system; The Internet","score_opus":0.013462582420809768,"score_gpt":0.2203255045831563,"score_spread":0.20686292216234653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1678876464","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":[0.64161175,0.0002901487,0.34632227,0.000008045536,0.00019237956,0.00008927773,6.328143e-7,0.00032786382,0.01115762],"genre_scores_gemma":[0.9945119,0.000061893275,0.0050176284,0.000016960377,0.0000782909,0.000018143588,0.000006939564,0.000025708714,0.0002625409],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923885,0.000011777696,0.0002083177,0.0001695672,0.00016304897,0.00020841078],"domain_scores_gemma":[0.9995657,0.000053097832,0.000025823741,0.00025950436,0.000024864248,0.000070982736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015085604,0.00011714373,0.00019326094,0.00026867716,0.00002162936,0.00004138884,0.00013540199,0.0000857535,0.00001710778],"category_scores_gemma":[0.000028200282,0.00011302033,0.00002840536,0.0011290121,0.000008697821,0.00016180344,0.00002467838,0.00017716792,0.000040564108],"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":[0.000007080326,0.000005196558,0.018504228,0.000016220456,0.000038639628,0.0000016120587,0.00026822503,0.9796734,0.000001808711,0.0009888571,0.000076642784,0.00041807882],"study_design_scores_gemma":[0.000107869935,0.000014871043,0.0020167322,0.00007415458,0.000018070174,4.0877669e-7,0.00009728259,0.99713176,0.000030576874,0.00013525161,0.00023561918,0.00013737875],"about_ca_topic_score_codex":0.000017716206,"about_ca_topic_score_gemma":0.000020794105,"teacher_disagreement_score":0.35290015,"about_ca_system_score_codex":0.000132136,"about_ca_system_score_gemma":0.0000029086286,"threshold_uncertainty_score":0.46088353},"labels":[],"label_agreement":null},{"id":"W1682274164","doi":"10.1109/glocom.2001.966246","title":"Efficient fair queuing with decoupled delay-bandwidth guarantees","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Bandwidth allocation; Scheduling (production processes); Bandwidth (computing); Queueing theory; Estimator; Queuing delay; Computer network; Dynamic bandwidth allocation; Upper and lower bounds; Weighted fair queueing; Generalized processor sharing; Fair queuing; Real-time computing; Round-robin scheduling; Dynamic priority scheduling; Mathematical optimization; Quality of service; Mathematics","score_opus":0.005327297077657128,"score_gpt":0.16686539227163932,"score_spread":0.16153809519398218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1682274164","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":[0.16308245,0.0005074155,0.825813,0.000022995499,0.00009692721,0.00013660388,8.9051827e-7,0.0008066021,0.009533109],"genre_scores_gemma":[0.967573,0.00009454323,0.03187395,0.000031775657,0.000050798844,0.000016319334,0.0000043455025,0.00004787404,0.00030742906],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993099,0.0000060427246,0.00014686325,0.00014951869,0.00013059296,0.00025706203],"domain_scores_gemma":[0.9996955,0.000034252644,0.000019229017,0.00016907953,0.00003208661,0.00004986879],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003195699,0.00014786782,0.00012998322,0.000060395047,0.000056370704,0.000023600065,0.00007787897,0.000045095127,0.00040611127],"category_scores_gemma":[0.0000048354946,0.00012138886,0.000023452849,0.00025429056,0.000020382653,0.00006283146,0.000010071141,0.00008957799,0.00007392313],"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":[0.0000043686255,0.000013480191,0.00014935923,0.000012241921,0.000015408192,0.0000074563773,0.00012567615,0.9954804,0.0001264545,0.00021951992,0.00045098003,0.003394653],"study_design_scores_gemma":[0.00036184938,0.000022494796,0.000060830054,0.00003653396,0.000007841987,0.00001233374,0.00003591284,0.9981975,0.0005410783,0.000010301206,0.0005247352,0.00018859432],"about_ca_topic_score_codex":0.0000031613051,"about_ca_topic_score_gemma":0.000040011153,"teacher_disagreement_score":0.8044905,"about_ca_system_score_codex":0.000053344713,"about_ca_system_score_gemma":0.0000020612456,"threshold_uncertainty_score":0.49500942},"labels":[],"label_agreement":null},{"id":"W1704945303","doi":"10.1109/incc.2004.1366580","title":"A high-capacity scheduling algorithm for systems employing embedded modulation","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Telecommunications link; Computer science; Link adaptation; Scheduling (production processes); Computer network; Wireless; Real-time computing; Distributed computing; Algorithm; Channel (broadcasting); Fading; Telecommunications; Mathematical optimization; Mathematics","score_opus":0.015576667024492036,"score_gpt":0.2207626878151585,"score_spread":0.20518602079066647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1704945303","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":[0.058943402,0.000079030404,0.9388982,0.000009171298,0.0006455517,0.0004290088,0.000006894025,0.00088857417,0.000100134625],"genre_scores_gemma":[0.5259446,0.000010324214,0.47372967,0.0000059723225,0.00017539358,0.000058081478,0.000026639684,0.00003471638,0.000014607414],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992411,0.0000068055156,0.00023662036,0.0001655105,0.00010888478,0.00024105112],"domain_scores_gemma":[0.9996559,0.000033949753,0.00003667101,0.00014799536,0.00007392203,0.000051565596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008106159,0.00014200622,0.00016416697,0.000069231195,0.00008719242,0.00004605394,0.00006284555,0.00009221376,0.0000039958404],"category_scores_gemma":[0.000014292788,0.00015257436,0.00003930048,0.00017809858,0.000010365905,0.00032129788,0.000009040413,0.00007889115,0.000009141156],"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":[0.0000014442153,0.0000066319667,0.000006174823,0.00003659872,0.000017572673,3.0418107e-7,0.00006372875,0.984011,0.0010132901,0.0039430577,0.00000847409,0.01089174],"study_design_scores_gemma":[0.00061994354,0.000013526424,0.000028359162,0.000054383778,0.000008287224,0.0000026097923,0.000043340515,0.9951826,0.0023772977,0.0014541674,0.0000310331,0.00018449362],"about_ca_topic_score_codex":0.000018368442,"about_ca_topic_score_gemma":0.0000041643284,"teacher_disagreement_score":0.4670012,"about_ca_system_score_codex":0.00018391799,"about_ca_system_score_gemma":0.00000793718,"threshold_uncertainty_score":0.62218016},"labels":[],"label_agreement":null},{"id":"W1758692241","doi":"10.5281/zenodo.43543","title":"Coordinated Scheduling For Wireless Backhaul Networks With Soft Frequency Reuse","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Blinq Network (Canada); University of Toronto","funders":"","keywords":"Backhaul (telecommunications); Computer science; Frequency reuse; Scheduling (production processes); Telecommunications link; Computer network; Wireless; Orthogonal frequency-division multiplexing; Reuse; Distributed computing; Wireless network; Computational complexity theory; Schedule; Base station; Mathematical optimization; Engineering; Telecommunications; Channel (broadcasting)","score_opus":0.005189385391537744,"score_gpt":0.18600203681681324,"score_spread":0.1808126514252755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1758692241","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":[0.052642755,0.00018806805,0.9440468,0.00008549018,0.00018209031,0.00066485006,0.0000018562915,0.0009716256,0.0012164937],"genre_scores_gemma":[0.7276754,0.00005889141,0.27150655,0.00005619318,0.00012987781,0.00021945954,0.000048752212,0.00009754881,0.00020734327],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989841,0.000009908258,0.00024130821,0.0002338619,0.00008810926,0.00044273495],"domain_scores_gemma":[0.9991621,0.000102077305,0.00004409869,0.00039937388,0.00018604517,0.00010631844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000056482517,0.00022738539,0.00021774613,0.000058327616,0.000089277055,0.00006555867,0.00023016646,0.00013466107,0.00015136808],"category_scores_gemma":[0.000022626778,0.00019917426,0.00003599933,0.0003334135,0.00003420906,0.0004763989,0.000028694456,0.00016429991,0.000032691518],"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":[0.000007263637,0.0000094034485,0.00036462248,0.000030335408,0.000036258185,0.0000010155649,0.000027597805,0.99207145,0.0006233343,0.0006472075,0.001577059,0.0046044393],"study_design_scores_gemma":[0.00054962497,0.00004260203,0.00009103847,0.000060239225,0.000013756442,0.0000035463868,0.000048741942,0.9977783,0.0004994189,0.0004691129,0.00013247906,0.00031115304],"about_ca_topic_score_codex":0.000018357483,"about_ca_topic_score_gemma":0.000022603832,"teacher_disagreement_score":0.6750326,"about_ca_system_score_codex":0.000069390764,"about_ca_system_score_gemma":0.000012166855,"threshold_uncertainty_score":0.81220907},"labels":[],"label_agreement":null},{"id":"W1761836155","doi":"10.1007/3-540-47922-8_28","title":"An Enhanced Genetic Algorithm Approach to the Channel Assignment Problem in Mobile Cellular Networks","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Guelph","funders":"","keywords":"Computer science; Crossover; Genetic algorithm; Channel (broadcasting); Bandwidth (computing); A priori and a posteriori; Algorithm; Interference (communication); Mathematical optimization; Artificial intelligence; Machine learning; Mathematics; Computer network","score_opus":0.007352250148517361,"score_gpt":0.19305332318431234,"score_spread":0.18570107303579497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1761836155","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":[0.00002029729,0.0014050823,0.995684,0.000015128402,0.00065725995,0.0012703105,0.0000035151315,0.00014822197,0.0007961345],"genre_scores_gemma":[0.20416181,0.00038217896,0.79387903,0.00021985818,0.0008917839,0.00025272754,0.000028195253,0.00011890784,0.00006552295],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99758387,0.000027697963,0.00041532473,0.0008626724,0.0004691945,0.00064121507],"domain_scores_gemma":[0.9988945,0.00007717198,0.000083617946,0.0007564848,0.00005803314,0.00013015029],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028000298,0.00046285908,0.0003708696,0.00032548167,0.00011133586,0.00013772825,0.0010419157,0.00027952137,0.000010481918],"category_scores_gemma":[0.000003421562,0.0003958294,0.000047693695,0.00060986774,0.00015443085,0.0001634699,0.00018099883,0.0007032253,0.000008427078],"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":[7.809386e-7,0.000014702087,4.6508512e-7,0.000010871965,0.0000028476318,0.0000042963215,0.00041123293,0.6711334,0.000028444607,0.000017939226,0.000005179014,0.32836983],"study_design_scores_gemma":[0.0001204217,0.000086862216,0.0000072974385,0.00015568557,0.0000045564466,0.000005229447,4.61245e-7,0.99687076,0.00042739618,0.0016089057,0.00025715397,0.0004552891],"about_ca_topic_score_codex":0.0000032053235,"about_ca_topic_score_gemma":0.000011703885,"teacher_disagreement_score":0.32791454,"about_ca_system_score_codex":0.00039416505,"about_ca_system_score_gemma":0.000029429424,"threshold_uncertainty_score":0.9998494},"labels":[],"label_agreement":null},{"id":"W1763069861","doi":"10.1109/glocom.2000.891898","title":"Optimal resource management in multimedia WCDMA systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Quality of service; Base station; Nonlinear programming; Resource allocation; Mathematical optimization; Computer network; Optimization problem; Resource management (computing); Code division multiple access; Bandwidth (computing); Distributed computing; Nonlinear system; Algorithm","score_opus":0.008519605704687608,"score_gpt":0.18589090280515694,"score_spread":0.17737129710046934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1763069861","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":[0.014965804,0.0017029619,0.65670323,0.000041686646,0.00046667163,0.00062961306,0.0000018542089,0.0011854661,0.3243027],"genre_scores_gemma":[0.90727234,0.00041154074,0.08682537,0.000022817892,0.00010869328,0.00007296317,0.000010602608,0.000056006505,0.005219676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993952,0.000010480377,0.00016821624,0.000120997494,0.00009743784,0.00020768779],"domain_scores_gemma":[0.9997659,0.00002055029,0.000011613599,0.00015703966,0.000005922902,0.000038990333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004138719,0.000097672215,0.00009713879,0.000093380535,0.000014658333,0.000017244482,0.000081369246,0.000044529603,0.00012987503],"category_scores_gemma":[0.0000021498226,0.00010277948,0.000014159192,0.00021767385,0.000008824828,0.000092651586,0.000020731091,0.00007688723,0.00012735721],"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":[0.0000011297709,0.000009818216,0.00004799723,0.000024777664,0.000008927209,0.000015374873,0.00010275623,0.9857025,0.000008885739,0.00025322364,0.0039043014,0.009920291],"study_design_scores_gemma":[0.00028794768,0.000004144853,0.000095189534,0.000024869456,0.0000026372845,0.0000018560178,0.00015152525,0.98592997,0.00002785407,0.000001622676,0.013354365,0.00011799721],"about_ca_topic_score_codex":0.0000027519422,"about_ca_topic_score_gemma":0.000002689366,"teacher_disagreement_score":0.8923065,"about_ca_system_score_codex":0.00007257412,"about_ca_system_score_gemma":2.56344e-7,"threshold_uncertainty_score":0.41912255},"labels":[],"label_agreement":null},{"id":"W1812927931","doi":"10.1109/cdc.2001.981023","title":"Stochastic power control for short-term flat fading wireless networks: almost sure QoS measures","year":2003,"lang":"en","type":"article","venue":"Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University; University of Ottawa","funders":"","keywords":"Fading; Computer science; Mathematical optimization; Probabilistic logic; Power control; Quality of service; Stochastic optimization; Stochastic programming; Wireless network; Wireless; Optimization problem; Optimal control; Linear programming; Term (time); Stochastic control; Stochastic process; Stochastic differential equation; Channel (broadcasting); Power (physics); Computer network; Mathematics; Telecommunications; Applied mathematics; Statistics","score_opus":0.014839866004710909,"score_gpt":0.22937349048549543,"score_spread":0.21453362448078453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1812927931","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":[0.35659495,0.00015183262,0.63920087,0.000082801766,0.0014368236,0.0016262328,0.0000381679,0.00019982472,0.00066850975],"genre_scores_gemma":[0.99577,0.00029205458,0.0030696378,0.00019799541,0.0002470892,0.00018553964,0.000003564561,0.00012444994,0.00010970559],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971874,0.000030653646,0.0008117727,0.00063452293,0.0005912918,0.0007443608],"domain_scores_gemma":[0.99748826,0.0005969717,0.00029473423,0.00032377467,0.0010437162,0.00025254325],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006695106,0.0006179828,0.0008966443,0.000180025,0.00031343478,0.00021872406,0.00058764446,0.00033576504,0.00003196575],"category_scores_gemma":[0.0005520116,0.0004901018,0.00023603858,0.00033821914,0.00016507566,0.0004047536,0.000036464295,0.00033176556,0.000007873967],"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":[0.003091984,0.00016061735,0.0038470663,0.00022708869,0.00048071356,0.0000023619634,0.0004684046,0.77314603,0.16611351,0.011858802,0.002164066,0.038439322],"study_design_scores_gemma":[0.0038537981,0.00022097497,0.00076307927,0.000614741,0.00014473956,0.000012073963,0.00012903186,0.99052566,0.0017618778,0.0012782299,0.00011513493,0.0005806809],"about_ca_topic_score_codex":0.0000013878702,"about_ca_topic_score_gemma":0.0000047478643,"teacher_disagreement_score":0.639175,"about_ca_system_score_codex":0.00011305501,"about_ca_system_score_gemma":0.000058289,"threshold_uncertainty_score":0.9997551},"labels":[],"label_agreement":null},{"id":"W1824895300","doi":"10.1007/s11036-015-0631-2","title":"Data and Control Plane Traffic Modelling for LTE Networks","year":2015,"lang":"en","type":"article","venue":"Mobile Networks and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Computer network; Core network; Network planning and design; Network packet; Cellular network; Software deployment; Bandwidth (computing); Distributed computing","score_opus":0.020295612027560268,"score_gpt":0.23523038123564385,"score_spread":0.21493476920808358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1824895300","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":[0.001160804,0.008214156,0.9890304,0.000018944109,0.000075391974,0.0010934311,0.00010346181,0.00022922194,0.000074140225],"genre_scores_gemma":[0.9878472,0.0026424355,0.006442738,0.00004489083,0.00072484027,0.0014036074,0.00081730913,0.00005237427,0.000024565898],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921095,0.000009086465,0.00020138692,0.00028262654,0.0000536732,0.00024224602],"domain_scores_gemma":[0.9992785,0.00013509617,0.00003909116,0.0003604828,0.000040208728,0.00014664259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014442916,0.00014581498,0.00017716913,0.000025548117,0.00012013551,0.00005443771,0.0001442264,0.00010260616,0.000001262902],"category_scores_gemma":[0.000002086337,0.00015281598,0.000013197523,0.00013155531,0.00004313727,0.00014841952,0.000039363495,0.0001200158,7.2004957e-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":[0.000009487405,0.000009974725,0.000018572737,0.000010741646,0.000016622564,1.1986478e-7,0.000008811941,0.9639736,0.0000012507047,0.00028662558,0.0014857424,0.03417848],"study_design_scores_gemma":[0.00056629605,0.00001996317,0.0000036851682,0.000011100006,0.00003515743,0.0000034748084,0.000029173027,0.939504,5.5656795e-7,0.00012114236,0.059549566,0.00015583872],"about_ca_topic_score_codex":8.7911417e-7,"about_ca_topic_score_gemma":0.000007629775,"teacher_disagreement_score":0.9866864,"about_ca_system_score_codex":0.000016437503,"about_ca_system_score_gemma":0.000006507698,"threshold_uncertainty_score":0.6231655},"labels":[],"label_agreement":null},{"id":"W1825347868","doi":"10.4018/978-1-59904-899-4.ch023","title":"End-to-End Security Comparisons Between IEEE 802.16e and 3G Technologies","year":2008,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Computer network; WiMAX; Cellular network; IEEE 802; Implementation; Protocol (science); Computer security; Telecommunications; Wireless; Quality of service","score_opus":0.01610699602573299,"score_gpt":0.22777660502932745,"score_spread":0.21166960900359447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1825347868","genre_codex":"other","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":[0.0013368686,0.0026372,0.04647402,0.000051034138,0.00057826046,0.000796689,0.00068724743,0.0034597025,0.94397897],"genre_scores_gemma":[0.9855027,0.0004482909,0.010199606,0.00005169851,0.00039362957,0.000040061877,0.000042489348,0.00017075648,0.003150719],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982562,0.000008611694,0.00044213576,0.0005095847,0.00029921468,0.00048422997],"domain_scores_gemma":[0.9990699,0.000060618342,0.000115579314,0.00053601875,0.00006504432,0.00015279384],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000042734813,0.00061703176,0.0007454552,0.00014065267,0.00012941608,0.000047729714,0.00033444163,0.0007792495,0.000009688461],"category_scores_gemma":[0.000011618451,0.00070719194,0.0001047076,0.000051010506,0.00021458177,0.00006913634,0.00017502732,0.000626845,0.00006758481],"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":[0.00006645513,0.000024179195,0.0013605828,0.00047795614,0.0011054111,0.00030727594,0.000559987,0.20776197,0.00006987026,0.5865513,0.07791487,0.12380015],"study_design_scores_gemma":[0.0021553782,0.00043087336,0.000775317,0.0017299908,0.00076786766,0.00031293812,0.00014150757,0.02415298,0.0018778837,0.22704597,0.73390657,0.00670274],"about_ca_topic_score_codex":0.000014236737,"about_ca_topic_score_gemma":0.00007090705,"teacher_disagreement_score":0.9841659,"about_ca_system_score_codex":0.00031085723,"about_ca_system_score_gemma":0.00003618176,"threshold_uncertainty_score":0.99953794},"labels":[],"label_agreement":null},{"id":"W1848767610","doi":"10.1109/wts.2014.6834994","title":"Solving binary and continuous knapsack problems for radio resource allocation over High Altitude Platforms","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Knapsack problem; Lagrangian relaxation; Multicast; Mathematical optimization; Continuous knapsack problem; Generalized assignment problem; Greedy algorithm; Computer science; Resource allocation; Integer programming; Change-making problem; Column generation; Benchmark (surveying); Optimization problem; Mathematics; Distributed computing; Computer network","score_opus":0.00504358211050494,"score_gpt":0.18861786172935546,"score_spread":0.18357427961885053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1848767610","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":[0.1044972,0.00022275929,0.89322925,0.000046786714,0.000121073346,0.00046130296,0.0000020421076,0.0004408572,0.0009787529],"genre_scores_gemma":[0.9462525,0.000107858985,0.052794266,0.000064593805,0.00016914714,0.00007269288,0.00007899209,0.000062321844,0.0003975877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992907,0.000005049936,0.00019966971,0.00018339013,0.000084077976,0.0002371163],"domain_scores_gemma":[0.99961084,0.00010089739,0.000040938558,0.00015880892,0.000030837484,0.000057682533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013141792,0.00014348676,0.00016480047,0.000055831537,0.00007728112,0.00003645928,0.00006862251,0.000088047294,0.000016432907],"category_scores_gemma":[0.000025226127,0.00013482256,0.000022360371,0.00008794033,0.000022853052,0.00027547733,0.000022211107,0.00007548444,0.0000034685665],"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":[0.000010523793,0.000008081977,0.00022766662,0.00008590393,0.000018663928,1.6281459e-7,0.000113161936,0.98112875,0.0019198253,0.0059917816,0.0018567393,0.008638743],"study_design_scores_gemma":[0.00072183495,0.000061518236,0.0007772597,0.00005014095,0.00001159281,0.0000026629589,0.00001992298,0.9870173,0.0007243752,0.00097476225,0.009431012,0.00020766452],"about_ca_topic_score_codex":0.0000064041624,"about_ca_topic_score_gemma":0.000015364929,"teacher_disagreement_score":0.84175533,"about_ca_system_score_codex":0.00004713069,"about_ca_system_score_gemma":0.000003642038,"threshold_uncertainty_score":0.54979044},"labels":[],"label_agreement":null},{"id":"W18542780","doi":"10.5489/cuaj.63","title":"WiMAX ou l’évolution des réseaux sans-fil ?","year":2006,"lang":"en","type":"article","venue":"Lex Electronica","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Humanities; Political science; Art","score_opus":0.004898035392716301,"score_gpt":0.20041515623418446,"score_spread":0.19551712084146816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W18542780","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":[0.046148837,0.0054157292,0.88958627,0.00010327976,0.00041867865,0.00025587695,0.000004472109,0.0015831533,0.056483686],"genre_scores_gemma":[0.98620415,0.00049745606,0.012109614,0.000027533446,0.00060066796,0.000030457744,0.00006394584,0.000063572326,0.00040260548],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998947,0.000018650491,0.00018772158,0.00017832928,0.00012306334,0.00054523087],"domain_scores_gemma":[0.9996636,0.000026261863,0.000028350838,0.00020686643,0.000034875207,0.000040083552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005623418,0.00016101888,0.0001306552,0.000057348203,0.00010195856,0.000025145484,0.000117228985,0.000091836635,0.000057735975],"category_scores_gemma":[0.0000083817595,0.00018256967,0.00004724835,0.0003124037,0.000051915875,0.00021741856,0.000012799094,0.00019768348,0.00005889938],"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":[0.000007795278,0.000017483966,0.00034477093,0.000016106203,0.000012543268,0.0000011357198,0.000009539279,0.9637419,0.00757215,0.015454432,0.0058994875,0.0069226855],"study_design_scores_gemma":[0.0007481713,0.00011171784,0.0057758805,0.000042640382,0.000036386766,0.000018445246,0.00000740909,0.87209904,0.015328436,0.048057023,0.057097435,0.00067740894],"about_ca_topic_score_codex":0.000046283123,"about_ca_topic_score_gemma":0.00029611142,"teacher_disagreement_score":0.9400553,"about_ca_system_score_codex":0.0004429361,"about_ca_system_score_gemma":0.00003053256,"threshold_uncertainty_score":0.7444975},"labels":[],"label_agreement":null},{"id":"W1871031609","doi":"10.1007/11946441_34","title":"Interference Aware Dynamic Subchannel Allocation in a Multi-cellular OFDMA System Based on Traffic Situation","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University","funders":"","keywords":"Channel allocation schemes; Quality of service; Computer science; Telecommunications link; Interference (communication); Orthogonal frequency-division multiple access; Computer network; Bandwidth (computing); Orthogonal frequency-division multiplexing; Dynamic bandwidth allocation; WiMAX; Adaptability; Bandwidth allocation; Channel (broadcasting); Frequency-division multiple access; Spectral efficiency; Real-time computing; Telecommunications; Wireless","score_opus":0.0104139913745345,"score_gpt":0.20929974076377855,"score_spread":0.19888574938924405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1871031609","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":[0.0017194864,0.0002162802,0.99610424,0.00003788987,0.0009198892,0.000553231,0.000009150674,0.00033399466,0.00010584861],"genre_scores_gemma":[0.96114844,0.000022558785,0.038432177,0.000044111148,0.00010077696,0.000035608242,0.00011178816,0.000071216484,0.00003334678],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979146,0.00002668253,0.00048986496,0.0007541136,0.00042240735,0.00039229373],"domain_scores_gemma":[0.9990378,0.00016644382,0.00014682452,0.000471835,0.00012028105,0.000056838857],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025447796,0.0004549204,0.00038116195,0.0009030638,0.000072412084,0.000091801856,0.0005256538,0.00033805586,0.0000042696533],"category_scores_gemma":[0.000016487866,0.0004905238,0.000058464888,0.0005191316,0.00012332087,0.00021298722,0.000057590492,0.00056807674,0.000011151689],"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":[0.000006555199,0.00001934444,0.000009550526,0.00014014087,0.000002300234,0.000015084917,0.00011301317,0.93893474,0.00020123436,0.000041779716,0.0000016514865,0.06051459],"study_design_scores_gemma":[0.00037492518,0.000048421924,0.00006923372,0.0019347753,0.0000064755495,0.0000023193686,4.4590553e-7,0.99649566,0.00049640506,0.00012520011,0.000004255772,0.0004418646],"about_ca_topic_score_codex":0.000011723037,"about_ca_topic_score_gemma":0.00040302548,"teacher_disagreement_score":0.9594289,"about_ca_system_score_codex":0.0012480438,"about_ca_system_score_gemma":0.000095707735,"threshold_uncertainty_score":0.99975467},"labels":[],"label_agreement":null},{"id":"W1930946327","doi":"","title":"Delay Minimization in Multihop Wireless Networks: Static Scheduling Does It","year":2012,"lang":"en","type":"preprint","venue":"CaltechAUTHORS (California Institute of Technology)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Minification; Scheduling (production processes); Wireless; Computer network; Wireless network; Distributed computing; Mathematical optimization; Telecommunications; Mathematics","score_opus":0.011900442874858185,"score_gpt":0.2425114400292734,"score_spread":0.23061099715441521,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1930946327","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":[0.19818832,0.0016646838,0.7939517,0.00030550285,0.002956214,0.0011204074,0.000163283,0.0015475415,0.00010235753],"genre_scores_gemma":[0.8111707,0.002785468,0.18473479,0.000030061348,0.00020499132,0.00038052615,0.0004892145,0.00019069228,0.000013571822],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99622375,0.00004680048,0.0016101047,0.00077361905,0.00034375352,0.0010019885],"domain_scores_gemma":[0.9978627,0.00006014889,0.000568514,0.001113307,0.00022115037,0.00017420051],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00040752496,0.00084231567,0.0012114818,0.0016034096,0.00010454238,0.00003891699,0.00092224305,0.0023992837,0.000026449276],"category_scores_gemma":[0.00023899268,0.00083786756,0.00017621642,0.001632501,0.00047504442,0.00035794676,0.0006955638,0.0022878975,0.000024503532],"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":[0.000023222412,0.0000849515,0.0012314161,0.0007533758,0.000091813454,0.00002232565,0.000113219794,0.97138435,0.0003058765,0.0012577523,0.000082972154,0.024648711],"study_design_scores_gemma":[0.000573292,0.000017415234,0.000029066572,0.0016541523,0.00009661899,0.000009107359,0.00013307462,0.98772824,0.0032003215,0.0022863126,0.0034062404,0.00086618133],"about_ca_topic_score_codex":0.000020787633,"about_ca_topic_score_gemma":0.00014317986,"teacher_disagreement_score":0.6129824,"about_ca_system_score_codex":0.0005459723,"about_ca_system_score_gemma":0.00011155488,"threshold_uncertainty_score":0.99940723},"labels":[],"label_agreement":null},{"id":"W1944531237","doi":"10.1109/vetec.1999.778374","title":"A framework for fair allocation of resources to Internet services in micro-cellular networks","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; The Internet; Computer network; Resource allocation; Internet traffic; Wireless network; Cellular network; Optimal allocation; Wireless; Distributed computing; Telecommunications; World Wide Web; Mathematical optimization","score_opus":0.0058341401912368135,"score_gpt":0.21292711404283085,"score_spread":0.20709297385159403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1944531237","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":[0.13399133,0.0003422096,0.8646511,0.000018414647,0.00011709967,0.00029024808,9.050249e-7,0.00009028222,0.0004984505],"genre_scores_gemma":[0.7687497,0.000028532308,0.2309782,0.00005913455,0.000033359192,0.000044987635,0.000011754277,0.000027932689,0.00006639776],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936444,0.000015947255,0.00024329644,0.0001385428,0.000055260065,0.0001825391],"domain_scores_gemma":[0.9996539,0.00008655043,0.000033788347,0.00015098108,0.000037349524,0.000037482954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009970813,0.00010722808,0.0001446965,0.00008826937,0.000010004211,0.000012734299,0.00010815993,0.00010756983,0.000023035045],"category_scores_gemma":[0.00001690271,0.000114907176,0.000026017759,0.00031273087,0.000007724719,0.000082149265,0.000012764443,0.000078843674,0.0000029906535],"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":[0.000012009421,0.000011754108,0.00063243543,0.00006528104,0.000009021591,1.9921198e-7,0.00049480115,0.9911922,0.0010240125,0.0055637243,0.000084876476,0.000909656],"study_design_scores_gemma":[0.0002153744,0.00003180452,0.00021717702,0.00018797007,0.0000055707787,3.6065077e-7,0.00022102507,0.9746166,0.019957853,0.0015210512,0.0028612218,0.0001639897],"about_ca_topic_score_codex":0.0000106604575,"about_ca_topic_score_gemma":0.00007774656,"teacher_disagreement_score":0.63475835,"about_ca_system_score_codex":0.00003904462,"about_ca_system_score_gemma":0.000002649569,"threshold_uncertainty_score":0.46857786},"labels":[],"label_agreement":null},{"id":"W1963068370","doi":"10.1002/wcm.2501","title":"A lookback scheduling framework for long‐term quality of service over multiple cells","year":2014,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Qatar National Research Fund; Fonds National de la Recherche Luxembourg; Qatar Foundation","keywords":"Computer science; Quality of service; Scheduling (production processes); Queue; Term (time); Computer network; Queueing theory; Traverse; Real-time computing; Mathematical optimization","score_opus":0.025121058927438676,"score_gpt":0.3002382588044697,"score_spread":0.27511719987703104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963068370","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":[0.41361508,0.00058778835,0.5852773,0.000016396976,0.00006289613,0.00026931943,0.000007509135,0.00011669418,0.000047022688],"genre_scores_gemma":[0.7672238,0.00038980186,0.23215513,0.00004389259,0.000052489817,0.000050473343,0.00004433842,0.000037797017,0.0000023158243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989567,0.000081265614,0.00047297153,0.00018177016,0.000085173335,0.00022213804],"domain_scores_gemma":[0.99717885,0.0014698096,0.00018046271,0.0009541959,0.0001542173,0.00006246497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032082232,0.00016240611,0.0003031026,0.00005478873,0.00022467227,0.00003389935,0.00041205046,0.00011570227,0.0000027839294],"category_scores_gemma":[0.00003995982,0.00018719723,0.000055452925,0.00023696231,0.00007258424,0.00010603095,0.00024944352,0.00021117365,0.0000013382305],"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":[0.000008035972,0.000053968204,0.0050743697,0.0003491336,0.000031127736,2.4842839e-8,0.00067049306,0.91659653,0.0044501727,0.004929735,0.000004295654,0.0678321],"study_design_scores_gemma":[0.0004289477,0.000019968322,0.0029144213,0.000283786,0.000013273406,4.8535543e-7,0.00008619556,0.9940771,0.0014470929,0.00034440047,0.00018415992,0.00020017955],"about_ca_topic_score_codex":0.000016935272,"about_ca_topic_score_gemma":0.000049657592,"teacher_disagreement_score":0.35360867,"about_ca_system_score_codex":0.000030118823,"about_ca_system_score_gemma":0.000009517464,"threshold_uncertainty_score":0.7633682},"labels":[],"label_agreement":null},{"id":"W1967497290","doi":"10.1109/tvt.2014.2367007","title":"Uplink Scheduler for SC-FDMA-Based Heterogeneous Traffic Networks With QoS Assurance and Guaranteed Resource Utilization","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","funders":"","keywords":"Telecommunications link; Quality of service; Computer science; Computer network; Frequency-division multiple access; Scheduling (production processes); Cellular network; Cellular traffic; Distributed computing; Orthogonal frequency-division multiplexing; Engineering","score_opus":0.007632898211547747,"score_gpt":0.20304276798494428,"score_spread":0.19540986977339653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967497290","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":[0.087744944,0.00032005788,0.9097367,0.00014577067,0.00017275247,0.0005806612,0.000006855478,0.0012828592,0.000009400923],"genre_scores_gemma":[0.97072846,0.000083780666,0.028595211,0.00009600097,0.000047585796,0.00030864624,0.00001778488,0.000111207046,0.000011353217],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882966,0.000030349336,0.00025971676,0.00039168575,0.00011174883,0.00037682964],"domain_scores_gemma":[0.99931216,0.00010786762,0.000053400774,0.00039304537,0.00007682738,0.000056676763],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000098303666,0.00028622113,0.00029131718,0.0003186611,0.0002106405,0.000025196052,0.00014345102,0.00042734997,0.000005175188],"category_scores_gemma":[0.0000073273764,0.0002895355,0.00006130729,0.0005745004,0.00015204155,0.00007556021,8.964844e-7,0.00034037005,0.0000028732593],"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":[0.00008681098,0.00003959551,0.000008350796,0.000044130287,0.000050655162,0.0000022256474,0.000009993365,0.960652,0.0005253734,0.000051489642,0.000014481946,0.03851491],"study_design_scores_gemma":[0.0012833005,0.0002615337,0.0000068727486,0.00010578425,0.00006225941,0.000037942384,0.000009066609,0.9732138,0.023145625,0.000022857523,0.0015481035,0.00030283624],"about_ca_topic_score_codex":4.915225e-7,"about_ca_topic_score_gemma":0.00003233708,"teacher_disagreement_score":0.8829835,"about_ca_system_score_codex":0.00005924546,"about_ca_system_score_gemma":0.000012601822,"threshold_uncertainty_score":0.99995565},"labels":[],"label_agreement":null},{"id":"W1968098382","doi":"10.1002/dac.1386","title":"Ubiquitous computing for communications and broadcasting","year":2012,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Ubiquitous computing; Broadcasting (networking); Presentation (obstetrics); Focus (optics); Wireless sensor network; Quality (philosophy); Data science; Multimedia; Telecommunications; Human–computer interaction; Computer security; Computer network","score_opus":0.02736784115071575,"score_gpt":0.30153684783958573,"score_spread":0.27416900668887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968098382","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":[0.045813166,0.035886597,0.91434246,0.0003188678,0.0018046221,0.00024482925,0.0000106689695,0.00009071776,0.0014880667],"genre_scores_gemma":[0.95110685,0.0026770425,0.0457288,0.00002188272,0.0004036571,0.00000845224,0.000018593617,0.000023238774,0.0000114716095],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999038,0.00007630551,0.0005443932,0.00003688339,0.00017978612,0.00012466658],"domain_scores_gemma":[0.9982135,0.00053025794,0.00034716583,0.00030212852,0.00054147246,0.00006544753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006103884,0.00008487849,0.00015484128,0.0001344828,0.00009202701,0.00007594609,0.000640138,0.000046900575,0.0000012613932],"category_scores_gemma":[0.000076136384,0.00008843158,0.000042850428,0.00007676789,0.000045062672,0.00050352834,0.00010930386,0.00015600777,0.0000014892388],"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":[0.000032407817,0.00008401443,0.009937253,0.000034560562,0.00035066484,4.848816e-7,0.0029150445,0.89955324,0.0013327713,0.016683793,0.0012525626,0.06782321],"study_design_scores_gemma":[0.0006389554,0.00002379563,0.0010166306,0.00032554904,0.00002635425,0.00018268067,0.000750745,0.94471645,0.00014953423,0.00015083657,0.0518658,0.00015268254],"about_ca_topic_score_codex":0.000003030931,"about_ca_topic_score_gemma":0.0000010103812,"teacher_disagreement_score":0.9052937,"about_ca_system_score_codex":0.00010460607,"about_ca_system_score_gemma":0.000010938878,"threshold_uncertainty_score":0.36061352},"labels":[],"label_agreement":null},{"id":"W1968683621","doi":"10.1049/iet-com:20060193","title":"Interaction between radio link level truncated ARQ, and TCP in multi-rate wireless networks: a cross-layer performance analysis","year":2007,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":28,"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; University of Manitoba; University of Waterloo","funders":"","keywords":"Computer science; Selective Repeat ARQ; Computer network; Automatic repeat request; Radio Link Protocol; TCP global synchronization; CUBIC TCP; Link adaptation; Queueing theory; Transmission Control Protocol; Hybrid automatic repeat request; TCP acceleration; Throughput; Go-Back-N ARQ; TCP Westwood plus; Physical layer; TCP Friendly Rate Control; Fading; Channel (broadcasting); Wireless; Telecommunications link; Network packet; Telecommunications","score_opus":0.06440537866338394,"score_gpt":0.32568304730015735,"score_spread":0.2612776686367734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968683621","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":[0.46198517,0.0004674882,0.5369043,0.000063368556,0.00006433641,0.00015700689,0.0000097363045,0.00017911014,0.00016950762],"genre_scores_gemma":[0.9763771,0.0032329846,0.019828292,0.000022158789,0.000058904072,0.00003904449,0.00034561506,0.000041810978,0.000054077645],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99881685,0.00007646547,0.0005239269,0.00019605299,0.00008286779,0.00030381462],"domain_scores_gemma":[0.9984096,0.00037243377,0.00011235303,0.00092210283,0.000101028854,0.00008246945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048479944,0.00018849535,0.00028582386,0.00036738697,0.00019937425,0.00006981773,0.00039737098,0.00015412556,0.0000072368825],"category_scores_gemma":[0.00002536852,0.0002183226,0.000055425862,0.0015950948,0.0001078963,0.0004968063,0.00011951994,0.00051054684,0.000007127604],"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":[0.000009130879,0.00002884419,0.11547977,0.000009946673,0.00012528125,4.5769036e-7,0.00033265023,0.8648632,0.000117704476,0.00003253452,0.000009100184,0.018991342],"study_design_scores_gemma":[0.00030205186,0.0000062228355,0.34632677,0.000030015435,0.00005578435,8.649904e-7,0.000036503876,0.65266126,0.00011791908,0.000005325102,0.00031204073,0.00014528041],"about_ca_topic_score_codex":0.000059319304,"about_ca_topic_score_gemma":0.0012114154,"teacher_disagreement_score":0.517076,"about_ca_system_score_codex":0.00017713623,"about_ca_system_score_gemma":0.000010229319,"threshold_uncertainty_score":0.8902937},"labels":[],"label_agreement":null},{"id":"W1968911620","doi":"10.1109/cdc.2011.6161433","title":"A Markovian jump guaranteed cost congestion control strategy for mobile networks subject to differentiated services traffic","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Markov process; Computer science; Network congestion; Quality of service; Network topology; Jump; Network traffic control; Control theory (sociology); Controller (irrigation); Computer network; Mathematical optimization; Topology (electrical circuits); Control (management); Engineering; Mathematics","score_opus":0.012974652751035978,"score_gpt":0.21707532541843638,"score_spread":0.2041006726674004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968911620","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":[0.18651904,0.00017716335,0.8094907,0.000003445484,0.0003408006,0.0019628769,0.000030977775,0.0008564138,0.0006186051],"genre_scores_gemma":[0.99635667,0.000053375155,0.0022907606,0.000088710105,0.000111818896,0.0007761709,0.00014568743,0.000086968204,0.00008982207],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988301,0.000030041005,0.00032438055,0.00027104965,0.00009120036,0.00045324556],"domain_scores_gemma":[0.999423,0.00007937404,0.000050826366,0.00021773881,0.00009733837,0.00013171163],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008684744,0.00026926046,0.00029702304,0.0001047486,0.000074500196,0.0000454612,0.00016697684,0.00015771715,0.00017287418],"category_scores_gemma":[0.000003929804,0.00026354517,0.00006995978,0.00027268048,0.000017094098,0.0001810327,0.000011627678,0.000114187416,0.000016404574],"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":[0.00021327175,0.000037879614,0.00020847651,0.00005640889,0.00006440961,0.0000016674497,0.00014765668,0.9847143,0.00018406029,0.00012018897,0.0001509746,0.014100702],"study_design_scores_gemma":[0.0014622009,0.00017498726,0.0023470481,0.000050687708,0.000049689785,0.0000029286118,0.00012286555,0.9950414,0.00021694059,0.000023455512,0.0001904386,0.0003174079],"about_ca_topic_score_codex":0.000018036746,"about_ca_topic_score_gemma":0.00042251233,"teacher_disagreement_score":0.80983764,"about_ca_system_score_codex":0.000060515467,"about_ca_system_score_gemma":0.000007638447,"threshold_uncertainty_score":0.9999817},"labels":[],"label_agreement":null},{"id":"W1969231301","doi":"10.1109/tcomm.2014.2367020","title":"Optimized Distributed Inter-Cell Interference Coordination (ICIC) Scheme Using Projected Subgradient and Network Flow Optimization","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Huawei Technologies (Canada); Carleton University","funders":"","keywords":"Subgradient method; Mathematical optimization; Scheduling (production processes); Interference (communication); Linear programming; Computer science; Computational complexity theory; Optimization problem; Single antenna interference cancellation; Polynomial; Mathematics; Algorithm; Channel (broadcasting); Decoding methods","score_opus":0.018901272718236946,"score_gpt":0.23589502661857137,"score_spread":0.21699375390033443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969231301","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":[0.0012618758,0.00017164815,0.99653673,0.00015382971,0.00035649212,0.00049349805,0.000050531682,0.00052057527,0.00045480626],"genre_scores_gemma":[0.61417574,0.0005485041,0.38490584,0.000014633218,0.000026759402,0.000099791825,0.00014895818,0.000045770346,0.000033982054],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987334,0.00016693781,0.00041650597,0.00026635057,0.00011949981,0.0002973321],"domain_scores_gemma":[0.99810886,0.0002331634,0.00014311481,0.0012253992,0.00018787774,0.0001016011],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018599117,0.00026921876,0.0002730196,0.00016589399,0.00074416795,0.00013227148,0.0004869908,0.0001441057,0.000023445811],"category_scores_gemma":[0.000020146565,0.000313742,0.00006548465,0.00045625586,0.00016082313,0.00042927428,0.000013660927,0.00042575176,0.000005307415],"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":[0.000023816978,0.00008951711,0.0000118937505,0.000022303626,0.00003589287,1.3330087e-7,0.00013653233,0.99367243,0.00043482232,0.00007372494,0.0000690492,0.0054298616],"study_design_scores_gemma":[0.00074562064,0.00004945628,0.000016184182,0.00014895068,0.000060744514,0.000004441685,0.000032961525,0.9976499,0.0006063763,0.00006238139,0.00033139327,0.00029158345],"about_ca_topic_score_codex":0.00001844899,"about_ca_topic_score_gemma":0.000051160587,"teacher_disagreement_score":0.61291385,"about_ca_system_score_codex":0.00020541067,"about_ca_system_score_gemma":0.0000232438,"threshold_uncertainty_score":0.99993145},"labels":[],"label_agreement":null},{"id":"W1969289004","doi":"10.1109/twc.2013.061413.121703","title":"Optimal Tradeoff Between Sum-Rate Efficiency and Jain's Fairness Index in Resource Allocation","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":197,"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":"Mathematical optimization; Computer science; Resource allocation; Ergodic theory; Convex optimization; Wireless; Index (typography); Fairness measure; Regular polygon; Optimization problem; Mathematics; Throughput; Telecommunications; Computer network","score_opus":0.0144264469425774,"score_gpt":0.2308395822781793,"score_spread":0.2164131353356019,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969289004","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":[0.23202413,0.00015537959,0.76577425,0.0006633512,0.00006368051,0.0005328784,0.000017625649,0.00035973667,0.00040897116],"genre_scores_gemma":[0.99403304,0.00085479463,0.0043934667,0.00004992764,0.000022621243,0.00045262772,0.00004908804,0.000075851895,0.00006860176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851125,0.00018212608,0.00048978033,0.0002876864,0.00016576418,0.00036338335],"domain_scores_gemma":[0.9981791,0.0004516205,0.0000708856,0.0010955262,0.00007417496,0.00012868551],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019270318,0.00027336972,0.00028212197,0.0003653108,0.00033137022,0.00008502411,0.00057010056,0.00019587642,0.000026910959],"category_scores_gemma":[0.000005291991,0.00032105972,0.000053421496,0.0008671588,0.0002100269,0.00052976224,0.000008332275,0.00065370277,0.000035458772],"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":[0.0000051998154,0.00009944579,0.00023078479,0.00002295835,0.000023570747,3.1853276e-7,0.00052427885,0.96716917,0.0006094036,0.00014748862,0.000042732638,0.031124642],"study_design_scores_gemma":[0.0005733195,0.000032302938,0.005803332,0.000102856444,0.000024703902,0.0000030533772,0.00036716455,0.99049294,0.0017557995,0.00007627234,0.00039431066,0.00037394743],"about_ca_topic_score_codex":0.00008740392,"about_ca_topic_score_gemma":0.00016622033,"teacher_disagreement_score":0.7620089,"about_ca_system_score_codex":0.00017243836,"about_ca_system_score_gemma":0.000025372743,"threshold_uncertainty_score":0.9999241},"labels":[],"label_agreement":null},{"id":"W1969403444","doi":"10.1002/ett.2853","title":"QoS‐based power allocation for cognitive radios with AMC and ARQ in Nakagami‐<i>m</i> fading channels","year":2014,"lang":"en","type":"article","venue":"Transactions on Emerging Telecommunications Technologies","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fading; Nakagami distribution; Computer science; Quality of service; Computer network; Automatic repeat request; Network packet; Hybrid automatic repeat request; Interference (communication); Link adaptation; Electronic engineering; Engineering; Telecommunications link; Channel (broadcasting)","score_opus":0.009056494665053668,"score_gpt":0.22986700712321764,"score_spread":0.22081051245816397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969403444","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":[0.025168445,0.00028849673,0.97066516,0.0010049305,0.00006982371,0.0006295599,0.000010462086,0.001880432,0.0002826979],"genre_scores_gemma":[0.90742797,0.000640662,0.09096465,0.000031932723,0.0000059905806,0.00082606403,0.000034327466,0.00005501823,0.000013393618],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910516,0.000035678484,0.00025915744,0.00023874076,0.00008606581,0.00027518524],"domain_scores_gemma":[0.99882895,0.00046459847,0.0000622877,0.00053590396,0.00008418083,0.000024073195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015156191,0.000214025,0.00020878867,0.0005380183,0.00028364785,0.00003370156,0.0002687593,0.00014568017,0.0000047002454],"category_scores_gemma":[0.000057103167,0.00022666097,0.000034097167,0.0007391748,0.00014962252,0.00024386014,0.0000067655633,0.00035100992,0.0000023810505],"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":[0.000024458059,0.000058146896,0.000044347533,0.000028910259,0.000029338496,1.5137323e-7,0.00021721226,0.9395355,0.00032543825,0.00061137177,0.000014915025,0.059110194],"study_design_scores_gemma":[0.0011632841,0.00016915107,0.00014056872,0.00029877957,0.000040229865,0.0000043298587,0.0012474861,0.9808694,0.013955905,0.00062838924,0.0010864069,0.0003960689],"about_ca_topic_score_codex":0.0000047863073,"about_ca_topic_score_gemma":0.000078962694,"teacher_disagreement_score":0.8822595,"about_ca_system_score_codex":0.00010272621,"about_ca_system_score_gemma":0.000013261452,"threshold_uncertainty_score":0.9242966},"labels":[],"label_agreement":null},{"id":"W1970030023","doi":"10.1109/glocom.2013.6831660","title":"Rate allocation mechanisms for multi-class service transmission over cognitive radio networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Computer science; Queueing theory; Cognitive radio; Markov decision process; Quality of service; Mathematical optimization; Markov process; Queue; Resource allocation; Transmission (telecommunications); Service (business); Computer network; Wireless; Telecommunications; Mathematics; Statistics","score_opus":0.012427820292567802,"score_gpt":0.22767501639223173,"score_spread":0.21524719609966392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970030023","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":[0.0022542411,0.00012036501,0.9954092,0.000081745755,0.00022272245,0.0010662532,0.0000033252081,0.0005111186,0.000331051],"genre_scores_gemma":[0.79172367,0.0002012688,0.2057881,0.0005759624,0.00013625131,0.00055883476,0.00027430503,0.00012490006,0.0006166798],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999207,0.000022590026,0.00021136327,0.0002027652,0.00007354217,0.00028272622],"domain_scores_gemma":[0.99948144,0.00010812148,0.00003535714,0.00010859247,0.00017476843,0.00009169944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007733164,0.00018686774,0.00015188943,0.000045516605,0.000073834584,0.000038963546,0.00008061122,0.0001423315,0.000250039],"category_scores_gemma":[0.000007811583,0.00018125495,0.0000420121,0.00021778756,0.000008073237,0.0004246878,0.000008941351,0.00010081262,0.000035688045],"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":[0.000013244685,0.000016353648,0.0000025115276,0.00003759915,0.000026537942,1.6424322e-7,0.00007838342,0.97060406,0.004340343,0.0005682467,0.00055053405,0.023762021],"study_design_scores_gemma":[0.0011167281,0.000025293606,0.00019527321,0.000058134676,0.000022885479,7.253873e-7,0.000054048152,0.99185675,0.0057115196,0.0003612144,0.00035806885,0.00023932855],"about_ca_topic_score_codex":0.000015073087,"about_ca_topic_score_gemma":0.000021837912,"teacher_disagreement_score":0.78962106,"about_ca_system_score_codex":0.00005563508,"about_ca_system_score_gemma":0.00000724253,"threshold_uncertainty_score":0.7391362},"labels":[],"label_agreement":null},{"id":"W1971346204","doi":"10.1109/tvt.2011.2178622","title":"Efficient Scheduling Algorithms for Multiantenna CDMA Systems","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":24,"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 du Québec à Montréal","funders":"","keywords":"Computer science; Scheduling (production processes); Code division multiple access; Electronic engineering; Cellular radio; Algorithm; Computer network; Engineering; Base station; Mathematical optimization; Mathematics","score_opus":0.01926873368938945,"score_gpt":0.22127545634838525,"score_spread":0.2020067226589958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971346204","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":[0.032216907,0.00042298564,0.96364725,0.000024109533,0.001206764,0.00061581103,0.000020176612,0.0017857631,0.00006023585],"genre_scores_gemma":[0.89593905,0.00007007931,0.10339542,0.000008649147,0.000032590022,0.00044249164,0.0000034109016,0.00007768617,0.000030619645],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998936,0.000012017843,0.0002820479,0.0002873456,0.00010241523,0.00038017952],"domain_scores_gemma":[0.9994146,0.000032363903,0.000042992215,0.00036051733,0.00009556009,0.000053951342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007642178,0.00021906805,0.00023621888,0.0004210353,0.00014838109,0.000010884441,0.00018420731,0.00035406367,0.0000102407475],"category_scores_gemma":[0.000004608152,0.00023490375,0.00009380706,0.0005113026,0.00007697439,0.00004434222,0.0000010514456,0.00031301996,0.00003455533],"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":[0.0000136613735,0.00006887105,0.0000018542564,0.000039965314,0.00006577771,0.000006627214,0.00006163474,0.9813056,0.0038829553,0.00030679052,0.000004393478,0.014241872],"study_design_scores_gemma":[0.0005008571,0.0000795109,0.0000023975706,0.00006511527,0.0000378226,0.000025250927,0.00014529386,0.9521677,0.046474013,0.00006197316,0.00020702323,0.00023303801],"about_ca_topic_score_codex":0.000005062658,"about_ca_topic_score_gemma":0.000004230914,"teacher_disagreement_score":0.86372215,"about_ca_system_score_codex":0.000107847,"about_ca_system_score_gemma":0.000009500284,"threshold_uncertainty_score":0.9579097},"labels":[],"label_agreement":null},{"id":"W1971493099","doi":"10.1007/s11276-013-0626-5","title":"Efficient and practical resource block allocation for LTE-based D2D network via graph coloring","year":2013,"lang":"en","type":"article","venue":"Wireless Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Graph coloring; Reuse; Graph; Distributed computing; Scheduling (production processes); Computer network; Throughput; Mathematical optimization; Theoretical computer science; Wireless; Mathematics; Telecommunications","score_opus":0.0072538837413604,"score_gpt":0.21328063409371859,"score_spread":0.20602675035235818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971493099","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":[0.07268147,0.0006442243,0.9240199,0.00021450227,0.00045746582,0.0011848336,0.0000019156137,0.0005781659,0.00021753377],"genre_scores_gemma":[0.96748614,0.000092388065,0.030544894,0.00018902426,0.000824789,0.00062583335,0.000073348056,0.00013515097,0.00002839926],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99809265,0.00006283449,0.00044620005,0.00042628858,0.00020821638,0.0007638117],"domain_scores_gemma":[0.99859715,0.00059011416,0.00012446883,0.00034149317,0.00013377926,0.00021298784],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026409436,0.0003432358,0.0003436682,0.00008694574,0.00026429482,0.00011229612,0.00011464884,0.00028248402,0.000014101473],"category_scores_gemma":[0.00002203143,0.00037373236,0.00007811453,0.0005018878,0.00009492912,0.00013819357,0.000046897105,0.00035162672,0.000008699893],"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":[0.000044040273,0.000032900898,0.00020970359,0.00005519244,0.000037270183,0.000002006979,0.00003282748,0.9829343,0.00012597107,0.00044252328,0.0037835916,0.012299689],"study_design_scores_gemma":[0.0007601588,0.000059223214,0.00034813897,0.00011270431,0.00004303157,0.000009347477,0.000022762517,0.9963127,0.000115448565,0.00015931204,0.0016497497,0.00040744874],"about_ca_topic_score_codex":0.000007359445,"about_ca_topic_score_gemma":0.000012514513,"teacher_disagreement_score":0.8948047,"about_ca_system_score_codex":0.0001073479,"about_ca_system_score_gemma":0.000018822644,"threshold_uncertainty_score":0.99987143},"labels":[],"label_agreement":null},{"id":"W1972151267","doi":"10.1109/icc.2013.6655598","title":"Power-efficient QoS scheduler for LTE uplink","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Telecommunications link; Computer science; Quality of service; Power (physics); Minification; Computer network; Multi-user; Scheduling (production processes); Real-time computing; Mathematical optimization; Mathematics","score_opus":0.0047530159144968396,"score_gpt":0.19521637667927857,"score_spread":0.19046336076478174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972151267","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":[0.019589853,0.000085162035,0.96939355,0.000077917175,0.0004536719,0.00044601443,0.0000010599663,0.0004819115,0.009470845],"genre_scores_gemma":[0.7848849,0.000014190478,0.21380404,0.000077981815,0.00012372436,0.00018357574,0.000011754134,0.00005062133,0.00084920507],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949074,0.0000022753582,0.000127595,0.00010972111,0.00005522225,0.00021443107],"domain_scores_gemma":[0.99969715,0.000033494238,0.000012768967,0.00014794592,0.000056508317,0.00005215009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000028632501,0.00009606874,0.00008464042,0.000036517606,0.000033256925,0.000023963281,0.0000660684,0.0000526567,0.00056374265],"category_scores_gemma":[0.000010280082,0.00008936706,0.00003242001,0.00009898867,0.000010050853,0.000094745046,0.0000133088015,0.000051909163,0.00026702948],"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":[9.383387e-7,0.000007565332,0.000015412885,0.000009111238,0.000007319858,7.00386e-8,0.000020575862,0.98920226,0.0007494428,0.0023860254,0.0050012036,0.0026000817],"study_design_scores_gemma":[0.00019178125,0.000011285695,0.00010618962,0.000006898374,0.000002236926,4.2746473e-7,0.000016465963,0.9939495,0.0017866541,0.00016617235,0.0036370815,0.00012531392],"about_ca_topic_score_codex":0.0000010323707,"about_ca_topic_score_gemma":3.9946391e-7,"teacher_disagreement_score":0.765295,"about_ca_system_score_codex":0.000034520726,"about_ca_system_score_gemma":0.0000034921597,"threshold_uncertainty_score":0.61725867},"labels":[],"label_agreement":null},{"id":"W1972351246","doi":"10.1109/icc.2013.6655535","title":"Energy-efficient power allocation for multicarrier systems with delay-outage probability constraints","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Subcarrier; Fading; Mathematical optimization; Transmission (telecommunications); Power (physics); Computer science; Efficient energy use; Channel (broadcasting); Control theory (sociology); Orthogonal frequency-division multiplexing; Mathematics; Telecommunications; Engineering; Electrical engineering","score_opus":0.006050105042833312,"score_gpt":0.18541735410605512,"score_spread":0.1793672490632218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972351246","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":[0.038689673,0.000046952806,0.9575165,0.000018117156,0.00017254328,0.0009694822,0.0000071996824,0.000371483,0.0022080613],"genre_scores_gemma":[0.9544061,0.0000030358467,0.04474653,0.00001903563,0.000027772903,0.00057811383,0.000029836345,0.000037751757,0.00015183726],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921584,0.000013744905,0.00021538386,0.00019615686,0.000115984796,0.00024285991],"domain_scores_gemma":[0.99940974,0.00006633816,0.000033296863,0.00021619606,0.00019285183,0.00008159593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000068648165,0.00014677984,0.0001331094,0.00003380334,0.00004603377,0.00004425569,0.000067182285,0.00007184005,0.00009093809],"category_scores_gemma":[0.000013572204,0.00011838092,0.000024251336,0.000110587855,0.00006752935,0.00013276975,0.000009025175,0.000047269892,0.000012625435],"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":[0.0000054552443,0.000020580734,0.00006198386,0.000036098205,0.000022065831,2.2160086e-7,0.00007837606,0.9923993,0.00040043503,0.0050244536,0.000190748,0.001760283],"study_design_scores_gemma":[0.00033615218,0.000030888597,0.00007616414,0.000023814522,0.000008325434,0.0000035608332,0.000101053396,0.99831676,0.00048945216,0.000074611504,0.00036792966,0.00017127581],"about_ca_topic_score_codex":0.000015307634,"about_ca_topic_score_gemma":0.000008149707,"teacher_disagreement_score":0.9157164,"about_ca_system_score_codex":0.00010142359,"about_ca_system_score_gemma":0.000014494194,"threshold_uncertainty_score":0.48274338},"labels":[],"label_agreement":null},{"id":"W1972430058","doi":"10.1109/qbsc.2012.6221360","title":"Scheduling vs. pseudo-scheduling models in IEEE 802.16j wireless relay networks","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Defence Research and Development Canada; Concordia University","funders":"","keywords":"Computer science; Fair-share scheduling; Round-robin scheduling; Dynamic priority scheduling; Scheduling (production processes); Rate-monotonic scheduling; Two-level scheduling; WiMAX; Earliest deadline first scheduling; Wireless broadband; Mathematical optimization; Distributed computing; Computer network; Wireless; Wireless network; Quality of service; Mathematics; Telecommunications","score_opus":0.013604650234253371,"score_gpt":0.2222713268583988,"score_spread":0.20866667662414543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972430058","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":[0.25071466,0.00090943585,0.74400353,0.000021079837,0.00089340715,0.0002065107,7.672281e-7,0.0006406949,0.0026099298],"genre_scores_gemma":[0.84650534,0.00074638374,0.15177989,0.00008426666,0.0005998158,0.000048234375,0.000016668313,0.00013564005,0.00008375596],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979112,0.00004367374,0.0005421153,0.0002967748,0.00021857698,0.0009876683],"domain_scores_gemma":[0.9991716,0.00011820625,0.00006742973,0.00037661096,0.000049372287,0.00021678302],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003524231,0.00035523184,0.00038002073,0.00017962734,0.000086426284,0.00004514177,0.00022495374,0.00031182665,0.000046146964],"category_scores_gemma":[0.00001380065,0.0003875855,0.000076090226,0.0006550247,0.000032733347,0.0012945652,0.00005163923,0.00060442,0.000039931245],"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":[0.000014138802,0.000031631873,0.0017324919,0.00003055075,0.000020367346,0.0000029263808,0.00022574456,0.99159265,0.00032184258,0.0025943075,0.00006136403,0.0033720047],"study_design_scores_gemma":[0.00043570375,0.000008323688,0.00015283105,0.00011775054,0.000012469608,0.000007042508,0.000080720376,0.9977424,0.00075783615,0.00017090041,0.000048078397,0.00046592366],"about_ca_topic_score_codex":0.000013465394,"about_ca_topic_score_gemma":0.000025800276,"teacher_disagreement_score":0.5957907,"about_ca_system_score_codex":0.0002180026,"about_ca_system_score_gemma":0.000014313172,"threshold_uncertainty_score":0.9998576},"labels":[],"label_agreement":null},{"id":"W1972456124","doi":"10.1007/s11276-007-0077-y","title":"An efficient delay constrained scheduling scheme for IEEE 802.16 networks","year":2007,"lang":"en","type":"article","venue":"Wireless Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Computer science; Scheduling (production processes); Adaptability; Queue; Scheme (mathematics); Simple (philosophy); Distributed computing; Real-time computing; Computer network; Mathematical optimization; Mathematics","score_opus":0.00811876012927952,"score_gpt":0.23958730119923183,"score_spread":0.2314685410699523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972456124","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":[0.12314254,0.0010520454,0.87122655,0.000012035591,0.0020216042,0.0008030739,0.000009024064,0.0012654781,0.00046766724],"genre_scores_gemma":[0.9254649,0.0002105769,0.071370244,0.00012821663,0.0022162246,0.00010318079,0.0002314603,0.000247904,0.000027281156],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967488,0.000042246193,0.0008173331,0.0006272223,0.00028452525,0.0014798674],"domain_scores_gemma":[0.99817836,0.00039543913,0.00017227758,0.0006210607,0.0002099444,0.00042291108],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007987336,0.0005707349,0.0005505184,0.00017664502,0.00033297416,0.00011099662,0.00042299478,0.0005744465,0.00002859929],"category_scores_gemma":[0.00001908632,0.00064304826,0.00017753823,0.00072616525,0.00015867337,0.00025949677,0.00003379242,0.00063861127,0.0000071324457],"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":[0.00010924002,0.00006317772,0.00019200596,0.00003695602,0.00007037453,0.000012951851,0.000059041813,0.96031195,0.00043177203,0.0013448434,0.00030568268,0.037062015],"study_design_scores_gemma":[0.0012601491,0.00007738115,0.000058181056,0.00013960355,0.000038707094,0.00001909559,0.00009555892,0.996542,0.0004914346,0.000041844625,0.00049594627,0.0007401388],"about_ca_topic_score_codex":0.0000040879186,"about_ca_topic_score_gemma":0.00005285909,"teacher_disagreement_score":0.8023224,"about_ca_system_score_codex":0.00031052477,"about_ca_system_score_gemma":0.000031853462,"threshold_uncertainty_score":0.9996021},"labels":[],"label_agreement":null},{"id":"W1972966796","doi":"10.1109/icc.2010.5501765","title":"Pattern-Based Channel Quality Prediction for Adaptive Coding and Modulation in Wireless Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; École de Technologie Supérieure","funders":"","keywords":"Computer science; Coding (social sciences); Link adaptation; Wireless; Context (archaeology); Channel (broadcasting); Wireless network; Data mining; Algorithm; Real-time computing; Computer network; Fading; Telecommunications; Mathematics","score_opus":0.01485599095444304,"score_gpt":0.23541015144342636,"score_spread":0.22055416048898333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972966796","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":[0.18857718,0.000008829918,0.81046724,0.000019809646,0.00034266023,0.000305166,0.0000089060895,0.00019012082,0.00008006661],"genre_scores_gemma":[0.9937713,0.000017944307,0.0058114026,0.000024011288,0.00016616617,0.00009510869,0.0000774428,0.000029058045,0.000007571937],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938065,0.000015063315,0.00020909653,0.000160533,0.00006358736,0.00017109714],"domain_scores_gemma":[0.9996709,0.00011823537,0.000036069534,0.00009786976,0.000038615613,0.000038299913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017081758,0.00010880229,0.00012318089,0.00006612103,0.000043142907,0.000016605833,0.000033819226,0.00013854519,0.0000049209243],"category_scores_gemma":[0.000011874984,0.000119552366,0.000017864028,0.000116514224,0.000017242253,0.00018498884,0.000007322213,0.00016885066,2.5168606e-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":[0.000017683882,0.000008018323,0.0027605076,0.000022214363,0.000003934612,1.2215965e-7,0.000038881622,0.9759648,0.0008504176,0.00049073907,0.00002011222,0.01982256],"study_design_scores_gemma":[0.0005674604,0.000016654805,0.018096484,0.00002394047,0.000003029656,2.7260583e-7,0.000021051033,0.9804757,0.0004895007,0.00017892009,0.0000062987488,0.000120646575],"about_ca_topic_score_codex":0.000017265693,"about_ca_topic_score_gemma":0.00032534648,"teacher_disagreement_score":0.80519414,"about_ca_system_score_codex":0.00003795073,"about_ca_system_score_gemma":0.0000041548205,"threshold_uncertainty_score":0.4875204},"labels":[],"label_agreement":null},{"id":"W1973059521","doi":"10.1109/iit.2007.4430479","title":"Optimal Frame Length for Keeping Normalized Goodput with Lowest Requirement on BER","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Université du Québec à Montréal","funders":"","keywords":"Goodput; Frame (networking); Computer science; Overhead (engineering); Bit error rate; Transmission (telecommunications); Automatic repeat request; Computer network; Reliability (semiconductor); Algorithm; Wireless; Hybrid automatic repeat request; Real-time computing; Channel (broadcasting); Telecommunications; Throughput; Physics","score_opus":0.010049862207233374,"score_gpt":0.23563829669656194,"score_spread":0.22558843448932858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973059521","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":[0.04260808,0.000037447586,0.944031,0.000035110475,0.00018360044,0.0004285562,0.0000025855684,0.00047902926,0.012194612],"genre_scores_gemma":[0.674092,0.000029044986,0.3250363,0.00016880702,0.00018384453,0.00003928351,0.00003123446,0.000076226985,0.00034324653],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897844,0.000004973454,0.00023786846,0.00019583435,0.00016488363,0.00041802364],"domain_scores_gemma":[0.9995257,0.0001015115,0.00003752966,0.00020127876,0.00005252797,0.00008140321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017770867,0.00018515467,0.00016509139,0.00007482607,0.00007042771,0.000023520855,0.00008673286,0.00007989356,0.00005253332],"category_scores_gemma":[0.000011394202,0.00016650882,0.000037716858,0.00015980688,0.000020233234,0.00020208185,0.000013556339,0.00011393317,0.000016418378],"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":[0.00012314797,0.000023172515,0.00009216922,0.000026496986,0.000034211163,0.000003306762,0.00007205877,0.99249125,0.00040128268,0.00232187,0.00023456878,0.0041764523],"study_design_scores_gemma":[0.0020490615,0.00036283393,0.0003418959,0.00012655747,0.00002877515,0.0000055906567,0.000086886816,0.9659552,0.021797521,0.00004252422,0.008666029,0.0005371434],"about_ca_topic_score_codex":0.0000030787473,"about_ca_topic_score_gemma":0.00003236275,"teacher_disagreement_score":0.6314839,"about_ca_system_score_codex":0.00012817023,"about_ca_system_score_gemma":0.000007604835,"threshold_uncertainty_score":0.6790033},"labels":[],"label_agreement":null},{"id":"W1973422724","doi":"10.1109/glocom.2008.ecp.1009","title":"Connection-Based Scheduling for Supporting Real-Time Traffic in Wireless Mesh Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Network packet; Scheduling (production processes); Wireless mesh network; Latency (audio); Distributed computing; Fair-share scheduling; Real-time computing; Wireless network; Wireless; Mathematical optimization; Quality of service; Mathematics","score_opus":0.010087309142217142,"score_gpt":0.2271188937624594,"score_spread":0.21703158462024225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973422724","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":[0.39458448,0.000015879838,0.60384476,0.000016492511,0.00014148852,0.00028721534,0.0000013034427,0.0006295497,0.00047883735],"genre_scores_gemma":[0.95287544,0.00011280871,0.046458572,0.000029437266,0.00016313478,0.000095952084,0.00009091185,0.000082110535,0.000091652655],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998814,0.000017486593,0.00041549045,0.00023045404,0.00008033221,0.00044223852],"domain_scores_gemma":[0.99938846,0.00026985738,0.00006241713,0.0001549058,0.00005479711,0.000069566304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016258877,0.00018620177,0.00025573888,0.00012532246,0.00011143963,0.000014300349,0.00008712013,0.0001372079,0.00006575828],"category_scores_gemma":[0.00003105064,0.00021324502,0.00006461531,0.00039278204,0.000027156611,0.00016905075,0.000007303224,0.00014394318,0.000007224959],"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":[0.000018787812,0.000016607173,0.0003548293,0.00002472979,0.000009023305,0.0000053237513,0.00004610775,0.9952194,0.00052614306,0.00025039513,0.00018972019,0.003338926],"study_design_scores_gemma":[0.0007644317,0.000021714703,0.000104732404,0.000042235286,0.000005641986,0.0000045306124,0.0000320794,0.9977828,0.0009582386,0.000013537611,0.000020175701,0.00024988304],"about_ca_topic_score_codex":0.000007501334,"about_ca_topic_score_gemma":0.000041362648,"teacher_disagreement_score":0.55829096,"about_ca_system_score_codex":0.000120179175,"about_ca_system_score_gemma":0.000029701177,"threshold_uncertainty_score":0.86958796},"labels":[],"label_agreement":null},{"id":"W1974122131","doi":"10.1155/wcn/2006/75820","title":"Capacity Planning for Group-Mobility Users in OFDMA Wireless Networks","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Computer science; Capacity planning; Orthogonal frequency-division multiple access; Microcell; Dimensioning; Computer network; Channel (broadcasting); Maximal-ratio combining; Channel capacity; Signal-to-interference ratio; Capacity utilization; Frequency-division multiple access; Interference (communication); Randomness; Wireless; Telecommunications; Orthogonal frequency-division multiplexing; Fading; Statistics; Mathematics","score_opus":0.028405808956710712,"score_gpt":0.2562951977997157,"score_spread":0.227889388843005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974122131","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":[0.61105734,0.009338853,0.37728566,0.00024313455,0.00072441995,0.00053004327,0.00000913428,0.00024676253,0.00056462234],"genre_scores_gemma":[0.9832482,0.00943989,0.0063217417,0.0000686742,0.00065928913,0.00011512666,0.000049393682,0.000088955785,0.000008753902],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980579,0.00019097525,0.00074705674,0.00026119896,0.00017116133,0.0005717154],"domain_scores_gemma":[0.99816346,0.0007662117,0.0002434997,0.00061958726,0.000087694534,0.00011951718],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00070723897,0.00032197454,0.00041728764,0.00020869538,0.0006512602,0.000170937,0.00052793033,0.00018278485,0.000003036141],"category_scores_gemma":[0.000007405897,0.0003418648,0.00010100214,0.0005205323,0.00014384242,0.00035158207,0.0000983982,0.00097533583,5.3098563e-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":[0.000041918498,0.00008999271,0.024149753,0.000026234344,0.0000286618,0.0000034320628,0.00012732655,0.90914255,0.00014235974,0.0015520615,0.00017891184,0.064516805],"study_design_scores_gemma":[0.0008264135,0.000051174735,0.009914668,0.00060015975,0.000021367287,0.000025515938,0.00006159823,0.98316723,0.000025277317,0.0007531728,0.0041887336,0.00036468724],"about_ca_topic_score_codex":0.000019883766,"about_ca_topic_score_gemma":0.00019133411,"teacher_disagreement_score":0.3721908,"about_ca_system_score_codex":0.00022432767,"about_ca_system_score_gemma":0.000012862432,"threshold_uncertainty_score":0.9999033},"labels":[],"label_agreement":null},{"id":"W1974421059","doi":"10.1016/j.jcss.2010.02.006","title":"The design and evaluation of fair scheduling in wireless mesh networks","year":2010,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Round-robin scheduling; Fair-share scheduling; Dynamic priority scheduling; Two-level scheduling; Scheduling (production processes); Maximum throughput scheduling; Rate-monotonic scheduling; Distributed computing; Computer network; Mathematical optimization; Mathematics; Quality of service","score_opus":0.01739725792280923,"score_gpt":0.249744633077948,"score_spread":0.23234737515513876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974421059","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":[0.4581481,0.00043120168,0.54093724,0.000009386878,0.00038996685,0.000054199973,2.718048e-8,0.000004031045,0.000025835534],"genre_scores_gemma":[0.96993315,0.00014388513,0.029790387,0.0000015593473,0.00012672872,0.0000010323986,3.3188442e-8,0.000002948339,2.5953207e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924207,0.00008813528,0.00028644237,0.000053400814,0.00024391356,0.00008602314],"domain_scores_gemma":[0.99946404,0.0002175328,0.00013157424,0.00004097914,0.00011820412,0.000027703507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029282258,0.000051122563,0.00012538613,0.00006790871,0.0000817294,0.00006329338,0.000105442596,0.000030268837,2.3402713e-7],"category_scores_gemma":[0.000007705975,0.000032418313,0.000012827732,0.00016941664,0.00007781353,0.0002156599,0.000013586094,0.00011194083,2.7929488e-8],"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":[0.0000026770194,0.0000015297366,0.00086255436,0.000011504049,0.000004160159,4.1522094e-7,0.000107160784,0.96444786,0.00014796006,0.00088106,0.000005410671,0.033527683],"study_design_scores_gemma":[0.00018074193,0.00003232044,0.0020414407,0.00013125286,0.0000066829143,0.00004213451,0.00014458975,0.9972037,0.00007685155,0.000103039114,0.0000020399775,0.000035200832],"about_ca_topic_score_codex":6.506723e-7,"about_ca_topic_score_gemma":0.0000044886806,"teacher_disagreement_score":0.5117851,"about_ca_system_score_codex":0.000012858141,"about_ca_system_score_gemma":0.000024465777,"threshold_uncertainty_score":0.13219804},"labels":[],"label_agreement":null},{"id":"W1974435352","doi":"10.1109/iwcmc.2013.6583727","title":"WiMAX network with Quality of Service for streaming multimedia applications","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Eion (Canada); Algonquin College","funders":"","keywords":"WiMAX; Computer science; Quality of service; Computer network; Multimedia; Protocol (science); Mobile QoS; Service (business); Focus (optics); Telecommunications; Service provider; Wireless","score_opus":0.01084665907600116,"score_gpt":0.23530057830610734,"score_spread":0.22445391923010619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974435352","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":[0.0069879713,0.00005893415,0.9903702,0.000046025187,0.00002526714,0.00075380615,0.0000057485886,0.00022412481,0.0015279198],"genre_scores_gemma":[0.4432649,0.000013770319,0.5557903,0.000049834507,0.00010478387,0.0006197466,0.000059617327,0.0000314025,0.00006564573],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947643,0.0000060792104,0.00019387057,0.00009952793,0.00006365598,0.00016045426],"domain_scores_gemma":[0.99943775,0.00014999855,0.000047690686,0.00018221732,0.00014310752,0.000039230254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000045815792,0.00008676608,0.00012935641,0.000016459273,0.000031620042,0.000007724575,0.00007383552,0.00003954784,0.00004359484],"category_scores_gemma":[0.000004140943,0.00007690766,0.000016339363,0.00023424978,0.0000132198475,0.00014555005,0.000009717366,0.000039100418,0.000009885276],"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":[0.000003385943,0.000008434658,0.0005915013,0.00008073741,0.000017057202,7.308213e-9,0.000036500503,0.9842364,0.00046680754,0.0008119154,0.00028505025,0.013462175],"study_design_scores_gemma":[0.00028826165,0.000010050568,0.0023590906,0.000017543827,0.00000775546,1.7869588e-7,0.00006729877,0.99556845,0.00061422563,0.00047215543,0.00047358513,0.00012138889],"about_ca_topic_score_codex":0.000051343563,"about_ca_topic_score_gemma":0.00015674507,"teacher_disagreement_score":0.4362769,"about_ca_system_score_codex":0.000018752964,"about_ca_system_score_gemma":0.000005869032,"threshold_uncertainty_score":0.31362033},"labels":[],"label_agreement":null},{"id":"W1974737638","doi":"10.1002/ett.965","title":"Efficient packet data service in a spread spectrum OFDM cellular system with 2‐dimensional radio resource allocation","year":2004,"lang":"en","type":"article","venue":"European Transactions on Telecommunications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Orthogonal frequency-division multiplexing; Link adaptation; Fading; Hybrid automatic repeat request; Network packet; Spectral efficiency; Throughput; Transmission delay; Real-time computing; Telecommunications link; Wireless; Telecommunications; Channel (broadcasting)","score_opus":0.013497502702964282,"score_gpt":0.1999728325211275,"score_spread":0.1864753298181632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974737638","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":[0.045401644,0.0002858868,0.9459969,0.00089777005,0.00008776942,0.0005224248,0.000084804306,0.00085268804,0.005870155],"genre_scores_gemma":[0.97174615,0.000060063543,0.027448826,0.000057871373,0.000032740845,0.000034333392,0.0004664336,0.00012189824,0.00003170697],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838674,0.00027306585,0.00041249697,0.00036044387,0.00027069295,0.00029656797],"domain_scores_gemma":[0.99733275,0.000098215765,0.00007501465,0.0023284764,0.00006783631,0.000097701944],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00041618382,0.0002453525,0.00018677438,0.00026380847,0.0002935234,0.00004392711,0.0008564473,0.000045384913,0.000016989106],"category_scores_gemma":[0.000006170192,0.0002612875,0.000031278327,0.0011008867,0.000051731193,0.00015564916,0.000025553963,0.0005086206,0.00016634227],"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":[0.000018566627,0.00018577458,0.0000030402855,0.000030185683,0.00003515393,0.0000059067497,0.00031968902,0.99722475,0.00028713702,0.00036041014,0.000028206268,0.0015011517],"study_design_scores_gemma":[0.0013143308,0.000046037254,0.0007358286,0.00040558793,0.00005220618,0.000037650647,0.00032442363,0.9941904,0.0010914466,0.0000095713895,0.001422594,0.0003699355],"about_ca_topic_score_codex":0.000053646327,"about_ca_topic_score_gemma":0.0007689434,"teacher_disagreement_score":0.92634445,"about_ca_system_score_codex":0.00046805633,"about_ca_system_score_gemma":0.000052373663,"threshold_uncertainty_score":0.9999839},"labels":[],"label_agreement":null},{"id":"W1975627893","doi":"10.1109/twc.2013.022113.120678","title":"Frequency Domain Packet Scheduling with MIMO for 3GPP LTE Downlink","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":26,"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":"MIMO; Computer science; Scheduling (production processes); Telecommunications link; Approximation algorithm; Submodular set function; Mathematical optimization; Job shop scheduling; Orthogonal frequency-division multiplexing; Greedy algorithm; Algorithm; Subcarrier; Mathematics; Computer network; Channel (broadcasting)","score_opus":0.015334330080909493,"score_gpt":0.2362499057858478,"score_spread":0.22091557570493833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975627893","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":[0.03229852,0.00022630888,0.96346164,0.00075339817,0.00020897735,0.0011268691,0.00008594712,0.00081320957,0.0010251617],"genre_scores_gemma":[0.6837685,0.00070231943,0.31368968,0.00006458531,0.00003286315,0.0015249148,0.00006418842,0.00009602237,0.000056917874],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986503,0.00006764222,0.0004206197,0.00027122546,0.00017189424,0.00041832766],"domain_scores_gemma":[0.9975145,0.00038214854,0.00008478348,0.0016603222,0.0002139438,0.00014431975],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010120736,0.00031378292,0.00028161964,0.00020322774,0.00061554025,0.00009063214,0.00068223104,0.00016295293,0.000079878955],"category_scores_gemma":[0.0000030380118,0.00031687232,0.0001147305,0.00052303134,0.00018077515,0.00056057307,0.0000036737692,0.00050546223,0.00010041778],"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":[0.0000122553,0.00015940664,0.000022959404,0.000048599213,0.00012694534,3.4064072e-7,0.00034908814,0.9703052,0.005242958,0.0025401725,0.00012199228,0.021070061],"study_design_scores_gemma":[0.0014970496,0.00013303978,0.00008771656,0.0002714961,0.000098633645,0.000012856189,0.00050438195,0.9841552,0.007489064,0.0040204665,0.000891124,0.0008389835],"about_ca_topic_score_codex":0.000037740032,"about_ca_topic_score_gemma":0.00029622513,"teacher_disagreement_score":0.65147,"about_ca_system_score_codex":0.0001740754,"about_ca_system_score_gemma":0.000041651703,"threshold_uncertainty_score":0.99992836},"labels":[],"label_agreement":null},{"id":"W1976275892","doi":"10.5539/nct.v1n1p67","title":"Dynamic Radio Resource Allocation for Macro-Femto Hybrid Cellular Network Maintaining Fairness","year":2012,"lang":"en","type":"article","venue":"Network and Communication Technologies","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Femtocell; Femto-; Quality of service; Throughput; Resource allocation; Macro; Transmission (telecommunications); Cellular network; Wireless; Base station; Telecommunications","score_opus":0.007231940679929581,"score_gpt":0.21052413382575877,"score_spread":0.2032921931458292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976275892","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":[0.0150359105,0.04823082,0.9316892,0.00047654915,0.00019884613,0.0006110242,0.000004355427,0.0031230513,0.0006302198],"genre_scores_gemma":[0.8837301,0.0068556936,0.10860347,0.000033475433,0.000107992666,0.00031757497,0.00023795957,0.0000660959,0.000047596386],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986974,0.00005937514,0.00033885692,0.00019281101,0.00010097325,0.0006105914],"domain_scores_gemma":[0.99863464,0.00027446612,0.00012684768,0.00086369587,0.000053003143,0.000047325582],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004586977,0.00023960197,0.00025370411,0.000072969604,0.00044163002,0.00005494628,0.00047791837,0.00020349275,0.0000032802195],"category_scores_gemma":[0.000044004282,0.00026463263,0.00004081241,0.0003919513,0.00015600806,0.0003122025,0.0002187013,0.00031785388,0.0000038277367],"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":[0.000016165555,0.000011599781,0.00064449775,0.000031275576,0.000034319797,1.6049565e-7,0.000105675615,0.87435555,0.00009626208,0.015045081,0.003406114,0.10625327],"study_design_scores_gemma":[0.00038829405,0.000039373255,0.00032886936,0.00014705495,0.00004489272,0.000009638478,0.0008180085,0.9161969,0.0007496902,0.01835538,0.062451724,0.00047016196],"about_ca_topic_score_codex":0.0000012725943,"about_ca_topic_score_gemma":0.0000062513554,"teacher_disagreement_score":0.86869425,"about_ca_system_score_codex":0.00012022618,"about_ca_system_score_gemma":0.00000659551,"threshold_uncertainty_score":0.99998057},"labels":[],"label_agreement":null},{"id":"W1976445502","doi":"10.1109/wimob.2010.5645044","title":"Scheduling and resource allocation for multiclass services in LTE uplink systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":40,"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":"Quality of service; Computer science; Telecommunications link; Scheduling (production processes); Computer network; Resource allocation; Distributed computing; Limiting; Mathematical optimization; Engineering; Mathematics","score_opus":0.0046012747149186085,"score_gpt":0.2078291960919841,"score_spread":0.2032279213770655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976445502","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":[0.38472217,0.00016467564,0.61405617,0.000036235622,0.00018208861,0.0002909617,7.8169313e-7,0.00019459086,0.00035231016],"genre_scores_gemma":[0.9098929,0.000019600433,0.08985451,0.000012576149,0.00008385229,0.000050004604,0.000016414026,0.000024023095,0.00004611093],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958915,0.0000042266897,0.0001404832,0.00011001876,0.00003769996,0.00011844319],"domain_scores_gemma":[0.9997611,0.00006497954,0.000019107723,0.00009866254,0.000025958187,0.000030207366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000100224825,0.000073135874,0.00008149815,0.000051268118,0.000027120066,0.000032207758,0.00004616386,0.000076013435,7.9963365e-7],"category_scores_gemma":[0.000009285359,0.00007550122,0.0000075736166,0.00008712152,0.000007843767,0.00014876886,0.0000104294,0.0000935135,0.0000013226771],"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":[0.0000033842782,0.000003044865,0.0005519673,0.00012738502,0.0000031201484,1.1425335e-7,0.000098330944,0.9882241,0.007537192,0.0013827826,0.0000041521425,0.0020644527],"study_design_scores_gemma":[0.0002835074,0.0000040160326,0.00026165435,0.000036933867,0.0000027059327,9.816503e-7,0.00014104744,0.99764806,0.0007627877,0.000039616323,0.0007315938,0.00008712378],"about_ca_topic_score_codex":0.000012578799,"about_ca_topic_score_gemma":0.00016489314,"teacher_disagreement_score":0.52517074,"about_ca_system_score_codex":0.000014993543,"about_ca_system_score_gemma":0.0000022053864,"threshold_uncertainty_score":0.30788505},"labels":[],"label_agreement":null},{"id":"W1976654852","doi":"10.1109/itwksps.2010.5503214","title":"Throughput-delay trade-off of CSMA policies in wireless networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Throughput; Computer network; Computer science; Wireless network; Wireless; Telecommunications","score_opus":0.004984255140530295,"score_gpt":0.21344413820577343,"score_spread":0.20845988306524313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976654852","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":[0.5866121,0.00022135342,0.3975767,0.00009562539,0.00069100806,0.00021415461,0.0000036177094,0.00040208158,0.014183365],"genre_scores_gemma":[0.9922169,0.00036010068,0.007119707,0.000038415692,0.00015351843,0.000011757962,0.000011524666,0.00004588321,0.000042189316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991869,0.000010771525,0.0002982616,0.00012553437,0.000096340176,0.00028220122],"domain_scores_gemma":[0.9996072,0.00006553965,0.00003624455,0.0002303385,0.0000151236145,0.0000455187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007085097,0.0001470067,0.00021418935,0.00008391654,0.000019746194,0.000010317834,0.00014318734,0.00015262884,0.000059376194],"category_scores_gemma":[0.000006902535,0.00014586962,0.00003769956,0.0003827905,0.000055913497,0.00018610996,0.000022830463,0.0003082059,0.0000029854257],"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":[0.0000036388733,0.000016195416,0.0017680229,0.000013260137,0.000008021097,0.0000016486877,0.00015800471,0.9703256,0.0018306746,0.005438236,0.00035686934,0.020079859],"study_design_scores_gemma":[0.0002578929,0.000012092908,0.002921432,0.000019142662,0.0000038238218,0.0000048103498,0.00004652436,0.99304134,0.0025408585,0.00015633742,0.0008219803,0.00017378174],"about_ca_topic_score_codex":0.000025944995,"about_ca_topic_score_gemma":0.000493161,"teacher_disagreement_score":0.4056048,"about_ca_system_score_codex":0.000022611503,"about_ca_system_score_gemma":0.0000073625783,"threshold_uncertainty_score":0.59483904},"labels":[],"label_agreement":null},{"id":"W1977167986","doi":"10.1016/s0166-5316(02)00087-1","title":"A performance analysis of a discrete-time queueing system with server interruption for modeling wireless ATM multiplexer","year":2002,"lang":"en","type":"article","venue":"Performance Evaluation","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Multiplexer; Queueing theory; Computer science; Computer network; Layered queueing network; Wireless; Queueing system; Real-time computing; Multiplexing; Telecommunications","score_opus":0.03147146219320217,"score_gpt":0.2537607558979556,"score_spread":0.22228929370475342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977167986","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":[0.6785366,0.00013564722,0.3204204,0.0000031235572,0.000073722906,0.000511934,0.000005885028,0.00015413451,0.00015854705],"genre_scores_gemma":[0.9927648,0.00012498962,0.0064041954,0.0000030275476,0.000090225054,0.00033731162,0.0001935855,0.000056759938,0.000025106267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984902,0.000036183577,0.00047739776,0.00022996026,0.00045265903,0.00031357788],"domain_scores_gemma":[0.9991262,0.000038407623,0.00016440607,0.00027930478,0.00034194303,0.000049747316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005443005,0.00022405584,0.0003652643,0.0003345643,0.000116060415,0.000021850668,0.00011250929,0.00009021971,0.00005659685],"category_scores_gemma":[0.000010214064,0.00020942595,0.000089942565,0.0009506915,0.000021577127,0.0010443865,0.0000160388,0.00009717154,0.000012535157],"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":[0.000057437934,0.000016659113,0.005294557,0.0003261419,0.00025845895,3.6747593e-8,0.0007932252,0.9707983,0.00076949777,0.000008757001,0.0000034066757,0.021673525],"study_design_scores_gemma":[0.00070751336,0.00006988423,0.0023749645,0.00032284536,0.0008248705,0.0000014115549,0.00009926949,0.9944559,0.00088419224,3.3853266e-7,0.0000028634192,0.00025599662],"about_ca_topic_score_codex":0.0000055618375,"about_ca_topic_score_gemma":0.000015343314,"teacher_disagreement_score":0.3142282,"about_ca_system_score_codex":0.00036419078,"about_ca_system_score_gemma":0.000009655137,"threshold_uncertainty_score":0.8540142},"labels":[],"label_agreement":null},{"id":"W1979114316","doi":"10.1007/s11235-009-9171-z","title":"Cross-layer resource allocation for real-time services in OFDM-based cognitive radio systems","year":2009,"lang":"en","type":"article","venue":"Telecommunication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; PHY; Quality of service; Physical layer; Orthogonal frequency-division multiplexing; Computer network; Cognitive radio; Network packet; Resource allocation; Telecommunications link; Throughput; Transmitter power output; Wireless; Channel (broadcasting); Transmitter; Telecommunications","score_opus":0.01425218832265736,"score_gpt":0.2697380619960559,"score_spread":0.25548587367339853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979114316","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":[0.43770662,0.010166441,0.5231794,0.00031108686,0.00070015294,0.008373987,0.00013515957,0.0034547048,0.015972419],"genre_scores_gemma":[0.99565357,0.00024608622,0.0022044678,0.000035078083,0.00012845558,0.0005052955,0.00091732596,0.00007053723,0.00023918194],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982732,0.00020165171,0.0007334781,0.00026290186,0.00019580855,0.0003329471],"domain_scores_gemma":[0.9982612,0.00042364324,0.00024005244,0.0007513123,0.0002540678,0.00006968972],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006032985,0.00024328101,0.00037229407,0.00022381562,0.0001374946,0.0001595373,0.00043693438,0.00020214755,0.0000052747487],"category_scores_gemma":[0.00002948273,0.00028033042,0.000052451207,0.0004949921,0.00002962013,0.0003707846,0.000017599194,0.00017044651,0.000036321628],"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":[0.000051457566,0.000041412717,0.00037027473,0.00021292618,0.000018004606,3.4836557e-7,0.0003368622,0.99453026,0.0023716425,0.00031619027,0.00013596134,0.001614649],"study_design_scores_gemma":[0.0011223536,0.000052072977,0.0025467118,0.00056257413,0.000015323474,0.0000036277474,0.00028437603,0.9917897,0.0005582095,0.00001375163,0.0027602108,0.0002910709],"about_ca_topic_score_codex":0.00009504677,"about_ca_topic_score_gemma":0.000021227517,"teacher_disagreement_score":0.5579469,"about_ca_system_score_codex":0.00032161604,"about_ca_system_score_gemma":0.000026610676,"threshold_uncertainty_score":0.9999649},"labels":[],"label_agreement":null},{"id":"W1979213681","doi":"10.1109/isit.2010.5513303","title":"Network capacity region of multi-queue multi-server queueing system with time varying connectivities","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Queueing theory; Queue; Computer science; Bulk queue; Computer network; Real-time computing; Queueing system; Upper and lower bounds; Layered queueing network; Queue management system; Mathematics","score_opus":0.01510965410585875,"score_gpt":0.19408608275185665,"score_spread":0.17897642864599791,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979213681","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":[0.23763311,0.00005579609,0.7597721,0.0000051189704,0.00028661237,0.00026627563,0.0000018164152,0.0007765292,0.0012026194],"genre_scores_gemma":[0.87228423,0.000007484877,0.12727934,0.000010270594,0.00013881533,0.000024071875,0.0000071972795,0.00007211904,0.00017647992],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989995,0.000036521236,0.00028480144,0.00021813021,0.00013273935,0.000328325],"domain_scores_gemma":[0.99927676,0.0001238922,0.00010154091,0.00032722967,0.000102170685,0.0000684267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013532444,0.00022966554,0.00031907158,0.000063708394,0.00009397192,0.000023015818,0.00012496133,0.0001503344,0.000018721723],"category_scores_gemma":[0.000017326154,0.00020799827,0.000042199346,0.00025475107,0.000067879206,0.00038281266,0.000028729648,0.0002937765,0.00001026572],"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":[0.000014790797,0.000016123,0.0019430415,0.00016587296,0.000038206595,0.0000066853813,0.0001694199,0.99242425,0.003366662,0.0015377309,0.000056448604,0.0002607491],"study_design_scores_gemma":[0.00063460646,0.000019946381,0.00044990666,0.0002432273,0.000016644792,0.0000349906,0.00008858268,0.99404544,0.004158848,0.000009067185,0.00002664104,0.00027210522],"about_ca_topic_score_codex":0.00013701788,"about_ca_topic_score_gemma":0.00042033935,"teacher_disagreement_score":0.6346511,"about_ca_system_score_codex":0.000071110546,"about_ca_system_score_gemma":0.000012346902,"threshold_uncertainty_score":0.84819233},"labels":[],"label_agreement":null},{"id":"W1980330432","doi":"10.1109/icc.2014.6883564","title":"Scheduling and resource allocation for wireless dynamic adaptive streaming of scalable videos over HTTP","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":22,"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":"Dynamic Adaptive Streaming over HTTP; Computer science; Dash; Computer network; Scalability; Wireless; Scheduling (production processes); WiMAX; Wireless broadband; Quality of experience; Resource allocation; Wireless network; Video streaming; Real-time computing; Quality of service; Telecommunications","score_opus":0.005215771890769126,"score_gpt":0.20839173964571273,"score_spread":0.2031759677549436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980330432","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":[0.22848552,0.000092281116,0.7704932,0.000010449164,0.000032132997,0.0001737112,0.000002354083,0.00011688194,0.0005934672],"genre_scores_gemma":[0.895168,0.000038079845,0.1045863,0.000011867346,0.000032074546,0.000022237351,0.000020279338,0.000036302503,0.00008487372],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941045,0.000012273316,0.00018857609,0.00015116803,0.00007744045,0.00016006384],"domain_scores_gemma":[0.99957335,0.00015897832,0.00005056578,0.00012875132,0.000051279116,0.00003707798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010808708,0.00011054297,0.00015370174,0.000058653306,0.000044789795,0.000012083153,0.00005223471,0.000067965135,0.0000049136675],"category_scores_gemma":[0.000026830628,0.00011711328,0.00002141115,0.00011545683,0.000026637514,0.00017513118,0.000018145467,0.00005740752,7.307112e-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":[0.000014470629,0.000005818638,0.00012478011,0.00006859508,0.000015202966,3.2765726e-8,0.00006701084,0.96001273,0.005851384,0.0035750733,0.000017039734,0.03024785],"study_design_scores_gemma":[0.0003646057,0.00003272939,0.00034725506,0.00008360534,0.000013091116,4.682366e-7,0.0001006782,0.9940228,0.0044617965,0.00030678444,0.00014117369,0.00012502476],"about_ca_topic_score_codex":0.0000071535073,"about_ca_topic_score_gemma":0.000026156758,"teacher_disagreement_score":0.6666825,"about_ca_system_score_codex":0.000044954788,"about_ca_system_score_gemma":0.000004739485,"threshold_uncertainty_score":0.4775741},"labels":[],"label_agreement":null},{"id":"W1980494204","doi":"10.1109/pimrc.2013.6666411","title":"Fast optimal energy-efficient resource allocation for downlink multi-user OFDM systems","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Subcarrier; Transmitter power output; Orthogonal frequency-division multiplexing; Telecommunications link; Computer science; Base station; Spectral efficiency; Resource allocation; Multiplexing; User equipment; Mathematical optimization; Efficient energy use; Resource management (computing); Power (physics); Electronic engineering; Channel (broadcasting); Real-time computing; Computer network; Telecommunications; Mathematics; Engineering; Electrical engineering; Transmitter","score_opus":0.007530503358708762,"score_gpt":0.19949701588591925,"score_spread":0.1919665125272105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980494204","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":[0.0049180863,0.0002508171,0.9920502,0.000036381683,0.00027796085,0.0005475404,0.0000054829616,0.0006033099,0.0013102364],"genre_scores_gemma":[0.8447507,0.000036968915,0.14715277,0.000055999302,0.00027717082,0.0007136406,0.00016573623,0.00010216453,0.0067448253],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990919,0.000014957022,0.00027414365,0.00020501074,0.00012031776,0.0002936372],"domain_scores_gemma":[0.99944633,0.000059555223,0.000042879146,0.0002377676,0.00013291434,0.00008058017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006542611,0.00016845227,0.00015104553,0.00007239058,0.000068753696,0.00007089546,0.00012144432,0.00010554239,0.00003712131],"category_scores_gemma":[0.000012959069,0.00015997008,0.00004286162,0.00015361757,0.000016911936,0.00016219528,0.000021883347,0.000062801795,0.000048483824],"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":[0.0000032161797,0.00002160483,0.000007632285,0.000038916198,0.000015918897,1.2632115e-7,0.00006353342,0.98955756,0.0011303497,0.0026569555,0.0036760485,0.0028281193],"study_design_scores_gemma":[0.0003909971,0.000015772317,0.00003437672,0.000024344374,0.0000075405787,0.0000015040159,0.00016315492,0.9771789,0.0014507724,0.0000023076577,0.020532286,0.00019804537],"about_ca_topic_score_codex":0.000030510291,"about_ca_topic_score_gemma":0.000004431649,"teacher_disagreement_score":0.84489745,"about_ca_system_score_codex":0.00009984639,"about_ca_system_score_gemma":0.0000063409375,"threshold_uncertainty_score":0.65233904},"labels":[],"label_agreement":null},{"id":"W1980870358","doi":"10.1007/s11277-006-9059-0","title":"Medium Access Control for Integrated Multimedia Wireless Access with the Use of a Video Packet Discard Scheme","year":2006,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Computer network; Quality of service; Network packet; Wireless network; Throughput; Wireless; Telecommunications","score_opus":0.04151579013070823,"score_gpt":0.281075533800077,"score_spread":0.23955974366936877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980870358","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":[0.18726076,0.0007268423,0.8051381,0.0030823473,0.00015829479,0.0019681812,0.0008600601,0.00053251674,0.00027290278],"genre_scores_gemma":[0.97932154,0.00034611006,0.018050412,0.000113539616,0.00011091653,0.0009578316,0.0008878179,0.00011946264,0.00009237978],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983228,0.00014126881,0.0005030096,0.0002783033,0.0003329243,0.00042169384],"domain_scores_gemma":[0.99638414,0.0014860202,0.0002532505,0.0012586308,0.0005296701,0.000088267356],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018646863,0.00035900803,0.000466677,0.00014014948,0.00032117817,0.00023008145,0.0018407949,0.00014897858,0.00001513414],"category_scores_gemma":[0.000045792334,0.00026929658,0.00013665989,0.00077912887,0.00059284567,0.0010708651,0.00022393277,0.00044770964,0.000002448516],"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":[0.0006212582,0.0005449823,0.017637312,0.00034443077,0.00079923595,0.0000030301255,0.0016487195,0.9243932,0.009708936,0.0053905924,0.02270139,0.016206931],"study_design_scores_gemma":[0.0014568822,0.000032303353,0.003152665,0.00015983777,0.000107526306,0.0000043269097,0.00021541996,0.9869056,0.0009954299,0.000060686085,0.0065454324,0.00036392285],"about_ca_topic_score_codex":0.00032967937,"about_ca_topic_score_gemma":0.0025264006,"teacher_disagreement_score":0.7920608,"about_ca_system_score_codex":0.0001307474,"about_ca_system_score_gemma":0.0000985879,"threshold_uncertainty_score":0.9999759},"labels":[],"label_agreement":null},{"id":"W1981773217","doi":"10.1109/tvt.2014.2351837","title":"Toward Optimal Admission Control and Resource Allocation for LTE-A Femtocell Uplink","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":41,"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":"Femtocell; Computer science; Telecommunications link; Computer network; Scheduling (production processes); Throughput; 3rd Generation Partnership Project 2; Resource allocation; Base station; Greedy algorithm; Heuristic; User equipment; Quality of service; Admission control; Markov decision process; Mathematical optimization; Markov process; Wireless; Algorithm; Telecommunications; Mathematics","score_opus":0.00675562234346364,"score_gpt":0.2050324763139711,"score_spread":0.19827685397050746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981773217","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":[0.022138566,0.00016849942,0.9752022,0.00078063476,0.00015705303,0.00050774036,0.000006893853,0.0009823684,0.000056013243],"genre_scores_gemma":[0.96752316,0.0001118678,0.03188365,0.00007231171,0.000040055762,0.0002444651,0.000010057008,0.000061199185,0.000053240532],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913156,0.000019509476,0.00022118259,0.00028065947,0.00008274937,0.00026432364],"domain_scores_gemma":[0.9994738,0.000088201916,0.000040815336,0.00027064307,0.000057690922,0.00006882022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000104589795,0.00019187626,0.00021670441,0.0002658626,0.00013879445,0.000015955096,0.00011992497,0.00036702192,0.0000068874574],"category_scores_gemma":[0.000012698542,0.00020620778,0.000055356013,0.0002590949,0.000068754045,0.000086193926,0.0000010643844,0.00027820672,0.000008428451],"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":[0.00004029649,0.000025377394,0.0000031444793,0.00003738138,0.000028747763,6.8330917e-7,0.000023793544,0.9205801,0.010465275,0.00036251967,0.00005987147,0.06837283],"study_design_scores_gemma":[0.0011320398,0.0001794174,0.000005062219,0.00003421177,0.000048123216,0.000013683269,0.000028678221,0.9334916,0.056901317,0.00029562344,0.0076664123,0.00020381725],"about_ca_topic_score_codex":7.456315e-7,"about_ca_topic_score_gemma":0.0000018426914,"teacher_disagreement_score":0.94538456,"about_ca_system_score_codex":0.00006037758,"about_ca_system_score_gemma":0.000008195233,"threshold_uncertainty_score":0.84089094},"labels":[],"label_agreement":null},{"id":"W1981954312","doi":"10.1109/icc.2006.255544","title":"Joint Bandwidth Allocation and Connection Admission Control for Polling Services in IEEE 802.16 Broadband Wireless Networks","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Polling; Computer science; Computer network; Wireless broadband; Bandwidth allocation; Admission control; Link adaptation; IEEE 802; Network packet; Queueing theory; Bandwidth (computing); Wireless network; Wireless; Quality of service; Telecommunications; Channel (broadcasting); Fading","score_opus":0.02831310386250166,"score_gpt":0.2732424491771529,"score_spread":0.24492934531465124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981954312","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":[0.062093094,0.000500315,0.93008244,0.0011016574,0.0007243308,0.0007274305,0.000080081074,0.00024365532,0.004446993],"genre_scores_gemma":[0.99414015,0.0016073942,0.002984847,0.000114442955,0.00021359327,0.00025782397,0.0005061352,0.00004177815,0.00013386272],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878025,0.000066049346,0.0004980411,0.0002523204,0.00017036895,0.00023299111],"domain_scores_gemma":[0.99884236,0.00022638886,0.00015716141,0.000436921,0.00027671797,0.0000604271],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019732137,0.00021904355,0.00022466393,0.00023288695,0.0001852295,0.000118751355,0.00038655012,0.00014921099,0.000022372771],"category_scores_gemma":[0.000012688976,0.00024550388,0.000046988487,0.00018758843,0.000064454325,0.00034695605,0.000025962292,0.0002605421,0.000004377219],"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":[0.000060739687,0.00009133159,0.00076305616,0.000028205784,0.000030507623,3.1230164e-7,0.00006263853,0.9606315,0.0052534747,0.025585506,0.00028405807,0.007208677],"study_design_scores_gemma":[0.0012158093,0.000033502754,0.0015811928,0.00026518805,0.000015699467,0.0000033369377,0.00007203608,0.9920203,0.0013669349,0.0023830584,0.0008045358,0.00023841305],"about_ca_topic_score_codex":0.00018451971,"about_ca_topic_score_gemma":0.0015016317,"teacher_disagreement_score":0.932047,"about_ca_system_score_codex":0.00024275742,"about_ca_system_score_gemma":0.000028584214,"threshold_uncertainty_score":0.9999997},"labels":[],"label_agreement":null},{"id":"W1982586504","doi":"10.1007/s11277-008-9448-7","title":"A Channel based Fair Scheduling Scheme for Downlink Data Transmission in TD-CDMA Networks","year":2008,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Scheduling (production processes); Maximum throughput scheduling; Telecommunications link; Throughput; Code division multiple access; Computer network; Fairness measure; Network packet; Channel (broadcasting); Proportionally fair; Data transmission; Wireless; Real-time computing; Dynamic priority scheduling; Round-robin scheduling; Telecommunications; Quality of service; Mathematical optimization","score_opus":0.07385997584558751,"score_gpt":0.2848493049720901,"score_spread":0.2109893291265026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982586504","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":[0.008720834,0.0031805495,0.985839,0.00078642037,0.000080814294,0.0005816219,0.00009855441,0.00041552624,0.00029664865],"genre_scores_gemma":[0.8038873,0.002587771,0.19103627,0.00009019699,0.00009448574,0.00021389,0.0019924217,0.00007744867,0.000020228958],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985682,0.000070635644,0.00042513807,0.0003401674,0.00017610072,0.0004197809],"domain_scores_gemma":[0.99779177,0.00039100522,0.00007198686,0.0015292166,0.0000978369,0.000118212345],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025057263,0.0002552255,0.00029469188,0.00016530501,0.00045791036,0.000026371397,0.0013620697,0.00019388995,0.0000144466385],"category_scores_gemma":[0.000024035382,0.00029503656,0.00007736649,0.0005824326,0.00014871097,0.0004330104,0.00017094535,0.0005352012,0.000006544584],"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":[0.000031678625,0.000099121266,0.00017905231,0.00005118862,0.000024138395,0.000001692855,0.00047672202,0.9911623,0.00031753923,0.00023485151,0.0002868931,0.0071348287],"study_design_scores_gemma":[0.0009253842,0.000014621733,0.00025314692,0.00018841535,0.000014511277,0.0000059969966,0.00012345487,0.9938905,0.000057244095,0.000033706583,0.0041708443,0.0003221641],"about_ca_topic_score_codex":0.000017381135,"about_ca_topic_score_gemma":0.00009789568,"teacher_disagreement_score":0.79516643,"about_ca_system_score_codex":0.00013315464,"about_ca_system_score_gemma":0.000080819584,"threshold_uncertainty_score":0.9999502},"labels":[],"label_agreement":null},{"id":"W1984252660","doi":"10.1007/s11277-014-1615-4","title":"Variable Cyclic Prefix for Contention-Based Wireless Access in OFDM-Based Vehicular Communication Systems","year":2014,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Handshaking; Computer science; Cyclic prefix; Computer network; Multipath propagation; Network packet; Wireless; Carrier sense multiple access with collision avoidance; Orthogonal frequency-division multiplexing; Transmission (telecommunications); Fading; Real-time computing; Telecommunications; Channel (broadcasting); Throughput","score_opus":0.02650479128932431,"score_gpt":0.2684424663623827,"score_spread":0.2419376750730584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984252660","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":[0.05870498,0.001487204,0.9343256,0.00073919835,0.00024200708,0.0017035035,0.00012745099,0.00072228786,0.0019477821],"genre_scores_gemma":[0.96897393,0.00023186262,0.02673606,0.00016619284,0.00005691933,0.0020343636,0.0016109429,0.00013023132,0.00005952],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977022,0.00042031365,0.00073272205,0.00035438917,0.000298118,0.0004922688],"domain_scores_gemma":[0.99577916,0.0014348094,0.0002343411,0.0020588005,0.00036389925,0.00012900578],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000703275,0.00036054922,0.00050501985,0.0003204891,0.00041475566,0.00021569339,0.0018094007,0.00025979796,0.00001040811],"category_scores_gemma":[0.00009485717,0.00042765005,0.00013595405,0.0008416764,0.00021626987,0.0005113183,0.00014866394,0.00050177437,0.000010534344],"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":[0.000035733385,0.0001827248,0.001774723,0.00024513426,0.000040344046,1.822908e-7,0.000117591946,0.96890676,0.001293094,0.025422052,0.00026276155,0.0017189082],"study_design_scores_gemma":[0.0017156388,0.000032648928,0.0007720039,0.000531326,0.00004466064,0.0000011919312,0.00011724529,0.991262,0.000274684,0.00034976786,0.004450607,0.0004482364],"about_ca_topic_score_codex":0.00021198747,"about_ca_topic_score_gemma":0.00049327745,"teacher_disagreement_score":0.9102689,"about_ca_system_score_codex":0.00038635943,"about_ca_system_score_gemma":0.00010765196,"threshold_uncertainty_score":0.99981755},"labels":[],"label_agreement":null},{"id":"W1988259170","doi":"10.1155/asp/2006/65716","title":"Fine-Granularity Loading Schemes Using Adaptive Reed-Solomon Coding for xDSL-DMT Systems","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"McGill University","keywords":"Granularity; Digital subscriber line; Computer science; Coding (social sciences); Algorithm; Link adaptation; Real-time computing; Mathematics; Decoding methods; Telecommunications; Statistics","score_opus":0.019299380121759448,"score_gpt":0.2697997941663114,"score_spread":0.2505004140445519,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988259170","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":[0.039735276,0.018952211,0.9393174,0.000012217755,0.00059936475,0.00037087715,0.000008635051,0.00020614275,0.0007978616],"genre_scores_gemma":[0.94310313,0.00028155302,0.055489082,0.000015497235,0.00094565284,0.000023056064,0.000010823207,0.00010958796,0.000021626061],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975938,0.000075286414,0.00087690627,0.00036013802,0.00041017946,0.00068366487],"domain_scores_gemma":[0.998866,0.0002492,0.00043159767,0.000118284894,0.0002282757,0.00010659578],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005155423,0.00040430718,0.00050041435,0.00036756985,0.00047043708,0.00026783513,0.0002449543,0.00014774567,0.0000056743306],"category_scores_gemma":[0.00005874612,0.00041144568,0.00010551282,0.00062875554,0.00007240064,0.0020019168,0.000023530969,0.0007344169,0.0000019583817],"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":[0.00013830842,0.000035804005,0.0009713202,0.00022946164,0.00001091186,0.00003875071,0.000067296736,0.967418,0.007257559,0.00052602147,0.000019953986,0.023286622],"study_design_scores_gemma":[0.0010354473,0.000102547354,0.000044247914,0.0022373283,0.000024577028,0.00013789398,0.00018788164,0.9873023,0.005818711,0.0016780422,0.0009320639,0.00049898506],"about_ca_topic_score_codex":0.0000034602845,"about_ca_topic_score_gemma":0.000013528671,"teacher_disagreement_score":0.9033678,"about_ca_system_score_codex":0.00058330654,"about_ca_system_score_gemma":0.00005327237,"threshold_uncertainty_score":0.99983376},"labels":[],"label_agreement":null},{"id":"W1988394897","doi":"10.1109/wcnc.2013.6554664","title":"Resource allocation in a K-user wireless broadcast system with N-layer superposition coding","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"","keywords":"Computer science; Computational complexity theory; Wireless; Fading; Resource allocation; Coding (social sciences); Maximization; Mathematical optimization; Physical layer; Channel (broadcasting); Throughput; Algorithm; Computer network; Mathematics; Telecommunications; Statistics","score_opus":0.0055288571721056065,"score_gpt":0.17967187083980968,"score_spread":0.17414301366770407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988394897","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":[0.3609754,0.000041885887,0.63184303,0.000044254673,0.00004633658,0.00040306826,6.095699e-7,0.00054276735,0.006102668],"genre_scores_gemma":[0.99276865,0.000019850902,0.0067078015,0.000027925755,0.000056839843,0.00015077864,0.000033193468,0.00005518419,0.0001797676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921405,0.000024931625,0.00021554514,0.00017327606,0.0001355047,0.0002366599],"domain_scores_gemma":[0.9996624,0.000030933425,0.00002580649,0.00017540326,0.000053534615,0.00005193183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005862448,0.00014700693,0.00014393473,0.000113199654,0.000040881572,0.000052322466,0.00007569319,0.00007808345,0.000038344486],"category_scores_gemma":[0.0000019469087,0.00013449366,0.000013849973,0.00034165228,0.000014798218,0.00048219212,0.000012692486,0.00011548192,0.000070081514],"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":[0.000008258227,0.000010040573,0.0010372803,0.000077506804,0.00000903756,0.0000027818899,0.00018682689,0.98733455,0.004773219,0.0028064924,0.00031384642,0.0034401838],"study_design_scores_gemma":[0.00040235222,0.00001829582,0.0013992622,0.00023957461,0.000004812313,0.000014062701,0.00058163627,0.9943954,0.002536614,0.0000041970093,0.0002014682,0.00020234898],"about_ca_topic_score_codex":0.00006764304,"about_ca_topic_score_gemma":0.000056691417,"teacher_disagreement_score":0.63179326,"about_ca_system_score_codex":0.0002296582,"about_ca_system_score_gemma":0.000005927824,"threshold_uncertainty_score":0.5484493},"labels":[],"label_agreement":null},{"id":"W1989255300","doi":"10.1145/2487166.2487205","title":"Efficient demand assignment in multi-connected microgrids","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Distributed computing; Grid; Distributed generation; Generator (circuit theory); Set (abstract data type); Microgrid; Resource (disambiguation); Distributed power generation; Duration (music); On demand; Demand response; Electricity generation; Power (physics); Computer network; Engineering; Renewable energy; Electrical engineering; Control (management); Electricity; Mathematics","score_opus":0.007163071033707756,"score_gpt":0.19880192909898448,"score_spread":0.19163885806527672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989255300","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":[0.29513827,0.00015247084,0.7033348,0.000021827407,0.00010535788,0.00024894395,4.08031e-7,0.0002466723,0.0007512223],"genre_scores_gemma":[0.95972896,0.000024650873,0.04001314,0.00002979754,0.00001561582,0.00006246651,0.000005707511,0.000022184891,0.00009750219],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945784,0.00001068784,0.00015777313,0.00011015139,0.00005956353,0.00020400438],"domain_scores_gemma":[0.9997948,0.000026602613,0.000011074463,0.0001067108,0.000018087168,0.00004275804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000034644367,0.000095969226,0.00009205696,0.000061063285,0.00001505852,0.00001686905,0.000053023912,0.00004772253,0.00023268061],"category_scores_gemma":[0.000006692715,0.000090281144,0.000014810323,0.00017186743,0.000009946313,0.000042319854,0.000015320473,0.00007025085,0.00013094411],"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":[6.103012e-7,0.000029756271,0.0006238812,0.0000064199676,0.000004306483,9.022047e-7,0.000058127316,0.98965055,0.006833876,0.000027625378,0.0003198622,0.0024440838],"study_design_scores_gemma":[0.00041977785,0.000005469797,0.004508225,0.00001342187,0.0000013633619,7.2451735e-7,0.000033510023,0.9898216,0.0049639503,0.000010414392,0.000103619415,0.00011790185],"about_ca_topic_score_codex":0.000013861194,"about_ca_topic_score_gemma":0.000019785593,"teacher_disagreement_score":0.66459066,"about_ca_system_score_codex":0.00008749127,"about_ca_system_score_gemma":0.0000026513956,"threshold_uncertainty_score":0.3681558},"labels":[],"label_agreement":null},{"id":"W1989377671","doi":"10.1109/ita.2010.5454108","title":"Delay performance of CSMA policies in multihop wireless networks: A new perspective","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","funders":"","keywords":"Computer network; Computer science; Carrier sense multiple access with collision avoidance; Network packet; Wireless network; Interference (communication); Throughput; Wireless; Channel (broadcasting); Transmission delay; Propagation delay; Exponential backoff; Distributed computing; Telecommunications","score_opus":0.004490342186270684,"score_gpt":0.21280471724692218,"score_spread":0.2083143750606515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989377671","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":[0.86372536,0.00012285788,0.13030528,0.000029682651,0.00026265404,0.00015041877,9.678396e-7,0.00019185932,0.0052109053],"genre_scores_gemma":[0.98564565,0.00028648865,0.013671209,0.000017712911,0.00015893765,0.000009410566,0.0000037097575,0.000036299658,0.00017059727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992942,0.000007021124,0.00022227151,0.00013051607,0.000089188754,0.00025675917],"domain_scores_gemma":[0.99960446,0.00004744563,0.000035814424,0.00019018796,0.000060771075,0.00006131651],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052865274,0.00014080913,0.0001825576,0.00011588156,0.000021341186,0.000009301033,0.00012918258,0.000105672596,0.000040730803],"category_scores_gemma":[0.000013248875,0.0001408093,0.000029581779,0.00041171446,0.000044487944,0.00023331467,0.000025865435,0.00027894892,0.000005058793],"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":[0.000011941078,0.000012573819,0.0055377996,0.000010459141,0.000008620389,7.305321e-7,0.00062628096,0.9824837,0.0013958041,0.002355106,0.00009076787,0.0074662445],"study_design_scores_gemma":[0.00034570746,0.000020332118,0.004847213,0.000023851713,0.0000033601373,0.0000035679532,0.00021618609,0.9916018,0.0026384646,0.000052283183,0.00008947113,0.00015776063],"about_ca_topic_score_codex":0.00022730902,"about_ca_topic_score_gemma":0.00086432346,"teacher_disagreement_score":0.12192025,"about_ca_system_score_codex":0.000060758186,"about_ca_system_score_gemma":0.000019461238,"threshold_uncertainty_score":0.5742036},"labels":[],"label_agreement":null},{"id":"W1989501077","doi":"10.1109/pimrc.2008.4699808","title":"QoS-based optimal logarithmic-time uplink scheduling algorithm for packets with hard or soft deadlines in WiMAX","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Nortel (Canada); Queen's University","funders":"","keywords":"Computer science; Network packet; Telecommunications link; Logarithm; WiMAX; Scheduling (production processes); Quality of service; Mathematical optimization; Algorithm; Distributed computing; Computer network; Wireless; Mathematics; Telecommunications","score_opus":0.015941823408634637,"score_gpt":0.22272371240404243,"score_spread":0.20678188899540778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989501077","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":[0.03235012,0.00012097229,0.96604484,0.00006352997,0.00012991275,0.0005233604,0.0000121732155,0.000659539,0.00009556259],"genre_scores_gemma":[0.044209037,0.00005586835,0.95460457,0.00008878706,0.00025073363,0.00013321349,0.00011653754,0.00012715964,0.0004141015],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986735,0.000011461015,0.00033852656,0.0003313068,0.00015256723,0.0004926117],"domain_scores_gemma":[0.99932396,0.0001822075,0.000050355986,0.00022670186,0.00011907168,0.00009767917],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000093602124,0.00030260303,0.0003459151,0.00016538944,0.00009990685,0.000024834253,0.00014504514,0.00015192598,0.00007586244],"category_scores_gemma":[0.000032811105,0.00025520963,0.000053052663,0.00040864514,0.00006302988,0.0003003734,0.000018127103,0.00018324374,0.000025032727],"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":[0.000091195085,0.000036097448,0.00028299767,0.000032787873,0.000022309327,0.000034950954,0.000036349804,0.98057973,0.00017243947,0.000012166109,0.00023377815,0.018465223],"study_design_scores_gemma":[0.0019756255,0.00011497502,0.00012788876,0.000079500474,0.000013078146,0.000028190329,0.000016647138,0.993936,0.0029841296,0.000012044352,0.00031744485,0.00039444736],"about_ca_topic_score_codex":0.000004105494,"about_ca_topic_score_gemma":0.000019622863,"teacher_disagreement_score":0.018070776,"about_ca_system_score_codex":0.000113709684,"about_ca_system_score_gemma":0.000080495076,"threshold_uncertainty_score":0.99999},"labels":[],"label_agreement":null},{"id":"W1990395834","doi":"10.1109/iwqos.2007.376551","title":"On the Stability Region of Linear-Memory Scheduling for Time Varying Channels","year":2007,"lang":"en","type":"article","venue":"International Workshop on Quality of Service","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Computer science; Scheduling (production processes); Fair-share scheduling; Dynamic priority scheduling; Mathematical optimization; Processor scheduling; Two-level scheduling; Distributed computing; Rate-monotonic scheduling; Round-robin scheduling; Time complexity; Parallel computing; Algorithm; Resource (disambiguation); Computer network; Mathematics; Quality of service","score_opus":0.05453556149124307,"score_gpt":0.3143575415357443,"score_spread":0.25982198004450124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990395834","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":[0.48372787,0.000033778964,0.5121498,0.0014585153,0.0004842134,0.0003300006,0.000018198287,0.00008794867,0.0017096861],"genre_scores_gemma":[0.9916992,0.000013660943,0.007420037,0.0004975319,0.00021987864,0.000015353535,0.000048947622,0.000030171363,0.000055179404],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869555,0.00004167987,0.0005661405,0.00018305166,0.00034366478,0.00016991432],"domain_scores_gemma":[0.99664026,0.0024302343,0.00021954697,0.0002825829,0.00039228273,0.00003510469],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010525176,0.00013971727,0.00020467448,0.00008591708,0.000054892036,0.000009167708,0.00031340282,0.00009804025,0.00005704858],"category_scores_gemma":[0.00035744844,0.00012664498,0.00008552968,0.00025387696,0.000033940745,0.00012213652,0.000034263252,0.00017772632,0.000008789817],"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":[0.00033403133,0.000068749505,0.000027615255,0.000112251735,0.00005446677,3.2156234e-7,0.00047153342,0.98803836,0.0028420417,0.0054560406,0.00004346785,0.0025511119],"study_design_scores_gemma":[0.0005457013,0.00003276845,0.00028387317,0.00045973537,0.0000084982175,8.2756287e-7,0.00031699662,0.96500856,0.029364925,0.0036991788,0.00009266819,0.000186294],"about_ca_topic_score_codex":0.0000129765895,"about_ca_topic_score_gemma":0.000014807596,"teacher_disagreement_score":0.5079714,"about_ca_system_score_codex":0.000100675476,"about_ca_system_score_gemma":0.000010620628,"threshold_uncertainty_score":0.51644325},"labels":[],"label_agreement":null},{"id":"W1991080284","doi":"10.1109/glocom.2014.7036971","title":"Resource pooling in network virtualization and heterogeneous scenarios using Stochastic Petri nets","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Pooling; Computer science; Provisioning; Stochastic Petri net; Virtualization; Distributed computing; Resource (disambiguation); Resource allocation; Petri net; Blocking (statistics); Wireless network; Markov process; Heterogeneous network; Computer network; Wireless; Artificial intelligence","score_opus":0.0070208361642243745,"score_gpt":0.20060857767405077,"score_spread":0.19358774150982638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991080284","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":[0.15259026,0.000307714,0.8464319,0.0000064058577,0.00010532241,0.00012181226,2.7423363e-7,0.00019835422,0.00023796322],"genre_scores_gemma":[0.9838588,0.000026781949,0.015775096,0.00007548042,0.0001774511,0.0000042141805,0.000011500045,0.000052615014,0.000018015822],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999194,0.000036591042,0.00022277187,0.00017545791,0.00009241404,0.0002787389],"domain_scores_gemma":[0.99966294,0.00009908149,0.000032636617,0.00012978929,0.000016560443,0.000058967576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012118127,0.00014002272,0.00015475777,0.00009644588,0.000063161744,0.000033766042,0.000053187276,0.000079588615,0.000012430371],"category_scores_gemma":[0.000039903687,0.0001580522,0.000013983183,0.00031560744,0.000017115652,0.000120591125,0.000030789073,0.00009913118,0.0000022833106],"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":[0.0000056375447,0.000003449706,0.00033470485,0.000011038216,0.0000043126633,0.000001183747,0.00007129438,0.9948797,0.00012546674,0.00016495508,0.000019198465,0.0043790597],"study_design_scores_gemma":[0.00025087796,0.000014717561,0.00010243952,0.00007539663,0.0000060680054,0.000013129306,0.000012346454,0.9989583,0.000048720918,0.00010788552,0.00023740248,0.0001727191],"about_ca_topic_score_codex":0.0000072708317,"about_ca_topic_score_gemma":0.000039963037,"teacher_disagreement_score":0.8312686,"about_ca_system_score_codex":0.00006761793,"about_ca_system_score_gemma":0.0000038657768,"threshold_uncertainty_score":0.64451814},"labels":[],"label_agreement":null},{"id":"W1991640524","doi":"10.1002/dac.1209","title":"On the design of algorithms for mobile multimedia systems: A survey","year":2011,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Computer science; Computer network; Wireless broadband; WiMAX; Multimedia; Quality of service; The Internet; Wireless; Multicast; Bandwidth (computing); IMT Advanced; Mobile broadband; IP Multimedia Subsystem; Mobile QoS; Telecommunications; Multimedia Broadcast Multicast Service; Broadband networks; Wireless network; Internet access; Broadband; Service provider; Service (business); Mobile computing; Mobile technology; Mobile Web; World Wide Web","score_opus":0.08563129976662025,"score_gpt":0.29289976787738947,"score_spread":0.2072684681107692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991640524","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":[0.004159632,0.0025172818,0.990923,0.00001868608,0.0014680669,0.0005748717,0.000043355056,0.000027124768,0.00026801616],"genre_scores_gemma":[0.9835828,0.00082504033,0.015303045,0.0000075303565,0.0000990054,0.00010831932,0.000021638552,0.000027255473,0.000025362073],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984595,0.0003387841,0.00072743156,0.000053629785,0.00033374052,0.0000869237],"domain_scores_gemma":[0.99601346,0.0017955253,0.00059152226,0.00032748346,0.0012386275,0.000033399963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001478203,0.0001016048,0.00021336829,0.00014370274,0.000035648827,0.00003346354,0.00089331827,0.000058242513,0.000009533444],"category_scores_gemma":[0.00021159307,0.00007603076,0.00006347746,0.00010828532,0.0000429596,0.00017993257,0.000027450513,0.00014250363,0.000003847696],"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":[0.000088838344,0.00004686196,0.000101050035,0.0000075602447,0.00018504856,4.881964e-7,0.000621104,0.9949024,0.000094288305,0.0018068274,0.0009993049,0.0011462349],"study_design_scores_gemma":[0.00045519532,0.000095332696,0.00031019526,0.0003041971,0.000012208169,0.000016574237,0.00035287472,0.9970137,0.00040355005,0.00019400149,0.00076046295,0.00008173016],"about_ca_topic_score_codex":0.000037339596,"about_ca_topic_score_gemma":0.0000024898336,"teacher_disagreement_score":0.97942317,"about_ca_system_score_codex":0.0001040196,"about_ca_system_score_gemma":0.000027951006,"threshold_uncertainty_score":0.31004444},"labels":[],"label_agreement":null},{"id":"W1991750576","doi":"10.1016/j.mcm.2010.08.008","title":"Mobile WiMAX MAC and PHY layer optimization for IPTV","year":2010,"lang":"en","type":"article","venue":"Mathematical and Computer Modelling","topic":"Advanced Wireless Network Optimization","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":"Simon Fraser University","funders":"","keywords":"WiMAX; Computer network; Computer science; Mobile broadband; Wireless broadband; IMT Advanced; Retransmission; IPTV; Network packet; Telecommunications; Wireless network; Wireless; Mobile computing; Mobile technology; Mobile Web","score_opus":0.010684187523548765,"score_gpt":0.20431869285918894,"score_spread":0.19363450533564017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991750576","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":[0.036110036,0.000099499215,0.96318775,0.000007054182,0.00009454329,0.0002244426,0.0000020577322,0.00015060458,0.00012399346],"genre_scores_gemma":[0.29392463,0.00007048672,0.7057649,0.000019347532,0.00012794673,0.00004441132,0.0000056055624,0.000025033884,0.000017663177],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99952084,0.0000033154483,0.00014606892,0.00013875654,0.000051942243,0.00013909955],"domain_scores_gemma":[0.9997482,0.000064243904,0.00001638331,0.00008836904,0.000025993431,0.000056840596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052272568,0.00010920322,0.00013696376,0.000027728103,0.000057736732,0.000051161835,0.00004027191,0.00006432112,0.00001220943],"category_scores_gemma":[0.0000015021739,0.00010096275,0.000019257774,0.00004195051,0.000023574401,0.00011526091,0.000024736799,0.00009209359,0.0000015462515],"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":[0.000002452808,0.000010815014,0.0000030398335,0.00011415017,0.000007030111,2.2065008e-7,0.00015847628,0.9817821,0.00006324795,0.009343225,0.000020383823,0.008494856],"study_design_scores_gemma":[0.00018073448,0.000021144486,3.4663813e-7,0.000024770927,0.000008588407,0.000005807271,0.0000043477817,0.98454386,0.00014555674,0.01471944,0.00022294982,0.0001224391],"about_ca_topic_score_codex":1.05027695e-7,"about_ca_topic_score_gemma":9.768257e-8,"teacher_disagreement_score":0.2578146,"about_ca_system_score_codex":0.0000039740735,"about_ca_system_score_gemma":0.000001561682,"threshold_uncertainty_score":0.41171417},"labels":[],"label_agreement":null},{"id":"W1992752766","doi":"10.1049/iet-com.2013.0128","title":"Multi‐objective resource allocation in multiuser orthogonal frequency division multiplexing system","year":2013,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Orthogonal frequency-division multiplexing; Computer science; Resource allocation; Division (mathematics); Frequency-division multiplexing; Multiplexing; Telecommunications; Orthogonal frequency-division multiple access; Computer network; Mathematics; Arithmetic","score_opus":0.01761153776532924,"score_gpt":0.24279195568721426,"score_spread":0.22518041792188503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992752766","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":[0.1203538,0.0014516946,0.86929816,0.00035706448,0.00019884476,0.0016174676,0.000028210348,0.0014445282,0.00525021],"genre_scores_gemma":[0.846553,0.00013298803,0.15254565,0.00002006463,0.000026309246,0.0004350365,0.00020675389,0.000053134194,0.000027019663],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987862,0.0001569716,0.00044040446,0.00020432568,0.00014288897,0.00026922143],"domain_scores_gemma":[0.9981972,0.00029190822,0.000084858926,0.0012127341,0.00014229452,0.00007102218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016450127,0.00019184488,0.0001866321,0.00018191052,0.00019677429,0.00004907748,0.0005727907,0.00012507799,0.000017036484],"category_scores_gemma":[0.000077816956,0.00020919077,0.00004660324,0.00043551423,0.00006836416,0.0005283846,0.00015743804,0.00036869463,0.00011835299],"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":[0.0000013196725,0.00006607605,0.0050357645,0.000030410345,0.000016670685,4.3419084e-7,0.0010357082,0.9821121,0.0046811504,0.0013602506,0.00008138849,0.0055787396],"study_design_scores_gemma":[0.00041362797,0.000006858896,0.042388946,0.00017211873,0.0000039962674,0.0000017806636,0.0006306024,0.9556608,0.00016859572,0.00008028719,0.0002609291,0.00021141751],"about_ca_topic_score_codex":0.00019672353,"about_ca_topic_score_gemma":0.0005409111,"teacher_disagreement_score":0.72619927,"about_ca_system_score_codex":0.00035936103,"about_ca_system_score_gemma":0.00001626892,"threshold_uncertainty_score":0.85305524},"labels":[],"label_agreement":null},{"id":"W1993039069","doi":"10.1109/aina.2010.76","title":"Increasing TCP Throughput and Fairness in Cognitive WLAN over Fiber","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Computer network; Throughput; Cognitive radio; Transmitter; Wi-Fi; Fairness measure; Wireless; Telecommunications; Wireless network","score_opus":0.005514620621334397,"score_gpt":0.22868154925706158,"score_spread":0.22316692863572718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993039069","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":[0.9158016,0.000045750447,0.066449806,0.000010048206,0.00011402656,0.00010486403,0.0000019518884,0.00014263284,0.017329313],"genre_scores_gemma":[0.9893072,0.000034858844,0.010368813,0.000031889274,0.00006247132,0.0000079000265,0.000008678736,0.000024362123,0.00015381377],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958044,0.0000096991425,0.00009979884,0.00011451505,0.00005291957,0.00014262654],"domain_scores_gemma":[0.9997652,0.000106097184,0.00001124314,0.0000660909,0.00001726848,0.000034073008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057561534,0.00009078723,0.00009394793,0.000044744967,0.00002096304,0.000019625162,0.000028571523,0.00007191778,0.0003628773],"category_scores_gemma":[0.000028818347,0.00009076562,0.00000868366,0.00012285344,0.00002824137,0.00022990495,0.000021831835,0.00017159224,0.000015453692],"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":[0.0001543382,0.00012116705,0.21282499,0.00019024737,0.00010434653,0.00006766269,0.0028089003,0.5569551,0.02696802,0.0071069915,0.0007864412,0.1919118],"study_design_scores_gemma":[0.0011965041,0.000012374837,0.078379884,0.000094934425,0.000011277194,0.000029112234,0.00015564081,0.91588503,0.0019645374,0.0009056868,0.00092584995,0.00043914476],"about_ca_topic_score_codex":0.000034842462,"about_ca_topic_score_gemma":0.00023487298,"teacher_disagreement_score":0.35892993,"about_ca_system_score_codex":0.000012878688,"about_ca_system_score_gemma":0.0000035496005,"threshold_uncertainty_score":0.39732522},"labels":[],"label_agreement":null},{"id":"W1993297616","doi":"10.1109/infcom.2010.5462013","title":"Practical Scheduling Algorithms for Concurrent Transmissions in Rate-adaptive Wireless Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Victoria","funders":"","keywords":"Computer science; Scheduling (production processes); Fair-share scheduling; Distributed computing; Dynamic priority scheduling; Job shop scheduling; Round-robin scheduling; Maximum throughput scheduling; Rate-monotonic scheduling; Computational complexity theory; Wireless network; Mathematical optimization; Wireless; Algorithm; Computer network; Mathematics; Quality of service","score_opus":0.02636296342750339,"score_gpt":0.297542455844979,"score_spread":0.27117949241747563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993297616","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":[0.0067804656,0.000057207908,0.9907875,0.00013843682,0.0010340625,0.00047303233,0.0000041909984,0.0002905125,0.00043458786],"genre_scores_gemma":[0.73050153,0.00010191856,0.26895678,0.000025427911,0.0001973119,0.00011283772,0.00002498007,0.00004736593,0.00003185836],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903065,0.000020830897,0.00027987317,0.0002187911,0.00007879839,0.00037107497],"domain_scores_gemma":[0.9992802,0.00036896334,0.000029961713,0.00013543223,0.000061511826,0.00012391875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018394714,0.00017806185,0.00020359637,0.000066238106,0.00006250404,0.000026458583,0.0000837012,0.00018329905,0.000055306205],"category_scores_gemma":[0.00004124392,0.0001736242,0.000050305516,0.00023779015,0.000038434147,0.00025859597,0.00001224292,0.0005541421,0.0000039262554],"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":[0.000014869903,0.000032094926,0.000031418185,0.000010756333,0.000011507338,0.0000026600842,0.00004554257,0.95939034,0.0009156537,0.008493043,0.00017255987,0.03087954],"study_design_scores_gemma":[0.0006649352,0.00002368614,0.0000631592,0.00003324149,0.000009781258,0.0000034748061,0.000063581356,0.9965787,0.0012530204,0.0001697467,0.0009120831,0.00022460583],"about_ca_topic_score_codex":0.0000029997625,"about_ca_topic_score_gemma":0.000088321336,"teacher_disagreement_score":0.723721,"about_ca_system_score_codex":0.00004079732,"about_ca_system_score_gemma":0.000028735909,"threshold_uncertainty_score":0.70801896},"labels":[],"label_agreement":null},{"id":"W1994178926","doi":"10.1016/j.compeleceng.2008.02.001","title":"A tabu search algorithm for the global planning problem of third generation mobile networks","year":2008,"lang":"en","type":"article","venue":"Computers & Electrical Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Carleton University","funders":"","keywords":"Tabu search; UMTS frequency bands; General Packet Radio Service; Base station; Computer science; Cellular network; Network packet; Core network; Network planning and design; Computer network; Radio access network; Mathematical optimization; Mobile telephony; Distributed computing; Algorithm; Mobile radio; Mathematics; Wireless; Telecommunications; Mobile station","score_opus":0.011788272224722549,"score_gpt":0.22125939685171814,"score_spread":0.20947112462699558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994178926","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":[0.0038455972,0.0032045592,0.9917341,0.0000066493535,0.00030088835,0.0005304935,0.000003541105,0.00035409105,0.000020115196],"genre_scores_gemma":[0.5856149,0.00039374683,0.41294017,0.000020129533,0.00074599567,0.00017922604,0.00004004794,0.000059257636,0.0000065162035],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989352,0.000011062587,0.00028193966,0.00018545309,0.00016720495,0.00041912013],"domain_scores_gemma":[0.9994606,0.0002091192,0.000033410233,0.00015666259,0.0000708277,0.00006940158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009852298,0.00018586229,0.00022809261,0.00006120407,0.00011057822,0.000019892545,0.00019834901,0.00009838669,9.152253e-7],"category_scores_gemma":[0.000006986969,0.0001705413,0.0000773801,0.00065978296,0.000021622509,0.0001132374,0.00003279275,0.00021879739,6.0302733e-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":[0.0000032541643,0.000009679619,0.00004073727,0.000015845719,0.000043174932,0.000002712843,0.00005766766,0.93163586,0.00021299276,0.00015605008,0.0005417004,0.06728035],"study_design_scores_gemma":[0.00027653325,0.000074138065,0.00010920754,0.000025646183,0.000012267137,0.000025808908,0.0000020418975,0.9982033,0.00048442162,0.000007070152,0.00060747133,0.00017211938],"about_ca_topic_score_codex":0.0000025639652,"about_ca_topic_score_gemma":2.1463968e-7,"teacher_disagreement_score":0.5817693,"about_ca_system_score_codex":0.0001706202,"about_ca_system_score_gemma":0.000019485127,"threshold_uncertainty_score":0.6954472},"labels":[],"label_agreement":null},{"id":"W1994228025","doi":"10.1109/glocom.2012.6503689","title":"Optimal bit and power loading for OFDM systems with average BER and total power constraints","year":2012,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Memorial University of Newfoundland","funders":"","keywords":"Orthogonal frequency-division multiplexing; Bit error rate; Fading; Bit (key); Computer science; Power (physics); Constraint (computer-aided design); Transmitter power output; Joint (building); Throughput; Algorithm; Electronic engineering; Mathematics; Telecommunications; Engineering; Wireless; Computer network; Decoding methods; Channel (broadcasting)","score_opus":0.00693378916516827,"score_gpt":0.20411702825556297,"score_spread":0.1971832390903947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994228025","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":[0.14074127,0.0015704654,0.8502784,0.000009883572,0.0006969915,0.00096838886,0.000069949856,0.00030147677,0.0053631756],"genre_scores_gemma":[0.95151764,0.00009496161,0.047645643,0.000009146057,0.00011042279,0.000099126824,0.000054799824,0.000105839754,0.00036242465],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885535,0.00001267228,0.00026432023,0.00035677815,0.00012502662,0.00038583518],"domain_scores_gemma":[0.9993951,0.0000845388,0.0000775639,0.0002236904,0.00006872895,0.00015038985],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011267893,0.00037139424,0.00040785607,0.00008954354,0.000057000856,0.00012452288,0.00006425049,0.0002930076,0.00007776326],"category_scores_gemma":[0.0000085453285,0.0003347561,0.000034969486,0.00004917741,0.000103308055,0.00020600585,0.00013419897,0.00029321102,0.0000027281496],"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":[0.000023020038,0.0000084832445,0.0003376168,0.0003095618,0.0001331679,0.000003751865,0.00027996025,0.99751765,0.000084117375,0.00081693655,0.00017187338,0.0003138741],"study_design_scores_gemma":[0.0011918697,0.000073283176,0.0004790131,0.0006480111,0.00009302637,0.00019926441,0.00027874048,0.9951513,0.0001974252,0.000031181145,0.00059407396,0.0010628535],"about_ca_topic_score_codex":0.0000039710485,"about_ca_topic_score_gemma":0.0000013538173,"teacher_disagreement_score":0.81077635,"about_ca_system_score_codex":0.00006947333,"about_ca_system_score_gemma":0.000016359783,"threshold_uncertainty_score":0.9999105},"labels":[],"label_agreement":null},{"id":"W1994983146","doi":"10.1109/glocom.2012.6503983","title":"Finite state Markov modelling for high speed railway wireless communication channel","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":50,"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":"Computer science; Wireless; Computer network; Channel (broadcasting); Markov chain; Handover; Fading; Markov model; Markov process; Path loss; Wireless network; Distributed computing; Key (lock); Mobility model; Telecommunications","score_opus":0.01851053679025434,"score_gpt":0.22186947856307407,"score_spread":0.20335894177281974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994983146","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":[0.018578196,0.0003953742,0.9786302,0.000041636653,0.00025856993,0.00035165573,0.000014457328,0.00045991075,0.0012700394],"genre_scores_gemma":[0.8920513,0.0007244764,0.106234774,0.000037681748,0.00011839682,0.00004614544,0.00017238049,0.000075043106,0.0005398079],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991675,0.00002027218,0.0002366134,0.00010704399,0.00008982024,0.00037874831],"domain_scores_gemma":[0.9992959,0.00019061632,0.00004712761,0.00031997674,0.00006455235,0.0000818306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001755901,0.00015811287,0.00016211321,0.000065150845,0.00009158623,0.000023530925,0.00014637536,0.000069731905,0.000028549592],"category_scores_gemma":[0.0000073737924,0.00016772325,0.000035622925,0.00015340655,0.00001844482,0.0004864374,0.000031691812,0.00010703406,0.000019899508],"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":[0.00001440833,0.000014889682,0.000016452612,0.00003335743,0.000018379978,7.940544e-8,0.00025126996,0.993348,0.00008814566,0.0013422297,0.00035933644,0.0045134244],"study_design_scores_gemma":[0.00036239446,0.0000074091495,0.000015749349,0.000025332465,0.000009678674,7.109085e-7,0.000035008878,0.9955671,0.0021125395,0.0010642923,0.00058643037,0.00021337743],"about_ca_topic_score_codex":0.000010121361,"about_ca_topic_score_gemma":0.000006157057,"teacher_disagreement_score":0.8734731,"about_ca_system_score_codex":0.00006629685,"about_ca_system_score_gemma":0.00000404108,"threshold_uncertainty_score":0.6839556},"labels":[],"label_agreement":null},{"id":"W1996440628","doi":"10.1007/s11277-006-9219-2","title":"Scheduling Algorithms and Throughput Maximization for the Downlink of Packet-Data Cellular Systems with Multiple Antennas at the Base Station","year":2006,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Base station; MIMO; Transmitter power output; Scheduling (production processes); Telecommunications link; Network packet; Spectral efficiency; Transmitter; Computer network; Algorithm; Channel (broadcasting); Mathematical optimization; Mathematics","score_opus":0.03419804185072944,"score_gpt":0.24795921617788172,"score_spread":0.21376117432715228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996440628","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":[0.053027887,0.009656528,0.9349381,0.000651241,0.00007092636,0.0009195297,0.0005363882,0.00011713454,0.000082287756],"genre_scores_gemma":[0.9669931,0.0016472331,0.029007621,0.000013593396,0.000071847644,0.00018296274,0.0019918971,0.00005136527,0.000040377625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896204,0.000101434045,0.00031445024,0.00020059006,0.00023323412,0.00018825047],"domain_scores_gemma":[0.99732345,0.000930403,0.00016250473,0.0012965583,0.00025964458,0.000027460412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040032525,0.0001673956,0.00017287485,0.00004135218,0.00065437553,0.000061413884,0.00060075737,0.00006605362,0.0000027986957],"category_scores_gemma":[0.000032750486,0.000113926944,0.00002966224,0.00028203355,0.00028904268,0.00027860576,0.00019386066,0.00016826845,0.0000011482902],"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":[0.000023289966,0.000032003936,0.0008637717,0.00007077979,0.00006278073,1.6327927e-7,0.00043570693,0.9924922,0.0013730433,0.0015847319,0.00013004792,0.0029314961],"study_design_scores_gemma":[0.0005657758,0.00001523739,0.0005458521,0.00007993022,0.000099278535,0.000005740223,0.0011628813,0.99622405,0.0003178734,0.00005215539,0.0007866547,0.0001445994],"about_ca_topic_score_codex":0.00017893958,"about_ca_topic_score_gemma":0.0008652671,"teacher_disagreement_score":0.9139652,"about_ca_system_score_codex":0.0000837731,"about_ca_system_score_gemma":0.000030209623,"threshold_uncertainty_score":0.50329936},"labels":[],"label_agreement":null},{"id":"W1996461238","doi":"10.1109/glocom.2008.ecp.119","title":"Vertical Handoff between 802.11 and 802.16 Wireless Access Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Bell (Canada); University of Waterloo","funders":"","keywords":"Handover; Computer network; Computer science; Quality of service; Wireless network; Overhead (engineering); Wireless; Scheme (mathematics); Telecommunications","score_opus":0.01677960411620442,"score_gpt":0.2292020925920033,"score_spread":0.2124224884757989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996461238","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":[0.36824927,0.00023666745,0.6285478,0.000029487665,0.00015547304,0.00013243112,0.0000016654637,0.00047670407,0.002170538],"genre_scores_gemma":[0.99645466,0.00073009444,0.002055151,0.00006700656,0.00040101758,0.000019187477,0.000037137776,0.0000681223,0.00016764611],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988868,0.00002128,0.00027066146,0.00025054096,0.00015457917,0.00041612316],"domain_scores_gemma":[0.99940896,0.00013378465,0.00001710181,0.00022323386,0.000038391627,0.00017853391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000054523876,0.00022354037,0.000289799,0.00006452011,0.0001075782,0.000051916377,0.00016522505,0.00016765909,0.00006356364],"category_scores_gemma":[0.000011254,0.00021820911,0.000037581878,0.0002890864,0.000099483506,0.00046124763,0.00009679871,0.00020279604,0.000011724639],"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":[0.0000106205325,0.000011970061,0.07758894,0.000020170124,0.000038002545,0.000013108009,0.00004112636,0.9091858,0.000035676818,0.0004042729,0.004101984,0.008548302],"study_design_scores_gemma":[0.00079843233,0.0000228892,0.025646802,0.00004196183,0.000028216295,0.000021947415,0.000008820571,0.9703965,0.0011847144,0.000103797145,0.0013034595,0.0004424672],"about_ca_topic_score_codex":0.000019255762,"about_ca_topic_score_gemma":0.000038007638,"teacher_disagreement_score":0.62820536,"about_ca_system_score_codex":0.00006609718,"about_ca_system_score_gemma":0.000009420714,"threshold_uncertainty_score":0.88983095},"labels":[],"label_agreement":null},{"id":"W1996776639","doi":"10.1016/j.peva.2009.02.004","title":"Packet delay analysis for multichannel communication systems with MSW-ARQ","year":2009,"lang":"en","type":"article","venue":"Performance Evaluation","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Transmission delay; Selective Repeat ARQ; Network packet; Automatic repeat request; Go-Back-N ARQ; Processing delay; Computer science; Hybrid automatic repeat request; Sliding window protocol; End-to-end delay; Real-time computing; Computer network; Algorithm; Transmission (telecommunications); Telecommunications","score_opus":0.020609232487367738,"score_gpt":0.26061504888820686,"score_spread":0.24000581640083912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996776639","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":[0.39085302,0.0005969161,0.60717213,0.000032890897,0.00007773399,0.0007404412,0.00000516469,0.00018886058,0.00033284342],"genre_scores_gemma":[0.98110133,0.00035793384,0.017549714,0.000016608688,0.00007327819,0.0002892601,0.0005647586,0.000022493134,0.00002463561],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990555,0.000041138275,0.00025531207,0.00015230048,0.00029717392,0.00019854156],"domain_scores_gemma":[0.9991176,0.00005292418,0.00009204137,0.00035706465,0.00034278992,0.000037589718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055465446,0.00014211824,0.00018431943,0.0001879716,0.00014227741,0.000042348674,0.00011436543,0.00006631446,0.000010118184],"category_scores_gemma":[0.00002144628,0.00013351615,0.00003906772,0.00069017196,0.000014745247,0.0005023578,0.0000051021575,0.00007919031,0.000007676175],"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":[0.000028039427,0.000012914401,0.0009924374,0.000017813427,0.00008833642,3.3022832e-8,0.00023736968,0.9777355,0.00006226715,0.00004858753,0.00007473839,0.020701963],"study_design_scores_gemma":[0.0006055515,0.000084377585,0.010816841,0.000044484474,0.0003515925,0.0000011255116,0.00005456433,0.98743176,0.0002971375,0.0000313038,0.00010480055,0.00017643323],"about_ca_topic_score_codex":0.0000023215252,"about_ca_topic_score_gemma":0.000015603006,"teacher_disagreement_score":0.5902483,"about_ca_system_score_codex":0.0001854574,"about_ca_system_score_gemma":0.000016508764,"threshold_uncertainty_score":0.5444631},"labels":[],"label_agreement":null},{"id":"W1996894843","doi":"10.1504/ijcnds.2008.021077","title":"Strategies for fast scanning, ranging and handovers in WiMAX/802.16","year":2008,"lang":"en","type":"article","venue":"International Journal of Communication Networks and Distributed Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":14,"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; Mitacs","keywords":"Computer science; Ranging; WiMAX; Handover; Computer network; Base station; Offset (computer science); Real-time computing; Mobile station; Telecommunications; Wireless; Operating system","score_opus":0.010672261707015022,"score_gpt":0.2365594080644354,"score_spread":0.22588714635742038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996894843","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":[0.049663402,0.01082774,0.93864524,0.00008123873,0.00036621132,0.00013571432,0.000023302955,0.000025866457,0.00023127715],"genre_scores_gemma":[0.9924068,0.006300188,0.0009968039,0.000011960276,0.00014240784,0.000012981568,0.00010593273,0.0000143986645,0.000008526632],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917346,0.000043488177,0.00045654527,0.00006516562,0.00014232787,0.00011900476],"domain_scores_gemma":[0.99918395,0.00018359956,0.00021816137,0.00010153527,0.0002626831,0.000050077964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023932457,0.00010211677,0.0001970667,0.00011803421,0.000079139674,0.0001017899,0.00019918814,0.00006417855,0.0000014232892],"category_scores_gemma":[0.000022068361,0.00010205174,0.00003376947,0.00010415187,0.000058829042,0.00045037852,0.00003181482,0.00015924274,8.51257e-8],"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":[0.000051988252,0.0000100336065,0.0025484448,0.000010653111,0.000053062733,0.0000034978762,0.00018240101,0.99286616,0.000017196651,0.0017351353,0.00097499305,0.0015464353],"study_design_scores_gemma":[0.001327165,0.000026552714,0.0014229978,0.000308398,0.000009270941,0.00017284023,0.0010179305,0.9920064,0.0000052202345,0.00023425893,0.0033596347,0.00010930072],"about_ca_topic_score_codex":0.000015483869,"about_ca_topic_score_gemma":0.000014902273,"teacher_disagreement_score":0.9427434,"about_ca_system_score_codex":0.00011645429,"about_ca_system_score_gemma":0.000021992622,"threshold_uncertainty_score":0.41615492},"labels":[],"label_agreement":null},{"id":"W1997195463","doi":"10.5539/mas.v4n12p140","title":"Resource Allocation -WiMAX Systems","year":2010,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; WiMAX; Fading; Resource allocation; Channel state information; Telecommunications link; Channel (broadcasting); Wireless; Mathematical optimization; Computer network; Telecommunications; Mathematics","score_opus":0.00477335381179823,"score_gpt":0.19109064781839144,"score_spread":0.18631729400659322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997195463","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":[0.037595395,0.000036798614,0.93219584,0.000017182296,0.00036590465,0.00019087551,8.834522e-7,0.00046905453,0.02912806],"genre_scores_gemma":[0.98988456,0.0000049743385,0.009840398,0.000020964899,0.000103412276,0.00004601329,0.0000044374283,0.000023578581,0.00007163784],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905455,0.0000027485917,0.00013357347,0.00024108238,0.00029304822,0.00027502357],"domain_scores_gemma":[0.9994863,0.000018395327,0.000027275257,0.00034412649,0.00003836242,0.00008553901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024965624,0.000099365054,0.000082522216,0.00008781972,0.00015875831,0.00009050264,0.00032019915,0.00005250606,0.0000052966],"category_scores_gemma":[0.000011569246,0.000103657585,0.000009873064,0.00046917354,0.00016588348,0.00019761248,0.000036229943,0.00018192285,0.000042951717],"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":[7.970489e-7,0.00000238996,0.000006906967,0.0000047937806,5.829834e-7,1.3427297e-7,0.000085711676,0.60742253,0.38205945,0.005099641,0.000053528365,0.005263538],"study_design_scores_gemma":[0.00007118886,0.000001929846,0.00009393547,0.000004071725,0.0000016278082,0.0000025244901,0.00002045487,0.9876866,0.009340704,0.0004550567,0.0021976053,0.00012433113],"about_ca_topic_score_codex":0.0000014474156,"about_ca_topic_score_gemma":0.0000035930505,"teacher_disagreement_score":0.95228916,"about_ca_system_score_codex":0.00005497308,"about_ca_system_score_gemma":0.000022875218,"threshold_uncertainty_score":0.42270336},"labels":[],"label_agreement":null},{"id":"W1997211193","doi":"10.1109/wcl.2013.102513.130586","title":"A New Multicast Scheduling Scheme for Cellular Networks","year":2014,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced Wireless Network Optimization","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":"University of Victoria","funders":"","keywords":"Computer science; Multicast; Scheduling (production processes); Throughput; Computational complexity theory; Distributed computing; Computer network; Mathematical optimization; Algorithm; Wireless; Mathematics","score_opus":0.0148212454460398,"score_gpt":0.23296925596472645,"score_spread":0.21814801051868665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997211193","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":[0.020735534,0.00041649028,0.9759617,0.0011668041,0.0004339489,0.00042543825,0.0000041480484,0.00065996713,0.00019599703],"genre_scores_gemma":[0.58810276,0.00017303468,0.4108064,0.00032371408,0.0002835679,0.00011959555,0.00008335834,0.00008666381,0.00002091561],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987708,0.00006549734,0.00038316695,0.00023326196,0.00012168839,0.0004256195],"domain_scores_gemma":[0.9976656,0.0004166538,0.00008707413,0.0016203083,0.000067971065,0.00014238515],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018185559,0.00025104455,0.00026741432,0.00011148894,0.00027611302,0.0000728954,0.000903482,0.00012522074,0.000006872113],"category_scores_gemma":[0.000028199047,0.00030462,0.00010362083,0.0003373761,0.000090427864,0.0002425923,0.00007907796,0.0003463062,0.000022349474],"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":[0.000005347455,0.000014577654,0.00006846436,0.000022434118,0.00003718919,1.7165752e-7,0.0000821002,0.94482225,0.032583646,0.0015244248,0.001735917,0.019103466],"study_design_scores_gemma":[0.0005687702,0.00000918407,0.000019302583,0.000073499046,0.000023229924,0.0000014100699,0.000017111757,0.98796684,0.002538513,0.00005208581,0.008402334,0.0003277533],"about_ca_topic_score_codex":0.000008917976,"about_ca_topic_score_gemma":0.00001856821,"teacher_disagreement_score":0.5673672,"about_ca_system_score_codex":0.00010243465,"about_ca_system_score_gemma":0.000013838282,"threshold_uncertainty_score":0.9999406},"labels":[],"label_agreement":null},{"id":"W1999186337","doi":"10.1109/ccece.2008.4564857","title":"Optimal linear-time QoS-based scheduling for WiMAX","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University","funders":"","keywords":"WiMAX; Telecommunications link; Computer science; Scheduling (production processes); Subframe; Quality of service; Job shop scheduling; Network packet; Computer network; Distributed computing; Fair-share scheduling; Mathematical optimization; Wireless; Linear programming; Algorithm; Mathematics; Telecommunications","score_opus":0.013497587443978885,"score_gpt":0.19031085986362528,"score_spread":0.1768132724196464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999186337","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":[0.10236029,0.00012335966,0.89558643,0.00019642079,0.00021977811,0.00044594673,0.000015609961,0.0006023316,0.0004498448],"genre_scores_gemma":[0.9141211,0.000101711536,0.08497205,0.00014318943,0.00040049804,0.00010354703,0.000029796085,0.000074908115,0.000053217835],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981943,0.0000036780223,0.00030599922,0.00046882677,0.00017601551,0.000851207],"domain_scores_gemma":[0.99888134,0.00007588521,0.000043784898,0.0001121982,0.00029416903,0.0005926041],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000075824544,0.00041374404,0.00039334357,0.0003730036,0.0002074164,0.00012597727,0.0002610544,0.0002062844,0.000027835773],"category_scores_gemma":[0.000038430127,0.00046511574,0.00006602294,0.0004332214,0.000054465763,0.00025031617,0.000019970943,0.00040869354,0.000014915736],"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":[0.000023419796,0.00001629054,0.00019015136,0.000091485635,0.000035589812,0.000011835891,0.00014663249,0.9810508,0.0011775478,0.006953487,0.0004290752,0.009873724],"study_design_scores_gemma":[0.00047517937,0.00020649108,0.00024763407,0.00012600858,0.000012894659,0.0000270264,0.0000039882466,0.99607444,0.0009851198,0.000052241307,0.0012392196,0.00054974714],"about_ca_topic_score_codex":0.000077722914,"about_ca_topic_score_gemma":0.000037012895,"teacher_disagreement_score":0.8117608,"about_ca_system_score_codex":0.00020000638,"about_ca_system_score_gemma":0.00025775796,"threshold_uncertainty_score":0.99978006},"labels":[],"label_agreement":null},{"id":"W2000165099","doi":"10.1109/mass.2011.132","title":"Power Efficient High Quality Multimedia Multicast in LTE Wireless Networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Multimedia Broadcast Multicast Service; Computer science; EnodeB; Computer network; Quality of experience; Video quality; Multicast; Scalability; Quality of service; Base station; Network packet; User equipment","score_opus":0.013834689619730327,"score_gpt":0.22549398703067572,"score_spread":0.21165929741094539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000165099","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":[0.35098472,0.00006754967,0.6418281,0.0000051148986,0.0005294637,0.00021723875,0.000002385198,0.00044031828,0.0059250747],"genre_scores_gemma":[0.96391374,0.000039655755,0.03580854,0.000029639536,0.000051357543,0.000029108396,0.000014219424,0.000054658976,0.000059090708],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874395,0.00004382477,0.0004012441,0.00024482457,0.00014192572,0.00042424514],"domain_scores_gemma":[0.9994125,0.00009382929,0.0000403208,0.00030618955,0.00004213977,0.000105025705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001780093,0.00020644799,0.00024180904,0.000091472364,0.00002881124,0.0000117112095,0.0001485862,0.00014076462,0.00038815034],"category_scores_gemma":[0.000019431753,0.00020458776,0.00003992677,0.0003400858,0.000047719244,0.00010575019,0.00004428269,0.00023145719,0.000055966466],"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":[0.000018794532,0.00007180181,0.0016914833,0.000008974365,0.0000100367415,0.000007203201,0.0004775318,0.992305,0.00012688848,0.0010913725,0.000051364637,0.004139542],"study_design_scores_gemma":[0.0005647386,0.000010982033,0.024722919,0.000023855777,0.000002982089,8.373063e-7,0.000075252734,0.9735576,0.0007224553,0.000027395336,0.000025744712,0.0002652345],"about_ca_topic_score_codex":0.00007561999,"about_ca_topic_score_gemma":0.0000937998,"teacher_disagreement_score":0.612929,"about_ca_system_score_codex":0.00009786941,"about_ca_system_score_gemma":0.000005486174,"threshold_uncertainty_score":0.8342847},"labels":[],"label_agreement":null},{"id":"W2000308072","doi":"10.1049/iet-com.2009.0140","title":"Cross-layer optimisation of network performance over multiple-input multiple-output wireless mobile channels","year":2010,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Computer science; MIMO; Fading; Channel (broadcasting); Throughput; Computer network; Markov process; Channel capacity; Transmission (telecommunications); Physical layer; Buffer overflow; Markov chain; Quality of service; Wireless; Telecommunications; Mathematics; Statistics","score_opus":0.018500537304882193,"score_gpt":0.2697353760823955,"score_spread":0.2512348387775133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000308072","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":[0.929508,0.00039859558,0.06642613,0.000036097823,0.00087350956,0.0006625429,0.000036811864,0.0005106075,0.0015477465],"genre_scores_gemma":[0.9512103,0.0011806209,0.046529952,0.000024372852,0.00022631779,0.00034051988,0.0002477672,0.00008823139,0.00015190021],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859595,0.00005038578,0.00055757066,0.00021611537,0.00020172815,0.00037825905],"domain_scores_gemma":[0.99698085,0.00049680786,0.00017900665,0.0020140184,0.00023193016,0.00009737967],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023094557,0.00025111614,0.0002815266,0.000097380434,0.00032002747,0.00005589486,0.00091387134,0.00022218442,0.000064930406],"category_scores_gemma":[0.00006263031,0.00028719316,0.000090029,0.00048470683,0.00024238389,0.0005439902,0.00023884037,0.0005994554,0.000027520973],"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":[0.000012573727,0.00006370595,0.021186117,0.00003324096,0.000032393946,1.3432849e-7,0.00036258315,0.96031994,0.0054517672,0.00018926345,0.00024596122,0.0121023515],"study_design_scores_gemma":[0.0005839323,0.000024001793,0.014122227,0.00006122341,0.000016286753,0.0000028731486,0.00002394178,0.9748479,0.004150354,0.000034094897,0.0058484394,0.00028470534],"about_ca_topic_score_codex":0.00002051181,"about_ca_topic_score_gemma":0.00012150517,"teacher_disagreement_score":0.021702355,"about_ca_system_score_codex":0.000059385635,"about_ca_system_score_gemma":0.00002368599,"threshold_uncertainty_score":0.99995804},"labels":[],"label_agreement":null},{"id":"W2000351350","doi":"10.1007/s11276-007-0025-x","title":"Real-time CBR traffic scheduling in IEEE 802.16-based wireless mesh networks","year":2007,"lang":"en","type":"article","venue":"Wireless Networks","topic":"Advanced Wireless Network Optimization","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":"McMaster University","funders":"","keywords":"Computer science; Fair-share scheduling; Round-robin scheduling; Computer network; Dynamic priority scheduling; Scheduling (production processes); Rate-monotonic scheduling; Earliest deadline first scheduling; Bottleneck; Network packet; IEEE 802; Distributed computing; Real-time computing; Mathematical optimization; Embedded system; Quality of service","score_opus":0.0066404526489133725,"score_gpt":0.2173382701217506,"score_spread":0.21069781747283722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000351350","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":[0.40491655,0.0004018871,0.59037185,0.000019120604,0.0011850769,0.00053508446,0.0000036680535,0.0013896914,0.0011770925],"genre_scores_gemma":[0.9887724,0.0014250136,0.007193838,0.000114970346,0.0016276587,0.00009350847,0.00023883865,0.0004285305,0.000105253865],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9949087,0.00014060535,0.0013802932,0.00090847147,0.0005357021,0.002126257],"domain_scores_gemma":[0.9976352,0.00064093765,0.00026465612,0.0008698042,0.00014146503,0.0004479624],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010854191,0.0009122653,0.0010349372,0.00050058187,0.00023566771,0.00012789587,0.0006558965,0.00097006396,0.00009132019],"category_scores_gemma":[0.000016942608,0.0010790522,0.00024180616,0.0022049942,0.00018195392,0.00047146197,0.00006386977,0.0014088692,0.000049050803],"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":[0.00014856011,0.00009562269,0.0006903807,0.000058062153,0.00005331977,0.00009502202,0.00008249703,0.94626254,0.0004989986,0.00025233987,0.0005956897,0.051166955],"study_design_scores_gemma":[0.0017146942,0.000051347444,0.0005629648,0.00048839784,0.00004055752,0.000011048575,0.000056778605,0.99528134,0.0005239353,0.00001968845,0.0001292247,0.0011200169],"about_ca_topic_score_codex":0.00003272806,"about_ca_topic_score_gemma":0.00039047824,"teacher_disagreement_score":0.58385587,"about_ca_system_score_codex":0.0008237296,"about_ca_system_score_gemma":0.0000681155,"threshold_uncertainty_score":0.99916595},"labels":[],"label_agreement":null},{"id":"W2000770891","doi":"10.1109/wcnc.2013.6555228","title":"Constellation and rate selection in adaptive modulation and coding based on finite blocklength analysis","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Constellation; Coding (social sciences); Channel code; Computer science; Link adaptation; Selection (genetic algorithm); Modulation (music); Channel (broadcasting); Constellation diagram; Algorithm; Coding gain; Channel capacity; Code rate; Telecommunications; Mathematics; Decoding methods; Bit error rate; Statistics; Artificial intelligence; Fading; Physics","score_opus":0.007183950583912561,"score_gpt":0.19057861882909524,"score_spread":0.1833946682451827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000770891","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":[0.21855447,0.000015556816,0.7793878,0.000016541697,0.000014785118,0.00018035548,6.972001e-7,0.00009907476,0.0017307546],"genre_scores_gemma":[0.98846704,0.00006513698,0.011382729,0.000021762718,0.000013008476,0.000008467122,0.000015036174,0.000011312589,0.000015525877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954706,0.000031437765,0.00013606649,0.00013736455,0.000051240677,0.000096847565],"domain_scores_gemma":[0.99970645,0.00016790054,0.000027102364,0.000040965126,0.0000289536,0.000028615568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007171675,0.00008981406,0.00011232781,0.0002924369,0.000034280583,0.000028919598,0.000010719327,0.00005260019,0.000037825706],"category_scores_gemma":[0.000009198422,0.00009403883,0.000011263816,0.0005544365,0.000012630035,0.00021467522,0.000004091045,0.0000653584,0.000001849649],"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":[0.000006701502,0.0000035008452,0.010532489,0.0000053559475,0.00001798711,1.0295537e-7,0.000029377547,0.98212975,0.0004627059,0.000093020775,0.0000069751204,0.0067120367],"study_design_scores_gemma":[0.00025657934,0.000019126286,0.03718766,0.000013424975,0.000022166507,1.4320281e-7,0.000020672605,0.9619799,0.0002943118,0.00010542488,0.0000034369684,0.00009713737],"about_ca_topic_score_codex":0.000022622024,"about_ca_topic_score_gemma":0.000057678077,"teacher_disagreement_score":0.76991254,"about_ca_system_score_codex":0.000048094797,"about_ca_system_score_gemma":0.0000025743705,"threshold_uncertainty_score":0.3834792},"labels":[],"label_agreement":null},{"id":"W2000813696","doi":"10.1145/1815396.1815441","title":"Comparing uplink schedulers for LTE","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University","funders":"","keywords":"Telecommunications link; Computer science; Flexibility (engineering); Frequency-division multiple access; User equipment; Computer network; Scheduling (production processes); Orthogonal frequency-division multiplexing; Base station; Channel (broadcasting); Engineering","score_opus":0.01149312832750662,"score_gpt":0.22176936896328073,"score_spread":0.2102762406357741,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000813696","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":[0.06667597,0.000015532034,0.9234013,0.00002424626,0.00053731044,0.00012258964,4.080206e-7,0.00049178506,0.008730869],"genre_scores_gemma":[0.7395197,0.0000064522187,0.26019675,0.000014722155,0.00011035164,0.000019745135,0.000008925197,0.000023077358,0.0001002773],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966395,8.9268104e-7,0.00008680091,0.00007455367,0.000030883064,0.00014294207],"domain_scores_gemma":[0.9997927,0.00002868881,0.000009000798,0.000111343405,0.00002129156,0.00003699539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003538858,0.00006597151,0.00007419285,0.000026633557,0.000033457098,0.00001443746,0.00006161544,0.00004565457,0.000051408468],"category_scores_gemma":[0.000009878403,0.00006845364,0.000021661152,0.00006336243,0.000010632893,0.00010100833,0.000008741144,0.00010369679,0.000018709483],"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":[0.000001843854,0.0000025106874,0.0004867331,0.000011129958,0.000006257293,7.743201e-8,0.000011519682,0.9839736,0.005136405,0.0067455545,0.0006398205,0.0029845373],"study_design_scores_gemma":[0.0001862645,0.0000031014051,0.00016357728,0.000003320391,0.0000028508628,5.8238356e-7,0.0000070224696,0.9907507,0.005296303,0.00029457395,0.0031985512,0.0000931797],"about_ca_topic_score_codex":6.252464e-7,"about_ca_topic_score_gemma":0.000016318003,"teacher_disagreement_score":0.6728437,"about_ca_system_score_codex":0.000010096965,"about_ca_system_score_gemma":0.0000025746922,"threshold_uncertainty_score":0.27914584},"labels":[],"label_agreement":null},{"id":"W2000926708","doi":"10.1155/2009/642878","title":"Fairness in Radio Resource Management for Wireless Networks","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Toronto Metropolitan University; Memorial University of Newfoundland","funders":"","keywords":"Computer science; Radio resource management; Computer network; Wireless network; Wireless; Telecommunications; Cognitive radio; Resource (disambiguation)","score_opus":0.01659737060490116,"score_gpt":0.248749752649981,"score_spread":0.23215238204507985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000926708","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":[0.036685638,0.016201254,0.93686783,0.0011538449,0.0007155041,0.0010142868,0.000003791163,0.00040576226,0.0069521023],"genre_scores_gemma":[0.954336,0.037017286,0.0078095077,0.00021774672,0.00042850414,0.000049884395,0.00003245074,0.00006643984,0.00004221074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983179,0.00013962016,0.0006111609,0.00023363082,0.00017105174,0.000526634],"domain_scores_gemma":[0.99857795,0.00034297022,0.00017017599,0.00071296364,0.00005234356,0.00014359232],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005520198,0.00029331056,0.00036038936,0.0002649415,0.00052153587,0.00016925507,0.0006474434,0.00012932922,0.0000022076456],"category_scores_gemma":[0.000003107387,0.00030979438,0.00008464782,0.0005752841,0.00006789729,0.00023883552,0.00007962504,0.00072837994,9.992086e-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":[0.000041354255,0.00004594705,0.000255462,0.000012746332,0.000027890173,0.000007973589,0.00011750976,0.5605817,0.000013022979,0.00467978,0.00036699302,0.4338496],"study_design_scores_gemma":[0.0010485483,0.000090901536,0.0012368098,0.00063282275,0.000025064199,0.000048574246,0.00012976593,0.96753514,0.000009860372,0.00093287777,0.02794993,0.00035968807],"about_ca_topic_score_codex":5.314531e-7,"about_ca_topic_score_gemma":0.000010674346,"teacher_disagreement_score":0.9290583,"about_ca_system_score_codex":0.0001763626,"about_ca_system_score_gemma":0.000007699807,"threshold_uncertainty_score":0.9999354},"labels":[],"label_agreement":null},{"id":"W2001133881","doi":"10.1109/sarnof.2010.5469758","title":"On energy efficiency of pilot assisted modulation schemes","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Channel (broadcasting); Efficient energy use; Channel state information; Modulation (music); Computer science; Power (physics); Energy (signal processing); Electronic engineering; Spectral efficiency; Telecommunications; Wireless; Electrical engineering; Mathematics; Engineering; Statistics; Physics; Acoustics","score_opus":0.0076496978347491956,"score_gpt":0.20780904243586354,"score_spread":0.20015934460111434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001133881","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":[0.2578489,0.000008845524,0.73131305,0.0000059114545,0.00020602446,0.000029649449,5.925564e-7,0.00019752682,0.010389517],"genre_scores_gemma":[0.9823018,0.0000073354213,0.017479332,0.000009596319,0.000033769287,0.0000043382456,0.000010611421,0.000016978489,0.00013625607],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996318,0.000003849203,0.00011946529,0.00007428078,0.0000850809,0.00008551144],"domain_scores_gemma":[0.99975264,0.00003506193,0.000022003931,0.00013735825,0.000031378564,0.000021538772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000024855308,0.00006534981,0.00006939289,0.000056391844,0.000016724449,0.000004229539,0.00004991684,0.000037725436,0.00008879104],"category_scores_gemma":[0.000017444661,0.000062425956,0.000014217588,0.00015853405,0.000014164449,0.00006569597,0.000006228906,0.000061602535,0.0000042678685],"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":[0.000004068269,0.000023317305,0.000035506724,0.0000046453683,0.0000032546839,9.807778e-8,0.000004069273,0.8734893,0.08495817,0.029985089,0.00007402809,0.011418428],"study_design_scores_gemma":[0.00013797979,0.000034638262,0.0009179036,0.000005925887,0.0000016190486,4.035976e-7,0.000001103206,0.9454422,0.052752562,0.00040906252,0.0002267578,0.00006987172],"about_ca_topic_score_codex":0.0000036342701,"about_ca_topic_score_gemma":0.00001602322,"teacher_disagreement_score":0.7244529,"about_ca_system_score_codex":0.000010268037,"about_ca_system_score_gemma":0.0000032303055,"threshold_uncertainty_score":0.2545657},"labels":[],"label_agreement":null},{"id":"W2001252974","doi":"10.1109/glocom.2012.6503666","title":"Energy-efficient power allocation for delay-constrained systems","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":28,"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":"Mathematical optimization; Efficient energy use; Computer science; Rayleigh fading; Power (physics); Quality of service; Probabilistic logic; Constraint (computer-aided design); Energy (signal processing); Channel (broadcasting); Fading; Control theory (sociology); Mathematics; Telecommunications; Engineering; Statistics; Electrical engineering","score_opus":0.007322513010840628,"score_gpt":0.20376210236590547,"score_spread":0.19643958935506484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001252974","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":[0.0042773667,0.0005550264,0.98744667,0.0000100522975,0.00086631626,0.0001846421,0.0000036155873,0.0003849031,0.0062714014],"genre_scores_gemma":[0.98492223,0.000014719989,0.014452968,0.00002036751,0.0001545147,0.00010556559,0.000037550202,0.000033029988,0.00025908326],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994484,0.000006752184,0.0001523982,0.000075129225,0.00007003132,0.00024728067],"domain_scores_gemma":[0.9997123,0.000042193125,0.000020807784,0.00011405674,0.000045752695,0.00006491236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007852922,0.000094026516,0.000082416394,0.000042728636,0.00003440354,0.000014091802,0.000044697503,0.000057511803,0.00002322595],"category_scores_gemma":[0.0000061765277,0.000091352566,0.000025933554,0.00009968975,0.000009892334,0.00011249238,0.000005904328,0.000026100304,0.00001000256],"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":[0.000002298994,0.000012830642,0.000018402296,0.000012580004,0.000011700554,5.0961088e-8,0.00006564317,0.9655802,0.000653349,0.031368565,0.000762885,0.0015114786],"study_design_scores_gemma":[0.00015911803,0.000007922559,0.000016070331,0.0000092214605,0.0000062974377,0.0000035337443,0.00006518517,0.9909635,0.00095568463,0.000014430003,0.0076776748,0.00012134667],"about_ca_topic_score_codex":0.0000023327434,"about_ca_topic_score_gemma":9.440501e-7,"teacher_disagreement_score":0.9806448,"about_ca_system_score_codex":0.0000661393,"about_ca_system_score_gemma":0.000004631105,"threshold_uncertainty_score":0.37252495},"labels":[],"label_agreement":null},{"id":"W2001782922","doi":"10.1145/1185373.1185439","title":"A game-theoretic approach to bandwidth allocation and admission control for polling services in IEEE 802.16 broadband wireless networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Manitoba","funders":"","keywords":"Polling; Computer science; Computer network; Wireless broadband; Bandwidth allocation; Admission control; Quality of service; Queueing theory; Base station; WiMAX; Bandwidth (computing); Wireless; Broadband networks; Wireless network; Broadband; Telecommunications","score_opus":0.003793435524684118,"score_gpt":0.19518641238303522,"score_spread":0.1913929768583511,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001782922","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":[0.10261173,0.00053238345,0.8947587,0.000028116818,0.00010141413,0.0007715365,0.0000032045473,0.00020001095,0.0009928856],"genre_scores_gemma":[0.984728,0.00012371637,0.014458335,0.00009627313,0.00020246724,0.00016993828,0.00007419039,0.00006177994,0.000085313965],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894655,0.000024004836,0.0003082324,0.00028199895,0.000098745484,0.00034050018],"domain_scores_gemma":[0.9995717,0.000097249285,0.000042565727,0.000147076,0.000047182722,0.00009425734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015218195,0.0002070253,0.00024769263,0.00012325421,0.000052369913,0.00005713374,0.00009211768,0.00013485142,0.0000038310645],"category_scores_gemma":[0.0000037112295,0.00020103279,0.000027651427,0.00028243,0.000017683346,0.00018965738,0.000010373113,0.00009780973,8.3396054e-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":[0.00006683659,0.000026289215,0.0007225923,0.00014767169,0.000007710783,2.3497415e-7,0.00008626458,0.9900949,0.0006031079,0.0025694438,0.000053608022,0.0056213234],"study_design_scores_gemma":[0.0013233698,0.00002659177,0.00052976864,0.000121894154,0.000015285295,0.000002152648,0.00005241557,0.99602515,0.0007587982,0.0007622355,0.00014089703,0.0002414182],"about_ca_topic_score_codex":0.00003611922,"about_ca_topic_score_gemma":0.00009187362,"teacher_disagreement_score":0.88211626,"about_ca_system_score_codex":0.00009075064,"about_ca_system_score_gemma":0.0000072660196,"threshold_uncertainty_score":0.8197879},"labels":[],"label_agreement":null},{"id":"W2002031602","doi":"10.1145/1143549.1143595","title":"Traffic prediction based access control using different video traffic models in 3G CDMA high speed data networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Computer network; Network packet; Telecommunications link; Cellular network; Real-time computing; Traffic generation model; Code division multiple access; Frame (networking)","score_opus":0.02446769208048916,"score_gpt":0.233946710151627,"score_spread":0.20947901807113783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002031602","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":[0.35072422,0.000157058,0.64769393,0.000018889434,0.00032616156,0.00038217357,0.000040539537,0.0005709923,0.000086036365],"genre_scores_gemma":[0.9940062,0.000053204814,0.00445457,0.000037431855,0.00040373887,0.000016215503,0.0009182115,0.00009605571,0.000014369223],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99821085,0.000058121983,0.0005594462,0.00045457445,0.00023296142,0.0004840198],"domain_scores_gemma":[0.9990995,0.000115427545,0.00007395384,0.0006007444,0.000036489582,0.000073869654],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012969886,0.00032099502,0.0003707817,0.00019960283,0.00006654464,0.00011504183,0.00043500794,0.00019299946,0.000047219517],"category_scores_gemma":[0.000006447566,0.00032172233,0.000042981483,0.00046747853,0.000028506192,0.0011544909,0.000052779233,0.00026082073,0.0000013538792],"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":[0.000042757456,0.000073158684,0.00025301895,0.000022803628,0.000016384196,0.0000045715897,0.0000059516815,0.9956821,0.000106555424,0.000053240772,0.00031502888,0.0034243972],"study_design_scores_gemma":[0.0021256544,0.000013782961,0.0018524749,0.00007451458,0.00004160643,0.0000017214519,0.0000050792505,0.9954802,0.000046533827,0.000047677204,0.00001279055,0.00029797415],"about_ca_topic_score_codex":0.00005226175,"about_ca_topic_score_gemma":0.00036774416,"teacher_disagreement_score":0.643282,"about_ca_system_score_codex":0.00025038377,"about_ca_system_score_gemma":0.000017434748,"threshold_uncertainty_score":0.99992347},"labels":[],"label_agreement":null},{"id":"W2002205691","doi":"10.1109/wcnc.2014.6952520","title":"Low-complexity QoS-aware frequency provisioning in downlink multi-user multicarrier systems","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Computer science; Provisioning; Quality of service; Telecommunications link; Fading; Multi-user; Computer network; Real-time computing; Set (abstract data type); Distributed computing; Channel (broadcasting)","score_opus":0.013719023441401218,"score_gpt":0.2304127118830512,"score_spread":0.21669368844165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002205691","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":[0.04633812,0.00010560473,0.9495357,0.000015576366,0.0007122993,0.0004795832,0.000005827602,0.00077128725,0.002035971],"genre_scores_gemma":[0.92501867,0.000020857608,0.0743359,0.00002525233,0.0001846664,0.00006294518,0.000034495155,0.000066153385,0.000251071],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869245,0.00005583108,0.00040954954,0.00028590448,0.00016189551,0.00039436173],"domain_scores_gemma":[0.9993409,0.00008511924,0.00004381095,0.00034949818,0.000076498865,0.00010415242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016885306,0.00022736192,0.00026904687,0.0001168216,0.00006247368,0.000056180692,0.00017126331,0.00014439966,0.000058943187],"category_scores_gemma":[0.00007594589,0.00021620051,0.000037942948,0.00028254406,0.000039482824,0.00035679006,0.00003759351,0.00024931144,0.00006790035],"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":[0.0000024162027,0.000022764358,0.0027875751,0.00011141836,0.0000061667056,0.0000025520926,0.00012368319,0.9922209,0.00072624936,0.0023911374,0.00008240896,0.001522759],"study_design_scores_gemma":[0.00064214494,0.000011284484,0.0022915613,0.00014908676,0.0000039659926,0.000001725208,0.0000820493,0.99564826,0.000438118,0.00006269535,0.00038252218,0.00028660064],"about_ca_topic_score_codex":0.000076323915,"about_ca_topic_score_gemma":0.0001624314,"teacher_disagreement_score":0.8786805,"about_ca_system_score_codex":0.00014439886,"about_ca_system_score_gemma":0.000009977193,"threshold_uncertainty_score":0.88164014},"labels":[],"label_agreement":null},{"id":"W2002503368","doi":"10.1049/iet-com.2013.0296","title":"Wireless local area network service providers’ price competition in presence of heterogeneous user demand","year":2013,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Oligopoly; Revenue; Monopoly; Duopoly; Economic surplus; Competition (biology); Price discrimination; Service provider; Microeconomics; Revenue model; Nash equilibrium; Business; Service (business); Computer science; Industrial organization; Economics; Cournot competition; Marketing; Finance","score_opus":0.013530411104274307,"score_gpt":0.22037749995048522,"score_spread":0.20684708884621092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002503368","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":[0.1740905,0.0017246961,0.8196669,0.0008075618,0.00012460939,0.001129457,0.0000109958255,0.00033393185,0.0021113479],"genre_scores_gemma":[0.9751389,0.0009032114,0.023493698,0.00007658464,0.000019883708,0.00023728772,0.00008310684,0.000033803415,0.00001354598],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990654,0.00009631415,0.00035918388,0.00012857465,0.000113230475,0.00023727499],"domain_scores_gemma":[0.9983913,0.0002649461,0.0000857404,0.0010448733,0.00015926368,0.0000538779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000087012464,0.00013449973,0.00018566524,0.000058936243,0.00008036495,0.000025566665,0.00058317144,0.00008829431,0.000038209295],"category_scores_gemma":[0.000011938743,0.00015441388,0.000027448694,0.0005764181,0.0000944888,0.00036322334,0.00016944538,0.0002112431,0.00002390932],"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":[0.0000029176308,0.00004570723,0.0012988263,0.00005000257,0.000014465836,3.0386144e-7,0.00033206595,0.99526346,0.00034629935,0.00088001066,0.00027523827,0.0014907101],"study_design_scores_gemma":[0.00020836742,0.0000110333085,0.0029204534,0.00017310707,0.0000077183795,0.0000040309324,0.00010974115,0.9948151,0.0002690609,0.00062517717,0.000702858,0.00015333721],"about_ca_topic_score_codex":0.00016829807,"about_ca_topic_score_gemma":0.0016146163,"teacher_disagreement_score":0.8010484,"about_ca_system_score_codex":0.00007734354,"about_ca_system_score_gemma":0.000017707176,"threshold_uncertainty_score":0.6296815},"labels":[],"label_agreement":null},{"id":"W2002542048","doi":"10.1007/s11277-010-0145-y","title":"Adaptive Opportunistic Multicast Scheduling Over Next-Generation Wireless Networks","year":2010,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Multicast; Computer science; Source-specific multicast; Computer network; Xcast; Pragmatic General Multicast; Protocol Independent Multicast; Distributed computing; Distance Vector Multicast Routing Protocol; Link adaptation; IP multicast; Reliable multicast; Scheduling (production processes); Channel (broadcasting); Fading; Mathematical optimization","score_opus":0.062270391385437864,"score_gpt":0.2730342086674338,"score_spread":0.21076381728199592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002542048","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":[0.31782207,0.00068208645,0.6759571,0.0003160696,0.0010220584,0.0005749125,0.00007108758,0.001006309,0.0025483237],"genre_scores_gemma":[0.9579817,0.0010712825,0.039294675,0.00010256694,0.00051167293,0.0001757148,0.0006621562,0.00013005812,0.000070187016],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983162,0.000095607735,0.00048143815,0.0003424635,0.00027986703,0.0004844214],"domain_scores_gemma":[0.99784505,0.00029286754,0.00013063777,0.0012749928,0.00021975212,0.00023667002],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000221998,0.00036381662,0.00031763787,0.0001432987,0.0006547661,0.00015728448,0.000813084,0.00028627086,0.00012593137],"category_scores_gemma":[0.000036900703,0.00042624443,0.000114477196,0.00048265618,0.0003321127,0.00062277354,0.0002049315,0.0012590241,0.000037324946],"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":[0.000025988724,0.00020698817,0.00056985294,0.000032597636,0.0001557003,0.000006992929,0.0010823796,0.8202715,0.073832676,0.037966043,0.0005155828,0.065333694],"study_design_scores_gemma":[0.00035732065,0.00001835144,0.00035076973,0.000047996724,0.000043303793,0.000013900529,0.00025430982,0.99738526,0.00017510503,0.000055645425,0.00084004493,0.00045796233],"about_ca_topic_score_codex":0.00002705242,"about_ca_topic_score_gemma":0.0005499183,"teacher_disagreement_score":0.6401596,"about_ca_system_score_codex":0.00013168472,"about_ca_system_score_gemma":0.00006700675,"threshold_uncertainty_score":0.9998189},"labels":[],"label_agreement":null},{"id":"W2002724791","doi":"10.1109/jsac.2014.140411","title":"A Real-Time Adaptive Algorithm for Video Streaming over Multiple Wireless Access Networks","year":2014,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":116,"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":"Computer science; Computer network; Quality of service; Video quality; Codec; Wireless network; Wireless; Testbed; Real-time computing; Transcoding; Computer hardware; Telecommunications","score_opus":0.018611517232122926,"score_gpt":0.27596832161287843,"score_spread":0.2573568043807555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002724791","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":[0.02157149,0.00017267282,0.97595984,0.000067016816,0.00031581149,0.0005075388,0.00002735756,0.0003347617,0.0010435041],"genre_scores_gemma":[0.8955947,0.00223867,0.10125007,0.00006715563,0.00040198554,0.00017644973,0.00010403753,0.00012806631,0.000038854916],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99823546,0.0002575095,0.00060687686,0.0002159634,0.00020281681,0.00048138702],"domain_scores_gemma":[0.99642575,0.0019297142,0.0002560819,0.00086255174,0.00037388626,0.00015199324],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034496933,0.00028727838,0.0003725184,0.00030662486,0.00033915433,0.00014940377,0.0010595326,0.00016065789,0.000013265747],"category_scores_gemma":[0.0001403437,0.00031084742,0.00008943205,0.00097298133,0.000065091735,0.00054699916,0.000081284496,0.0008799436,0.000005506896],"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":[0.000033165754,0.000098722994,0.00036953267,0.0000036305762,0.00006323482,0.0000012475168,0.000083548875,0.93930715,0.00049324334,0.00013044981,0.0011158526,0.058300205],"study_design_scores_gemma":[0.0011105106,0.00008151341,0.0016648972,0.00027352985,0.000027243994,0.000019360712,0.00001910098,0.99508566,0.00023992608,0.00031394046,0.0008434978,0.00032080823],"about_ca_topic_score_codex":0.00002506654,"about_ca_topic_score_gemma":0.00019337746,"teacher_disagreement_score":0.8747098,"about_ca_system_score_codex":0.00043048014,"about_ca_system_score_gemma":0.000053568823,"threshold_uncertainty_score":0.9999344},"labels":[],"label_agreement":null},{"id":"W2002962057","doi":"10.1007/s11277-008-9590-2","title":"Performance Evaluation of the Enhanced MI-MAC Protocol for Multimedia Integration over Wireless Cellular Networks","year":2008,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Computer network; Scheduling (production processes); Telecommunications link; Handover; Protocol (science); Wireless network; Wireless; Channel (broadcasting); Cellular network; Telecommunications","score_opus":0.044962081828483505,"score_gpt":0.2975812915168779,"score_spread":0.2526192096883944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002962057","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":[0.51601624,0.000194844,0.40468222,0.0001235995,0.00034256006,0.07636202,0.00004684302,0.00032804086,0.0019036043],"genre_scores_gemma":[0.8877395,0.00012619454,0.0054805707,0.000019203128,0.000093321665,0.10629163,0.00014332568,0.000060347582,0.000045952456],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983453,0.00017943165,0.00049990107,0.00020924046,0.0004894972,0.0002766183],"domain_scores_gemma":[0.9978488,0.0002492417,0.00023653227,0.0010295607,0.0005796893,0.00005615272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004102214,0.00024016676,0.00024398425,0.00007930696,0.0005379117,0.00001551449,0.0007524751,0.00016247804,0.00004175376],"category_scores_gemma":[0.000047199475,0.00021561839,0.00013983148,0.00050549937,0.000321825,0.00031836465,0.00011136162,0.00035201455,0.0000031246466],"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":[0.000065575354,0.0001496501,0.0009229765,0.0001015329,0.00006304914,6.098266e-8,0.0022519787,0.91297054,0.023373157,0.0002563698,0.0005069447,0.059338138],"study_design_scores_gemma":[0.0012219681,0.000028092642,0.0029804825,0.00019175847,0.000044373526,0.0000017633471,0.0001001992,0.97161514,0.02325648,0.000023863302,0.0003118937,0.0002239664],"about_ca_topic_score_codex":0.000009942214,"about_ca_topic_score_gemma":0.00007130492,"teacher_disagreement_score":0.39920166,"about_ca_system_score_codex":0.00022803087,"about_ca_system_score_gemma":0.00011286569,"threshold_uncertainty_score":0.87926626},"labels":[],"label_agreement":null},{"id":"W2003155084","doi":"10.1002/ett.1196","title":"Adaptive modulation over nonlinear time‐varying channels","year":2007,"lang":"en","type":"article","venue":"European Transactions on Telecommunications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Link adaptation; Modulation (music); Computer science; Nonlinear system; Quadrature amplitude modulation; Transmission (telecommunications); Bit error rate; Control theory (sociology); Channel (broadcasting); Electronic engineering; Amplifier; QAM; Telecommunications; Bandwidth (computing); Physics; Engineering; Fading; Artificial intelligence; Acoustics","score_opus":0.014004055658360196,"score_gpt":0.22919663707628665,"score_spread":0.21519258141792647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003155084","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":[0.0033561955,0.00010277189,0.9571959,0.000055412536,0.00019151233,0.00024791018,0.000020897156,0.00093740487,0.03789201],"genre_scores_gemma":[0.90680146,0.0002700632,0.09204285,0.00006553596,0.00010247851,0.000013404816,0.00009827189,0.00011968591,0.0004862219],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989006,0.000104794504,0.0003698746,0.00018998572,0.00014377593,0.0002909747],"domain_scores_gemma":[0.99883103,0.00019268855,0.00006080036,0.0007453561,0.00007218396,0.00009792043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029862908,0.00020065144,0.00013703322,0.0002557964,0.00038997992,0.00003729782,0.00032194323,0.000057520032,0.00021065604],"category_scores_gemma":[0.000008805553,0.0002415118,0.00008108371,0.00058671465,0.000049696744,0.00031479858,0.00000762178,0.0004274961,0.0004991129],"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":[0.000011664538,0.00006979546,0.0000026042167,0.000003270101,0.000033846416,0.0000013150102,0.00021892197,0.9359263,0.0009083637,0.000060205857,0.00008828251,0.06267544],"study_design_scores_gemma":[0.00034091703,0.000041886422,0.00068494916,0.00004222836,0.000021382926,0.000004995719,0.000036799593,0.9921519,0.0019140292,0.000045200683,0.0044286265,0.00028704206],"about_ca_topic_score_codex":0.000003110068,"about_ca_topic_score_gemma":0.000010467146,"teacher_disagreement_score":0.9034453,"about_ca_system_score_codex":0.00014603145,"about_ca_system_score_gemma":0.000008429824,"threshold_uncertainty_score":0.98485655},"labels":[],"label_agreement":null},{"id":"W2003451136","doi":"10.1109/glocom.2012.6504000","title":"Joint handoff and resource management for throughput fairness in a wireless mesh network","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Throughput; Computer science; Handover; Computer network; Heuristic; Wireless mesh network; Resource management (computing); Resource allocation; Maximum throughput scheduling; Scheme (mathematics); Channel (broadcasting); Wireless network; Wireless; Distributed computing; Telecommunications; Quality of service; Mathematics; Dynamic priority scheduling","score_opus":0.011356539791307949,"score_gpt":0.21172912644365321,"score_spread":0.20037258665234525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003451136","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":[0.022780173,0.00064937194,0.9623774,0.000045039233,0.0002346631,0.0006385954,0.0000014601054,0.00028096457,0.012992302],"genre_scores_gemma":[0.96016717,0.00032918903,0.03856277,0.00006985982,0.00025680696,0.00017418098,0.00001719179,0.000052487605,0.00037037267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912405,0.000013895082,0.00020421064,0.00014357346,0.00007665737,0.00043761652],"domain_scores_gemma":[0.99970555,0.000047073194,0.000023109136,0.00014962493,0.000010044881,0.00006456894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017901183,0.00014446184,0.00018286673,0.000050131228,0.000047115267,0.00002037595,0.000050865037,0.00006193905,0.000011813625],"category_scores_gemma":[0.0000027071321,0.00014325454,0.000024417543,0.00019739171,0.000018635368,0.00021680954,0.000038800885,0.00007066992,0.0000030928582],"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":[0.00002306556,0.000021243854,0.0013713448,0.00015990547,0.000033321543,0.0000013186853,0.00025363476,0.9328981,0.00003096198,0.040315606,0.0047714687,0.02012],"study_design_scores_gemma":[0.001517628,0.000019772911,0.0035773825,0.00015078028,0.000025831698,0.0000044339413,0.00031041482,0.9755814,0.0005315594,0.0013135598,0.016538301,0.00042890816],"about_ca_topic_score_codex":0.0000021757287,"about_ca_topic_score_gemma":0.000016919246,"teacher_disagreement_score":0.937387,"about_ca_system_score_codex":0.000059316328,"about_ca_system_score_gemma":0.0000013532883,"threshold_uncertainty_score":0.58417505},"labels":[],"label_agreement":null},{"id":"W2003480200","doi":"10.1109/tcomm.2014.2359875","title":"Limiting Properties of Overloaded Multiuser Wireless Systems With Throughput-Optimal Scheduling","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Victoria","funders":"","keywords":"Maximum throughput scheduling; Scheduling (production processes); Computer science; Queue; Round-robin scheduling; Wireless; Throughput; Mathematical optimization; Proportionally fair; Distributed computing; Buffer overflow; Job shop scheduling; Fair-share scheduling; Dynamic priority scheduling; Computer network; Mathematics; Quality of service","score_opus":0.025701760114796916,"score_gpt":0.2210854360386223,"score_spread":0.19538367592382538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003480200","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":[0.10752545,0.00032110943,0.89049655,0.000047780282,0.00016120076,0.00030595265,0.000009928119,0.00042882768,0.0007032008],"genre_scores_gemma":[0.9520606,0.000522451,0.047078643,0.000011159602,0.00002728369,0.00017372964,0.000007132531,0.00007256982,0.00004644016],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989714,0.00009716985,0.00037350255,0.00016166318,0.00017606418,0.00022020597],"domain_scores_gemma":[0.99838114,0.0001838713,0.00009840377,0.0011363192,0.00014459636,0.00005567925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011473232,0.00019809847,0.00025299535,0.00012309565,0.0002993351,0.00003723458,0.00041848922,0.00009489993,0.0000042938555],"category_scores_gemma":[0.0000051963325,0.00018764067,0.000056305213,0.00037033332,0.00015837727,0.0003065858,0.000003980332,0.00036723434,0.00001183307],"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":[0.00001786886,0.00008203721,0.000012462424,0.00008317362,0.00006724526,8.85808e-8,0.00059667265,0.9871282,0.008722849,0.00030328755,0.000004177887,0.0029819089],"study_design_scores_gemma":[0.0004013718,0.00005231775,0.000017018425,0.0005087843,0.000042970496,0.000004775935,0.0003415513,0.9687041,0.029547662,0.0000040809946,0.00016314858,0.00021223583],"about_ca_topic_score_codex":0.000034312812,"about_ca_topic_score_gemma":0.000062914114,"teacher_disagreement_score":0.8445351,"about_ca_system_score_codex":0.00007818538,"about_ca_system_score_gemma":0.00002112087,"threshold_uncertainty_score":0.7651765},"labels":[],"label_agreement":null},{"id":"W2004110521","doi":"10.1109/icc.2012.6364468","title":"Joint routing, scheduling and power allocation in OFDMA wireless ad hoc networks","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Wireless ad hoc network; Scheduling (production processes); Network packet; Wireless network; Integer programming; Job shop scheduling; Mathematical optimization; Computer network; Optimization problem; Routing (electronic design automation); Wireless; Algorithm; Mathematics; Telecommunications","score_opus":0.008760993604874751,"score_gpt":0.2087243992291087,"score_spread":0.19996340562423395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004110521","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":[0.43523124,0.0045776605,0.55888575,0.0000338237,0.0002539341,0.000120304874,2.5804306e-7,0.0002190116,0.00067800266],"genre_scores_gemma":[0.98146856,0.0021242276,0.016143385,0.00004509346,0.00010017231,0.000022414406,0.000009272128,0.000042832384,0.000044025834],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992122,0.000016751028,0.00022521941,0.00012453322,0.00007731581,0.00034395957],"domain_scores_gemma":[0.99971664,0.000027792883,0.000033938803,0.00011955575,0.000022621334,0.00007944015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001590049,0.00013716579,0.00014383534,0.00007043071,0.000034004075,0.00002187957,0.000043457865,0.00010533734,0.000039445436],"category_scores_gemma":[0.00001076694,0.0001437956,0.00001643904,0.0002116989,0.000016505996,0.00039870804,0.000030340758,0.00016625047,0.0000057121383],"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":[0.0000030479493,0.000012699011,0.00634049,0.000010669771,0.000007398632,3.2658383e-7,0.0002652498,0.9700487,0.00047107053,0.00079889985,0.00003257171,0.022008853],"study_design_scores_gemma":[0.00022648361,0.000006146505,0.00988199,0.000067572306,0.0000045465185,0.000002083437,0.00011639538,0.98884404,0.0004872547,0.00001890069,0.00016088408,0.00018369946],"about_ca_topic_score_codex":0.0000026872672,"about_ca_topic_score_gemma":0.000020611478,"teacher_disagreement_score":0.54623735,"about_ca_system_score_codex":0.00007103822,"about_ca_system_score_gemma":0.0000037195364,"threshold_uncertainty_score":0.58638144},"labels":[],"label_agreement":null},{"id":"W2004792052","doi":"10.1109/icc.2012.6364054","title":"Optimal server assignment in multi-server parallel queueing systems with random connectivities and random service failures","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Network packet; Computer network; Bernoulli's principle; Bulk queue; Queueing theory; Queue; Queue management system; Fork–join queue; Server; Real-time computing; Engineering","score_opus":0.013141793788100174,"score_gpt":0.21214396064111826,"score_spread":0.19900216685301808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004792052","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":[0.35247713,0.002043085,0.6440404,0.000031602765,0.00020975107,0.00063804083,0.0000019819972,0.00026970866,0.00028828726],"genre_scores_gemma":[0.9797247,0.00014093542,0.019620914,0.000037571124,0.000097020915,0.00017194134,0.0000119019205,0.00006124916,0.00013377593],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998847,0.000083641076,0.000275263,0.00019017942,0.00017161696,0.00043229404],"domain_scores_gemma":[0.9994155,0.00019798352,0.000049060287,0.00017308154,0.000058620448,0.000105757215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002658876,0.0002621725,0.0003772835,0.000083092214,0.000058372574,0.000068922505,0.00007487199,0.00010010679,0.000025875353],"category_scores_gemma":[0.000014636036,0.0002152591,0.000023263246,0.0001867995,0.000024244753,0.000885338,0.000037199472,0.00015126012,0.0000059945887],"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":[0.00024338608,0.000029382834,0.011103321,0.00016234258,0.00005914884,0.0000027925828,0.00068926753,0.9872644,0.00006277276,0.00027992568,0.000045209268,0.000058039295],"study_design_scores_gemma":[0.012091489,0.00001988247,0.002855915,0.00018264106,0.000023901956,0.000009971357,0.0012554482,0.98266125,0.00023765465,0.0000029486973,0.00028361037,0.00037528266],"about_ca_topic_score_codex":0.0003149366,"about_ca_topic_score_gemma":0.0007952218,"teacher_disagreement_score":0.6272476,"about_ca_system_score_codex":0.000097792414,"about_ca_system_score_gemma":0.000008484449,"threshold_uncertainty_score":0.8778012},"labels":[],"label_agreement":null},{"id":"W2006477797","doi":"10.1109/spawc.2014.6941899","title":"Rate adaptation using long range channel prediction based on discrete prolate spheroidal sequences","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University","funders":"","keywords":"Computer science; Subspace topology; Channel (broadcasting); Link adaptation; Algorithm; Throughput; Transmission (telecommunications); Fading; Wireless; Artificial intelligence; Telecommunications","score_opus":0.014303790140562551,"score_gpt":0.21214144443424782,"score_spread":0.19783765429368527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006477797","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":[0.050531443,0.000023900626,0.9468947,0.000026859376,0.00034723076,0.00026266722,0.0000043699015,0.000576562,0.0013322388],"genre_scores_gemma":[0.9808092,0.000016539212,0.01873082,0.00004837137,0.00021600067,0.000025806743,0.000047966132,0.00004835196,0.000056942663],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991637,0.0000742633,0.00019822293,0.00019564698,0.00014683462,0.00022136701],"domain_scores_gemma":[0.9996432,0.00006239787,0.000049527614,0.00014845027,0.000041243573,0.00005517371],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021175371,0.0001654515,0.00012769473,0.00007110446,0.00010486575,0.000038981376,0.000061459636,0.00007814676,0.000031694104],"category_scores_gemma":[0.000025250198,0.00015672113,0.000032781365,0.00021047435,0.000020516614,0.00038542255,0.000006532411,0.0001299532,0.00001196712],"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":[0.000027335209,0.000004863526,0.00025767647,0.000026153883,0.0000067591504,7.285342e-7,0.0000687141,0.9965306,0.000741529,0.00004954685,0.000013376702,0.0022727486],"study_design_scores_gemma":[0.00041802926,0.00005571006,0.00080628484,0.00007347378,0.000012845331,9.1378234e-7,0.000026577052,0.9968344,0.0014623688,0.000119078766,0.000025296396,0.00016499824],"about_ca_topic_score_codex":0.000011726038,"about_ca_topic_score_gemma":0.00003304365,"teacher_disagreement_score":0.93027776,"about_ca_system_score_codex":0.00009294156,"about_ca_system_score_gemma":0.000009497532,"threshold_uncertainty_score":0.63909024},"labels":[],"label_agreement":null},{"id":"W2007715709","doi":"10.1109/cjece.2004.1425805","title":"Scheduling algorithms for high-throughput packet data service in cellular radio systems","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Alberta","funders":"","keywords":"Computer science; Scheduling (production processes); Network packet; Algorithm; Channel (broadcasting); Throughput; Wireless; Data transmission; Maximum throughput scheduling; Computer network; Real-time computing; Quality of service; Fair-share scheduling; Round-robin scheduling; Telecommunications; Mathematical optimization; Mathematics","score_opus":0.01314587845846779,"score_gpt":0.1902714432972891,"score_spread":0.1771255648388213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007715709","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":[0.07014008,0.0049857264,0.92404616,0.00006478842,0.00061083556,0.00011201042,0.000009377576,0.00002903558,0.0000020022835],"genre_scores_gemma":[0.9028205,0.00010287575,0.09632125,0.000024443803,0.0006705547,0.0000032628147,0.000018233217,0.00003809361,7.6677924e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999073,0.000008143485,0.0003262247,0.00013922008,0.000094518546,0.00035887767],"domain_scores_gemma":[0.99937886,0.00006292865,0.000042405438,0.00014539038,0.00008517309,0.00028524225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017932862,0.0001457191,0.00025503853,0.0002519117,0.00003556472,0.000068861744,0.00024338893,0.00008020583,6.0962014e-7],"category_scores_gemma":[0.000021094858,0.00015586623,0.00002064803,0.00041280792,0.000006443413,0.00028285076,0.00001402715,0.0002542634,4.2040972e-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":[0.0000017450013,0.0000032280745,0.000035937075,0.00005301565,0.00002829515,0.000042499905,0.000049097915,0.9953683,0.00008905928,0.000822731,0.00003539418,0.0034706842],"study_design_scores_gemma":[0.0007229979,0.000043167693,0.00015944487,0.00015881502,0.000016669293,0.0000926635,0.0000042271363,0.99780387,0.00013379984,0.00012946043,0.00056478824,0.00017009997],"about_ca_topic_score_codex":0.0002614886,"about_ca_topic_score_gemma":0.00029565016,"teacher_disagreement_score":0.83268046,"about_ca_system_score_codex":0.00025794847,"about_ca_system_score_gemma":0.0001324622,"threshold_uncertainty_score":0.635604},"labels":[],"label_agreement":null},{"id":"W2008498079","doi":"10.1109/pimrc.2012.6362516","title":"Economics of user-in-the-loop demand control with differentiated QoS in cellular networks","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Provisioning; Quality of service; Computer network; Handover; Base station; Wireless; Laptop; Network congestion; Telecommunications","score_opus":0.003844980699624036,"score_gpt":0.1612052260729376,"score_spread":0.15736024537331358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008498079","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":[0.5477693,0.00021841984,0.45139265,0.000005883525,0.000098945566,0.00016382655,6.561457e-7,0.000029640198,0.00032069662],"genre_scores_gemma":[0.99855494,0.00013616799,0.0011075991,0.000022811368,0.00009672074,0.000019668478,0.000012520074,0.000026495467,0.00002304952],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993792,0.00002866951,0.00022047253,0.00007504045,0.0000389468,0.00025764032],"domain_scores_gemma":[0.9996949,0.000075975935,0.00003733077,0.00015122766,0.000010207862,0.000030350311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010828982,0.00011305861,0.00018599413,0.000057011486,0.000010410898,0.000007968813,0.00008955147,0.00006604447,0.00002245944],"category_scores_gemma":[0.0000024478948,0.000085947424,0.000017330376,0.0001562084,0.000016956094,0.00016817464,0.0000069829925,0.00011309092,0.000001692008],"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":[0.000017334356,0.00002678911,0.047756974,0.000009703455,0.000013588739,6.409504e-7,0.00007258848,0.95132613,0.000079846286,0.00045896534,0.00003237728,0.00020504206],"study_design_scores_gemma":[0.0010495275,0.000013536655,0.0151666375,0.000020889338,0.000011574294,0.0000010182711,0.000038635026,0.9829649,0.00054382795,0.000010782828,0.000059176546,0.00011951956],"about_ca_topic_score_codex":0.0000074166333,"about_ca_topic_score_gemma":0.00013779385,"teacher_disagreement_score":0.45078567,"about_ca_system_score_codex":0.00003372343,"about_ca_system_score_gemma":0.0000028781417,"threshold_uncertainty_score":0.35048342},"labels":[],"label_agreement":null},{"id":"W2010592117","doi":"10.1007/s11036-008-0045-5","title":"Efficient Structured Policies for Admission Control in Heterogeneous Wireless Networks","year":2007,"lang":"en","type":"article","venue":"Mobile Networks and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Wireless network; Quality of service; Mathematical optimization; Curse of dimensionality; Markov decision process; Wireless; Computational complexity theory; Distributed computing; Base station; Admission control; Computer network; Algorithm; Telecommunications; Artificial intelligence; Mathematics; Markov process","score_opus":0.0034790498066419144,"score_gpt":0.22398664157628037,"score_spread":0.22050759176963847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010592117","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":[0.05216113,0.0023065826,0.943577,0.000009858652,0.00010455873,0.0015745076,0.000011740534,0.00018995265,0.00006465755],"genre_scores_gemma":[0.99692714,0.00036729503,0.0007922687,0.00007521075,0.00044435402,0.0012661291,0.00006309263,0.000052803964,0.000011677709],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891514,0.000010081323,0.00032931785,0.00024221119,0.00007052591,0.00043273155],"domain_scores_gemma":[0.99939024,0.00017520084,0.000055703298,0.00020865917,0.000041186006,0.00012897642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014104454,0.00018853384,0.00021478713,0.000079242636,0.00014399631,0.000030242065,0.00010030052,0.00016155686,0.000004751076],"category_scores_gemma":[0.0000022813317,0.00019158499,0.000043293083,0.00033284342,0.000045195397,0.000026337202,0.000019169269,0.00015156949,4.5779547e-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":[0.000021152846,0.00002073589,0.0002524033,0.00001359618,0.0000091658185,4.6680753e-7,0.000015259182,0.948603,0.00014470828,0.0005175097,0.0000675476,0.050334454],"study_design_scores_gemma":[0.00060870365,0.000023639586,0.00064958434,0.00002204062,0.000012557547,0.0000043719238,0.000026847807,0.9937719,0.000079219586,0.00008084222,0.0045249253,0.0001953374],"about_ca_topic_score_codex":0.0000033568692,"about_ca_topic_score_gemma":0.000051970634,"teacher_disagreement_score":0.94476604,"about_ca_system_score_codex":0.00006703517,"about_ca_system_score_gemma":0.000005532206,"threshold_uncertainty_score":0.7812609},"labels":[],"label_agreement":null},{"id":"W2011260757","doi":"10.1109/imoc.2011.6169356","title":"New analytic results for the incomplete Toronto function and incomplete Lipschitz-Hankel Integrals","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":10,"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":"Bessel function; Function (biology); Lipschitz continuity; Mathematics; Computer science; Discrete mathematics; Algorithm; Combinatorics; Pure mathematics; Mathematical analysis","score_opus":0.029873995772781877,"score_gpt":0.22022643680676793,"score_spread":0.19035244103398605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011260757","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":[0.0013717107,0.0006842426,0.9863873,0.00006279684,0.00038386116,0.00041240916,0.000010851563,0.0003226731,0.010364128],"genre_scores_gemma":[0.894942,0.00032801126,0.103142075,0.0001203148,0.0003342004,0.00004930115,0.000035174828,0.000053620508,0.0009953142],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920297,0.000013677371,0.00027781367,0.00019712748,0.00008469398,0.0002237414],"domain_scores_gemma":[0.99937797,0.0001716087,0.000047953792,0.00027600056,0.000044727807,0.00008172664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013972445,0.00016911358,0.00016488553,0.00003235249,0.000102860045,0.000030807347,0.00012713781,0.00006274048,0.00009110793],"category_scores_gemma":[0.000036586738,0.00012239265,0.00004625357,0.00011271742,0.000023425791,0.0003137706,0.000038404884,0.000083187144,0.000007992295],"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":[0.0012449322,0.00003903133,0.00058918673,0.00014920151,0.00055626826,0.0000014304449,0.0024083436,0.5782036,0.001086853,0.04854805,0.055340298,0.31183276],"study_design_scores_gemma":[0.0011970046,0.00014013029,0.006035923,0.00003450598,0.00008055696,0.0000032417358,0.00024694606,0.9761281,0.00020724199,0.0053371713,0.010306653,0.00028250788],"about_ca_topic_score_codex":0.00047015198,"about_ca_topic_score_gemma":0.0024414633,"teacher_disagreement_score":0.8935703,"about_ca_system_score_codex":0.000074064155,"about_ca_system_score_gemma":0.000009460904,"threshold_uncertainty_score":0.49910277},"labels":[],"label_agreement":null},{"id":"W2012071412","doi":"10.1109/glocom.2013.6831630","title":"An efficient cross layer design for OFDMA-based wireless networks with channel reuse","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Physical layer; Wireless network; Computer network; Scheduling (production processes); Mathematical optimization; Network topology; Wireless ad hoc network; Relay; Convex optimization; Wireless; Node (physics); Optimization problem; Channel allocation schemes; Channel (broadcasting); Distributed computing; Power (physics); Regular polygon; Algorithm; Telecommunications; Mathematics; Engineering","score_opus":0.013633648311833946,"score_gpt":0.23122977967115912,"score_spread":0.21759613135932518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012071412","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":[0.09506906,0.00006762661,0.9028943,0.00003604807,0.00015926144,0.000986143,0.0000032785401,0.00071040523,0.00007384275],"genre_scores_gemma":[0.8645645,0.000013612567,0.13429606,0.00010243791,0.00013757021,0.00067151216,0.000031170464,0.00011116281,0.00007198899],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989274,0.000022381319,0.00020458108,0.00026480644,0.00012494807,0.00045584937],"domain_scores_gemma":[0.99904734,0.000114496026,0.00004259232,0.0004903315,0.00017040438,0.00013483466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010282189,0.0002315721,0.00019083648,0.00005920192,0.00010780335,0.00010451407,0.00025311136,0.00012039298,0.00006252022],"category_scores_gemma":[0.0000073695705,0.00019293006,0.000033769164,0.000237968,0.0000403906,0.00022869541,0.000014976547,0.00010508741,0.000010490406],"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":[0.000046270492,0.00004383753,0.000083004146,0.000024297568,0.000016851933,7.374875e-7,0.000043070588,0.99742097,0.00039169137,0.00006797041,0.0007948264,0.0010664915],"study_design_scores_gemma":[0.0008163152,0.00010941289,0.00018493559,0.000038595397,0.000011055398,7.30939e-7,0.000016976817,0.99264723,0.005805871,0.000028917788,0.000033626668,0.00030634162],"about_ca_topic_score_codex":0.000009960257,"about_ca_topic_score_gemma":0.0000070193123,"teacher_disagreement_score":0.7694954,"about_ca_system_score_codex":0.00006064704,"about_ca_system_score_gemma":0.000015044481,"threshold_uncertainty_score":0.78674597},"labels":[],"label_agreement":null},{"id":"W2012663563","doi":"10.1109/vtcfall.2014.6965881","title":"Analysis of Practical Frequency Selective Scheduling Algorithms in LTE Networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Aboriginal Affairs Northern Dev Canada","funders":"","keywords":"Computer science; Orthogonal frequency-division multiple access; Scheduling (production processes); Orthogonal frequency-division multiplexing; Algorithm; Coding (social sciences); Frequency-division multiple access; Proportionally fair; Limiting; Dynamic priority scheduling; LTE Advanced; Telecommunications link; Round-robin scheduling; Real-time computing; Computer network; Mathematical optimization; Mathematics; Engineering; Quality of service","score_opus":0.0077077253216322,"score_gpt":0.2501279782280711,"score_spread":0.2424202529064389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012663563","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":[0.016818509,0.00007199065,0.97868294,0.000015093754,0.00007026592,0.00007116864,5.7321364e-7,0.00012689889,0.0041425354],"genre_scores_gemma":[0.78149223,0.000062595864,0.2183409,0.00001290107,0.000045784374,0.0000076021047,0.000013309272,0.000016818449,0.000007871962],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923635,0.000039752937,0.00026957568,0.00014983688,0.0000995823,0.00020489004],"domain_scores_gemma":[0.9995087,0.00019634244,0.000045378954,0.00014810699,0.0000608405,0.000040636256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017698114,0.00010411033,0.00026468176,0.0002585411,0.000015304257,0.000008393995,0.000056276735,0.000092727634,0.00003837005],"category_scores_gemma":[0.00008276767,0.00010812336,0.00005245834,0.0017867219,0.000018604114,0.00019236669,0.000012775926,0.00019018275,0.0000021166352],"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":[0.0000024817348,0.000013351087,0.0074414327,0.000004352375,0.00015418707,7.6041783e-7,0.000041145035,0.98681015,0.000080411104,0.0016230312,0.0000071993704,0.0038215],"study_design_scores_gemma":[0.00013111379,0.000013035998,0.0040646293,0.000009835396,0.000100563826,4.6969416e-7,0.000018382332,0.9951053,0.0002279779,0.0002076409,0.000007706967,0.00011329015],"about_ca_topic_score_codex":0.000021085363,"about_ca_topic_score_gemma":0.00012325226,"teacher_disagreement_score":0.7646737,"about_ca_system_score_codex":0.00006753277,"about_ca_system_score_gemma":0.000007595075,"threshold_uncertainty_score":0.44091424},"labels":[],"label_agreement":null},{"id":"W2013356207","doi":"10.1109/glocomw.2014.7063566","title":"Near-optimal resource block and power allocation mechanisms in uplink for LTE and LTE-Advanced","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Telecommunications link; LTE Advanced; Computer science; Resource allocation; Throughput; Base station; Computer network; 3rd Generation Partnership Project 2; Heuristic; System-level simulation; Wireless; Telecommunications; Simulation","score_opus":0.003551996904350259,"score_gpt":0.19426465610187862,"score_spread":0.19071265919752836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013356207","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":[0.14874667,0.00010931813,0.8499617,0.000086688786,0.000051023424,0.0002816312,9.70844e-7,0.00016490855,0.00059710955],"genre_scores_gemma":[0.76849693,0.000045306,0.2311782,0.00006122797,0.000019157673,0.000038511902,0.000009853099,0.000036336365,0.00011448921],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993692,0.000010318629,0.00016721745,0.00019838299,0.000056839774,0.00019801607],"domain_scores_gemma":[0.9996843,0.0000863996,0.00002488948,0.00012585951,0.000024810293,0.00005376099],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012296598,0.00012787388,0.00013861568,0.000050173192,0.000051380106,0.00003353149,0.000043338074,0.000080685066,0.000005771409],"category_scores_gemma":[0.000030163339,0.00013534496,0.000012126551,0.00010291245,0.000021427366,0.00016133052,0.000023600485,0.00007530225,0.000001586118],"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":[0.000020656287,0.000005365772,0.000044021457,0.00002168815,0.0000044390677,1.9858548e-7,0.00012234438,0.98583084,0.0019192473,0.0036579387,0.000057555317,0.008315687],"study_design_scores_gemma":[0.0007153988,0.000060550174,0.00024268686,0.00002190546,0.000004878074,0.0000026724229,0.000037382546,0.993819,0.0017806706,0.0008628984,0.0022838674,0.0001681195],"about_ca_topic_score_codex":0.0000015679426,"about_ca_topic_score_gemma":0.00001229673,"teacher_disagreement_score":0.61975026,"about_ca_system_score_codex":0.000025642565,"about_ca_system_score_gemma":0.0000031872542,"threshold_uncertainty_score":0.5519207},"labels":[],"label_agreement":null},{"id":"W2013368588","doi":"10.1109/fgcn.2007.19","title":"A Model-Driven Simulation for Performance Evaluation of 1xEV-DO","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Radio signal; Radio access network; Radio resource management; Quality of service; Computer network; Wireless; Wireless network; Radio networks; Cellular network; Remote radio head; Radio access technology; Mobile radio; Cellular radio; Quality (philosophy); Telecommunications; Radio frequency; Cognitive radio; User equipment; Mobile station; Base station","score_opus":0.03964337164961613,"score_gpt":0.30316079210131575,"score_spread":0.2635174204516996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013368588","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":[0.2564104,0.000031570795,0.74107236,0.0000012803051,0.000049191047,0.0003168712,0.0000011859225,0.00007911032,0.0020380216],"genre_scores_gemma":[0.90815175,0.000014187607,0.09170889,0.0000038273297,0.00003705271,0.000020248155,0.00002018771,0.000017878623,0.000025983136],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994424,0.0000040121568,0.00019105969,0.00007253752,0.00017551843,0.0001144779],"domain_scores_gemma":[0.99956644,0.000058621667,0.00003490639,0.00009475344,0.00022658308,0.000018677783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034834992,0.00006231263,0.00007140992,0.000058469857,0.000021579903,0.0000034787604,0.000036459573,0.000045275265,0.000014962832],"category_scores_gemma":[0.000022136783,0.00006518975,0.000021780283,0.000116466734,0.0000070659617,0.00019021184,0.000004473598,0.000027116139,0.0000015555221],"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":[0.00001732358,0.000004743488,0.00013561557,0.00001912627,0.0000055168907,6.3415855e-9,0.00008026304,0.94215083,0.00066531956,0.00024061269,0.00001720549,0.05666344],"study_design_scores_gemma":[0.00060338026,0.000014628081,0.00035320938,0.000013374324,0.000016995014,7.8273274e-8,0.000010879859,0.9952015,0.0034874156,0.00019634512,0.000029233044,0.00007291254],"about_ca_topic_score_codex":1.8875406e-7,"about_ca_topic_score_gemma":0.0000034825641,"teacher_disagreement_score":0.6517413,"about_ca_system_score_codex":0.00007395094,"about_ca_system_score_gemma":0.000008882741,"threshold_uncertainty_score":0.2658361},"labels":[],"label_agreement":null},{"id":"W2013379876","doi":"10.1109/iwcmc.2012.6314241","title":"Cross-layer design for cognitive radios with joint AMC and ARQ under delay QoS constraint","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Computer science; Cognitive radio; Link adaptation; Computer network; Quality of service; Underlay; Physical layer; Transmitter; Fading; Nakagami distribution; Automatic repeat request; Spectral efficiency; Network packet; Hybrid automatic repeat request; Channel (broadcasting); Wireless; Telecommunications link; Signal-to-noise ratio (imaging); Telecommunications","score_opus":0.03490155716940948,"score_gpt":0.25701595734834254,"score_spread":0.22211440017893305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013379876","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":[0.030940458,0.00026929576,0.966685,0.0000123459895,0.00011690894,0.000590031,0.000008293734,0.00020727685,0.0011704112],"genre_scores_gemma":[0.84289014,0.00003732104,0.15662317,0.00007609428,0.00012312422,0.00008521842,0.000012052207,0.000045509143,0.00010736957],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993289,0.000012853483,0.00014057741,0.00012926114,0.000069541566,0.00031882824],"domain_scores_gemma":[0.9995457,0.0001735193,0.000026826814,0.00007443685,0.0000708672,0.00010867788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000105589745,0.00015561644,0.00014817923,0.00003760026,0.000063218715,0.000034295517,0.000025691146,0.000068677415,0.00007207549],"category_scores_gemma":[0.000015522075,0.00012926385,0.000019464736,0.00007215785,0.00009367635,0.0002979647,0.000009378438,0.00007735169,0.0000062655154],"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":[0.00005093717,0.000016729105,0.00075269863,0.000027567312,0.00007840103,0.000001053679,0.00017446786,0.9929581,0.0005804752,0.0019321023,0.00023737011,0.003190041],"study_design_scores_gemma":[0.0030492474,0.00016067819,0.0031028898,0.00010319549,0.000090083675,0.00010389334,0.000516435,0.96162236,0.029977309,0.00029673532,0.00030693947,0.0006702556],"about_ca_topic_score_codex":0.0000010829202,"about_ca_topic_score_gemma":0.0000026669725,"teacher_disagreement_score":0.8119497,"about_ca_system_score_codex":0.000044779586,"about_ca_system_score_gemma":0.000011288739,"threshold_uncertainty_score":0.5271227},"labels":[],"label_agreement":null},{"id":"W2013474209","doi":"10.1109/iwqos.2010.5542742","title":"Streaming scalable video over WiMAX networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Multicast; WiMAX; Computer network; Scalability; Broadcasting (networking); Wireless broadband; Wireless network; Optimization problem; Wireless; Distributed computing; Algorithm; Telecommunications","score_opus":0.0027017211936534616,"score_gpt":0.18841566741478308,"score_spread":0.1857139462211296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013474209","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":[0.059291076,0.00009004496,0.8970661,0.000012583884,0.00086773233,0.00009741,8.827117e-7,0.0008529468,0.041721214],"genre_scores_gemma":[0.96600455,0.00006140655,0.03295199,0.00004595205,0.00032057826,0.000010185247,0.000013161306,0.000049565544,0.0005426208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994043,0.0000038216594,0.00013086513,0.00012661585,0.00007789411,0.00025647218],"domain_scores_gemma":[0.99964494,0.00004177236,0.0000150859205,0.00021271846,0.000019080606,0.00006638338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004573098,0.00011738943,0.000099003904,0.000035806905,0.000046464247,0.000032427895,0.00008653738,0.000101706726,0.000575942],"category_scores_gemma":[0.000008993183,0.00011789878,0.000025087169,0.00016346142,0.000019255272,0.0002533564,0.000022549666,0.0002484793,0.00003353717],"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":[0.0000012414987,0.0000044033595,0.0009856904,0.000004264564,0.0000068858317,0.000001153288,0.000007610822,0.97826654,0.0011966849,0.00075807644,0.0020652052,0.016702233],"study_design_scores_gemma":[0.00013953165,0.0000037808811,0.0013278353,0.00000770387,0.0000040907885,0.0000021205421,0.0000047527687,0.99301344,0.0009230014,0.00011736935,0.0043067993,0.00014957452],"about_ca_topic_score_codex":0.000007403902,"about_ca_topic_score_gemma":0.000080453516,"teacher_disagreement_score":0.9067135,"about_ca_system_score_codex":0.000020633244,"about_ca_system_score_gemma":0.0000036898077,"threshold_uncertainty_score":0.63061607},"labels":[],"label_agreement":null},{"id":"W2013794162","doi":"10.1007/s11390-008-9169-0","title":"Uplink Scheduling for Supporting Real Time Voice Traffic in IEEE 802.16 Backhaul Networks","year":2008,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Network packet; Scheduling (production processes); Real-time computing; Telecommunications link; Latency (audio); Real-time communication; Voice over IP; Telecommunications; Operating system; The Internet","score_opus":0.007132869994282196,"score_gpt":0.22649981576444358,"score_spread":0.2193669457701614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013794162","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":[0.47322193,0.00014543264,0.526177,0.00010360057,0.00022878493,0.000055547825,9.3603084e-8,0.00005794174,0.000009657214],"genre_scores_gemma":[0.8240569,0.00045353099,0.17526604,0.000019032646,0.00018790673,0.000001972471,3.3460273e-7,0.000011399436,0.0000028836548],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898815,0.0000054751367,0.000409782,0.00014393443,0.00011863689,0.0003340495],"domain_scores_gemma":[0.9994145,0.000062963976,0.00014059631,0.00010341333,0.0002216531,0.000056874353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004836946,0.00010091747,0.00023516663,0.0005332539,0.00011750903,0.00002251409,0.0002849377,0.00011938777,9.698277e-7],"category_scores_gemma":[0.00003165786,0.00009689043,0.000025598692,0.0010133005,0.00022379059,0.00040253773,0.00003735764,0.00026805725,9.668911e-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":[0.0000046054497,0.000008576502,0.00020971705,0.0000057643642,0.0000041742373,0.000016812963,0.00004468944,0.916309,0.0007893508,0.000057063964,0.00008742028,0.082462855],"study_design_scores_gemma":[0.00036984953,0.00011625295,0.0001225748,0.000050625844,0.000003568425,0.00042879765,0.0000097477405,0.99784905,0.0006549456,0.00022127802,0.00007513059,0.00009820248],"about_ca_topic_score_codex":3.061056e-7,"about_ca_topic_score_gemma":0.0000017707378,"teacher_disagreement_score":0.35091096,"about_ca_system_score_codex":0.00009236931,"about_ca_system_score_gemma":0.000071583185,"threshold_uncertainty_score":0.39510772},"labels":[],"label_agreement":null},{"id":"W2014103891","doi":"10.1145/1280940.1280957","title":"Efficient resource allocation in clustered wireless mesh networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Subcarrier; Computer network; Resource allocation; Quality of service; Network packet; Scheduling (production processes); Wireless; Fading; Maximum throughput scheduling; Distributed computing; Channel (broadcasting); Dynamic priority scheduling; Mathematical optimization; Round-robin scheduling; Orthogonal frequency-division multiplexing; Telecommunications","score_opus":0.005979235814960337,"score_gpt":0.21052532667863283,"score_spread":0.20454609086367248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014103891","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":[0.12793328,0.00008214175,0.8632275,0.000019063998,0.00015249469,0.00017997128,2.0227493e-7,0.0003598416,0.008045503],"genre_scores_gemma":[0.9942598,0.000030791376,0.005329007,0.00006067387,0.00011041255,0.000009009205,0.000021915566,0.000040554823,0.00013783459],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990787,0.000014895537,0.00028937086,0.00015891546,0.00012181076,0.00033633807],"domain_scores_gemma":[0.99962646,0.00007654592,0.000026997368,0.00018639678,0.000023426734,0.000060151782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027925652,0.00012672108,0.0001223104,0.00012010097,0.000029290186,0.000013854134,0.000095708114,0.00010937356,0.000020692287],"category_scores_gemma":[0.0000069714956,0.0001366806,0.000021557387,0.0004875529,0.000017033984,0.000043054533,0.000022381935,0.0001539679,0.000010109863],"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":[0.000013519999,0.000014319009,0.00024416737,0.00000937294,0.0000037993,0.0000033800577,0.00010183452,0.9848366,0.00015271074,0.0009455578,0.00023578249,0.013438955],"study_design_scores_gemma":[0.0003062972,0.000006579551,0.0014780379,0.000028017144,0.0000022942158,0.000001857182,0.00008435679,0.9969544,0.00059813564,0.000008350254,0.00037594492,0.00015573236],"about_ca_topic_score_codex":0.000005358449,"about_ca_topic_score_gemma":0.00010630502,"teacher_disagreement_score":0.8663265,"about_ca_system_score_codex":0.00015839736,"about_ca_system_score_gemma":0.0000037440193,"threshold_uncertainty_score":0.5573673},"labels":[],"label_agreement":null},{"id":"W2014562508","doi":"10.1109/chinacom.2007.4469576","title":"A Power Adjustment Scheme for Improving Outage Probability in a CDMA System","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Outage probability; Computer science; Coding (social sciences); Interference (communication); Power (physics); Channel (broadcasting); Code division multiple access; Bit error rate; Transmitter power output; Power control; Code rate; Scheme (mathematics); Electronic engineering; Control theory (sociology); Fading; Statistics; Algorithm; Mathematics; Telecommunications; Decoding methods; Transmitter; Engineering; Control (management)","score_opus":0.007100980526124235,"score_gpt":0.21408713530425819,"score_spread":0.20698615477813395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014562508","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":[0.100463346,0.00013293659,0.8943191,0.0000061213877,0.00023827629,0.0008800504,0.0000024849417,0.0004843297,0.0034733124],"genre_scores_gemma":[0.8495662,0.0000013579282,0.15018727,0.000010528737,0.000046019548,0.00009162873,0.000005394794,0.000028569524,0.00006300901],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991538,0.000005368598,0.00028078613,0.00017174416,0.000079530015,0.00030879895],"domain_scores_gemma":[0.9996666,0.000051804527,0.000025797699,0.00017351848,0.000034332217,0.000047995094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029506188,0.00011729215,0.00013750781,0.000064067026,0.000019405757,0.000009478193,0.00006252067,0.00007269918,0.000011347769],"category_scores_gemma":[0.000023911862,0.00011549096,0.00003340575,0.00016237164,0.0000082952265,0.00012850613,0.000018270293,0.00007348505,0.000004524076],"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":[0.000043159987,0.00004208887,0.0010259467,0.00065090664,0.000012098707,0.0000036604797,0.00023180322,0.9779606,0.0032735665,0.006984599,0.000058734444,0.009712822],"study_design_scores_gemma":[0.00059623015,0.000029646146,0.0011844634,0.00004751021,0.0000031681755,0.0000018213655,0.00024666317,0.99532133,0.002074305,0.000071449016,0.00023928373,0.000184153],"about_ca_topic_score_codex":0.000005462672,"about_ca_topic_score_gemma":0.000070569775,"teacher_disagreement_score":0.7491029,"about_ca_system_score_codex":0.00043160148,"about_ca_system_score_gemma":0.000008191459,"threshold_uncertainty_score":0.47095847},"labels":[],"label_agreement":null},{"id":"W2015594166","doi":"10.1109/isspit.2006.270891","title":"Optimum Throughput Constrained Opportunistic Scheduling in Cellular Data Networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Scheduling (production processes); Exploit; Fading; Telecommunications link; Fair-share scheduling; Round-robin scheduling; Computer network; Dynamic priority scheduling; Distributed computing; Channel (broadcasting); Quality of service; Mathematical optimization; Mathematics","score_opus":0.02037556615116609,"score_gpt":0.2256037279891536,"score_spread":0.2052281618379875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015594166","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":[0.0034209252,0.00042019153,0.981691,0.000029845212,0.00026135222,0.00016876386,0.000011319433,0.0004791685,0.013517423],"genre_scores_gemma":[0.8552443,0.00014129202,0.14327724,0.000027269718,0.00023601328,0.0000071577906,0.00089526933,0.000050061353,0.0001214238],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888736,0.000016958473,0.00035029094,0.0002797951,0.00010516318,0.000360407],"domain_scores_gemma":[0.9992876,0.00006859585,0.00003354318,0.0005389082,0.000020557572,0.000050782484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014671589,0.00017904103,0.00019533653,0.00006743069,0.000038387603,0.000037225425,0.00028277485,0.00011082148,0.000110388835],"category_scores_gemma":[0.000013491448,0.00019773748,0.000018298144,0.00030523812,0.00004839865,0.00032935877,0.00008754803,0.00019560393,0.000012179253],"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":[0.0000022151053,0.000013990838,0.00028266993,0.000012430531,0.000006392124,0.000030187552,0.0000042817214,0.9933192,0.00027100614,0.00396376,0.0004869722,0.0016069075],"study_design_scores_gemma":[0.0003360967,0.0000046255955,0.000060726066,0.00003264207,0.0000078370895,0.0000036815632,0.000023393917,0.99838597,0.00007486237,0.00032873728,0.0005156074,0.00022580537],"about_ca_topic_score_codex":0.000021062415,"about_ca_topic_score_gemma":0.00006482727,"teacher_disagreement_score":0.85182333,"about_ca_system_score_codex":0.000057070178,"about_ca_system_score_gemma":0.000018262763,"threshold_uncertainty_score":0.80635005},"labels":[],"label_agreement":null},{"id":"W2016739648","doi":"10.1109/glocom.2006.792","title":"WLC30-6: Admission Control in Power Constrained OFDM/TDMA Wireless Mesh Networks","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Computer science; Wireless mesh network; Router; Computer network; Network packet; Sleep mode; Mesh networking; Switched mesh; Markov decision process; Time division multiple access; Shared mesh; Markov process; Power (physics); Wireless; Wireless network; Power consumption; Telecommunications","score_opus":0.002707240748214062,"score_gpt":0.18765943726305678,"score_spread":0.1849521965148427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016739648","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":[0.108792014,0.00067011156,0.87600493,0.00014251577,0.00081817206,0.000497266,0.000021168136,0.00077037106,0.012283451],"genre_scores_gemma":[0.99754107,0.000074397525,0.0018196634,0.0001062669,0.00018740671,0.000028327555,0.000067085544,0.000059703107,0.00011605523],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864924,0.000041728923,0.00041624272,0.0002489458,0.00015326633,0.0004905883],"domain_scores_gemma":[0.9994652,0.00008334704,0.000061688275,0.00024895105,0.000041284013,0.000099488425],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011395513,0.00025459606,0.00032025244,0.00009671079,0.00005178538,0.000035179168,0.00015372402,0.00019800392,0.00018952714],"category_scores_gemma":[0.000011419183,0.00027383506,0.00006275745,0.0003615177,0.0000458057,0.000187419,0.000022199267,0.00025112942,0.000024049781],"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":[0.00002763826,0.0000335536,0.0029246807,0.000011199511,0.000011868203,0.0000262343,0.000019274887,0.9857362,0.00047524384,0.0021455442,0.0039271396,0.0046614343],"study_design_scores_gemma":[0.0016898426,0.000020861933,0.0039617415,0.0000785458,0.000009253741,0.0000087357685,0.00002359756,0.9912977,0.00015118181,0.00032386862,0.0021086615,0.0003259996],"about_ca_topic_score_codex":0.000034007877,"about_ca_topic_score_gemma":0.00012094536,"teacher_disagreement_score":0.88874906,"about_ca_system_score_codex":0.00015470538,"about_ca_system_score_gemma":0.000020591004,"threshold_uncertainty_score":0.9999714},"labels":[],"label_agreement":null},{"id":"W2017442621","doi":"10.1109/spawc.2006.346392","title":"Joint Adaptive Transmission and Combining with Optimized Rate and Power Allocation","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Victoria","funders":"","keywords":"Fading; Computer science; Link adaptation; Power control; Transmission (telecommunications); Joint (building); Cooperative diversity; Power (physics); Spectral efficiency; Throughput; Diversity combining; Adaptation (eye); Channel (broadcasting); Control theory (sociology); Computer network; Telecommunications; Control (management); Wireless; Engineering; Artificial intelligence","score_opus":0.00519592084753263,"score_gpt":0.17236650696913747,"score_spread":0.16717058612160485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017442621","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":[0.05488476,0.0003143969,0.94051677,0.000052490417,0.000017913633,0.00014540798,5.4112513e-7,0.00020241324,0.0038653098],"genre_scores_gemma":[0.8526992,0.00018398158,0.14694238,0.000014497309,0.000009087778,0.000008751022,0.000011759186,0.000023248454,0.000107089036],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995932,0.000013129202,0.00011176657,0.00012152421,0.000050466624,0.000109891],"domain_scores_gemma":[0.99984014,0.000024447698,0.000018646193,0.0000551585,0.000024949137,0.000036675567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005118796,0.00010515707,0.00011065268,0.000037387195,0.000044967008,0.000021448928,0.000014452059,0.000038813436,0.000017053628],"category_scores_gemma":[0.0000011414736,0.00008676564,0.0000066559633,0.00007978159,0.00002641739,0.00017831667,0.000005461783,0.000058861286,8.9615475e-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":[0.00003856204,0.0000057706266,0.000037239028,0.000008229838,0.0000076242254,0.0000012597724,0.000085566295,0.99453956,0.00217744,0.000950081,0.00007281571,0.0020758323],"study_design_scores_gemma":[0.001059765,0.000053455446,0.0014538902,0.000048013,0.000010417347,0.0000056581816,0.000056287085,0.9939571,0.0028803768,0.0002031842,0.00012204399,0.0001497983],"about_ca_topic_score_codex":0.000008042668,"about_ca_topic_score_gemma":0.0000040639757,"teacher_disagreement_score":0.7978144,"about_ca_system_score_codex":0.000015997817,"about_ca_system_score_gemma":0.0000035193596,"threshold_uncertainty_score":0.35382003},"labels":[],"label_agreement":null},{"id":"W2017761501","doi":"10.1002/wcm.771","title":"Call admission control with opportunistic scheduling scheme","year":2009,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Base station; Computer science; Scheduling (production processes); Computer network; Queue; Coding (social sciences); Admission control; Real-time computing; Wireless; Queueing theory; Telecommunications; Engineering; Statistics; Mathematics; Operations management","score_opus":0.010842017568582867,"score_gpt":0.2420061925269504,"score_spread":0.23116417495836755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017761501","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":[0.17295635,0.002428028,0.8223361,0.00014426022,0.000042991644,0.00037460768,0.000004609191,0.0005746445,0.0011384324],"genre_scores_gemma":[0.90030974,0.001121312,0.09833662,0.0000802228,0.000040486346,0.000020741523,0.000047478745,0.000029810768,0.000013566483],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991607,0.0000399681,0.0002744774,0.00017767162,0.000098565026,0.00024861304],"domain_scores_gemma":[0.9988646,0.00014118475,0.000076584976,0.0006969096,0.00008599306,0.00013473211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012362811,0.00017984577,0.0002208782,0.00006947977,0.00035483245,0.00005817352,0.00029973424,0.00006987378,0.000003456013],"category_scores_gemma":[0.000008942248,0.00017436367,0.000024014405,0.00021655882,0.00007635114,0.00013388784,0.00006919088,0.0002694374,0.000002108515],"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":[0.000010224579,0.000051502826,0.0004784112,0.000027220874,0.000023883193,0.0000026697912,0.00023020012,0.75692654,0.002978418,0.0027980653,0.000024108702,0.23644876],"study_design_scores_gemma":[0.0005296068,0.00007318602,0.00029716844,0.00020080605,0.000015776193,0.00001576316,0.0000859015,0.99688005,0.00006471529,0.000044936143,0.0015713874,0.0002206916],"about_ca_topic_score_codex":0.0000024514713,"about_ca_topic_score_gemma":0.0000029118949,"teacher_disagreement_score":0.7273534,"about_ca_system_score_codex":0.00004500906,"about_ca_system_score_gemma":0.00002412855,"threshold_uncertainty_score":0.7110344},"labels":[],"label_agreement":null},{"id":"W2019462839","doi":"10.1016/j.disc.2008.05.025","title":"Generating asymptotically optimal broadcasting schedules to minimize average waiting time","year":2008,"lang":"en","type":"article","venue":"Discrete Mathematics","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Schedule; Asymptotically optimal algorithm; Scheduling (production processes); Mathematical optimization; Computer science; Broadcasting (networking); Block (permutation group theory); Mathematics; Heuristic; Algorithm; Combinatorics; Computer network","score_opus":0.01167587249279253,"score_gpt":0.21394774198053612,"score_spread":0.2022718694877436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019462839","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":[0.31937376,0.00005143059,0.6774905,0.000023061346,0.00006992235,0.00018148363,0.0000071737254,0.0004774008,0.002325296],"genre_scores_gemma":[0.32977685,0.00001724827,0.66963774,0.00004219933,0.00020674698,0.000022860162,0.000024030243,0.0001036784,0.00016867086],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983976,0.000022313947,0.00054013066,0.00025387201,0.00028782076,0.00049825275],"domain_scores_gemma":[0.9991558,0.00021302188,0.000081416765,0.0003029099,0.00007481133,0.00017204594],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015084636,0.00030062214,0.00035455375,0.00009039877,0.00024038185,0.0000649663,0.00020230426,0.00010175902,0.00009155199],"category_scores_gemma":[0.00028207182,0.00031355684,0.00007890798,0.000284646,0.00004264506,0.00020654376,0.000098503544,0.00020637683,0.0002225524],"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":[0.0000025758143,0.000013835901,0.000032468997,0.00008290185,0.000027386082,0.000020084784,0.0010218417,0.9910415,0.0059251636,0.00077690644,0.00008514064,0.0009702421],"study_design_scores_gemma":[0.00019955427,0.000016845925,0.000017468778,0.0001801617,0.0000150142105,0.00004712101,0.000112262576,0.9964518,0.0024501558,0.000090616086,0.000046602956,0.00037242926],"about_ca_topic_score_codex":4.608469e-7,"about_ca_topic_score_gemma":2.4450952e-7,"teacher_disagreement_score":0.010403098,"about_ca_system_score_codex":0.00007418536,"about_ca_system_score_gemma":0.000016815879,"threshold_uncertainty_score":0.99993163},"labels":[],"label_agreement":null},{"id":"W2020130667","doi":"10.1109/iscc.2013.6755024","title":"Exploiting multiuser diversity for OFDMA next generation wireless networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Ottawa","funders":"","keywords":"Computer science; Computer network; Orthogonal frequency-division multiple access; Quality of service; WiMAX; Scheduling (production processes); Interoperability; Frequency-division multiple access; Wireless network; Exploit; Orthogonal frequency-division multiplexing; Throughput; Cellular network; Next-generation network; Wireless; Telecommunications; Engineering; The Internet","score_opus":0.03838126574831443,"score_gpt":0.2064653111252781,"score_spread":0.16808404537696367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020130667","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":[0.24054854,0.00008374537,0.75803316,0.00002770009,0.0003173855,0.00037043908,0.00000129323,0.00040077552,0.00021696332],"genre_scores_gemma":[0.9612485,0.00020201289,0.03748107,0.000084566826,0.000509617,0.00017762838,0.000055217082,0.0000428008,0.0001985804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993431,0.000009182212,0.00015872272,0.00015557282,0.000076377546,0.0002570631],"domain_scores_gemma":[0.9996381,0.00005309759,0.000030187435,0.0001236244,0.00009518628,0.000059798527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004339431,0.00013093655,0.000119113836,0.000036068443,0.00020928944,0.00005995893,0.00009390351,0.000088908986,0.00014132881],"category_scores_gemma":[0.0000073615106,0.00013694118,0.000041177496,0.000111346344,0.000011854226,0.0007445335,0.00006705911,0.0000741945,0.00001817478],"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":[0.0000013534905,0.0000060249886,0.00066220073,0.000011697665,0.000014239578,1.286262e-7,0.00007382665,0.95587844,0.0033663658,0.00020418681,0.0034932715,0.03628824],"study_design_scores_gemma":[0.00026742747,0.0000069205466,0.0002445791,0.000010844824,0.000008283256,2.772905e-7,0.00006907496,0.9971113,0.0019285395,0.00004143152,0.00013469289,0.00017661911],"about_ca_topic_score_codex":0.00002849189,"about_ca_topic_score_gemma":0.000028550356,"teacher_disagreement_score":0.72069997,"about_ca_system_score_codex":0.000056364875,"about_ca_system_score_gemma":0.000002300967,"threshold_uncertainty_score":0.5584299},"labels":[],"label_agreement":null},{"id":"W2020902546","doi":"10.1007/s11277-010-0029-1","title":"CSI-Based Resource Allocation for OFDM Downlink Broadband Multimedia Services in Cellular Systems","year":2010,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Computer science; Orthogonal frequency-division multiplexing; Channel state information; Fading; Telecommunications link; Resource allocation; Throughput; Computer network; Interference (communication); Wireless; Multiplexing; Wireless broadband; Channel (broadcasting); Telecommunications; Wireless network","score_opus":0.011885299747954728,"score_gpt":0.2359899756665547,"score_spread":0.22410467591859995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020902546","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":[0.7044109,0.0043035075,0.28196427,0.0016798049,0.0009080291,0.002967742,0.00030025092,0.0013206957,0.0021447947],"genre_scores_gemma":[0.97299075,0.00013593669,0.024672015,0.00005156907,0.00013165988,0.0005671037,0.001319948,0.00007506341,0.00005593464],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99881065,0.00007202149,0.0003997269,0.00022999807,0.0001812419,0.00030638737],"domain_scores_gemma":[0.9982126,0.0004516602,0.0001019834,0.0009928864,0.00014598624,0.000094897056],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027293217,0.00021852112,0.00024033504,0.00017905446,0.00023105732,0.00007075846,0.0007351293,0.00021157633,0.000010095832],"category_scores_gemma":[0.00002058432,0.00025382696,0.00006662209,0.00037459965,0.00011617599,0.00021540772,0.00006039478,0.0005063306,0.000013044092],"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":[0.000038524697,0.00017535152,0.0012420127,0.00040717586,0.000040141713,8.568292e-7,0.0020809069,0.92886347,0.05327618,0.0017812471,0.00024450207,0.0118496595],"study_design_scores_gemma":[0.0007200007,0.0000112884745,0.0005197366,0.00011700099,0.000017476646,0.000001314371,0.0004033862,0.9845078,0.0010795111,0.000026752965,0.012336547,0.00025917825],"about_ca_topic_score_codex":0.00008760455,"about_ca_topic_score_gemma":0.0010980092,"teacher_disagreement_score":0.26857984,"about_ca_system_score_codex":0.00010060671,"about_ca_system_score_gemma":0.000041505966,"threshold_uncertainty_score":0.9999914},"labels":[],"label_agreement":null},{"id":"W2021198450","doi":"10.1109/ciss.2008.4558650","title":"Appropriate control of wireless networks with flow level dynamics","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Round-robin scheduling; Scheduling (production processes); Network congestion; Upper and lower bounds; Wireless network; Dynamic priority scheduling; Fair-share scheduling; Queue; Rate-monotonic scheduling; Mathematical optimization; Distributed computing; Control theory (sociology); Computer network; Wireless; Mathematics; Network packet; Quality of service; Control (management)","score_opus":0.0074583430464887,"score_gpt":0.16904414705592674,"score_spread":0.16158580400943803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021198450","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":[0.01973928,0.00009379348,0.97782457,0.000009337477,0.00010370845,0.00017399913,0.000009533924,0.00028363237,0.0017621728],"genre_scores_gemma":[0.93703175,0.00019085279,0.06244296,0.000017589182,0.000059149035,0.000014544581,0.000030746374,0.0000530594,0.0001593285],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993124,0.000010699406,0.00020412351,0.0001242727,0.00012495233,0.00022356525],"domain_scores_gemma":[0.9996035,0.00003763118,0.000043145592,0.0001945635,0.00007038734,0.0000507593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003580928,0.0001499023,0.000231346,0.00004098183,0.00004112491,0.0000043118603,0.000095425705,0.0000824961,0.000018418405],"category_scores_gemma":[0.000002467642,0.00012822,0.000029120652,0.00022705593,0.000060534694,0.000119703975,0.000009502161,0.00012294996,0.0000027792908],"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":[0.000022303917,0.000012118285,0.0011076375,0.000014337311,0.000040763745,0.0000050312865,0.000032257,0.9890847,0.000027968557,0.00053358416,0.000059131,0.009060137],"study_design_scores_gemma":[0.0007637131,0.000027336742,0.0005011794,0.000020152345,0.000011122162,0.0000146809125,0.000013619412,0.99828327,0.00015964409,0.000019018793,0.000019715548,0.0001665223],"about_ca_topic_score_codex":0.0000056809477,"about_ca_topic_score_gemma":0.000049336933,"teacher_disagreement_score":0.9172925,"about_ca_system_score_codex":0.000053732394,"about_ca_system_score_gemma":0.000011441883,"threshold_uncertainty_score":0.52286595},"labels":[],"label_agreement":null},{"id":"W2021763947","doi":"10.1002/dac.670","title":"Token bank fair queuing: a new scheduling algorithm for wireless multimedia services","year":2004,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":26,"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; Communications Research Centre Canada","funders":"","keywords":"Computer science; Computer network; Fair queuing; Quality of service; Scheduling (production processes); Token bucket; Proportionally fair; Wireless network; Wireless; Network packet; Algorithm; Distributed computing; Round-robin scheduling; Dynamic priority scheduling; Telecommunications","score_opus":0.011750038440506988,"score_gpt":0.26368610992910474,"score_spread":0.25193607148859776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021763947","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":[0.011927,0.00393699,0.9815963,0.0003616308,0.0016349788,0.00023383864,0.00001312413,0.00010137266,0.00019475626],"genre_scores_gemma":[0.77245224,0.0012702196,0.22538048,0.000036818794,0.00071412505,0.000017459837,0.000053721727,0.000040682728,0.0000342611],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985758,0.00004002328,0.0007495357,0.00008793879,0.00039925316,0.00014744414],"domain_scores_gemma":[0.9981733,0.00017057273,0.00046636525,0.00026270153,0.0008231994,0.00010387306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003118668,0.00014914921,0.00024561046,0.00021513429,0.000060524562,0.00014233429,0.0009347277,0.00009382527,0.0000051840443],"category_scores_gemma":[0.000023448129,0.00015363433,0.0001031097,0.00013475964,0.000022248407,0.0007041159,0.000053301348,0.00021922484,0.0000076055],"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":[0.000016154765,0.000023044699,0.00004655588,0.000012817125,0.00015844547,0.0000020900152,0.0007367327,0.95431924,0.00042981643,0.0007400188,0.00008093979,0.043434147],"study_design_scores_gemma":[0.0017384511,0.000026803946,0.00005865798,0.00073921756,0.000020421674,0.000065711094,0.00055357796,0.9876612,0.0009305987,0.00057192234,0.00747024,0.00016318662],"about_ca_topic_score_codex":0.000052412448,"about_ca_topic_score_gemma":0.000017388118,"teacher_disagreement_score":0.7605252,"about_ca_system_score_codex":0.0003345092,"about_ca_system_score_gemma":0.00008030467,"threshold_uncertainty_score":0.62650263},"labels":[],"label_agreement":null},{"id":"W2022056479","doi":"10.1109/pacrim.2007.4313297","title":"Effect of traffic conditions on scheduling algorithms in a cross-layer downlink model","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Scheduling (production processes); Telecommunications link; Round-robin scheduling; Fair-share scheduling; Queueing theory; Traffic model; Algorithm; Dynamic priority scheduling; Rate-monotonic scheduling; Real-time computing; Computer network; Quality of service; Mathematical optimization; Mathematics","score_opus":0.009328938036357289,"score_gpt":0.29353137067670504,"score_spread":0.2842024326403477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022056479","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":[0.5585442,0.000029797604,0.43984678,0.0000023615382,0.000059227263,0.00012408062,0.000003511786,0.00014658265,0.0012434672],"genre_scores_gemma":[0.96884567,0.000019996223,0.030978374,0.00001233465,0.000037072525,0.0000130531325,0.000023400478,0.000030059824,0.00004003323],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992701,0.000011029726,0.00025971365,0.00012725561,0.000106186,0.00022575668],"domain_scores_gemma":[0.99959034,0.00018678067,0.000024491195,0.00013173561,0.000023960249,0.00004267537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002526741,0.00012552907,0.00016637919,0.0001569613,0.000024670231,0.000008746551,0.00006381153,0.000096578486,0.000023059247],"category_scores_gemma":[0.000021346212,0.00012054742,0.000040070718,0.00027888012,0.000026467716,0.00012551172,0.000007782454,0.0001610461,0.000011248876],"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":[0.00002247619,0.000017316057,0.00010047764,0.000031937372,0.000006852152,0.0000026726307,0.000048284845,0.99157923,0.0012281311,0.0002334388,0.0000078163275,0.006721338],"study_design_scores_gemma":[0.00063495105,0.00005901941,0.00020172783,0.0000456596,0.0000041705184,9.782457e-7,0.0000057372295,0.9799239,0.01897646,0.000031192165,0.0000030722047,0.00011311582],"about_ca_topic_score_codex":0.0000011157097,"about_ca_topic_score_gemma":0.000012022835,"teacher_disagreement_score":0.41030148,"about_ca_system_score_codex":0.000072334806,"about_ca_system_score_gemma":0.0000056827744,"threshold_uncertainty_score":0.4915781},"labels":[],"label_agreement":null},{"id":"W2022258728","doi":"10.1109/glocomw.2008.ecp.82","title":"Dynamic Frequency Allocation in Fractional Frequency Reused OFDMA Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":22,"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","funders":"","keywords":"Trunking; Subcarrier; Computer science; Orthogonal frequency-division multiplexing; Telecommunications link; Frequency reuse; Scheduling (production processes); Frequency allocation; Reuse; Computer network; Channel allocation schemes; Interference (communication); Frequency-division multiple access; Orthogonal frequency-division multiple access; Distributed computing; Real-time computing; Mathematical optimization; Telecommunications; Base station; Wireless; Engineering; Mathematics","score_opus":0.007220925678311983,"score_gpt":0.20852168093352474,"score_spread":0.20130075525521277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022258728","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":[0.07562464,0.00079034554,0.9168585,0.00010652364,0.00043068294,0.00020031302,0.0000021531494,0.00055935554,0.0054274676],"genre_scores_gemma":[0.9586755,0.0020723229,0.03872557,0.00005917233,0.00008410473,0.00007186029,0.00009620496,0.000049718023,0.00016552037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903697,0.000021412321,0.00031796395,0.0002009847,0.00014996479,0.00027272053],"domain_scores_gemma":[0.99957955,0.00005431103,0.000041151223,0.00021694714,0.00005381621,0.00005420464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058112666,0.00016391676,0.00015031712,0.00013733712,0.0000669991,0.000008952337,0.00012332041,0.00014872944,0.00026642694],"category_scores_gemma":[0.000019680056,0.00018448937,0.000032902917,0.00049767655,0.000031594205,0.0004523256,0.000011595517,0.00025559112,0.00003170507],"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":[0.0000023321857,0.000020119911,0.007685839,0.0000064317824,0.000009927165,0.000008612081,0.000042973264,0.9890791,0.0007940908,0.00091106794,0.00025263586,0.0011868447],"study_design_scores_gemma":[0.00027274076,0.000008877841,0.024905736,0.000024425652,0.000003227514,0.000011423116,0.000009542692,0.9734164,0.00005479265,0.0010421908,0.000045042463,0.00020562805],"about_ca_topic_score_codex":0.000051870018,"about_ca_topic_score_gemma":0.0002719109,"teacher_disagreement_score":0.88305086,"about_ca_system_score_codex":0.0002715098,"about_ca_system_score_gemma":0.00002490293,"threshold_uncertainty_score":0.75232583},"labels":[],"label_agreement":null},{"id":"W2022464122","doi":"10.1109/isit.2006.261757","title":"Scheduling and Codeword Length Optimization in Time Varying Wireless Networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Fading; Computer science; Scheduling (production processes); Code word; Channel state information; Maximum throughput scheduling; Algorithm; Real-time computing; Round-robin scheduling; Decoding methods; Wireless; Fair-share scheduling; Computer network; Mathematics; Telecommunications; Mathematical optimization; Quality of service","score_opus":0.0038388871983893436,"score_gpt":0.18279426698808202,"score_spread":0.17895537978969267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022464122","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":[0.062886454,0.00042346845,0.93285674,0.000017188248,0.000081769314,0.00014902567,6.0635483e-7,0.00044083467,0.0031439078],"genre_scores_gemma":[0.87908506,0.00035536283,0.12018875,0.000020375197,0.00012677979,0.000013502056,0.00005140653,0.000054551914,0.0001041888],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917173,0.000017215592,0.00025836824,0.00018558369,0.00009664638,0.00027044944],"domain_scores_gemma":[0.9997374,0.000061438695,0.000029322784,0.00011274782,0.000022017908,0.00003707484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000094020266,0.00015742838,0.00016811716,0.000106956984,0.00005033655,0.000052624557,0.00007130637,0.00011713484,0.000040595663],"category_scores_gemma":[0.000004623584,0.0001783315,0.00001531674,0.00035495154,0.000021289312,0.0003113676,0.000028825889,0.00015792093,0.0000046745513],"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":[0.000005191578,0.000009621782,0.0015596754,0.000010949457,0.0000040756872,0.000002538258,0.000012196209,0.99494165,0.00011117937,0.00034406385,0.000039735023,0.0029590938],"study_design_scores_gemma":[0.00036650398,0.0000049278547,0.0002510724,0.000051304574,0.0000045663437,0.0000030754957,0.0000050073772,0.99887216,0.00013796221,0.0000775886,0.000021811697,0.00020402714],"about_ca_topic_score_codex":0.00001555139,"about_ca_topic_score_gemma":0.000019210844,"teacher_disagreement_score":0.81619865,"about_ca_system_score_codex":0.00006516964,"about_ca_system_score_gemma":0.0000041166973,"threshold_uncertainty_score":0.7272147},"labels":[],"label_agreement":null},{"id":"W2022902647","doi":"10.1109/mcom.2005.1561929","title":"Cross-layer design for resource allocation in 3G wireless networks and beyond","year":2005,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":98,"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":"Queensland Cyber Infrastructure Foundation","keywords":"Computer science; Computer network; Quality of service; Physical layer; Protocol stack; Resource allocation; Wireless network; Distributed computing; Application layer; Wireless; Radio resource management; Layer (electronics); Provisioning; Wireless sensor network; Telecommunications","score_opus":0.02731721453474228,"score_gpt":0.2796266933469298,"score_spread":0.2523094788121875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022902647","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":[0.009166277,0.0025549468,0.9849082,0.0006517628,0.00009050621,0.00063082005,0.0000064412097,0.00025538402,0.0017356505],"genre_scores_gemma":[0.8567258,0.0021021187,0.14015856,0.00012101723,0.00013919733,0.00031173756,0.00011495829,0.000064584834,0.0002619851],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907136,0.000065950866,0.00036011596,0.00017662041,0.000072819224,0.0002531546],"domain_scores_gemma":[0.99848634,0.00038619616,0.00006254177,0.00092152145,0.00008582242,0.000057592315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029857625,0.00016309066,0.00017284247,0.0001239028,0.000149642,0.000058122383,0.0004058348,0.00011998472,0.000006697827],"category_scores_gemma":[0.000026131847,0.00019614496,0.000025487996,0.00035813608,0.000105866464,0.00033257387,0.0000638819,0.00022089006,0.0000111922145],"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":[0.000016609734,0.000035733385,0.00018096692,0.000012561902,0.000009836387,1.2080147e-7,0.000115732095,0.96281713,0.0008889012,0.0007035715,0.0016742224,0.03354463],"study_design_scores_gemma":[0.00059890153,0.000016220309,0.0009256238,0.000030355284,0.000010167364,0.0000029773391,0.000012500034,0.97239065,0.0003870433,0.00015356968,0.025277523,0.00019448448],"about_ca_topic_score_codex":0.0000014562941,"about_ca_topic_score_gemma":0.00010449661,"teacher_disagreement_score":0.8475596,"about_ca_system_score_codex":0.00012352849,"about_ca_system_score_gemma":0.000011563012,"threshold_uncertainty_score":0.79985595},"labels":[],"label_agreement":null},{"id":"W2022904660","doi":"10.1155/2009/212783","title":"Cross-Layer Resource Scheduling for Video Traffic in the Downlink of OFDMA-Based Wireless 4G Networks","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":23,"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; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Scheduling (production processes); Quality of service; Fairness measure; Network packet; Maximum throughput scheduling; Fair queuing; Telecommunications link; Wireless; Proportionally fair; Round-robin scheduling; Real-time computing; Throughput; Fair-share scheduling; Mathematical optimization; Telecommunications","score_opus":0.027926117011187194,"score_gpt":0.2877528192243039,"score_spread":0.2598267022131167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022904660","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":[0.70976835,0.016388465,0.27084103,0.0013543394,0.00029943194,0.00072217884,0.0000081230255,0.0001630949,0.0004549568],"genre_scores_gemma":[0.98511076,0.007591107,0.0063004363,0.00047821982,0.00038265355,0.000046798727,0.000029437024,0.000056786354,0.0000037892037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99800485,0.00026498258,0.0008393832,0.00021125989,0.000210978,0.00046855366],"domain_scores_gemma":[0.99734247,0.0012819329,0.0003564573,0.0008006245,0.00012511438,0.00009341336],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011367986,0.00029270272,0.00040880684,0.00021644364,0.00061661797,0.00019505259,0.0009303621,0.00015142703,0.000003110153],"category_scores_gemma":[0.000017821627,0.00025024472,0.00013880263,0.0007219668,0.00014490307,0.00021665827,0.00004289319,0.0010312886,3.4537143e-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":[0.00006792066,0.000075614305,0.00070215715,0.000016432226,0.000020171841,0.0000022816953,0.00020389826,0.8133012,0.000102427424,0.00066271744,0.00004102707,0.18480417],"study_design_scores_gemma":[0.0010378151,0.0001199084,0.0011422379,0.0007559633,0.000029904344,0.000021019097,0.00010183524,0.99232966,0.000059828195,0.00014488226,0.003995112,0.00026185194],"about_ca_topic_score_codex":9.837925e-7,"about_ca_topic_score_gemma":0.000018237612,"teacher_disagreement_score":0.2753424,"about_ca_system_score_codex":0.000082772975,"about_ca_system_score_gemma":0.00002831203,"threshold_uncertainty_score":0.999995},"labels":[],"label_agreement":null},{"id":"W2023757603","doi":"10.1109/cdc.2011.6160652","title":"Delay optimal server assignment to symmetric parallel queues with random connectivities","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Bulk queue; Queueing theory; Scheduling (production processes); Fork–join queue; Queue; Queue management system; Layered queueing network; Bernoulli's principle","score_opus":0.013116375078587065,"score_gpt":0.18929058555289946,"score_spread":0.1761742104743124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023757603","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":[0.076076075,0.00013860685,0.9068422,0.000009091605,0.00013027036,0.00030529068,0.0000014671502,0.0004795778,0.01601747],"genre_scores_gemma":[0.8811379,0.000052250358,0.11813529,0.000057596866,0.000051166433,0.00009380653,0.000004601334,0.00004629995,0.0004210706],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992604,0.00001833812,0.00015071368,0.00016756111,0.00014181048,0.0002611398],"domain_scores_gemma":[0.999584,0.00006269644,0.000020225556,0.0001743956,0.00006355775,0.00009509759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006933955,0.00017248625,0.00018965667,0.00012630492,0.000040588882,0.000020180474,0.000091697686,0.00004912793,0.00021039632],"category_scores_gemma":[0.000014996219,0.00013965601,0.000026858264,0.0003408978,0.000017249764,0.00024121533,0.00002372046,0.000074793534,0.00004177395],"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":[0.00012109596,0.00001871972,0.00035595434,0.000010955257,0.000053122843,0.000005745338,0.00029354153,0.9954997,0.000015520514,0.0020158333,0.0006065055,0.0010033322],"study_design_scores_gemma":[0.0034672047,0.0003927154,0.00152531,0.000071331524,0.000052104348,0.000012746922,0.0005468957,0.98339885,0.008081069,0.00019957774,0.001408234,0.00084393885],"about_ca_topic_score_codex":0.000027457741,"about_ca_topic_score_gemma":0.000049701095,"teacher_disagreement_score":0.8050618,"about_ca_system_score_codex":0.000076064905,"about_ca_system_score_gemma":0.00000775044,"threshold_uncertainty_score":0.5695007},"labels":[],"label_agreement":null},{"id":"W2024778847","doi":"10.1109/ccece.2008.4564855","title":"Delay-sensitive and channel-aware scheduling in next generation wireless networks","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Computer science; Computer network; Queuing delay; Transmission delay; Network packet; Processing delay; Scheduling (production processes); Fair queuing; Queueing theory; Network delay; Wireless network; Queue; End-to-end delay; Real-time computing; Round-robin scheduling; Distributed computing; Wireless; Quality of service; Dynamic priority scheduling; Engineering; Telecommunications","score_opus":0.021870586451709154,"score_gpt":0.1838445450463211,"score_spread":0.16197395859461194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024778847","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":[0.47903207,0.00020944676,0.51999855,0.0000825444,0.00014603342,0.00022146283,0.0000024222504,0.00018613912,0.00012135682],"genre_scores_gemma":[0.99614125,0.0015288196,0.0018360653,0.00010569128,0.00027660048,0.00003983172,0.00001801373,0.000045738434,0.000007999542],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848586,0.000007197475,0.0002747285,0.00043980803,0.00013224299,0.0006601422],"domain_scores_gemma":[0.9992656,0.00003568425,0.000036172554,0.000072688235,0.00016700717,0.00042285933],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006832431,0.0003475836,0.0003360461,0.00040420625,0.00014280634,0.00016919928,0.00012040601,0.00021064804,0.000004334105],"category_scores_gemma":[0.000011447387,0.0004006738,0.00002302534,0.00049269496,0.00004838302,0.00039930528,0.000029236486,0.00052947516,0.0000018563725],"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":[0.000008571283,0.000010085941,0.0004832073,0.000040141233,0.000022183778,0.000057299825,0.0005647868,0.9652766,0.00055500143,0.0064063095,0.000055113265,0.026520684],"study_design_scores_gemma":[0.0002721043,0.00007860858,0.0017550172,0.00014856654,0.0000057632856,0.00009236054,0.000023148526,0.9969075,0.000204726,0.00004271521,0.00002703916,0.00044248236],"about_ca_topic_score_codex":0.0003010632,"about_ca_topic_score_gemma":0.00073904166,"teacher_disagreement_score":0.5181625,"about_ca_system_score_codex":0.00019286737,"about_ca_system_score_gemma":0.00009392208,"threshold_uncertainty_score":0.9998445},"labels":[],"label_agreement":null},{"id":"W2025879359","doi":"10.1145/1870121.1870126","title":"A framework for cross-layer optimization of video streaming in wireless networks","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Multimedia Computing Communications and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":28,"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":"Computer science; Wireless network; Computer network; Cross-layer optimization; Wireless; IEEE 802; WiMAX; Protocol stack; Wi-Fi; Video quality; Application layer; Real-time computing; Wireless sensor network; Quality of service; Telecommunications; Engineering","score_opus":0.033366039911168904,"score_gpt":0.29506348407944943,"score_spread":0.26169744416828056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025879359","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":[0.0034445317,0.00026808938,0.99486864,0.00003905513,0.00006726194,0.00089690107,0.000031867847,0.00022446933,0.00015916815],"genre_scores_gemma":[0.5341465,0.000871597,0.46451938,0.00001062952,0.00001986535,0.0003517654,0.000045745914,0.00003192436,0.0000025810193],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885213,0.000040774616,0.0005375875,0.00024855376,0.00008038253,0.00024054755],"domain_scores_gemma":[0.9972828,0.0011293435,0.00013255974,0.0012460621,0.0001368436,0.0000724022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001655356,0.00019282747,0.00023887314,0.00021583472,0.0003101697,0.000025792533,0.00057623046,0.00017101053,0.000011525456],"category_scores_gemma":[0.00002274757,0.00023082322,0.00006241621,0.00063962064,0.0001826726,0.00015878766,0.00003094085,0.00033867618,0.0000012592224],"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":[0.000010352752,0.00014877578,0.00044833412,0.000028961991,0.000024335255,3.9906542e-8,0.0004410411,0.84219074,0.00005620875,0.0017560592,0.0000013040402,0.15489383],"study_design_scores_gemma":[0.00041998868,0.000027746359,0.00077960844,0.00012125199,0.00002768094,0.0000012706369,0.00013189223,0.99643725,0.0004283013,0.0013491729,0.00007636893,0.00019948182],"about_ca_topic_score_codex":0.00002206472,"about_ca_topic_score_gemma":0.000030282163,"teacher_disagreement_score":0.530702,"about_ca_system_score_codex":0.000056724413,"about_ca_system_score_gemma":0.00001583229,"threshold_uncertainty_score":0.94126976},"labels":[],"label_agreement":null},{"id":"W2025929411","doi":"10.1145/1925101.1925103","title":"Using simulcast and scalable video coding to efficiently control channel switching delay in mobile tv broadcast networks","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Multimedia Computing Communications and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Computer network; Broadcasting (networking); Testbed; Energy consumption; Mobile device; Channel (broadcasting); Control channel; Efficient energy use; Scalability; Real-time computing; Base station; Engineering; Electrical engineering","score_opus":0.025921565806295253,"score_gpt":0.2634481739801952,"score_spread":0.23752660817389995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025929411","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":[0.017731233,0.00082535646,0.9797505,0.00005032976,0.00006712076,0.0011288455,0.000017228944,0.0002730665,0.00015628945],"genre_scores_gemma":[0.8062193,0.0008913808,0.1924118,0.000062713996,0.000032851927,0.0003163632,0.000014436629,0.000048563998,0.0000025875618],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867475,0.000068762485,0.00045795907,0.00034237868,0.00009655933,0.00035961403],"domain_scores_gemma":[0.9979345,0.0006720354,0.00007843335,0.0010566665,0.00008125697,0.0001770998],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023231278,0.0002460019,0.00026481628,0.00030780502,0.0006951774,0.00006165786,0.0004714329,0.00011546929,0.0000066375787],"category_scores_gemma":[0.000012938332,0.00029308113,0.00003913199,0.00078571175,0.00009982308,0.00017122591,0.000060730054,0.0004555736,0.000005725408],"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":[0.0000070044944,0.00009998096,0.00016778972,0.00001186343,0.000018802706,2.6469473e-7,0.0010109139,0.8056554,0.00030665548,0.000042974083,0.0000015930108,0.19267677],"study_design_scores_gemma":[0.00058505137,0.000031013402,0.00040307976,0.00012244402,0.00003626055,0.000009966213,0.0003271692,0.99775475,0.00009683451,0.00006774366,0.0002920624,0.00027361396],"about_ca_topic_score_codex":0.00008846291,"about_ca_topic_score_gemma":0.00008920606,"teacher_disagreement_score":0.7884881,"about_ca_system_score_codex":0.00009916913,"about_ca_system_score_gemma":0.000013822751,"threshold_uncertainty_score":0.99995214},"labels":[],"label_agreement":null},{"id":"W2026073050","doi":"10.1109/vtcfall.2012.6399363","title":"Towards Improved QoS in 802.16e Mobile WiMAX","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo; University of Alberta","funders":"","keywords":"WiMAX; Computer science; Quality of service; Computer network; Code (set theory); IEEE 802; Telecommunications; Wireless; Programming language","score_opus":0.004992548512130839,"score_gpt":0.21162412801924904,"score_spread":0.2066315795071182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026073050","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":[0.13569736,0.0014398793,0.8107938,0.000022922972,0.00196991,0.00057450146,0.0000036719764,0.001061248,0.0484367],"genre_scores_gemma":[0.9709807,0.00011616578,0.028081702,0.000034329976,0.00035972206,0.000088263434,0.000010142418,0.00003840026,0.00029059764],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940175,0.000007178294,0.00014422926,0.000080608945,0.00005890986,0.00030731823],"domain_scores_gemma":[0.999755,0.000014373238,0.000011849973,0.00014280995,0.000012481188,0.0000634636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006408556,0.00010318496,0.00010723688,0.000053594602,0.000012822293,0.0000084825115,0.00006496772,0.00006464698,0.00020074341],"category_scores_gemma":[0.000007206194,0.00010201899,0.000020193538,0.00019652183,0.000009365741,0.0003241695,0.000021185313,0.00009790111,0.000051937528],"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":[0.0000032615508,0.00002408946,0.001295758,0.000017603454,0.0000060949797,4.932447e-7,0.0002046553,0.965435,0.0026233231,0.00034239105,0.00091986713,0.029127443],"study_design_scores_gemma":[0.00042601686,0.00001954383,0.0023534629,0.0000139453405,0.000004494072,0.0000024325827,0.00009872521,0.9728814,0.009965332,0.000052501167,0.013886743,0.00029541424],"about_ca_topic_score_codex":0.000012611486,"about_ca_topic_score_gemma":0.000017452805,"teacher_disagreement_score":0.8352833,"about_ca_system_score_codex":0.000085737855,"about_ca_system_score_gemma":0.000004951004,"threshold_uncertainty_score":0.41602138},"labels":[],"label_agreement":null},{"id":"W2026457192","doi":"10.1109/glocomw.2012.6477680","title":"Performance evaluation of LTE EPC self-healing solutions","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"3rd Generation Partnership Project 2; Computer science; Overhead (engineering); Computer network; Network packet; Wireless; Bandwidth (computing); Wireless network; General partnership; Cellular network; Core (optical fiber); LTE Advanced; Self-healing; Computer architecture; Telecommunications; Telecommunications link; Operating system","score_opus":0.0288112395892197,"score_gpt":0.2524277855713561,"score_spread":0.2236165459821364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026457192","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":[0.58024174,0.00090076245,0.39457467,0.000010480724,0.0004571953,0.00021753577,0.0000013014975,0.0004517142,0.023144582],"genre_scores_gemma":[0.96810836,0.00021104122,0.0315089,0.0000043231594,0.00010527355,0.000017727109,0.000009889101,0.000015594947,0.000018912773],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994131,0.000016985672,0.00014567701,0.000045821424,0.00017867006,0.00019977293],"domain_scores_gemma":[0.99971426,0.000018376568,0.000024824669,0.00011132162,0.000095547046,0.000035693127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000373992,0.000060867656,0.00006713333,0.00004575358,0.00004315781,0.0000026457153,0.00003691666,0.000036960486,0.000089413836],"category_scores_gemma":[0.0000111536265,0.0000633005,0.00001608751,0.00016558799,0.0000075531175,0.0003622534,0.000010460802,0.000048225702,0.000021730895],"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":[5.5027425e-7,0.000011252908,0.0017282446,0.000016697704,0.000009087156,3.6488816e-9,0.00014068573,0.9860436,0.00039287077,0.0003294766,0.000114381386,0.011213192],"study_design_scores_gemma":[0.00013053528,0.0000044245458,0.0041942894,0.000012895901,0.000026674454,7.124757e-7,0.00002047788,0.9930173,0.002290513,0.000015904736,0.00021584709,0.000070401074],"about_ca_topic_score_codex":0.0000011202783,"about_ca_topic_score_gemma":0.0000014580276,"teacher_disagreement_score":0.3878666,"about_ca_system_score_codex":0.000090925045,"about_ca_system_score_gemma":0.0000101732685,"threshold_uncertainty_score":0.25813192},"labels":[],"label_agreement":null},{"id":"W2027756699","doi":"10.1145/1815396.1815483","title":"Scheduling alternatives for mobile WiMAX end-to-end simulations and analysis","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"WiMAX; Computer science; Quality of service; Throughput; Weighted fair queueing; Maximum throughput scheduling; Scheduling (production processes); Computer network; Wireless broadband; Queueing theory; Wireless; Mobile broadband; Real-time computing; Wireless network; Dynamic priority scheduling; Round-robin scheduling; Telecommunications; Mathematical optimization; Mathematics","score_opus":0.007193450842048696,"score_gpt":0.2613742715792775,"score_spread":0.2541808207372288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027756699","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":[0.29809737,0.000029723773,0.7011138,0.000013389012,0.00007564311,0.00017211914,0.000017293843,0.00013306478,0.00034759563],"genre_scores_gemma":[0.7243772,0.000012181606,0.27535635,0.000013679924,0.00006364373,0.000040137154,0.000037233214,0.000016727297,0.000082835366],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953836,0.0000034093464,0.00012446496,0.00014112005,0.000057347446,0.00013527936],"domain_scores_gemma":[0.9996019,0.00014292951,0.00001664251,0.00012688679,0.000047634232,0.00006397884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000041760468,0.000088364264,0.00012129447,0.00015995771,0.0000635376,0.000031534113,0.000051227144,0.000038686387,0.00013887828],"category_scores_gemma":[0.000027668606,0.00008993681,0.000035178713,0.00035508262,0.000015944257,0.00016486326,0.000016106882,0.00007266343,0.0000026281018],"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":[0.0000018238143,0.0000045355027,0.0012756634,0.000005221493,0.00009079057,9.29995e-8,0.00010171114,0.9837083,0.005987545,0.00069845736,0.0000067616143,0.008119071],"study_design_scores_gemma":[0.00012690586,0.000009506799,0.0006872325,0.0000021549274,0.00006236056,2.025113e-7,0.000027493292,0.9949532,0.0029599199,0.00020826976,0.00085187703,0.00011084496],"about_ca_topic_score_codex":0.0000034724994,"about_ca_topic_score_gemma":0.00012821055,"teacher_disagreement_score":0.42627984,"about_ca_system_score_codex":0.000011381439,"about_ca_system_score_gemma":0.000003103253,"threshold_uncertainty_score":0.36675167},"labels":[],"label_agreement":null},{"id":"W2028067114","doi":"10.1109/icc.2008.70","title":"A New Modeling Approach for Utility-Based Resource Allocation in OFDM Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":21,"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":"Mathematical optimization; Orthogonal frequency-division multiplexing; Resource allocation; Computer science; Heuristic; Nonlinear programming; Integer programming; Genetic algorithm; Optimization problem; Integer (computer science); Convergence (economics); Base station; Nonlinear system; Mathematics; Computer network","score_opus":0.023714264671681775,"score_gpt":0.2139509642087093,"score_spread":0.19023669953702751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028067114","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":[0.0019581185,0.0001973625,0.99489653,0.000022036025,0.00003483899,0.0003770968,6.748599e-7,0.00034546133,0.002167895],"genre_scores_gemma":[0.6279083,0.000021791691,0.3716829,0.00004132049,0.00008119791,0.00004611024,0.00010768925,0.00003149318,0.000079176214],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926835,0.0000122601605,0.0002251201,0.0001806545,0.0000799043,0.00023372794],"domain_scores_gemma":[0.9996802,0.00004182623,0.00001724076,0.00017926261,0.000025887934,0.000055586876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009292862,0.000119971075,0.00013324886,0.00007580241,0.000046277106,0.000007887721,0.00008406379,0.00009913148,0.000008814238],"category_scores_gemma":[0.000012127407,0.00013328236,0.00003424287,0.00028483715,0.000008474204,0.00011318207,0.000007863628,0.00010919863,6.516601e-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":[0.00002157376,0.000011652794,0.00013142456,0.000017734747,0.0000033489578,2.4421846e-7,0.00005451117,0.99419516,0.000010195839,0.00011660378,0.00074592594,0.0046915943],"study_design_scores_gemma":[0.0005315559,0.0000075857856,0.000020444413,0.000011720036,0.0000030257745,9.315692e-7,0.000019698367,0.9987587,0.000062960986,0.000055132172,0.00038953472,0.0001387104],"about_ca_topic_score_codex":0.0000150152455,"about_ca_topic_score_gemma":0.000014127858,"teacher_disagreement_score":0.62595016,"about_ca_system_score_codex":0.00006541148,"about_ca_system_score_gemma":0.000021949552,"threshold_uncertainty_score":0.5435097},"labels":[],"label_agreement":null},{"id":"W2028080553","doi":"10.1109/cnsr.2010.33","title":"Scheduling and Resource Allocation in LTE Uplink with a Delay Requirement","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":28,"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; Telecommunications link; Scheduling (production processes); Quality of service; Frequency-division multiple access; User equipment; Computer network; Distributed computing; Mathematical optimization; Orthogonal frequency-division multiplexing; Channel (broadcasting); Base station; Mathematics","score_opus":0.005532364341235737,"score_gpt":0.20323489400272413,"score_spread":0.19770252966148838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028080553","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":[0.40686315,0.000052869178,0.5908467,0.00006828556,0.00003083274,0.00010340436,8.573848e-8,0.00013701433,0.0018976477],"genre_scores_gemma":[0.82010657,0.000029692561,0.17973125,0.00002348889,0.000030565734,0.00001363923,0.0000055570426,0.000018436991,0.00004077522],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996069,0.0000038042344,0.00010701205,0.000106848405,0.000057176625,0.00011826769],"domain_scores_gemma":[0.9998122,0.000017137012,0.000013735726,0.000109082976,0.000015550588,0.000032287608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007926675,0.000072177274,0.00006190712,0.000051610463,0.000021146549,0.000015620677,0.00003308862,0.00004464068,0.000011504635],"category_scores_gemma":[0.0000069567227,0.00006554901,0.0000041191443,0.00013527228,0.000015166572,0.00013581061,0.000011078727,0.00013666069,0.000002373861],"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":[0.000006164188,0.0000042446927,0.0011543726,0.000009468654,0.0000034509885,0.0000012171339,0.00009223598,0.98639935,0.004112267,0.0011685077,0.000010101598,0.0070385966],"study_design_scores_gemma":[0.00026082265,0.000011458311,0.0005739638,0.000024838124,0.000002587314,0.0000038577114,0.00003352597,0.99713326,0.0012845952,0.00005763269,0.0005154822,0.00009798326],"about_ca_topic_score_codex":0.0000041784347,"about_ca_topic_score_gemma":0.00017621547,"teacher_disagreement_score":0.41324344,"about_ca_system_score_codex":0.00002065009,"about_ca_system_score_gemma":0.0000044472054,"threshold_uncertainty_score":0.2673011},"labels":[],"label_agreement":null},{"id":"W2028189358","doi":"10.1109/tvt.2006.878718","title":"Dynamic Downlink OFDM Resource Allocation With Interference Mitigation and Macro Diversity for Multimedia Services in Wireless Cellular Systems","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Spectral efficiency; Subcarrier; Telecommunications link; Computer network; Resource allocation; Wireless; Multiplexing; Quality of service; Interference (communication); Bandwidth (computing); Electronic engineering; Telecommunications; Engineering; Channel (broadcasting)","score_opus":0.002760057432909409,"score_gpt":0.17366022605927298,"score_spread":0.17090016862636356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028189358","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":[0.4447751,0.00009687089,0.55447435,0.000051947845,0.000045821136,0.0002878821,0.000011202998,0.0002507885,0.0000060062807],"genre_scores_gemma":[0.99189985,0.00007269435,0.0077990224,0.000006956519,0.000009462623,0.00011763682,0.000045122964,0.000030699986,0.000018568448],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992378,0.000020665637,0.00018884346,0.00024482317,0.00008251811,0.000225346],"domain_scores_gemma":[0.9996476,0.00004175698,0.00004974938,0.00018193292,0.00005292339,0.00002600905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006999672,0.0001617331,0.00017288172,0.00032359574,0.00013064797,0.000017916878,0.00012205126,0.000265484,9.991704e-7],"category_scores_gemma":[7.1077443e-7,0.00017489401,0.000020997435,0.00037322319,0.00008130382,0.00012837857,0.0000029598564,0.00023128885,0.0000014108226],"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":[0.000032012285,0.000035029585,0.00028084588,0.00014058039,0.000018911764,0.000004667605,0.000096293006,0.9740743,0.019639513,0.00008809498,0.0000016526304,0.005588089],"study_design_scores_gemma":[0.0006555705,0.000064949,0.00018154886,0.00016283857,0.000029124842,0.000010628062,0.00020356303,0.9636196,0.034732416,0.00013468132,0.000032580796,0.00017248132],"about_ca_topic_score_codex":0.00007159245,"about_ca_topic_score_gemma":0.0005840111,"teacher_disagreement_score":0.54712474,"about_ca_system_score_codex":0.00018748481,"about_ca_system_score_gemma":0.00000766058,"threshold_uncertainty_score":0.71319705},"labels":[],"label_agreement":null},{"id":"W2028516246","doi":"10.1016/j.peva.2007.06.011","title":"On processor sharing and its applications to cellular data network provisioning","year":2007,"lang":"en","type":"article","venue":"Performance Evaluation","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Provisioning; Processor sharing; Queue; Computer science; Telecommunications link; Scheduling (production processes); Computer network; Channel (broadcasting); Distributed computing; Shared resource; Queueing theory; Homogeneous; Mathematical optimization; Mathematics","score_opus":0.041358707089383905,"score_gpt":0.30760071198720224,"score_spread":0.26624200489781835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028516246","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":[0.48125628,0.00054856046,0.51581824,0.000023312115,0.00012235004,0.0010492508,0.0000021376718,0.00019862656,0.0009812627],"genre_scores_gemma":[0.98916495,0.00011744197,0.009885458,0.000045930345,0.00034473493,0.00017862984,0.0001986514,0.000035235345,0.000028970015],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988835,0.000007334213,0.00022985986,0.000306486,0.00030849976,0.00026434913],"domain_scores_gemma":[0.9993184,0.000049404458,0.00004606209,0.00036665835,0.00014863622,0.0000707997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011469661,0.00012295089,0.00009179534,0.000087012144,0.00017951563,0.000036693164,0.00020633922,0.00005119832,0.00001708604],"category_scores_gemma":[0.000078509416,0.0001324738,0.000006250855,0.0004461387,0.0000063852417,0.0005122075,0.00008692032,0.00011551302,0.00004772568],"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":[0.00001027055,0.0000055954,0.00042574242,0.000041155006,0.000004408358,7.7478404e-8,0.00007633048,0.8743315,0.00042185205,0.00014607239,0.00009249311,0.12444453],"study_design_scores_gemma":[0.00017301133,0.000027056029,0.0014121771,0.00009421628,0.00001634533,7.404878e-7,0.000011377887,0.9951366,0.0019611875,0.00013421148,0.0008799099,0.00015316188],"about_ca_topic_score_codex":2.4784063e-7,"about_ca_topic_score_gemma":0.000004671664,"teacher_disagreement_score":0.50790864,"about_ca_system_score_codex":0.00009334119,"about_ca_system_score_gemma":0.000015107693,"threshold_uncertainty_score":0.5402125},"labels":[],"label_agreement":null},{"id":"W2029292829","doi":"10.1007/s11042-013-1447-3","title":"Cross-layer video transmission over IEEE 802.11e multihop networks","year":2013,"lang":"en","type":"article","venue":"Multimedia Tools and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science; Computer network; Bottleneck; Scheduling (production processes); Wireless; Link layer; Wireless network; Metrics; Real-time computing; Routing protocol; Routing (electronic design automation); Wireless Routing Protocol; Embedded system; Telecommunications; Network packet","score_opus":0.011409613914431503,"score_gpt":0.24463370507216245,"score_spread":0.23322409115773093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029292829","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":[0.019369902,0.0008909999,0.977258,0.000055564306,0.00012738991,0.0010230176,0.000023578485,0.00044550732,0.00080602086],"genre_scores_gemma":[0.9364721,0.0015633991,0.058483787,0.00011582127,0.0006028904,0.002027749,0.00019936913,0.000095864365,0.00043899467],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99899167,0.000011038326,0.0002883684,0.00028128095,0.00011336087,0.00031426564],"domain_scores_gemma":[0.99927044,0.00015704251,0.000042154406,0.00027888265,0.00006484582,0.0001866318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004676752,0.00021056287,0.00017638518,0.00004564183,0.00017286463,0.00014106903,0.00012771253,0.00016564521,0.00031350178],"category_scores_gemma":[0.000006586369,0.00020386079,0.00004697604,0.00022758708,0.00007372684,0.00047232406,0.00001804917,0.00020464398,0.00010206265],"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":[0.0000018314042,0.00002141539,0.000669797,0.000017314838,0.000011703538,2.1411917e-7,0.00005886827,0.6651642,0.0047232076,0.00004616881,0.0010779317,0.32820737],"study_design_scores_gemma":[0.0004677675,0.0000074717336,0.01124182,0.000019215466,0.000011839522,0.0000014887827,0.00000837471,0.9591166,0.0010284656,0.000098009914,0.027748179,0.00025076442],"about_ca_topic_score_codex":0.000016203923,"about_ca_topic_score_gemma":0.0000032328123,"teacher_disagreement_score":0.91877425,"about_ca_system_score_codex":0.0000341759,"about_ca_system_score_gemma":0.0000061189835,"threshold_uncertainty_score":0.8313202},"labels":[],"label_agreement":null},{"id":"W2029584533","doi":"10.1002/wcm.1050","title":"Power efficient scheduling over fading channel for cross‐layer optimization","year":2010,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","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":"Western University","funders":"","keywords":"Computer science; Fading; Scheduling (production processes); Markov decision process; Computer network; Base station; Physical layer; Network packet; Queueing theory; Wireless; Mathematical optimization; Channel (broadcasting); Markov process; Telecommunications","score_opus":0.01176573105344811,"score_gpt":0.27417277056693645,"score_spread":0.2624070395134883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029584533","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":[0.3658191,0.0004827717,0.6324088,0.000015146995,0.00030028142,0.0003867758,0.0000069181124,0.00028563495,0.00029453327],"genre_scores_gemma":[0.8398508,0.00024022022,0.15955415,0.00002109642,0.00007930372,0.00011603915,0.00006542976,0.00006407782,0.000008868547],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989852,0.000022733864,0.00035307696,0.00023546304,0.00009117239,0.00031237004],"domain_scores_gemma":[0.9986434,0.00028463348,0.00010060495,0.0007324426,0.00015523363,0.00008370771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025029865,0.00019573464,0.00019763708,0.000112565205,0.00064358074,0.00013913374,0.0003585175,0.0001343169,0.000010395434],"category_scores_gemma":[0.000025874218,0.00022351854,0.000054628195,0.0002480131,0.00011308572,0.00015165244,0.00022939856,0.00034597953,0.0000015583058],"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":[0.0000033553206,0.00003069962,0.0001520187,0.000029599058,0.000015881058,1.03319124e-7,0.00052240584,0.98673207,0.0028157446,0.0013781907,0.000008324242,0.008311618],"study_design_scores_gemma":[0.00043416437,0.000016790924,0.00011206387,0.000064002415,0.0000096203585,0.0000043406867,0.000107604166,0.9975716,0.00047956212,0.000033306216,0.0009167848,0.00025020028],"about_ca_topic_score_codex":0.0000023186,"about_ca_topic_score_gemma":0.000003739974,"teacher_disagreement_score":0.47403172,"about_ca_system_score_codex":0.00004008012,"about_ca_system_score_gemma":0.000013597666,"threshold_uncertainty_score":0.91148216},"labels":[],"label_agreement":null},{"id":"W2029708398","doi":"10.1145/1577222.1577244","title":"Optimal admission control policies for heterogeneous wireless networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Wireless network; Quality of service; Wireless; Distributed computing; Mathematical optimization; Base station; Curse of dimensionality; Markov decision process; Optimal control; Heterogeneous wireless network; Call Admission Control; Heterogeneous network; Computer network; Admission control; Markov process; Telecommunications; Mathematics; Artificial intelligence","score_opus":0.006322095770748761,"score_gpt":0.2314822996382969,"score_spread":0.22516020386754812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029708398","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":[0.040942788,0.0003412725,0.9565804,0.000023460336,0.00032718788,0.00035574607,0.0000040887535,0.0006290399,0.0007960271],"genre_scores_gemma":[0.9712872,0.00008507714,0.027793894,0.00013531414,0.0004080659,0.00002878526,0.000023413324,0.00007018137,0.00016806326],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999033,0.0000061641013,0.00025222125,0.00014892426,0.00008907246,0.00047064968],"domain_scores_gemma":[0.99947923,0.00014257335,0.00003127975,0.00015642008,0.000053354066,0.00013712244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012216547,0.0001732641,0.00018203004,0.00006355427,0.00008031724,0.00002346223,0.00010265322,0.00012756053,0.00003072571],"category_scores_gemma":[0.000010125778,0.00016717621,0.00006707791,0.00013545349,0.00002093537,0.00010281342,0.000012520027,0.00008767761,0.0000039852403],"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":[0.000053457064,0.000008824999,0.000094426105,0.000011797372,0.000021575117,0.0000023109271,0.000024406922,0.98395133,0.0006683729,0.00035481193,0.00059503154,0.014213641],"study_design_scores_gemma":[0.0006551964,0.00004210315,0.000070844486,0.000014222115,0.000011606723,0.000008562503,0.000018093393,0.991603,0.004814632,0.000022476499,0.0025334344,0.00020581104],"about_ca_topic_score_codex":0.0000023678317,"about_ca_topic_score_gemma":0.00001353594,"teacher_disagreement_score":0.9303444,"about_ca_system_score_codex":0.00006627485,"about_ca_system_score_gemma":0.0000055415894,"threshold_uncertainty_score":0.68172485},"labels":[],"label_agreement":null},{"id":"W2030262608","doi":"10.1109/glocom.2014.7037581","title":"HOL delay based scheduling in wireless networks with flow-level dynamics","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Victoria","funders":"","keywords":"Computer science; HOL; Scheduling (production processes); Round-robin scheduling; Fair-share scheduling; Dynamic priority scheduling; Rate-monotonic scheduling; Queue; Maximum throughput scheduling; Distributed computing; Wireless; Wireless network; Earliest deadline first scheduling; Real-time computing; Algorithm; Parallel computing; Computer network; Mathematical optimization; Mathematics; Quality of service","score_opus":0.0058198750035713875,"score_gpt":0.1825812684734091,"score_spread":0.1767613934698377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030262608","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":[0.050540823,0.000025538446,0.9469403,0.000024772768,0.00013130493,0.00014772138,0.0000018566374,0.00040774533,0.001779924],"genre_scores_gemma":[0.7516875,0.000016956586,0.24798821,0.00006579437,0.00006877155,0.000021211115,0.000056018704,0.00006541291,0.000030123163],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907565,0.000024432857,0.00021775348,0.0002043776,0.00012490481,0.0003528868],"domain_scores_gemma":[0.99952644,0.00009283811,0.0000289764,0.00024032216,0.000039503953,0.00007193572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012514004,0.00019931878,0.00020099322,0.000098998564,0.000039293256,0.000028803099,0.00012199385,0.00012316248,0.000020940744],"category_scores_gemma":[0.000008882661,0.00018778718,0.000023311279,0.00041061855,0.000024462697,0.00017222384,0.00001572238,0.00024855425,0.0000067592714],"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":[0.000010946726,0.000010722435,0.0024872185,0.000016849233,0.0000073143674,0.0000033143451,0.000010582631,0.9784543,0.000011270865,0.0008133114,0.000013760414,0.018160418],"study_design_scores_gemma":[0.0006384864,0.000019615969,0.0005045773,0.00008434885,0.0000057815105,0.0000021585738,0.0000138753985,0.9983243,0.00008034231,0.000024676796,0.000028242626,0.00027364807],"about_ca_topic_score_codex":0.000008386969,"about_ca_topic_score_gemma":0.0006626763,"teacher_disagreement_score":0.70114666,"about_ca_system_score_codex":0.00014358974,"about_ca_system_score_gemma":0.00001205901,"threshold_uncertainty_score":0.76577395},"labels":[],"label_agreement":null},{"id":"W2030296220","doi":"10.1109/glocom.2014.7037547","title":"Robust resource allocation for predictive video streaming under channel uncertainty","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Channel (broadcasting); Resource allocation; Transmission (telecommunications); Quality of service; Video streaming; Channel allocation schemes; Resource management (computing); Computer network; Real-time computing; Wireless; Telecommunications","score_opus":0.013206937729929917,"score_gpt":0.20482064955391371,"score_spread":0.1916137118239838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030296220","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":[0.0011151369,0.000036067788,0.99216515,0.00010154108,0.000125747,0.0002916695,0.000004735498,0.000535067,0.0056248712],"genre_scores_gemma":[0.97188073,0.000018938634,0.026850583,0.00010109328,0.0003011784,0.00011273412,0.0001436525,0.000058652073,0.00053242286],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99935895,0.000015194049,0.00015276803,0.0001741372,0.00008652246,0.00021239651],"domain_scores_gemma":[0.99953604,0.00015940898,0.000030142766,0.00016361546,0.000061254905,0.00004951094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010686445,0.00012428824,0.00011147412,0.000050905244,0.000071585804,0.000018195775,0.00007651877,0.00007747689,0.000010626291],"category_scores_gemma":[0.000040384097,0.00012651377,0.000029821489,0.00012731926,0.000016956341,0.00015214481,0.000013741012,0.00006637168,0.0000044130447],"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":[0.000011690105,0.0000059714303,0.000005516114,0.000020697495,0.000016606322,2.8171886e-8,0.000084004576,0.989297,0.000075387405,0.0025771721,0.0011543796,0.0067515946],"study_design_scores_gemma":[0.00031456095,0.00003537912,0.00006806972,0.000026967047,0.000011875073,4.7474848e-7,0.00015363746,0.9954723,0.00041965494,0.0016117077,0.001743055,0.00014230734],"about_ca_topic_score_codex":0.0000041535723,"about_ca_topic_score_gemma":0.000024278359,"teacher_disagreement_score":0.9707656,"about_ca_system_score_codex":0.000111306894,"about_ca_system_score_gemma":0.0000052450764,"threshold_uncertainty_score":0.5159081},"labels":[],"label_agreement":null},{"id":"W2030486781","doi":"10.1109/wcnc.2013.6554569","title":"Routing and link scheduling with QoS in IEEE 802.16 mesh networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Lethbridge","funders":"","keywords":"Computer science; Computer network; Dynamic Source Routing; Wireless mesh network; Distributed computing; Static routing; Link-state routing protocol; Source routing; Quality of service; Metrics; Policy-based routing; Routing protocol; Routing (electronic design automation); Wireless network; Wireless","score_opus":0.004577700036316543,"score_gpt":0.18075017661221957,"score_spread":0.17617247657590301,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030486781","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":[0.14157864,0.00017310336,0.8551523,0.000043534732,0.00016481514,0.00019680955,9.9361785e-8,0.0002747722,0.0024158964],"genre_scores_gemma":[0.937155,0.00016942214,0.062153228,0.00004717874,0.000322205,0.00002835445,0.0000038531093,0.000042266824,0.000078492674],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993424,0.000009548735,0.00016720312,0.00014876809,0.00006296635,0.00026912685],"domain_scores_gemma":[0.99973094,0.000051547428,0.00002238895,0.00011315033,0.000025912961,0.000056038043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005766202,0.0001311742,0.0001363353,0.00005149788,0.000034302207,0.000046246794,0.000050301467,0.00008109958,0.00004245853],"category_scores_gemma":[0.00000648945,0.00011625421,0.000009343377,0.00021822916,0.000017486065,0.00031695442,0.000015468566,0.00019414598,0.000008410975],"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":[0.0000018571965,0.0000021424667,0.0028977809,0.0000093679455,0.000007037625,0.0000011569908,0.00004978014,0.9839467,0.000076549906,0.0002353925,0.00007316512,0.012699071],"study_design_scores_gemma":[0.0002864071,0.000012953426,0.00087353727,0.000078544304,0.0000031877253,0.0000031487348,0.00006676556,0.99827677,0.00016267352,0.00004219111,0.000028395916,0.00016544489],"about_ca_topic_score_codex":0.00002897404,"about_ca_topic_score_gemma":0.00006617864,"teacher_disagreement_score":0.79557633,"about_ca_system_score_codex":0.00005022894,"about_ca_system_score_gemma":0.0000040395435,"threshold_uncertainty_score":0.4740709},"labels":[],"label_agreement":null},{"id":"W2031195480","doi":"10.1155/2010/430615","title":"A Stochastic Multiobjective Optimization Framework for Wireless Sensor Networks","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Computer science; Mathematical optimization; Stochastic optimization; Wireless sensor network; Multi-objective optimization; Stochastic programming; Dual (grammatical number); Optimization problem; Lagrange multiplier; Algorithm; Mathematics","score_opus":0.017345204064411725,"score_gpt":0.26773292713191243,"score_spread":0.25038772306750073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031195480","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":[0.013187682,0.0013593647,0.9824838,0.00022107491,0.001686747,0.0005410963,0.000008480264,0.00030114196,0.00021063209],"genre_scores_gemma":[0.8095112,0.0057097813,0.18320014,0.00010398087,0.0011863019,0.00010287096,0.000043700995,0.0001304809,0.000011565232],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982722,0.00012490508,0.000590177,0.0002820367,0.00019580011,0.0005349237],"domain_scores_gemma":[0.9968588,0.0015334969,0.00029866907,0.0008231074,0.0002561332,0.00022980146],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00044949522,0.00037026207,0.00038966927,0.00020530017,0.0011354164,0.00026857742,0.0005505346,0.00030313263,0.00001150068],"category_scores_gemma":[0.000052595802,0.00038349623,0.00011769308,0.00047750378,0.0001778145,0.00032119866,0.00010729392,0.0017908762,0.0000020457971],"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":[0.000047077065,0.00004601927,0.00011065751,0.000011040258,0.00006630213,0.0000014537554,0.0002141105,0.9036774,0.000122026206,0.0036770504,0.000052783125,0.09197407],"study_design_scores_gemma":[0.000616383,0.00007808926,0.00007994953,0.0003233113,0.000049306436,0.000080824226,0.00010276894,0.99621487,0.000023095623,0.0008529048,0.0011665447,0.00041195357],"about_ca_topic_score_codex":0.0000011585003,"about_ca_topic_score_gemma":0.00001767939,"teacher_disagreement_score":0.7992836,"about_ca_system_score_codex":0.00009442975,"about_ca_system_score_gemma":0.00002637171,"threshold_uncertainty_score":0.9998617},"labels":[],"label_agreement":null},{"id":"W2032383861","doi":"10.1239/jap/1214950349","title":"Dynamic Distributed Scheduling in Random Access Networks","year":2008,"lang":"en","type":"article","venue":"Journal of Applied Probability","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Random access; Queue; Scheduling (production processes); Aloha; Computer science; Network packet; Quality of service; Queueing theory; Computer network; Distributed computing; Mathematics; Mathematical optimization; Throughput","score_opus":0.011126060263418511,"score_gpt":0.2288776650458725,"score_spread":0.217751604782454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032383861","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":[0.47464082,0.00019415906,0.524544,0.000014625991,0.0001452347,0.00018842705,0.0000015248248,0.000046069494,0.00022513406],"genre_scores_gemma":[0.97009987,0.00038572322,0.029384637,0.000010939684,0.00007239336,0.000012049653,0.00001023633,0.000023418434,7.611349e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987387,0.000025486444,0.000680599,0.00012781164,0.00017794609,0.00024943418],"domain_scores_gemma":[0.9993537,0.00011986282,0.00018452245,0.00017356862,0.00008760153,0.00008071435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000418683,0.00015186938,0.0003724033,0.000086640524,0.00005060932,0.000021173808,0.0002448396,0.0001119694,0.000013735219],"category_scores_gemma":[0.000044290904,0.00014376812,0.00007203155,0.00048024213,0.000059200465,0.00030178222,0.000036337606,0.00049756054,0.0000010880353],"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":[0.00024507774,0.00004205816,0.0028312071,0.000030311705,0.000017839495,0.000010713373,0.000060817074,0.9947221,0.00007595846,0.000058777405,0.000024859452,0.0018802747],"study_design_scores_gemma":[0.0017955954,0.000013510926,0.007777688,0.000039359642,0.000009783177,0.00002674883,0.000010510726,0.9870243,0.00015022968,0.0029479025,0.000055665267,0.00014869141],"about_ca_topic_score_codex":6.4954196e-7,"about_ca_topic_score_gemma":0.000009638944,"teacher_disagreement_score":0.49545902,"about_ca_system_score_codex":0.00030538833,"about_ca_system_score_gemma":0.000044400887,"threshold_uncertainty_score":0.5862694},"labels":[],"label_agreement":null},{"id":"W2032600114","doi":"10.1145/1143549.1143747","title":"Performance evaluation for unsolicited grant service flows in 802.16 networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Retransmission; Computer science; Quality of service; Computer network; Throughput; Service (business); Automatic repeat request; Lossy compression; Limit (mathematics); Task (project management); Simple (philosophy); Channel (broadcasting); Wireless; Telecommunications; Engineering","score_opus":0.009735429182174073,"score_gpt":0.2168533012965081,"score_spread":0.20711787211433402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032600114","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":[0.36983696,0.00014831037,0.6264835,0.000032654003,0.00019035488,0.0005747079,0.0000015911578,0.00024679673,0.0024851514],"genre_scores_gemma":[0.9881079,0.00007747351,0.010994895,0.000064042615,0.000211177,0.00020976682,0.00024244515,0.00004257549,0.00004973136],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991871,0.000014477392,0.0002565565,0.0001429424,0.00012972788,0.00026916518],"domain_scores_gemma":[0.99964875,0.000044471315,0.000026987635,0.00014181777,0.00011614547,0.000021833717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018856456,0.00013227153,0.00012752143,0.00009131623,0.000040456285,0.00001548941,0.00007505988,0.00008815766,0.000034388464],"category_scores_gemma":[0.0000044001213,0.00013725997,0.000021968466,0.00053096586,0.0000036512397,0.00023513887,0.000008820903,0.00007944918,0.0000063957045],"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":[0.000011782113,0.000009734536,0.0005910808,0.000024613031,0.0000033599715,8.970045e-8,0.000017681743,0.9814417,0.00011118789,0.00007876828,0.00037311506,0.017336888],"study_design_scores_gemma":[0.0007554554,0.000011082077,0.0029440403,0.000034682656,0.0000098516675,7.3641655e-7,0.000007952369,0.9952462,0.0002043706,0.000117544696,0.00049880065,0.00016929158],"about_ca_topic_score_codex":0.00004731844,"about_ca_topic_score_gemma":0.0015270314,"teacher_disagreement_score":0.61827093,"about_ca_system_score_codex":0.0001793595,"about_ca_system_score_gemma":0.000008498683,"threshold_uncertainty_score":0.55972993},"labels":[],"label_agreement":null},{"id":"W2032906529","doi":"10.1109/vetecf.2007.374","title":"A Novel Subcarrier Allocation Algorithm for Multiuser OFDM System With Fairness: User's Perspective","year":2007,"lang":"en","type":"article","venue":"IEEE Vehicular Technology Conference","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":30,"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":"Subcarrier; Computer science; Telecommunications link; Orthogonal frequency-division multiplexing; Base station; Bit error rate; Max-min fairness; Resource allocation; Channel (broadcasting); Transmitter power output; Transmission (telecommunications); Multiuser detection; Algorithm; Fairness measure; Computer network; Mathematical optimization; Real-time computing; Wireless; Transmitter; Telecommunications; Code division multiple access; Mathematics; Throughput","score_opus":0.008065143597554437,"score_gpt":0.2213579867546369,"score_spread":0.21329284315708244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032906529","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":[0.029039226,0.00017424843,0.96775264,0.00008352084,0.00026179376,0.00079898525,0.000018476834,0.0016990899,0.00017205231],"genre_scores_gemma":[0.803012,0.000018009368,0.19654648,0.000011800856,0.000067232395,0.00021627232,0.000018380504,0.0000678471,0.000041940482],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986504,0.000008872565,0.00027955565,0.00042128685,0.00017054206,0.0004693574],"domain_scores_gemma":[0.99864215,0.00005459148,0.00009668343,0.0004197326,0.00072079344,0.00006607834],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017394089,0.00028928692,0.00030036512,0.00033367393,0.00011290999,0.000027845432,0.00027776,0.0004294133,0.0000023849193],"category_scores_gemma":[0.00002472498,0.00028175118,0.000044912747,0.000681288,0.00016762121,0.00021481526,0.000020990414,0.0002897412,0.000007880695],"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":[0.00006993223,0.00010039511,0.0005021847,0.00017489032,0.00036876046,0.000052060735,0.0005148067,0.78586483,0.06312288,0.100771315,0.00006478841,0.04839313],"study_design_scores_gemma":[0.0011383971,0.00010032558,0.0001276049,0.00016130361,0.00004892262,0.000070586946,0.002103849,0.933235,0.06190548,0.000188889,0.00049340515,0.00042622982],"about_ca_topic_score_codex":0.000019683217,"about_ca_topic_score_gemma":0.00013515147,"teacher_disagreement_score":0.7739728,"about_ca_system_score_codex":0.00037606113,"about_ca_system_score_gemma":0.000050174138,"threshold_uncertainty_score":0.99996346},"labels":[],"label_agreement":null},{"id":"W2033290556","doi":"10.1109/glocom.2010.5684174","title":"Cross Layer Design for Video Transmissions in Metro Passenger Information Systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Handover; Markov decision process; Transmission (telecommunications); Computer network; Real-time computing; Distortion (music); Cross-layer optimization; Application layer; Process (computing); Markov process; Telecommunications; Wireless; Wireless network","score_opus":0.01378879022578801,"score_gpt":0.2498935656861644,"score_spread":0.23610477546037636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033290556","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":[0.014674695,0.000033499924,0.982967,0.000018080871,0.00049911154,0.0005112213,0.00000531806,0.00027306905,0.0010180126],"genre_scores_gemma":[0.90627515,0.000011818606,0.09333876,0.000020805397,0.00005637232,0.00018855343,0.000020435087,0.00002169623,0.00006643321],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993923,0.000009584474,0.0002610932,0.000068661066,0.000076827426,0.00019157778],"domain_scores_gemma":[0.99960756,0.00013777691,0.000023769582,0.00012502231,0.000055766457,0.000050087983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017137511,0.000098738885,0.00011089353,0.00010882194,0.00004021847,0.00006193096,0.00007096498,0.00009475615,0.000035470694],"category_scores_gemma":[0.000037785234,0.00009063475,0.000025977166,0.00019104464,0.000008705694,0.0007850464,0.0000039444017,0.00015249771,0.000014066627],"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":[0.00000848781,0.000004565126,0.00020862192,0.00004576658,0.0000048080783,1.6637874e-7,0.00007814505,0.9939923,0.0021844665,0.0010389644,0.0004326571,0.0020010355],"study_design_scores_gemma":[0.00040323232,0.000008508719,0.00030655766,0.000014843618,0.0000032206917,7.204942e-7,0.00004140374,0.9835809,0.0040595112,0.000058541056,0.011398108,0.00012447445],"about_ca_topic_score_codex":0.0000064753835,"about_ca_topic_score_gemma":0.000034600427,"teacher_disagreement_score":0.89160043,"about_ca_system_score_codex":0.000032624936,"about_ca_system_score_gemma":0.000011251898,"threshold_uncertainty_score":0.3695978},"labels":[],"label_agreement":null},{"id":"W2033311501","doi":"10.1109/ahici.2011.6113934","title":"Joint power and subcarrier allocation in multi-hop OFDMA network: A cross-layer approach","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"University of British Columbia","funders":"","keywords":"Goodput; Computer science; Computer network; Subcarrier; Orthogonal frequency-division multiple access; Network packet; Hop (telecommunications); Frequency-division multiple access; Wireless network; Transmitter power output; Resource allocation; Physical layer; Wireless; Orthogonal frequency-division multiplexing; Telecommunications; Throughput; Channel (broadcasting); Transmitter","score_opus":0.03865193642879667,"score_gpt":0.24294333866221704,"score_spread":0.20429140223342038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033311501","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":[0.20382813,0.0004946288,0.78652984,0.000006573769,0.00016999907,0.00026937865,0.0000010917314,0.0002696741,0.008430667],"genre_scores_gemma":[0.8972324,0.00013467138,0.102204815,0.000038743325,0.00003519786,0.00005874097,0.000009837797,0.00004362691,0.00024192949],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917024,0.000016678414,0.00024317598,0.0002059867,0.00007566029,0.00028824114],"domain_scores_gemma":[0.9996863,0.000010346564,0.000028397519,0.00016999368,0.00004166776,0.00006329177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012538522,0.0001517189,0.00015281343,0.00006434668,0.00003446008,0.00002463797,0.000061019142,0.000113833295,0.00010910681],"category_scores_gemma":[0.000009568178,0.0001496236,0.000021673286,0.00023442684,0.000035923225,0.00029326012,0.000034791537,0.00013383041,0.0000072653584],"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":[0.000010708035,0.00003137712,0.020438226,0.00001946843,0.000013911346,0.0000014429197,0.0007411559,0.9759468,0.00037526598,0.0009560053,0.00014552068,0.0013201248],"study_design_scores_gemma":[0.0005074222,0.000009837931,0.054209992,0.000016865279,0.000004352475,0.000002660808,0.00006200089,0.9438419,0.00091639435,0.00010434579,0.00011188737,0.00021237426],"about_ca_topic_score_codex":0.000025360652,"about_ca_topic_score_gemma":0.00004231092,"teacher_disagreement_score":0.6934043,"about_ca_system_score_codex":0.000043249067,"about_ca_system_score_gemma":0.000005837947,"threshold_uncertainty_score":0.6101473},"labels":[],"label_agreement":null},{"id":"W2034393041","doi":"10.1109/icc.2010.5502516","title":"Opportunistic Multicast Scheduling with Erasure-Correction Coding over Wireless Channels","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Multicast; Computer science; Fading; Computer network; Source-specific multicast; Erasure; Xcast; Scheduling (production processes); Binary erasure channel; Channel state information; Channel (broadcasting); Erasure code; Coding (social sciences); Wireless; Distributed computing; Decoding methods; Algorithm; Channel capacity; Telecommunications; Mathematics; Mathematical optimization","score_opus":0.008749024913474868,"score_gpt":0.214237224413585,"score_spread":0.20548819950011013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034393041","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":[0.21338084,0.000007325826,0.7810428,0.000012112111,0.0019824693,0.00015479761,0.0000014153543,0.00070284226,0.0027153697],"genre_scores_gemma":[0.97011286,0.000030177345,0.02906791,0.000025621626,0.0003270766,0.000025208969,0.000024574041,0.00007742157,0.0003091532],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991483,0.000008191718,0.00018413275,0.00020775494,0.00015676366,0.0002948512],"domain_scores_gemma":[0.99950457,0.0000675767,0.00003862899,0.00020561273,0.00006850722,0.000115123796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008326701,0.00019312438,0.00016355784,0.00008543952,0.00010190468,0.000058801306,0.000083819235,0.00011077712,0.00017487572],"category_scores_gemma":[0.000022301705,0.00017871315,0.00002436966,0.00023528397,0.000038079965,0.0002897195,0.000015682454,0.00036635017,0.00002037477],"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":[0.000011010624,0.00001352975,0.000557299,0.000022568545,0.000019612493,0.0000065531717,0.00007123593,0.9684117,0.021176474,0.00096063624,0.00010304662,0.008646322],"study_design_scores_gemma":[0.00031346318,0.000017602137,0.00026582996,0.00004745268,0.000013617886,0.00002160034,0.00004373116,0.9935039,0.0052230367,0.000017413591,0.0002706014,0.00026172592],"about_ca_topic_score_codex":0.000008523887,"about_ca_topic_score_gemma":0.000076215016,"teacher_disagreement_score":0.75673205,"about_ca_system_score_codex":0.00004146166,"about_ca_system_score_gemma":0.000014435494,"threshold_uncertainty_score":0.7287711},"labels":[],"label_agreement":null},{"id":"W2035061388","doi":"10.1504/ijaacs.2014.058013","title":"A local search heuristic to solve the planning problem of 3G UMTS all-IP release 4 networks with realistic traffic","year":2013,"lang":"en","type":"article","venue":"International Journal of Autonomous and Adaptive Communications Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; UMTS frequency bands; Heuristic; Local search (optimization); Mathematical optimization; Incremental heuristic search; Network planning and design; Search algorithm; Algorithm; Computer network; Beam search; Artificial intelligence; Mathematics","score_opus":0.02260417451414537,"score_gpt":0.25805607717984547,"score_spread":0.2354519026657001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035061388","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":[0.020952221,0.0022792353,0.97516525,0.0005304603,0.00014362247,0.00041755495,0.000012907595,0.000028552919,0.00047018437],"genre_scores_gemma":[0.976615,0.00033605745,0.022813141,0.000030813695,0.00009650939,0.000039365168,0.00001448331,0.000027106578,0.000027506698],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869704,0.00009997895,0.00066053524,0.00009490889,0.0002924625,0.0001550728],"domain_scores_gemma":[0.9979777,0.00042493065,0.00031008603,0.00034683326,0.00083771674,0.00010273346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033513288,0.00013795526,0.0002517883,0.00014850259,0.00008878401,0.00009732282,0.0007385911,0.000046745256,0.0000050436347],"category_scores_gemma":[0.000021583592,0.00009816391,0.00004466122,0.00015801033,0.0001465051,0.00020243421,0.00010471496,0.0003281586,0.0000028319928],"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":[0.00003768189,0.000032806878,0.00005275513,0.000012731627,0.00021508658,0.0000049130335,0.00086500077,0.98775846,0.000034340468,0.0022925383,0.00036865677,0.008325008],"study_design_scores_gemma":[0.0002901449,0.00015298034,0.0007464084,0.0005147769,0.000029402494,0.00015436109,0.0012466039,0.9957457,0.0000072404623,0.000047006295,0.00095761986,0.00010775976],"about_ca_topic_score_codex":0.00008738734,"about_ca_topic_score_gemma":0.000019804951,"teacher_disagreement_score":0.9556628,"about_ca_system_score_codex":0.00016609991,"about_ca_system_score_gemma":0.000058538128,"threshold_uncertainty_score":0.4003008},"labels":[],"label_agreement":null},{"id":"W2035307429","doi":"10.1109/twc.2014.012814.131045","title":"Routing, Scheduling and Power Allocation in Generic OFDMA Wireless Networks: Optimal Design and Efficiently Computable Bounds","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Scheduling (production processes); Mathematical optimization; Geometric programming; Upper and lower bounds; Monomial; Wireless network; Job shop scheduling; Linear programming; Wireless; Integer programming; Routing (electronic design automation); Mathematics; Algorithm; Computer network; Discrete mathematics","score_opus":0.014743172801297211,"score_gpt":0.2296899002534231,"score_spread":0.21494672745212587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035307429","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":[0.18972428,0.0007050839,0.8085127,0.00012776977,0.00017836817,0.000367075,0.0000043431965,0.00031309552,0.00006729806],"genre_scores_gemma":[0.92657304,0.0039471397,0.06908016,0.0000569355,0.000023240358,0.00019945503,0.000017302484,0.00008381646,0.0000189297],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983821,0.00023955152,0.00047455908,0.00034528138,0.00015802855,0.00040051492],"domain_scores_gemma":[0.998369,0.0005045926,0.00009627881,0.00081460027,0.00008755962,0.00012796177],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038449295,0.000305819,0.00032905044,0.0002744722,0.00051161024,0.00012927409,0.00037619396,0.00018576991,0.000006882922],"category_scores_gemma":[0.0000053050776,0.0003675158,0.0000423486,0.0007167587,0.00021446783,0.00034167324,0.000014471519,0.00054793624,0.000003840003],"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":[0.00001560774,0.000112462265,0.00008074217,0.00001863418,0.000030810806,2.8594243e-7,0.00038694357,0.96380335,0.000916279,0.0005625129,0.000007918911,0.03406447],"study_design_scores_gemma":[0.00062870124,0.000051936644,0.00023331206,0.00017267707,0.000033538425,0.0000075444304,0.000110265726,0.9973285,0.000965474,0.000028723927,0.0000887662,0.00035053285],"about_ca_topic_score_codex":0.000027941991,"about_ca_topic_score_gemma":0.00006924073,"teacher_disagreement_score":0.7394325,"about_ca_system_score_codex":0.00013844541,"about_ca_system_score_gemma":0.00002497109,"threshold_uncertainty_score":0.9998777},"labels":[],"label_agreement":null},{"id":"W2035815988","doi":"10.1109/glocomw.2014.7063590","title":"Frequency allocation for green multiuser OFDM systems using evolutionary algorithm","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Computational complexity theory; Orthogonal frequency-division multiplexing; Mathematical optimization; Computer science; Fitness function; Evolutionary algorithm; Channel (broadcasting); Genetic algorithm; Channel allocation schemes; Algorithm; Function (biology); Power (physics); Mathematics; Wireless; Telecommunications","score_opus":0.011687237579719584,"score_gpt":0.22019838644324252,"score_spread":0.20851114886352293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035815988","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":[0.001966727,0.0002719433,0.995681,0.000012858189,0.00052395655,0.00036592266,0.000008095979,0.00044293795,0.00072658504],"genre_scores_gemma":[0.37272853,0.000022470007,0.62616897,0.000017072018,0.00049026497,0.00008068783,0.00009211963,0.00006342676,0.0003364575],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933296,0.000017250382,0.0002094386,0.00014667596,0.000098052056,0.00019559263],"domain_scores_gemma":[0.9995865,0.0000575987,0.000034864293,0.00016763886,0.00010844522,0.00004493552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008501959,0.000120569384,0.00012222482,0.00006285308,0.00007103615,0.000013924362,0.00007547237,0.000085383625,0.000009265819],"category_scores_gemma":[0.000014838017,0.0001271927,0.00003073898,0.0001291155,0.000013069509,0.00027385424,0.0000095710475,0.000049758688,0.000010657007],"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":[8.1451765e-7,0.0000057446914,0.000100028454,0.000047775942,0.000013162097,9.3346955e-8,0.000018753233,0.98670185,0.0015549138,0.0018246712,0.00021712075,0.009515083],"study_design_scores_gemma":[0.00024250783,0.000010562452,0.00012280121,0.000028634178,0.000011117673,0.0000033331307,0.000016913542,0.9977385,0.00021905854,0.00041932357,0.0010241979,0.00016305876],"about_ca_topic_score_codex":0.00009149238,"about_ca_topic_score_gemma":0.000009175236,"teacher_disagreement_score":0.3707618,"about_ca_system_score_codex":0.00014268234,"about_ca_system_score_gemma":0.00000850182,"threshold_uncertainty_score":0.5186768},"labels":[],"label_agreement":null},{"id":"W2036696049","doi":"10.1155/2010/273486","title":"A Survey of Scheduling and Interference Mitigationin LTE","year":2010,"lang":"en","type":"article","venue":"Journal of Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":139,"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":"Scheduling (production processes); Computer science; Quality of service; Interference (communication); LTE Advanced; Computer network; Key (lock); Engineering; Telecommunications link; Operations management","score_opus":0.0051558616298660286,"score_gpt":0.1885723214471171,"score_spread":0.18341645981725108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036696049","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":[0.46949515,0.0003993079,0.5299567,0.0000040277896,0.000117025076,0.000012791219,2.756437e-7,0.000011844574,0.000002899163],"genre_scores_gemma":[0.9325825,0.00015282667,0.067147665,0.0000036134156,0.00010178789,3.5555823e-7,5.6244306e-7,0.000009925674,7.593685e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953604,0.0000075716266,0.00024121958,0.000051394516,0.000064857544,0.000098897355],"domain_scores_gemma":[0.9996301,0.00012578952,0.000054464737,0.00003856267,0.000086637454,0.00006442867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012644978,0.000075869415,0.00016443602,0.000100982914,0.000011546618,0.000019571438,0.000055994118,0.00004343268,0.0000012316618],"category_scores_gemma":[0.000037045025,0.000070750495,0.000016920827,0.00018197559,0.000011600031,0.00012224149,0.000016219174,0.00029284434,8.589226e-8],"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":[0.0000064457713,0.000007845416,0.0031673773,0.000030336741,0.000028215209,0.000002677285,0.00004543167,0.9539384,0.011338449,0.00026086255,0.0000102675895,0.03116365],"study_design_scores_gemma":[0.00015647853,0.00006049667,0.03033748,0.000046077686,0.0000052461555,0.000050962193,4.4579934e-7,0.9672811,0.0019455007,0.000032501175,0.00001519393,0.00006849491],"about_ca_topic_score_codex":0.0000013199173,"about_ca_topic_score_gemma":0.0000015104774,"teacher_disagreement_score":0.46308735,"about_ca_system_score_codex":0.0000075444605,"about_ca_system_score_gemma":0.0000070905007,"threshold_uncertainty_score":0.28851214},"labels":[],"label_agreement":null},{"id":"W2036707114","doi":"10.1007/s11036-006-5190-0","title":"Energy Efficient Schedulers in Wireless Networks: Design and Optimization","year":2006,"lang":"en","type":"article","venue":"Mobile Networks and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Computer science; Energy consumption; Scheduling (production processes); Sleep mode; Network packet; Wireless network; Wireless; Quality of service; Computer network; Efficient energy use; Real-time computing; Mathematical optimization; Power (physics); Power consumption; Telecommunications; Electrical engineering","score_opus":0.0031385564569275702,"score_gpt":0.17996016548984906,"score_spread":0.1768216090329215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036707114","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":[0.0030384066,0.0034498598,0.99249905,0.000008966689,0.00004802284,0.0005529824,0.0000014365885,0.0002066761,0.00019459245],"genre_scores_gemma":[0.9786,0.003334524,0.016162526,0.000023612072,0.00023889648,0.001476419,0.0000920527,0.000050997216,0.000020966607],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909186,0.000027633474,0.00026458924,0.000269859,0.00006740532,0.0002786291],"domain_scores_gemma":[0.99959904,0.00009512373,0.0000461038,0.00016792314,0.000028015671,0.00006378674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000937879,0.00017724506,0.0001676293,0.00008298486,0.00012217263,0.000053160427,0.000067188375,0.00012848398,0.000005409976],"category_scores_gemma":[6.432072e-7,0.00019748631,0.000016869415,0.0005068889,0.000066308334,0.00008010806,0.000027609098,0.00011870312,4.3169638e-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":[0.0000040032246,0.000027938877,0.0001375297,0.00000677944,0.000004390085,4.77001e-7,0.0000038031978,0.97880757,0.000014570627,0.0031860692,0.000110235895,0.017696617],"study_design_scores_gemma":[0.00026731618,0.000010572226,0.00012999368,0.000023908537,0.00000937886,0.0000028722236,0.0000136290155,0.9983124,0.000021602693,0.000106152926,0.0009021665,0.00019999787],"about_ca_topic_score_codex":0.000014976067,"about_ca_topic_score_gemma":0.000016126054,"teacher_disagreement_score":0.97633654,"about_ca_system_score_codex":0.000049851205,"about_ca_system_score_gemma":0.000005391008,"threshold_uncertainty_score":0.8053258},"labels":[],"label_agreement":null},{"id":"W2036994083","doi":"10.1002/wcm.179","title":"A QoS‐based charging and resource allocation framework for next generation wireless networks","year":2003,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Quality of service; Resource allocation; Computer network; Bandwidth (computing); Wireless network; Bandwidth allocation; Wireless; Revenue; The Internet; Resource management (computing); Telecommunications; World Wide Web","score_opus":0.030075567632502468,"score_gpt":0.2616503546865096,"score_spread":0.23157478705400714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036994083","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":[0.10914385,0.005051682,0.88450885,0.0000712554,0.00014767436,0.0006545306,0.0000035025128,0.00028556798,0.00013307216],"genre_scores_gemma":[0.845901,0.001540615,0.15185383,0.00009128761,0.00015222731,0.00023745725,0.00015033553,0.00006713818,0.000006094433],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877787,0.00012341225,0.00038988554,0.0002953095,0.00009091393,0.0003226386],"domain_scores_gemma":[0.9983068,0.000622692,0.00012885904,0.0007399916,0.000104442945,0.0000972155],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003539462,0.00023441868,0.000253547,0.000103333376,0.0007129356,0.00016460566,0.00023287864,0.00016835444,0.0000022499094],"category_scores_gemma":[0.000033665496,0.0002783378,0.000040448143,0.0003104268,0.00010957799,0.00019966043,0.00007027399,0.0002921341,5.267107e-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":[0.000003536071,0.000028230692,0.00019145879,0.00005720826,0.000019926494,1.3981845e-7,0.00043843777,0.8514218,0.0010960682,0.024255633,0.000053778527,0.1224338],"study_design_scores_gemma":[0.0003687731,0.000030379246,0.000037267877,0.00017739732,0.000022918619,0.000004589753,0.00030281,0.99225646,0.00041858968,0.0001453128,0.005946597,0.00028890534],"about_ca_topic_score_codex":0.0000034068219,"about_ca_topic_score_gemma":0.000009370072,"teacher_disagreement_score":0.73675716,"about_ca_system_score_codex":0.000068609515,"about_ca_system_score_gemma":0.000019420055,"threshold_uncertainty_score":0.99996686},"labels":[],"label_agreement":null},{"id":"W2037307676","doi":"10.1109/tvt.2010.2044820","title":"A Dual-Decomposition-Based Resource Allocation for OFDMA Networks With Imperfect CSI","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Blackberry (Canada); University of Waterloo","funders":"","keywords":"Computer science; Resource allocation; Quality of service; Channel state information; Orthogonal frequency-division multiple access; Frequency-division multiple access; Mathematical optimization; Computer network; Channel allocation schemes; Orthogonal frequency-division multiplexing; Channel (broadcasting); Wireless; Mathematics; Telecommunications","score_opus":0.003081321085178687,"score_gpt":0.20528761313337213,"score_spread":0.20220629204819343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037307676","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":[0.09292068,0.000055287142,0.9040921,0.0005485342,0.00028700847,0.00058937614,0.000015001264,0.0014615214,0.000030541618],"genre_scores_gemma":[0.962815,0.000033184268,0.035962235,0.00007324089,0.000068350615,0.0008899548,0.000039294016,0.00009701087,0.000021716685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901617,0.000015341197,0.00021974019,0.00030461355,0.00011118942,0.00033294217],"domain_scores_gemma":[0.9992572,0.000104826584,0.000052219304,0.00042049252,0.0001089117,0.000056335928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000076984434,0.00023932668,0.00020994805,0.00035813707,0.00021303809,0.000021906015,0.00013916152,0.0004506745,0.00002062171],"category_scores_gemma":[0.000003671699,0.00024037641,0.00007697361,0.00065057847,0.0001115927,0.00009681395,6.599913e-7,0.00062565075,0.0000058754626],"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":[0.000058678594,0.0000635072,0.000011039965,0.000020751768,0.00005712551,0.000003112672,0.000009773421,0.9488767,0.029107893,0.00015155808,0.00005870234,0.021581175],"study_design_scores_gemma":[0.00080832705,0.00017507414,0.000010803689,0.00004392796,0.000062088366,0.000020906235,0.000012844924,0.8670355,0.13001189,0.000052834534,0.0015156369,0.0002501632],"about_ca_topic_score_codex":0.000002137316,"about_ca_topic_score_gemma":0.00008225281,"teacher_disagreement_score":0.8698943,"about_ca_system_score_codex":0.00006836263,"about_ca_system_score_gemma":0.000021124264,"threshold_uncertainty_score":0.9802265},"labels":[],"label_agreement":null},{"id":"W2038489696","doi":"10.1109/jcn.2014.000091","title":"Composite differential evolution aided channel allocation in OFDMA systems with proportional rate constraints","year":2014,"lang":"en","type":"article","venue":"Journal of Communications and Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Telecommunications link; Differential evolution; Orthogonal frequency-division multiple access; Code (set theory); Mathematical optimization; Orthogonal frequency-division multiplexing; Channel (broadcasting); Algorithm; Set (abstract data type); Telecommunications; Mathematics","score_opus":0.0072301761256411134,"score_gpt":0.2043708895328796,"score_spread":0.1971407134072385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038489696","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":[0.08270854,0.002238254,0.9144178,0.00015491998,0.00015560501,0.00014941394,0.0000014886264,0.000026320315,0.00014763794],"genre_scores_gemma":[0.99411297,0.002824075,0.002866595,0.000009002051,0.00012347619,0.000016866496,0.000024228282,0.000016599166,0.0000062107115],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991573,0.00012989566,0.0004271826,0.00006111727,0.000101207435,0.00012326031],"domain_scores_gemma":[0.9991954,0.00011465332,0.00024423312,0.00022061805,0.00017013824,0.000054984972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002839432,0.0001022348,0.00019945388,0.00012169579,0.00008987663,0.000038695176,0.00016859264,0.0000672341,0.0000027158878],"category_scores_gemma":[0.0000071188865,0.00008867953,0.000021810794,0.00018932571,0.0001132858,0.00022878646,0.000028045639,0.00024897765,2.310207e-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":[0.00002912005,0.00003542848,0.0014976886,0.000015719115,0.000032358963,4.1003878e-7,0.000050016344,0.99192286,0.00023563729,0.0020656479,0.0000390962,0.0040760464],"study_design_scores_gemma":[0.0006398311,0.000053620308,0.011432197,0.00031768478,0.000024542753,0.000036619516,0.00004426531,0.98705626,0.000010423525,0.00018602925,0.00010122491,0.000097308766],"about_ca_topic_score_codex":0.000003524042,"about_ca_topic_score_gemma":0.00002674149,"teacher_disagreement_score":0.91155124,"about_ca_system_score_codex":0.00007118113,"about_ca_system_score_gemma":0.000017054046,"threshold_uncertainty_score":0.36162463},"labels":[],"label_agreement":null},{"id":"W2038877772","doi":"10.1007/s00530-010-0210-0","title":"Real-time video streaming over multipath in multi-hop wireless networks","year":2010,"lang":"en","type":"article","venue":"Multimedia Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Computer network; Network packet; Retransmission; Throughput; Wireless network; Packet loss; Real-time computing; Wireless","score_opus":0.007948534883930153,"score_gpt":0.22389489349149988,"score_spread":0.21594635860756972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038877772","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":[0.82436454,0.00034476575,0.16605319,0.0000064510236,0.005455791,0.0013885405,0.000034070916,0.0016021716,0.0007504811],"genre_scores_gemma":[0.964193,0.0002281666,0.034067232,0.0000055050727,0.0007171082,0.00021986516,0.00012266634,0.0002007414,0.00024573997],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99768084,0.000079866295,0.00071934186,0.00047432323,0.0002866095,0.0007590438],"domain_scores_gemma":[0.99862605,0.00034529375,0.00013881536,0.0005869921,0.00007870519,0.00022413378],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032433655,0.00044346962,0.0005636921,0.0002422708,0.000077829594,0.00008297723,0.00030442415,0.00045572742,0.000051470983],"category_scores_gemma":[0.000071125505,0.0004728967,0.000079174795,0.0004956778,0.000068001005,0.000399716,0.000060685983,0.0007106274,0.000105511936],"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":[0.000011733698,0.00005420676,0.0074202437,0.00006724885,0.000025406027,0.0000319063,0.0004987904,0.9302305,0.0448604,0.000007751118,0.00024307208,0.01654872],"study_design_scores_gemma":[0.001460119,0.000010388584,0.0074631847,0.00018810872,0.000010662347,0.000008092659,0.000083865256,0.98954993,0.00041959935,7.9673634e-7,0.00030720822,0.00049805426],"about_ca_topic_score_codex":0.0005269914,"about_ca_topic_score_gemma":0.0005328614,"teacher_disagreement_score":0.13982844,"about_ca_system_score_codex":0.000182677,"about_ca_system_score_gemma":0.000021073096,"threshold_uncertainty_score":0.99977225},"labels":[],"label_agreement":null},{"id":"W2039261184","doi":"10.1109/bsc.2008.4563200","title":"A slot allocation technique for WiMAX backhaul networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Backhaul (telecommunications); WiMAX; Computer network; Computer science; Base station; Wireless; Internet access; Wireless network; The Internet; Telecommunications","score_opus":0.010156503462293928,"score_gpt":0.20635410306905533,"score_spread":0.1961975996067614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039261184","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":[0.00040765465,0.00014359238,0.99349684,0.000027456319,0.00016034296,0.000544627,0.000001108849,0.00067109696,0.0045472854],"genre_scores_gemma":[0.73266214,0.00037942536,0.2656671,0.000060033737,0.0002166776,0.0004172871,0.00005721167,0.000057292316,0.0004828548],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947715,0.00000531204,0.00015041203,0.00011897628,0.000055193672,0.00019297987],"domain_scores_gemma":[0.9997012,0.000040739702,0.000018189223,0.00015004145,0.000051202762,0.000038652423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004791612,0.00010716705,0.00010132827,0.000041388714,0.000066030676,0.0000061628243,0.00007117749,0.00009014492,0.000028390983],"category_scores_gemma":[0.0000089510195,0.00011310094,0.00003222372,0.00017589112,0.000018446333,0.00014958803,0.00000905582,0.000070563394,0.000007894327],"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":[0.0000048995157,0.0000061266965,0.000030602183,0.000010326083,0.000006853012,5.8378055e-7,0.000015330494,0.9910378,0.0011992111,0.0010944348,0.0047148624,0.001878983],"study_design_scores_gemma":[0.0001697599,0.000018418774,0.000063589636,0.000010858384,0.0000035970688,0.0000120743,0.0000040176396,0.9876633,0.007286695,0.00017278404,0.004447859,0.00014704339],"about_ca_topic_score_codex":0.000001432495,"about_ca_topic_score_gemma":0.0000042218753,"teacher_disagreement_score":0.73225445,"about_ca_system_score_codex":0.000055110002,"about_ca_system_score_gemma":0.000006948382,"threshold_uncertainty_score":0.46121225},"labels":[],"label_agreement":null},{"id":"W2041317510","doi":"10.1155/2012/843527","title":"An Algorithm That Predicts CSI to Allocate Bandwidth for Healthcare Monitoring in Hospital's Waiting Rooms","year":2012,"lang":"en","type":"article","venue":"International Journal of Telemedicine and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Bandwidth (computing); Wireless; Algorithm; Channel state information; Reliability (semiconductor); Bandwidth allocation; Healthcare system; Real-time computing; Health care; Telecommunications","score_opus":0.012136782278773645,"score_gpt":0.2939276616513955,"score_spread":0.28179087937262187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041317510","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":[0.08948178,0.001059553,0.90670615,0.0015882399,0.00066924765,0.0003937927,0.000019381801,0.000040394872,0.000041468917],"genre_scores_gemma":[0.9484985,0.0006022227,0.048046008,0.00007452278,0.0026127729,0.00011237479,0.000025357313,0.000022561431,0.000005707023],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916875,0.000008441093,0.00033885153,0.000085023785,0.00021118362,0.00018773046],"domain_scores_gemma":[0.99935484,0.00006743601,0.00010937959,0.00007668809,0.0002122249,0.0001794252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021164189,0.00009657408,0.00014297367,0.00018491567,0.000037834732,0.000020256663,0.0001743358,0.000039590082,0.0000025330066],"category_scores_gemma":[0.000020396394,0.000092069255,0.00002452367,0.0001226716,0.000013819301,0.0003815413,0.000016157606,0.00013111702,6.749914e-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":[0.000021680804,0.00014994797,0.043921005,0.000042475793,0.00008417878,0.0000035017695,0.0012064305,0.21333776,0.0009896853,0.0006598704,0.00047648023,0.73910695],"study_design_scores_gemma":[0.005575277,0.0010817015,0.091532685,0.0014073249,0.00012064541,0.00023432584,0.0045365063,0.78212684,0.011377623,0.0025809305,0.098430686,0.0009954363],"about_ca_topic_score_codex":0.0000067606434,"about_ca_topic_score_gemma":0.0000033484098,"teacher_disagreement_score":0.8590167,"about_ca_system_score_codex":0.00009797448,"about_ca_system_score_gemma":0.000012767247,"threshold_uncertainty_score":0.3754475},"labels":[],"label_agreement":null},{"id":"W2041762453","doi":"10.1109/wowmom.2007.4351760","title":"Optimal Shaping for Transmission over Wireless Fading Channels","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Fading; Computer science; Wireless; Channel (broadcasting); Transmission (telecommunications); Computer network; Telecommunications","score_opus":0.016896983358714094,"score_gpt":0.25389005065283815,"score_spread":0.23699306729412406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041762453","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":[0.052338347,0.00015282129,0.9441367,0.000013631953,0.000314637,0.00025204595,0.0000012810017,0.0005396879,0.0022508726],"genre_scores_gemma":[0.86583614,0.00006530821,0.13343543,0.000035836787,0.00025567831,0.00001686563,0.000016589707,0.00006602229,0.00027210743],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915457,0.0000030387093,0.00021256974,0.00015836497,0.00009787517,0.000373589],"domain_scores_gemma":[0.9996913,0.00008229004,0.000019955349,0.0000927351,0.000028781744,0.00008490356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015345225,0.00014353907,0.0001364639,0.00008593368,0.00007774137,0.000021058006,0.0000799559,0.00009592771,0.00006877834],"category_scores_gemma":[0.000003989904,0.00014689262,0.00005500181,0.00016915602,0.000010896565,0.00023475879,0.000008291687,0.00008126909,0.0000039234847],"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":[0.000016726333,0.000005508254,0.000015893176,0.000048668004,0.000010311942,0.0000013338878,0.00016637491,0.9419158,0.008481934,0.0006053856,0.00028488683,0.048447147],"study_design_scores_gemma":[0.00039159317,0.000016083295,0.000040886414,0.000053240303,0.000006086378,0.0000019933354,0.000036362297,0.96433574,0.0301887,0.00006539736,0.004662187,0.00020171051],"about_ca_topic_score_codex":0.000001083288,"about_ca_topic_score_gemma":0.0000014570375,"teacher_disagreement_score":0.81349784,"about_ca_system_score_codex":0.00006828193,"about_ca_system_score_gemma":0.0000038829207,"threshold_uncertainty_score":0.5990107},"labels":[],"label_agreement":null},{"id":"W2041956541","doi":"10.1016/j.comnet.2011.05.008","title":"Comparison of different meta-heuristics to solve the global planning problem of UMTS networks","year":2011,"lang":"en","type":"article","venue":"Computer Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; UMTS frequency bands; Heuristics; Mathematical optimization; Operations research; Distributed computing; Computer network; Mathematics","score_opus":0.050233537821847675,"score_gpt":0.27208933704747085,"score_spread":0.22185579922562318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041956541","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":[0.004954336,0.0022069367,0.99090445,0.000007063728,0.000711593,0.00038723176,0.0000047006797,0.00016546885,0.0006582462],"genre_scores_gemma":[0.8768978,0.000049063037,0.12260736,0.000038884766,0.00032179037,0.000025116384,0.000018793084,0.000038624123,0.0000025710106],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984939,0.000042926436,0.0006550946,0.00022564728,0.00018552606,0.00039691586],"domain_scores_gemma":[0.99903786,0.00013814491,0.00019913907,0.00041615986,0.000102324906,0.00010634335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011808159,0.00029668232,0.00068530644,0.00004024129,0.000059624774,0.000017648852,0.00043988405,0.00013747838,0.000015124318],"category_scores_gemma":[0.0000029970247,0.0002222867,0.00015123212,0.00038761893,0.00006613985,0.00006456691,0.0001989534,0.00026480868,0.000001286803],"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":[0.000024670615,0.000053039013,0.0059302347,0.00003273007,0.0004105265,0.0000015979085,0.0004885129,0.97867507,0.0000011144413,0.0013523547,0.0025108396,0.01051932],"study_design_scores_gemma":[0.00016421113,0.00010441316,0.004412935,0.000099325334,0.0002515349,0.0000021303354,0.000015073609,0.99415773,0.000059218542,0.00035199817,0.000176625,0.00020477916],"about_ca_topic_score_codex":0.000004333968,"about_ca_topic_score_gemma":0.000009181615,"teacher_disagreement_score":0.8719435,"about_ca_system_score_codex":0.0000500033,"about_ca_system_score_gemma":0.0000055518844,"threshold_uncertainty_score":0.90645885},"labels":[],"label_agreement":null},{"id":"W2042106536","doi":"10.1023/b:ijwi.0000031813.76079.2a","title":"An Improved Round Robin Packet Scheduler for Wireless Networks","year":2004,"lang":"en","type":"article","venue":"International Journal of Wireless Information Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Weighted round robin; Network packet; Quality of service; Scheduling (production processes); Wireless network; Maximum throughput scheduling; Wireless; Fairness measure; Distributed computing; Round-robin scheduling; Throughput; Fair-share scheduling; Mathematical optimization; Telecommunications","score_opus":0.00537595054861443,"score_gpt":0.23548659324910384,"score_spread":0.23011064270048942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042106536","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":[0.052358948,0.00019141275,0.94244456,0.00014504927,0.0041580107,0.00034034555,0.000022182714,0.00017829775,0.00016120431],"genre_scores_gemma":[0.9780314,0.00078274094,0.01835699,0.00033467184,0.002045997,0.000039465885,0.00033342122,0.00006788331,0.000007416944],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99752957,0.000031004707,0.0013659677,0.00013930131,0.00049264496,0.00044154242],"domain_scores_gemma":[0.9973422,0.000109293076,0.0007599387,0.00024543365,0.0013249778,0.00021814159],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00047198794,0.00033903585,0.00039424308,0.0003658277,0.000119161894,0.00036127862,0.0007746199,0.00030373016,0.000022273358],"category_scores_gemma":[0.000032677388,0.0003437855,0.00020637394,0.00029703404,0.0000671262,0.004909525,0.000041580104,0.0005433089,0.000005301096],"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":[0.00020453223,0.000050289193,0.00007257038,0.000016295835,0.00018860432,0.0000040754085,0.00021955078,0.9311524,0.00012390963,0.0028500713,0.0004386055,0.06467907],"study_design_scores_gemma":[0.0027498333,0.00015540632,0.00015695585,0.00018719421,0.000033071366,0.0000941405,0.00015928916,0.993264,0.00051533687,0.00057823485,0.0017429678,0.00036354558],"about_ca_topic_score_codex":0.0000047782205,"about_ca_topic_score_gemma":0.000011984302,"teacher_disagreement_score":0.9256725,"about_ca_system_score_codex":0.0005590226,"about_ca_system_score_gemma":0.00009262174,"threshold_uncertainty_score":0.9999014},"labels":[],"label_agreement":null},{"id":"W2042830833","doi":"10.1109/isssta.2006.311766","title":"Analysis of Throughput and Fairness of WCDMA Networks with Downlink Scheduling","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Maximum throughput scheduling; Proportionally fair; Computer science; Fairness measure; Scheduling (production processes); Telecommunications link; Throughput; Computer network; W-CDMA; Round-robin scheduling; Max-min fairness; Distributed computing; Code division multiple access; Mathematical optimization; Dynamic priority scheduling; Quality of service; Wireless; Mathematics; Resource allocation; Telecommunications","score_opus":0.0024948694986090016,"score_gpt":0.17419207544471416,"score_spread":0.17169720594610516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042830833","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":[0.21827488,0.00038085534,0.77996427,0.0000035761789,0.000016339322,0.00004839293,0.0000015965252,0.00006701017,0.0012430747],"genre_scores_gemma":[0.92424864,0.00011232468,0.07554458,0.0000028628297,0.000027717042,0.0000026220237,0.000027252421,0.000015665726,0.000018349176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946624,0.0000066599514,0.0002200917,0.00010679783,0.000083624174,0.00011656551],"domain_scores_gemma":[0.9996849,0.000044158995,0.000058369435,0.00013821128,0.000056791032,0.000017610133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000043054628,0.00009454557,0.00026414517,0.00011501629,0.000015072782,0.000005638241,0.000044213193,0.00005441244,0.000016894879],"category_scores_gemma":[0.0000019417585,0.00008038187,0.000032189775,0.00087121973,0.000044078257,0.0001059329,0.000012805344,0.000053262687,1.17137645e-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":[0.000006739477,0.000008121459,0.020804195,0.000022422391,0.00018505038,4.2689518e-7,0.000019811736,0.9765161,0.000114003065,0.0010219888,0.0000052725964,0.0012958212],"study_design_scores_gemma":[0.00017340861,0.000012051825,0.010148047,0.000021426302,0.00020911469,4.4510367e-7,0.000030496614,0.9884534,0.0008103769,0.000041780182,0.0000070566007,0.00009238818],"about_ca_topic_score_codex":0.00004586039,"about_ca_topic_score_gemma":0.00014743442,"teacher_disagreement_score":0.70597374,"about_ca_system_score_codex":0.000011336903,"about_ca_system_score_gemma":0.0000031468492,"threshold_uncertainty_score":0.32778776},"labels":[],"label_agreement":null},{"id":"W2042858188","doi":"10.1109/tnet.2011.2176140","title":"Optimal Control of Wireless Networks With Finite Buffers","year":2011,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Computer science; Queue; Bounded function; Scheduling (production processes); Flow network; Notation; Algorithm; Theoretical computer science; Discrete mathematics; Computer network; Mathematics; Mathematical optimization; Arithmetic","score_opus":0.014251260490836366,"score_gpt":0.19166796158321012,"score_spread":0.17741670109237376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042858188","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":[0.013113167,0.0002624626,0.9838193,0.000007788772,0.0011119426,0.0003432802,0.000010554014,0.0005081034,0.00082340447],"genre_scores_gemma":[0.9708313,0.00050397334,0.028101807,0.000043431875,0.00026593835,0.00007945193,0.0000075880935,0.00013561684,0.00003090719],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841803,0.000051778366,0.00043803084,0.00031341944,0.00022913433,0.0005496099],"domain_scores_gemma":[0.9988415,0.00026550196,0.00012129208,0.0005601624,0.00008257623,0.0001289406],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001226306,0.0003587567,0.00041499184,0.00016995273,0.00015442762,0.000019891188,0.00031070257,0.00019380006,0.00007180629],"category_scores_gemma":[0.0000021366427,0.00035879813,0.00011727802,0.0006342501,0.00011457633,0.00022863518,0.0000026153941,0.0004889956,0.000006367924],"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":[0.00024337579,0.00005744205,0.00020589601,0.000024076102,0.00017789919,0.000010306132,0.00024487113,0.96418756,0.000064570646,0.000022120072,0.000021584145,0.034740303],"study_design_scores_gemma":[0.0011022614,0.0001891529,0.00011367882,0.00025270108,0.00011443411,0.000010091054,0.000055133856,0.9959681,0.0015812812,0.000028473361,0.0001878794,0.00039679726],"about_ca_topic_score_codex":0.000011358774,"about_ca_topic_score_gemma":0.000034316854,"teacher_disagreement_score":0.95771813,"about_ca_system_score_codex":0.00008220575,"about_ca_system_score_gemma":0.000018154135,"threshold_uncertainty_score":0.9998864},"labels":[],"label_agreement":null},{"id":"W2042926266","doi":"10.1109/tvt.2014.2320596","title":"Channel Time Allocations and Handoff Management for Fair Throughput in Wireless Mesh Networks","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Handover; Computer network; Computer science; Throughput; Channel allocation schemes; Channel (broadcasting); Wireless mesh network; Heuristic; Wireless; Optimization problem; Wireless network; Algorithm; Telecommunications","score_opus":0.0041107348904896816,"score_gpt":0.19323166855397655,"score_spread":0.18912093366348687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042926266","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":[0.009627381,0.000084678264,0.98826987,0.00030421326,0.00021598574,0.00062148826,0.000005577095,0.0007472979,0.00012350091],"genre_scores_gemma":[0.98981047,0.00061921414,0.008665614,0.000047573143,0.000027507032,0.0006527492,0.000013666991,0.00006047864,0.000102730904],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990601,0.000018077737,0.00023321855,0.0002947747,0.00007188088,0.00032196098],"domain_scores_gemma":[0.9995425,0.0000570892,0.000030453508,0.00029881907,0.0000339769,0.00003719247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009524333,0.00019830203,0.00023621778,0.0003817779,0.00012259385,0.00001504006,0.00012643637,0.0002827377,0.0000054591405],"category_scores_gemma":[0.0000018873206,0.00022687613,0.00004548543,0.00053216604,0.00008127606,0.00010639151,0.0000024403064,0.00025238234,0.000009636786],"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":[0.000010913615,0.000040755855,0.0000022614815,0.000033904296,0.000049864437,0.0000016485396,0.000021694761,0.95540816,0.0003045111,0.0022349847,0.000052998337,0.0418383],"study_design_scores_gemma":[0.00084913935,0.00006315174,0.000014855456,0.00006527539,0.000035565015,0.0000070792194,0.000030897467,0.992884,0.0041123237,0.00120536,0.0005134213,0.00021896727],"about_ca_topic_score_codex":0.0000016468254,"about_ca_topic_score_gemma":0.000034233606,"teacher_disagreement_score":0.98018306,"about_ca_system_score_codex":0.00007805411,"about_ca_system_score_gemma":0.0000034153618,"threshold_uncertainty_score":0.925174},"labels":[],"label_agreement":null},{"id":"W2043060026","doi":"10.1186/1687-1499-2013-256","title":"Optimizing end user QoS in heterogeneous network environments using reputation and prediction","year":2013,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Handover; Reputation; Quality of service; Service provider; Heterogeneous network; Service (business); End user; Computer network; Bandwidth (computing); Vertical handover; Quality (philosophy); Telecommunications; World Wide Web; Wireless network","score_opus":0.019530746567967553,"score_gpt":0.23250245077481718,"score_spread":0.21297170420684963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043060026","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":[0.7386309,0.012176879,0.24742582,0.00011088407,0.0008115278,0.0004805924,0.0000023211987,0.00010425821,0.0002568483],"genre_scores_gemma":[0.9440535,0.03287479,0.022394788,0.000057738187,0.00050504407,0.00002830868,0.000017280741,0.000061067105,0.000007501166],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998601,0.00017418714,0.0005225845,0.00019199292,0.00015610886,0.0003540923],"domain_scores_gemma":[0.9990921,0.00019547575,0.00017953836,0.00038473276,0.000025343197,0.00012278499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002852208,0.00021946547,0.00022969993,0.00014762029,0.00048740578,0.00019169085,0.0001937278,0.00011049808,0.000010797918],"category_scores_gemma":[0.000004620993,0.00023656143,0.00003294552,0.00026133726,0.000085227344,0.000549214,0.00011660604,0.0005579757,0.0000021916528],"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":[0.000008870104,0.000018621993,0.0039306125,0.0000067472274,0.00002704727,0.0000034543239,0.00024380331,0.9440563,0.0008200651,0.00004152063,0.000029422106,0.050813533],"study_design_scores_gemma":[0.0004021226,0.000047034733,0.0023651265,0.00036054273,0.000017995493,0.00015020685,0.0000615452,0.99445176,0.000039150353,0.00015970007,0.0017386938,0.00020611708],"about_ca_topic_score_codex":0.0000059799454,"about_ca_topic_score_gemma":0.000014838769,"teacher_disagreement_score":0.22503103,"about_ca_system_score_codex":0.00016464945,"about_ca_system_score_gemma":0.0000076192805,"threshold_uncertainty_score":0.9646695},"labels":[],"label_agreement":null},{"id":"W2043445027","doi":"10.1109/glocom.2014.7037551","title":"Distributed energy-efficient resource allocation with fairness in wireless multicell OFDMA networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":8,"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":"Computer science; Max-min fairness; Fairness measure; Resource allocation; Nash equilibrium; Resource management (computing); Wireless; Computer network; Throughput; Wireless network; Efficient energy use; Mathematical optimization; Game theory; Orthogonal frequency-division multiple access; Energy consumption; Distributed computing; Orthogonal frequency-division multiplexing; Telecommunications; Channel (broadcasting); Engineering; Mathematics","score_opus":0.0025444529234061914,"score_gpt":0.16173025006136812,"score_spread":0.15918579713796194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043445027","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":[0.07610763,0.00006491557,0.92216015,0.00003401816,0.00007550141,0.00012722932,0.0000019368263,0.0004112196,0.0010174098],"genre_scores_gemma":[0.99656564,0.00004871881,0.0028774058,0.00003949735,0.00008579968,0.000068205794,0.0001778387,0.00005826156,0.000078633304],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898696,0.000046800382,0.00024617783,0.00023894229,0.00015309385,0.00032801044],"domain_scores_gemma":[0.99947864,0.00009601506,0.000047204845,0.00025252465,0.00005165276,0.00007396944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000109635606,0.00019539325,0.00018788548,0.00008101051,0.000044411845,0.000028071137,0.00013330842,0.00010724123,0.000013838718],"category_scores_gemma":[0.000007344775,0.00017780387,0.000019524117,0.0005619771,0.00003281048,0.00008633217,0.00002450156,0.00013844365,0.0000029622272],"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":[0.000021638176,0.000036033744,0.0004666343,0.000017655408,0.000008116783,0.0000012374986,0.000034233264,0.9881039,0.00011786914,0.0027394355,0.00009405631,0.008359149],"study_design_scores_gemma":[0.00058349315,0.000016151003,0.0007667086,0.00007141563,0.000008129704,8.5651936e-7,0.000037910773,0.9956361,0.0011928941,0.000008071128,0.0014268302,0.00025142072],"about_ca_topic_score_codex":0.00002662975,"about_ca_topic_score_gemma":0.00014267076,"teacher_disagreement_score":0.920458,"about_ca_system_score_codex":0.0001128883,"about_ca_system_score_gemma":0.0000055930846,"threshold_uncertainty_score":0.72506315},"labels":[],"label_agreement":null},{"id":"W2043575395","doi":"10.1109/milcom.2007.4455263","title":"Dynamic Scheduling in High Speed Downlink Packet Access Networks: Heuristic Approach","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Telecommunications link; Computer science; Heuristic; Scheduling (production processes); Computation; Network packet; Dynamic programming; Mathematical optimization; Reduction (mathematics); Distributed computing; Computer network; Algorithm; Mathematics","score_opus":0.008605192716643825,"score_gpt":0.24413594598177477,"score_spread":0.23553075326513095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043575395","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":[0.13632998,0.00031422326,0.8584647,0.000010760178,0.00033089737,0.00022596259,0.0000012252159,0.00052411645,0.0037981463],"genre_scores_gemma":[0.89253074,0.00023524415,0.10682779,0.000040180188,0.0001267044,0.000006114881,0.00010327713,0.00006630868,0.000063633655],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986343,0.000016484786,0.00040199023,0.00026702197,0.00014360629,0.00053664146],"domain_scores_gemma":[0.99946773,0.000107161235,0.000043380147,0.000256423,0.000032444193,0.00009288378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027269335,0.00022249718,0.00024289345,0.00019241429,0.000040607272,0.00006074064,0.00024697513,0.00015876497,0.000040403094],"category_scores_gemma":[0.000025184889,0.00023252836,0.000034937635,0.0007977689,0.000028118071,0.0003557512,0.000058967013,0.00033430842,0.000012952951],"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":[0.000012813025,0.000023012613,0.0020654462,0.000032709522,0.000011247263,0.000010376415,0.00002282411,0.99201554,0.00003424685,0.00038948032,0.000037625578,0.0053446973],"study_design_scores_gemma":[0.00042203322,0.0000063475836,0.0070768096,0.000034005832,0.0000066083257,0.000004150105,0.00003726225,0.99179375,0.000050259623,0.00027065055,0.000024043584,0.00027409327],"about_ca_topic_score_codex":0.00001777493,"about_ca_topic_score_gemma":0.0001157247,"teacher_disagreement_score":0.7562008,"about_ca_system_score_codex":0.00019089464,"about_ca_system_score_gemma":0.0000074254253,"threshold_uncertainty_score":0.9482231},"labels":[],"label_agreement":null},{"id":"W2043638109","doi":"10.1109/twc.2006.1638644","title":"Selective relative best scheduling for best-effort downlink packet data","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Scheduling (production processes); Telecommunications link; Maximum throughput scheduling; Diversity gain; Network packet; Exploit; Fairness measure; Computer network; Throughput; Channel (broadcasting); Round-robin scheduling; Real-time computing; Dynamic priority scheduling; Wireless; Fading; Mathematical optimization; Telecommunications; Mathematics; Quality of service","score_opus":0.040983809785523406,"score_gpt":0.28980582935577487,"score_spread":0.24882201957025146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043638109","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":[0.005621786,0.000552377,0.9885494,0.00029343902,0.0003267461,0.0009856663,0.0007255303,0.0006367567,0.0023083028],"genre_scores_gemma":[0.8769244,0.0013314966,0.11991702,0.000024217237,0.000094685056,0.0006269453,0.00069922453,0.00012492655,0.000257113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99828506,0.00008277828,0.000546336,0.00042282487,0.00024350345,0.00041949216],"domain_scores_gemma":[0.99608153,0.0005881852,0.00011610377,0.0028091362,0.00031614324,0.00008891661],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00024703448,0.00033691694,0.0003197216,0.00023343427,0.0008314799,0.000066536384,0.0012291723,0.00022399683,0.000014999789],"category_scores_gemma":[0.000010184827,0.00039916972,0.00011316975,0.00076639204,0.0001863295,0.00088299986,0.00001486505,0.0006877135,0.00006621734],"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":[0.00001780632,0.00032592047,0.000018317554,0.000025843237,0.00012302255,2.4285634e-7,0.00011070737,0.97817415,0.0006230986,0.0017852396,0.0002322478,0.018563405],"study_design_scores_gemma":[0.00077043497,0.000060117214,0.000025610841,0.00013863438,0.00021571695,0.0000045689007,0.00013813822,0.990445,0.0044066077,0.0011191681,0.0022320407,0.0004439463],"about_ca_topic_score_codex":0.000067463734,"about_ca_topic_score_gemma":0.00097201194,"teacher_disagreement_score":0.8713026,"about_ca_system_score_codex":0.00031064643,"about_ca_system_score_gemma":0.0000755832,"threshold_uncertainty_score":0.99984604},"labels":[],"label_agreement":null},{"id":"W2043943624","doi":"10.1109/tvt.2014.2303081","title":"Stability Region of Opportunistic Scheduling in Wireless Networks","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Victoria","funders":"","keywords":"Scheduling (production processes); Round-robin scheduling; Fair-share scheduling; Dynamic priority scheduling; Rate-monotonic scheduling; Computer science; Proportionally fair; Two-level scheduling; Mathematical optimization; Ergodic theory; Flow shop scheduling; Earliest deadline first scheduling; Distributed computing; Mathematics; Computer network; Mathematical analysis","score_opus":0.011222489461320035,"score_gpt":0.2046108924943464,"score_spread":0.19338840303302637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043943624","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":[0.25473619,0.00004122071,0.74433655,0.000050523704,0.00019892515,0.00015244873,0.0000015686396,0.0004198962,0.000062656225],"genre_scores_gemma":[0.9947599,0.000234048,0.004870513,0.000011414335,0.00001575229,0.000056880188,0.0000042896404,0.000043271426,0.00000390522],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989713,0.000042848587,0.0003688846,0.00024236427,0.000099481294,0.0002751414],"domain_scores_gemma":[0.99933124,0.00007482053,0.000059378002,0.00043931569,0.00005427328,0.00004096251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013560294,0.00017299961,0.00029518775,0.0003650942,0.0000481294,0.0000046524806,0.00016425952,0.00036487906,0.0000095140595],"category_scores_gemma":[0.000009215015,0.0002003091,0.00005695716,0.0008019212,0.00013529629,0.000082576385,0.0000014301736,0.0004989218,0.0000028742786],"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":[0.0000123765485,0.0000546957,0.000116924966,0.00003661693,0.000014603344,0.0000062382264,0.000013517333,0.95479506,0.0023862172,0.0009887466,0.0000012596917,0.04157374],"study_design_scores_gemma":[0.0003362136,0.00005899537,0.00003150356,0.000086925655,0.000014863375,0.00001235283,0.000033402743,0.97511977,0.023661867,0.0004433033,0.000035612284,0.00016520258],"about_ca_topic_score_codex":0.0000041786525,"about_ca_topic_score_gemma":0.000042511518,"teacher_disagreement_score":0.74002373,"about_ca_system_score_codex":0.00010725604,"about_ca_system_score_gemma":0.000011571204,"threshold_uncertainty_score":0.81683683},"labels":[],"label_agreement":null},{"id":"W2046654093","doi":"10.1109/ictta.2008.4530168","title":"Analytic Evaluation of Achievable Downlink Service Rate and Server Sharing in 3G Wireless Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer network; Computer science; Wireless network; Telecommunications link; Wireless; Wi-Fi array; Link adaptation; Wireless WAN; Quality of service; Fixed wireless; Radio resource management; Stochastic geometry models of wireless networks; Markov process; Channel (broadcasting); Distributed computing; Fading; Telecommunications","score_opus":0.0241484559451286,"score_gpt":0.23520335055721886,"score_spread":0.21105489461209026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046654093","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":[0.9414647,0.00039616524,0.056567185,0.000019980907,0.00007028305,0.00022662498,6.747208e-7,0.00010375764,0.0011506226],"genre_scores_gemma":[0.99777985,0.0005195791,0.0015158118,0.000035818615,0.000037196074,0.000016434562,0.000023855277,0.000028839957,0.000042607135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990947,0.0000384521,0.00029443938,0.00019149926,0.00017574495,0.00020512211],"domain_scores_gemma":[0.9995252,0.0000449263,0.00004743413,0.00020523096,0.00013495762,0.000042243973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044461282,0.00013188248,0.00020382782,0.000107176216,0.000037053313,0.0000098305645,0.00009137066,0.00008851139,0.000051842846],"category_scores_gemma":[0.000010952734,0.00013985056,0.000017544182,0.00064713205,0.000017153183,0.00032725907,0.000042293384,0.00013109736,0.000002977269],"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":[0.000008033176,0.000009553446,0.010715044,0.000041802217,0.000015059113,0.0000012054962,0.00011574684,0.98722994,0.00023613575,0.00008603571,0.0000148148265,0.0015266135],"study_design_scores_gemma":[0.000631204,0.0000067408546,0.027380552,0.000058543632,0.00002239157,0.0000034541927,0.000025998592,0.9712884,0.0003200953,0.00011945106,0.00000493552,0.00013823491],"about_ca_topic_score_codex":0.000058850994,"about_ca_topic_score_gemma":0.0004066857,"teacher_disagreement_score":0.05631515,"about_ca_system_score_codex":0.0000859257,"about_ca_system_score_gemma":0.000014641816,"threshold_uncertainty_score":0.570294},"labels":[],"label_agreement":null},{"id":"W2046838078","doi":"10.1109/twc.2014.2320726","title":"Mobile Terminal Energy Management for Sustainable Multi-Homing Video Transmission","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Computer science; Video quality; Computer network; Real-time computing; Network packet; Upper and lower bounds; Bandwidth (computing); Wireless; Telecommunications","score_opus":0.01149748363748133,"score_gpt":0.24692554214209908,"score_spread":0.23542805850461776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046838078","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":[0.0006016351,0.00025964386,0.9963452,0.000050027986,0.00013730586,0.0006437994,0.000012881536,0.0006255624,0.0013239479],"genre_scores_gemma":[0.87103015,0.0025546898,0.12220397,0.000052085106,0.000026706006,0.0021223063,0.000045524313,0.00010250669,0.0018620335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986986,0.00008034779,0.00038676374,0.00026629926,0.00014200818,0.0004259705],"domain_scores_gemma":[0.998222,0.00024187104,0.00005869392,0.0012394747,0.00011892647,0.0001190182],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015572045,0.00026313728,0.00024103845,0.00025718924,0.0007232944,0.0000588236,0.00062646565,0.00012762834,0.000018007526],"category_scores_gemma":[0.0000015862728,0.00030363115,0.00013935505,0.0003944295,0.00008812484,0.00032812232,0.0000059741756,0.00023658495,0.000008330127],"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":[0.00001877531,0.00016589534,6.1405916e-7,0.000099907746,0.000044770986,7.161226e-7,0.00020832107,0.7267667,0.0005506827,0.0023546442,0.00012304432,0.26966596],"study_design_scores_gemma":[0.000897751,0.00007838445,0.000004827614,0.000099774705,0.000055567903,0.0000036489823,0.0002793943,0.9273277,0.007453468,0.00022204302,0.06325987,0.00031760655],"about_ca_topic_score_codex":0.000013755776,"about_ca_topic_score_gemma":0.000033782628,"teacher_disagreement_score":0.8741412,"about_ca_system_score_codex":0.00019313447,"about_ca_system_score_gemma":0.000013551664,"threshold_uncertainty_score":0.9999416},"labels":[],"label_agreement":null},{"id":"W2047937590","doi":"10.1109/glocom.2012.6503894","title":"Channel adaptive power allocation and pilot optimization for OFDM systems","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"University of Alberta","funders":"","keywords":"Orthogonal frequency-division multiplexing; Channel state information; Transmitter; Channel (broadcasting); Computer science; Resource allocation; Power (physics); Mathematical optimization; Transmission (telecommunications); Function (biology); Transmitter power output; Electronic engineering; Control theory (sociology); Wireless; Telecommunications; Mathematics; Engineering; Computer network","score_opus":0.016948252774118544,"score_gpt":0.21094834147693078,"score_spread":0.19400008870281224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047937590","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":[0.0011440879,0.00087099266,0.9951817,0.000014858291,0.00047935444,0.00048040965,0.0000044496687,0.00027799545,0.0015461788],"genre_scores_gemma":[0.95380634,0.00012697057,0.0455205,0.000016557182,0.00015001846,0.00012960013,0.000041426993,0.000041119736,0.00016748057],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995043,0.000009307172,0.00013470829,0.00009136313,0.000060424714,0.00019986027],"domain_scores_gemma":[0.99971855,0.000041904816,0.000028341328,0.00008483513,0.000063819854,0.00006252695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008425913,0.000104783525,0.00009834886,0.000049351627,0.000045799927,0.000018593613,0.000030148023,0.00004829596,0.000011866552],"category_scores_gemma":[0.000010869513,0.00010580464,0.000010806501,0.00009390253,0.000010900447,0.00044323877,0.000008914823,0.000033693083,0.0000036861293],"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":[0.000012011972,0.00001216002,0.000016883094,0.000024287558,0.000013386387,1.9059181e-8,0.00011891645,0.99545276,0.00007474674,0.0036541512,0.000377642,0.0002430404],"study_design_scores_gemma":[0.0002466271,0.000056010922,0.000057860016,0.000016684622,0.000009312256,0.0000018735885,0.0001329679,0.9988285,0.0002181411,0.000021678381,0.00027791638,0.0001324799],"about_ca_topic_score_codex":0.0000026105038,"about_ca_topic_score_gemma":9.541625e-7,"teacher_disagreement_score":0.9526622,"about_ca_system_score_codex":0.000050336872,"about_ca_system_score_gemma":0.0000028126374,"threshold_uncertainty_score":0.4314588},"labels":[],"label_agreement":null},{"id":"W2048047401","doi":"10.1109/mwc.2007.314548","title":"Radio resource management games in wireless networks: an approach to bandwidth allocation and admission control for polling service in IEEE 802.16 [Radio Resource Management and Protocol Engineering for IEEE 802.16]","year":2007,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":77,"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 Manitoba; Tellabs (Canada)","funders":"University of Manitoba","keywords":"Computer science; Game theory; Polling; Computer network; Wireless network; Resource allocation; Resource management (computing); Quality of service; Nash equilibrium; Admission control; Call Admission Control; Radio resource management; Bandwidth allocation; Wireless; Telecommunications; Mathematical optimization","score_opus":0.01649155635268073,"score_gpt":0.25911384689794037,"score_spread":0.24262229054525963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048047401","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":[0.01866791,0.00034348,0.94186395,0.00020594212,0.0000928831,0.038008742,0.000019093859,0.00034098155,0.0004569948],"genre_scores_gemma":[0.85480875,0.00034950217,0.08911296,0.00017896801,0.0001596203,0.054927357,0.0001847787,0.00020337291,0.000074716285],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971932,0.0001285001,0.00095901656,0.0006680475,0.00024816845,0.0008030306],"domain_scores_gemma":[0.9975634,0.00048248726,0.00018342391,0.0013694749,0.000103614606,0.00029756973],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011825473,0.00050508144,0.0005644692,0.0006545138,0.00031168,0.00013491188,0.00081728067,0.00024748675,6.912573e-7],"category_scores_gemma":[0.00001358107,0.0006000242,0.00006183072,0.0010485472,0.000060112114,0.0004182844,0.000113579765,0.00040507215,5.32489e-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":[0.0002988141,0.00019963786,0.00028330102,0.00086864043,0.000078455356,0.0000013528239,0.00080496276,0.959451,0.00047543563,0.0025288938,0.00018916812,0.03482029],"study_design_scores_gemma":[0.004073899,0.00006849966,0.0012027064,0.0007924735,0.0000625724,0.0000060426382,0.00088891387,0.9834102,0.00043463276,0.00007267236,0.008352769,0.00063462084],"about_ca_topic_score_codex":0.000033591565,"about_ca_topic_score_gemma":0.0003568053,"teacher_disagreement_score":0.852751,"about_ca_system_score_codex":0.0006023222,"about_ca_system_score_gemma":0.000016139047,"threshold_uncertainty_score":0.9996451},"labels":[],"label_agreement":null},{"id":"W2048194897","doi":"10.1007/s11276-008-0132-3","title":"A new bandwidth allocation mechanism for next generation wireless cellular networks","year":2008,"lang":"en","type":"article","venue":"Wireless Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Computer network; Quality of service; Time division multiple access; Bandwidth (computing); Throughput; Wireless; Multiplexing; Wireless network; Cellular traffic; Cellular network; Channel (broadcasting); Scheme (mathematics); Channel allocation schemes; Telecommunications","score_opus":0.021891743707991462,"score_gpt":0.20572599616569864,"score_spread":0.18383425245770718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048194897","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":[0.043230485,0.001440593,0.95070755,0.00006616554,0.0022519843,0.001072467,0.0000052802616,0.0010483488,0.00017711632],"genre_scores_gemma":[0.9628518,0.003898206,0.026631763,0.00020750902,0.004550347,0.0003288133,0.00077153347,0.0002928371,0.00046718356],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972639,0.00006562098,0.0007352548,0.0006494055,0.00033453817,0.0009512894],"domain_scores_gemma":[0.99849325,0.00013485047,0.0001905386,0.00060850754,0.00024289906,0.00032997708],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018624357,0.0005983101,0.0005708208,0.00015202771,0.0004846556,0.00011544843,0.00037832547,0.0005768211,0.00004820936],"category_scores_gemma":[0.000012928547,0.0006899604,0.00019621088,0.0006673515,0.00006005341,0.00069645676,0.00005350996,0.00044821447,0.000015620924],"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":[0.000037562066,0.000025942929,0.000035668232,0.000027542414,0.00007019179,0.0000089954,0.00014012064,0.9391409,0.004263543,0.008857957,0.010409294,0.036982242],"study_design_scores_gemma":[0.0012022863,0.00006679965,0.000024092364,0.0000703845,0.000056378147,0.000021814743,0.00002260146,0.99195546,0.004667583,0.000352176,0.0008192951,0.00074112247],"about_ca_topic_score_codex":0.000022613456,"about_ca_topic_score_gemma":0.00006930916,"teacher_disagreement_score":0.9240758,"about_ca_system_score_codex":0.00024763163,"about_ca_system_score_gemma":0.00007175238,"threshold_uncertainty_score":0.9995552},"labels":[],"label_agreement":null},{"id":"W2048241951","doi":"10.1155/2012/642649","title":"A Jointly Optimized Variable<i>M</i>-QAM and Power Allocation Scheme for Image Transmission","year":2012,"lang":"en","type":"article","venue":"Journal of Computer Networks and Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Transmission (telecommunications); Quadrature amplitude modulation; Image quality; Rayleigh fading; Transmitter; QAM; Algorithm; Modulation (music); Peak signal-to-noise ratio; Signal-to-noise ratio (imaging); Bit error rate; Image (mathematics); Channel (broadcasting); Fading; Telecommunications; Artificial intelligence; Decoding methods","score_opus":0.009234523778811446,"score_gpt":0.2301363347056336,"score_spread":0.22090181092682215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048241951","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":[0.0013509688,0.010698262,0.9870276,0.00036712544,0.00018709194,0.00016530583,0.0000013442933,0.00003860886,0.00016369761],"genre_scores_gemma":[0.30187756,0.0062716594,0.69155425,0.00006876519,0.00018044746,0.000009637857,0.000010996386,0.0000213174,0.000005358163],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926955,0.000047939742,0.00037611858,0.0000583079,0.00006965254,0.00017841694],"domain_scores_gemma":[0.9990843,0.00022119019,0.00014105895,0.00027075567,0.00015369042,0.00012902103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003235013,0.00011822939,0.00021247346,0.0000672487,0.00014459687,0.00005831774,0.00019140782,0.00007550014,0.000004592962],"category_scores_gemma":[0.000005788379,0.000110637986,0.000046063735,0.00012877956,0.000048566042,0.00052255404,0.000058856454,0.00020949473,1.8788775e-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":[0.00003889539,0.00007702217,0.00007176102,0.000030625008,0.000090923604,1.8280352e-7,0.0003355089,0.9541151,0.00043398517,0.003413096,0.0023425082,0.039050415],"study_design_scores_gemma":[0.0007341909,0.0000509961,0.00027109965,0.00011022309,0.00003965473,0.000049634917,0.00001858937,0.98136544,0.000016666998,0.00025956705,0.016964667,0.00011929126],"about_ca_topic_score_codex":3.6127656e-7,"about_ca_topic_score_gemma":1.7745796e-7,"teacher_disagreement_score":0.3005266,"about_ca_system_score_codex":0.000023463235,"about_ca_system_score_gemma":0.0000105269655,"threshold_uncertainty_score":0.4511686},"labels":[],"label_agreement":null},{"id":"W2048246470","doi":"10.1007/s11276-014-0697-y","title":"Bee colony optimization aided adaptive resource allocation in OFDMA systems with proportional rate constraints","year":2014,"lang":"en","type":"article","venue":"Wireless Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Resource allocation; Mathematical optimization; Orthogonal frequency-division multiple access; Orthogonal frequency-division multiplexing; Telecommunications; Computer network; Mathematics","score_opus":0.005567075929725015,"score_gpt":0.18282231882482336,"score_spread":0.17725524289509834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048246470","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":[0.023189478,0.00025877098,0.97390974,0.000051369538,0.0002341411,0.00078939804,0.000006178238,0.0004329014,0.0011280375],"genre_scores_gemma":[0.99201703,0.00017985204,0.006684237,0.000050536753,0.00033161356,0.00032544308,0.00022647851,0.00010678256,0.00007799934],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981598,0.0001862947,0.000531103,0.0003915421,0.00025839815,0.00047286396],"domain_scores_gemma":[0.99913746,0.0001677238,0.00020329088,0.00021977747,0.00015907107,0.00011267198],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038673353,0.0003186848,0.00037800623,0.0001533907,0.00010593898,0.00006612627,0.00016756465,0.00024754638,0.000023632272],"category_scores_gemma":[0.000018883555,0.00032237006,0.00003243846,0.00064765406,0.00016161811,0.00031788525,0.000025842306,0.00031433924,0.0000041550616],"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":[0.00011331815,0.000031393007,0.000727441,0.000038941867,0.000038678198,0.0000056885206,0.000077115285,0.98995596,0.0000621814,0.002381007,0.00034100548,0.0062272903],"study_design_scores_gemma":[0.0010714317,0.00007150327,0.0006113664,0.00040188563,0.000021489332,0.000010266075,0.00009212514,0.9970619,0.000059695027,0.000021438758,0.00019579791,0.00038109662],"about_ca_topic_score_codex":0.000013856111,"about_ca_topic_score_gemma":0.0000724008,"teacher_disagreement_score":0.9688276,"about_ca_system_score_codex":0.00022727999,"about_ca_system_score_gemma":0.00003881472,"threshold_uncertainty_score":0.9999228},"labels":[],"label_agreement":null},{"id":"W2048546627","doi":"10.1109/vtcspring.2013.6692527","title":"Dynamic Scheduling with Statistical Delay Guarantees and Traffic Dropping","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Scheduling (production processes); Fading; Mathematical optimization; Online algorithm; Dynamic priority scheduling; Wireless; Wireless network; Real-time computing; Algorithm; Computer network; Mathematics; Decoding methods; Quality of service; Telecommunications","score_opus":0.0027991395408177204,"score_gpt":0.18566154972619373,"score_spread":0.182862410185376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048546627","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":[0.36637324,0.00013519757,0.63283515,0.000013741599,0.00002164453,0.000086793756,8.029338e-7,0.00023789896,0.000295564],"genre_scores_gemma":[0.71932894,0.00007045038,0.28050378,0.000011909564,0.000008335703,0.000012359944,0.000006950406,0.000023973376,0.000033318207],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995285,0.000005757821,0.00010725119,0.000116042065,0.00006511036,0.00017729525],"domain_scores_gemma":[0.9997948,0.00005017768,0.000010087246,0.00007348861,0.000022450995,0.000049018054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000020014468,0.000102425554,0.000098919205,0.000036128105,0.000039514674,0.00003989696,0.00003276989,0.000034530603,0.0000885662],"category_scores_gemma":[0.0000052540504,0.0000852198,0.0000057340467,0.00008209496,0.000033948414,0.00020379227,0.0000081569615,0.000085609696,0.000020628],"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":[0.0000018454413,0.000002942939,0.000065923006,0.000019798368,0.0000117840555,0.00000242893,0.00004248234,0.98118055,0.00032444095,0.00045811254,0.000015838363,0.017873827],"study_design_scores_gemma":[0.00017589769,0.000018238183,0.00047897306,0.00002928739,0.0000052825153,0.000014582039,0.00008197383,0.99894315,0.000030458667,0.000076178585,0.000014352884,0.00013165492],"about_ca_topic_score_codex":0.0000032044877,"about_ca_topic_score_gemma":0.000020779153,"teacher_disagreement_score":0.3529557,"about_ca_system_score_codex":0.00002357468,"about_ca_system_score_gemma":0.0000038346407,"threshold_uncertainty_score":0.34751627},"labels":[],"label_agreement":null},{"id":"W2048977498","doi":"10.1109/mwc.2007.314550","title":"Performance of packet voice transmission using IEEE 802.16 protocol","year":2007,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":40,"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":"Computer network; Computer science; Polling; Network packet; Scheduling (production processes); IEEE 802; Bandwidth allocation; Dynamic bandwidth allocation; Base station; Telecommunications link; Bandwidth (computing); Quality of service; Real-time computing","score_opus":0.031074349217608304,"score_gpt":0.2992008946272084,"score_spread":0.26812654540960007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048977498","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":[0.27403674,0.00010013269,0.7110522,0.000024546145,0.00015851382,0.011059163,0.000010349567,0.0003995492,0.0031588417],"genre_scores_gemma":[0.94662356,0.00026949533,0.04990808,0.000013458506,0.000062168474,0.0029901455,0.000021600998,0.0000752696,0.000036228947],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985929,0.000057846086,0.0006007106,0.00015972408,0.0002143035,0.00037450079],"domain_scores_gemma":[0.9980981,0.00017482058,0.0001554861,0.0013108483,0.00015946971,0.00010127996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003325857,0.00021434476,0.0002559653,0.00015920847,0.00026027797,0.000015001271,0.0007312554,0.0001464656,0.000014327439],"category_scores_gemma":[0.0000055518367,0.00023340825,0.00006894852,0.0006395005,0.00015939593,0.00035805235,0.000045733195,0.0003334132,0.000010686406],"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":[0.00004740436,0.00012374738,0.0009795242,0.00025792912,0.00003229474,5.480265e-7,0.0003988296,0.85745764,0.07695799,0.000126121,0.00012964885,0.06348829],"study_design_scores_gemma":[0.0004859933,0.000031619053,0.00043366122,0.00029871013,0.000019459654,0.0000063966418,0.000052761046,0.91245097,0.08206938,0.000026381897,0.0038616988,0.0002629617],"about_ca_topic_score_codex":0.000013272846,"about_ca_topic_score_gemma":0.000033887143,"teacher_disagreement_score":0.6725868,"about_ca_system_score_codex":0.00018225407,"about_ca_system_score_gemma":0.000038840175,"threshold_uncertainty_score":0.95181125},"labels":[],"label_agreement":null},{"id":"W2049878284","doi":"10.1109/isit.2007.4557378","title":"On the capacity region of parallel Gaussian broadcast channels with common information","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Generalization; Computer science; Transmitter; Gaussian; Mathematical optimization; Constraint (computer-aided design); Boundary (topology); Scalar (mathematics); Optimization problem; Regular polygon; Transmitter power output; Convex optimization; Topology (electrical circuits); Algorithm; Mathematics; Telecommunications; Combinatorics; Channel (broadcasting)","score_opus":0.011579501079885484,"score_gpt":0.19320805490148585,"score_spread":0.18162855382160037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049878284","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":[0.08700438,0.000007736703,0.8929327,0.00007850656,0.000066897905,0.00018030197,7.6118334e-7,0.00013165771,0.019597031],"genre_scores_gemma":[0.995683,0.00002263082,0.0041225944,0.000086767686,0.000025984715,0.0000059763383,0.000010919626,0.0000113263,0.000030776253],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951,0.0000083843615,0.00017619834,0.00004366416,0.000120741264,0.00014100576],"domain_scores_gemma":[0.9996464,0.00006760817,0.000055752378,0.00016994368,0.000032095213,0.00002819988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009948559,0.00009019263,0.00008831943,0.000055389064,0.000041002095,0.00001075463,0.00007070138,0.000046119214,0.000012810457],"category_scores_gemma":[0.0000067029005,0.000057368554,0.000015480045,0.00019119422,0.0000328833,0.00029001967,0.0000065970257,0.00010127288,0.000008560658],"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":[0.000031951895,0.0000059815993,0.00008758996,0.00001405665,0.000007775447,5.684193e-7,0.00032708308,0.9775009,0.000012189634,0.01718183,0.00042661972,0.0044034407],"study_design_scores_gemma":[0.0006449616,0.00017154687,0.0021574828,0.00014217249,0.0000106100415,0.000021382277,0.0004392908,0.9863756,0.006394921,0.0013383892,0.0020046919,0.00029899346],"about_ca_topic_score_codex":0.000013285852,"about_ca_topic_score_gemma":0.000029558218,"teacher_disagreement_score":0.90867865,"about_ca_system_score_codex":0.000036461268,"about_ca_system_score_gemma":0.000002418775,"threshold_uncertainty_score":0.23394218},"labels":[],"label_agreement":null},{"id":"W2050635014","doi":"10.1109/noms.2014.6838421","title":"Traffic engineering for software-defined radio access networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Huawei Technologies (Canada)","funders":"","keywords":"Computer network; Computer science; Backhaul (telecommunications); Radio access network; Wireless network; Wireless; Software-defined radio; Robustness (evolution); Traffic engineering; Access network; Radio resource management; Telecommunications link; Remote radio head; Distributed computing; Cognitive radio; Base station; Telecommunications","score_opus":0.006953052100589856,"score_gpt":0.20476890115225627,"score_spread":0.1978158490516664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050635014","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":[0.0039227465,0.00016824818,0.99273825,0.00001778182,0.0006450493,0.00026093808,0.0000014050295,0.0019743608,0.00027122104],"genre_scores_gemma":[0.80588484,0.000074376476,0.1930602,0.00004986385,0.00052205217,0.000120383935,0.000047913432,0.00012820054,0.00011218993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999199,0.00000581961,0.0002021377,0.00017253098,0.00007115317,0.00034940758],"domain_scores_gemma":[0.9994376,0.0002311296,0.000021749718,0.00019947896,0.000032062602,0.00007798864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009059944,0.00018177772,0.0001917577,0.000070388734,0.000045783843,0.000058783466,0.00019170908,0.000100497935,0.000025663585],"category_scores_gemma":[0.00006489411,0.00019205827,0.000058690748,0.00021204454,0.000008485046,0.0002665018,0.000020748668,0.00010215633,0.000005327873],"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":[0.0000043753616,0.0000040896584,0.000030227679,0.00003617843,0.000015268242,1.5658371e-7,0.00000898686,0.9692613,0.000022784769,0.0006305904,0.0017375473,0.02824851],"study_design_scores_gemma":[0.00037417863,0.000016124333,0.000109708606,0.000018372804,0.00001030433,0.0000015928076,0.0000010661548,0.99238497,0.0001556524,0.000039219904,0.0066476795,0.0002411548],"about_ca_topic_score_codex":4.6361637e-7,"about_ca_topic_score_gemma":0.0000036814558,"teacher_disagreement_score":0.8019621,"about_ca_system_score_codex":0.000049557275,"about_ca_system_score_gemma":0.0000036503086,"threshold_uncertainty_score":0.7831909},"labels":[],"label_agreement":null},{"id":"W2050803576","doi":"10.1007/s11277-009-9680-9","title":"A Coordinated Location-dependent Downlink Scheduling Scheme in Cellular TD-CDMA Networks with Partitioned Cells: A Two-Cell Two-Partition Case","year":2009,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Telecommunications link; Scheduling (production processes); Cellular network; Base station; Computer network; Throughput; Partition (number theory); Code division multiple access; Real-time computing; Mathematical optimization; Wireless; Telecommunications; Mathematics","score_opus":0.011588067302903172,"score_gpt":0.23554705509593074,"score_spread":0.22395898779302756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050803576","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":[0.37957135,0.0023046792,0.6137623,0.00057343737,0.00012715698,0.0009012358,0.000029845076,0.0007816352,0.0019483591],"genre_scores_gemma":[0.96476626,0.0005666255,0.03354091,0.00011889956,0.00010431712,0.0002296637,0.00054725556,0.000080031845,0.00004603737],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979354,0.0001892497,0.00063322345,0.00040429775,0.00027120084,0.0005666393],"domain_scores_gemma":[0.99808335,0.00017566791,0.00018015414,0.0010752631,0.00030089324,0.00018465306],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003049567,0.00039508095,0.0003751132,0.00025040348,0.00049426424,0.00011808127,0.0004997151,0.00016615815,0.000040734558],"category_scores_gemma":[0.000012052223,0.00044658978,0.00007018206,0.0013274554,0.00015831727,0.0005527805,0.00007909427,0.00083707756,0.000045500223],"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":[0.000042612795,0.00028081797,0.0002098181,0.000030984527,0.000028693134,0.00008845762,0.0006663031,0.9882167,0.007807491,0.0012542284,0.000033859145,0.0013400653],"study_design_scores_gemma":[0.0020055675,0.00005823698,0.000063413296,0.00022503287,0.000045081237,0.00010074174,0.0006902403,0.99333555,0.0027832359,0.00009623314,0.00007497943,0.00052167114],"about_ca_topic_score_codex":0.0001097939,"about_ca_topic_score_gemma":0.0009821161,"teacher_disagreement_score":0.5851949,"about_ca_system_score_codex":0.00039251545,"about_ca_system_score_gemma":0.000079921636,"threshold_uncertainty_score":0.9997986},"labels":[],"label_agreement":null},{"id":"W2051287757","doi":"10.1109/chinacom.2008.4685018","title":"Memetic algorithms with multi-local-search for resource allocation in multiuser OFDM based Cognitive Radio systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Orthogonal frequency-division multiplexing; Cognitive radio; Memetic algorithm; Computer science; Wireless; Flexibility (engineering); Resource allocation; Multiplexing; Spectral efficiency; Algorithm; Computer network; Local search (optimization); Channel (broadcasting); Telecommunications; Mathematics","score_opus":0.025370004309161205,"score_gpt":0.2443725950185302,"score_spread":0.219002590709369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051287757","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":[0.01578872,0.00024042619,0.9821455,0.00001867483,0.00005904185,0.0012123747,0.000009910518,0.0003038852,0.0002214839],"genre_scores_gemma":[0.89586425,0.00003925008,0.10317783,0.000025452953,0.00005076602,0.00037320657,0.00012130262,0.00008325565,0.0002646755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886316,0.00005063306,0.00027179,0.00026662016,0.00020610249,0.0003417004],"domain_scores_gemma":[0.9992807,0.00028087368,0.000031510182,0.00016495801,0.00016369375,0.000078257515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001609328,0.0001913675,0.00022716692,0.00018638083,0.00007517546,0.000015368534,0.00009009514,0.000099864636,0.000008208722],"category_scores_gemma":[0.000023921473,0.00017775557,0.000028369866,0.00042812503,0.00007397553,0.00016260095,0.000009176734,0.0001438523,0.0000082862],"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":[0.000066704284,0.000048950697,0.00054245937,0.00008143736,0.00002099553,0.000007604116,0.00029273474,0.9956612,0.00011366208,0.000025974667,0.0000643163,0.0030739908],"study_design_scores_gemma":[0.0029673716,0.00006760415,0.0007904555,0.00014811724,0.0000113906,0.000007721249,0.00050326675,0.99180776,0.0032792324,4.7357847e-7,0.00017221463,0.0002443853],"about_ca_topic_score_codex":0.000061882325,"about_ca_topic_score_gemma":0.00006974172,"teacher_disagreement_score":0.8800755,"about_ca_system_score_codex":0.00018404584,"about_ca_system_score_gemma":0.000032892924,"threshold_uncertainty_score":0.72486615},"labels":[],"label_agreement":null},{"id":"W2051733258","doi":"10.1109/icc.2013.6655573","title":"Uplink resource allocation for interworking of WLAN and OFDMA-based femtocell systems","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Femtocell; Subcarrier; Computer network; Resource allocation; Telecommunications link; Frequency-division multiple access; Orthogonal frequency-division multiple access; Orthogonal frequency-division multiplexing; Transmitter power output; Optimization problem; Physical layer; Distributed computing; Wireless; Base station; Algorithm; Telecommunications; Channel (broadcasting); Transmitter","score_opus":0.00746212787741573,"score_gpt":0.18519292017977315,"score_spread":0.17773079230235742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051733258","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":[0.033531748,0.00036052414,0.96481484,0.00004201285,0.00008716492,0.00048191386,0.0000010826607,0.00015479611,0.00052589964],"genre_scores_gemma":[0.9802444,0.000023163868,0.019339066,0.000016550735,0.000055361717,0.00013740537,0.000020488562,0.000028344986,0.0001352342],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995703,0.000006675812,0.00018106517,0.00009065978,0.000044297023,0.00010699756],"domain_scores_gemma":[0.99970555,0.00007684931,0.000034731296,0.00010173267,0.00005221957,0.000028930042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052755666,0.00007716388,0.00010979494,0.000048985927,0.000019512563,0.000020133852,0.00004773626,0.000051334286,0.00001045668],"category_scores_gemma":[0.0000075919197,0.00007488458,0.000015817466,0.000075845885,0.000012746173,0.00007777177,0.000008247395,0.000035940648,0.0000018259196],"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":[0.0000035735666,0.000004079974,0.00030155643,0.00017685654,0.000008199091,2.294832e-8,0.00004129861,0.99081403,0.0030400434,0.0002825682,0.00041978149,0.0049079624],"study_design_scores_gemma":[0.00021747003,0.00001588039,0.00009147237,0.00010041668,0.0000064002247,2.9222954e-7,0.000062706844,0.99603766,0.0028927168,0.00002776605,0.000466199,0.000081023696],"about_ca_topic_score_codex":0.000015623622,"about_ca_topic_score_gemma":0.0000029174419,"teacher_disagreement_score":0.9467126,"about_ca_system_score_codex":0.000021467553,"about_ca_system_score_gemma":0.0000030248054,"threshold_uncertainty_score":0.30537045},"labels":[],"label_agreement":null},{"id":"W2051835769","doi":"10.1145/1198513.1198523","title":"Optimally scheduling video-on-demand to minimize delay when sender and receiver bandwidth may differ","year":2006,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Communication source; Upper and lower bounds; Bandwidth (computing); Network packet; Scheduling (production processes); Computer network; Real-time computing; Bandwidth allocation; Channel (broadcasting); Algorithm; Mathematics; Mathematical optimization","score_opus":0.009493140495814548,"score_gpt":0.21849763498636207,"score_spread":0.20900449449054753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051835769","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":[0.017302629,0.00016193293,0.980298,0.0005146051,0.0003976439,0.00031069256,0.000035020876,0.0004072671,0.000572202],"genre_scores_gemma":[0.41235572,0.00024018025,0.58627176,0.00020444795,0.00016739253,0.000080934966,0.000018986593,0.00010006869,0.0005605108],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866706,0.000031456122,0.00029508452,0.0004013545,0.00022480123,0.0003802193],"domain_scores_gemma":[0.99915546,0.000188127,0.000030062938,0.0004259814,0.000052848187,0.0001475156],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008311943,0.00031440292,0.00025871757,0.00021023168,0.00018824959,0.0000671745,0.00016667503,0.00015897093,0.0001249788],"category_scores_gemma":[0.000012107069,0.0003232996,0.00006873353,0.0002578402,0.000039181654,0.0002321898,0.0000067772316,0.00030453928,0.000054453725],"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":[0.000043493925,0.000051244373,0.000032430667,0.000015115433,0.000049256174,0.0000091332795,0.00013080549,0.9551976,0.00037194794,0.000025883586,0.0002549363,0.04381821],"study_design_scores_gemma":[0.0021175332,0.00016694567,0.002301462,0.00017786866,0.00010831351,0.000041548326,0.0000907603,0.9825587,0.0070553496,0.001317473,0.0030928566,0.00097117963],"about_ca_topic_score_codex":0.000013179906,"about_ca_topic_score_gemma":0.00001271319,"teacher_disagreement_score":0.39505312,"about_ca_system_score_codex":0.00010976709,"about_ca_system_score_gemma":0.0000101327805,"threshold_uncertainty_score":0.9999219},"labels":[],"label_agreement":null},{"id":"W2051942439","doi":"10.1109/twc.2013.062713.130302","title":"Energy and Content Aware Multi-Homing Video Transmission in Heterogeneous Networks","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Computer science; Network packet; Quality of service; Video quality; Computer network; Multihoming; Wireless; Transmission (telecommunications); Wireless network; Optimization problem; Linearization; Heterogeneous network; Piecewise; Real-time computing; Algorithm; Telecommunications; The Internet","score_opus":0.0250163501901829,"score_gpt":0.23216419490624968,"score_spread":0.2071478447160668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051942439","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":[0.018618463,0.0013750813,0.97889477,0.0001872167,0.00014455272,0.00035136478,0.000008351203,0.00035912328,0.00006105901],"genre_scores_gemma":[0.97559804,0.011267535,0.012345905,0.00008251313,0.0000132989435,0.0005210872,0.000022479504,0.000078838886,0.000070313035],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998783,0.00010613868,0.0004369579,0.00024126595,0.00010894101,0.00032372636],"domain_scores_gemma":[0.99867773,0.00023008502,0.000049062277,0.00083305466,0.000069508795,0.00014053196],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000612492,0.00025744256,0.0002613916,0.00021521084,0.00028599479,0.0000573306,0.00036464207,0.00017471377,0.00003662752],"category_scores_gemma":[0.0000010013242,0.0002849078,0.000070118615,0.00037736696,0.00011267879,0.00034180793,0.0000053952426,0.00037591317,0.000007022166],"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":[0.0000055626333,0.00009703794,0.000022787803,0.000011073278,0.000024234976,8.034861e-7,0.00014526522,0.788793,0.0013257439,0.00003311684,0.000013898636,0.20952746],"study_design_scores_gemma":[0.0006379159,0.000022490554,0.00012026333,0.00014763483,0.00001779515,0.0000095745,0.00010345002,0.9954241,0.0029288966,0.000021102354,0.00028758278,0.00027921074],"about_ca_topic_score_codex":0.00018914697,"about_ca_topic_score_gemma":0.00084877823,"teacher_disagreement_score":0.96654886,"about_ca_system_score_codex":0.00013620357,"about_ca_system_score_gemma":0.000011721649,"threshold_uncertainty_score":0.9999603},"labels":[],"label_agreement":null},{"id":"W2053742886","doi":"10.1145/2713168.2713179","title":"Dynamic configuration of single frequency networks in mobile streaming systems","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Unicast; Computer network; Multicast; Wireless network; Multi-frequency network; Bandwidth (computing); Wireless; Cellular network; Distributed computing; Heterogeneous network; Telecommunications","score_opus":0.009468461240817743,"score_gpt":0.2130424024171775,"score_spread":0.20357394117635977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053742886","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":[0.08038309,0.0015712676,0.9109862,0.0000012596432,0.00034423382,0.00023948635,0.0000014076802,0.00017385723,0.0062992126],"genre_scores_gemma":[0.9953952,0.000068770714,0.0043532266,0.00000158312,0.000024295297,0.000032720796,0.000039653594,0.000023446491,0.00006113727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938637,0.000017629516,0.00027946598,0.00008974668,0.0000854486,0.00014131273],"domain_scores_gemma":[0.999709,0.000029214196,0.000044530327,0.00012233257,0.00005599799,0.000038912665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007811684,0.00008786597,0.00014874367,0.00007120332,0.000007397378,0.0000117331365,0.00005362332,0.00007291745,0.000007421603],"category_scores_gemma":[0.000010200206,0.00009313947,0.0000125021415,0.00018353043,0.00001685311,0.00019978026,0.000006445367,0.00006418909,0.0000029805847],"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":[0.000001672787,0.000012399507,0.0003566164,0.000019524412,0.0000040674518,0.0000011331986,0.00010636643,0.9944064,0.0020132854,0.0003911212,0.000027091848,0.0026603313],"study_design_scores_gemma":[0.00020985959,0.000033133638,0.00008021495,0.00005556747,0.0000025574961,0.0000014106507,0.0002508531,0.9987567,0.00042786068,0.000054975135,0.000032994893,0.00009385172],"about_ca_topic_score_codex":0.00003761182,"about_ca_topic_score_gemma":0.000094214236,"teacher_disagreement_score":0.91501206,"about_ca_system_score_codex":0.00016445026,"about_ca_system_score_gemma":0.0000091516085,"threshold_uncertainty_score":0.37981173},"labels":[],"label_agreement":null},{"id":"W2055061559","doi":"10.1109/vetecf.2008.264","title":"Resource Allocation for Downlink Spectrum Sharing in Cognitive Radio Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Group for Research in Decision Analysis; Institut National de la Recherche Scientifique; University of Waterloo","funders":"","keywords":"Cognitive radio; Heuristics; Resource allocation; Computer science; Telecommunications link; Resource management (computing); Base station; Mathematical optimization; Optimization problem; Orthogonal frequency-division multiplexing; Frequency allocation; Shared resource; Computer network; Distributed computing; Telecommunications; Algorithm; Wireless; Mathematics","score_opus":0.015251196534152241,"score_gpt":0.22476798782540683,"score_spread":0.20951679129125458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055061559","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":[0.02416569,0.00026448525,0.9698137,0.00005054281,0.00009601532,0.00038342096,0.0000015251419,0.00033962764,0.004884965],"genre_scores_gemma":[0.989304,0.00027594596,0.00951378,0.00005104292,0.0002314435,0.000080358834,0.00010840556,0.000045480272,0.0003895088],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992802,0.000006547104,0.00020059776,0.0001871746,0.0000619244,0.00026353355],"domain_scores_gemma":[0.9997055,0.00010095983,0.000023449866,0.00010986156,0.000020706586,0.000039548235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007421786,0.00011829069,0.00013044072,0.00008410348,0.000058015703,0.000010111852,0.00007879969,0.000081935395,0.000028098688],"category_scores_gemma":[0.000020481413,0.00013382004,0.000028804714,0.00026488327,0.000019802068,0.00016068289,0.00001603172,0.00012548517,0.000004517213],"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":[0.000018888824,0.000008149153,0.0011300015,0.000007671054,0.00000878114,0.0000024724409,0.00012580276,0.99555266,0.00001687584,0.0004431686,0.00052318827,0.0021623685],"study_design_scores_gemma":[0.00057305425,0.000015395979,0.0016238857,0.000041260824,0.0000045338043,0.0000069122802,0.000039314604,0.9963333,0.00043940777,0.0001624058,0.0005958749,0.0001646806],"about_ca_topic_score_codex":0.0000044049098,"about_ca_topic_score_gemma":0.000043260625,"teacher_disagreement_score":0.9651383,"about_ca_system_score_codex":0.00009905664,"about_ca_system_score_gemma":0.000005386859,"threshold_uncertainty_score":0.5457023},"labels":[],"label_agreement":null},{"id":"W2055259198","doi":"10.1145/1164717.1164739","title":"QoS-guaranteed wireless packet scheduling for mixed services in HSDPA","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Dalhousie University","funders":"","keywords":"Computer science; Scheduling (production processes); Quality of service; Computer network; Network packet; Wireless; Dynamic priority scheduling; Round-robin scheduling; Distributed computing; Real-time computing; Engineering; Telecommunications","score_opus":0.004517214451634471,"score_gpt":0.20089727901775842,"score_spread":0.19638006456612395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055259198","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":[0.5154225,0.0001904344,0.4820351,0.000024701687,0.00029953723,0.00028657238,0.0000063238044,0.00042187635,0.0013129443],"genre_scores_gemma":[0.9432053,0.000029775569,0.05620084,0.00003528147,0.00023000494,0.000070114,0.00007513171,0.00005806053,0.00009550103],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999145,0.000009119323,0.00027304917,0.00017549815,0.000084306055,0.00031308265],"domain_scores_gemma":[0.99970067,0.00006550528,0.000030414176,0.0001434946,0.000033695433,0.00002621095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007743673,0.00015912275,0.0001867938,0.00009794392,0.00003728142,0.000029507182,0.00011021058,0.0000939183,0.000015713766],"category_scores_gemma":[0.0000027712474,0.00016789426,0.000038911225,0.00027897808,0.00001174522,0.00019884281,0.000014210255,0.0000837846,0.000010083214],"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":[0.00001194422,0.00001530078,0.0016085489,0.00011865354,0.000006095508,0.0000013655772,0.000038154056,0.9917897,0.002479285,0.0019278082,0.00013415779,0.0018689956],"study_design_scores_gemma":[0.0007032057,0.00000829505,0.00089496485,0.00006606936,0.0000050925178,0.0000011982207,0.00009438748,0.9885539,0.008126086,0.00072380964,0.00060912303,0.00021391705],"about_ca_topic_score_codex":0.000043422904,"about_ca_topic_score_gemma":0.0008403721,"teacher_disagreement_score":0.42778277,"about_ca_system_score_codex":0.00006255188,"about_ca_system_score_gemma":0.0000059808094,"threshold_uncertainty_score":0.6846529},"labels":[],"label_agreement":null},{"id":"W2055538208","doi":"10.1109/twc.2012.091812.120329","title":"Decentralized Radio Resource Allocation for Single-Network and Multi-Homing Services in Cooperative Heterogeneous Wireless Access Medium","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"Utah Agricultural Experiment Station","keywords":"Computer network; Computer science; Wireless network; Multihoming; Radio resource management; Multi-frequency network; Resource allocation; Heterogeneous network; Heterogeneous wireless network; Wireless; Wireless WAN; Bandwidth allocation; Radio access network; Distributed computing; Wi-Fi array; Bandwidth (computing); Telecommunications; Base station; The Internet","score_opus":0.03230417346238739,"score_gpt":0.2782918667180496,"score_spread":0.24598769325566222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055538208","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":[0.078239165,0.001974757,0.9175492,0.00021945233,0.0003681323,0.0011242642,0.000051712654,0.00040055416,0.00007278005],"genre_scores_gemma":[0.9752691,0.0036072389,0.019839926,0.000097579265,0.00007181127,0.00083929766,0.00012927748,0.000121091354,0.000024694542],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981649,0.00020165165,0.000567645,0.00028938815,0.00016032097,0.00061612995],"domain_scores_gemma":[0.99803907,0.0006262863,0.0001217301,0.0009099555,0.00011519006,0.00018778227],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025903972,0.0003491402,0.0003881979,0.00021059408,0.00045080125,0.000114925235,0.0006655509,0.00021103604,0.00000792266],"category_scores_gemma":[0.0000048198954,0.00040668767,0.00007637187,0.0006440006,0.00015068165,0.0008407464,0.000015302829,0.00039644266,0.000003994793],"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":[0.000059311154,0.00030990335,0.00023511867,0.00009037295,0.00007974095,3.409555e-7,0.0013436856,0.9782422,0.003390968,0.00013099004,0.000023314447,0.016094064],"study_design_scores_gemma":[0.0015003267,0.000037161506,0.00019344757,0.0002800558,0.00007287292,0.000014336499,0.00028041354,0.9799685,0.016041081,0.000017651617,0.0011257093,0.00046845817],"about_ca_topic_score_codex":0.000030252737,"about_ca_topic_score_gemma":0.0012392473,"teacher_disagreement_score":0.89770925,"about_ca_system_score_codex":0.00028460624,"about_ca_system_score_gemma":0.000023386496,"threshold_uncertainty_score":0.9998385},"labels":[],"label_agreement":null},{"id":"W2057458116","doi":"10.1109/titb.2011.2154384","title":"Cross-Layer Ultrasound Video Streaming Over Mobile WiMAX and HSUPA Networks","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Information Technology in Biomedicine","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":45,"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":"Information Technology Research Centre; Cardiff University; Kingston University","keywords":"WiMAX; Mobile broadband; IMT Advanced; Computer science; Computer network; Interoperability; Network packet; Quality of service; Broadband; Wireless broadband; Mobile computing; Telecommunications; Mobile technology; Wireless; Wireless network; Mobile Web","score_opus":0.00615366433738879,"score_gpt":0.2235796573165212,"score_spread":0.21742599297913243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057458116","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":[0.19348042,0.00014488773,0.8045875,0.000019385432,0.0004883003,0.0002876101,0.000013345457,0.00062144274,0.00035710348],"genre_scores_gemma":[0.9949196,0.0009487531,0.0038202994,0.000057475285,0.000022111835,0.00016730562,0.00002216521,0.000022686403,0.000019599898],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989689,0.0000076601655,0.000488068,0.00013373316,0.00011632688,0.00028531445],"domain_scores_gemma":[0.9995116,0.000067165885,0.00007368365,0.0002447303,0.000049043683,0.000053759468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010308564,0.00020008837,0.00020282614,0.0010180881,0.00009672306,0.000017929173,0.0001214006,0.00034608252,0.00015403546],"category_scores_gemma":[0.000007275569,0.0002022534,0.000023075616,0.0010479665,0.00025313263,0.0009344673,0.0000018769398,0.000415735,0.000017580745],"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":[0.00003776824,0.000040063474,0.0012217445,0.000043148248,0.000035097004,0.0000027542467,0.00073054957,0.8839522,0.0008000627,0.00010162073,0.00005757826,0.112977415],"study_design_scores_gemma":[0.0037540465,0.00051497953,0.0059917034,0.0003171809,0.000054364504,0.000105661944,0.0013983516,0.94382846,0.040794242,0.00080094027,0.001685285,0.0007548021],"about_ca_topic_score_codex":0.000015667561,"about_ca_topic_score_gemma":0.000014545819,"teacher_disagreement_score":0.80143917,"about_ca_system_score_codex":0.00011398105,"about_ca_system_score_gemma":0.000007658818,"threshold_uncertainty_score":0.82476544},"labels":[],"label_agreement":null},{"id":"W2057597091","doi":"10.1109/twc.2012.100112.112254","title":"Performance Modeling and Stability of Semi-Persistent Scheduling with Initial Random Access in LTE","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":44,"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","funders":"","keywords":"Random access; Voice over IP; Computer science; Scheduling (production processes); Computer network; Network packet; Stability (learning theory); Mathematical optimization; Mathematics; The Internet","score_opus":0.03881129812064971,"score_gpt":0.2709410568966308,"score_spread":0.23212975877598108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057597091","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":[0.50887746,0.00021367363,0.4903819,0.000021757714,0.00005749706,0.00018125327,0.0000082300085,0.00007033789,0.0001878672],"genre_scores_gemma":[0.9879887,0.0023507639,0.00945705,0.00000806494,0.000012983443,0.00013472185,0.0000097497905,0.000036728565,0.0000012500215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990645,0.0000755019,0.00035499447,0.00012810284,0.00013208673,0.00024482972],"domain_scores_gemma":[0.9989106,0.00018146462,0.000053056156,0.0007026617,0.00007470193,0.00007749165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001994506,0.00016315578,0.00023813218,0.00016628484,0.00017921366,0.000020360856,0.0003167683,0.000078713594,0.0000082015595],"category_scores_gemma":[0.0000026508073,0.00016876723,0.000044854314,0.0004367325,0.00012952944,0.00080407644,0.0000073188135,0.0003807721,0.0000010528388],"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":[0.000073278665,0.00013996179,0.0012831679,0.000075973665,0.000035443765,5.3828796e-8,0.000801643,0.9905715,0.0005266197,0.0000214519,1.4589804e-7,0.006470755],"study_design_scores_gemma":[0.0008925643,0.000026116006,0.0001366926,0.00019074821,0.0000373529,0.000002761511,0.0002726479,0.9915716,0.0066908463,0.0000037118334,0.000003175815,0.00017179003],"about_ca_topic_score_codex":0.000024293413,"about_ca_topic_score_gemma":0.00013866756,"teacher_disagreement_score":0.48092484,"about_ca_system_score_codex":0.000106420885,"about_ca_system_score_gemma":0.000022719181,"threshold_uncertainty_score":0.6882128},"labels":[],"label_agreement":null},{"id":"W2058448956","doi":"10.1109/glocomw.2013.6825000","title":"Radio resource allocation for multicast transmissions over High Altitude Platforms","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Multicast; Computer science; Subgradient method; Mathematical optimization; Simplex algorithm; Resource allocation; Linear programming; Linear programming relaxation; Optimization problem; Lagrangian relaxation; Integer programming; Relaxation (psychology); Computer network; Algorithm; Mathematics","score_opus":0.00633282961731227,"score_gpt":0.20499421386730596,"score_spread":0.1986613842499937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058448956","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":[0.032503426,0.000059334645,0.9650167,0.00014134377,0.00010218052,0.0005975015,0.000003958396,0.00047293314,0.0011025876],"genre_scores_gemma":[0.86336017,0.000048444686,0.13535246,0.00007044874,0.00011204154,0.00019807846,0.00009476902,0.000054369546,0.00070920604],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993628,0.0000025807126,0.00018487877,0.00013611684,0.000087177876,0.0002264166],"domain_scores_gemma":[0.99961287,0.00007615711,0.000017779083,0.00016694245,0.000036070796,0.000090171015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003389957,0.00012405751,0.00011152801,0.000047890237,0.00006789825,0.000025382653,0.00008551076,0.00008167232,0.00034187353],"category_scores_gemma":[0.00001246438,0.00010745914,0.00003738899,0.00010792187,0.000015145186,0.00032162358,0.000006608465,0.000071908784,0.00003916924],"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":[0.0000047379663,0.000013281445,0.000025560295,0.00002324033,0.000016572809,1.1302985e-7,0.00009811808,0.9737587,0.0024807795,0.0026626082,0.0059756297,0.014940654],"study_design_scores_gemma":[0.00059493794,0.000015473572,0.0009865606,0.000018189849,0.000009094525,9.50734e-7,0.000032492393,0.98532885,0.0024090316,0.00055563275,0.009880528,0.00016827839],"about_ca_topic_score_codex":0.000013407915,"about_ca_topic_score_gemma":0.000008828602,"teacher_disagreement_score":0.83085674,"about_ca_system_score_codex":0.000056181423,"about_ca_system_score_gemma":0.00000492054,"threshold_uncertainty_score":0.43820566},"labels":[],"label_agreement":null},{"id":"W2059686654","doi":"10.1109/tac.2013.2283098","title":"Explicit Characterization of Stability Region for Stationary Multi-Queue Multi-Server Systems","year":2013,"lang":"en","type":"preprint","venue":"IEEE Transactions on Automatic Control","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Queue; Hyperplane; Stability (learning theory); Linear inequality; Polytope; Queueing theory; Mathematics; Finite set; Applied mathematics; Computer science; Discrete mathematics; Combinatorics; Mathematical analysis; Inequality","score_opus":0.028048585534318205,"score_gpt":0.2418055134247278,"score_spread":0.2137569278904096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059686654","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":[0.09589072,0.00007470398,0.8958238,0.000033156575,0.0018151423,0.0048769796,0.0006524898,0.0008289517,0.0000041012395],"genre_scores_gemma":[0.9756312,0.00013716894,0.019206578,0.000019835394,0.0000705638,0.0044066235,0.00027714638,0.00015063274,0.00010025933],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976172,0.00014306317,0.0011471668,0.00047916308,0.00027887628,0.00033452598],"domain_scores_gemma":[0.9979362,0.00034619193,0.00045887707,0.0007518325,0.00040223394,0.00010468836],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019774279,0.0004947759,0.00081267813,0.00027938368,0.00010434176,0.000063033905,0.00024137608,0.0004537304,0.0000525285],"category_scores_gemma":[0.000017959877,0.00054323365,0.0002603895,0.00018348714,0.000043145883,0.00032792788,0.0000027748472,0.00033556268,0.000013120288],"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":[0.000042453663,0.00024702697,0.000013701155,0.0017817583,0.00023279047,6.280188e-7,0.00030580125,0.9818066,0.0075282496,0.00002615207,0.000013264295,0.008001596],"study_design_scores_gemma":[0.002227531,0.000058703787,0.00054712227,0.00055211876,0.00016886597,0.0000021335036,0.00006570408,0.992859,0.0030535916,0.00002380516,0.00001750275,0.0004238904],"about_ca_topic_score_codex":0.000043579446,"about_ca_topic_score_gemma":0.00002348193,"teacher_disagreement_score":0.8797405,"about_ca_system_score_codex":0.00038053063,"about_ca_system_score_gemma":0.00007361146,"threshold_uncertainty_score":0.9997019},"labels":[],"label_agreement":null},{"id":"W2059739072","doi":"10.1145/1161089.1161116","title":"On the complexity of scheduling in wireless networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":379,"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":"Computer science; Scheduling (production processes); Wireless network; Wireless; Computer network; Distributed computing; Telecommunications; Mathematical optimization; Mathematics","score_opus":0.015503011942079543,"score_gpt":0.20670122686967593,"score_spread":0.1911982149275964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059739072","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":[0.3418093,0.000048335474,0.6492382,0.00004682129,0.000066452245,0.00008869645,4.943994e-7,0.00009509685,0.00860658],"genre_scores_gemma":[0.9943798,0.000019475994,0.0054813325,0.000023550852,0.000046511796,0.0000064369096,0.000006629269,0.000016346825,0.00001986889],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99955225,0.000014409349,0.00016559588,0.000067374254,0.000066779736,0.000133583],"domain_scores_gemma":[0.99973315,0.000094742594,0.000021227515,0.00012804833,0.000013534686,0.000009296735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006892517,0.000072944975,0.0000973696,0.000032356544,0.000019746789,0.0000056538156,0.00007840139,0.000039186412,0.000037354617],"category_scores_gemma":[0.0000041922494,0.000055982615,0.000018273258,0.00023261334,0.00005772479,0.00004161638,0.000010919779,0.00011691096,0.0000027025092],"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":[0.0000026712562,0.000008694666,0.00039249973,0.000003990832,0.0000017266699,3.2681393e-7,0.0000050334356,0.84528804,0.00009804487,0.15369844,0.0000932262,0.00040728642],"study_design_scores_gemma":[0.00010458408,0.0000042058014,0.0018289336,0.000028119788,9.329323e-7,2.0879702e-7,0.00001037565,0.991709,0.0009331928,0.0053108577,0.00000818192,0.000061429855],"about_ca_topic_score_codex":0.000028187998,"about_ca_topic_score_gemma":0.00014046388,"teacher_disagreement_score":0.65257055,"about_ca_system_score_codex":0.000029452316,"about_ca_system_score_gemma":0.000002064485,"threshold_uncertainty_score":0.22829048},"labels":[],"label_agreement":null},{"id":"W2059746594","doi":"10.1109/iwcmc.2013.6583704","title":"Evaluation of TCP performance with LTE downlink schedulers in a vehicular environment","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of New Brunswick","funders":"","keywords":"Computer science; Computer network; Scheduling (production processes); Network packet; Throughput; Telecommunications link; LTE Advanced; Media access control; Transport layer; Wireless; Layer (electronics); Engineering; Telecommunications","score_opus":0.007964807651940103,"score_gpt":0.17912336877653726,"score_spread":0.17115856112459715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059746594","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":[0.92180514,0.00012802362,0.07601653,0.000017123642,0.000019091185,0.0003332645,2.1459812e-7,0.00004344733,0.0016371772],"genre_scores_gemma":[0.97198397,0.00015828217,0.027708415,0.0000061840656,0.000009801089,0.00009348726,0.000006821036,0.000014914374,0.000018138311],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934274,0.000018055453,0.00014257168,0.00008797864,0.00029342185,0.000115233204],"domain_scores_gemma":[0.9997693,0.000008200994,0.000024489595,0.00013293605,0.00004288915,0.00002220567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018097892,0.000077945995,0.00008511141,0.00005528602,0.000009350799,0.0000045093607,0.000042979293,0.000035444664,0.0003141639],"category_scores_gemma":[0.0000038886214,0.00006661735,0.000009204102,0.00011374029,0.00001814757,0.00023406719,0.000007960704,0.000062299194,0.00004134136],"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":[0.0000016995251,0.000009429099,0.0020427126,0.000012843505,0.000009398959,7.838768e-8,0.000046111258,0.975976,0.00076268124,0.00002026897,0.000008619817,0.02111015],"study_design_scores_gemma":[0.0004354183,0.000022475873,0.015471672,0.000031152307,0.000012641629,4.532495e-7,0.000030485422,0.97997606,0.0038749683,0.00003080762,0.000028155513,0.00008572444],"about_ca_topic_score_codex":0.00000620334,"about_ca_topic_score_gemma":0.0000047852923,"teacher_disagreement_score":0.05017883,"about_ca_system_score_codex":0.00011709802,"about_ca_system_score_gemma":0.000009131774,"threshold_uncertainty_score":0.3439874},"labels":[],"label_agreement":null},{"id":"W2059826035","doi":"10.1109/mwc.2003.1209591","title":"Soft QoS provisioning using the token bank fair queuing scheduling algorithm","year":2003,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia; Communications Research Centre Canada","funders":"","keywords":"Computer science; Computer network; Fair queuing; Token bucket; Quality of service; Network packet; Scheduling (production processes); Provisioning; Statistical time division multiplexing; Round-robin scheduling; Distributed computing; Wireless network; Algorithm; Wireless; Dynamic priority scheduling; Multiplexing; Telecommunications","score_opus":0.025190099166736483,"score_gpt":0.2676101587157301,"score_spread":0.2424200595489936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059826035","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":[0.022337368,0.0018519689,0.9726687,0.00009403922,0.00055389316,0.00042781484,0.0000073308283,0.0006152061,0.0014436636],"genre_scores_gemma":[0.71271914,0.0005851251,0.286313,0.00005015831,0.00010815224,0.000083334635,0.000020685273,0.00008851521,0.00003192154],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984536,0.00021013073,0.00045926322,0.00022677572,0.00021819827,0.00043199537],"domain_scores_gemma":[0.9974729,0.00039099008,0.00012376084,0.0017796695,0.00014595897,0.0000867193],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003410291,0.00026387774,0.00023734065,0.00010954198,0.0009807111,0.00013087236,0.0009459263,0.00012886855,0.000016392893],"category_scores_gemma":[0.000059977803,0.00024906464,0.0000847753,0.0006823226,0.00016271394,0.0004623636,0.00011825484,0.0006129034,0.000018540175],"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":[8.055953e-7,0.000023766108,0.00008302178,0.000013712461,0.000035126657,7.347416e-7,0.00048164773,0.9672179,0.0034084953,0.0019530843,0.000042291795,0.026739419],"study_design_scores_gemma":[0.00020245515,0.0000054982966,0.000022068494,0.00013906484,0.00002953485,0.000016552427,0.00050555234,0.9928694,0.0027234964,0.00021886207,0.0029696447,0.00029788146],"about_ca_topic_score_codex":0.000018752371,"about_ca_topic_score_gemma":0.000028295082,"teacher_disagreement_score":0.69038177,"about_ca_system_score_codex":0.00020780678,"about_ca_system_score_gemma":0.00006828877,"threshold_uncertainty_score":0.9999962},"labels":[],"label_agreement":null},{"id":"W2060598493","doi":"10.1109/vetecf.2008.419","title":"Optimal Linear-Time Algorithm for Uplink Scheduling of Packets with Hard or Soft Deadlines in WiMAX","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Nortel (Canada); Queen's University","funders":"","keywords":"Computer science; Telecommunications link; Network packet; Scheduling (production processes); WiMAX; Quality of service; Mathematical optimization; Distributed computing; Algorithm; Computer network; Wireless; Mathematics","score_opus":0.015981336347951475,"score_gpt":0.22911291842584586,"score_spread":0.21313158207789437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060598493","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":[0.103186175,0.00010899959,0.89601105,0.000017888755,0.00005031771,0.0003083905,0.0000074272216,0.00023362777,0.00007612773],"genre_scores_gemma":[0.07504024,0.00011624101,0.92418015,0.000015549676,0.00012513419,0.000047085607,0.000041490526,0.00007283816,0.00036129728],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990865,0.0000063655916,0.00031820725,0.00019174723,0.000111338006,0.00028585826],"domain_scores_gemma":[0.99950606,0.000117042575,0.00005029887,0.00015903462,0.000113197864,0.000054399472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000068851696,0.00018548158,0.0002981594,0.00010317022,0.00004026377,0.0000057189886,0.000097606644,0.000097081196,0.00004373054],"category_scores_gemma":[0.000029047518,0.0001514432,0.000038168993,0.00032369696,0.000047220416,0.00021977072,0.000017448841,0.00010908043,0.000007772748],"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":[0.00006300386,0.000024965428,0.00031512987,0.000038117392,0.000021919392,0.0000087308745,0.000070566624,0.98516625,0.0003812852,0.000011055127,0.00005662553,0.013842329],"study_design_scores_gemma":[0.0010089893,0.00009666452,0.00012363191,0.000072393195,0.000009109341,0.000020276342,0.000021697526,0.9919567,0.0063784025,0.000009435363,0.000090550406,0.00021213466],"about_ca_topic_score_codex":0.0000028403472,"about_ca_topic_score_gemma":0.000007269203,"teacher_disagreement_score":0.028169073,"about_ca_system_score_codex":0.000039325754,"about_ca_system_score_gemma":0.00003837059,"threshold_uncertainty_score":0.6175674},"labels":[],"label_agreement":null},{"id":"W2060979176","doi":"10.1109/glocom.2011.6134078","title":"Fast Local D.C. Programming for Optimal Power Allocation in Wireless Networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Saskatchewan","funders":"","keywords":"Mathematical optimization; Maximization; Computer science; Computation; Constraint (computer-aided design); Computational complexity theory; Wireless network; Wireless; Global optimization; Exploit; Iterative method; Interference (communication); Optimization problem; Algorithm; Mathematics; Channel (broadcasting)","score_opus":0.010655239721379547,"score_gpt":0.20960851321402665,"score_spread":0.1989532734926471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060979176","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":[0.012487453,0.00007081077,0.9845945,0.0000057272546,0.00021708308,0.00046017393,6.57844e-7,0.00038112764,0.001782468],"genre_scores_gemma":[0.85986596,0.00002650234,0.1397364,0.00001624749,0.0000486631,0.00017209395,0.000029575383,0.000052254018,0.00005230638],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991568,0.00000874387,0.00024059354,0.00017718635,0.000067807996,0.0003489099],"domain_scores_gemma":[0.99970615,0.000027442939,0.000026711816,0.0001398377,0.000045737368,0.00005411288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009089734,0.00014836671,0.00014109218,0.00007272272,0.00003034872,0.000015255993,0.00010175743,0.0001167909,0.000039977167],"category_scores_gemma":[0.0000041302083,0.00015816769,0.00003381515,0.00023950281,0.00003120694,0.0002424819,0.000017064336,0.000111556015,0.000005014325],"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":[0.000021377811,0.000025294916,0.0002500164,0.000013165334,0.000008661738,0.0000011440534,0.00021298756,0.90583634,0.00002530416,0.0019305921,0.0000795384,0.09159559],"study_design_scores_gemma":[0.0003468616,0.000039480747,0.00036025344,0.000025840456,0.0000046153355,0.0000016632894,0.00018689057,0.9978773,0.0006322108,0.000035451667,0.00029319763,0.00019624055],"about_ca_topic_score_codex":0.000009086833,"about_ca_topic_score_gemma":0.00006836135,"teacher_disagreement_score":0.8473785,"about_ca_system_score_codex":0.00008301422,"about_ca_system_score_gemma":0.0000071787053,"threshold_uncertainty_score":0.64498913},"labels":[],"label_agreement":null},{"id":"W2061161450","doi":"10.1016/j.jnca.2011.10.008","title":"A cross layer architecture for multicast and unicast video transmission in mobile broadband networks","year":2011,"lang":"en","type":"article","venue":"Journal of Network and Computer Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Multicast; Computer network; Unicast; Scalable Video Coding; Quality of service; Scalability; Real-time computing","score_opus":0.01109593737157007,"score_gpt":0.23883800288175575,"score_spread":0.22774206551018567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061161450","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":[0.01591366,0.004034861,0.97949445,0.00001487188,0.000065544744,0.00039989065,0.0000018513646,0.000027211798,0.00004762761],"genre_scores_gemma":[0.7300218,0.0021807791,0.26701644,0.000045087418,0.00058739615,0.000104982195,0.000004981946,0.00003083915,0.0000077225395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926645,0.000017137878,0.00034788245,0.00012410177,0.0000538482,0.00019060321],"domain_scores_gemma":[0.99953264,0.00011360953,0.000085947846,0.00010375539,0.000059920763,0.00010415361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012565717,0.00012345155,0.00020533703,0.000060985793,0.00007820605,0.000032727454,0.00009840709,0.00008400658,0.000003790611],"category_scores_gemma":[7.8923114e-7,0.000110999026,0.000041502182,0.00018268825,0.00004519385,0.00010914516,0.000021728818,0.00020846119,1.4285986e-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":[0.000035584908,0.000023315677,0.000644595,0.000021048045,0.000017167045,0.000001141501,0.00023649244,0.78507036,0.000013651175,0.00013545343,0.00012467428,0.21367653],"study_design_scores_gemma":[0.0007975913,0.000094010764,0.0045215376,0.00008734157,0.000022178512,0.00006532109,0.000008990233,0.97485095,0.000013790012,0.0010559573,0.018349936,0.00013239923],"about_ca_topic_score_codex":6.3171177e-7,"about_ca_topic_score_gemma":0.000004540799,"teacher_disagreement_score":0.7141081,"about_ca_system_score_codex":0.00001552002,"about_ca_system_score_gemma":0.0000065107533,"threshold_uncertainty_score":0.4526409},"labels":[],"label_agreement":null},{"id":"W2063324885","doi":"10.1109/glocom.2012.6503123","title":"Energy efficient scheduling for delay constrained communication in wireless body area networks","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Computer science; Lyapunov optimization; Energy consumption; Scheduling (production processes); Transmission delay; Wireless sensor network; Data transmission; Efficient energy use; Wireless; Distributed computing; Propagation delay; Computer network; Real-time computing; Mathematical optimization; Network packet; Telecommunications; Chaotic; Engineering","score_opus":0.009581189152556877,"score_gpt":0.21983712308057102,"score_spread":0.21025593392801414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063324885","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":[0.05357114,0.00084076653,0.9432545,0.00001805252,0.00018785452,0.00019212996,0.0000018103783,0.0002614758,0.0016722917],"genre_scores_gemma":[0.95171386,0.0002397406,0.047634095,0.0000397524,0.000085188025,0.00011206619,0.00010981163,0.00004324368,0.0000222315],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913734,0.000024809922,0.0002706165,0.00010562551,0.0000687617,0.00039282025],"domain_scores_gemma":[0.9994126,0.00018818465,0.000040570612,0.00024175673,0.00004222618,0.00007465537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018538284,0.00014318617,0.000161638,0.000079340585,0.000061103274,0.000016991555,0.00012213083,0.00011324255,0.000017423788],"category_scores_gemma":[0.000010808192,0.00015307016,0.00003496227,0.0002361039,0.000031873853,0.00014870657,0.000027781472,0.000112347436,0.0000013985097],"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":[0.000008900688,0.000030987387,0.00040739804,0.000009441149,0.000010288057,1.4642234e-7,0.000057631136,0.97879976,0.00023585967,0.014691933,0.00004933729,0.005698328],"study_design_scores_gemma":[0.00044510738,0.0000062502977,0.00008736945,0.000045759945,0.000006558679,0.0000022867073,0.00006322965,0.9982112,0.00065504346,0.00004692734,0.0002507997,0.00017947004],"about_ca_topic_score_codex":0.000007714822,"about_ca_topic_score_gemma":0.000032069696,"teacher_disagreement_score":0.89814276,"about_ca_system_score_codex":0.00010494067,"about_ca_system_score_gemma":0.0000070472,"threshold_uncertainty_score":0.62420195},"labels":[],"label_agreement":null},{"id":"W2063476153","doi":"10.1109/mcom.2007.358861","title":"WIRELESS BROADBAND ACCESS: WIMAX AND BEYOND - Integration of WiMAX and WiFi: Optimal Pricing for Bandwidth Sharing","year":2007,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":162,"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 Manitoba","funders":"","keywords":"WiMAX; Computer network; Computer science; Wireless broadband; Internet access; Backhaul (telecommunications); Bandwidth (computing); Mobile broadband; Quality of service; Telecommunications; Broadband; Wireless network; Wireless; The Internet; Base station","score_opus":0.026211538089869264,"score_gpt":0.2923781511269859,"score_spread":0.26616661303711664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063476153","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":[0.17981791,0.001973212,0.81488276,0.00010652129,0.00012303266,0.0004886999,0.000019322451,0.000154397,0.0024341638],"genre_scores_gemma":[0.8794237,0.0025331755,0.11766333,0.000026603668,0.000057598376,0.00004955465,0.000098745535,0.000050996947,0.00009629538],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989895,0.000017518774,0.00045288188,0.00020723396,0.000099127596,0.00023374395],"domain_scores_gemma":[0.99859273,0.00031681944,0.0001341297,0.00072136254,0.0001616371,0.00007333743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034311434,0.00018834366,0.00025845307,0.00024296711,0.00018256645,0.00007529495,0.00042774127,0.000094151954,0.000003375875],"category_scores_gemma":[0.000042144515,0.0002060684,0.000030344247,0.0004304433,0.00016891226,0.0006485718,0.00017039926,0.00019354095,8.339543e-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":[0.00020997842,0.00021164476,0.0055323727,0.00067061564,0.00020339986,0.0000016654385,0.0029225524,0.51781034,0.15653718,0.013401741,0.0013819655,0.30111653],"study_design_scores_gemma":[0.0009422886,0.00006116117,0.004779736,0.00018983262,0.00006187711,0.000011947511,0.000122567,0.9805675,0.0106809195,0.00067360123,0.0015964062,0.0003121692],"about_ca_topic_score_codex":0.000006011258,"about_ca_topic_score_gemma":0.000112868234,"teacher_disagreement_score":0.69960576,"about_ca_system_score_codex":0.000062428015,"about_ca_system_score_gemma":0.000011337175,"threshold_uncertainty_score":0.84032255},"labels":[],"label_agreement":null},{"id":"W2063608768","doi":"10.1016/j.comnet.2013.07.029","title":"A semi-Markov decision process-based joint call admission control for inter-RAT cell re-selection in next generation wireless networks","year":2013,"lang":"en","type":"article","venue":"Computer Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Computer science; Markov decision process; Wireless network; Admission control; Wireless; Service (business); Computer network; Selection (genetic algorithm); Call Admission Control; Mathematical optimization; Operations research; Markov process; Quality of service; Telecommunications; Artificial intelligence","score_opus":0.012690482120211996,"score_gpt":0.22075599379151267,"score_spread":0.20806551167130066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063608768","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":[0.033645853,0.0005366025,0.96213025,0.000050656763,0.001477651,0.001683307,0.0000015432084,0.00043640123,0.0000377324],"genre_scores_gemma":[0.9506846,0.00013682873,0.046145353,0.0003539154,0.001782462,0.00055773614,0.00017774948,0.00013698898,0.000024349647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976875,0.0000902916,0.00077698455,0.00057053595,0.00019552647,0.0006791705],"domain_scores_gemma":[0.9987944,0.0002830969,0.00017798785,0.00027816507,0.00026125627,0.00020510519],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025269596,0.00044791875,0.00048864813,0.00021968981,0.00014673482,0.00022526237,0.00023191827,0.00043551653,0.000040973122],"category_scores_gemma":[0.000015859794,0.00045815614,0.00012509926,0.00057707296,0.00002676474,0.00060467084,0.000039805895,0.00049574394,0.000007396098],"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":[0.00006700832,0.00005337447,0.00026017308,0.00005369186,0.000010761027,0.0000016741268,0.000040749943,0.85946804,0.00063223863,0.0000040620366,0.012357035,0.1270512],"study_design_scores_gemma":[0.002105381,0.00015361456,0.00017396164,0.00034731612,0.000018660981,0.0000025445547,0.000005587724,0.9958291,0.0005162099,0.00006131406,0.00030899362,0.00047729386],"about_ca_topic_score_codex":0.000009114058,"about_ca_topic_score_gemma":0.00007943719,"teacher_disagreement_score":0.91703874,"about_ca_system_score_codex":0.0003060063,"about_ca_system_score_gemma":0.00003667864,"threshold_uncertainty_score":0.99978703},"labels":[],"label_agreement":null},{"id":"W2063976404","doi":"10.1109/glocomw.2012.6477560","title":"Efficiently computable bounds on the rates achieved by a cross layer design with binary scheduling in generic OFDMA wireless networks","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Upper and lower bounds; Computer science; Wireless network; Binary number; Scheduling (production processes); Wireless; Rounding; Approximation algorithm; Mathematical optimization; Algorithm; Topology (electrical circuits); Computer network; Mathematics; Telecommunications; Combinatorics","score_opus":0.018853483088581067,"score_gpt":0.23410881024118474,"score_spread":0.21525532715260368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063976404","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":[0.46985766,0.000812654,0.5286253,0.000026403579,0.00012640467,0.00022021179,9.191877e-7,0.00017444209,0.00015602549],"genre_scores_gemma":[0.98334455,0.00015326995,0.01588362,0.00015910907,0.00013216108,0.00009580486,0.000019430297,0.000091819085,0.00012022472],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986237,0.00008814207,0.00024251253,0.00021069929,0.000171546,0.00066334463],"domain_scores_gemma":[0.9993135,0.00026645447,0.000052531286,0.00024260116,0.000036958136,0.00008801083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031964606,0.00027142736,0.00022323756,0.00006481048,0.00017177376,0.000107388834,0.00019329497,0.00011395968,0.000034632514],"category_scores_gemma":[0.000006073912,0.00018801955,0.000026974456,0.0007387282,0.00006574956,0.0002985259,0.000040534993,0.00031061846,0.0000120927525],"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":[0.00006141474,0.00007900937,0.0067740404,0.0000103960765,0.000024710369,0.0000014973816,0.000106787586,0.9901739,0.0013299321,0.00019445682,0.00049555715,0.00074833556],"study_design_scores_gemma":[0.00044892638,0.00004890627,0.0010901723,0.000070475355,0.000007428404,0.0000024187868,0.00005296363,0.9944077,0.0034851038,0.0000049046885,0.00011027002,0.00027071525],"about_ca_topic_score_codex":0.000009682084,"about_ca_topic_score_gemma":0.00000458143,"teacher_disagreement_score":0.5134869,"about_ca_system_score_codex":0.00012342789,"about_ca_system_score_gemma":0.000013060473,"threshold_uncertainty_score":0.7667214},"labels":[],"label_agreement":null},{"id":"W2064631522","doi":"10.1109/pimrc.2013.6666452","title":"QoE-aware joint scheduling of buffered video on demand and best effort flows","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Quality of experience; Scheduling (production processes); Computer network; Real-time computing; Robustness (evolution); Dynamic priority scheduling; Video on demand; Quality of service; Telecommunications link; Distributed computing","score_opus":0.009249558468074778,"score_gpt":0.19642651612205023,"score_spread":0.18717695765397546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064631522","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":[0.65674704,0.00016405822,0.3411514,0.000022760516,0.00008770873,0.00020285466,0.0000011582694,0.00013618878,0.0014868139],"genre_scores_gemma":[0.96506196,0.0001977295,0.03453419,0.000018358132,0.000048076603,0.00002145107,0.000007354461,0.000030798263,0.00008006857],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994333,0.0000051811794,0.00019894537,0.00012323455,0.00008579379,0.00015356521],"domain_scores_gemma":[0.99970007,0.000030209841,0.00002542647,0.00014569533,0.00003964834,0.000058949732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003534583,0.00012045562,0.00016885457,0.00005611029,0.000028302087,0.000016466138,0.00004123281,0.000065959524,0.000117087504],"category_scores_gemma":[0.000010386165,0.00010929366,0.000022034135,0.00007791564,0.000015101545,0.0001595463,0.000021321272,0.00008208776,0.000032497217],"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":[0.0000024559024,0.000010805033,0.00041149277,0.000056556757,0.000014361301,4.5187915e-7,0.0000348348,0.9917455,0.0033646044,0.00016169711,0.000103489445,0.004093805],"study_design_scores_gemma":[0.00025466163,0.00004377233,0.0010009578,0.000097359094,0.0000073724177,0.0000015325651,0.000042877764,0.986267,0.0119463885,0.00016482941,0.000043310007,0.00012996342],"about_ca_topic_score_codex":0.000015009765,"about_ca_topic_score_gemma":0.000011566717,"teacher_disagreement_score":0.3083149,"about_ca_system_score_codex":0.00002259411,"about_ca_system_score_gemma":0.000003256051,"threshold_uncertainty_score":0.4456866},"labels":[],"label_agreement":null},{"id":"W2065555815","doi":"10.1002/wcm.924","title":"Opportunistic delay‐margin‐based resource allocation for next‐generation wireless networks","year":2010,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Scheduling (production processes); Quality of service; Network packet; Queueing theory; Telecommunications link; Base station; Fair queuing; Wireless; Queuing delay; Wireless network; Real-time computing; Telecommunications; Round-robin scheduling; Dynamic priority scheduling","score_opus":0.03178643622644925,"score_gpt":0.2602732978368992,"score_spread":0.22848686161044993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065555815","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":[0.15119833,0.0006158502,0.8463181,0.00010361078,0.00029723276,0.0007556414,0.000012215014,0.00045376775,0.0002452349],"genre_scores_gemma":[0.9409127,0.00056930794,0.056544553,0.00009421626,0.00030371427,0.00034986308,0.0011146633,0.00009123203,0.00001972891],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986497,0.00007028791,0.000496674,0.0003079108,0.000118034404,0.00035738747],"domain_scores_gemma":[0.99789375,0.0004823739,0.00015986044,0.0011332243,0.00019320879,0.00013755664],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036599918,0.00026329904,0.000267114,0.00012187821,0.00072920736,0.000165904,0.0004949619,0.00019886877,0.000005724077],"category_scores_gemma":[0.000021357144,0.0003104401,0.000063222324,0.0003057895,0.00016012955,0.0002236617,0.00015011964,0.0004433194,0.0000014619345],"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":[0.0000051631127,0.000042849722,0.00009375827,0.00004001327,0.00001811009,3.0237035e-7,0.0001288914,0.7544996,0.011424304,0.0049187895,0.0002351674,0.22859304],"study_design_scores_gemma":[0.0004275523,0.00003627608,0.00004390997,0.00006242251,0.000030451825,0.0000066763664,0.00008934758,0.9847522,0.0003213982,0.000031477117,0.013873267,0.00032502],"about_ca_topic_score_codex":0.000008158086,"about_ca_topic_score_gemma":0.00007920497,"teacher_disagreement_score":0.7897736,"about_ca_system_score_codex":0.00005666616,"about_ca_system_score_gemma":0.000039776256,"threshold_uncertainty_score":0.9999348},"labels":[],"label_agreement":null},{"id":"W2065648759","doi":"10.1002/wcm.266","title":"Interference management using basestation coordination in broadband wireless access networks","year":2006,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University; Memorial University of Newfoundland","funders":"","keywords":"Computer science; Computer network; Network packet; Hybrid automatic repeat request; Transmission delay; Wireless broadband; Quality of service; Real-time computing; Scheduling (production processes); Packet loss; Throughput; Radio Link Protocol; Wireless; Wireless network; Telecommunications; Telecommunications link","score_opus":0.015597736619908237,"score_gpt":0.26885523371751513,"score_spread":0.2532574970976069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065648759","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":[0.43509308,0.0008746844,0.56284136,0.000012412165,0.000081705,0.00032637487,0.000001917301,0.00015691426,0.0006115426],"genre_scores_gemma":[0.9846219,0.0011644905,0.013882698,0.000014022447,0.00004799649,0.00007507621,0.0001311055,0.000043183194,0.000019532099],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988222,0.00008551231,0.0004707746,0.00024095588,0.00009719935,0.00028337527],"domain_scores_gemma":[0.99906784,0.00015468303,0.00011946196,0.00054427184,0.00007394291,0.000039771065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018632734,0.00020035678,0.00021657918,0.00022556736,0.00020479207,0.00015374678,0.00043893696,0.00008174367,0.0000025586942],"category_scores_gemma":[0.0000019863478,0.00024387045,0.00002606251,0.0006282606,0.00008927986,0.00042182865,0.00036246274,0.00023488823,7.0276536e-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":[0.0000032473831,0.00004427665,0.004938409,0.00005007001,0.000008618354,0.000001411795,0.00009160467,0.86440533,0.00019512733,0.0017121716,0.00002523913,0.12852451],"study_design_scores_gemma":[0.00039524614,0.000010902677,0.0045904336,0.00029382616,0.000013371947,0.0000050410426,0.00014232252,0.9938882,0.00006422067,0.0001470261,0.00020544912,0.00024396143],"about_ca_topic_score_codex":0.00010811847,"about_ca_topic_score_gemma":0.00014686157,"teacher_disagreement_score":0.54952884,"about_ca_system_score_codex":0.00016534446,"about_ca_system_score_gemma":0.000008140241,"threshold_uncertainty_score":0.9944749},"labels":[],"label_agreement":null},{"id":"W2066218456","doi":"10.1109/iswpc.2008.4556217","title":"Fair scheduling in multirate wireless access networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Computer network; Maximum throughput scheduling; Scheduling (production processes); Link adaptation; Wireless network; Physical layer; Wireless distribution system; Proportionally fair; Media access control; Wireless; Access control; Provisioning; Link layer; Access network; Round-robin scheduling; Distributed computing; Quality of service; Dynamic priority scheduling; Channel (broadcasting); Wi-Fi; Fading; Telecommunications","score_opus":0.01778363761885003,"score_gpt":0.23361722452064776,"score_spread":0.2158335869017977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066218456","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":[0.3241903,0.00017671204,0.6720341,0.000009861558,0.0002002384,0.000111833695,3.1363913e-7,0.00046488477,0.0028118242],"genre_scores_gemma":[0.98249364,0.0008892615,0.016232904,0.000049698967,0.000120035744,0.000025291003,0.000012005587,0.000052497526,0.00012467301],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991597,0.000013931131,0.00023970439,0.00017364927,0.000089829366,0.00032317624],"domain_scores_gemma":[0.999682,0.000042587006,0.000023291075,0.0001674388,0.000026265312,0.000058431884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000049786966,0.00015410915,0.00017010809,0.000098371165,0.00004279693,0.000022508344,0.00018053383,0.00010180475,0.000033906534],"category_scores_gemma":[0.000006567042,0.00016382235,0.000026670974,0.00049781415,0.000027825097,0.0005041319,0.000045351506,0.00021474183,0.0000154246],"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":[0.0000041890594,0.000009372434,0.007227761,0.000008371917,0.0000052208457,0.000018385215,0.000048279333,0.9876327,0.000082600935,0.000116884716,0.00012507381,0.00472115],"study_design_scores_gemma":[0.00033392746,0.000003604465,0.0027161967,0.00002808741,0.0000013570682,0.0000056553386,0.00001414566,0.9960635,0.00051750016,0.000024593837,0.00008296184,0.0002084751],"about_ca_topic_score_codex":0.000015311442,"about_ca_topic_score_gemma":0.00007647065,"teacher_disagreement_score":0.6583034,"about_ca_system_score_codex":0.0000711189,"about_ca_system_score_gemma":0.0000078937055,"threshold_uncertainty_score":0.66804814},"labels":[],"label_agreement":null},{"id":"W2068468191","doi":"10.1109/mcit.2010.5444867","title":"Quantifying Quality of Service differentiation for WiMAX networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Guelph","funders":"","keywords":"Quality of service; Computer science; Mobile QoS; Computer network; WiMAX; Scheduling (production processes); Throughput; Differentiated services; Admission control; Service (business); Wireless; Service provider; Telecommunications; Mathematics; Mathematical optimization","score_opus":0.032712257828806546,"score_gpt":0.28779656130612213,"score_spread":0.2550843034773156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068468191","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":[0.20048434,0.000021736063,0.7983989,0.00002396221,0.00041774643,0.0001489628,0.000002941564,0.00018142215,0.00032000756],"genre_scores_gemma":[0.94894487,0.00001588038,0.05078171,0.000030332147,0.00010644497,0.000020505102,0.000058566806,0.000025346304,0.000016379176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994599,0.000008006274,0.0002417686,0.0000915513,0.0000645988,0.0001341465],"domain_scores_gemma":[0.99954504,0.000117354604,0.00005560359,0.00015896167,0.00009637563,0.000026663438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010934528,0.0000825617,0.00013300696,0.000028530347,0.000030323046,0.00000960376,0.00007194592,0.00008403456,0.000035530975],"category_scores_gemma":[0.000021636672,0.000083342784,0.000033565753,0.0001458828,0.000007736254,0.00013256507,0.000011328013,0.00009666935,0.0000013375854],"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":[0.000008356587,0.000008555649,0.0015545448,0.000090398666,0.000011312511,1.11562555e-8,0.00003169207,0.9673649,0.020949194,0.0061897906,0.00006060302,0.0037306566],"study_design_scores_gemma":[0.0002305664,0.000004363624,0.0073282714,0.000008123523,0.0000061495284,1.3358662e-7,0.000013458619,0.9874423,0.0045708297,0.00021104324,0.00008612904,0.00009859885],"about_ca_topic_score_codex":0.000011990452,"about_ca_topic_score_gemma":0.00060818304,"teacher_disagreement_score":0.7484605,"about_ca_system_score_codex":0.000009223281,"about_ca_system_score_gemma":0.0000030143851,"threshold_uncertainty_score":0.33986202},"labels":[],"label_agreement":null},{"id":"W2068671295","doi":"10.1016/j.peva.2010.11.001","title":"Dynamic multiple-frame bandwidth provisioning with fairness and revenue considerations for Broadband Wireless Access Systems","year":2010,"lang":"en","type":"article","venue":"Performance Evaluation","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Qatar Foundation","keywords":"Bandwidth (computing); Broadband; Computer science; Provisioning; Computer network; Wireless broadband; Wireless; Frame (networking); Telecommunications; Wireless network","score_opus":0.016051130720777105,"score_gpt":0.26854866297528784,"score_spread":0.2524975322545107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068671295","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":[0.7728805,0.00011666857,0.22514205,0.000018345701,0.00041089527,0.0012249954,0.000017032213,0.00012118927,0.000068309484],"genre_scores_gemma":[0.98885286,0.00008527727,0.010013044,0.000007393317,0.000095353724,0.0007588841,0.00010151953,0.000051108454,0.000034563865],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902165,0.000025165657,0.00025044815,0.00023431117,0.0002514664,0.00021694612],"domain_scores_gemma":[0.99915016,0.0001941588,0.000098503195,0.00020762508,0.00029597673,0.000053551863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004090935,0.00017243384,0.00017462003,0.00009432387,0.00023874793,0.00017820405,0.00007688922,0.00010017791,0.0000070634624],"category_scores_gemma":[0.000111312154,0.0001608705,0.000014838752,0.00015997622,0.000053727028,0.0009568635,0.000017754579,0.00018892145,0.0000017306565],"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":[0.00002384988,0.00000861765,0.0075356807,0.00016107982,0.000015473963,1.5183483e-7,0.00030354777,0.9702506,0.0056920163,0.000060471608,0.000044702687,0.015903814],"study_design_scores_gemma":[0.0010712737,0.00004507199,0.013602881,0.00014496289,0.00004399974,0.000017252072,0.00004414187,0.9832992,0.001344142,0.00010521115,0.000060599,0.00022129455],"about_ca_topic_score_codex":0.0000065260833,"about_ca_topic_score_gemma":0.00023363627,"teacher_disagreement_score":0.21597233,"about_ca_system_score_codex":0.000078445904,"about_ca_system_score_gemma":0.00005677097,"threshold_uncertainty_score":0.65601087},"labels":[],"label_agreement":null},{"id":"W2069509565","doi":"10.1109/chinacom.2007.4469341","title":"Fair Adaptive Resource Allocation for Multiuser OFDM Cognitive Radio Systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":63,"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":"Cognitive radio; Orthogonal frequency-division multiplexing; Computer science; Resource allocation; Throughput; Transmitter power output; Computer network; Resource management (computing); Interference (communication); Constraint (computer-aided design); Radio resource management; Real-time computing; Telecommunications; Transmitter; Wireless; Engineering","score_opus":0.01257009105345925,"score_gpt":0.22851663272995584,"score_spread":0.2159465416764966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069509565","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":[0.0039793425,0.0002939198,0.98783064,0.000009078873,0.00021945841,0.00076410966,0.000009477143,0.0005417438,0.006352207],"genre_scores_gemma":[0.9728897,0.000020025665,0.025795301,0.000027594431,0.00023779112,0.00008753393,0.00008602098,0.000061407736,0.00079459837],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999224,0.00001186428,0.0002271021,0.00016765368,0.000106285726,0.00026306216],"domain_scores_gemma":[0.99936014,0.00029825035,0.0000407106,0.0001054612,0.0001321094,0.00006331645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018443033,0.00013752042,0.00013774371,0.00007763509,0.00005641724,0.000016996624,0.00006135788,0.0000960848,0.0000068215127],"category_scores_gemma":[0.000037135775,0.0001423215,0.00003418477,0.00017437777,0.000020563293,0.00017418631,0.000008987916,0.00007758651,0.000015468237],"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":[0.000062672814,0.000010889204,0.000037545702,0.000029644281,0.000038472128,9.853505e-7,0.00025785228,0.9890271,0.00030415942,0.0021904388,0.0010449878,0.0069952672],"study_design_scores_gemma":[0.00066758256,0.000040214618,0.00021686904,0.000065928805,0.000018124847,0.0000026407924,0.0012296371,0.9903408,0.0034282247,0.000025857025,0.003757966,0.00020610071],"about_ca_topic_score_codex":0.0000072314797,"about_ca_topic_score_gemma":0.000023393452,"teacher_disagreement_score":0.9689104,"about_ca_system_score_codex":0.00012065602,"about_ca_system_score_gemma":0.000005898404,"threshold_uncertainty_score":0.58037025},"labels":[],"label_agreement":null},{"id":"W2071444230","doi":"10.1049/iet-com:20060336","title":"Joint rate and power adaptation for radio resource management in uplink wideband code division multiple access systems","year":2008,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo; Toronto Metropolitan University","funders":"","keywords":"Computer science; Throughput; Power control; Transmitter power output; Telecommunications link; Bit error rate; Link adaptation; Code division multiple access; Interference (communication); Fading; Power (physics); Code rate; Wideband; Computer network; Real-time computing; Electronic engineering; Telecommunications; Transmitter; Engineering; Wireless; Channel (broadcasting); Decoding methods","score_opus":0.05856204277610793,"score_gpt":0.2725907698827809,"score_spread":0.21402872710667298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071444230","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":[0.022975987,0.0026990564,0.9714229,0.00024171858,0.0000994959,0.0010655279,0.0000181119,0.00021386311,0.0012633419],"genre_scores_gemma":[0.96554065,0.0034095254,0.030393995,0.000020796246,0.000010569155,0.00034203302,0.00016076436,0.000037010683,0.00008467236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927837,0.00006138697,0.0002995268,0.00014030005,0.000066043394,0.00015438745],"domain_scores_gemma":[0.9988988,0.00025651592,0.000062398554,0.00069653033,0.000045109824,0.000040619463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017673128,0.00011311356,0.000148157,0.000121089346,0.0002141416,0.000043455115,0.00029957382,0.000053715674,0.0000012767629],"category_scores_gemma":[0.000029746589,0.00012713883,0.00002231761,0.00022521704,0.00005140617,0.00027198863,0.00014018152,0.000116957126,0.0000019960553],"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":[0.000008937928,0.000024620755,0.0006154354,0.000036803194,0.00001839182,6.9168846e-7,0.0006100529,0.9954289,0.00009022446,0.00067725556,0.0007057517,0.0017829213],"study_design_scores_gemma":[0.000710801,0.000010936858,0.0076705245,0.000092810136,0.000008493575,0.0000024678945,0.00018416127,0.9826494,0.000042520827,0.00009838264,0.008391265,0.00013826504],"about_ca_topic_score_codex":0.000017420021,"about_ca_topic_score_gemma":0.00007817428,"teacher_disagreement_score":0.94256467,"about_ca_system_score_codex":0.00008486265,"about_ca_system_score_gemma":0.000005213476,"threshold_uncertainty_score":0.5184571},"labels":[],"label_agreement":null},{"id":"W2071671550","doi":"10.1007/s11036-005-4450-8","title":"Non-Cooperative Games for Service Differentiation in CDMA Systems","year":2005,"lang":"en","type":"article","venue":"Mobile Networks and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nortel (Canada)","funders":"National Science Foundation","keywords":"Computer science; Quality of service; Service provider; Differentiated service; Service (business); Mobile QoS; Service level objective; Revenue; Computer network; Code division multiple access; Class (philosophy); Resource allocation; Resource (disambiguation); Service design; Business; Marketing; Artificial intelligence","score_opus":0.004308782704149472,"score_gpt":0.21165541571225857,"score_spread":0.2073466330081091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071671550","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":[0.019807793,0.0015325465,0.9766023,0.000034249708,0.000058504014,0.0015581022,0.000010662898,0.00011927081,0.00027656235],"genre_scores_gemma":[0.99015015,0.0007795194,0.0010240314,0.000040026942,0.00044917653,0.0073215137,0.00015019464,0.00002992689,0.00005547489],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994324,0.000005952239,0.00019497595,0.00016176497,0.000038705446,0.00016623504],"domain_scores_gemma":[0.999694,0.00005506312,0.000031307794,0.00012951295,0.000051359115,0.000038757324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042171712,0.0001111716,0.00013201346,0.000039512575,0.000076682554,0.000039506733,0.00005771611,0.0000746843,0.0000032997787],"category_scores_gemma":[7.9818653e-7,0.00011573736,0.000014587108,0.0002542253,0.000010443197,0.00012985322,0.000012060033,0.00007698071,0.0000031911004],"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":[0.0000022545066,0.000017869485,0.00015516402,0.000028436862,0.0000064390842,2.0310171e-8,0.00004227079,0.9831279,0.00008453589,0.00088535686,0.00023512158,0.015414652],"study_design_scores_gemma":[0.0002725962,0.000008947641,0.0006784759,0.000026087382,0.0000075687667,5.886e-7,0.000061516796,0.98384607,0.000046210607,0.00003334658,0.014896758,0.00012180837],"about_ca_topic_score_codex":0.000004414904,"about_ca_topic_score_gemma":0.00007840234,"teacher_disagreement_score":0.97557825,"about_ca_system_score_codex":0.00004880054,"about_ca_system_score_gemma":0.000003777714,"threshold_uncertainty_score":0.4719633},"labels":[],"label_agreement":null},{"id":"W2071858447","doi":"10.1109/pimrc.2011.6139942","title":"Distributed self-optimization for efficient reconfiguration in overlapping heterogenous wireless access networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"","keywords":"Control reconfiguration; Computer science; Distributed computing; Heterogeneous network; Wireless network; Distributed algorithm; Bandwidth (computing); Optimization problem; Wireless; Computer network; Algorithm; Embedded system","score_opus":0.018541454339932362,"score_gpt":0.22137194570304722,"score_spread":0.20283049136311485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071858447","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":[0.042572487,0.000068258465,0.9544754,0.0000052394894,0.00036392445,0.00074584014,0.000009707025,0.00070927007,0.0010498404],"genre_scores_gemma":[0.96211773,0.00014457337,0.037058767,0.000023794695,0.0000752994,0.00018584216,0.00032568976,0.00006136232,0.0000069356233],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988811,0.00002281416,0.0003959691,0.00024632848,0.000087616434,0.0003661746],"domain_scores_gemma":[0.99953777,0.00005426191,0.0000752459,0.00018883104,0.00008414389,0.000059746333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000115782306,0.00019689671,0.00020409713,0.0001200943,0.000058914775,0.000053704836,0.0001627289,0.00014504486,0.000047839225],"category_scores_gemma":[0.000010815265,0.00021759437,0.000045491663,0.00045554052,0.000012088755,0.00034984495,0.00002290368,0.000106503656,0.0000019252059],"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":[0.000024607943,0.00004867499,0.00032200673,0.000035835954,0.000018250821,0.0000011035164,0.000189027,0.9960841,0.000041449806,0.00024152678,0.000062415056,0.0029310123],"study_design_scores_gemma":[0.00051707175,0.000023637422,0.0004196668,0.000037936104,0.000011466095,0.0000020185469,0.000027982853,0.9978279,0.00081169204,0.00003288321,0.000032933585,0.00025481422],"about_ca_topic_score_codex":0.0000110737965,"about_ca_topic_score_gemma":0.000045060366,"teacher_disagreement_score":0.91954523,"about_ca_system_score_codex":0.00021123029,"about_ca_system_score_gemma":0.00001076872,"threshold_uncertainty_score":0.88732404},"labels":[],"label_agreement":null},{"id":"W2072306584","doi":"10.1007/s11276-009-0208-8","title":"Control of wireless networks with flow level dynamics under constant time scheduling","year":2009,"lang":"en","type":"article","venue":"Wireless Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Round-robin scheduling; Scheduling (production processes); Network congestion; Maximum throughput scheduling; Wireless network; Dynamic priority scheduling; Fair-share scheduling; Rate-monotonic scheduling; Earliest deadline first scheduling; Queue; Queuing delay; Mathematical optimization; Distributed computing; Computer network; Wireless; Network packet; Mathematics; Quality of service","score_opus":0.005701554008814687,"score_gpt":0.18879754590655903,"score_spread":0.18309599189774434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072306584","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":[0.026375653,0.0011569759,0.9697347,0.00008716445,0.0003784248,0.0005863821,0.000040352585,0.0007316636,0.0009086852],"genre_scores_gemma":[0.980954,0.0004448523,0.017449647,0.00020433175,0.00044108025,0.000030450052,0.0002221002,0.00018550587,0.00006806233],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99705446,0.00008831553,0.00084378227,0.0005419667,0.00042464476,0.0010468098],"domain_scores_gemma":[0.9982838,0.00026092425,0.00029008838,0.0006586348,0.00025062528,0.0002559442],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002588812,0.00067121914,0.0009895072,0.00016173327,0.00017561867,0.00007490645,0.00042383894,0.00050195213,0.000043008975],"category_scores_gemma":[0.000007312574,0.00066002854,0.00014939473,0.0009061477,0.00023081037,0.00036295448,0.000036909467,0.00079237856,0.000009056741],"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":[0.00016320762,0.00006615049,0.0002826552,0.000026925582,0.00016884157,0.000020780091,0.00003179584,0.949265,0.0001466576,0.004109393,0.00012791187,0.04559065],"study_design_scores_gemma":[0.0021248371,0.00014513724,0.0003195089,0.0004362894,0.00010494694,0.00002467249,0.000046859826,0.9957661,0.000080092344,0.00016792963,0.000023305261,0.0007602898],"about_ca_topic_score_codex":0.0000052225087,"about_ca_topic_score_gemma":0.000051587896,"teacher_disagreement_score":0.95457834,"about_ca_system_score_codex":0.00030097103,"about_ca_system_score_gemma":0.000059989306,"threshold_uncertainty_score":0.9995851},"labels":[],"label_agreement":null},{"id":"W2072629980","doi":"10.1002/ett.1249","title":"Efficient resource management for packet mode cdma2000","year":2007,"lang":"en","type":"article","venue":"European Transactions on Telecommunications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"CDMA2000; Computer science; Computer network; Network packet; Throughput; Wireless; Scheduling (production processes); Real-time computing; Telecommunications; Code division multiple access; Engineering","score_opus":0.010404988639302776,"score_gpt":0.23813696575112664,"score_spread":0.22773197711182386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072629980","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":[0.00094391074,0.000121288846,0.88611823,0.00009641844,0.00009142537,0.00044741755,0.00003471095,0.00069706934,0.11144955],"genre_scores_gemma":[0.82851166,0.0002966114,0.16957375,0.00009353363,0.000040966534,0.000071162984,0.000089231355,0.00012286448,0.0012002374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900687,0.00006385154,0.00032929843,0.00018071737,0.00010979866,0.0003094748],"domain_scores_gemma":[0.99873763,0.00018688412,0.000040190756,0.0009071863,0.00003997716,0.0000881294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031785262,0.00016759417,0.00010883815,0.00021180915,0.0004027223,0.000027079288,0.00038386407,0.00003470108,0.000038946437],"category_scores_gemma":[0.0000038033081,0.00019657139,0.00008856096,0.00040576866,0.000043238044,0.000041559706,0.0000067058813,0.00023604774,0.00009843184],"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":[0.000014952716,0.000098338634,5.9571494e-7,0.000017010158,0.00003903716,8.496036e-7,0.00017741285,0.9146939,0.000056165874,0.00064443145,0.00053446606,0.08372282],"study_design_scores_gemma":[0.000845845,0.000056404675,0.00034447407,0.00007042806,0.000070603506,0.0000054162247,0.0003965296,0.773072,0.0015969573,0.000067124216,0.22303155,0.00044263483],"about_ca_topic_score_codex":0.0000012620229,"about_ca_topic_score_gemma":0.000018145898,"teacher_disagreement_score":0.8275677,"about_ca_system_score_codex":0.0001340295,"about_ca_system_score_gemma":0.000003649245,"threshold_uncertainty_score":0.80159485},"labels":[],"label_agreement":null},{"id":"W2072642336","doi":"10.1145/1185373.1185417","title":"Multiuser prefetching with queuing prioritization in heterogeneous wireless systems","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Instruction prefetch; Roaming; Computer science; Scalability; Queueing theory; Prioritization; Computer network; Wireless network; Distributed computing; Heterogeneous network; Wireless; Queuing delay; Database; Operating system","score_opus":0.002710188037351225,"score_gpt":0.16456765270196533,"score_spread":0.1618574646646141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072642336","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":[0.45454922,0.0002045227,0.54315287,0.0000025999645,0.00010550693,0.00022953661,8.1285856e-7,0.00044137414,0.0013135208],"genre_scores_gemma":[0.9923389,0.00003312967,0.0072844285,0.0000049011683,0.000098790726,0.00004016575,0.0000281125,0.00006508493,0.00010650355],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920726,0.000019701192,0.0002424712,0.00016672943,0.00012426233,0.00023958953],"domain_scores_gemma":[0.9997453,0.000027289938,0.000032226184,0.00013664394,0.00003248424,0.000026041103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004970001,0.00014789245,0.00014902955,0.000099584104,0.000034043955,0.000049468737,0.00006134902,0.00006885943,0.0000041134986],"category_scores_gemma":[0.0000019046748,0.00014002794,0.000012592756,0.00026516005,0.00000997407,0.00026604944,0.000009799285,0.00009683186,0.00000450696],"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":[0.0000053179324,0.00001071192,0.004985596,0.000049666163,0.0000048096745,0.000009597671,0.000053201016,0.99265033,0.00085966266,0.0003949875,0.000013746256,0.0009623818],"study_design_scores_gemma":[0.00037744403,0.000009218762,0.0007648394,0.00012717975,0.0000033979325,0.000012440719,0.00003283878,0.996771,0.0016064363,0.000018937779,0.00007926109,0.00019700221],"about_ca_topic_score_codex":0.00015898678,"about_ca_topic_score_gemma":0.00058615394,"teacher_disagreement_score":0.53778964,"about_ca_system_score_codex":0.00013910785,"about_ca_system_score_gemma":0.000006109699,"threshold_uncertainty_score":0.5710174},"labels":[],"label_agreement":null},{"id":"W2072776533","doi":"10.1109/vetecf.2010.5594592","title":"QoS Assured Uplink Scheduler for WiMAX Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Eion (Canada); Carleton University","funders":"Ontario Centres of Excellence","keywords":"WiMAX; Computer science; Quality of service; Computer network; Scheduling (production processes); Wireless broadband; Admission control; Telecommunications link; Broadband networks; Wireless; Distributed computing; Broadband; Wireless network; Telecommunications; Engineering","score_opus":0.003331837760917735,"score_gpt":0.19826854153762305,"score_spread":0.19493670377670533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072776533","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":[0.0029133274,0.00007413183,0.99000347,0.000052709354,0.0017293367,0.00027431434,0.0000013989064,0.00067927776,0.00427202],"genre_scores_gemma":[0.65689135,0.000033367276,0.34127527,0.00007455798,0.00096249033,0.00008776121,0.000043777887,0.000074966316,0.0005564622],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993993,0.00000283924,0.00014913392,0.00013526187,0.00005442959,0.00025904214],"domain_scores_gemma":[0.9995897,0.000064251144,0.00001862257,0.00021022599,0.00005320944,0.00006399346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007314477,0.00012369118,0.00011845122,0.000032894113,0.00004913422,0.000025399075,0.0000987023,0.00015093735,0.00015118447],"category_scores_gemma":[0.000020927011,0.00012280451,0.000042487183,0.00012389728,0.000016970245,0.00014745514,0.000013356201,0.00021344317,0.00001968286],"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":[0.000004444821,0.0000053574945,0.00010556534,0.00000813269,0.00001418911,2.2592835e-7,0.0000062533345,0.9792095,0.0013099553,0.0030600955,0.0049480777,0.011328208],"study_design_scores_gemma":[0.00028353385,0.000007981248,0.000125893,0.0000044294234,0.000007803574,0.0000011802204,0.000002717312,0.98205024,0.0012160719,0.00023339044,0.015904715,0.00016205678],"about_ca_topic_score_codex":6.6326965e-7,"about_ca_topic_score_gemma":0.000019242176,"teacher_disagreement_score":0.65397805,"about_ca_system_score_codex":0.000013498362,"about_ca_system_score_gemma":0.0000053564013,"threshold_uncertainty_score":0.5007823},"labels":[],"label_agreement":null},{"id":"W2073836577","doi":"10.1109/icc.2010.5502515","title":"A Unified Scheduling Framework Based on Virtual Timers for Selfish-Policy Shared Spectrum","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Timer; Distributed computing; Scheduling (production processes); Fairness measure; Wireless; Mathematical optimization; Operating system; Throughput","score_opus":0.00642629525197212,"score_gpt":0.2339912483728002,"score_spread":0.22756495312082808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073836577","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":[0.010060865,0.000005031208,0.98272896,0.0004584879,0.0005498774,0.0003532906,0.000015601603,0.00091801386,0.0049098586],"genre_scores_gemma":[0.677279,0.000004865263,0.32156718,0.00029997356,0.0005212835,0.000047967296,0.00005258317,0.00007930828,0.0001478493],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990628,0.000007981825,0.00019331092,0.0002304743,0.00013138264,0.00037405832],"domain_scores_gemma":[0.9992192,0.00027819193,0.000032352244,0.00032429246,0.000033394565,0.00011261569],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008440274,0.00020262551,0.00016782082,0.00017181497,0.00008667461,0.000051365612,0.00016099736,0.00021350302,0.00027112488],"category_scores_gemma":[0.00018934204,0.00021304707,0.00006592392,0.0003976374,0.000023976181,0.00014038946,0.000013548229,0.00039157138,0.000054964617],"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":[0.000031799034,0.000016877619,0.000019889501,0.000012579214,0.000013841119,6.5291704e-7,0.00004061532,0.97170544,0.0010486254,0.025029577,0.0003636269,0.0017164671],"study_design_scores_gemma":[0.00044714328,0.00005889766,0.00005337757,0.000032319906,0.000007641302,5.143364e-7,0.000018445067,0.99138236,0.0043204087,0.0018358387,0.0015890205,0.0002540086],"about_ca_topic_score_codex":0.0000036671404,"about_ca_topic_score_gemma":0.000016445274,"teacher_disagreement_score":0.66721815,"about_ca_system_score_codex":0.000068382295,"about_ca_system_score_gemma":0.000041041523,"threshold_uncertainty_score":0.86878073},"labels":[],"label_agreement":null},{"id":"W2075146768","doi":"10.1109/tvt.2011.2162428","title":"Net Throughput Maximization of Per-Chunk User Scheduling for MIMO-OFDM Downlink","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Alberta","funders":"","keywords":"Telecommunications link; Scheduling (production processes); Orthogonal frequency-division multiplexing; Computer science; MIMO; Throughput; Multiplexing; Real-time computing; Channel state information; Overhead (engineering); Computer network; Channel (broadcasting); Mathematics; Wireless; Mathematical optimization; Telecommunications","score_opus":0.014603725438976823,"score_gpt":0.21561569979422338,"score_spread":0.20101197435524656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075146768","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":[0.04109898,0.00023577253,0.95647913,0.00007899938,0.0004902782,0.0005093045,0.000026273286,0.0009547374,0.00012650233],"genre_scores_gemma":[0.7700353,0.00031191355,0.22930482,0.000020409661,0.000027197764,0.00017246086,0.000015311158,0.00007543696,0.000037115726],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988533,0.000016104928,0.00038811422,0.0002971712,0.000115630944,0.0003296657],"domain_scores_gemma":[0.99924153,0.000038563452,0.00008503108,0.00044884972,0.0001448817,0.0000411618],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007323985,0.00023818659,0.0003003269,0.00041546352,0.0001139924,0.0000071858854,0.00022219395,0.0004834015,0.000067745656],"category_scores_gemma":[0.0000079458305,0.00026549635,0.00012003557,0.0005724985,0.0001207023,0.0001962021,0.0000019212862,0.00032386582,0.000018046981],"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":[0.000033584707,0.000083387655,0.000023561868,0.00005867603,0.00008723411,0.0000016670347,0.000117258205,0.9753746,0.008417712,0.0010690131,0.00001823828,0.014715079],"study_design_scores_gemma":[0.00083948165,0.0001864559,0.000020962689,0.000074843265,0.000101258505,0.000015444206,0.00011899359,0.6789043,0.316851,0.0016006911,0.0009473743,0.0003391984],"about_ca_topic_score_codex":0.000005435193,"about_ca_topic_score_gemma":0.00001962742,"teacher_disagreement_score":0.7289364,"about_ca_system_score_codex":0.00007932434,"about_ca_system_score_gemma":0.000017398846,"threshold_uncertainty_score":0.99997973},"labels":[],"label_agreement":null},{"id":"W2075308017","doi":"10.1109/icc.2007.795","title":"Optimal Adaptive Modulation and Coding with Switching Costs","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Fading; Link adaptation; Coding (social sciences); Markov decision process; Mathematical optimization; Monotone polygon; Markov process; Monotonic function; Channel (broadcasting); Mathematics; Telecommunications","score_opus":0.0061989666706700535,"score_gpt":0.2019139048116251,"score_spread":0.19571493814095506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075308017","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":[0.22885105,0.000037054022,0.76675624,0.000003692597,0.000029828681,0.000074228265,2.0532106e-7,0.00020497735,0.004042702],"genre_scores_gemma":[0.806705,0.00002145265,0.19318491,0.000008454755,0.000037685022,0.0000016733575,0.0000029506025,0.000019101313,0.000018749046],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995999,0.0000029460068,0.00008888664,0.00009326505,0.00007003727,0.00014499835],"domain_scores_gemma":[0.99982446,0.00004122863,0.000015635926,0.000054471926,0.00002232693,0.00004189432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007256772,0.00008116237,0.00006666486,0.000047582937,0.00004529794,0.000015344987,0.00002030341,0.00003294669,0.0000058015744],"category_scores_gemma":[0.0000030137173,0.00007398979,0.0000054611896,0.00011215128,0.000008735921,0.00023811054,0.00000847889,0.00007045493,0.0000015565023],"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":[0.000018136923,0.0000017496841,0.00053921033,0.0000038118405,0.000007914925,0.0000024578248,0.00009712648,0.973103,0.0013254719,0.001468348,0.0000070754563,0.023425693],"study_design_scores_gemma":[0.00020161597,0.000021382506,0.003446173,0.000026164016,0.0000036324568,0.000006862128,0.00012148554,0.9945421,0.0014830547,0.00001996755,0.000018423576,0.0001090896],"about_ca_topic_score_codex":0.0000039806914,"about_ca_topic_score_gemma":0.000030799045,"teacher_disagreement_score":0.577854,"about_ca_system_score_codex":0.00006676567,"about_ca_system_score_gemma":0.0000019750023,"threshold_uncertainty_score":0.30172157},"labels":[],"label_agreement":null},{"id":"W2075414864","doi":"10.1109/vetecs.2010.5493662","title":"Inter-Cell Interference Coordination in OFDMA Networks: A Novel Approach Based on Integer Programming","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Throughput; Computer science; Interference (communication); Scheme (mathematics); Integer programming; Enhanced Data Rates for GSM Evolution; Mathematical optimization; Binary number; Linear programming; Integer (computer science); Algorithm; Mathematics; Computer network; Telecommunications; Wireless; Channel (broadcasting)","score_opus":0.006950404612803795,"score_gpt":0.2017398273490094,"score_spread":0.1947894227362056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075414864","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":[0.010795645,0.000013544238,0.98235077,0.0000564153,0.00041290413,0.00034111284,0.0000010211756,0.0003950105,0.0056335563],"genre_scores_gemma":[0.8900063,0.0000037302386,0.1094703,0.00006746372,0.000081229315,0.00015509283,0.00003535591,0.000047981626,0.00013252399],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905986,0.000012977332,0.0002776521,0.00025524333,0.000100441575,0.00029383606],"domain_scores_gemma":[0.9995261,0.00007110886,0.000043583947,0.00023275148,0.00006911952,0.00005733385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015247337,0.00020365234,0.000166566,0.00019873517,0.0000246969,0.0000532217,0.00018419695,0.00014738209,0.000050674793],"category_scores_gemma":[0.000036052104,0.00019700149,0.000036105146,0.0004646621,0.000029830531,0.00020949096,0.000030287156,0.00057321636,0.0000063119796],"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":[0.000014475223,0.00014673328,0.0005977581,0.000030015251,0.0000031450759,5.797372e-7,0.00005976977,0.9581184,0.0015299991,0.0003612192,0.000147458,0.03899046],"study_design_scores_gemma":[0.00052944483,0.000033801392,0.00012569029,0.00007166028,0.0000034888567,8.000716e-7,0.000054369975,0.99753314,0.0009488474,0.000010682549,0.0004711474,0.00021691063],"about_ca_topic_score_codex":0.000009835548,"about_ca_topic_score_gemma":0.0000851604,"teacher_disagreement_score":0.87921065,"about_ca_system_score_codex":0.00007562614,"about_ca_system_score_gemma":0.000009983281,"threshold_uncertainty_score":0.8033488},"labels":[],"label_agreement":null},{"id":"W2075662546","doi":"10.1155/wcn/2006/17526","title":"Adaptive Downlink Resource Allocation Strategies for Real-Time Data Services in OFDM Cellular Systems","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Telecommunications link; Resource allocation; Fading; Orthogonal frequency-division multiplexing; Channel (broadcasting); Minification; Bandwidth (computing); Interference (communication); Real-time computing; Computer network","score_opus":0.027683546849438825,"score_gpt":0.25037235639585226,"score_spread":0.22268880954641343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075662546","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":[0.17856593,0.065671965,0.7358659,0.00085245963,0.0010924063,0.0023972704,0.00013621584,0.0009318258,0.014486038],"genre_scores_gemma":[0.9789253,0.011760633,0.008049573,0.000017727838,0.00056941353,0.00004013262,0.0005386452,0.00006664573,0.00003193267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984849,0.0001881615,0.0006076517,0.00023280851,0.00016433108,0.00032215897],"domain_scores_gemma":[0.99809235,0.00045815957,0.00025660387,0.0010365171,0.00009179978,0.00006458612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006079904,0.00022739668,0.0002928173,0.0001738035,0.00042132955,0.00029742197,0.00085460517,0.000116024086,0.0000014236957],"category_scores_gemma":[0.000002191006,0.00023557754,0.000033155557,0.000347009,0.00006201596,0.0005964905,0.00015671665,0.0004150473,0.000002262713],"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":[0.000033986256,0.00004182911,0.00023179183,0.000047213885,0.000030248946,0.0000028069908,0.00016908748,0.97974116,0.00072978245,0.0041860687,0.00029085434,0.014495145],"study_design_scores_gemma":[0.00043787688,0.000043873795,0.0001881158,0.0006110458,0.000023635157,0.000015576637,0.000581986,0.9875594,0.00001671221,0.00049143983,0.009794915,0.00023542347],"about_ca_topic_score_codex":0.000058315258,"about_ca_topic_score_gemma":0.0001650714,"teacher_disagreement_score":0.80035937,"about_ca_system_score_codex":0.00013301965,"about_ca_system_score_gemma":0.000027641858,"threshold_uncertainty_score":0.96065736},"labels":[],"label_agreement":null},{"id":"W2075838418","doi":"10.1109/mwc.2007.314545","title":"Dynamic resource allocation in OFDMA wireless metropolitan area networks [Radio Resource Management and Protocol Engineering for IEEE 802.16]","year":2007,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":72,"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":"Ministère de la Santé et des Services sociaux","keywords":"Computer science; Resource allocation; Radio resource management; Orthogonal frequency-division multiple access; Subcarrier; Resource management (computing); Computer network; Frequency-division multiple access; IEEE 802; Wireless network; Wireless; Access control; Orthogonal frequency-division multiplexing; Telecommunications; Channel (broadcasting)","score_opus":0.013491994810477925,"score_gpt":0.2598984873527367,"score_spread":0.24640649254225877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075838418","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":[0.018382346,0.00053330546,0.9557921,0.00016943901,0.00013697264,0.022939187,0.000018488168,0.0006696673,0.0013584767],"genre_scores_gemma":[0.9241981,0.00056583027,0.03238132,0.00004896146,0.000083251936,0.042203486,0.00016794227,0.00019864106,0.00015247118],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99774605,0.00007851875,0.0008150437,0.00041718944,0.00022781568,0.00071538857],"domain_scores_gemma":[0.99753577,0.0005038359,0.00016998465,0.0015292186,0.000090245405,0.00017092524],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006249305,0.00041275137,0.00041347017,0.000498394,0.00027810613,0.000078138,0.0008617977,0.00024258421,0.0000028264703],"category_scores_gemma":[0.000014417973,0.00050428516,0.000081863385,0.0009796524,0.00014015411,0.00028489347,0.00013131407,0.0005183851,0.0000016827466],"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":[0.000053281852,0.000096508425,0.00033071236,0.00025022647,0.0000833735,0.0000021935987,0.00021236508,0.9649358,0.00072383427,0.004517382,0.0003768344,0.028417522],"study_design_scores_gemma":[0.0011415319,0.000029755556,0.00093794643,0.00039258317,0.00004086139,0.000005971443,0.00046255815,0.984832,0.00054947386,0.00009274559,0.0110148145,0.00049978006],"about_ca_topic_score_codex":0.000023927721,"about_ca_topic_score_gemma":0.00047694685,"teacher_disagreement_score":0.9234108,"about_ca_system_score_codex":0.0011107385,"about_ca_system_score_gemma":0.000014226123,"threshold_uncertainty_score":0.9997409},"labels":[],"label_agreement":null},{"id":"W2075905011","doi":"10.1109/icc.2010.5502105","title":"Service-Aware Optimal Spectrum Sharing Algorithm in Heterogeneous Wireless Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Radio resource management; Wireless network; Wireless; Scheduling (production processes); Cognitive radio; Shared resource; Heterogeneous network; Resource management (computing); Throughput; Resource allocation; Distributed computing; Telecommunications","score_opus":0.004696969871115545,"score_gpt":0.19836530575830488,"score_spread":0.19366833588718935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075905011","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":[0.24270205,0.00006412806,0.75507176,0.0000389897,0.0007088329,0.00018187324,0.0000027328292,0.0006785666,0.0005510649],"genre_scores_gemma":[0.96469533,0.000097637305,0.034509454,0.00008335629,0.00037842718,0.000033969533,0.00004399961,0.00010685695,0.0000509671],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872977,0.000007450697,0.00029577565,0.00031282782,0.00012435611,0.00052981847],"domain_scores_gemma":[0.99944687,0.000027590282,0.000030233328,0.0003559356,0.000028593666,0.00011076406],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007647133,0.00024817462,0.00022533884,0.00011050009,0.000050617575,0.000057026722,0.0002789274,0.00020212628,0.00021746707],"category_scores_gemma":[0.0000018751251,0.00027555175,0.0000405648,0.00047425987,0.00001698212,0.00024742502,0.00009423806,0.0005491948,0.000031242536],"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":[0.0000032807234,0.000012924282,0.0006233292,0.0000128972015,0.0000107490905,0.00002594154,0.000041698884,0.97798896,0.00019253715,0.00008145569,0.000029556802,0.0209767],"study_design_scores_gemma":[0.00029902207,0.000009102449,0.00025786887,0.000022503478,0.0000041737285,0.000030947045,0.000022898701,0.9973564,0.0014738442,0.00006717684,0.00013874896,0.00031731836],"about_ca_topic_score_codex":0.000046230216,"about_ca_topic_score_gemma":0.001699351,"teacher_disagreement_score":0.72199327,"about_ca_system_score_codex":0.00006651848,"about_ca_system_score_gemma":0.0000073371148,"threshold_uncertainty_score":0.99996966},"labels":[],"label_agreement":null},{"id":"W2076435874","doi":"10.1007/s11277-011-0325-4","title":"Packet Delay Statistics of the Multichannel Selective-Repeat Automatic-Repeat-Request","year":2011,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Communications Research Centre Canada","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Computer science; Transmission delay; Network packet; Processing delay; Scheduling (production processes); Real-time computing; Computer network; Automatic repeat request; Go-Back-N ARQ; End-to-end delay; Hybrid automatic repeat request; Transmitter; Selective Repeat ARQ; Queue; Queuing delay; Algorithm; Channel (broadcasting); Mathematics; Mathematical optimization; Telecommunications link","score_opus":0.030094937143743433,"score_gpt":0.2381616539797505,"score_spread":0.20806671683600708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076435874","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":[0.36441258,0.002234979,0.608276,0.0003129133,0.0007568075,0.0016678812,0.0010252037,0.0014964946,0.01981712],"genre_scores_gemma":[0.9186434,0.00043603187,0.080538824,0.000031687556,0.000026600417,0.00008990991,0.00008407374,0.000064708474,0.00008472553],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987563,0.00015429717,0.00042076258,0.00016475092,0.00022829966,0.00027559686],"domain_scores_gemma":[0.99797994,0.00026191722,0.0001549395,0.0012658708,0.00026159143,0.00007572278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014176259,0.00022091245,0.00024785736,0.00007438478,0.00030402443,0.000016194193,0.00094567327,0.00010577132,0.00005880164],"category_scores_gemma":[0.00006138994,0.00019802967,0.00008417555,0.00044887874,0.00033393526,0.0001826037,0.00021039584,0.00037927326,0.00001799918],"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":[0.0001619058,0.0030302026,0.045175824,0.0013856982,0.0026490458,0.000021306256,0.15556659,0.36226034,0.023363514,0.1760477,0.015456368,0.21488151],"study_design_scores_gemma":[0.00028451093,0.000026205233,0.006411925,0.00010560667,0.00006820894,0.000011649773,0.00046176347,0.9894176,0.0020802969,0.00060959876,0.00026350617,0.00025910125],"about_ca_topic_score_codex":0.00008552941,"about_ca_topic_score_gemma":0.000357103,"teacher_disagreement_score":0.6271573,"about_ca_system_score_codex":0.00013372823,"about_ca_system_score_gemma":0.00005536965,"threshold_uncertainty_score":0.80754155},"labels":[],"label_agreement":null},{"id":"W2076985535","doi":"10.1117/12.815557","title":"Multimedia application performance on a WiMAX network","year":2009,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"","keywords":"WiMAX; Voice over IP; Computer science; Computer network; Network packet; Packet loss; The Internet; Telecommunications link; Ethernet; Multimedia; Cable modem; Telecommunications; Wireless; Operating system","score_opus":0.0064073781149733625,"score_gpt":0.20791737622481732,"score_spread":0.20150999810984396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076985535","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":[0.9926139,0.00012408619,0.0016392819,0.0005980709,0.00027602864,0.0006752938,0.000014883028,0.00032247865,0.003735988],"genre_scores_gemma":[0.78267276,0.0003866897,0.21546686,0.00014394708,0.00094275415,0.00019507838,0.000023421795,0.00008999338,0.000078509336],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99798113,8.364491e-9,0.0006340521,0.00034513816,0.0005587332,0.00048096667],"domain_scores_gemma":[0.99870306,0.00010476858,0.00024416862,0.00007999362,0.0007515212,0.00011649841],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003341283,0.00036089774,0.00038067767,0.00008677875,0.00008967077,0.00006196262,0.00070245983,0.00021090606,0.0000055357286],"category_scores_gemma":[0.00012835713,0.0003305432,0.00033964065,0.00048717557,0.0001054351,0.00054588827,0.000048854075,0.0003671688,0.000004101251],"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":[0.00015130345,0.00013214491,0.00035156068,0.00039470938,0.00027785156,6.509784e-8,0.00017269966,0.50214624,0.24398483,0.23469867,0.0067681526,0.010921773],"study_design_scores_gemma":[0.00075108936,0.00028512266,0.0016845091,0.0002945927,0.00006637614,0.0000055119904,0.000097783144,0.95240587,0.040339503,0.0008829761,0.0028028581,0.00038382525],"about_ca_topic_score_codex":8.0900486e-7,"about_ca_topic_score_gemma":5.134764e-8,"teacher_disagreement_score":0.4502596,"about_ca_system_score_codex":0.0002081182,"about_ca_system_score_gemma":0.0000126935065,"threshold_uncertainty_score":0.99991465},"labels":[],"label_agreement":null},{"id":"W2077539535","doi":"10.1109/vetecf.2010.5594591","title":"Performance Analysis of Proportional Fair Scheduling in OFDMA Wireless Systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Memorial University of Newfoundland","funders":"","keywords":"Subcarrier; Orthogonal frequency-division multiplexing; Computer science; Orthogonal frequency-division multiple access; Proportionally fair; Scheduling (production processes); Frequency-division multiple access; Maximum throughput scheduling; Wireless; Computer network; Max-min fairness; Round-robin scheduling; Real-time computing; Resource allocation; Dynamic priority scheduling; Mathematical optimization; Quality of service; Telecommunications; Channel (broadcasting); Mathematics","score_opus":0.0047454989595167125,"score_gpt":0.20043110744274203,"score_spread":0.19568560848322533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077539535","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":[0.9053983,0.000039759634,0.09339464,0.0000047695607,0.00020323078,0.000097153745,0.0000027975602,0.00010909872,0.00075025787],"genre_scores_gemma":[0.99292725,0.00007505956,0.006840841,0.0000018450542,0.00004053977,0.000029157067,0.000024510207,0.000015965055,0.000044828386],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992971,0.0000056840076,0.00030963946,0.000109415196,0.00013807077,0.00014009411],"domain_scores_gemma":[0.9996948,0.000020860714,0.00005303895,0.00013984213,0.000062670464,0.000028735332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001041987,0.00008717668,0.00021297883,0.00029519357,0.00001644878,0.000008101726,0.00008190365,0.000072140974,0.00006000201],"category_scores_gemma":[0.000005893622,0.00008456788,0.000037406102,0.0010075356,0.000022145601,0.00018284399,0.000011908026,0.00015194158,0.0000023599528],"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":[0.0000023628693,0.000011086753,0.09855584,0.00005117224,0.000071693736,3.536665e-7,0.000031246625,0.89285034,0.006226777,0.00068391144,0.0000025890608,0.0015126204],"study_design_scores_gemma":[0.00009340156,0.0000035719934,0.031604156,0.000023514527,0.00003900113,4.777055e-7,0.00003113947,0.96626824,0.0018288745,0.0000023781683,0.000012105749,0.00009316031],"about_ca_topic_score_codex":0.00001522411,"about_ca_topic_score_gemma":0.00010054779,"teacher_disagreement_score":0.08752896,"about_ca_system_score_codex":0.000024444715,"about_ca_system_score_gemma":0.00001126782,"threshold_uncertainty_score":0.3448578},"labels":[],"label_agreement":null},{"id":"W2077820612","doi":"10.1109/ieeegcc.2009.5734249","title":"Optimization of pilot placement in adaptive M-PSK modulation systems in Rayleigh fading channel","year":2009,"lang":"en","type":"article","venue":"exhibition","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"Defence Research and Development Canada","keywords":"Rayleigh fading; Fading; Link adaptation; Channel (broadcasting); Decoding methods; Computer science; Channel state information; Frame (networking); Phase-shift keying; Modulation (music); Electronic engineering; Control theory (sociology); Bit error rate; Algorithm; Telecommunications; Engineering; Physics; Wireless; Acoustics","score_opus":0.015337767057188064,"score_gpt":0.21449781610489219,"score_spread":0.19916004904770412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077820612","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":[0.09858954,0.00021881607,0.8994254,0.000012426045,0.00017812433,0.00048687737,0.0000040391506,0.00011393978,0.0009708297],"genre_scores_gemma":[0.9939771,0.00013063572,0.0056423605,0.0000071975824,0.000064731204,0.000037383117,0.000110961286,0.000021084841,0.000008510252],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999081,0.000041129726,0.00039340442,0.00015818106,0.00014703316,0.00017922124],"domain_scores_gemma":[0.99972147,0.000024562632,0.000081378785,0.00010133871,0.000047172467,0.000024065634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001461733,0.0001275436,0.00017946308,0.0003158537,0.000019023808,0.000011702834,0.00004053084,0.0000702448,0.000008410233],"category_scores_gemma":[0.000012531185,0.00015744344,0.000016341337,0.00048194386,0.000008238269,0.00044495318,0.0000059424665,0.000096957774,0.0000019999045],"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":[0.00004906417,0.0000473763,0.00009023543,0.000024538116,0.0000024856022,0.0000014661778,0.00025969584,0.9960032,0.0021953937,0.0006954581,0.000020383826,0.00061067],"study_design_scores_gemma":[0.00077420584,0.000117149626,0.002513946,0.00030543303,0.0000025694906,0.0000010055081,0.000111327914,0.9946159,0.00115209,0.00026558724,0.0000019223892,0.0001388247],"about_ca_topic_score_codex":0.00001652757,"about_ca_topic_score_gemma":0.000017146353,"teacher_disagreement_score":0.8953876,"about_ca_system_score_codex":0.00032345648,"about_ca_system_score_gemma":0.0000063510765,"threshold_uncertainty_score":0.6420357},"labels":[],"label_agreement":null},{"id":"W2078082765","doi":"10.1109/accessnets.2007.4447132","title":"Strategies for fast scanning and handovers in WiMAX/802.16","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":22,"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":"WiMAX; Handover; Computer science; Computer network; Base station; Mobile station; Channel (broadcasting); Cellular network; Real-time computing; Telecommunications; Wireless","score_opus":0.006469467879478156,"score_gpt":0.22545794638690422,"score_spread":0.21898847850742606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078082765","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":[0.04170358,0.00015343635,0.93942285,0.000008185972,0.000072664654,0.00012195611,9.235197e-7,0.00013249376,0.018383928],"genre_scores_gemma":[0.96487534,0.000045349625,0.03488315,0.000018596103,0.00004015418,0.000007633366,0.000005850743,0.000018716108,0.00010518286],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996014,0.0000016036228,0.0001055127,0.000079999,0.00003559613,0.00017588408],"domain_scores_gemma":[0.99985576,0.00005067254,0.000009841108,0.000045447796,0.00001162189,0.000026673348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000073189214,0.00006951712,0.00007540755,0.000060783517,0.00002160919,0.000023962573,0.000024955329,0.000036832582,0.000007931736],"category_scores_gemma":[0.0000045381557,0.00007228619,0.000009337095,0.0001027955,0.000014225404,0.00023526889,0.000006638046,0.00004339908,6.497715e-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":[0.000011890128,0.0000021706658,0.00066269137,0.00002259456,0.000003856809,9.323718e-7,0.0001363525,0.97675896,0.00047772264,0.0042281207,0.00016355714,0.01753113],"study_design_scores_gemma":[0.001008943,0.000024698898,0.0012201655,0.00004621237,0.000004001387,0.0000024575206,0.0020983848,0.98920006,0.0022570635,0.0024296495,0.0014872323,0.00022114988],"about_ca_topic_score_codex":0.000007594533,"about_ca_topic_score_gemma":0.0002693193,"teacher_disagreement_score":0.92317176,"about_ca_system_score_codex":0.00004752576,"about_ca_system_score_gemma":0.0000046354407,"threshold_uncertainty_score":0.2947745},"labels":[],"label_agreement":null},{"id":"W2078485538","doi":"10.1109/glocomw.2013.6825003","title":"Erlang analysis of cellular networks using stochastic Petri nets and user-in-the-loop extension for demand control","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Erlang (programming language); Computer science; Stochastic Petri net; Petri net; Markov chain; Computer network; Distributed computing; Erlang distribution; Provisioning; Real-time computing; Theoretical computer science","score_opus":0.008298365359206788,"score_gpt":0.2099247857441858,"score_spread":0.20162642038497902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078485538","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":[0.23226658,0.0006506924,0.76659584,0.000010381023,0.000042828156,0.00038749093,0.0000015063254,0.000031164935,0.000013529578],"genre_scores_gemma":[0.9895393,0.00003512332,0.010270495,0.000038361057,0.000035581274,0.000027243514,0.000017392504,0.000022032958,0.000014462177],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992888,0.000024354884,0.00025132482,0.00014187788,0.00008493181,0.00020871818],"domain_scores_gemma":[0.9993787,0.00030409056,0.00005312496,0.0001650104,0.00006433172,0.00003475128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014031697,0.00011987312,0.00028362684,0.00018318555,0.000039913106,0.000023991845,0.000065391,0.00006853645,0.000017256189],"category_scores_gemma":[0.000022058946,0.000097383585,0.000054892476,0.00053950783,0.000020725654,0.00014126406,0.000009797067,0.00006723917,3.842266e-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":[0.000006860642,0.0000069128487,0.0005663656,0.000012523246,0.000095553674,5.513526e-7,0.00003464915,0.99651295,0.002000422,0.0000726587,0.00005274683,0.0006377801],"study_design_scores_gemma":[0.0004754173,0.000015573032,0.0020926937,0.000019011466,0.00030234468,9.096042e-7,0.000050552608,0.99684083,0.00005718116,0.000033423537,0.000005116865,0.000106924206],"about_ca_topic_score_codex":0.000027113,"about_ca_topic_score_gemma":0.000032979333,"teacher_disagreement_score":0.7572727,"about_ca_system_score_codex":0.000020470463,"about_ca_system_score_gemma":0.0000026693858,"threshold_uncertainty_score":0.39711872},"labels":[],"label_agreement":null},{"id":"W2078515993","doi":"10.1016/j.comnet.2007.01.031","title":"QoS-aware bandwidth allocation and admission control in IEEE 802.16 broadband wireless access networks: A non-cooperative game theoretic approach","year":2007,"lang":"en","type":"article","venue":"Computer Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Computer network; Polling; Bandwidth allocation; Quality of service; Wireless broadband; Admission control; Queueing theory; Bandwidth (computing); Base station; Call Admission Control; WiMAX; Wireless; Wireless network; Telecommunications","score_opus":0.006290188177697909,"score_gpt":0.22390130159399613,"score_spread":0.2176111134162982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078515993","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":[0.026645627,0.00129065,0.9693536,0.000018570123,0.001129691,0.0008741721,0.0000019500976,0.00028860776,0.00039709048],"genre_scores_gemma":[0.9932772,0.0010065146,0.0036131518,0.00026173025,0.0015346741,0.0000671202,0.00010734038,0.00010894751,0.000023345598],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99781775,0.000104305895,0.000585758,0.0005681359,0.00019623108,0.0007277865],"domain_scores_gemma":[0.9988466,0.0003161435,0.000120093566,0.00036024966,0.00011508074,0.00024186562],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00044360867,0.0004647548,0.0005366023,0.00018574295,0.000099033176,0.00019722695,0.00034727543,0.00035756416,0.000009497908],"category_scores_gemma":[0.0000057379943,0.00045378605,0.000057885958,0.00070197973,0.00011252458,0.0005581449,0.00009282025,0.00058297184,0.0000016247857],"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":[0.00010831473,0.000047997983,0.0015012539,0.000052598778,0.000038723763,0.000011957034,0.00023751667,0.9465282,0.000013723143,0.00013371253,0.0010315728,0.050294425],"study_design_scores_gemma":[0.0019447765,0.000061238614,0.0031573293,0.00031311536,0.000024652569,0.000016777718,0.000024664276,0.99374604,0.00004175391,0.0000603104,0.000112027476,0.00049730606],"about_ca_topic_score_codex":0.0000062481745,"about_ca_topic_score_gemma":0.00002863158,"teacher_disagreement_score":0.96663153,"about_ca_system_score_codex":0.00020243194,"about_ca_system_score_gemma":0.000020159558,"threshold_uncertainty_score":0.9997914},"labels":[],"label_agreement":null},{"id":"W2078587687","doi":"10.1109/vtcfall.2013.6692356","title":"Performance Gains of Spectrum Sharing in Multi-Operator LTE-Advanced Systems","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Upgrade; Operator (biology); Distributed computing; Spectrum (functional analysis); Time-sharing; Spectrum management; Computer network; Telecommunications; Cognitive radio; Wireless","score_opus":0.014249627737277686,"score_gpt":0.21861935466114898,"score_spread":0.2043697269238713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078587687","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":[0.8843682,0.00026996172,0.11205336,0.0000063407397,0.0002389623,0.00037150757,9.571727e-7,0.00022682654,0.0024639126],"genre_scores_gemma":[0.98724604,0.00029565164,0.011995647,0.0000061509368,0.00002723804,0.00007031305,0.000003832544,0.00003883821,0.00031631647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920326,0.00000614716,0.00030418232,0.00014909112,0.00008488968,0.00025239744],"domain_scores_gemma":[0.9996689,0.000015731644,0.00003208796,0.00021002295,0.00003001317,0.000043221506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004852704,0.00012956145,0.00019156997,0.000099100806,0.000018853316,0.000017741724,0.00012851237,0.00005351562,0.000065421526],"category_scores_gemma":[0.000007034306,0.00012725109,0.000018088529,0.00026171847,0.000013652331,0.00047935746,0.000029204466,0.00010558729,0.00005087767],"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":[0.0000015764748,0.000011522245,0.012830657,0.0000876379,0.0000048607894,4.4150326e-7,0.00007527602,0.98085475,0.0049579726,0.00011683715,0.000015111788,0.0010433599],"study_design_scores_gemma":[0.00037317636,0.000013202322,0.007339976,0.00011422887,0.0000012627472,0.0000010132316,0.00008203406,0.9857339,0.006163506,0.0000041577105,0.000026800933,0.00014673713],"about_ca_topic_score_codex":0.000038851456,"about_ca_topic_score_gemma":0.000030506204,"teacher_disagreement_score":0.10287784,"about_ca_system_score_codex":0.00009106066,"about_ca_system_score_gemma":0.0000049897526,"threshold_uncertainty_score":0.5189149},"labels":[],"label_agreement":null},{"id":"W2078668522","doi":"10.1109/ccece.2006.277544","title":"A Real-Time Radio Resource Allocation Scheme in OFDMA System","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Lakehead University","funders":"","keywords":"Orthogonal frequency-division multiple access; Computer science; Resource allocation; Greedy algorithm; Orthogonal frequency-division multiplexing; Mathematical optimization; Frequency-division multiple access; Computational complexity theory; Transmission (telecommunications); Scheme (mathematics); Resource management (computing); Optimization problem; Algorithm; Distributed computing; Mathematics; Computer network; Telecommunications","score_opus":0.0028192050564897725,"score_gpt":0.17186819074696338,"score_spread":0.1690489856904736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078668522","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":[0.3896988,0.0005029248,0.40906608,0.00013032016,0.00017256531,0.00066169415,0.000004097182,0.0037919388,0.19597158],"genre_scores_gemma":[0.96259046,0.00005014811,0.035516873,0.000004892625,0.00015719465,0.000049156763,0.000056204703,0.00005263887,0.0015224443],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937445,0.000016288604,0.00021707229,0.00012566196,0.00009145192,0.00017508725],"domain_scores_gemma":[0.99975556,0.000025031166,0.000023768527,0.00015470572,0.000017759552,0.0000231783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007213957,0.00010003365,0.00012059029,0.00008787296,0.00001925055,0.000013875189,0.00006559639,0.00006947097,0.000028970288],"category_scores_gemma":[0.000003103355,0.000108858694,0.000017287392,0.00030476795,0.0000083180375,0.00012072459,0.0000093837025,0.00006149392,0.00005290383],"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":[0.0000032039168,0.000006696906,0.00034167295,0.000037807084,0.0000032123987,0.000002238628,0.000017670221,0.984257,0.009995354,0.0029933567,0.0018564406,0.00048537357],"study_design_scores_gemma":[0.00022656911,0.0000034251452,0.0010779672,0.00006889017,0.0000025191987,0.0000025403108,0.000025856163,0.9956476,0.001945608,0.000016991266,0.00085658324,0.0001254251],"about_ca_topic_score_codex":0.000079954065,"about_ca_topic_score_gemma":0.000028864128,"teacher_disagreement_score":0.57289165,"about_ca_system_score_codex":0.00021325694,"about_ca_system_score_gemma":0.0000051351212,"threshold_uncertainty_score":0.44391286},"labels":[],"label_agreement":null},{"id":"W2078834394","doi":"10.1109/twc.2011.030911.100915","title":"Dynamic Spectrum Management for WCDMA/DVB Heterogeneous Systems","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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":"Computer science; Digital Video Broadcasting; Code division multiple access; Broadcasting (networking); Frequency allocation; Spread spectrum; Computer network; Scheme (mathematics); Spectrum management; Digital television; Wireless; Telecommunications; Cognitive radio; Mathematics","score_opus":0.022647623352730666,"score_gpt":0.23715314262824588,"score_spread":0.21450551927551523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078834394","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":[0.0019310737,0.0004214094,0.9925896,0.000056277437,0.0007693779,0.0010229724,0.0000957588,0.0008953277,0.0022182297],"genre_scores_gemma":[0.9622795,0.0032948167,0.032591473,0.000022817081,0.000013726522,0.0013079463,0.000044973927,0.00011828471,0.00032644309],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880755,0.000052185005,0.00040522666,0.00024473472,0.00013394743,0.0003563543],"domain_scores_gemma":[0.9979732,0.000110480374,0.000067417524,0.0016986121,0.000053863438,0.00009643192],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008467155,0.00026151084,0.00023634905,0.00022988676,0.00041060385,0.000038200087,0.0007340896,0.00011520675,0.000027969249],"category_scores_gemma":[5.7337127e-7,0.00030899834,0.00013128328,0.00035637015,0.000093100374,0.00018021387,0.00000541473,0.0002545929,0.000056022684],"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":[0.000020683543,0.00017093307,0.0000013492522,0.000079468104,0.00016987437,0.000001340228,0.00023113705,0.98551327,0.00011540098,0.0017563635,0.00004541211,0.011894785],"study_design_scores_gemma":[0.00044275395,0.00005647685,0.000017492588,0.00009081677,0.000092285525,0.000012340579,0.00012255982,0.99504393,0.0022006347,0.00029583182,0.0012818828,0.00034296385],"about_ca_topic_score_codex":0.00001494944,"about_ca_topic_score_gemma":0.00015370219,"teacher_disagreement_score":0.9603484,"about_ca_system_score_codex":0.00023271421,"about_ca_system_score_gemma":0.000009926994,"threshold_uncertainty_score":0.9999362},"labels":[],"label_agreement":null},{"id":"W2078964535","doi":"10.1109/ccece.2010.5575230","title":"Adaptive resource allocation for real-time services in OFDMA systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Resource allocation; Upper and lower bounds; Resource management (computing); Mathematical optimization; Frequency-division multiple access; Distributed computing; Linear programming; Orthogonal frequency-division multiplexing; Computer network; Algorithm; Mathematics","score_opus":0.004615582662031803,"score_gpt":0.19802888028571447,"score_spread":0.19341329762368267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078964535","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":[0.36224172,0.00023155897,0.6032297,0.00012951967,0.0008016979,0.0018819399,0.00002337351,0.0016361874,0.029824292],"genre_scores_gemma":[0.97588754,0.000053961292,0.022828596,0.000012035833,0.00017704064,0.00020642148,0.00005969149,0.000047641297,0.0007270998],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950254,0.000008368612,0.00016012811,0.000118772754,0.00006115081,0.00014904432],"domain_scores_gemma":[0.9996974,0.00006751491,0.000028029528,0.00013557944,0.00004147223,0.000029992205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000860965,0.00008906071,0.00010711664,0.00006171782,0.00002200659,0.000018003257,0.00008197931,0.00008776276,0.00001648025],"category_scores_gemma":[0.0000039699644,0.00009126714,0.000014507886,0.00014237806,0.0000072960156,0.0001600343,0.000009294606,0.00007844323,0.00001399012],"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":[0.000009596734,0.00000577165,0.000074561336,0.00005153548,0.0000059789295,1.7762925e-7,0.00012393153,0.9843789,0.011897716,0.0016807826,0.00023056062,0.0015405304],"study_design_scores_gemma":[0.00019500748,0.000010053592,0.00024523257,0.00003828989,0.0000036868232,5.840552e-7,0.00012252647,0.99658495,0.000971726,0.000055319368,0.0016672831,0.000105311854],"about_ca_topic_score_codex":0.000059974744,"about_ca_topic_score_gemma":0.00021504168,"teacher_disagreement_score":0.6136458,"about_ca_system_score_codex":0.00003147042,"about_ca_system_score_gemma":0.0000043136465,"threshold_uncertainty_score":0.3721766},"labels":[],"label_agreement":null},{"id":"W2079281532","doi":"10.1002/ett.2736","title":"Joint subcarrier and power allocation in downlink OFDMA systems: an multi‐objective approach","year":2013,"lang":"en","type":"article","venue":"Transactions on Emerging Telecommunications Technologies","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Subcarrier; Sorting; Computer science; Orthogonal frequency-division multiple access; Telecommunications link; Mathematical optimization; Genetic algorithm; Resource allocation; Joint (building); Power (physics); Orthogonal frequency-division multiplexing; Algorithm; Engineering; Mathematics; Computer network","score_opus":0.0158966000707203,"score_gpt":0.23405388789858872,"score_spread":0.21815728782786842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079281532","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":[0.08199845,0.0017732087,0.91084003,0.0005536128,0.000094773,0.0009771365,0.000011297373,0.0032813605,0.00047012203],"genre_scores_gemma":[0.89667046,0.0036054223,0.09808197,0.0000081179705,0.0000034829277,0.001524473,0.000026784051,0.00004920999,0.000030055155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998861,0.00007272656,0.0003957985,0.0002818375,0.00010438063,0.00028425537],"domain_scores_gemma":[0.9987367,0.00006809901,0.00006710438,0.0009819479,0.000108722976,0.00003745974],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013027136,0.00023609959,0.00023641577,0.00063081464,0.00025192354,0.00006974375,0.0003767202,0.00023473243,0.000017236864],"category_scores_gemma":[0.000023858453,0.00025165075,0.000034109096,0.0008542224,0.00015158467,0.00068471767,0.00001694883,0.00060077553,0.000011673693],"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":[0.000002254926,0.00014637974,0.00012199843,0.000024529043,0.000034681383,1.2005587e-7,0.0006093655,0.95939463,0.0012188966,0.0005794058,0.000016970134,0.037850767],"study_design_scores_gemma":[0.00032540518,0.00003902351,0.0022151007,0.00007039448,0.000015866994,0.0000047444687,0.0073616034,0.9875937,0.0016573485,0.00026266972,0.00013055746,0.000323573],"about_ca_topic_score_codex":0.00012814904,"about_ca_topic_score_gemma":0.000078440244,"teacher_disagreement_score":0.81467205,"about_ca_system_score_codex":0.00018957818,"about_ca_system_score_gemma":0.000013147866,"threshold_uncertainty_score":0.99999356},"labels":[],"label_agreement":null},{"id":"W2079475160","doi":"10.1145/1185373.1185398","title":"A link performance model for multi-user wireless fading channels","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Fading; Computer science; Computer network; Link (geometry); Wireless; Channel (broadcasting); Telecommunications","score_opus":0.01939264380881439,"score_gpt":0.22930068114115143,"score_spread":0.20990803733233704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079475160","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":[0.038258705,0.000083014515,0.9598056,0.00001799108,0.00019960808,0.00028271612,0.000004029171,0.00061422103,0.0007341314],"genre_scores_gemma":[0.81379867,0.000057952333,0.18169555,0.000022097265,0.00023716925,0.0001041846,0.000028510776,0.000063535954,0.0039923536],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992876,0.0000024694168,0.00018695983,0.00015193543,0.00006970159,0.0003013089],"domain_scores_gemma":[0.9997448,0.000019727422,0.000022714772,0.00013247933,0.00004696454,0.000033322875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000044941477,0.00014835197,0.00013467015,0.00005841137,0.00007400741,0.000022893977,0.00008979016,0.000083408966,0.000007036286],"category_scores_gemma":[0.0000023264108,0.00015272333,0.000039172333,0.00012462612,0.000011641292,0.0002807125,0.000014167784,0.00007394545,0.000010289357],"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":[0.0000041246003,0.000007781638,0.00009037936,0.00004951017,0.0000053481212,1.707753e-7,0.00004952187,0.9919562,0.00049133383,0.0018469,0.0003987982,0.005099948],"study_design_scores_gemma":[0.00045037322,0.0000071291715,0.000035842397,0.00002517752,0.000005218349,7.9812094e-7,0.000004637276,0.9932341,0.0054717446,0.000077679855,0.00047949175,0.00020781384],"about_ca_topic_score_codex":0.000002334838,"about_ca_topic_score_gemma":0.000011042404,"teacher_disagreement_score":0.77811,"about_ca_system_score_codex":0.000057711055,"about_ca_system_score_gemma":0.0000056608183,"threshold_uncertainty_score":0.62278765},"labels":[],"label_agreement":null},{"id":"W2080296812","doi":"10.1109/wcl.2012.012012.110257","title":"Optimal Energy-Efficient Channel Exploration for Opportunistic Spectrum Usage","year":2012,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":39,"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":"Computer science; Channel (broadcasting); Energy (signal processing); State (computer science); Optimal stopping; Channel state information; Efficient energy use; Mathematical optimization; Algorithm; Wireless; Computer network; Telecommunications; Mathematics","score_opus":0.0391848611990751,"score_gpt":0.251679458433113,"score_spread":0.2124945972340379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080296812","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":[0.01785305,0.00030770912,0.9778562,0.0019381011,0.0007631875,0.0003663631,0.000043999946,0.0005244054,0.0003469542],"genre_scores_gemma":[0.9693494,0.00059308135,0.028124755,0.0003998889,0.00028900895,0.0006496541,0.00044353894,0.000106618434,0.00004404119],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986672,0.00007139363,0.0003807321,0.0001785506,0.00016335763,0.00053880515],"domain_scores_gemma":[0.998249,0.00021636489,0.00010736032,0.0012261532,0.000048129845,0.00015298375],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002053978,0.0002511239,0.0002259849,0.00016944099,0.00033714008,0.000050215276,0.0006047723,0.000090391695,0.000007856153],"category_scores_gemma":[0.000011684607,0.00029830137,0.00008738382,0.00033027728,0.00012219773,0.00049300905,0.00007150026,0.00018195409,0.000018964221],"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":[0.00000733341,0.00008196899,0.000010649268,0.000019674677,0.000033248387,3.2466184e-7,0.00043567718,0.9803414,0.00793961,0.0061938893,0.002647127,0.0022891124],"study_design_scores_gemma":[0.00028765874,0.00001214927,0.00002122939,0.000035128047,0.00003025386,0.0000044445123,0.00010048426,0.9884852,0.0037606917,0.000046417736,0.0068734023,0.0003429276],"about_ca_topic_score_codex":0.000006667763,"about_ca_topic_score_gemma":0.000011121893,"teacher_disagreement_score":0.95149636,"about_ca_system_score_codex":0.00020866569,"about_ca_system_score_gemma":0.000014591343,"threshold_uncertainty_score":0.9999469},"labels":[],"label_agreement":null},{"id":"W2080399105","doi":"10.5296/npa.v4i4.2171","title":"Cross Layer Design for Efficient Video Streaming over LTE Using Scalable Video Coding","year":2012,"lang":"en","type":"article","venue":"Network Protocols and Algorithms","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Ottawa","funders":"","keywords":"Computer science; Multimedia Broadcast Multicast Service; Unicast; Multicast; Computer network; Video quality; Scalable Video Coding; Cellular network; Real-time computing; Scalability","score_opus":0.040634546993086273,"score_gpt":0.314875826326438,"score_spread":0.27424127933335174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080399105","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":[0.005269261,0.00043902698,0.9657144,0.0000029892678,0.00033129085,0.02782104,0.0000092696655,0.00026406892,0.00014867476],"genre_scores_gemma":[0.23449776,0.00005561523,0.70241034,0.0000705859,0.0038030494,0.058706395,0.000024420051,0.00026689548,0.00016492236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99817514,0.000045359324,0.00037905027,0.0002928438,0.0001866724,0.00092092133],"domain_scores_gemma":[0.99919796,0.00022712466,0.00010415989,0.0002163525,0.000071022805,0.00018340466],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00061114883,0.00030336628,0.00032609917,0.00006308729,0.0003744463,0.00017117517,0.00010935462,0.00015729567,0.000028364222],"category_scores_gemma":[0.000024301391,0.00030142165,0.00006521243,0.00037587286,0.00005021042,0.0004072038,0.00006276958,0.00017165758,0.0000028712475],"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":[0.0000370348,0.000027682634,0.0018146421,0.00012815921,0.000026323889,8.27606e-7,0.000074052376,0.97260803,0.00040773797,0.00015614067,0.00024316885,0.024476197],"study_design_scores_gemma":[0.0009652037,0.00004644448,0.0004698691,0.00036487204,0.000019883657,0.0000062625695,0.000008814708,0.9906968,0.0017633144,0.00011007441,0.0051756985,0.00037274975],"about_ca_topic_score_codex":0.0000033614415,"about_ca_topic_score_gemma":5.2881035e-7,"teacher_disagreement_score":0.26330402,"about_ca_system_score_codex":0.00012459402,"about_ca_system_score_gemma":0.000015667574,"threshold_uncertainty_score":0.9999438},"labels":[],"label_agreement":null},{"id":"W2080479468","doi":"10.1002/wcm.174","title":"Future mobile broadband wireless networks: a radio resource management perspective","year":2003,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Nortel (Canada)","funders":"","keywords":"Computer science; Computer network; Wireless broadband; Radio resource management; Telecommunications; Mobile broadband; Wireless network; Radio access network; Municipal wireless network; Wireless; Quality of service; Broadband networks; Exploit; Resource management (computing); Wireless WAN; Broadband; Wi-Fi array; Base station; Computer security; Mobile station","score_opus":0.006250530176406996,"score_gpt":0.22842776052418406,"score_spread":0.22217723034777706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080479468","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":[0.15494429,0.054389868,0.7585348,0.00006793427,0.000552972,0.002298379,0.000012110366,0.0014689285,0.027730733],"genre_scores_gemma":[0.9664236,0.013597344,0.019263828,0.000041243562,0.00015521127,0.00028437757,0.00004853809,0.00009446813,0.00009143747],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984165,0.00017761445,0.00041372003,0.00038242067,0.00015132164,0.00045842014],"domain_scores_gemma":[0.9981663,0.00018552248,0.00011290329,0.0012937982,0.00010646379,0.00013496587],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025887357,0.0003277261,0.00034543136,0.00013767787,0.000644152,0.00011198058,0.0005300922,0.00014064951,0.00001039503],"category_scores_gemma":[0.000003083268,0.00036822047,0.00007415417,0.00060907716,0.0001719446,0.00016799726,0.00027344708,0.0004576948,0.000004100598],"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":[0.000005119379,0.00007108163,0.00019893712,0.00005183954,0.00009338272,0.0000032000094,0.0014801151,0.8519332,0.000034850178,0.02709012,0.00026264467,0.1187755],"study_design_scores_gemma":[0.0006108046,0.000043184406,0.00012411641,0.00014450493,0.000042148517,0.000029525885,0.008866929,0.9223276,0.000044505778,0.00012375304,0.06718728,0.00045567882],"about_ca_topic_score_codex":0.000005731362,"about_ca_topic_score_gemma":0.000009588858,"teacher_disagreement_score":0.8114793,"about_ca_system_score_codex":0.00020531626,"about_ca_system_score_gemma":0.000012724159,"threshold_uncertainty_score":0.999877},"labels":[],"label_agreement":null},{"id":"W2080984478","doi":"10.1109/vtcfall.2012.6399158","title":"Joint Optimization of Bit and Power Allocation for Multicarrier Systems with Average BER Constraint","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Communications Research Centre Canada; Memorial University of Newfoundland","funders":"","keywords":"Bit error rate; Fading; Joint (building); Computer science; Bit (key); Constraint (computer-aided design); Throughput; Power (physics); Orthogonal frequency-division multiplexing; Bit rate; Mathematical optimization; Algorithm; Real-time computing; Wireless; Telecommunications; Computer network; Mathematics; Engineering; Decoding methods; Channel (broadcasting)","score_opus":0.008596787579534736,"score_gpt":0.1969861924080224,"score_spread":0.18838940482848765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080984478","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":[0.0145847425,0.00020523585,0.98346984,0.00001023948,0.0001271087,0.0004531323,0.000007186831,0.00009910443,0.0010433897],"genre_scores_gemma":[0.8633382,0.000032622687,0.13643602,0.000006976142,0.000028671642,0.000043666994,0.000026349993,0.000027178614,0.00006036399],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995108,0.000008298049,0.00017968401,0.00007961141,0.00007123744,0.00015037223],"domain_scores_gemma":[0.9996769,0.00003721911,0.00004355048,0.00009584687,0.00008896223,0.000057554273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000082703904,0.00009556021,0.0001287054,0.000045753924,0.000023011857,0.000011429878,0.000019457684,0.000053981043,0.000024621226],"category_scores_gemma":[0.000013137332,0.00008121733,0.000012684136,0.0000738108,0.000034711127,0.00023772284,0.000006207972,0.000032405358,6.3291844e-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":[0.0000079106585,0.000010076826,0.00029190377,0.000065280256,0.00002524921,4.909104e-8,0.00017239321,0.99612266,0.00061419624,0.002391783,0.00003990819,0.00025858943],"study_design_scores_gemma":[0.00039507606,0.000026619547,0.00014741239,0.000039051556,0.000015585934,0.000004721555,0.00013283851,0.9970789,0.0019307462,0.0000036761764,0.00011261976,0.000112757916],"about_ca_topic_score_codex":0.0000023292093,"about_ca_topic_score_gemma":8.9727007e-7,"teacher_disagreement_score":0.8487534,"about_ca_system_score_codex":0.000030233965,"about_ca_system_score_gemma":0.000005299515,"threshold_uncertainty_score":0.33119467},"labels":[],"label_agreement":null},{"id":"W2081187248","doi":"10.1109/pimrc.2012.6362851","title":"Optimal tradeoff between efficiency and Jain's fairness index in resource allocation","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":47,"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":"Index (typography); Set (abstract data type); Mathematical optimization; Computer science; Resource allocation; Resource efficiency; Resource (disambiguation); Mathematics; Computer network","score_opus":0.007677468482377464,"score_gpt":0.20971159591165184,"score_spread":0.20203412742927437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081187248","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":[0.4237994,0.00017992916,0.5736906,0.00002951999,0.000035825906,0.00010253423,6.073541e-7,0.00015029295,0.0020113087],"genre_scores_gemma":[0.99411094,0.000024660048,0.0056296545,0.000012621388,0.000118107266,0.000011992604,0.000016133663,0.000025953388,0.000049962648],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99935323,0.000017634584,0.00016237328,0.00010615642,0.00009149027,0.000269139],"domain_scores_gemma":[0.9997461,0.000055079105,0.000016888569,0.0001031013,0.000008271616,0.00007056327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013488994,0.0001054973,0.00011287851,0.00009273147,0.000026870577,0.000013127644,0.00006046835,0.00008328835,0.0000128331485],"category_scores_gemma":[0.000009338218,0.00010999613,0.000010402126,0.0002631689,0.000022832754,0.000295435,0.00001865576,0.000113939495,0.0000048659194],"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":[0.000002149917,0.000010206016,0.035279237,0.000013915165,0.0000031357015,1.8702329e-7,0.00039553829,0.9564048,0.000053837648,0.0002676463,0.00005245956,0.007516872],"study_design_scores_gemma":[0.00034290054,0.000010726788,0.11193909,0.000020596139,0.0000056737217,0.0000021855726,0.00020117451,0.8855329,0.00060461956,0.000018457225,0.001103523,0.00021812941],"about_ca_topic_score_codex":0.0000057904044,"about_ca_topic_score_gemma":0.0000046436235,"teacher_disagreement_score":0.5703115,"about_ca_system_score_codex":0.000052334184,"about_ca_system_score_gemma":0.000003145994,"threshold_uncertainty_score":0.4485512},"labels":[],"label_agreement":null},{"id":"W2081195274","doi":"10.1145/1870085.1870088","title":"Optimal scheduling in high-speed downlink packet access networks","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"","keywords":"Telecommunications link; Computer science; Markov decision process; Scheduling (production processes); Heuristic; Network packet; Mathematical optimization; Dynamic programming; Dynamic priority scheduling; Markov process; Distributed computing; Computer network; Algorithm; Mathematics; Quality of service","score_opus":0.015504737510225365,"score_gpt":0.2523002044070183,"score_spread":0.23679546689679293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081195274","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":[0.40872595,0.000019619014,0.59053963,0.000023755592,0.00039528805,0.00009421766,0.0000013282662,0.00019514156,0.000005060128],"genre_scores_gemma":[0.84969795,0.00008061921,0.14993493,0.00003244187,0.00018685027,0.0000074421814,0.000024571224,0.000033358592,0.0000018360324],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913865,0.00001861057,0.00027152954,0.00025191708,0.000103222286,0.00021604873],"domain_scores_gemma":[0.99946606,0.000118444215,0.000026610847,0.0002766129,0.00005053018,0.00006172532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009379873,0.00017654127,0.0001604379,0.00018042851,0.00011958225,0.00010556243,0.00015449531,0.0001689749,0.000009103325],"category_scores_gemma":[0.0000041267863,0.00019950607,0.00003397168,0.0002605422,0.000014643631,0.0004832161,0.000008731556,0.00051582995,0.000002049081],"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":[0.000018986564,0.000020238662,0.00005488911,0.000008315401,0.000010550342,7.892515e-7,0.000073440846,0.9385657,0.000026183827,0.000026441478,4.3975075e-7,0.06119408],"study_design_scores_gemma":[0.0005398919,0.000018863859,0.00014175312,0.000041056686,0.000010711353,0.0000015124119,0.0000049212076,0.99859,0.000034512792,0.0004078551,0.0000043037994,0.00020461062],"about_ca_topic_score_codex":0.000011164019,"about_ca_topic_score_gemma":0.000027597205,"teacher_disagreement_score":0.440972,"about_ca_system_score_codex":0.000028832643,"about_ca_system_score_gemma":0.0000062512236,"threshold_uncertainty_score":0.81356215},"labels":[],"label_agreement":null},{"id":"W2081336934","doi":"10.1016/j.dam.2013.11.018","title":"Directed weighted improper coloring for cellular channel allocation","year":2013,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Advanced Wireless Network Optimization","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":"Polytechnique Montréal; École de Technologie Supérieure; Group for Research in Decision Analysis","funders":"","keywords":"Mathematics; Combinatorics; Vertex (graph theory); Fractional coloring; Integer (computer science); Complete coloring; Edge coloring; Discrete mathematics; Graph coloring; Channel (broadcasting); Graph; Integer programming; Set (abstract data type); Algorithm; Computer science; Line graph; Graph power","score_opus":0.008197128570197996,"score_gpt":0.1945219894499761,"score_spread":0.1863248608797781,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081336934","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":[0.032353796,0.000068252164,0.9602745,0.00002385846,0.00013938449,0.0014968425,0.0000068110744,0.00095784967,0.0046787118],"genre_scores_gemma":[0.72298276,0.000045778266,0.27483052,0.00001823128,0.0001375207,0.0015194499,0.00016879657,0.00013352984,0.00016338698],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906766,0.000003248884,0.000312452,0.00017845453,0.00012638001,0.00031178907],"domain_scores_gemma":[0.99944246,0.00007026412,0.00007112417,0.00026379872,0.00008248717,0.00006985236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006509506,0.00021336143,0.00023073102,0.000059569273,0.000080998354,0.000049654922,0.00013515633,0.00010310496,0.000041742907],"category_scores_gemma":[0.000011428961,0.00019953922,0.00004382388,0.0001945586,0.00002286448,0.00015387668,0.000026466781,0.00008962646,0.00008244815],"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":[0.000014079178,0.00008304878,0.000002167694,0.0011524413,0.00015891188,5.655337e-7,0.0019136661,0.5746847,0.38586575,0.027506175,0.0025551333,0.006063406],"study_design_scores_gemma":[0.00030917657,0.000010633354,0.000005028831,0.000032047068,0.000026825292,4.2698355e-7,0.00016067839,0.9279621,0.06260819,0.008347427,0.00028011916,0.00025731063],"about_ca_topic_score_codex":0.0000013196673,"about_ca_topic_score_gemma":9.3539313e-7,"teacher_disagreement_score":0.690629,"about_ca_system_score_codex":0.00006275829,"about_ca_system_score_gemma":0.000005915017,"threshold_uncertainty_score":0.81369734},"labels":[],"label_agreement":null},{"id":"W2083172734","doi":"10.1145/1621076.1621080","title":"Fitness landscape analysis for resource allocation in multiuser OFDM based cognitive radio systems","year":2009,"lang":"en","type":"article","venue":"ACM SIGMOBILE Mobile Computing and Communications Review","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Memetic algorithm; Orthogonal frequency-division multiplexing; Computer science; Cognitive radio; Resource allocation; Evolutionary algorithm; Mathematical optimization; Local search (optimization); Genetic algorithm; Fitness landscape; Optimization problem; Wireless; Artificial intelligence; Machine learning; Algorithm; Mathematics; Channel (broadcasting); Telecommunications; Computer network","score_opus":0.0197409793210339,"score_gpt":0.29121274745949444,"score_spread":0.2714717681384605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083172734","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":[0.010695339,0.37461042,0.6107198,0.00030608146,0.00004948622,0.0029642638,0.000023271168,0.00038802472,0.00024327391],"genre_scores_gemma":[0.947628,0.038496442,0.012314212,0.00015160015,0.000027987362,0.0006823368,0.00066181074,0.000027015307,0.000010557586],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986316,0.00021988107,0.00056273805,0.00026285293,0.00009972486,0.00022318188],"domain_scores_gemma":[0.9971576,0.0012287818,0.0001435844,0.0012588794,0.00015332302,0.00005785694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058849354,0.00019989087,0.00051469787,0.00019935746,0.00017543443,0.00004598726,0.0005345699,0.00007757904,0.0000038596245],"category_scores_gemma":[0.00020872262,0.0002116134,0.00010420372,0.0012554087,0.000042140986,0.000100370635,0.00008311808,0.00018122788,0.0000021400278],"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":[0.0000039814704,0.000057454774,0.000708475,0.00044741193,0.00006061859,2.1676074e-7,0.000092070004,0.9309561,0.000009765983,0.00007212126,0.0001688598,0.06742291],"study_design_scores_gemma":[0.00046628292,0.000043113076,0.0010840591,0.0022419693,0.00025541827,0.0000018064599,0.0001021233,0.98967284,0.000012517064,0.000015397987,0.005868718,0.0002357411],"about_ca_topic_score_codex":0.0000061398787,"about_ca_topic_score_gemma":0.000010241012,"teacher_disagreement_score":0.9369327,"about_ca_system_score_codex":0.000059421254,"about_ca_system_score_gemma":0.000016994885,"threshold_uncertainty_score":0.8629344},"labels":[],"label_agreement":null},{"id":"W2083604276","doi":"10.1109/glocom.2012.6504037","title":"Rate adaptation strategy for video streaming over multiple wireless access networks","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Victoria","funders":"","keywords":"Computer science; Real Time Streaming Protocol; Video quality; Testbed; Wireless; Wireless network; Computer network; Codec; Quality of service; Real-time computing; Markov decision process; Multimedia; Markov process; The Internet; Telecommunications","score_opus":0.029801101419262215,"score_gpt":0.26871312551175286,"score_spread":0.23891202409249065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083604276","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":[0.0657828,0.00026905612,0.93161803,0.000004043193,0.0005274346,0.0004025858,0.0000064557316,0.0004690977,0.0009205032],"genre_scores_gemma":[0.9889397,0.000096880896,0.009956814,0.000047981972,0.00051195885,0.00012737053,0.00011344731,0.00008273102,0.00012308432],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990084,0.000020791493,0.0002498116,0.00015699212,0.0000827647,0.00048123757],"domain_scores_gemma":[0.9993621,0.00025189982,0.000058754373,0.00016649727,0.000055583445,0.00010518331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013317047,0.00019502468,0.00016757792,0.000058715726,0.000068081885,0.00007595329,0.00012748805,0.00009648677,0.0000457825],"category_scores_gemma":[0.0000196271,0.00020060857,0.000047438807,0.0002138137,0.0000144042,0.0013974921,0.00002616863,0.00010565373,0.0000049082614],"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":[0.000017170587,0.000015027002,0.0020191115,0.000022900133,0.000023090552,2.113438e-7,0.00005345693,0.9691301,0.00023387071,0.0006936994,0.00065587886,0.02713551],"study_design_scores_gemma":[0.00050972734,0.000011614572,0.0026597662,0.000021142967,0.000015253471,6.840737e-7,0.00007689396,0.99488926,0.0009189382,0.00006365617,0.00058158167,0.00025146658],"about_ca_topic_score_codex":0.000018073313,"about_ca_topic_score_gemma":0.00009539079,"teacher_disagreement_score":0.9231569,"about_ca_system_score_codex":0.00007942269,"about_ca_system_score_gemma":0.000007754589,"threshold_uncertainty_score":0.818058},"labels":[],"label_agreement":null},{"id":"W2084310512","doi":"10.1145/2656346.2656354","title":"Power efficient high-rate data service provisioning in vehicular networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Queue; Provisioning; Base station; Throughput; Channel (broadcasting); Resource allocation; Transmitter power output; Transmission (telecommunications); Service (business); Resource management (computing); Power (physics); Wireless; Telecommunications; Transmitter","score_opus":0.005977049103027929,"score_gpt":0.1988220636290345,"score_spread":0.19284501452600658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084310512","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":[0.09270193,0.00011234603,0.90464294,0.00007088891,0.00030692763,0.00016485114,0.0000014386655,0.0003514676,0.0016472408],"genre_scores_gemma":[0.9829302,0.000023023396,0.016589778,0.00017809443,0.00007894187,0.00000854897,0.00011972198,0.000045559667,0.000026161972],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910706,0.000037517955,0.0002133197,0.00026162874,0.00009991409,0.00028054757],"domain_scores_gemma":[0.9991976,0.00007484367,0.000025176958,0.0006182301,0.000033111093,0.000051034007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029127125,0.0001382349,0.00014423227,0.000057886096,0.00003562339,0.000033594584,0.00029294373,0.00008067039,0.000051774085],"category_scores_gemma":[0.00002605606,0.00013234041,0.000009601562,0.00042647804,0.000007524341,0.00017129997,0.00015144846,0.0001693797,0.00003442105],"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":[0.00000312495,0.000009666765,0.000108147906,0.000011644272,0.000004504315,0.00000168977,0.000026162965,0.9971535,0.000088333465,0.000580582,0.00022089163,0.0017917372],"study_design_scores_gemma":[0.0002707516,0.0000072850653,0.0010192413,0.00005143372,0.0000030642188,7.082033e-7,0.0000117496,0.99703664,0.00007173221,0.000028108394,0.0013313307,0.00016796378],"about_ca_topic_score_codex":0.000016629167,"about_ca_topic_score_gemma":0.00005588829,"teacher_disagreement_score":0.8902283,"about_ca_system_score_codex":0.00004185658,"about_ca_system_score_gemma":0.0000049355094,"threshold_uncertainty_score":0.53966856},"labels":[],"label_agreement":null},{"id":"W2085584328","doi":"10.1145/1185373.1185382","title":"Jitter-free probability bounds for video streaming over random VBR channel","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Toronto","funders":"","keywords":"Jitter; Computer science; Channel (broadcasting); Computer network; Variable bitrate; Video streaming; Real-time computing; Telecommunications; Bit rate","score_opus":0.006172162600275326,"score_gpt":0.19812872703878012,"score_spread":0.19195656443850478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085584328","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":[0.04799549,0.00013176801,0.94616926,0.000044958033,0.0002674168,0.0006068244,0.000016302545,0.0006282401,0.0041397335],"genre_scores_gemma":[0.93420196,0.000010185078,0.06441267,0.00005191792,0.00043222887,0.00021443753,0.00006977674,0.00006999298,0.0005368121],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991253,0.000009945777,0.000247903,0.00020757501,0.00010470804,0.0003045599],"domain_scores_gemma":[0.99943316,0.00012021241,0.000032155524,0.00033198565,0.0000456494,0.000036862315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010737647,0.00016698775,0.0001874925,0.00004415152,0.00007245876,0.00004056889,0.00012860182,0.00006673929,0.000043588087],"category_scores_gemma":[0.000038385147,0.00016372361,0.00006976671,0.00013735396,0.00002500191,0.00025408427,0.000029571544,0.00006846549,0.0000035562136],"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":[0.000034060162,0.000020956493,0.00026072058,0.00006272088,0.000012000295,4.838546e-7,0.00002084857,0.9910797,0.00028780143,0.0010201802,0.005891124,0.0013094097],"study_design_scores_gemma":[0.0026882635,0.000019446336,0.00069124653,0.000023088536,0.000014125242,0.0000012751167,0.000008605845,0.9716243,0.0019618683,0.019678097,0.0030346708,0.0002549673],"about_ca_topic_score_codex":0.00002559149,"about_ca_topic_score_gemma":0.00015893955,"teacher_disagreement_score":0.8862065,"about_ca_system_score_codex":0.00010231873,"about_ca_system_score_gemma":0.000007373539,"threshold_uncertainty_score":0.6676455},"labels":[],"label_agreement":null},{"id":"W2086023880","doi":"10.1109/qest.2012.35","title":"Decoupled Speed Scaling: Analysis and Evaluation","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"","keywords":"Scaling; Scheduling (production processes); Computer science; Robustness (evolution); Speedup; Parallel computing; Control theory (sociology); Distributed computing; Mathematical optimization; Mathematics; Geometry","score_opus":0.013650438054303835,"score_gpt":0.25916381005775085,"score_spread":0.24551337200344703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086023880","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":[0.4863547,0.00046145977,0.5099077,0.0000059541385,0.00007296519,0.000074607764,3.2210514e-7,0.0001428951,0.0029793652],"genre_scores_gemma":[0.97843564,0.00007551739,0.021331692,0.000009972288,0.00007163133,0.0000038053838,0.000024480009,0.000011150438,0.00003609319],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960583,0.000010516103,0.00009275605,0.000058875074,0.00010302213,0.00012896814],"domain_scores_gemma":[0.999794,0.000024999257,0.0000120573195,0.00008445797,0.000031042542,0.000053439042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001794863,0.000058703274,0.00008346711,0.00009652415,0.000022042455,0.000011227779,0.000019621162,0.000031776726,0.0002296641],"category_scores_gemma":[0.000013673862,0.000057327114,0.000020074573,0.0004046879,0.0000066631424,0.00019718138,0.0000071117465,0.000028725732,0.000010938155],"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":[8.179859e-7,0.000003500037,0.017328776,0.000002886284,0.00007379092,2.2596229e-8,0.000050032773,0.96833885,0.00027833096,0.00009268555,0.00003673383,0.013793585],"study_design_scores_gemma":[0.00011266144,0.0000012075642,0.031239156,0.0000013413307,0.00020148305,3.3497267e-7,0.00001579783,0.96740943,0.0008368393,0.000037472855,0.00007270464,0.00007155062],"about_ca_topic_score_codex":0.0000024599574,"about_ca_topic_score_gemma":0.000010143257,"teacher_disagreement_score":0.49208096,"about_ca_system_score_codex":0.000033660664,"about_ca_system_score_gemma":0.0000016385519,"threshold_uncertainty_score":0.2514661},"labels":[],"label_agreement":null},{"id":"W2086608915","doi":"10.1109/iccnc.2012.6167508","title":"Modeling of packet dropout for UAV wireless communications","year":2012,"lang":"en","type":"article","venue":"2012 International Conference on Computing, Networking and Communications (ICNC)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Defence Research and Development Canada; Communications Research Centre Canada; Innovation, Science and Economic Development Canada","funders":"","keywords":"Dropout (neural networks); Network packet; Computer science; Fading; Markov process; Channel (broadcasting); Markov model; Wireless; Markov chain; Computer network; Hidden Markov model; Real-time computing; Telecommunications; Artificial intelligence; Machine learning; Mathematics","score_opus":0.0809714249141146,"score_gpt":0.3159724799125385,"score_spread":0.2350010549984239,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086608915","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":[0.017411916,0.004415974,0.94891244,0.0007732658,0.0012017923,0.0005209368,0.000048537593,0.00038431853,0.026330834],"genre_scores_gemma":[0.95214254,0.0049351766,0.04206608,0.000056764005,0.00032513108,0.000060383387,0.0002968411,0.000048613474,0.00006846626],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867064,0.00009527104,0.0005276405,0.00017419604,0.00018705474,0.00034518394],"domain_scores_gemma":[0.9977569,0.00038501248,0.00018421478,0.0012454771,0.00032362918,0.000104777915],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040150594,0.00022548815,0.00026738326,0.00015440122,0.00033593934,0.00006576806,0.001241722,0.00011423385,0.000016549184],"category_scores_gemma":[0.00002336814,0.0002547705,0.0000755853,0.00019073793,0.00017897149,0.00029494902,0.00042733052,0.00033646484,0.0000064885635],"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":[0.00003131378,0.0002382037,0.0021218795,0.000052305346,0.00019961872,7.39003e-8,0.0012931124,0.54730076,0.00022586303,0.3532049,0.00082487805,0.09450712],"study_design_scores_gemma":[0.0003122299,0.00002226224,0.0000984353,0.00027007714,0.000026068079,0.0000038767434,0.00020204944,0.99061185,0.000027756147,0.0015088104,0.006674617,0.00024195712],"about_ca_topic_score_codex":0.0000140157235,"about_ca_topic_score_gemma":0.00002937035,"teacher_disagreement_score":0.93473065,"about_ca_system_score_codex":0.00008312486,"about_ca_system_score_gemma":0.000024728179,"threshold_uncertainty_score":0.99999046},"labels":[],"label_agreement":null},{"id":"W2088099099","doi":"10.1109/pimrc.2011.6139815","title":"Cross-layer dynamic subcarrier allocation in multiuser OFDM system with MAC layer diverse QoS constraints","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Subcarrier; Computer science; Physical layer; Quality of service; Orthogonal frequency-division multiplexing; PHY; Computer network; Channel state information; Channel (broadcasting); Real-time computing; Wireless; Telecommunications","score_opus":0.015496231805392542,"score_gpt":0.2282266986703104,"score_spread":0.21273046686491787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088099099","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":[0.466834,0.000030261552,0.5220473,0.000003024805,0.00029303663,0.00039312014,0.000008879928,0.0005187622,0.009871586],"genre_scores_gemma":[0.9833064,0.000015508456,0.016171262,0.000016580621,0.000027826696,0.000049452057,0.000025617821,0.00005964481,0.00032769778],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990379,0.00002090372,0.0002605121,0.00024151028,0.00014275231,0.00029638867],"domain_scores_gemma":[0.9995191,0.00002026963,0.00004506525,0.0002566434,0.000085177584,0.00007372367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000085337175,0.00020024311,0.00017787138,0.00010890558,0.000041315267,0.00002364952,0.00011598217,0.00011939919,0.0003225319],"category_scores_gemma":[0.000006051722,0.0001817429,0.000024744182,0.00024990196,0.00008400979,0.00038899345,0.000023952496,0.00014094818,0.00007967814],"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":[0.00004555203,0.0000232109,0.033279646,0.000082433304,0.000035449462,0.00002747115,0.0006449412,0.96181947,0.0009462934,0.0010634444,0.000030250076,0.0020018597],"study_design_scores_gemma":[0.0011443584,0.000022358534,0.02617638,0.00010089686,0.000013627305,0.000013441136,0.00065069593,0.96883637,0.0026580384,0.000006352725,0.00003919051,0.0003382867],"about_ca_topic_score_codex":0.00007958096,"about_ca_topic_score_gemma":0.0005100692,"teacher_disagreement_score":0.5164724,"about_ca_system_score_codex":0.00022091436,"about_ca_system_score_gemma":0.000015601581,"threshold_uncertainty_score":0.74112606},"labels":[],"label_agreement":null},{"id":"W2088356983","doi":"10.1002/wcm.792","title":"Performance modeling of QoS in a multicode multicarrier CDMA wireless network with fading","year":2009,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Toronto Metropolitan University","funders":"","keywords":"Computer science; Real-time computing; Network packet; Computer network; Fading; Quality of service; Queue; Code division multiple access; Cellular network","score_opus":0.01147312085419989,"score_gpt":0.23266975471747472,"score_spread":0.22119663386327484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088356983","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":[0.77643615,0.0009476641,0.22166294,0.000013711484,0.000051819585,0.0003267828,0.0000015901669,0.00015371124,0.00040565265],"genre_scores_gemma":[0.94043946,0.001988302,0.05739633,0.000015957603,0.00006487028,0.00003502201,0.000019117997,0.0000383813,0.000002529605],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875844,0.000052638916,0.00049346656,0.00021154762,0.00011908735,0.0003648074],"domain_scores_gemma":[0.998862,0.0001567363,0.00010343645,0.0007174065,0.00009188707,0.00006851227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020320971,0.00021504449,0.00035130867,0.00011744074,0.00022027724,0.000027975462,0.00037286055,0.000087468594,0.0000010883983],"category_scores_gemma":[0.000004805512,0.00022262624,0.000028995635,0.00050461636,0.000091043294,0.00021377266,0.00012776525,0.00032801193,4.958933e-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":[0.0000105729505,0.000037820377,0.0034694755,0.00004330604,0.00001228666,5.926436e-7,0.0009629606,0.8992243,0.0004176836,0.00028825496,0.0000017274698,0.095531054],"study_design_scores_gemma":[0.00055584154,0.00005792466,0.0008565847,0.0006401654,0.000012846728,0.0000060630414,0.00027593045,0.9971774,0.00011395445,0.000013646436,0.000042155927,0.00024747432],"about_ca_topic_score_codex":0.000013215556,"about_ca_topic_score_gemma":0.000029216531,"teacher_disagreement_score":0.1642666,"about_ca_system_score_codex":0.00006370661,"about_ca_system_score_gemma":0.00001738481,"threshold_uncertainty_score":0.9078435},"labels":[],"label_agreement":null},{"id":"W2088863311","doi":"10.1145/2810362.2810366","title":"SLA","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Ottawa","funders":"","keywords":"Computer science; Computer network; Broadcasting (networking); Frame (networking); Vehicular ad hoc network; Scheduling (production processes); Resource allocation; Real-time computing; Distributed computing; Wireless; Wireless ad hoc network; Telecommunications","score_opus":0.015497740859150068,"score_gpt":0.19217306458167868,"score_spread":0.17667532372252862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088863311","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":[0.0033386275,0.000092171285,0.82530165,0.000014223971,0.00017420188,0.00002128944,1.2615247e-7,0.000501206,0.17055649],"genre_scores_gemma":[0.9543074,0.000014861588,0.044691566,0.000026210715,0.00006734625,0.0000028798788,0.0000029939722,0.000013021377,0.000873734],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998563,0.0000013286162,0.000031881704,0.000025245987,0.000031635525,0.000053642834],"domain_scores_gemma":[0.999901,0.0000033693398,0.0000018887647,0.00004987366,0.0000106396255,0.00003320303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000140819175,0.000025694257,0.000024234725,0.000010017566,0.0000035848263,0.0000036562817,0.000021482872,0.00001321602,0.000026499934],"category_scores_gemma":[0.0000034987036,0.00002453872,0.000004196427,0.000054135526,0.0000028080992,0.000059162223,0.0000039268944,0.000018593717,0.000103363454],"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":[2.8404054e-7,6.6179524e-7,0.00005251973,7.338091e-7,0.0000010784781,3.5515072e-7,0.000018471846,0.9845827,0.000027735832,0.000973264,0.01054189,0.003800312],"study_design_scores_gemma":[0.00009292394,0.0000033562799,0.00002827437,0.0000012735653,6.927484e-7,0.0000010347378,0.000017180146,0.97622067,0.00076815963,0.000574663,0.02223983,0.000051944055],"about_ca_topic_score_codex":4.187266e-7,"about_ca_topic_score_gemma":0.0000013609219,"teacher_disagreement_score":0.95096874,"about_ca_system_score_codex":0.000015844038,"about_ca_system_score_gemma":0.0000018109067,"threshold_uncertainty_score":0.13285626},"labels":[],"label_agreement":null},{"id":"W2089968732","doi":"10.5555/1554126.1554144","title":"Multi-objective scheduling for MUD based ad-hoc networks","year":2008,"lang":"en","type":"article","venue":"International Wireless Internet Conference","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Maximum throughput scheduling; Scheduling (production processes); Quality of service; Distributed computing; Round-robin scheduling; Computer network; Proportionally fair; Fair-share scheduling; Dynamic priority scheduling; Throughput; Job shop scheduling; Queueing theory; Wireless ad hoc network; Mathematical optimization; Wireless","score_opus":0.027000867468768425,"score_gpt":0.25632305810232525,"score_spread":0.22932219063355683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089968732","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":[0.059630632,0.00040930227,0.93641055,0.0000633234,0.0017883638,0.00036544388,0.000038171558,0.00049891893,0.0007953103],"genre_scores_gemma":[0.91080004,0.0004945322,0.08714425,0.00012722614,0.00025164842,0.00022896154,0.000190828,0.00008473702,0.0006777719],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984734,0.00002580127,0.0004375382,0.00041893646,0.0002593427,0.0003849657],"domain_scores_gemma":[0.99883157,0.00021785274,0.00011981718,0.00022859278,0.00049425126,0.000107909145],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009282894,0.00032308663,0.00028484617,0.00016791048,0.00007959193,0.00006773059,0.0005494138,0.0001726843,0.00017773359],"category_scores_gemma":[0.00007038888,0.00036333108,0.00012870698,0.00015266157,0.00011892613,0.00034170784,0.00006445513,0.00031172961,0.00003162975],"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":[0.000102340106,0.000055049706,0.0006497787,0.000019122966,0.00010505234,0.000013711043,0.00024051145,0.98160636,0.00073302153,0.0009730957,0.00039307366,0.015108852],"study_design_scores_gemma":[0.001146458,0.000045766305,0.00062145106,0.00016752291,0.000010539504,0.000015752865,0.000039303086,0.9910189,0.0033186516,0.0000672523,0.0031661335,0.00038228187],"about_ca_topic_score_codex":0.000005902185,"about_ca_topic_score_gemma":0.00005262111,"teacher_disagreement_score":0.8511694,"about_ca_system_score_codex":0.00025252582,"about_ca_system_score_gemma":0.000057630197,"threshold_uncertainty_score":0.99988186},"labels":[],"label_agreement":null},{"id":"W2090481002","doi":"10.1109/ccp.2011.26","title":"QoS Performance Testing of Multimedia Delivery over WiMAX Networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Algonquin College; Eion (Canada)","funders":"","keywords":"WiMAX; IPTV; Computer science; Multimedia; Quality of service; Computer network; Wireless; Variety (cybernetics); IP Multimedia Subsystem; Focus (optics); Telecommunications","score_opus":0.017595892738932164,"score_gpt":0.17862616874942724,"score_spread":0.16103027601049508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090481002","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":[0.45565778,0.00021870724,0.5218566,4.299685e-7,0.0003998233,0.00012803939,9.863784e-7,0.00043680973,0.021300845],"genre_scores_gemma":[0.8350026,0.00012831557,0.1646653,0.000010682695,0.000103723636,0.000006432577,0.0000039924653,0.000029147437,0.00004981312],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999431,0.0000052588252,0.00019701559,0.00009594,0.00007446304,0.0001962877],"domain_scores_gemma":[0.99966437,0.000057642545,0.00003830426,0.00014669319,0.000052253286,0.000040724863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004485201,0.00010841955,0.00011861078,0.00004217682,0.000023454979,0.0000031807936,0.000087350956,0.000062354055,0.00015318903],"category_scores_gemma":[0.000013939419,0.000108175875,0.00002031789,0.00022046089,0.00002746987,0.00023735438,0.000025074969,0.00009902153,0.000010046529],"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":[0.0000052872456,0.000008078717,0.017085878,0.000021107251,0.000009868516,7.8448267e-7,0.000084353254,0.9470951,0.0002756172,0.000015565874,0.00018363351,0.035214752],"study_design_scores_gemma":[0.00015952834,0.000018940087,0.016554799,0.000038988946,0.000006570815,0.0000013082616,0.000009128108,0.97980964,0.0032284423,0.0000051568345,0.000043981665,0.00012352492],"about_ca_topic_score_codex":0.000012382462,"about_ca_topic_score_gemma":0.0000041784206,"teacher_disagreement_score":0.37934482,"about_ca_system_score_codex":0.000022570592,"about_ca_system_score_gemma":0.000004747588,"threshold_uncertainty_score":0.4411284},"labels":[],"label_agreement":null},{"id":"W2091064324","doi":"10.1109/rws.2012.6175334","title":"An intelligent high availability AMC design","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Polytechnique Montréal","funders":"","keywords":"Fading; Channel state information; Computer science; Channel (broadcasting); Link adaptation; Coding (social sciences); Degradation (telecommunications); Electronic engineering; Wireless; Computer network; Telecommunications; Mathematics; Engineering; Statistics","score_opus":0.018969763337515287,"score_gpt":0.2327749069777644,"score_spread":0.2138051436402491,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091064324","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":[0.026951617,0.00013964224,0.970503,0.0000054710576,0.00032405867,0.0001277216,6.3079466e-7,0.0006044179,0.0013434609],"genre_scores_gemma":[0.8306158,0.000049384853,0.16905685,0.000021127602,0.00013469582,0.000012006345,0.000008107637,0.000023599896,0.000078409365],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994607,0.000027143396,0.00012694189,0.00008537263,0.000067108565,0.00023275691],"domain_scores_gemma":[0.99959356,0.00003924916,0.00001017595,0.00023100134,0.000019888521,0.00010610563],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013821425,0.00009195586,0.00007941369,0.000024045563,0.000024120316,0.000010672984,0.00007356286,0.000047926504,0.00057133666],"category_scores_gemma":[0.0000092250075,0.00008714314,0.000014160463,0.000106259526,0.00001422856,0.00036984487,0.000008986807,0.00006431216,0.00017740008],"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":[0.0000027732958,0.000026763533,0.0009932827,0.0000057418483,0.0000048406155,1.04550445e-7,0.00008332065,0.98336905,0.00054077466,0.0011828109,0.0005460025,0.0132445535],"study_design_scores_gemma":[0.000077929595,0.000025186091,0.0021066528,0.0000041593707,0.0000065550757,0.0000012830164,0.00003264497,0.9593148,0.036072917,0.0004833086,0.0016567573,0.00021777146],"about_ca_topic_score_codex":0.0000038749336,"about_ca_topic_score_gemma":0.0000021249564,"teacher_disagreement_score":0.8036642,"about_ca_system_score_codex":0.000071758426,"about_ca_system_score_gemma":0.0000028156892,"threshold_uncertainty_score":0.6255736},"labels":[],"label_agreement":null},{"id":"W2091359857","doi":"10.1109/twc.2013.110813.120268","title":"One Bit Feedback for CDF-Based Scheduling with Resource Sharing Constraints","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Computer science; Scheduling (production processes); Overhead (engineering); Fading; Logarithm; Throughput; Computer network; Base station; Wireless; Channel (broadcasting); Mathematical optimization; Telecommunications; Mathematics","score_opus":0.02509734798293482,"score_gpt":0.2380890432854836,"score_spread":0.2129916953025488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091359857","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":[0.015978564,0.00009266647,0.980211,0.0005802384,0.00008457478,0.0010612918,0.00005268925,0.0008455189,0.0010934316],"genre_scores_gemma":[0.8281831,0.00012569773,0.1701596,0.000104795654,0.000024682513,0.0011466596,0.000065776985,0.00011522057,0.000074453426],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986772,0.000042046035,0.0003975974,0.0002993562,0.000183361,0.00040045442],"domain_scores_gemma":[0.997552,0.0004590971,0.00008614391,0.0015642936,0.0001949032,0.000143585],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000105241816,0.0002731735,0.00027695217,0.000226646,0.0005829299,0.000108801156,0.0007243861,0.00014417806,0.00009226108],"category_scores_gemma":[0.000004609842,0.00031461034,0.00009700823,0.0005446211,0.0002972918,0.00034926448,0.000004642428,0.0004876074,0.000063054555],"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":[0.000019034605,0.00014677884,0.000013787952,0.000051243314,0.0000820908,1.2441485e-7,0.00010639683,0.95367795,0.002012242,0.0004124106,0.00003361885,0.04344431],"study_design_scores_gemma":[0.0010192151,0.000062504434,0.00004901367,0.00030217657,0.000061394254,0.0000024418032,0.00016113221,0.9876566,0.009779285,0.0001163512,0.00040127843,0.00038858718],"about_ca_topic_score_codex":0.000017128685,"about_ca_topic_score_gemma":0.00009528734,"teacher_disagreement_score":0.81220454,"about_ca_system_score_codex":0.00017087338,"about_ca_system_score_gemma":0.00004273749,"threshold_uncertainty_score":0.9999306},"labels":[],"label_agreement":null},{"id":"W2091736188","doi":"10.1109/wcnc.2013.6554629","title":"Online QoS-based dynamic scheduling in multi-channel wireless networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Fading; Scheduling (production processes); Dynamic priority scheduling; Quality of service; Fair-share scheduling; A priori and a posteriori; Wireless; Online algorithm; Wireless network; Mathematical optimization; Computer network; Round-robin scheduling; Channel (broadcasting); Distributed computing; Algorithm; Mathematics; Telecommunications","score_opus":0.01041597917955668,"score_gpt":0.2296367044818109,"score_spread":0.21922072530225423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091736188","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":[0.15899217,0.0002835288,0.8394395,0.00004677304,0.0003197457,0.0002850816,0.0000018509477,0.0005465347,0.00008477273],"genre_scores_gemma":[0.9063534,0.00013410015,0.09302742,0.00009888205,0.00007189511,0.00006022811,0.000099527264,0.000079086385,0.00007546913],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998944,0.000018089067,0.00031105996,0.00021801001,0.0000947725,0.0004140985],"domain_scores_gemma":[0.9995486,0.00006256245,0.00003288822,0.00022145236,0.000050216015,0.000084257954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053814147,0.0002144385,0.00021121325,0.00014043551,0.000033768454,0.00003175616,0.00013895077,0.00014992626,0.000100487974],"category_scores_gemma":[0.000010343241,0.00022468649,0.000038841066,0.00041847533,0.000023482957,0.0002653774,0.000024329698,0.00028173858,0.00003861635],"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":[0.0000022269219,0.000059177815,0.0002871579,0.00001893015,0.000006319363,0.0000024250012,0.000017420598,0.99464333,0.00015077637,0.000014368307,0.000037707778,0.0047601555],"study_design_scores_gemma":[0.0007019121,0.000008491522,0.0019542265,0.00007324833,0.000003006983,6.931165e-7,0.00006755746,0.9968081,0.000087231594,0.000023275921,0.000007878418,0.0002643699],"about_ca_topic_score_codex":0.000035306588,"about_ca_topic_score_gemma":0.00038906126,"teacher_disagreement_score":0.74736124,"about_ca_system_score_codex":0.00010875389,"about_ca_system_score_gemma":0.000009898155,"threshold_uncertainty_score":0.9162449},"labels":[],"label_agreement":null},{"id":"W2091815602","doi":"10.1109/glocomw.2013.6825052","title":"Resource allocation for network-integrated device-to-device communications using smart relays","year":2013,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Relay; Resource allocation; Computer science; Computer network; Spectral efficiency; Throughput; Quality of service; Cellular network; Distributed computing; Power (physics); Wireless; Telecommunications","score_opus":0.04602963647799984,"score_gpt":0.283895175454664,"score_spread":0.23786553897666413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091815602","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":[0.0027943153,0.0012948468,0.98545754,0.0003207975,0.0006646764,0.003161705,0.000032134987,0.0012395985,0.0050343797],"genre_scores_gemma":[0.11183881,0.00049690093,0.8815997,0.0004287064,0.0005787499,0.0016654155,0.0024749702,0.0003080385,0.0006087036],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979263,0.00010480043,0.0007332895,0.00043056018,0.0001808805,0.00062420155],"domain_scores_gemma":[0.997009,0.00033727442,0.00019832456,0.0018448168,0.00040484365,0.000205758],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003585213,0.0004933308,0.00048576522,0.00018100423,0.0002432183,0.00013729846,0.00086928025,0.000531792,0.00003786464],"category_scores_gemma":[0.000090822454,0.00055312185,0.00012883241,0.00055867183,0.000040981104,0.00024123791,0.0006153493,0.0007333643,0.00005891043],"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":[0.00000755397,0.000018493298,0.00009397362,0.00013958068,0.00008917762,7.748658e-8,0.00014686282,0.97999513,0.00010959517,0.0014877572,0.014408353,0.003503422],"study_design_scores_gemma":[0.00015117318,0.0000099376275,0.000050565824,0.00044689872,0.0000798099,0.0000016497853,0.0000805326,0.8963948,0.00010217793,0.00034622455,0.101811625,0.00052464096],"about_ca_topic_score_codex":0.000117814685,"about_ca_topic_score_gemma":0.00018613975,"teacher_disagreement_score":0.1090445,"about_ca_system_score_codex":0.00057169085,"about_ca_system_score_gemma":0.00006947296,"threshold_uncertainty_score":0.999692},"labels":[],"label_agreement":null},{"id":"W2092420525","doi":"10.1007/s11235-006-5522-1","title":"A Sequential Algorithm for Constructing Delay-Constrained Multirings for Multipoint-to-Multipoint Communications","year":2006,"lang":"en","type":"article","venue":"Telecommunication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Polytechnique Montréal","funders":"","keywords":"Computer science; Multicast; Scalability; Convergence (economics); Network packet; Topology (electrical circuits); Reliability (semiconductor); Algorithm; Distributed computing; Set (abstract data type); Relaxation (psychology); Network topology; Ring (chemistry); Computer network; Mathematics","score_opus":0.022023687839889238,"score_gpt":0.268245008322115,"score_spread":0.24622132048222578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092420525","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":[0.0028240352,0.0007959882,0.98976964,0.0001447933,0.00044114835,0.004164762,0.00023427902,0.0009861209,0.00063921744],"genre_scores_gemma":[0.44542196,0.00004994615,0.55108964,0.000020574402,0.00017332993,0.0024842834,0.0006029523,0.00009201619,0.00006529569],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979506,0.000104688625,0.0010010805,0.00030688703,0.00014974774,0.00048700452],"domain_scores_gemma":[0.9967143,0.0008533836,0.00027175326,0.0015774182,0.00047445347,0.00010869627],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005285729,0.0003129119,0.00042455437,0.00021513607,0.00043373575,0.00013473471,0.00088258367,0.00017856206,0.0000036064189],"category_scores_gemma":[0.000098773526,0.00037607487,0.00014422809,0.00035090244,0.00012269242,0.00028555217,0.00014442476,0.00021563515,0.000015651882],"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":[0.000019810032,0.00006921435,0.000080769285,0.00014469912,0.00009401788,2.2410187e-7,0.00039945167,0.8996455,0.008909195,0.004186233,0.0008229549,0.085627906],"study_design_scores_gemma":[0.0015447609,0.00003288727,0.000023550056,0.00012748435,0.000034544028,0.000025051148,0.00047177225,0.97095877,0.0017298913,0.00012030485,0.024525203,0.0004057861],"about_ca_topic_score_codex":0.0001453704,"about_ca_topic_score_gemma":0.00012928569,"teacher_disagreement_score":0.44259793,"about_ca_system_score_codex":0.00032514808,"about_ca_system_score_gemma":0.000039052542,"threshold_uncertainty_score":0.9998691},"labels":[],"label_agreement":null},{"id":"W2092425861","doi":"10.1002/wcm.372","title":"Scheduling with base station diversity and fairness analysis for the downlink of CDMA cellular networks","year":2006,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","keywords":"Computer science; Base station; Scheduling (production processes); Computer network; Maximum throughput scheduling; Telecommunications link; Fading; Network packet; Fairness measure; Cellular network; Code division multiple access; Wireless network; Diversity combining; Wireless; Round-robin scheduling; Channel (broadcasting); Fair-share scheduling; Throughput; Quality of service; Telecommunications; Mathematical optimization; Mathematics","score_opus":0.010386139592191947,"score_gpt":0.21015747015617295,"score_spread":0.199771330563981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092425861","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":[0.39814413,0.0021094684,0.59944487,0.000012941614,0.000011256482,0.00020976897,0.0000059924505,0.00004655354,0.0000150570395],"genre_scores_gemma":[0.95950824,0.0008867488,0.039407253,0.000004874265,0.000024052002,0.000030989995,0.00011980702,0.000015621481,0.0000024351361],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994115,0.0000359546,0.0002187115,0.00013007225,0.00006795809,0.00013577152],"domain_scores_gemma":[0.99878323,0.0005160976,0.00011208972,0.00044888057,0.00011452266,0.000025204832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019124284,0.00011033212,0.00018712692,0.00007732667,0.00089763955,0.00002905623,0.00020119695,0.00004528165,6.437403e-7],"category_scores_gemma":[0.0000030005244,0.000093531795,0.000035341913,0.0004442966,0.0001337872,0.00009472564,0.0003197103,0.00011247098,3.2175716e-8],"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":[0.0000056539598,0.000016313616,0.013922517,0.00003069642,0.00009795995,9.264915e-8,0.00030574808,0.96788704,0.000088363995,0.001324733,0.0000013988632,0.01631949],"study_design_scores_gemma":[0.00027268112,0.000017848695,0.0043337666,0.00003575407,0.00019775722,5.753666e-7,0.00037736795,0.99446726,0.0000940982,0.000045995886,0.000046852798,0.00011006772],"about_ca_topic_score_codex":0.00008457037,"about_ca_topic_score_gemma":0.000128445,"teacher_disagreement_score":0.5613641,"about_ca_system_score_codex":0.000020545947,"about_ca_system_score_gemma":0.0000049492837,"threshold_uncertainty_score":0.69040084},"labels":[],"label_agreement":null},{"id":"W2093207996","doi":"10.1109/wcnc.2014.6952531","title":"Cell outage compensation for irregular cellular networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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":"Base station; Robustness (evolution); Computer science; Cellular network; Cellular radio; Computer network; Distributed computing; Compensation (psychology); Outage probability; Resource allocation; Fading","score_opus":0.004089919642193073,"score_gpt":0.16957262795919806,"score_spread":0.16548270831700498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093207996","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":[0.0034464584,0.00013397067,0.9888202,0.000015101761,0.0003820382,0.0002609014,0.0000011436574,0.000485593,0.006454594],"genre_scores_gemma":[0.9310501,0.000022330732,0.06791079,0.00005328475,0.00027701986,0.00003189619,0.000102255864,0.00005367873,0.00049864076],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941546,0.000012686061,0.0001600264,0.00013162207,0.000066389715,0.00021382989],"domain_scores_gemma":[0.99963635,0.00007249075,0.000026001602,0.00018306744,0.000034432585,0.000047627138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009722607,0.00011992343,0.00012406953,0.00003411215,0.000052134743,0.000022015724,0.000078548255,0.00008090419,0.00003905599],"category_scores_gemma":[0.000006090667,0.00012700733,0.000041347215,0.00009062956,0.000011447642,0.00010935965,0.000010437903,0.000061917766,0.000017456192],"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":[0.0000027356928,0.000005370757,0.000028454584,0.000023746838,0.000004171941,1.0653304e-7,0.000015600073,0.9902972,0.0011083588,0.002412727,0.0019470707,0.0041544824],"study_design_scores_gemma":[0.0003254002,0.000016720718,0.000033770753,0.0000059871945,0.000008736945,1.906836e-7,0.000007984472,0.9807561,0.0057503753,0.00036909047,0.012568005,0.00015761999],"about_ca_topic_score_codex":6.538575e-7,"about_ca_topic_score_gemma":0.000002166837,"teacher_disagreement_score":0.92760366,"about_ca_system_score_codex":0.0000308259,"about_ca_system_score_gemma":0.0000017492378,"threshold_uncertainty_score":0.51792085},"labels":[],"label_agreement":null},{"id":"W2095170270","doi":"10.1109/glocom.2010.5683712","title":"A New Rate Control Technique for cdma2000 1xEV","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"CDMA2000; Base station; Computer science; Transmission (telecommunications); Markov process; Scheme (mathematics); Frame (networking); Real-time computing; Markov chain; Computer network; Mobile telephony; Set (abstract data type); Process (computing); Code division multiple access; Mobile radio; Telecommunications; Mathematics; Statistics","score_opus":0.002798931503326049,"score_gpt":0.19873627791523252,"score_spread":0.19593734641190647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095170270","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":[0.00021953371,0.000019495234,0.99229646,0.00005850896,0.00026454078,0.0005348795,0.0000033551364,0.0005627076,0.0060405],"genre_scores_gemma":[0.46283275,0.000015697622,0.5342205,0.000102974125,0.00031606437,0.00022507366,0.000009821513,0.000056527995,0.002220586],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996087,0.0000033041022,0.00010647593,0.00008882542,0.000030200674,0.00016252678],"domain_scores_gemma":[0.9997058,0.00005855982,0.000012891863,0.00013886305,0.000025080386,0.000058812177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000062435385,0.00008811003,0.00009475205,0.00003242871,0.000023486411,0.000013640315,0.000069030575,0.000082650346,0.00014964823],"category_scores_gemma":[0.000017190663,0.00008519596,0.000028807393,0.00007979375,0.0000066042276,0.000100447316,0.000004093505,0.00010868196,0.00001615534],"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":[0.0000152258235,0.0000042773227,0.000022406419,0.000013782168,0.000013875563,5.19857e-7,0.000012831078,0.8191329,0.1425866,0.007972029,0.011100066,0.019125436],"study_design_scores_gemma":[0.0009197613,0.000021483986,0.00003338927,0.000008036461,0.000010186414,0.0000034629459,0.00000264045,0.8437999,0.09680625,0.0034579805,0.054709863,0.00022705685],"about_ca_topic_score_codex":0.000004277385,"about_ca_topic_score_gemma":0.000035337147,"teacher_disagreement_score":0.4626132,"about_ca_system_score_codex":0.000014013342,"about_ca_system_score_gemma":0.000011786104,"threshold_uncertainty_score":0.34741905},"labels":[],"label_agreement":null},{"id":"W2095362577","doi":"10.1109/itc.2010.5608722","title":"Distributed radio resource allocation for the downlink of multi-cell OFDMA radio systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Université de Montréal","funders":"","keywords":"Telecommunications link; Computer science; Resource allocation; Frequency-division multiple access; Constraint (computer-aided design); Mathematical optimization; Orthogonal frequency-division multiplexing; Power control; Resource management (computing); Convergence (economics); Spectral efficiency; Reuse; Computer network; Power (physics); Mathematics; Channel (broadcasting); Engineering","score_opus":0.008061008649266685,"score_gpt":0.20642114826342398,"score_spread":0.1983601396141573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095362577","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":[0.0073918304,0.000864448,0.99008214,0.00008524433,0.00043783488,0.0006529327,0.000053826316,0.00024466455,0.00018704643],"genre_scores_gemma":[0.98414105,0.00012862937,0.0147785535,0.0000069321122,0.00016917042,0.0001464187,0.0001773177,0.000042368472,0.00040957762],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993375,0.00001292846,0.00026222767,0.00012154335,0.000094718336,0.00017107585],"domain_scores_gemma":[0.99926513,0.00023303868,0.00007114076,0.00030638935,0.000085162785,0.00003912787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014810028,0.000119209944,0.00014842908,0.0000317721,0.0000625381,0.000019748344,0.0001766891,0.00010402032,0.000013718633],"category_scores_gemma":[0.000034309458,0.000089920344,0.000047157235,0.00016807274,0.000033735436,0.00008274064,0.000012765836,0.00014109543,0.0000028120228],"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":[0.000007795377,0.000019038194,0.000058350644,0.00007421653,0.000021315158,7.7448426e-8,0.000056949277,0.98249316,0.01286539,0.00063761446,0.0013626007,0.0024034758],"study_design_scores_gemma":[0.0005619638,0.000009393708,0.00014196623,0.000013932148,0.000023530307,0.000001314506,0.000074203715,0.97260934,0.008240323,0.0000036830472,0.018212184,0.000108188564],"about_ca_topic_score_codex":0.000011602214,"about_ca_topic_score_gemma":0.000018731665,"teacher_disagreement_score":0.9767492,"about_ca_system_score_codex":0.000030316049,"about_ca_system_score_gemma":0.000008506305,"threshold_uncertainty_score":0.36668453},"labels":[],"label_agreement":null},{"id":"W2095476597","doi":"10.1109/mascot.2009.5366777","title":"Service differentiation in multi-rate HSDPA systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Quality of service; Computer network; Scheduling (production processes); Telecommunications link; Network packet; Differentiated services; Distributed computing; Engineering","score_opus":0.011810571946881067,"score_gpt":0.21403490673550205,"score_spread":0.20222433478862098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095476597","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":[0.13740388,0.00014994496,0.86052746,0.000046666184,0.00023285717,0.00017764329,8.345498e-7,0.00041870758,0.0010420072],"genre_scores_gemma":[0.99551415,0.0000604173,0.004185272,0.000060764043,0.000032783748,0.00000896968,0.000023123494,0.000013825249,0.00010067852],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995651,0.000014393542,0.00015006326,0.00008732929,0.00004725826,0.00013581052],"domain_scores_gemma":[0.99982417,0.0000122775045,0.000015688056,0.00009977058,0.000023536886,0.00002454488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037382197,0.00008312471,0.0000902693,0.000059145637,0.000013139811,0.000020283576,0.00004956895,0.000049662445,0.000010719436],"category_scores_gemma":[0.0000035350004,0.00008379672,0.000008978869,0.00025046518,0.0000014132914,0.00016909925,0.000004134428,0.00006222598,0.000027540918],"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":[0.0000014396578,0.000010976198,0.00029227085,0.000015466872,0.0000019476433,7.152671e-7,0.000058897975,0.9964346,0.001578074,0.00027702298,0.000047871068,0.0012806952],"study_design_scores_gemma":[0.0002701125,0.000004364,0.018606536,0.000024717825,0.0000016810542,4.6113502e-7,0.000031009433,0.9805318,0.00034556593,0.000030196008,0.000057013644,0.000096515716],"about_ca_topic_score_codex":0.0000156887,"about_ca_topic_score_gemma":0.00011812812,"teacher_disagreement_score":0.8581103,"about_ca_system_score_codex":0.000058201244,"about_ca_system_score_gemma":0.00000185909,"threshold_uncertainty_score":0.34171313},"labels":[],"label_agreement":null},{"id":"W2095551006","doi":"10.1504/ijmc.2013.050996","title":"Robust scheduling algorithm for guaranteed bit rate services","year":2012,"lang":"en","type":"article","venue":"International Journal of Mobile Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":6,"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 Essex; McGill University","keywords":"Computer science; Retransmission; Computer network; Network packet; Quality of service; Algorithm; Scheduling (production processes); Hybrid automatic repeat request; Channel (broadcasting); Telecommunications link; Real-time computing","score_opus":0.02565131102087545,"score_gpt":0.2849189617638436,"score_spread":0.2592676507429682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095551006","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":[0.013235391,0.0060562855,0.9784239,0.00018958021,0.0014041663,0.00020168984,0.000042450232,0.00007770467,0.0003688475],"genre_scores_gemma":[0.6302728,0.0021444925,0.36684275,0.000075742806,0.00050381717,0.000054831027,0.000054987417,0.0000316831,0.000018864259],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991035,0.00004001374,0.0004769371,0.000049723076,0.00016548383,0.00016435304],"domain_scores_gemma":[0.9985425,0.00027600993,0.00023747534,0.0003209501,0.0005529736,0.00007007765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037573918,0.00010670799,0.00015077645,0.00016903078,0.00008311993,0.000048578935,0.0010078329,0.00005419125,0.000023132585],"category_scores_gemma":[0.000026038959,0.000109412314,0.00010015317,0.00012509394,0.000037249003,0.00062683335,0.000093910865,0.00020036122,0.000008859275],"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":[0.000010231314,0.00009748475,0.00034182848,0.000011804876,0.0002008179,4.9827185e-7,0.0006089396,0.9437573,0.0009899541,0.00053414505,0.00014961728,0.05329739],"study_design_scores_gemma":[0.0005548843,0.000022219861,0.00015943234,0.00012007003,0.000031782525,0.000044696877,0.00032364056,0.9651684,0.00084962463,0.000198014,0.032402243,0.00012496751],"about_ca_topic_score_codex":0.0000019848133,"about_ca_topic_score_gemma":0.0000039461775,"teacher_disagreement_score":0.6170374,"about_ca_system_score_codex":0.00011973421,"about_ca_system_score_gemma":0.000018788685,"threshold_uncertainty_score":0.44617048},"labels":[],"label_agreement":null},{"id":"W2095586187","doi":"10.1109/icwmc.2007.59","title":"On Improving the Performance of MI-MAC over Next Generation Wireless Cellular Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Telecommunications link; Computer network; Handover; Scheduling (production processes); Channel (broadcasting); Wireless network; Wireless; Protocol (science); Access control; Cellular network; Telecommunications; Engineering","score_opus":0.00904162229644287,"score_gpt":0.1914352665025945,"score_spread":0.18239364420615162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095586187","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":[0.513501,0.00012582989,0.4853539,0.0000028460051,0.0002304731,0.00008385006,2.1463491e-7,0.000074297546,0.0006276308],"genre_scores_gemma":[0.99696285,0.00015034582,0.002357912,0.000059260543,0.00031759645,0.0000059185422,0.000015823782,0.00003723983,0.00009302946],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925077,0.000010347713,0.0002422659,0.00011986101,0.00014323618,0.00023353662],"domain_scores_gemma":[0.99957305,0.0000760222,0.000054328677,0.00022937222,0.00003524335,0.000031983636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001980623,0.00012477655,0.00010263634,0.000044497436,0.00007726479,0.000019242743,0.000107833424,0.00008231437,0.00005401949],"category_scores_gemma":[0.000004845289,0.00009868344,0.000032454755,0.00021723977,0.000027271086,0.00020257024,0.000018094666,0.00015312426,0.00000454213],"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":[0.000008795732,0.000006433323,0.00012817398,0.000014532162,0.0000074951326,5.1270484e-7,0.00003659498,0.927958,0.044259086,0.0007139108,0.00020492439,0.026661528],"study_design_scores_gemma":[0.00012725535,0.0000276406,0.0002427024,0.000014793471,0.0000058257665,5.08279e-7,0.000013041236,0.8988719,0.100529626,0.0000048465945,0.000055916025,0.00010597],"about_ca_topic_score_codex":0.0000056972135,"about_ca_topic_score_gemma":0.00001598963,"teacher_disagreement_score":0.48346192,"about_ca_system_score_codex":0.000051034534,"about_ca_system_score_gemma":0.0000047506937,"threshold_uncertainty_score":0.4024194},"labels":[],"label_agreement":null},{"id":"W2095627734","doi":"10.1109/icc.2006.255692","title":"A Radio Resource Management Framework for IEEE 802.16-Based OFDM/TDD Wireless Mesh Networks","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Computer network; Computer science; Quality of service; Default gateway; Network packet; Wireless mesh network; Admission control; IEEE 802.11s; Queueing theory; IEEE 802; Call Admission Control; Wireless network; Wireless; Telecommunications","score_opus":0.03646006721821619,"score_gpt":0.29306071014194784,"score_spread":0.25660064292373164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095627734","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":[0.0006613589,0.000119568984,0.9515143,0.0012505549,0.0007170444,0.00063805614,0.000116123316,0.00048320484,0.044499792],"genre_scores_gemma":[0.90886885,0.0005373034,0.087294504,0.0002847605,0.0003780625,0.000672852,0.00096375466,0.000090357884,0.00090954144],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983663,0.000074835945,0.0005349841,0.0003224553,0.00033013747,0.00037129846],"domain_scores_gemma":[0.9976915,0.0004738259,0.00017319513,0.0013195225,0.00026492623,0.000077046985],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018020268,0.00030963073,0.00025210378,0.00023604045,0.0002667915,0.00014321071,0.0014759044,0.00019225886,0.000087956105],"category_scores_gemma":[0.000015041035,0.00036521239,0.00012953026,0.0003279838,0.00013727779,0.00017090212,0.00006453499,0.00045135958,0.00003332745],"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":[0.000031670825,0.00010613729,0.00005104341,0.000014609366,0.00006326366,8.804199e-7,0.00001610943,0.66686404,0.000044756594,0.3172211,0.010683556,0.0049028215],"study_design_scores_gemma":[0.0006064614,0.000029508117,0.00012399278,0.00026545997,0.00003385768,0.00000159963,0.000049355465,0.9693298,0.00028184848,0.009616059,0.019296648,0.00036543966],"about_ca_topic_score_codex":0.00002648808,"about_ca_topic_score_gemma":0.00014269301,"teacher_disagreement_score":0.90820754,"about_ca_system_score_codex":0.00039842643,"about_ca_system_score_gemma":0.000030209132,"threshold_uncertainty_score":0.99987996},"labels":[],"label_agreement":null},{"id":"W2095691144","doi":"10.1109/tmc.2006.85","title":"Queue-aware uplink bandwidth allocation and rate control for polling service in IEEE 802.16 broadband wireless networks","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":148,"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 Winnipeg; University of Manitoba","funders":"","keywords":"Polling; Computer network; Computer science; Wireless broadband; Quality of service; Bandwidth allocation; Wireless network; Wireless; Telecommunications","score_opus":0.005773359184752195,"score_gpt":0.2109810775830105,"score_spread":0.2052077183982583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095691144","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":[0.13369143,0.0002790983,0.8641117,0.000031865995,0.0006398769,0.00086176314,0.000012743868,0.00034968453,0.000021788243],"genre_scores_gemma":[0.99603313,0.00014787343,0.0031445322,0.00009062503,0.00025905055,0.0001771815,0.000031492644,0.000095061754,0.000021038037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985331,0.00005287828,0.0004970155,0.0003745673,0.000096574426,0.00044582033],"domain_scores_gemma":[0.99912596,0.00042279527,0.00009224847,0.0001951818,0.00009629167,0.00006750885],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002353854,0.0002959818,0.00033481818,0.00017638037,0.00025370374,0.00007179641,0.0001074706,0.00018708989,0.0000043491755],"category_scores_gemma":[0.0000012247096,0.00035143903,0.000063179665,0.00048449592,0.000026271247,0.00021891599,0.0000011053569,0.00033,0.0000019222603],"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":[0.000050841103,0.000042192845,0.00006895461,0.00009164233,0.000023170704,0.0000010767931,0.000077809884,0.9660026,0.0009952105,0.000026899983,0.000016004395,0.032603633],"study_design_scores_gemma":[0.0018469619,0.000045440862,0.00012770867,0.00021682361,0.00003376689,0.000004467073,0.000044360728,0.9934088,0.0038343184,0.00005847167,0.000045205063,0.00033367463],"about_ca_topic_score_codex":0.00008395866,"about_ca_topic_score_gemma":0.00040117206,"teacher_disagreement_score":0.8623417,"about_ca_system_score_codex":0.00022406691,"about_ca_system_score_gemma":0.000018337052,"threshold_uncertainty_score":0.9998938},"labels":[],"label_agreement":null},{"id":"W2095788754","doi":"","title":"Interference management using basestation coordination in broadband wireless access networks: Research Articles","year":2006,"lang":"en","type":"article","venue":"Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Carleton University; Memorial University of Newfoundland","funders":"","keywords":"Computer science; Computer network; Hybrid automatic repeat request; Wireless broadband; Network packet; Transmission delay; Quality of service; Automatic repeat request; Wireless; Radio Link Protocol; Wireless network; Scheduling (production processes); Packet loss; Real-time computing; Telecommunications; Engineering; Telecommunications link","score_opus":0.05291230586055779,"score_gpt":0.34532268531867455,"score_spread":0.29241037945811676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095788754","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":[0.480784,0.0012878894,0.5168248,0.000016787573,0.00003884982,0.000277984,6.9619006e-7,0.00008511944,0.0006839054],"genre_scores_gemma":[0.98315674,0.0008384942,0.015833614,0.0000053399135,0.00003323135,0.00005431067,0.00004191965,0.000021541202,0.000014798145],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910057,0.00012391337,0.00029338792,0.00015729327,0.00009244135,0.00023242582],"domain_scores_gemma":[0.9991654,0.00024142506,0.00004679137,0.0004202688,0.00009940413,0.00002669557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038333135,0.00009658045,0.00010899673,0.00023709249,0.00021832611,0.00014133294,0.00032388195,0.000042907846,0.0000018687257],"category_scores_gemma":[0.0000055376595,0.00011538114,0.000011946418,0.00075329805,0.000094682175,0.00030647748,0.00036274403,0.0002103692,7.066862e-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":[0.0000021162416,0.000025444966,0.004287292,0.000029212471,0.000003812244,7.198991e-7,0.00011752496,0.88373846,0.00020755973,0.0016082197,0.00004089709,0.10993873],"study_design_scores_gemma":[0.00021602059,0.000009821614,0.004369084,0.00020461109,0.000004509705,0.0000019253011,0.00024522995,0.99397826,0.000080971025,0.00059175154,0.00018584882,0.00011193686],"about_ca_topic_score_codex":0.000081391176,"about_ca_topic_score_gemma":0.000117373434,"teacher_disagreement_score":0.50237274,"about_ca_system_score_codex":0.00013332693,"about_ca_system_score_gemma":0.0000059635745,"threshold_uncertainty_score":0.47051063},"labels":[],"label_agreement":null},{"id":"W2096017667","doi":"10.1109/glocom.2006.610","title":"SPCp1-08: Adaptive Learning of Transmission Control Policies for MIMO Fading Channels under Delay Constraint","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Fading; Markov decision process; Computer science; MIMO; Mathematical optimization; Transmission (telecommunications); Convergence (economics); Markov process; Constraint (computer-aided design); Q-learning; Transmitter; Channel (broadcasting); Power control; Reinforcement learning; Resource allocation; Wireless; Power (physics); Mathematics; Telecommunications; Computer network; Artificial intelligence; Statistics","score_opus":0.00894306168979507,"score_gpt":0.21723389741076962,"score_spread":0.20829083572097457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096017667","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":[0.02174369,0.0005474622,0.9755318,0.00005906375,0.00015595615,0.000337242,0.000025323188,0.00021137862,0.0013880564],"genre_scores_gemma":[0.98489326,0.000043460997,0.014723789,0.000023248234,0.00013445558,0.000022531476,0.00003558671,0.000041561147,0.00008208824],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914753,0.000022754672,0.0002874755,0.00014157391,0.00009857823,0.0003020624],"domain_scores_gemma":[0.9995803,0.00014560136,0.00007459773,0.00008302121,0.00006976541,0.000046699006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008279132,0.00016603485,0.000257712,0.00007466569,0.000082805804,0.000014582153,0.000075875454,0.000098190416,0.000024744948],"category_scores_gemma":[0.000008617758,0.00017460265,0.0000832527,0.0001335551,0.000054551267,0.00010965101,0.0000067368287,0.00011616829,0.000002831653],"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":[0.000030391086,0.000011856152,0.000101545775,0.000033998153,0.000031318392,8.3499646e-7,0.00013443825,0.9867941,0.003304661,0.004962086,0.00019448074,0.0044002775],"study_design_scores_gemma":[0.0011770609,0.000065188484,0.00020529657,0.000093012546,0.000029506406,0.0000052693495,0.00018869665,0.9902669,0.0043673124,0.001400572,0.0019943637,0.00020682934],"about_ca_topic_score_codex":0.000038660553,"about_ca_topic_score_gemma":0.000009642111,"teacher_disagreement_score":0.9631496,"about_ca_system_score_codex":0.00008176102,"about_ca_system_score_gemma":0.000014016196,"threshold_uncertainty_score":0.71200895},"labels":[],"label_agreement":null},{"id":"W2096042046","doi":"10.1109/tvt.2010.2098427","title":"A Distributed Algorithm for Resource Allocation in OFDM Cognitive Radio Systems","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Resource allocation; Cognitive radio; Throughput; Resource management (computing); Resource (disambiguation); Max-min fairness; Mathematical optimization; Distributed computing; Computer network; Wireless; Telecommunications; Mathematics; Channel (broadcasting)","score_opus":0.005097825715908914,"score_gpt":0.2107548618315323,"score_spread":0.2056570361156234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096042046","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":[0.028615564,0.00010994523,0.9688983,0.000113018716,0.00048543725,0.00076593197,0.00011820556,0.0008726049,0.000021008493],"genre_scores_gemma":[0.9850624,0.000050072722,0.01383401,0.000009698823,0.00003973698,0.00083086937,0.00009146812,0.00005766715,0.000024057439],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990788,0.000017831666,0.000263848,0.00025666942,0.00009328528,0.00028954903],"domain_scores_gemma":[0.9994955,0.000094101255,0.0000417325,0.00024153673,0.00008768258,0.000039452527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009465168,0.00017893902,0.00021678304,0.00042756292,0.000087100365,0.00001544218,0.0001312924,0.0004490179,0.0000046340056],"category_scores_gemma":[0.000011761429,0.00020799992,0.000051885938,0.0007391229,0.000083049585,0.000096496515,7.806196e-7,0.0005777676,0.000009138063],"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":[0.000011693614,0.00005765335,0.000004503779,0.000020477597,0.00003753913,0.000004870097,0.000024202913,0.9032426,0.005252514,0.0001886786,0.000026203537,0.09112907],"study_design_scores_gemma":[0.0008819648,0.00006175231,0.000012479507,0.00006255222,0.000029981209,0.000029117306,0.0001350979,0.9592798,0.03741372,0.00010462281,0.001779895,0.00020906383],"about_ca_topic_score_codex":0.0000052434752,"about_ca_topic_score_gemma":0.000053147844,"teacher_disagreement_score":0.9564468,"about_ca_system_score_codex":0.00010462803,"about_ca_system_score_gemma":0.000013997353,"threshold_uncertainty_score":0.84819907},"labels":[],"label_agreement":null},{"id":"W2096299490","doi":"10.1109/tnet.2009.2030326","title":"On Burst Transmission Scheduling in Mobile TV Broadcast Networks","year":2009,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Scheduling (production processes); Computer network; Base station; Testbed; Real-time computing; Schedule","score_opus":0.01001123022695009,"score_gpt":0.23320184627877416,"score_spread":0.22319061605182408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096299490","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":[0.018934352,0.0015423048,0.9757651,0.00006661325,0.0015717311,0.00051907246,0.0000031227503,0.00081296294,0.0007847569],"genre_scores_gemma":[0.9831653,0.0029236344,0.012854553,0.00020258818,0.00057724933,0.0000878898,0.000019382764,0.000116851064,0.000052556126],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997798,0.00006733454,0.00055829907,0.00050241314,0.00029450306,0.0007794402],"domain_scores_gemma":[0.9989145,0.00024968386,0.0000670636,0.0005606494,0.000032622702,0.00017549537],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018798198,0.00045661026,0.00039583276,0.00035705933,0.0002691901,0.00007264409,0.00032123266,0.00032450413,0.00006967752],"category_scores_gemma":[0.0000034783375,0.00051667745,0.00015471033,0.00114648,0.00003331312,0.00028653964,0.0000018254027,0.0010545172,0.000021115788],"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":[0.000060936865,0.000076579105,0.0000072748044,0.000008367096,0.000012408819,0.000011679618,0.00008306987,0.6290365,0.00015744608,0.000018411964,0.0000359,0.37049145],"study_design_scores_gemma":[0.0008284456,0.00020379903,0.00006473953,0.0007134034,0.000023445007,0.000009378156,0.000033100016,0.99387914,0.00074529054,0.00062835315,0.0023567493,0.0005141282],"about_ca_topic_score_codex":0.000003965633,"about_ca_topic_score_gemma":0.00001383531,"teacher_disagreement_score":0.96423095,"about_ca_system_score_codex":0.0003041213,"about_ca_system_score_gemma":0.000015833884,"threshold_uncertainty_score":0.9997285},"labels":[],"label_agreement":null},{"id":"W2096668092","doi":"10.1109/glocom.2006.709","title":"WLC17-1: Performance Analysis of a Reservation Based Connection Admission Scheme in 802.16 Networks","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","funders":"","keywords":"Computer network; Computer science; Quality of service; Reservation; Wireless broadband; IEEE 802; Call Admission Control; Scheme (mathematics); IEEE 802.11e-2005; Broadband networks; Service (business); Revenue; Bandwidth (computing); Admission control; Differentiated services; Wireless network; Wireless; Broadband; Telecommunications; Mathematics","score_opus":0.006523415383979554,"score_gpt":0.20416830415924136,"score_spread":0.19764488877526182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096668092","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":[0.5555498,0.00016369262,0.44335407,0.000018322116,0.0000887754,0.000093874296,0.000002714255,0.00011158062,0.00061718625],"genre_scores_gemma":[0.9919442,0.00007630178,0.0075231153,0.000015898455,0.000059430637,0.000015881395,0.00031486407,0.000019089015,0.00003124397],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915546,0.000025069594,0.0003466502,0.00015139906,0.0001308951,0.00019050449],"domain_scores_gemma":[0.999581,0.00004628749,0.00008389456,0.00019950116,0.000060187063,0.00002913142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013680878,0.000117590884,0.00022624548,0.00033255122,0.000033955912,0.000010178187,0.000075570606,0.00010617174,0.00007408217],"category_scores_gemma":[0.00001740703,0.00013135927,0.000056504174,0.0019579425,0.000013563978,0.00022308106,0.000012499207,0.00011236716,0.0000018275877],"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":[0.000022042283,0.000020691745,0.08135906,0.000023407496,0.000022915892,3.930776e-7,0.0000058068267,0.915617,0.00032918138,0.000052131254,0.00026629496,0.002281098],"study_design_scores_gemma":[0.0003185296,0.000014397092,0.0937604,0.00005021752,0.000039189592,1.4363818e-7,0.000006025456,0.9045495,0.0008077676,0.000023720931,0.0003151645,0.000114941045],"about_ca_topic_score_codex":0.00011694228,"about_ca_topic_score_gemma":0.00057658716,"teacher_disagreement_score":0.4363944,"about_ca_system_score_codex":0.00019783825,"about_ca_system_score_gemma":0.000011280471,"threshold_uncertainty_score":0.53566754},"labels":[],"label_agreement":null},{"id":"W2096740421","doi":"10.1109/bsc.2008.4563201","title":"Optimal linear-time algorithm for uplink scheduling of packets with hard deadlines in WiMAX","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"WiMAX; Telecommunications link; Computer science; Scheduling (production processes); Network packet; Wireless; Mathematical optimization; Distributed computing; Computer network; Mathematics; Telecommunications","score_opus":0.01188179703071227,"score_gpt":0.21582636857224033,"score_spread":0.20394457154152806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096740421","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":[0.16555014,0.00012670619,0.8336961,0.000014918125,0.000042611824,0.00024153243,0.0000053565445,0.00018229068,0.00014033596],"genre_scores_gemma":[0.12917507,0.000109562425,0.87031704,0.000010420472,0.00010006962,0.00003505456,0.000038649738,0.00005652294,0.00015761906],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920833,0.0000055678283,0.0002749368,0.00016586886,0.00009760022,0.00024771024],"domain_scores_gemma":[0.99959874,0.00007082462,0.000041815765,0.00014409143,0.000098753626,0.00004576591],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000061832965,0.00015804496,0.00025393078,0.00009627506,0.00003292138,0.000004304446,0.00008310115,0.000082394276,0.000022054706],"category_scores_gemma":[0.000014643092,0.00014509086,0.000036290792,0.00027096897,0.000041212246,0.00018946442,0.0000140723805,0.000097610675,0.0000067687492],"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":[0.000020217743,0.00001917241,0.00042844084,0.000025640824,0.000017122107,0.000004472579,0.000060354923,0.9899366,0.00055793684,0.000021507056,0.00004024994,0.008868313],"study_design_scores_gemma":[0.00079698744,0.00005998974,0.0002097337,0.00005411911,0.0000068716663,0.000011792716,0.000015604639,0.98941004,0.00917936,0.000013522141,0.00006106986,0.00018092112],"about_ca_topic_score_codex":0.0000026128114,"about_ca_topic_score_gemma":0.000003247878,"teacher_disagreement_score":0.036620922,"about_ca_system_score_codex":0.000034801193,"about_ca_system_score_gemma":0.000021557857,"threshold_uncertainty_score":0.59166336},"labels":[],"label_agreement":null},{"id":"W2096795905","doi":"10.1109/tvt.2012.2189030","title":"BitQoS-Aware Resource Allocation for Multi-User Mixed-Traffic OFDM Systems","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Computer network; Quality of service; Scheduling (production processes); Orthogonal frequency-division multiplexing; Multi-user; Network packet; Throughput; Wireless; Real-time computing; Channel (broadcasting); Engineering","score_opus":0.01393710100106224,"score_gpt":0.23226846435283766,"score_spread":0.21833136335177541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096795905","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":[0.040335786,0.00076851546,0.954814,0.000101706435,0.0011527379,0.00073624885,0.00002707367,0.002047913,0.000015981774],"genre_scores_gemma":[0.98449624,0.00012450287,0.014125144,0.000020003592,0.00010065944,0.0007301675,0.00003162485,0.00011645581,0.00025521588],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987559,0.000029681169,0.0003176354,0.0002575707,0.00013311964,0.0005061181],"domain_scores_gemma":[0.99926436,0.000055654702,0.000058744077,0.00045110594,0.00008860599,0.000081551465],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012323988,0.00025707402,0.00025637524,0.00045909727,0.00017771179,0.000017600682,0.00019142061,0.00052107626,0.000006792392],"category_scores_gemma":[0.0000063319485,0.000283822,0.00009578757,0.0006272742,0.000069221365,0.00020757249,0.0000013328519,0.00035488297,0.000050471357],"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":[0.000008484403,0.00010183663,0.000012025607,0.000069722824,0.00007107529,8.2542135e-7,0.000041766783,0.98251057,0.0024081946,0.00039845268,0.00026050117,0.014116544],"study_design_scores_gemma":[0.0006714532,0.000048827565,0.00001129972,0.000067096036,0.00007191109,0.000025535332,0.0002352584,0.928217,0.041313685,0.000006029995,0.028993765,0.00033814702],"about_ca_topic_score_codex":0.0000018197711,"about_ca_topic_score_gemma":0.0000123834625,"teacher_disagreement_score":0.94416046,"about_ca_system_score_codex":0.00019023882,"about_ca_system_score_gemma":0.000010274894,"threshold_uncertainty_score":0.9999614},"labels":[],"label_agreement":null},{"id":"W2096848398","doi":"10.1109/cnsr.2010.35","title":"Prioritized Access for Emergency Stations in Next Generation Broadband Wireless Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Base station; Computer network; Computer science; Wireless broadband; WiMAX; Mobile broadband; Mobile telephony; IMT Advanced; Wireless network; Mobile station; Broadband; Cellular network; Telecommunications; Interference (communication); Wireless; Mobile radio; Mobile Web; Channel (broadcasting)","score_opus":0.030138464267145126,"score_gpt":0.28399696959300746,"score_spread":0.25385850532586235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096848398","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":[0.2294593,0.00007215231,0.76800734,0.000025265836,0.0011766787,0.00044481538,0.0000044779026,0.00021031284,0.00059968233],"genre_scores_gemma":[0.969781,0.0005222509,0.02849321,0.000019473233,0.0004997414,0.00025035016,0.0001972047,0.000052797393,0.00018399356],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991668,0.000010360476,0.0003155537,0.00017646712,0.000074123505,0.00025669122],"domain_scores_gemma":[0.9996175,0.00004436333,0.000035784768,0.0001677348,0.00008066537,0.000053909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008483971,0.00013537733,0.00013836219,0.00009454982,0.000073767056,0.00006629608,0.00013137543,0.00011942011,0.00018707132],"category_scores_gemma":[0.000019852892,0.00014945488,0.000032802192,0.0003344812,0.000011959257,0.00071119494,0.000016532224,0.00017565837,0.0000024730866],"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":[0.000005681384,0.000013537957,0.00088648783,0.000014383541,0.000006333848,2.8517337e-7,0.0000453982,0.9690042,0.011336228,0.0017333385,0.001254862,0.015699226],"study_design_scores_gemma":[0.00050552434,0.0000059623485,0.0012106602,0.0000053483104,0.0000055406617,5.6369606e-7,0.000011056501,0.9962162,0.0009285919,0.00028983483,0.000636976,0.00018376729],"about_ca_topic_score_codex":0.000009135222,"about_ca_topic_score_gemma":0.0014534021,"teacher_disagreement_score":0.7403217,"about_ca_system_score_codex":0.000031710268,"about_ca_system_score_gemma":0.000012377909,"threshold_uncertainty_score":0.60945934},"labels":[],"label_agreement":null},{"id":"W2097097299","doi":"10.1109/wcnc.2007.568","title":"Multi-Class Resource Management in a Cellular/WLAN Integrated Network","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":21,"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":"Computer science; Computer network; Cellular network; Resource management (computing); Resource allocation; Overhead (engineering); Distributed computing; Scheme (mathematics); Local area network; Wireless network; Radio resource management; Wireless; Telecommunications; Operating system","score_opus":0.007436382391322421,"score_gpt":0.20731678709269272,"score_spread":0.1998804047013703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097097299","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":[0.008296972,0.00019943745,0.95055276,0.000012334311,0.00015898247,0.00024022738,4.3755603e-7,0.0005406758,0.039998155],"genre_scores_gemma":[0.8199085,0.00007757441,0.1778826,0.00009262777,0.000109445304,0.000015160844,0.000048743153,0.000062292675,0.0018030398],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904966,0.000014421422,0.00026193168,0.00016586205,0.00009751409,0.00041060144],"domain_scores_gemma":[0.9996816,0.000033904245,0.00001997485,0.00019246855,0.000012959061,0.000059073947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022215258,0.00014690183,0.00012653614,0.00011637167,0.00002630319,0.000014882921,0.000113669994,0.000078826684,0.000044676483],"category_scores_gemma":[0.0000033122787,0.00014894274,0.000023661198,0.00065557193,0.000013953107,0.00006846587,0.000024832716,0.00016994691,0.00003279272],"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":[0.000011326517,0.000016561062,0.000390887,0.000013056228,0.00001536521,0.000042268814,0.000050428353,0.9865019,0.00026327922,0.000570617,0.0011511554,0.010973168],"study_design_scores_gemma":[0.0005003302,0.00000631819,0.0008980532,0.000041337047,0.0000046754058,9.0396645e-7,0.00017969916,0.9737929,0.00047366903,0.000038701965,0.023874855,0.00018853434],"about_ca_topic_score_codex":0.000007353012,"about_ca_topic_score_gemma":0.00025483652,"teacher_disagreement_score":0.81161153,"about_ca_system_score_codex":0.00014313999,"about_ca_system_score_gemma":0.0000018499778,"threshold_uncertainty_score":0.60737085},"labels":[],"label_agreement":null},{"id":"W2097245425","doi":"10.1109/ccece.2006.277296","title":"A Dynamic Scheduling Scheme for the Revers Packet Data Channel in CDMA2000 1XEV-DV","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"CDMA2000; Computer science; Scheduling (production processes); Maximum throughput scheduling; Network packet; Proportionally fair; Computer network; Dynamic priority scheduling; Round-robin scheduling; Real-time computing; Fair queuing; Transmission delay; Fair-share scheduling; Mathematical optimization; Code division multiple access; Quality of service; Mathematics","score_opus":0.015390722428875727,"score_gpt":0.2413682420332658,"score_spread":0.22597751960439005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097245425","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":[0.009026269,0.0009197357,0.987682,0.00024575213,0.00021777801,0.00042994478,0.000034097426,0.00028199184,0.001162442],"genre_scores_gemma":[0.8297945,0.00028891003,0.16879913,0.000055933207,0.00013374095,0.000073278476,0.00032471668,0.0000712188,0.0004585244],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918777,0.000009542078,0.00020423377,0.0002090272,0.00010734685,0.00028208195],"domain_scores_gemma":[0.9993065,0.00011706485,0.000025581545,0.0005034242,0.000026740054,0.00002070576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002319779,0.00013087929,0.00011912156,0.00005768114,0.000056993405,0.000026247462,0.00030689794,0.000066589746,0.000020769929],"category_scores_gemma":[0.000033703094,0.0001099062,0.000022227743,0.00027684722,0.000019919436,0.00028721945,0.000059420807,0.00012253846,0.000009427115],"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":[0.000004968072,0.0000076343995,0.000044371376,0.000017701483,0.000009229767,5.49485e-7,0.000016114476,0.99603504,0.00014448314,0.0003181445,0.0011898115,0.002211948],"study_design_scores_gemma":[0.00041521393,0.0000033945066,0.00013669359,0.000030498008,0.000009394663,0.0000011501504,0.00006966434,0.9968987,0.00008745934,0.0004921571,0.0017102974,0.00014535623],"about_ca_topic_score_codex":0.0000422227,"about_ca_topic_score_gemma":0.0006875145,"teacher_disagreement_score":0.8207683,"about_ca_system_score_codex":0.00009265822,"about_ca_system_score_gemma":0.000012677033,"threshold_uncertainty_score":0.4481845},"labels":[],"label_agreement":null},{"id":"W2097277121","doi":"10.1109/cdc.2005.1582659","title":"Structural Results on the Optimal Transmission Scheduling Policies and Costs for Correlated Sources and Channels","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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","funders":"","keywords":"Markov decision process; Computer science; Mathematical optimization; Scheduling (production processes); Transmission (telecommunications); Convexity; Channel (broadcasting); Markov process; Markov chain; Wireless; Monotonic function; Computer network; Mathematics; Telecommunications","score_opus":0.00853706806454044,"score_gpt":0.2111587519467301,"score_spread":0.20262168388218965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097277121","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":[0.76810515,0.00034572842,0.23031445,0.000331238,0.00006974167,0.00024700185,0.000007709066,0.00016528771,0.0004137006],"genre_scores_gemma":[0.98874605,0.000081261955,0.010869821,0.000028023884,0.00008794148,0.000009495619,0.00002361616,0.000021846336,0.00013196791],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995313,0.000009083157,0.00013346653,0.00011448916,0.000054884807,0.00015676496],"domain_scores_gemma":[0.99970734,0.00016432563,0.00002093505,0.000059791273,0.000018774308,0.000028816467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000055508735,0.00011150485,0.00008655589,0.000034570992,0.00013994593,0.00004668795,0.000034901925,0.000059405935,0.000002673451],"category_scores_gemma":[0.000011108657,0.00007510569,0.000013430848,0.00007448225,0.000035479392,0.00009241352,0.0000075786807,0.00007482293,2.8724716e-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":[0.000048413203,0.0000013358721,0.000023223716,0.000007717669,0.0000056170766,1.6518369e-7,0.00016374189,0.99290943,0.0006612303,0.0015478514,0.00011818577,0.004513074],"study_design_scores_gemma":[0.0005008517,0.000033560187,0.0002856295,0.000045932928,0.000006331101,0.0000031945463,0.00010590966,0.9938593,0.0046487744,0.00020859668,0.00019624575,0.00010568384],"about_ca_topic_score_codex":0.000017306325,"about_ca_topic_score_gemma":0.000003830139,"teacher_disagreement_score":0.22064088,"about_ca_system_score_codex":0.00001580419,"about_ca_system_score_gemma":0.0000018298474,"threshold_uncertainty_score":0.3062721},"labels":[],"label_agreement":null},{"id":"W2097422852","doi":"10.1109/vetecf.2000.886120","title":"An optimum rate/power allocation scheme for downlink in hybrid CDMA/TDMA cellular system","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Telecommunications link; Time division multiple access; Computer science; Computer network; Fading; Code division multiple access; Throughput; Bandwidth (computing); Wireless; Resource allocation; Channel (broadcasting); Electronic engineering; Telecommunications; Engineering","score_opus":0.00843309067361556,"score_gpt":0.19785596388044485,"score_spread":0.1894228732068293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097422852","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":[0.043772683,0.00027096047,0.9520198,0.00004225341,0.00030760976,0.0005341529,0.000005691272,0.0006928351,0.002353977],"genre_scores_gemma":[0.92817694,0.00004616509,0.07116163,0.000021712873,0.00010728998,0.0001180949,0.000094474075,0.00006471432,0.00020895689],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990294,0.000023581983,0.00031557033,0.00024249074,0.00008644283,0.00030250932],"domain_scores_gemma":[0.99947846,0.000039984385,0.00003688909,0.00030674486,0.000063706466,0.00007422427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001432535,0.00017873818,0.00018366077,0.00011074485,0.000043555392,0.0000372921,0.00013518553,0.00008546338,0.00010703962],"category_scores_gemma":[0.00001036324,0.0001926919,0.000036656565,0.00021448534,0.000012041906,0.0004059918,0.00001002024,0.000099756864,0.00006194369],"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":[0.000005861802,0.000026916352,0.00004940444,0.00007149596,0.000008801669,0.000003480179,0.000059350874,0.98910296,0.008050112,0.0012040071,0.00065929483,0.0007582859],"study_design_scores_gemma":[0.0005064116,0.000032963355,0.000017250719,0.00003767169,0.0000053577874,0.0000022403535,0.000079667516,0.9849352,0.013400721,0.00002793722,0.00072098395,0.00023354686],"about_ca_topic_score_codex":0.0000026194828,"about_ca_topic_score_gemma":0.0000053784506,"teacher_disagreement_score":0.8844043,"about_ca_system_score_codex":0.00017811962,"about_ca_system_score_gemma":0.000003969741,"threshold_uncertainty_score":0.78577477},"labels":[],"label_agreement":null},{"id":"W2097491623","doi":"10.1109/tvt.2007.907023","title":"A New QoS Provisioning Method for Adaptive Multimedia in Wireless Networks","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia; Carleton University","funders":"","keywords":"Computer science; Quality of service; Wireless network; Provisioning; Bandwidth (computing); Computer network; Bandwidth allocation; Wireless; Call Admission Control; Reinforcement learning; Distributed computing; Multimedia; Artificial intelligence; Telecommunications","score_opus":0.009983919378835825,"score_gpt":0.23395605798274013,"score_spread":0.2239721386039043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097491623","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":[0.005842079,0.00020052952,0.99146914,0.00009289854,0.00051788636,0.00079202227,0.0000058663486,0.0010513231,0.000028267848],"genre_scores_gemma":[0.59349525,0.00021252483,0.40575954,0.000019524958,0.000058701957,0.00032669914,0.0000049253863,0.00006989811,0.000052916002],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873835,0.000028499078,0.00032421254,0.0003555583,0.000113201226,0.0004401948],"domain_scores_gemma":[0.9993655,0.00015372054,0.000048296133,0.00030316567,0.00005728718,0.00007203706],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008514852,0.00025601368,0.00033461314,0.0005549935,0.00014387931,0.000006641389,0.00018886679,0.00049546274,0.00001204301],"category_scores_gemma":[0.000006873106,0.00028725222,0.00009378873,0.0009861217,0.000060592487,0.00014222278,0.0000016883026,0.0006150918,0.000008029484],"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":[0.000038562473,0.00003322918,0.000009137682,0.000007579828,0.0000343986,0.000016548986,0.00006978606,0.83122915,0.0013221158,0.00011010696,0.000074739735,0.16705467],"study_design_scores_gemma":[0.0010735427,0.000117025374,0.000013290313,0.000067793095,0.000019965984,0.000043173368,0.000045716337,0.96940553,0.028502345,0.00017350288,0.00026765311,0.0002704496],"about_ca_topic_score_codex":0.000015851629,"about_ca_topic_score_gemma":0.00008454825,"teacher_disagreement_score":0.58765316,"about_ca_system_score_codex":0.00017294449,"about_ca_system_score_gemma":0.000038725,"threshold_uncertainty_score":0.999958},"labels":[],"label_agreement":null},{"id":"W2097655034","doi":"10.1109/wcnc.2011.5779213","title":"Most balancing algorithms for optimal packet scheduling in multi-server wireless systems","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Scheduling (production processes); Computer network; Wireless; Distributed computing; Network packet; Fair-share scheduling; Algorithm; Quality of service; Mathematical optimization; Operating system","score_opus":0.03820985789662123,"score_gpt":0.2486773916845864,"score_spread":0.21046753378796518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097655034","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":[0.1217929,0.00024833973,0.8762038,0.0000024346912,0.0005135126,0.00045408492,0.0000073900683,0.00039954504,0.000378027],"genre_scores_gemma":[0.67657846,0.00005166626,0.3229844,0.000010697796,0.00007859279,0.000116880576,0.00002725431,0.00006978686,0.00008225989],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988811,0.000015208533,0.00035208772,0.00023561918,0.000099363264,0.00041664793],"domain_scores_gemma":[0.9995506,0.000052131003,0.000043011787,0.00020129632,0.00007843582,0.00007452306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001652592,0.00020339903,0.0002528385,0.00010498474,0.000045000037,0.000028651226,0.00013825146,0.00013224501,0.000018801791],"category_scores_gemma":[0.000019135312,0.00021258305,0.00003437615,0.00030227652,0.00001604429,0.0003444366,0.000027411006,0.00013933645,0.000011102339],"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":[0.000009842237,0.000023103757,0.0015365672,0.000096620905,0.00001703593,0.00000421085,0.00028143273,0.9953314,0.0003377988,0.0004900568,0.000034993845,0.001836933],"study_design_scores_gemma":[0.0007988001,0.000016980077,0.00047081104,0.00010839598,0.0000064632654,0.0000033752012,0.00037349208,0.9959966,0.0018932829,0.000009469963,0.000049290193,0.00027306483],"about_ca_topic_score_codex":0.00006268355,"about_ca_topic_score_gemma":0.000065394386,"teacher_disagreement_score":0.55478555,"about_ca_system_score_codex":0.00011797287,"about_ca_system_score_gemma":0.000013768338,"threshold_uncertainty_score":0.8668885},"labels":[],"label_agreement":null},{"id":"W2097866586","doi":"10.1002/dac.567","title":"A novel delineation mechanism for the ATM adaptation layer 2 over wireless ATM networks","year":2002,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Ottawa","funders":"","keywords":"ATM adaptation layer; Computer science; Computer network; Asynchronous Transfer Mode; Network packet; Payload (computing)","score_opus":0.03892732726751925,"score_gpt":0.26447745864563077,"score_spread":0.22555013137811153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097866586","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":[0.0034064634,0.0033766646,0.9902188,0.0005077408,0.0019210898,0.0003308985,0.000012368015,0.000062902975,0.00016308147],"genre_scores_gemma":[0.9848553,0.004649568,0.009415799,0.00009414565,0.00071854284,0.00006817426,0.000036797064,0.00004500118,0.00011668109],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847716,0.00006486099,0.0007880751,0.000085113956,0.00044641792,0.00013837394],"domain_scores_gemma":[0.9971493,0.0005400606,0.0005653578,0.0003249647,0.0013745022,0.00004581679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004373273,0.00014758584,0.00019084266,0.00012747299,0.0001219559,0.00014425557,0.00074157614,0.0001021369,0.000019069841],"category_scores_gemma":[0.000070771246,0.00012304746,0.00011579967,0.00016504244,0.000027563869,0.00054192694,0.00003825436,0.00023303456,0.000004724891],"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":[0.000024896104,0.000031059408,0.000030063966,0.000003665062,0.000181583,4.218814e-7,0.00035254538,0.97447354,0.00041084242,0.012940143,0.0011368268,0.010414442],"study_design_scores_gemma":[0.00086083496,0.000022450013,0.00008102424,0.00014367515,0.000036154426,0.000047554422,0.00025591863,0.99027264,0.0000965822,0.0001432063,0.007920406,0.00011956055],"about_ca_topic_score_codex":0.000016979262,"about_ca_topic_score_gemma":0.00001959425,"teacher_disagreement_score":0.9814488,"about_ca_system_score_codex":0.00022703409,"about_ca_system_score_gemma":0.000012037443,"threshold_uncertainty_score":0.501773},"labels":[],"label_agreement":null},{"id":"W2097899179","doi":"10.1109/icme.2000.869632","title":"Improving the performance of ITU-T G.729A for VoIP","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Ottawa","funders":"","keywords":"Packet loss; Computer science; Voice over IP; Computer network; Network packet; Encoder; Real-time computing; Algorithm; The Internet","score_opus":0.008164913752340255,"score_gpt":0.174611756833518,"score_spread":0.16644684308117774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097899179","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":[0.13332179,0.00037521083,0.8612698,0.000044751545,0.00019843958,0.0002665,0.0000020943867,0.00020447958,0.004316987],"genre_scores_gemma":[0.9794571,0.00013894508,0.019729493,0.000019092027,0.00006450169,0.000024001054,0.0000016078606,0.00001808485,0.00054719223],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996796,0.0000021835863,0.00010717213,0.000052142692,0.000045483615,0.000113408736],"domain_scores_gemma":[0.99977696,0.000045628396,0.000019922878,0.000121836376,0.000023723582,0.000011900127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003792644,0.00005501589,0.000060422542,0.000015921085,0.000035795056,0.0000051259326,0.000074407675,0.000023803976,0.000055159762],"category_scores_gemma":[0.000008396691,0.00003986478,0.000021288763,0.000083733416,0.000013620392,0.00010518327,0.000008638641,0.000039442857,0.000006042251],"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":[0.0000012601931,0.000002778259,0.00006975712,0.00004061917,0.0000043618347,2.2101904e-8,0.000052942014,0.9708764,0.0012924751,0.00021888925,0.0006899706,0.026750516],"study_design_scores_gemma":[0.00010885224,0.000016805578,0.00005580003,0.000006914151,0.0000037485117,5.346741e-7,0.000012570796,0.9875385,0.011190538,0.000008134843,0.0010047528,0.000052833784],"about_ca_topic_score_codex":9.583173e-7,"about_ca_topic_score_gemma":0.0000017126889,"teacher_disagreement_score":0.8461353,"about_ca_system_score_codex":0.000013371725,"about_ca_system_score_gemma":9.850936e-7,"threshold_uncertainty_score":0.16256385},"labels":[],"label_agreement":null},{"id":"W2098047202","doi":"10.1109/pacrim.2007.4313296","title":"Multi-Flow Merging Gain in Scheduling for Flow-Based Wireless Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Computer network; Quality of service; Wireless; Scheduling (production processes); Radio resource management; Network packet; Wireless network; Distributed computing; Telecommunications; Engineering","score_opus":0.011134917830975356,"score_gpt":0.24259116906090047,"score_spread":0.2314562512299251,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098047202","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":[0.015181408,0.00026842504,0.9829909,0.00001698816,0.0004011616,0.0003913465,0.0000019214167,0.00053461496,0.00021320982],"genre_scores_gemma":[0.47530943,0.000023567565,0.52434444,0.000054076794,0.00012276472,0.000029497118,0.000035515415,0.00005964148,0.000021058298],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986824,0.000012408495,0.00037864296,0.00023678823,0.00010223919,0.0005875703],"domain_scores_gemma":[0.9993924,0.00025049437,0.000035866226,0.00018639595,0.000047842408,0.00008701144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041174056,0.00021084682,0.00022186627,0.00017442604,0.00006351531,0.000023342178,0.00011917964,0.00015544456,0.000016340242],"category_scores_gemma":[0.00003105282,0.0002366673,0.000061036255,0.0004451787,0.000018240924,0.00016570806,0.000014713988,0.00020529181,0.0000029590412],"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":[0.000025235464,0.000019527888,0.00046092816,0.000034778517,0.000008515904,0.000004467395,0.00004179202,0.95121837,0.00053642277,0.00006604273,0.000027569746,0.047556352],"study_design_scores_gemma":[0.001227689,0.000009425527,0.00012978987,0.000089684785,0.000005485828,5.20454e-7,0.000079584956,0.9963622,0.0017061378,0.000012540262,0.000090970614,0.00028593812],"about_ca_topic_score_codex":0.0000049774258,"about_ca_topic_score_gemma":0.0002552007,"teacher_disagreement_score":0.46012804,"about_ca_system_score_codex":0.00015994054,"about_ca_system_score_gemma":0.000011757175,"threshold_uncertainty_score":0.96510124},"labels":[],"label_agreement":null},{"id":"W2098119380","doi":"10.1016/j.comnet.2010.03.012","title":"Interference aware resource allocation for hybrid hierarchical wireless networks","year":2010,"lang":"en","type":"article","venue":"Computer Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Computer science; Resource allocation; Computer network; Wireless network; Subcarrier; Radio resource management; Throughput; Interference (communication); Wireless; Quality of service; Distributed computing; Heuristic; Exploit; Orthogonal frequency-division multiplexing; Telecommunications; Channel (broadcasting)","score_opus":0.00630262066891268,"score_gpt":0.20701633522198595,"score_spread":0.20071371455307327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098119380","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":[0.010110365,0.00014996849,0.9855723,0.00007554863,0.002631237,0.0004689302,0.0000045572883,0.00082432345,0.00016277166],"genre_scores_gemma":[0.9558807,0.000085138185,0.039675355,0.00020192645,0.0035590383,0.000116583484,0.00032449947,0.00011625238,0.00004048006],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984628,0.000035438024,0.0003921612,0.0004165879,0.00012082,0.00057219143],"domain_scores_gemma":[0.99886173,0.0002935273,0.000074347365,0.00049439084,0.000102477374,0.00017352511],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016852938,0.00031517548,0.0002974671,0.00008018473,0.00015390643,0.000110208784,0.0004410231,0.0002294347,0.000015813805],"category_scores_gemma":[0.0000073730816,0.00034478106,0.000097963166,0.0002383883,0.000085862004,0.00019688395,0.00011767858,0.0008307579,0.00000557435],"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":[0.000021334054,0.000014381232,0.00007192552,0.000017588944,0.00002164021,0.0000023136472,0.000026350315,0.8069256,0.000025056617,0.0007467742,0.009112598,0.18301444],"study_design_scores_gemma":[0.00038692114,0.00004795408,0.00017030984,0.000075434305,0.00001404553,0.00001721031,0.0000024734854,0.99039364,0.000072772535,0.00021770333,0.008229705,0.00037185266],"about_ca_topic_score_codex":8.4392116e-7,"about_ca_topic_score_gemma":0.0000140564935,"teacher_disagreement_score":0.9458969,"about_ca_system_score_codex":0.00004886094,"about_ca_system_score_gemma":0.000012672799,"threshold_uncertainty_score":0.9999004},"labels":[],"label_agreement":null},{"id":"W2098592039","doi":"10.1109/tcomm.2011.091911.100007a","title":"A Weighted Queue-Based Model for Correlated Rayleigh and Rician Fading Channels","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Rician fading; Queue; Rayleigh fading; Fading; Channel (broadcasting); Computer science; Channel capacity; Algorithm; Mathematics; Telecommunications; Computer network","score_opus":0.0484424474503522,"score_gpt":0.24224605641726085,"score_spread":0.19380360896690865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098592039","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":[0.0011583489,0.00022385705,0.9960511,0.00009224629,0.00021159352,0.0004928467,0.000057383102,0.0005741435,0.0011384944],"genre_scores_gemma":[0.88640046,0.0005095708,0.112389304,0.00005221607,0.0000087847875,0.00040763977,0.000032380696,0.00006114694,0.00013850046],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927837,0.00003346754,0.0002513976,0.00015822775,0.00006630763,0.00021225655],"domain_scores_gemma":[0.99885255,0.00018820235,0.000045118202,0.0007480626,0.00008538636,0.00008067788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000722305,0.00017270315,0.00015907407,0.0001935732,0.00040318232,0.000020195539,0.00028370484,0.00012327451,0.00001659905],"category_scores_gemma":[0.0000027448782,0.00020031766,0.0000629135,0.0003268181,0.000081928476,0.00018918113,0.0000019706392,0.0002622478,0.000007609898],"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":[0.000021599446,0.00008767877,0.0000019428799,0.000014649226,0.00003815106,1.1403741e-7,0.00076805387,0.9926758,0.00025995637,0.0005453873,0.00004217039,0.0055445274],"study_design_scores_gemma":[0.0005418028,0.00003224458,0.000005631704,0.000053292737,0.000056924095,0.0000013986368,0.00003492716,0.9950112,0.0030505587,0.00081245863,0.00019337444,0.00020617775],"about_ca_topic_score_codex":0.000011389406,"about_ca_topic_score_gemma":0.00011501023,"teacher_disagreement_score":0.8852421,"about_ca_system_score_codex":0.00008040688,"about_ca_system_score_gemma":0.000021387881,"threshold_uncertainty_score":0.81687176},"labels":[],"label_agreement":null},{"id":"W2098610567","doi":"10.1145/1454630.1454655","title":"Downlink mixed-traffic scheduling with packet division multiplexing","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Quality of service; Network packet; Multiplexing; Jitter; Scheduling (production processes); Statistical time division multiplexing; Time-division multiplexing; Telecommunications link; Real-time computing; Telecommunications; Engineering","score_opus":0.009918460500941176,"score_gpt":0.1879068181400215,"score_spread":0.17798835763908033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098610567","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":[0.41468298,0.0001257227,0.5833397,0.000012601506,0.00009876101,0.000088082605,0.000001080746,0.0007640066,0.0008870901],"genre_scores_gemma":[0.8102045,0.00015387405,0.18938655,0.000015231803,0.00007680305,0.000008680314,0.000028776112,0.000048928232,0.000076658376],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919915,0.000010454093,0.00017297956,0.00018343337,0.00015839425,0.00027558638],"domain_scores_gemma":[0.99961215,0.000054189364,0.000024896503,0.00019179373,0.000040755116,0.000076185665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004247873,0.00016998191,0.00014920525,0.00007125811,0.00013114134,0.00001531288,0.000084626925,0.000069623005,0.000038596085],"category_scores_gemma":[0.000012270479,0.00014459265,0.000028766868,0.00027756635,0.00003658838,0.00026120365,0.00001994781,0.00016317358,0.000044749966],"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":[0.0000042124566,0.000010076142,0.0009120898,0.000012595076,0.000013193638,0.000011849002,0.00010852249,0.9899916,0.00041345035,0.000048117476,0.00012287564,0.0083514005],"study_design_scores_gemma":[0.00040018107,0.000018854356,0.0008982898,0.000048445723,0.0000033291517,0.000017132303,0.00003965141,0.9959117,0.002085049,0.0000073704123,0.000338747,0.00023120405],"about_ca_topic_score_codex":0.0000011677645,"about_ca_topic_score_gemma":0.0000142566305,"teacher_disagreement_score":0.39552152,"about_ca_system_score_codex":0.00004801247,"about_ca_system_score_gemma":0.000008566252,"threshold_uncertainty_score":0.58963174},"labels":[],"label_agreement":null},{"id":"W2098835300","doi":"10.1109/wowmom.2014.6918946","title":"TCP-aware scheduling in LTE networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"","keywords":"Computer science; Computer network; Scheduling (production processes); Fairness measure; Queue; Dynamic priority scheduling; Round-robin scheduling; Distributed computing; TCP Friendly Rate Control; Network congestion; Wireless; Throughput; Quality of service; Engineering; Network packet; Telecommunications","score_opus":0.003260176809799871,"score_gpt":0.179704932912606,"score_spread":0.17644475610280613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098835300","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":[0.016387625,0.00011279076,0.9759755,0.00001728166,0.00021597742,0.00006169431,1.2044572e-7,0.0004032709,0.0068257186],"genre_scores_gemma":[0.9677266,0.00008925686,0.03183966,0.000053936055,0.00016151738,0.000009119672,0.000008636708,0.000032940996,0.00007834193],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994845,0.000011700749,0.00013969315,0.000103936516,0.00005221443,0.00020797006],"domain_scores_gemma":[0.9997668,0.000041390213,0.000011270443,0.00013127181,0.000012536879,0.000036715308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007254891,0.000090662645,0.00010158687,0.000051691433,0.000018538205,0.000013796628,0.00006772679,0.000067227804,0.000046751466],"category_scores_gemma":[0.00001036994,0.00009572879,0.000016056307,0.00021559013,0.000007748258,0.00012595668,0.000015455977,0.00013195058,0.000022037477],"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":[0.0000010792843,0.0000024547476,0.001035231,0.0000061990027,0.0000020953742,5.469584e-7,0.000012704826,0.9865293,0.000019249028,0.0008317308,0.000089461326,0.0114699565],"study_design_scores_gemma":[0.00016494021,0.0000041591434,0.0004328624,0.00002587492,0.0000012299934,5.602882e-7,0.000009941072,0.9984048,0.000093921386,0.00014376311,0.0005998897,0.00011807178],"about_ca_topic_score_codex":0.000002871209,"about_ca_topic_score_gemma":0.000039919407,"teacher_disagreement_score":0.95133895,"about_ca_system_score_codex":0.000036363574,"about_ca_system_score_gemma":0.0000018465162,"threshold_uncertainty_score":0.3903707},"labels":[],"label_agreement":null},{"id":"W2099120675","doi":"10.1109/glocom.2005.1577846","title":"Optimal packet scheduling over correlated Nakagami-m channels with different diversity-combining techniques","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Nakagami distribution; Computer science; Fading; Network packet; Scheduling (production processes); Markov process; Bit error rate; Markov decision process; Markov chain; Transmission (telecommunications); Mathematical optimization; Channel (broadcasting); Algorithm; Mathematics; Computer network; Telecommunications; Statistics","score_opus":0.01482366636108302,"score_gpt":0.2399280109414401,"score_spread":0.22510434458035708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099120675","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":[0.4281896,0.0009475375,0.54923934,0.0007101428,0.000704201,0.0011407313,0.00018921487,0.003335339,0.015543929],"genre_scores_gemma":[0.89993906,0.0017099769,0.09737751,0.00013576917,0.00014845881,0.00011167229,0.00031936003,0.00007421646,0.00018397706],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972389,0.00014001013,0.00069494155,0.0005276043,0.0004223299,0.000976228],"domain_scores_gemma":[0.9976379,0.000116254865,0.00024939797,0.0013887517,0.00028834713,0.00031933674],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018483844,0.00067012483,0.0006183827,0.00021998025,0.00082960835,0.00023103501,0.0013606366,0.00036668277,0.0002633747],"category_scores_gemma":[0.000024362605,0.00068968744,0.00013684333,0.0007980006,0.0002376992,0.0008355345,0.00052839087,0.00080225914,0.00008156766],"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":[0.000055259676,0.00024787028,0.0025498634,0.000026532332,0.00022513217,0.000007104284,0.00028402905,0.96784824,0.0001436446,0.002285132,0.0038344625,0.022492712],"study_design_scores_gemma":[0.0015414011,0.00014847946,0.0017797401,0.0003807941,0.00014903613,0.00007359081,0.00023380162,0.98131144,0.0016241833,0.0003432392,0.011134523,0.0012797511],"about_ca_topic_score_codex":0.00006486595,"about_ca_topic_score_gemma":0.00040775817,"teacher_disagreement_score":0.47174948,"about_ca_system_score_codex":0.00088545535,"about_ca_system_score_gemma":0.000097073505,"threshold_uncertainty_score":0.9995554},"labels":[],"label_agreement":null},{"id":"W2099671751","doi":"10.1109/twc.2010.100510.091821","title":"Energy Efficient Quality of Service Traffic Scheduler for MIMO Downlink SVD Channels","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Computer science; Quality of service; Scheduling (production processes); Computer network; Telecommunications link; MIMO; Channel (broadcasting); Queue; Network packet; Energy consumption; Throughput; Real-time computing; Mathematical optimization; Wireless; Telecommunications; Engineering; Mathematics","score_opus":0.02695400048309945,"score_gpt":0.27701103927590925,"score_spread":0.2500570387928098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099671751","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":[0.12767719,0.00009658887,0.8698,0.0005001474,0.0007776988,0.00037726987,0.0001608779,0.00042047395,0.00018978828],"genre_scores_gemma":[0.9663461,0.00032769673,0.032467023,0.00008614117,0.000049121063,0.0005136481,0.00008308917,0.000081087135,0.000046105826],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985568,0.00008262192,0.00062335655,0.00024046726,0.000192458,0.00030429033],"domain_scores_gemma":[0.99705106,0.00059615413,0.00013699828,0.0017703113,0.0003331236,0.00011234088],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022390862,0.00025469795,0.00034042963,0.00021280373,0.00034650386,0.000026148791,0.00078240223,0.00022541414,0.000034692202],"category_scores_gemma":[0.000006257189,0.00029152972,0.00016731232,0.00069703686,0.00014542032,0.00013584144,0.0000055415007,0.0004970843,0.00001048813],"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":[0.000025246194,0.00032229978,7.651395e-7,0.0000688082,0.00006113581,4.1600476e-8,0.0002715244,0.94912225,0.019766472,0.0028380703,0.000023936977,0.027499424],"study_design_scores_gemma":[0.000623495,0.000026211279,0.000016795915,0.000050206698,0.00003916,0.00000157616,0.00008005823,0.9661855,0.031630978,0.00007634707,0.0009817674,0.00028787387],"about_ca_topic_score_codex":0.000041750784,"about_ca_topic_score_gemma":0.0011562464,"teacher_disagreement_score":0.8386689,"about_ca_system_score_codex":0.00006256961,"about_ca_system_score_gemma":0.000044544206,"threshold_uncertainty_score":0.9999537},"labels":[],"label_agreement":null},{"id":"W2100264826","doi":"10.1109/wcnc.2005.1424708","title":"Dynamic resource allocation for video traffic over time-varying CDMA wireless channels","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer network; Computer science; Quality of service; Provisioning; Wireless; Resource allocation; Wireless network; Distributed computing; Telecommunications","score_opus":0.005383003790789974,"score_gpt":0.21587920720188208,"score_spread":0.2104962034110921,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100264826","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":[0.1235246,0.00022753401,0.8726855,0.00018263441,0.00016928893,0.0005290343,0.00000548205,0.0011442063,0.0015317437],"genre_scores_gemma":[0.9612838,0.000041705418,0.03644907,0.0001672401,0.0002476742,0.00010577105,0.00013000653,0.000111251684,0.0014634731],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990405,0.000011879318,0.00025959828,0.00023270957,0.00012508497,0.0003302381],"domain_scores_gemma":[0.9995457,0.000094325515,0.000042550255,0.00021330375,0.00003820646,0.000065909764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000094762596,0.0001902713,0.00017294048,0.00009716346,0.000084333056,0.000037651953,0.00012568854,0.00009473406,0.00010280646],"category_scores_gemma":[0.000011162899,0.00021022465,0.000057770456,0.00021753552,0.000016593025,0.00034421403,0.000015711985,0.00009495744,0.00006624723],"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":[0.00001296948,0.000013379096,0.0000015512245,0.000028465663,0.000017173787,2.6941643e-7,0.0001090257,0.9430911,0.0023061985,0.00011730768,0.0018902086,0.052412383],"study_design_scores_gemma":[0.00047738422,0.000015799902,0.00001186466,0.000036557754,0.000012275189,0.0000026143825,0.000011669622,0.987147,0.001673599,0.000024320028,0.010332797,0.00025415295],"about_ca_topic_score_codex":6.4818727e-7,"about_ca_topic_score_gemma":0.000009282071,"teacher_disagreement_score":0.8377592,"about_ca_system_score_codex":0.00018566122,"about_ca_system_score_gemma":0.0000083304685,"threshold_uncertainty_score":0.85727125},"labels":[],"label_agreement":null},{"id":"W2100648790","doi":"10.1109/wcl.2013.052813.130085","title":"Joint Optimization of Bit and Power Loading for Multicarrier Systems","year":2013,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":26,"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; Memorial University of Newfoundland","funders":"","keywords":"Subcarrier; Transmitter power output; Computer science; Lagrange multiplier; Bit error rate; Mathematical optimization; Power (physics); Bisection method; Throughput; Weighting; Power optimization; Constraint (computer-aided design); Joint (building); Algorithm; Orthogonal frequency-division multiplexing; Wireless; Mathematics; Telecommunications; Decoding methods; Power consumption; Transmitter; Channel (broadcasting); Engineering","score_opus":0.01660448581424558,"score_gpt":0.22241142325306787,"score_spread":0.20580693743882228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100648790","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":[0.11884863,0.0005352875,0.87872607,0.00048800412,0.00023453901,0.00080616446,0.000016770817,0.0001937842,0.0001507581],"genre_scores_gemma":[0.901024,0.00041175247,0.0979709,0.00007421251,0.000025144122,0.00038300845,0.000042776563,0.000057606092,0.000010583029],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999116,0.00004578315,0.00039925924,0.0001410356,0.00009421634,0.00020367368],"domain_scores_gemma":[0.99868125,0.0002021038,0.000112470625,0.0008009519,0.00014044212,0.00006278854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009671492,0.00015491288,0.00023839102,0.00013799305,0.0001264817,0.000053669555,0.00028636734,0.00007655608,0.000007640948],"category_scores_gemma":[0.0000191133,0.00017166481,0.000043047934,0.00020270022,0.00013992761,0.00034567295,0.000048983045,0.00012116819,0.0000040193418],"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":[0.000001682465,0.0000127194835,0.00009974286,0.00006618697,0.000037007267,5.505782e-8,0.00023188166,0.9592801,0.038381536,0.00047646894,0.0007183659,0.0006942812],"study_design_scores_gemma":[0.00030139033,0.000009705172,0.00010123673,0.00010111773,0.000018146475,0.0000021985836,0.00012807864,0.9970281,0.0018727919,0.000011386351,0.0002481848,0.0001776587],"about_ca_topic_score_codex":0.000022968428,"about_ca_topic_score_gemma":0.0000022051993,"teacher_disagreement_score":0.78217536,"about_ca_system_score_codex":0.00006661104,"about_ca_system_score_gemma":0.000006566009,"threshold_uncertainty_score":0.7000288},"labels":[],"label_agreement":null},{"id":"W2101262324","doi":"10.1002/wcm.2262","title":"Dimensioning the packet loss burstiness over wireless channels: a novel metric, its analysis and application","year":2012,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Burstiness; Computer science; Dimensioning; Computer network; Metric (unit); Network packet; Packet loss","score_opus":0.012611648738681066,"score_gpt":0.25445890598619575,"score_spread":0.24184725724751469,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101262324","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":[0.46974042,0.0068279896,0.5226448,0.000047044407,0.00008856494,0.00035426833,0.000007700721,0.00019707195,0.00009210682],"genre_scores_gemma":[0.98978055,0.0031408868,0.0065922686,0.000038657072,0.00012206369,0.00016838565,0.00009350953,0.00005055607,0.0000131381785],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872375,0.00008365356,0.00039435484,0.00024441545,0.00016002887,0.0003938035],"domain_scores_gemma":[0.99801683,0.00061473873,0.00016698739,0.0009528344,0.00012311354,0.00012547176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004635755,0.0002497475,0.00033615067,0.0002469703,0.00074610685,0.00010191819,0.0004044804,0.000103500024,0.0000029979844],"category_scores_gemma":[0.000018117757,0.00022090613,0.000060678503,0.0017173833,0.0001626451,0.00031351825,0.00050019455,0.0003051864,0.0000026640528],"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":[0.0000063779116,0.00014628725,0.021464745,0.00010165205,0.0004193352,2.572756e-7,0.0028057722,0.7828301,0.0029879436,0.005860943,0.000028522249,0.18334803],"study_design_scores_gemma":[0.00024267519,0.000008470309,0.005758808,0.000048455866,0.00018475337,0.000009685161,0.00027383142,0.9914566,0.00026975162,0.000014029515,0.00146975,0.00026313786],"about_ca_topic_score_codex":0.000030591415,"about_ca_topic_score_gemma":0.000017091472,"teacher_disagreement_score":0.5200401,"about_ca_system_score_codex":0.000059716596,"about_ca_system_score_gemma":0.000007697956,"threshold_uncertainty_score":0.9008291},"labels":[],"label_agreement":null},{"id":"W2101278913","doi":"10.1109/twc.2006.1638659","title":"Efficient channel utilization for real-time video in OVSF-CDMA systems with QoS assurance","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","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":"University of Waterloo","funders":"","keywords":"Computer science; Computer network; Quality of service; Code division multiple access; Markov process; Frame (networking); Channel (broadcasting); Network packet; Real-time computing; Bandwidth (computing); Channel allocation schemes; Wireless; Telecommunications","score_opus":0.018152451352783483,"score_gpt":0.23956742465749775,"score_spread":0.22141497330471427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101278913","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":[0.019503064,0.00027998,0.97662824,0.00012253033,0.00030604255,0.0012796647,0.000118944896,0.00067258417,0.0010889467],"genre_scores_gemma":[0.98868173,0.00084404484,0.008449555,0.000009070846,0.000053814245,0.0015005828,0.00013517575,0.000117089476,0.00020891901],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99852276,0.00009550132,0.0005189994,0.00028717777,0.00020583897,0.00036970517],"domain_scores_gemma":[0.998028,0.0004570364,0.000109078355,0.0011750532,0.00016917627,0.000061646206],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015896888,0.00028420388,0.00032418716,0.00031409215,0.00035126365,0.00005749452,0.00043531824,0.00014978381,0.0000062197546],"category_scores_gemma":[0.0000030589968,0.0003071552,0.00006923,0.00090849405,0.00010795891,0.00016429,0.0000027460335,0.00026406007,0.000019610108],"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":[0.00003916795,0.0002395158,0.000008784545,0.000067986,0.000025086267,5.183591e-7,0.00012138072,0.9957865,0.0015166289,0.0005926022,0.0001229504,0.0014789],"study_design_scores_gemma":[0.00087050867,0.000047155234,0.00015613227,0.00028650626,0.000032070206,0.0000049008595,0.00006874676,0.9957615,0.0020947857,0.000028782672,0.00031968343,0.00032920734],"about_ca_topic_score_codex":0.00014320195,"about_ca_topic_score_gemma":0.0007683712,"teacher_disagreement_score":0.9691787,"about_ca_system_score_codex":0.0003042323,"about_ca_system_score_gemma":0.000042095722,"threshold_uncertainty_score":0.9999381},"labels":[],"label_agreement":null},{"id":"W2101755106","doi":"10.1109/wimob.2008.70","title":"Proportional Fairness for MIMO Multi-user Schedulers with Traffic Arrival Process","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 du Québec à Montréal","funders":"","keywords":"Computer science; Fairness measure; Computer network; Scheduling (production processes); Network packet; Fair queuing; Max-min fairness; MIMO; Network scheduler; Telecommunications link; Maximum throughput scheduling; Transmission delay; Quality of service; Wireless; Real-time computing; Throughput; Processing delay; Round-robin scheduling; Resource allocation; Dynamic priority scheduling; Channel (broadcasting); Mathematical optimization; Telecommunications; Mathematics","score_opus":0.014704831874638643,"score_gpt":0.22858124262737886,"score_spread":0.21387641075274022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101755106","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":[0.26464164,0.00003193062,0.7341097,0.0000227426,0.00007656186,0.00042374726,0.0000037263069,0.0005157408,0.00017418578],"genre_scores_gemma":[0.8222741,0.0000143280295,0.17671193,0.00001596777,0.000081851875,0.00020113516,0.00004683021,0.00005940323,0.0005944557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923366,0.00000381328,0.00016935197,0.0001908577,0.0001523575,0.00024994384],"domain_scores_gemma":[0.9996544,0.00001814127,0.00003108014,0.000110387926,0.0001186221,0.00006737794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029985462,0.00015973918,0.0001386515,0.000051608313,0.00009940247,0.000009655636,0.00008553159,0.00006426895,0.000034424844],"category_scores_gemma":[0.000009002987,0.00013389967,0.000030964035,0.00019647492,0.000057035802,0.00027109854,0.0000045588827,0.000083201325,0.000007100758],"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":[0.00003312749,0.000037675803,0.00060170953,0.00006481134,0.00002413545,0.0000032445357,0.00011874766,0.99788386,0.000057681198,0.00027868623,0.0001906547,0.00070569164],"study_design_scores_gemma":[0.0011650232,0.000040667095,0.00074179895,0.00002512433,0.0000099795225,0.0000269404,0.00010287959,0.9949892,0.002025334,0.000013064326,0.00058416,0.00027582716],"about_ca_topic_score_codex":3.4797173e-7,"about_ca_topic_score_gemma":0.000011881056,"teacher_disagreement_score":0.55763245,"about_ca_system_score_codex":0.00004303456,"about_ca_system_score_gemma":0.00004102498,"threshold_uncertainty_score":0.546027},"labels":[],"label_agreement":null},{"id":"W2102105576","doi":"10.1109/tcomm.2009.03.070115","title":"Optimal adaptive modulation and coding with switching costs","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Link adaptation; Fading; Coding (social sciences); Computer science; Markov decision process; Adaptive coding; Mathematical optimization; Monotonic function; Markov process; Control theory (sociology); Channel (broadcasting); Mathematics; Algorithm; Telecommunications","score_opus":0.015728875812314063,"score_gpt":0.23497690477160763,"score_spread":0.21924802895929357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102105576","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":[0.011870294,0.00013172353,0.9855184,0.00022875857,0.000049375634,0.00021843554,0.000007788335,0.00039936212,0.0015758419],"genre_scores_gemma":[0.8884227,0.00082217046,0.110621676,0.00003571288,0.000011411769,0.00003389395,0.000008400577,0.00002430303,0.000019715879],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994309,0.000033407043,0.0001611586,0.00013021164,0.00009623509,0.00014807437],"domain_scores_gemma":[0.9991887,0.00011684645,0.00003348224,0.0005494241,0.00005143986,0.000060108432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051810657,0.00013945272,0.00011494793,0.000118273805,0.00036500063,0.000037107304,0.00016541524,0.00005723861,0.000005411282],"category_scores_gemma":[0.0000012886426,0.0001476939,0.000022485283,0.00028273065,0.000040768165,0.00034680523,0.0000012163887,0.00029846994,0.0000050604713],"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":[0.000016751816,0.000035445373,0.0000030420379,0.0000021385188,0.000019164207,2.8586012e-7,0.00022968803,0.9340989,0.0012207404,0.00063779845,0.0000073559295,0.06372872],"study_design_scores_gemma":[0.00029427497,0.0000843974,0.00032650516,0.00007440125,0.000024100831,0.00000927067,0.00010706935,0.9975525,0.0012023731,0.0000935063,0.000062412975,0.00016920375],"about_ca_topic_score_codex":0.000005421496,"about_ca_topic_score_gemma":0.000052071544,"teacher_disagreement_score":0.8765524,"about_ca_system_score_codex":0.0001257466,"about_ca_system_score_gemma":0.000009473323,"threshold_uncertainty_score":0.6022783},"labels":[],"label_agreement":null},{"id":"W2102186816","doi":"10.1002/sat.926","title":"Efficient packet scheduling for heterogeneous multimedia provisioning over broadband satellite networks: An adaptive multidimensional QoS‐based design","year":2008,"lang":"en","type":"article","venue":"International Journal of Satellite Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Quality of service; Computer network; Network packet; Scheduling (production processes); Provisioning; Broadband; Distributed computing; Multimedia; Telecommunications","score_opus":0.04378986201401481,"score_gpt":0.28058245937935866,"score_spread":0.23679259736534386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102186816","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":[0.036057897,0.05859638,0.90374595,0.000053043554,0.0010408871,0.00038205623,0.000009396547,0.00008267077,0.000031741314],"genre_scores_gemma":[0.6052501,0.039120127,0.35487968,0.00005935915,0.00056351395,0.00001655886,0.00006087442,0.00004724263,0.0000024949675],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982379,0.00014332714,0.000763291,0.0002056798,0.0003459551,0.00030385217],"domain_scores_gemma":[0.9974543,0.0010091544,0.00040005604,0.0003665993,0.0006048594,0.00016506309],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00051646226,0.00025699128,0.00030494016,0.00024169555,0.00033788284,0.00007301643,0.0005296452,0.00012291258,0.0000043946966],"category_scores_gemma":[0.000025824973,0.00025580337,0.00012492816,0.00019643675,0.00016425665,0.00024614556,0.00010036121,0.0003520145,6.386512e-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":[0.00018641209,0.000090604255,0.00054987724,0.0000055554165,0.00012085056,0.000010918041,0.0002849162,0.8395723,0.00034306775,0.000043953092,0.0000045158054,0.158787],"study_design_scores_gemma":[0.0013096181,0.00014971105,0.00033816864,0.00042613852,0.000035431844,0.00012416179,0.000041727373,0.9916668,0.00019806784,0.0000422671,0.005412645,0.0002552774],"about_ca_topic_score_codex":0.000002546904,"about_ca_topic_score_gemma":0.0000062725976,"teacher_disagreement_score":0.56919223,"about_ca_system_score_codex":0.00015662718,"about_ca_system_score_gemma":0.000056562214,"threshold_uncertainty_score":0.9999894},"labels":[],"label_agreement":null},{"id":"W2102325130","doi":"10.1109/iwqos.2008.22","title":"Dynamic Control of Tunable Sub-Optimal Algorithms for Scheduling of Time-Varying Wireless Networks","year":2008,"lang":"en","type":"article","venue":"International Workshop on Quality of Service","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Computer science; Scheduling (production processes); Queue; Schedule; Algorithm; Dynamic priority scheduling; Asymptotically optimal algorithm; Mathematical optimization; Distributed computing; Computer network; Mathematics","score_opus":0.02259317062480769,"score_gpt":0.2842929873294574,"score_spread":0.2616998167046497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102325130","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":[0.3054946,0.00020684101,0.69335926,0.00013054033,0.0002702676,0.00024118774,0.00006659954,0.00006816536,0.00016254114],"genre_scores_gemma":[0.96177846,0.000229084,0.037513927,0.00010148404,0.00009270332,0.000030041489,0.00015777725,0.000052162886,0.000044372122],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819344,0.000043854314,0.0008951222,0.00022971885,0.00039734453,0.00024050161],"domain_scores_gemma":[0.99782896,0.0008128386,0.0004184565,0.0002444153,0.000641981,0.00005333458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035308834,0.00020696301,0.0005015866,0.00014650673,0.000051261988,0.0000070232877,0.00036573142,0.00015934018,0.00003247253],"category_scores_gemma":[0.000068574605,0.00024241405,0.0001402694,0.00032998074,0.00006701237,0.00022529226,0.000038326314,0.0001840037,0.0000030993933],"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":[0.00031198055,0.00009263555,0.000205094,0.00017594491,0.00019128465,7.5498775e-7,0.00017571075,0.98500484,0.010586988,0.00041666807,0.00001849159,0.0028195954],"study_design_scores_gemma":[0.0013210647,0.000030273699,0.00046770196,0.00036153002,0.00001869222,0.0000024717197,0.00006174636,0.9922102,0.005201043,0.00011009787,0.000019457244,0.0001957265],"about_ca_topic_score_codex":0.000028384164,"about_ca_topic_score_gemma":0.000014066404,"teacher_disagreement_score":0.65628386,"about_ca_system_score_codex":0.00009736474,"about_ca_system_score_gemma":0.000026995533,"threshold_uncertainty_score":0.9885358},"labels":[],"label_agreement":null},{"id":"W2102480603","doi":"10.1109/twc.2007.05162","title":"Adaptive scheduling for MIMO wireless networks: cross-layer approach and application to HSDPA","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":39,"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":"Medical Research Council","keywords":"Computer science; MIMO; Link adaptation; Scheduling (production processes); Telecommunications link; Computer network; Network packet; Wireless; Multi-user MIMO; Maximum throughput scheduling; Transmitter power output; Wireless network; Power control; Real-time computing; Round-robin scheduling; Fading; Fair-share scheduling; Channel (broadcasting); Mathematical optimization; Power (physics); Telecommunications; Mathematics","score_opus":0.023476128838670163,"score_gpt":0.2819182666598898,"score_spread":0.2584421378212196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102480603","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":[0.017927662,0.00030625885,0.9787424,0.000099612014,0.00023423774,0.0015555369,0.000055347024,0.0005574899,0.0005214578],"genre_scores_gemma":[0.8206283,0.0005952065,0.17732568,0.000093876195,0.00008092136,0.0010525563,0.00005215835,0.000120002034,0.00005132622],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99821395,0.000049097987,0.00057538674,0.00044219737,0.00018757976,0.000531816],"domain_scores_gemma":[0.99746764,0.0005752919,0.00009950893,0.0013724655,0.00024022847,0.00024485213],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040266098,0.00035414658,0.00033264526,0.0002972912,0.00081688364,0.00009344464,0.00062368903,0.00025199982,0.0000032418566],"category_scores_gemma":[0.0000052383525,0.00042539556,0.000107390515,0.0008555626,0.00019504568,0.00028510805,0.0000115263365,0.00052027096,0.000011341141],"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":[0.000074937554,0.00014385987,0.000024344616,0.000030923344,0.00006375464,1.3998711e-7,0.00029430143,0.9090272,0.0018792008,0.0018703267,0.000018089475,0.086572886],"study_design_scores_gemma":[0.00057630055,0.000059108123,0.00015619441,0.000058292822,0.000049938284,0.000005568108,0.00024193329,0.99378496,0.0039805714,0.000096426535,0.00055232254,0.0004383642],"about_ca_topic_score_codex":0.000018028271,"about_ca_topic_score_gemma":0.00018226275,"teacher_disagreement_score":0.80270064,"about_ca_system_score_codex":0.00022900265,"about_ca_system_score_gemma":0.000023039234,"threshold_uncertainty_score":0.9998198},"labels":[],"label_agreement":null},{"id":"W2102568874","doi":"10.1109/vetecs.2008.377","title":"Interference Avoidance through Dynamic Downlink OFDMA Subchannel Allocation using Intercell Coordination","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Throughput; Base station; Computer science; Interference (communication); Telecommunications link; Enhanced Data Rates for GSM Evolution; Computer network; Orthogonal frequency-division multiplexing; Scheme (mathematics); Cellular network; Channel allocation schemes; Real-time computing; Telecommunications; Channel (broadcasting); Wireless; Mathematics","score_opus":0.020990001062992418,"score_gpt":0.23761341211938197,"score_spread":0.21662341105638955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102568874","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":[0.21476887,0.00024393936,0.78308463,0.00006569419,0.00036192586,0.00014782304,0.0000025258544,0.00043434638,0.0008902392],"genre_scores_gemma":[0.9616733,0.0007921799,0.036934502,0.000044835408,0.0000637552,0.0000213894,0.00004449529,0.000045904162,0.0003796172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999131,0.000021634118,0.00027804857,0.00022202823,0.00011637806,0.00023087098],"domain_scores_gemma":[0.99956256,0.00003411201,0.000058532445,0.00019765446,0.00011098264,0.00003614524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004603536,0.00018482137,0.00015859825,0.00007409401,0.000112665984,0.000017536426,0.00014550127,0.0000963107,0.000064782354],"category_scores_gemma":[0.0000145706645,0.00019952032,0.000036208705,0.00031933107,0.000049202903,0.00065670675,0.000033385342,0.00016148087,0.00003430985],"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":[0.0000065668482,0.000015550047,0.00011674852,0.000028311537,0.000012133681,0.0000018596936,0.00053661456,0.9809003,0.015504507,0.00027489202,0.00013295839,0.002469553],"study_design_scores_gemma":[0.00020168688,0.00001544925,0.00020493263,0.0000752562,0.000007661517,0.000015131163,0.00006932188,0.99047035,0.008334349,0.00027538117,0.00010548334,0.00022499851],"about_ca_topic_score_codex":0.000029189401,"about_ca_topic_score_gemma":0.00004721905,"teacher_disagreement_score":0.74690443,"about_ca_system_score_codex":0.00024075297,"about_ca_system_score_gemma":0.000013608986,"threshold_uncertainty_score":0.81362027},"labels":[],"label_agreement":null},{"id":"W2102685832","doi":"10.1109/vetecs.2009.5073552","title":"Fair and Efficient Scheduling for Telemedicine Traffic Transmission over Wireless Cellular Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McMaster University","funders":"","keywords":"Telemedicine; Computer network; Computer science; Quality of service; Wireless; Scheduling (production processes); Wireless network; Bandwidth (computing); Telecommunications; Engineering; Health care","score_opus":0.0044650995011593754,"score_gpt":0.20434708896643738,"score_spread":0.19988198946527802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102685832","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":[0.23564094,0.0012148644,0.76214427,0.00006301103,0.000111998685,0.00032240484,6.6573966e-7,0.0003648372,0.00013703253],"genre_scores_gemma":[0.9615861,0.00034676987,0.037669253,0.000073753166,0.00020626368,0.000012679654,0.000028181497,0.000037983747,0.000039012004],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911606,0.000007720159,0.00023952786,0.00021301523,0.00011061287,0.000313081],"domain_scores_gemma":[0.9996587,0.00005753442,0.000024214733,0.00011889299,0.000027227112,0.00011342837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009856978,0.00018545952,0.00020451978,0.000064427084,0.00008332304,0.000018422965,0.000063405925,0.00011232444,0.000020752457],"category_scores_gemma":[0.000003648607,0.00016712333,0.000041126306,0.00018669604,0.000020749998,0.000071929666,0.000004627952,0.00012658956,5.9567884e-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":[0.000017363212,0.000015863847,0.000004840136,0.00002946923,0.0000065518366,0.0000012678742,0.000062104045,0.85333985,0.0028894972,0.00024021376,0.000101469435,0.14329153],"study_design_scores_gemma":[0.00089906796,0.00007045592,0.000080731945,0.00007751566,0.000018317076,0.000001880937,0.00002843221,0.996214,0.0017032963,0.000030279416,0.0006717623,0.00020428865],"about_ca_topic_score_codex":3.0197924e-7,"about_ca_topic_score_gemma":6.2205766e-7,"teacher_disagreement_score":0.7259452,"about_ca_system_score_codex":0.00003436386,"about_ca_system_score_gemma":0.000004727347,"threshold_uncertainty_score":0.68150914},"labels":[],"label_agreement":null},{"id":"W2103465373","doi":"10.1109/vetecs.2004.1390596","title":"Dynamic resource allocation for multimedia services over OFDM downlink in cellular systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Computer science; Telecommunications link; Quality of service; Orthogonal frequency-division multiplexing; Resource allocation; Computer network; Queueing theory; Throughput; Broadband; Channel (broadcasting); Resource management (computing); Spectral efficiency; Multimedia; Broadband networks; Real-time computing; Telecommunications; Wireless","score_opus":0.0032466309316063775,"score_gpt":0.20094760017676494,"score_spread":0.19770096924515856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103465373","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":[0.09476573,0.0012010237,0.90141016,0.00007179885,0.0002185215,0.00072773587,0.000008648157,0.0004919007,0.0011044795],"genre_scores_gemma":[0.95312643,0.00007221635,0.045864496,0.000037231835,0.00013043753,0.000098527475,0.00021727574,0.000048025475,0.00040538565],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992859,0.000011315168,0.0002494434,0.00015494067,0.00009138484,0.00020703304],"domain_scores_gemma":[0.9996743,0.00005982004,0.000033571705,0.00016847366,0.000026229947,0.000037568076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008876958,0.000123002,0.0001298835,0.00008970819,0.000022634877,0.0000223724,0.000096495496,0.00010036953,0.000016247755],"category_scores_gemma":[0.000003942238,0.00012899125,0.00002307901,0.0001579854,0.000007081073,0.00022234322,0.000011306058,0.00007228724,0.000020326128],"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":[0.0000059258955,0.0000105039135,0.000086693246,0.00011932795,0.000006664706,2.7580774e-7,0.00017714991,0.99158776,0.0025749912,0.00009674268,0.00011530516,0.00521869],"study_design_scores_gemma":[0.0004579981,0.000006248286,0.00018585748,0.000053138727,0.000005087513,4.0318193e-7,0.00009136845,0.98936427,0.0006710749,0.00001046935,0.009005912,0.00014814608],"about_ca_topic_score_codex":0.000018324658,"about_ca_topic_score_gemma":0.00024931462,"teacher_disagreement_score":0.85836065,"about_ca_system_score_codex":0.00015782475,"about_ca_system_score_gemma":0.0000039433044,"threshold_uncertainty_score":0.52601105},"labels":[],"label_agreement":null},{"id":"W2103599226","doi":"10.1109/aina.2006.60","title":"A Study for Providing Better Quality of Service to VoIP Users","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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","funders":"","keywords":"Voice over IP; Quality of service; Computer science; Computer network; Service provider; Telephony; Scheduling (production processes); Telephone network; Softswitch; Mobile communications over IP; Service (business); Telecommunications; Mobile radio telephone; The Internet; Business; Engineering; Mobile telephony; World Wide Web; Telephone line; Operations management","score_opus":0.025100335445504364,"score_gpt":0.2818225144576831,"score_spread":0.2567221790121787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103599226","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":[0.5158063,0.0000039181855,0.48289943,0.00013333661,0.00004944512,0.00052929274,0.0000032084952,0.00013396263,0.0004410832],"genre_scores_gemma":[0.9351383,1.456213e-7,0.06441732,0.0001427591,0.00006225496,0.00008581026,0.000008185847,0.000024335277,0.000120895864],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994524,0.000010542123,0.00022088623,0.00010544934,0.00008018,0.00013052039],"domain_scores_gemma":[0.99969435,0.000059103364,0.000024010364,0.00013500878,0.000067018336,0.0000205357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010439268,0.00007642816,0.00012444434,0.00003805959,0.000021313706,0.000007937664,0.000064933665,0.00002405803,0.000006867764],"category_scores_gemma":[0.000009426693,0.00007696044,0.000019555171,0.00020626828,0.0000025901425,0.0000919131,0.000015373453,0.000026502852,0.0000029854448],"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":[0.0000106416255,0.000031635314,0.005696027,0.000057459147,0.0000103584125,1.0995352e-7,0.00019910747,0.9902806,0.0022193864,0.00019185041,0.0007980598,0.0005047554],"study_design_scores_gemma":[0.0027545767,0.00023143494,0.044514928,0.000062616156,0.00004992432,5.6351655e-7,0.0017570128,0.91514266,0.031437576,0.0009191111,0.0022897637,0.00083985506],"about_ca_topic_score_codex":0.00010979937,"about_ca_topic_score_gemma":0.00083629566,"teacher_disagreement_score":0.41933197,"about_ca_system_score_codex":0.000032785974,"about_ca_system_score_gemma":0.000003059366,"threshold_uncertainty_score":0.31383556},"labels":[],"label_agreement":null},{"id":"W2103646184","doi":"10.1109/vetec.1998.686229","title":"An algorithm for maximal resource utilization in wireless multimedia CDMA communications","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Wireless; Quality of service; Resource allocation; Wireless network; Computational complexity theory; Optimization problem; Mathematical optimization; Algorithm; Code division multiple access; Computer network; Distributed computing; Telecommunications; Mathematics","score_opus":0.037161270119549,"score_gpt":0.2667786067010983,"score_spread":0.22961733658154931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103646184","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":[0.0018260321,0.00023859242,0.9943751,0.000050188486,0.000061223625,0.00037376626,0.0000143145935,0.00045680036,0.0026039735],"genre_scores_gemma":[0.42849958,0.00043815718,0.5702635,0.000044653567,0.000069254726,0.0001442576,0.00031338254,0.000062984334,0.00016422129],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993015,0.000028571048,0.00022992473,0.00014631532,0.00007791074,0.00021576368],"domain_scores_gemma":[0.9993047,0.00008130001,0.000026137726,0.0004895502,0.000040190454,0.000058092948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000073810756,0.0001184534,0.00012246994,0.000104907005,0.00006680736,0.000022296215,0.0002510859,0.00009127893,0.00006498128],"category_scores_gemma":[0.000010014309,0.0001371216,0.00002250827,0.00030700388,0.000035815287,0.00028404203,0.000022929215,0.000104329345,0.000012066892],"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":[0.0000017990781,0.00006663625,0.0001225163,0.000008754981,0.00000476076,3.9110077e-7,0.00026258506,0.45194557,0.00014421712,0.00048331093,0.00054739224,0.54641205],"study_design_scores_gemma":[0.00045969218,0.000019020412,0.00018031854,0.000014053447,0.0000039733104,0.0000011133716,0.00009281439,0.99435455,0.00041161114,0.00005078956,0.004254439,0.00015763551],"about_ca_topic_score_codex":0.0000047333483,"about_ca_topic_score_gemma":0.00007137358,"teacher_disagreement_score":0.5462544,"about_ca_system_score_codex":0.00007220266,"about_ca_system_score_gemma":0.0000023461414,"threshold_uncertainty_score":0.55916566},"labels":[],"label_agreement":null},{"id":"W2103806271","doi":"10.1109/tmm.2010.2076799","title":"Energy-Efficient Multicasting of Scalable Video Streams Over WiMAX Networks","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":77,"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":"Computer science; Multicast; Energy consumption; WiMAX; Computer network; Scalability; Quality of service; Video quality; Wireless; Real-time computing; IMT Advanced; Mobile computing; Distributed computing; Mobile technology; Mobile Web; Telecommunications","score_opus":0.005238289156049966,"score_gpt":0.205590914934917,"score_spread":0.20035262577886703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103806271","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":[0.06847168,0.00004150023,0.92874604,0.0000055473356,0.0018154393,0.00014298559,0.000022997914,0.00034733358,0.00040650155],"genre_scores_gemma":[0.9579824,0.000055066692,0.0416098,0.00001414989,0.00013933677,0.00004342424,0.000010405931,0.00007627041,0.00006911756],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987978,0.00001930082,0.00035820412,0.00024602105,0.00021709157,0.00036162802],"domain_scores_gemma":[0.9991065,0.00027781952,0.00006393422,0.0003372603,0.00007531593,0.0001391586],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008333186,0.00023579563,0.00023575098,0.00015212844,0.00009658044,0.000016947626,0.00013716928,0.00019775645,0.0002153186],"category_scores_gemma":[0.000008660726,0.0002511858,0.00009715897,0.00038749605,0.00009473188,0.00012596592,0.000001347366,0.00047983177,0.00001351281],"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":[0.000015762218,0.000094878465,0.000017504854,0.000011767513,0.000027178208,0.0000015389998,0.00007687679,0.816316,0.010687372,0.0000072225293,0.000030735457,0.17271318],"study_design_scores_gemma":[0.0005713889,0.000022497363,0.00008622259,0.000045973316,0.000029770421,0.0000034383231,0.00001603683,0.94949967,0.04940527,0.0000045644356,0.00009850061,0.00021665433],"about_ca_topic_score_codex":0.00003552527,"about_ca_topic_score_gemma":0.00010640729,"teacher_disagreement_score":0.88951075,"about_ca_system_score_codex":0.000050998904,"about_ca_system_score_gemma":0.000014073956,"threshold_uncertainty_score":0.99999404},"labels":[],"label_agreement":null},{"id":"W2103840610","doi":"10.1109/vetecs.2008.220","title":"Performance Comparison of Max-Delay Constrained Schedulers in Rayleigh Fading Channels","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Rayleigh fading; Computer science; Network packet; Fading; Scheduling (production processes); Energy consumption; Schedule; Wireless; Computer network; Channel (broadcasting); Efficient energy use; Mathematical optimization; Telecommunications; Engineering; Mathematics; Electrical engineering","score_opus":0.020755026866117087,"score_gpt":0.23446423456207013,"score_spread":0.21370920769595306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103840610","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":[0.8630623,0.00011242068,0.12962365,0.0000066831176,0.00016654268,0.00012168824,9.105309e-7,0.0001669668,0.006738805],"genre_scores_gemma":[0.9792088,0.0001902212,0.020460328,0.000006652602,0.000030457313,0.000009450819,0.000008070659,0.000023752813,0.00006221736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925214,0.000008674316,0.00030976732,0.00010882269,0.00010372104,0.00021689225],"domain_scores_gemma":[0.99975055,0.000034374487,0.00003713983,0.00011292653,0.000027241527,0.00003775858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051841143,0.00011892049,0.00023396869,0.00012657495,0.000033432996,0.0000030712456,0.00008312859,0.000068057605,0.00006439154],"category_scores_gemma":[0.000007651786,0.00012720031,0.000024048928,0.0003170689,0.00006229555,0.00019539126,0.000013163958,0.00012806793,0.000009493532],"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":[0.0000070539754,0.000014099992,0.021857347,0.000032204443,0.0000076191286,0.000002145289,0.00042878347,0.9744811,0.0010390827,0.00013655511,0.000058264253,0.0019357145],"study_design_scores_gemma":[0.0004319063,0.000019868066,0.001169936,0.000049453647,0.0000020257198,0.000006995731,0.00010197506,0.9835609,0.014467636,0.000006229334,0.000045737816,0.00013734201],"about_ca_topic_score_codex":0.0000029678781,"about_ca_topic_score_gemma":0.0000036620227,"teacher_disagreement_score":0.11614651,"about_ca_system_score_codex":0.000051690742,"about_ca_system_score_gemma":0.000010245271,"threshold_uncertainty_score":0.5187078},"labels":[],"label_agreement":null},{"id":"W2104395501","doi":"10.1109/ccece.2004.1345333","title":"Performance evaluation and total degradation of 16-QAM modulations over satellite channels","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University","funders":"","keywords":"QAM; Quadrature amplitude modulation; Constellation; Communications satellite; Nonlinear system; Computer science; Amplifier; Telecommunications; Star (game theory); Constellation diagram; Satellite constellation; Electronic engineering; Satellite; Topology (electrical circuits); Mathematics; Control theory (sociology); Bit error rate; Physics; Engineering; Bandwidth (computing); Channel (broadcasting); Artificial intelligence","score_opus":0.01169107288033343,"score_gpt":0.2303057815095715,"score_spread":0.21861470862923807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104395501","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":[0.7695188,0.00019939995,0.2284989,0.000012380174,0.00010444148,0.00017358745,0.0000011662794,0.00008153331,0.0014097748],"genre_scores_gemma":[0.9900729,0.00035809397,0.0093827965,0.000004587356,0.00003730476,0.000015655021,0.00005684337,0.000015341302,0.000056489407],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951077,0.000006753998,0.00015733128,0.00008943115,0.00014347215,0.00009225404],"domain_scores_gemma":[0.9997748,0.000011885399,0.000030128012,0.00009198967,0.00006731001,0.000023902727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007889753,0.00007645909,0.00007628845,0.00006547624,0.000032724336,0.000009188067,0.000021674276,0.00004169464,0.00003508903],"category_scores_gemma":[0.000008663214,0.00007993315,0.000012652226,0.00017228605,0.000015825033,0.00039079133,0.000007881409,0.000037604408,0.000002901383],"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":[0.0000023391367,0.0000059063273,0.0006699292,0.000014512942,0.000006225998,2.3647539e-8,0.0000638449,0.9562977,0.0011420596,0.00054976036,0.0000035975704,0.041244082],"study_design_scores_gemma":[0.00036797754,0.000016353348,0.024630822,0.000025280358,0.000011374322,0.0000016243312,0.000011963113,0.9668381,0.007702324,0.00029139954,0.000015306387,0.000087469394],"about_ca_topic_score_codex":0.0000051093957,"about_ca_topic_score_gemma":0.0000066256994,"teacher_disagreement_score":0.22055408,"about_ca_system_score_codex":0.00009482138,"about_ca_system_score_gemma":0.000008870717,"threshold_uncertainty_score":0.32595792},"labels":[],"label_agreement":null},{"id":"W2104725770","doi":"10.1109/wcnc.2005.1424709","title":"Efficient real-time video transmission in OVSF-CDMA system","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Quality of service; Computer network; Code division multiple access; Frame (networking); Network packet; Real-time computing; Bandwidth (computing); Channel (broadcasting); Transmission (telecommunications); Telecommunications link; Markov process; Transmission delay; Telecommunications","score_opus":0.0031008054556545092,"score_gpt":0.1862774133705042,"score_spread":0.18317660791484972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104725770","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":[0.14545332,0.00027113184,0.79300594,0.00007143733,0.00011606044,0.0003137667,0.0000013558437,0.0014821807,0.059284832],"genre_scores_gemma":[0.9595359,0.00007671927,0.039800625,0.000008625735,0.0000856457,0.000015277938,0.000007251553,0.00003995809,0.0004300094],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992635,0.00001593232,0.00023959312,0.00014320291,0.00011452204,0.00022322258],"domain_scores_gemma":[0.9997327,0.000031475196,0.0000150875,0.00014516078,0.00001362544,0.00006199478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008278385,0.00012032533,0.00014217682,0.00008977808,0.00002360375,0.000010458078,0.00006982729,0.000072645635,0.00011673705],"category_scores_gemma":[0.000002118347,0.000113523085,0.000026946023,0.00024220566,0.0000072712655,0.00005841839,0.000007380197,0.00007745883,0.00015935033],"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":[0.0000055030864,0.00001217598,0.000011575785,0.000037597234,0.0000028725021,0.0000026719056,0.00010180338,0.9777655,0.004875303,0.00028673562,0.00025935107,0.016638929],"study_design_scores_gemma":[0.00029508857,0.0000063122407,0.00012482567,0.00010748754,0.000003175593,0.0000032154173,0.000024319444,0.9949148,0.0029526032,0.000002239175,0.0014308164,0.00013509946],"about_ca_topic_score_codex":0.000006711622,"about_ca_topic_score_gemma":0.0000056446206,"teacher_disagreement_score":0.81408256,"about_ca_system_score_codex":0.00022518903,"about_ca_system_score_gemma":0.000005388899,"threshold_uncertainty_score":0.4629337},"labels":[],"label_agreement":null},{"id":"W2104783163","doi":"10.1109/iscc.2005.69","title":"Fair and Efficient Frame-Based Scheduling Algorithm for Multimedia Networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Latency (audio); Quality of service; Network packet; Scheduling (production processes); Computer network; The Internet; Voice over IP; Frame (networking); Real-time computing; Distributed computing; Multimedia; Telecommunications","score_opus":0.004778106267950455,"score_gpt":0.20740412598765579,"score_spread":0.20262601971970534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104783163","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":[0.0028871626,0.000611243,0.995348,0.00004636683,0.00018427226,0.0002890619,0.0000032517216,0.0004859367,0.0001447249],"genre_scores_gemma":[0.30255893,0.000032330336,0.69695985,0.00007082217,0.00026117536,0.00003833684,0.000021707814,0.000034513127,0.000022345153],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936813,0.0000048585634,0.0001530155,0.0001548833,0.00006711661,0.00025200483],"domain_scores_gemma":[0.99963576,0.00012846931,0.000018685612,0.0001069411,0.00003470736,0.00007546436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000065251545,0.00012986477,0.000119418524,0.000046893485,0.000056283756,0.000023634017,0.000049136153,0.00009459796,0.000019428844],"category_scores_gemma":[0.00001193477,0.00013142831,0.000028580493,0.00010938138,0.00002134623,0.00006354617,0.000010928143,0.00009934116,0.0000043104783],"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":[0.0000018164424,0.0000075914286,0.000010677353,0.0000061089604,0.0000052041546,1.4446371e-7,0.0000142068775,0.7264405,0.000026668919,0.000029127536,0.00006177216,0.27339622],"study_design_scores_gemma":[0.00060260046,0.000011827307,0.000024468563,0.000018708466,0.000007448317,5.38895e-7,0.000012449233,0.99737686,0.00074997323,0.000007724985,0.0010240807,0.00016333575],"about_ca_topic_score_codex":6.8807645e-7,"about_ca_topic_score_gemma":0.0000031536922,"teacher_disagreement_score":0.29967177,"about_ca_system_score_codex":0.00004583895,"about_ca_system_score_gemma":0.000005216167,"threshold_uncertainty_score":0.5359491},"labels":[],"label_agreement":null},{"id":"W2104864640","doi":"10.1109/wirelessvitae.2009.5172451","title":"Characterization and compensation of DC offset on adaptive MIMO direct conversion transceivers","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"University of Calgary","funders":"","keywords":"Offset (computer science); DC bias; Transmitter; MIMO; Transceiver; Control theory (sociology); Computer science; Gaussian; Electronic engineering; Channel state information; Bit error rate; Algorithm; Channel (broadcasting); Wireless; Voltage; Engineering; Telecommunications; Physics; Electrical engineering","score_opus":0.007301860264206749,"score_gpt":0.18574438768110993,"score_spread":0.17844252741690317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104864640","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":[0.5632012,0.00002315386,0.43062332,0.000071279625,0.00011068298,0.00024647557,0.000017037188,0.00022232675,0.0054845638],"genre_scores_gemma":[0.9983404,0.00021327812,0.0012194605,0.000044756212,0.000017398836,0.0000013271341,0.000114337316,0.000009411637,0.00003963022],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996095,0.0000136011095,0.000121100755,0.00009713456,0.00008118404,0.00007751451],"domain_scores_gemma":[0.9998207,0.000024624109,0.00003271977,0.00006448307,0.00003055664,0.000026934376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002883603,0.00008569611,0.00011432549,0.00006657994,0.000024615072,0.0000045503484,0.00002622884,0.000047497862,0.000023885916],"category_scores_gemma":[0.0000027124502,0.00008820139,0.000016506669,0.00011523255,0.000016078136,0.00017217005,0.0000012282079,0.000042891803,0.000003116959],"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":[0.00011853939,0.000032635166,0.0001795436,0.000025102712,0.000018015404,8.334232e-7,0.00040394592,0.71800184,0.25063318,0.0012941131,0.00009135088,0.029200902],"study_design_scores_gemma":[0.0005976963,0.00019833019,0.023721563,0.000063886604,0.0000146314005,7.68176e-7,0.00004885392,0.8320014,0.14287066,0.000047394424,0.0002702228,0.00016460476],"about_ca_topic_score_codex":0.0000012794964,"about_ca_topic_score_gemma":0.0000011677063,"teacher_disagreement_score":0.43513924,"about_ca_system_score_codex":0.000029639072,"about_ca_system_score_gemma":0.0000025227826,"threshold_uncertainty_score":0.35967484},"labels":[],"label_agreement":null},{"id":"W2104919294","doi":"10.1109/mcom.2008.4623700","title":"Book reviews (3 books reviewed)","year":2008,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; WiMAX; Zhàng; Implementation; Cryptography; Wireless; Wireless network; Computer network; Telecommunications; Computer security; Software engineering; China; Political science; Law","score_opus":0.04101154118357375,"score_gpt":0.2724126039030738,"score_spread":0.23140106271950006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104919294","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010757518,0.70186216,0.20162243,0.0007568343,0.00058207003,0.0009893274,0.00001029808,0.001191511,0.09287783],"genre_scores_gemma":[0.008270732,0.8977923,0.082909994,0.0012644497,0.0001954249,0.0003289914,0.00011116139,0.00009080092,0.0090361815],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99900424,0.00009158964,0.00046626432,0.00013474091,0.000094880226,0.0002082857],"domain_scores_gemma":[0.9974602,0.00007761793,0.00008100213,0.0022314147,0.00007559677,0.000074176176],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001384288,0.00018024322,0.00029293762,0.00007705525,0.00021643365,0.000010936955,0.00070223137,0.000059284423,0.00015267481],"category_scores_gemma":[0.00004304702,0.00018915403,0.000079186226,0.00033632733,0.00013078004,0.0002784021,0.00008028926,0.00026696987,0.001243486],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001696774,0.00003692364,0.000038457187,0.00006954923,0.000016670421,0.000002159807,0.000108969536,0.048426695,0.00079971657,0.00031422125,0.93582916,0.014355798],"study_design_scores_gemma":[0.00013166064,0.000007740649,0.000084791325,0.00010762694,0.000013361513,0.000025292988,0.0000010215961,0.05281744,0.00011864429,0.00003868165,0.9464669,0.00018680844],"about_ca_topic_score_codex":6.8063224e-7,"about_ca_topic_score_gemma":0.000007454106,"teacher_disagreement_score":0.19593012,"about_ca_system_score_codex":0.00007854561,"about_ca_system_score_gemma":0.000013335796,"threshold_uncertainty_score":0.9995342},"labels":[],"label_agreement":null},{"id":"W2105433213","doi":"10.1109/rws.2009.4957430","title":"Proportional fairness packet scheduling with transmit beamforming for multi-user MIMO systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 du Québec à Montréal","funders":"","keywords":"Computer science; Beamforming; Telecommunications link; Scheduling (production processes); Fairness measure; Network scheduler; Network packet; MIMO; Computer network; Transmission delay; Proportionally fair; Real-time computing; Round-robin scheduling; Processing delay; Throughput; Fair-share scheduling; Wireless; Telecommunications; Engineering; Quality of service","score_opus":0.014651126847970777,"score_gpt":0.23402469915955518,"score_spread":0.21937357231158439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105433213","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":[0.009731305,0.00017357178,0.98834723,0.00005431132,0.0001324574,0.0006810463,0.000006345198,0.00056179235,0.0003119371],"genre_scores_gemma":[0.56728077,0.00001749247,0.43202507,0.000020348776,0.00014083384,0.00008321383,0.0000489571,0.000039352813,0.00034397337],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991406,0.0000049787186,0.00024657848,0.00017964093,0.0001410905,0.00028708385],"domain_scores_gemma":[0.99966127,0.000021695452,0.00003843211,0.0001238806,0.00009050451,0.00006424708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000075991105,0.00017299384,0.00017810185,0.000059416016,0.00008165189,0.000038466675,0.00007591955,0.00007675947,0.000008685846],"category_scores_gemma":[0.000005565694,0.00014435039,0.000037582842,0.00016268229,0.000014396894,0.00035568065,0.0000025060915,0.00008831031,0.000003136855],"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":[0.000021650421,0.000016580783,0.00010231104,0.0000823077,0.000020821319,0.000001317342,0.00006353416,0.98989844,0.00040353314,0.004602538,0.000032864715,0.0047540967],"study_design_scores_gemma":[0.0008008733,0.00005232834,0.00011113353,0.000104800805,0.00001597788,0.000009810631,0.00011645751,0.99575204,0.0014452909,0.000046018184,0.0012978192,0.00024742814],"about_ca_topic_score_codex":0.0000016358428,"about_ca_topic_score_gemma":0.000007974433,"teacher_disagreement_score":0.5575495,"about_ca_system_score_codex":0.000060965715,"about_ca_system_score_gemma":0.000015768139,"threshold_uncertainty_score":0.5886438},"labels":[],"label_agreement":null},{"id":"W2105474904","doi":"10.1109/vtcf.2006.275","title":"Opportunistic QoS Enhanced Scheduler for Real-Time Traffic in Wireless Communication Systems","year":2006,"lang":"en","type":"article","venue":"IEEE Vehicular Technology Conference","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Computer network; Quality of service; Network packet; Network scheduler; Scheduling (production processes); Wireless; Provisioning; Throughput; Bandwidth (computing); Distributed computing; Real-time computing; Transmission delay; Processing delay; Telecommunications","score_opus":0.00936068934413427,"score_gpt":0.21549738514039862,"score_spread":0.20613669579626434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105474904","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":[0.61963373,0.0002362741,0.37749204,0.00008173824,0.00020221056,0.00070968445,0.000013201764,0.0011469757,0.00048416553],"genre_scores_gemma":[0.98979115,0.0004689207,0.008753685,0.000004298554,0.000050008573,0.0005938134,0.00016355123,0.000062506144,0.000112088346],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986909,0.000039712715,0.00046190692,0.00030744897,0.00009849477,0.00040152733],"domain_scores_gemma":[0.998975,0.000086747896,0.00011370517,0.000619517,0.00016930036,0.000035744742],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014894607,0.0002460956,0.0003764374,0.00035219168,0.00008183654,0.000035217276,0.00040977498,0.000460201,0.000007488791],"category_scores_gemma":[0.000020220672,0.00028639854,0.000040085135,0.00056191697,0.000160051,0.00014580644,0.00002558381,0.00028603923,0.000024153904],"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":[0.000007917864,0.00003533109,0.000040511663,0.000057176032,0.000014786291,0.0000053626704,0.000015602229,0.8564531,0.12036651,0.019493572,0.00012811797,0.0033820008],"study_design_scores_gemma":[0.00059387466,0.000029696057,0.00004856352,0.00021413984,0.000016936028,0.0000074765007,0.000046092067,0.97998804,0.017633984,0.000892319,0.00020831494,0.00032056196],"about_ca_topic_score_codex":0.00001882567,"about_ca_topic_score_gemma":0.0000712586,"teacher_disagreement_score":0.37015742,"about_ca_system_score_codex":0.00015201874,"about_ca_system_score_gemma":0.000046071887,"threshold_uncertainty_score":0.9999588},"labels":[],"label_agreement":null},{"id":"W2105808867","doi":"10.1109/wcnc.2005.1424595","title":"A new fairness index for radio resource allocation in wireless networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":147,"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":"Fairness measure; Computer science; Max-min fairness; Quality of service; Radio resource management; Resource allocation; Wireless network; Computer network; Wireless; Resource management (computing); Index (typography); Resource (disambiguation); Distributed computing; Telecommunications; Throughput","score_opus":0.005546826578741393,"score_gpt":0.20569930348608173,"score_spread":0.20015247690734034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105808867","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":[0.0045744176,0.00022959732,0.9926097,0.00016801336,0.00010199326,0.00036397844,5.166805e-7,0.00038530477,0.0015665188],"genre_scores_gemma":[0.95776,0.00008323701,0.040685266,0.0000738051,0.00051173085,0.00006844677,0.000044541564,0.00006117041,0.0007118504],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992007,0.000010916452,0.000245753,0.00017337852,0.00008331883,0.00028590305],"domain_scores_gemma":[0.9996377,0.00006798585,0.000027779624,0.00017319841,0.000022552724,0.000070741204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008819368,0.00014156765,0.00015318686,0.000094116156,0.000028414506,0.000023543687,0.00011845936,0.0001267911,0.000027801356],"category_scores_gemma":[0.0000073254946,0.000157886,0.000030224564,0.0003331231,0.000008733086,0.0002491296,0.000013264925,0.000121403544,0.0000049343516],"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":[0.000016579732,0.00000660655,0.0002752603,0.0000095451705,0.000005658069,2.3632174e-7,0.000068079826,0.85667944,0.00003347614,0.0015426525,0.0034154956,0.137947],"study_design_scores_gemma":[0.00070940057,0.00000814652,0.000486675,0.000028403434,0.0000035454498,0.0000014031353,0.000027309798,0.98773354,0.0002843451,0.000098198725,0.010431987,0.00018704997],"about_ca_topic_score_codex":0.000011764834,"about_ca_topic_score_gemma":0.0003116602,"teacher_disagreement_score":0.95318556,"about_ca_system_score_codex":0.00016535464,"about_ca_system_score_gemma":0.000014022893,"threshold_uncertainty_score":0.6438404},"labels":[],"label_agreement":null},{"id":"W2105842823","doi":"10.1109/vetecf.2009.5379110","title":"On Maximizing the Data Volume in a Wireless Sensor Network with Time-Varying Channels","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wireless sensor network; Computer science; Base station; Scheduling (production processes); Real-time computing; Volume (thermodynamics); Schedule; Data transmission; Transmitter power output; Channel (broadcasting); Transmission (telecommunications); Wireless; Wireless network; Computer network; Telecommunications; Engineering; Transmitter","score_opus":0.012538350399995195,"score_gpt":0.21158389496416807,"score_spread":0.19904554456417287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105842823","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":[0.053239606,0.00024294744,0.92964923,0.0008717221,0.00030164456,0.00073341257,0.0000073852925,0.0010470251,0.013907036],"genre_scores_gemma":[0.9789165,0.000083558465,0.019695086,0.0003918934,0.0003039037,0.000011130342,0.00007814971,0.000058774905,0.00046097502],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891126,0.000031158135,0.00019910595,0.00027818617,0.00016008715,0.00042022904],"domain_scores_gemma":[0.99913234,0.00009733465,0.000034552177,0.00067297556,0.000017951352,0.000044838467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016575478,0.00019756661,0.00019247296,0.00005263081,0.00008769975,0.00005564767,0.00035875954,0.00006372274,0.000049962095],"category_scores_gemma":[0.000010171623,0.00014207557,0.000014570048,0.0005111054,0.000020029991,0.00029383556,0.000047867867,0.0002500354,0.000052113828],"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":[0.000027973692,0.000011178362,0.00006671855,0.0000044960934,0.00001022549,0.000012635312,0.00005615363,0.9878836,0.000060807317,0.00033274855,0.0021315098,0.009401949],"study_design_scores_gemma":[0.00030267367,0.000039068356,0.00017554677,0.00012226173,0.000006531442,0.000008142573,0.0000158101,0.9984713,0.00006468076,0.00021133063,0.00037198985,0.00021065227],"about_ca_topic_score_codex":0.0000046317477,"about_ca_topic_score_gemma":0.000011817042,"teacher_disagreement_score":0.92567694,"about_ca_system_score_codex":0.00005762169,"about_ca_system_score_gemma":0.000008254266,"threshold_uncertainty_score":0.5793674},"labels":[],"label_agreement":null},{"id":"W2105916639","doi":"10.1109/wcnc.2008.356","title":"Statistical Connection Admission Control for Mobile WiMAX Systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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":"WiMAX; Computer science; Computer network; Coding (social sciences); Admission control; Quality of service; Real-time computing; Frame (networking); Connection (principal bundle); Variance (accounting); Wireless; Mathematics; Telecommunications; Statistics","score_opus":0.008590433358699433,"score_gpt":0.2232054443379469,"score_spread":0.21461501097924746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105916639","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":[0.0052365554,0.0002219894,0.9921341,0.0000047315643,0.00045111275,0.0005746329,0.000023879657,0.00048206077,0.00087091886],"genre_scores_gemma":[0.9824878,0.00008597356,0.016594999,0.000014616414,0.00015028575,0.00026626058,0.00005416982,0.00003286926,0.00031302896],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994861,0.000010828215,0.00016186728,0.00010792885,0.0000731452,0.00016014845],"domain_scores_gemma":[0.99962056,0.00015516156,0.000017569244,0.00008655391,0.000050101764,0.000070082606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000039256294,0.00008879892,0.00013208452,0.000029873467,0.00007539114,0.000008912537,0.000031427277,0.000058720518,0.000054849577],"category_scores_gemma":[0.00002760103,0.00008353422,0.000019462568,0.000061674196,0.0000148716135,0.00010036959,0.0000029050682,0.000047055615,0.000015032102],"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":[0.000020282489,0.000008493941,0.0000830187,0.00003231498,0.0000099537765,0.0000015004183,0.000016850789,0.9905672,0.00051125936,0.0020618183,0.005520254,0.0011670548],"study_design_scores_gemma":[0.00068712677,0.00006254545,0.00007592078,0.000010767745,0.0000070795427,0.000015378586,0.000027600383,0.99062794,0.00035106865,0.000053516185,0.007971088,0.000109939196],"about_ca_topic_score_codex":0.0000034117575,"about_ca_topic_score_gemma":9.924831e-7,"teacher_disagreement_score":0.97725123,"about_ca_system_score_codex":0.000057690188,"about_ca_system_score_gemma":0.000008656278,"threshold_uncertainty_score":0.3406427},"labels":[],"label_agreement":null},{"id":"W2106163264","doi":"10.1109/glocom.2005.1578237","title":"Realtime service provisioning in CDMA wireless cellular networks","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer network; Computer science; Quality of service; Code division multiple access; Service layer; Wireless network; Wireless; Provisioning; Mobile QoS; Resource allocation; Cellular network; Service (business); Service provider; Telecommunications","score_opus":0.01374594829628422,"score_gpt":0.24135443437532392,"score_spread":0.2276084860790397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106163264","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":[0.143459,0.005076936,0.77364844,0.004057132,0.0014849772,0.0024500096,0.00019362509,0.0031260543,0.0665038],"genre_scores_gemma":[0.9487149,0.0029966887,0.04673458,0.00041107417,0.0002491228,0.00019080161,0.0004371713,0.00008602987,0.00017960656],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966714,0.00021783367,0.0010881295,0.00055127556,0.00032467363,0.0011467091],"domain_scores_gemma":[0.9972098,0.00014434545,0.00022998912,0.0018272614,0.00028860767,0.0003000057],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036540427,0.00058076583,0.0006015754,0.00021195412,0.00034870094,0.00018861274,0.0015962,0.00042077314,0.00021160598],"category_scores_gemma":[0.00002433605,0.00069474836,0.000109842775,0.0016796413,0.00011213855,0.00079774513,0.00024328285,0.0008362176,0.00027237687],"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":[0.000015743788,0.00013970977,0.0006148085,0.000027327033,0.000039343642,0.0000048629086,0.00011185297,0.9285977,0.00016781055,0.0022158213,0.005275399,0.062789634],"study_design_scores_gemma":[0.0008408968,0.000022934102,0.0008819387,0.00020082976,0.000027978063,0.000022328391,0.000094245166,0.9699279,0.00022946724,0.00032912046,0.02673882,0.00068352965],"about_ca_topic_score_codex":0.00028197287,"about_ca_topic_score_gemma":0.0067338687,"teacher_disagreement_score":0.80525595,"about_ca_system_score_codex":0.0009906571,"about_ca_system_score_gemma":0.0001840831,"threshold_uncertainty_score":0.99955034},"labels":[],"label_agreement":null},{"id":"W2106188774","doi":"10.1109/lsp.2011.2110644","title":"Performance Analysis of Joint User Scheduling and Antenna Selection Over MIMO Fading Channels","year":2011,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":26,"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":"Rayleigh fading; MIMO; Computer science; Fading; Scheduling (production processes); Block code; 3G MIMO; Coding (social sciences); Electronic engineering; Telecommunications; Algorithm; Mathematical optimization; Decoding methods; Mathematics; Engineering; Channel (broadcasting); Statistics","score_opus":0.017963922635838483,"score_gpt":0.20701836204880925,"score_spread":0.18905443941297076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106188774","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":[0.5526669,0.00008270748,0.44702592,0.000005552622,0.000058887592,0.000042093958,5.779425e-7,0.00008841903,0.000028925419],"genre_scores_gemma":[0.98461866,0.000043208143,0.015118839,0.000081272425,0.00008400174,0.000007857181,0.0000038961216,0.000036898087,0.000005361956],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991377,0.000013255045,0.00026800067,0.00020057416,0.0001386677,0.00024181456],"domain_scores_gemma":[0.9997064,0.000013575896,0.000108885724,0.000069938156,0.000055350818,0.000045832745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011133579,0.00016176826,0.00025551667,0.00037741286,0.0000931984,0.000028542485,0.000062544816,0.000060565224,0.00001878097],"category_scores_gemma":[0.0000034595332,0.00017167868,0.000050412407,0.0008983047,0.000050323695,0.0005304823,0.000009812789,0.0001463937,8.7279693e-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":[0.000010499641,0.0000062115732,0.005428013,0.00011410645,0.0001235045,9.318171e-7,0.00067166245,0.7922639,0.19790444,0.0000010662433,0.000007656909,0.0034679875],"study_design_scores_gemma":[0.00012956579,0.000015338623,0.005423875,0.00014506404,0.00018088598,0.0000023723921,0.000022739478,0.95518196,0.03870778,0.0000038281255,0.0000031075097,0.0001834845],"about_ca_topic_score_codex":0.00000680675,"about_ca_topic_score_gemma":0.0000017667697,"teacher_disagreement_score":0.43195176,"about_ca_system_score_codex":0.000048342175,"about_ca_system_score_gemma":0.0000072623875,"threshold_uncertainty_score":0.70008534},"labels":[],"label_agreement":null},{"id":"W2106602359","doi":"10.1109/icc.2009.5198968","title":"Efficient Algorithms for Non-Realtime Video Multicasting in Wireless Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Multicast; Computer science; Computer network; Exploit; Wireless; Source-specific multicast; Channel (broadcasting); Reliability (semiconductor); Resource allocation; Session (web analytics); Multiplexing; Wireless network; Transmission (telecommunications); Distributed computing; Real-time computing; Telecommunications; Computer security","score_opus":0.00972781914807386,"score_gpt":0.2437490802559448,"score_spread":0.23402126110787094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106602359","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":[0.031891715,0.00006158368,0.9658609,0.00003892369,0.00021304586,0.00047917126,0.0000016230373,0.00035816614,0.0010948802],"genre_scores_gemma":[0.87500066,0.000024039658,0.124596834,0.000062377934,0.00017399149,0.00004147419,0.000019051135,0.000037778424,0.000043821754],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989202,0.000007976993,0.00030994494,0.00021659827,0.00009067349,0.00045458673],"domain_scores_gemma":[0.99954015,0.00015457762,0.00003130589,0.00015981373,0.000040428225,0.000073719544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012812196,0.00017716261,0.0002104982,0.00009250862,0.000049251343,0.000021952112,0.000101160906,0.00010336596,0.000008638656],"category_scores_gemma":[0.000020217072,0.00018481824,0.000044208304,0.0003331387,0.000012285091,0.00005997419,0.000012081095,0.00014202142,0.0000052323476],"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":[0.000008381166,0.000024779269,0.00003652559,0.0000099868,0.0000036649171,0.0000021573899,0.000047473248,0.90913314,0.00023511096,0.0001197139,0.000114971765,0.0902641],"study_design_scores_gemma":[0.00068174215,0.000030984484,0.0007060132,0.000062847,0.0000044308604,0.0000016465467,0.000018116018,0.9978749,0.00033438156,0.00003504788,0.00003334494,0.00021652547],"about_ca_topic_score_codex":0.000003894429,"about_ca_topic_score_gemma":0.0000092718,"teacher_disagreement_score":0.8431089,"about_ca_system_score_codex":0.000109216075,"about_ca_system_score_gemma":0.000006124193,"threshold_uncertainty_score":0.7536669},"labels":[],"label_agreement":null},{"id":"W2106829759","doi":"10.1109/wcnc.2005.1424682","title":"Mobility assisted opportunistic scheduling for downlink transmissions in cellular data networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":6,"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":"University of British Columbia","keywords":"Computer science; Scheduling (production processes); Workload; Telecommunications link; Proportionally fair; Computer network; Distributed computing; Round-robin scheduling; Fair-share scheduling; Real-time computing; Mathematical optimization; Quality of service; Mathematics","score_opus":0.04675159666678472,"score_gpt":0.27362178561373013,"score_spread":0.2268701889469454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106829759","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":[0.002430005,0.00043583877,0.9953338,0.00012439884,0.00013391505,0.0004312559,0.000035141977,0.00037151575,0.0007041272],"genre_scores_gemma":[0.7176958,0.00016941772,0.2809236,0.000035284036,0.00016864465,0.00004016521,0.0008504218,0.00003915931,0.000077508565],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889344,0.000018139339,0.00038043287,0.00030294948,0.0000820844,0.00032294795],"domain_scores_gemma":[0.99909246,0.0001487714,0.000027058979,0.00059050537,0.000029435609,0.00011176984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002549961,0.00015853858,0.00019606698,0.000060273123,0.000059673657,0.000021737675,0.0002834919,0.00013057882,0.000097669654],"category_scores_gemma":[0.00004183855,0.00016242001,0.000033767003,0.0002421182,0.000021237558,0.00030113573,0.000036926147,0.0001874562,0.0000034925395],"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":[0.000008425815,0.00004158641,0.000052198477,0.000029492105,0.000009098182,0.0000012968537,0.000013871767,0.946426,0.0004520594,0.00024379925,0.00020263712,0.05251958],"study_design_scores_gemma":[0.00042967356,0.0000070550054,0.00011873011,0.000038524795,0.000015064051,9.4588484e-7,0.000017589358,0.994247,0.00013329646,0.00006270462,0.0047383863,0.00019098376],"about_ca_topic_score_codex":0.0000028967004,"about_ca_topic_score_gemma":0.00007684489,"teacher_disagreement_score":0.71526575,"about_ca_system_score_codex":0.000085135645,"about_ca_system_score_gemma":0.0000219527,"threshold_uncertainty_score":0.66232955},"labels":[],"label_agreement":null},{"id":"W2106914338","doi":"10.1109/wcnc.2007.689","title":"A Hierarchical Model for Bandwidth Management and Admission Control in Integrated IEEE 802.16/802.11 Wireless Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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 Manitoba","funders":"","keywords":"Computer network; Computer science; Quality of service; Bandwidth (computing); Admission control; Bandwidth management; Bandwidth allocation; Dynamic bandwidth allocation; Call Admission Control; Wireless network; Wireless; Node (physics); Telecommunications; Engineering","score_opus":0.007207943429341873,"score_gpt":0.22270540768099661,"score_spread":0.21549746425165475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106914338","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":[0.023280567,0.00018737675,0.9745211,0.00004517934,0.00015701672,0.00074769347,0.000004839718,0.00028691292,0.0007693055],"genre_scores_gemma":[0.95059955,0.00030979095,0.04828193,0.00017670252,0.00007485136,0.00007835806,0.00004102665,0.00006210403,0.00037568255],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987118,0.000021002137,0.000372263,0.00028142935,0.00012960151,0.00048389964],"domain_scores_gemma":[0.99941033,0.00018882047,0.000033002725,0.00016472119,0.000041815623,0.00016128329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033732553,0.00023374264,0.00026882262,0.00016717832,0.00006172087,0.000028113347,0.000103737686,0.00019129312,0.00001198762],"category_scores_gemma":[0.000011050063,0.00021444407,0.000039355753,0.00028899027,0.000030610434,0.00015076842,0.000020708147,0.0002821367,7.199864e-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":[0.00016920241,0.000027958706,0.00052766665,0.000047583366,0.00002146679,0.000005901524,0.00006913984,0.9608552,0.000087289285,0.0013357898,0.0006769122,0.03617588],"study_design_scores_gemma":[0.002134196,0.000026356818,0.00029305017,0.000111940026,0.000016903568,0.0000019503245,0.00004250173,0.99620706,0.00011928413,0.00045815573,0.000337325,0.00025124892],"about_ca_topic_score_codex":0.000007015549,"about_ca_topic_score_gemma":0.00030213222,"teacher_disagreement_score":0.927319,"about_ca_system_score_codex":0.00015327767,"about_ca_system_score_gemma":0.000010582389,"threshold_uncertainty_score":0.8744775},"labels":[],"label_agreement":null},{"id":"W2107521218","doi":"10.1109/tsp.2010.2046894","title":"A Dynamical Games Approach to Transmission-Rate Adaptation in Multimedia WLAN","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","funders":"","keywords":"Computer science; Nash equilibrium; Scheduling (production processes); Markov decision process; Markov process; Wireless network; Computer network; Mathematical optimization; Fading; Channel (broadcasting); Wireless; Distributed computing; Telecommunications; Mathematics","score_opus":0.011242908686378993,"score_gpt":0.22709813937608112,"score_spread":0.2158552306897021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107521218","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":[0.023599906,0.00003121391,0.97504646,0.000035753812,0.0001648865,0.00028357294,0.0000053474964,0.00035839615,0.00047448036],"genre_scores_gemma":[0.8666462,0.000011993558,0.13305257,0.000035436613,0.000049878257,0.00010326178,0.000008687049,0.000058259804,0.00003372829],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989002,0.000028939696,0.00029716772,0.00029061784,0.00018162036,0.00030148876],"domain_scores_gemma":[0.9995912,0.00006941688,0.000028175671,0.00011451887,0.000047769612,0.00014893757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001301881,0.0002129558,0.00018523683,0.00028590398,0.0001088085,0.00005331742,0.00011753764,0.00015875736,0.000037180147],"category_scores_gemma":[0.000002639975,0.00022177723,0.000045966506,0.000626835,0.000034128956,0.0003576119,4.367448e-7,0.0006177276,0.000015794363],"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":[0.000031247513,0.000065866414,0.0000019003058,0.000036592028,0.000003993247,0.0000011713333,0.0007979655,0.6675812,0.029353365,0.0000026345067,0.0000023840173,0.30212167],"study_design_scores_gemma":[0.00039742197,0.000023914135,0.00007783105,0.00009090183,0.000011064372,0.0000050213075,0.00012951186,0.9905516,0.008335883,0.00005751378,0.00006837177,0.00025097845],"about_ca_topic_score_codex":0.0000054336483,"about_ca_topic_score_gemma":0.000044698812,"teacher_disagreement_score":0.84304625,"about_ca_system_score_codex":0.00007022972,"about_ca_system_score_gemma":0.000036481135,"threshold_uncertainty_score":0.9043813},"labels":[],"label_agreement":null},{"id":"W2107601408","doi":"10.1109/icc.2004.1312633","title":"Optimal and suboptimal scheduling over time varying flat fading channels","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Fading; Markov decision process; Scheduling (production processes); Mathematical optimization; Computer science; Markov process; Minification; Dynamic programming; Channel (broadcasting); Algorithm; Mathematics; Telecommunications; Statistics","score_opus":0.006876094702822668,"score_gpt":0.207351388169092,"score_spread":0.20047529346626933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107601408","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":[0.42503536,0.0002625809,0.57211715,0.000019892304,0.0001379984,0.00009785428,8.7222776e-7,0.0005265734,0.0018017308],"genre_scores_gemma":[0.7822382,0.00008980409,0.2173099,0.000026763802,0.00016142154,0.0000072075095,0.000009448341,0.000055277425,0.000101968886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991461,0.0000052905666,0.00018308051,0.0002113448,0.00011126413,0.00034291553],"domain_scores_gemma":[0.9997098,0.000030543153,0.000022526496,0.00012238402,0.000020420433,0.00009434484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006446598,0.00018920185,0.00017069496,0.00009274944,0.000095529955,0.000063072315,0.000070226924,0.0000929701,0.00011061044],"category_scores_gemma":[0.00001020621,0.0002048993,0.000030932457,0.00019430813,0.000026053234,0.00050557277,0.00004591382,0.00015153704,0.000050813243],"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":[0.000005233286,0.0000032492194,0.000043907417,0.000016272585,0.000017569197,0.00000628679,0.00015328327,0.9903635,0.008272046,0.00036388435,0.000012834604,0.000741933],"study_design_scores_gemma":[0.0005455172,0.000015839785,0.000040556384,0.000056886343,0.000009385823,0.000016180185,0.000011104608,0.989789,0.009066063,0.00014244208,0.00004572052,0.00026130877],"about_ca_topic_score_codex":0.0000032670514,"about_ca_topic_score_gemma":4.462556e-7,"teacher_disagreement_score":0.35720283,"about_ca_system_score_codex":0.00008960515,"about_ca_system_score_gemma":0.000007688921,"threshold_uncertainty_score":0.83555514},"labels":[],"label_agreement":null},{"id":"W2107706748","doi":"10.1109/twc.2009.080739","title":"Novel packet-level resource allocation with effective QoS provisioning for wireless mesh networks","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":44,"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":"Computer science; Subcarrier; Quality of service; Computer network; Network packet; Karush–Kuhn–Tucker conditions; Scheduling (production processes); Resource allocation; Wireless mesh network; Distributed computing; Provisioning; Wireless; Orthogonal frequency-division multiplexing; Channel (broadcasting); Wireless network; Mathematical optimization; Telecommunications","score_opus":0.017858834359282292,"score_gpt":0.24766339553190286,"score_spread":0.22980456117262058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107706748","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":[0.0049366136,0.00011101003,0.9906946,0.00048581118,0.00021679013,0.0020968567,0.00008662219,0.000971594,0.00040014487],"genre_scores_gemma":[0.93956316,0.00050073076,0.057869386,0.00016203054,0.00009928059,0.0013497467,0.00019436395,0.00013863905,0.00012268021],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998143,0.00010258875,0.00051581557,0.00043881402,0.0002739118,0.0005258314],"domain_scores_gemma":[0.99693465,0.0007692591,0.00015907166,0.0016993028,0.00027577195,0.000161954],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023372218,0.00045329542,0.00041130645,0.0002666032,0.0009218356,0.00010141935,0.00076031074,0.00025328243,0.000005912471],"category_scores_gemma":[0.000007353386,0.0004702437,0.0001412285,0.00091428723,0.00016396065,0.0004776543,0.000005068344,0.000716276,0.0000069575635],"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":[0.00010809056,0.0002709093,0.0000028408344,0.000023701641,0.00008934168,3.084271e-7,0.00032021696,0.7980718,0.0027367377,0.0017749071,0.00014357499,0.19645758],"study_design_scores_gemma":[0.0014566995,0.00028979374,0.0001777093,0.00033071794,0.00011416719,0.000013409937,0.00019411897,0.98849183,0.007692077,0.000062057385,0.0006043666,0.00057304977],"about_ca_topic_score_codex":0.0000109565635,"about_ca_topic_score_gemma":0.00019178035,"teacher_disagreement_score":0.9346265,"about_ca_system_score_codex":0.00032871572,"about_ca_system_score_gemma":0.000048460915,"threshold_uncertainty_score":0.99977493},"labels":[],"label_agreement":null},{"id":"W2107919046","doi":"10.1109/mnet.2007.314537","title":"Packet scheduling in 3.5G high-speed downlink packet access networks: breadth and depth","year":2007,"lang":"en","type":"article","venue":"IEEE Network","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":53,"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 Guelph; Queen's University","funders":"","keywords":"Computer science; UMTS frequency bands; Telecommunications link; Network packet; Scheduling (production processes); Computer network; Wireless; Real-time computing; Telecommunications; Engineering","score_opus":0.012235696815598461,"score_gpt":0.25057301108206037,"score_spread":0.2383373142664619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107919046","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":[0.4873592,0.003612595,0.49950647,0.000053353942,0.0055862754,0.0005668219,0.0000056094223,0.00085790176,0.002451774],"genre_scores_gemma":[0.9837685,0.0017041067,0.008610918,0.00018491215,0.005491527,0.000014000402,0.000061448445,0.00013668768,0.000027865894],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99759084,0.00005419038,0.0006023377,0.0004492792,0.0002255914,0.001077758],"domain_scores_gemma":[0.9989151,0.00031478185,0.000111512556,0.0003790846,0.000056217024,0.0002233145],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006015711,0.0004054587,0.00045721687,0.0001613394,0.00012325388,0.00013097226,0.00029465696,0.00032669894,0.000013551915],"category_scores_gemma":[0.000020648282,0.00044556262,0.0000544855,0.0011793879,0.00007802217,0.00055647537,0.000047970916,0.00058678957,0.000012090707],"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":[0.000069108675,0.000016786995,0.012490343,0.000029682253,0.00003312393,0.000039899638,0.00006127598,0.96594363,0.000043722095,0.0001139759,0.0021310165,0.019027447],"study_design_scores_gemma":[0.001214855,0.000035386765,0.045617312,0.00032678194,0.000030511503,0.000019575982,0.00003092044,0.94893086,0.00033401157,0.0014484896,0.0012493423,0.0007619749],"about_ca_topic_score_codex":0.000036104466,"about_ca_topic_score_gemma":0.000936247,"teacher_disagreement_score":0.49640933,"about_ca_system_score_codex":0.00015853721,"about_ca_system_score_gemma":0.00001526632,"threshold_uncertainty_score":0.9997996},"labels":[],"label_agreement":null},{"id":"W2107970055","doi":"10.1109/icc.2009.5199056","title":"How Much Multiuser Diversity Gain is Required over Large-Scale Fading?","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Fading; Bit error rate; Computer science; Diversity gain; Fading distribution; Scheduling (production processes); Electronic engineering; Algorithm; Mathematics; Rayleigh fading; Mathematical optimization; Decoding methods; Engineering","score_opus":0.008929400345637026,"score_gpt":0.20950442654282384,"score_spread":0.2005750261971868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107970055","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":[0.10045127,0.00010846865,0.8876003,0.0003466773,0.00021056265,0.0001760765,0.000012733459,0.0009084537,0.010185449],"genre_scores_gemma":[0.97267807,0.00007870758,0.024259442,0.00042373725,0.00009444112,0.0000019304116,0.000016611528,0.00002299989,0.002424086],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992224,0.000009907016,0.000099679,0.00019180306,0.0001536233,0.0003225965],"domain_scores_gemma":[0.99962175,0.000017616114,0.000021663067,0.00022666939,0.000033189583,0.000079110825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000050631057,0.0001514533,0.00014134761,0.000056646768,0.00013576,0.00003903067,0.00012831455,0.00010197834,0.00015881471],"category_scores_gemma":[0.000008736663,0.00015858836,0.000052446834,0.0002104568,0.000011323477,0.0004696212,0.00006718655,0.000105260704,0.000024909756],"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":[0.000025603065,0.00009348983,0.0072470247,0.00002443382,0.00005126643,0.00001649506,0.0021292658,0.9033422,0.0034577495,0.0018180179,0.06975508,0.01203939],"study_design_scores_gemma":[0.0006396574,0.000018279832,0.001861131,0.000014317765,0.000010516479,9.307108e-7,0.0001738327,0.98834133,0.004193443,0.0003940854,0.0040690494,0.0002834362],"about_ca_topic_score_codex":0.0000043081245,"about_ca_topic_score_gemma":0.000020931331,"teacher_disagreement_score":0.8722268,"about_ca_system_score_codex":0.00012570532,"about_ca_system_score_gemma":0.0000024551493,"threshold_uncertainty_score":0.6467046},"labels":[],"label_agreement":null},{"id":"W2108279480","doi":"10.1145/1454630.1454643","title":"Quality of service support and backoff strategies in wireless networks with error control protocol","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"","keywords":"HiperLAN; Computer science; Computer network; Quality of service; Throughput; WiMAX; Wireless network; Protocol (science); Wireless; Transmission (telecommunications); Wireless Application Protocol; Wireless lan; Telecommunications; Medicine","score_opus":0.016341308233622707,"score_gpt":0.26280197421430646,"score_spread":0.24646066598068375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108279480","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":[0.1907827,0.000011926877,0.7795519,0.000042586515,0.00002738611,0.023351533,0.0000047823696,0.00027294573,0.005954196],"genre_scores_gemma":[0.98744184,0.000008737605,0.0053144135,0.000053206848,0.000021954767,0.007099752,0.0000075977127,0.00002896793,0.000023549614],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991761,0.00003238146,0.0003278187,0.00014447905,0.00011440223,0.00020482785],"domain_scores_gemma":[0.9996109,0.000056285455,0.000063054205,0.0001523953,0.00007144973,0.000045916782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010199546,0.0001469208,0.0002796917,0.000042227253,0.000024353705,0.00000910731,0.00006730695,0.00007801613,0.00003277369],"category_scores_gemma":[0.0000019813294,0.00012616313,0.000012352948,0.0002725119,0.000051448234,0.000301947,0.0000116433,0.000120642704,8.925982e-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":[0.00012094228,0.00002149745,0.01416139,0.00013834774,0.000014060661,0.000004877009,0.0001263753,0.98421,0.00014530083,0.0006835556,0.00003390446,0.00033973824],"study_design_scores_gemma":[0.0024752556,0.00006651218,0.03106629,0.000042264965,0.00000334506,0.0000102453605,0.00021467675,0.96565044,0.00017273068,0.00003424743,0.000050021772,0.0002139794],"about_ca_topic_score_codex":0.00006561872,"about_ca_topic_score_gemma":0.0009968693,"teacher_disagreement_score":0.7966591,"about_ca_system_score_codex":0.000022556835,"about_ca_system_score_gemma":0.000031862226,"threshold_uncertainty_score":0.5144783},"labels":[],"label_agreement":null},{"id":"W2108707733","doi":"10.1186/s13638-015-0260-2","title":"A virtual queue-based back-pressure scheduling algorithm for wireless sensor networks","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":28,"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":"National Natural Science Foundation of China","keywords":"Computer science; Queue; Network packet; Computer network; Real-time computing; Multilevel queue; Scheduling (production processes); Algorithm; Queue management system; Mathematical optimization","score_opus":0.03338612190702028,"score_gpt":0.2652429474896973,"score_spread":0.231856825582677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108707733","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":[0.005612925,0.010082169,0.9817717,0.00032792002,0.0011220772,0.00043931356,0.000014515483,0.0002649696,0.00036442067],"genre_scores_gemma":[0.841922,0.008195131,0.14782888,0.00024977844,0.0014059521,0.000069235524,0.00008986614,0.000175065,0.00006410306],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977921,0.0002633412,0.0007041899,0.00030328677,0.00029765195,0.00063939794],"domain_scores_gemma":[0.997296,0.0007665312,0.00030120744,0.0008809344,0.00033763016,0.00041771645],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007954792,0.00042667938,0.00049969566,0.0002077022,0.0007478695,0.00030828247,0.000715322,0.0002432709,0.0000062665054],"category_scores_gemma":[0.000019396884,0.00043694166,0.00013996506,0.0005031266,0.0001588385,0.00034506494,0.00013668434,0.0010613077,0.0000060378625],"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":[0.000037920337,0.0000409367,0.00015815982,0.000010947423,0.00008013427,0.0000032095224,0.00010628975,0.7141854,0.000024775904,0.00026580913,0.00035294594,0.28473344],"study_design_scores_gemma":[0.0015764373,0.00017116417,0.00002027433,0.00049631414,0.000069144415,0.000057975518,0.00018148062,0.96804595,0.000045151082,0.00009295151,0.028769389,0.00047373798],"about_ca_topic_score_codex":0.000002479066,"about_ca_topic_score_gemma":0.0000098114715,"teacher_disagreement_score":0.8363091,"about_ca_system_score_codex":0.00014956245,"about_ca_system_score_gemma":0.000071143026,"threshold_uncertainty_score":0.99980825},"labels":[],"label_agreement":null},{"id":"W2108795729","doi":"10.11648/j.wcmc.20130104.15","title":"Optimal Resource Allocation for LTE Uplink Scheduling in Smart Grid Communications","year":2013,"lang":"en","type":"article","venue":"International Journal of Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Scheduling (production processes); Dynamic priority scheduling; Fair-share scheduling; Smart grid; Distributed computing; Computer network; Quality of service; Round-robin scheduling; Base station; Telecommunications link; Grid; 3rd Generation Partnership Project 2; Mathematical optimization; Engineering","score_opus":0.01488178823185648,"score_gpt":0.27540153578358084,"score_spread":0.26051974755172436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108795729","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":[0.3674896,0.003517096,0.6265203,0.0012252552,0.00038454076,0.0005062817,0.000007611427,0.00007582589,0.0002735258],"genre_scores_gemma":[0.7699349,0.002885246,0.22681443,0.00004863562,0.0001429143,0.00006746827,0.000069937436,0.000029505047,0.000006985744],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986379,0.000073276526,0.0008151385,0.0001186336,0.00016777277,0.00018723904],"domain_scores_gemma":[0.99770486,0.00063273567,0.000329702,0.00060528005,0.0006535636,0.00007386955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043388398,0.00015015423,0.00023564088,0.0002991074,0.00016664858,0.00013138627,0.0012998361,0.00008080055,0.0000049253863],"category_scores_gemma":[0.00005346328,0.00016594524,0.00007424536,0.00020387038,0.00012110572,0.00046401785,0.00036168165,0.00038672867,0.0000023817502],"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":[0.000009491272,0.00007884581,0.0009386528,0.000016121696,0.00006850541,4.883316e-7,0.0006842357,0.8578842,0.0011126637,0.0011853076,0.00011916642,0.13790232],"study_design_scores_gemma":[0.0006392307,0.000039493458,0.00056486257,0.00026681361,0.000012596497,0.000031726224,0.0005501546,0.99067086,0.00014933124,0.00016383313,0.0067584836,0.00015263325],"about_ca_topic_score_codex":0.000017286051,"about_ca_topic_score_gemma":0.000013795798,"teacher_disagreement_score":0.40244526,"about_ca_system_score_codex":0.00015810913,"about_ca_system_score_gemma":0.000036247344,"threshold_uncertainty_score":0.676705},"labels":[],"label_agreement":null},{"id":"W2109708969","doi":"10.1109/vetecs.2011.5956602","title":"Cross Layer Scheduling Algorithms for Downlink Multi-Antenna CDMA Systems","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 du Québec à Montréal","funders":"","keywords":"Computer science; Graph coloring; MIMO; Scheduling (production processes); Telecommunications link; Code division multiple access; Algorithm; Computer network; Fair-share scheduling; Distributed computing; Quality of service; Graph; Mathematical optimization; Theoretical computer science; Mathematics","score_opus":0.06479010902810527,"score_gpt":0.2832249462803457,"score_spread":0.21843483725224044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109708969","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":[0.009892231,0.000488796,0.98613125,0.0000024324595,0.0013260085,0.00043081946,0.000014075367,0.0008064656,0.00090791774],"genre_scores_gemma":[0.553549,0.000059605194,0.44536304,0.000013775477,0.00020014167,0.00011086515,0.00002185459,0.00006871654,0.0006130014],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990704,0.0000080425925,0.00028646635,0.00020553403,0.00008321518,0.00034636265],"domain_scores_gemma":[0.9994909,0.000039304978,0.000038801358,0.00021982266,0.00013349415,0.00007766275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000108959415,0.00017647965,0.00018701133,0.0000569671,0.000077317265,0.00005017803,0.0001357778,0.00012456352,0.000047387995],"category_scores_gemma":[0.000022259823,0.00016706562,0.000059584676,0.00013101392,0.000022661892,0.00030748258,0.000022236829,0.00010198509,0.00004594866],"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":[0.000008681598,0.000018707717,0.0005749221,0.000077415636,0.00003424503,0.000002009402,0.00020930897,0.9951769,0.0009743124,0.0004926038,0.000040812334,0.0023900631],"study_design_scores_gemma":[0.000570363,0.000015595195,0.00023915536,0.000037353933,0.0000092582795,0.000003206667,0.00008127194,0.99619514,0.0021047136,0.000022486509,0.00048771882,0.0002337681],"about_ca_topic_score_codex":0.000019396106,"about_ca_topic_score_gemma":0.0000066961,"teacher_disagreement_score":0.54365677,"about_ca_system_score_codex":0.000049964772,"about_ca_system_score_gemma":0.0000063812718,"threshold_uncertainty_score":0.6812738},"labels":[],"label_agreement":null},{"id":"W2109936554","doi":"10.1109/icc.2008.755","title":"Optimal Power and Retransmission Control Policies over Fading Channels with Packet Drop Penalty Costs","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Retransmission; Computer science; Fading; Power control; Channel (broadcasting); Computer network; Markov decision process; Transmission (telecommunications); Network packet; Markov process; Power (physics); Mathematical optimization; Telecommunications; Mathematics","score_opus":0.0054019132459116465,"score_gpt":0.20015739706040417,"score_spread":0.19475548381449254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109936554","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":[0.4754251,0.00022799068,0.52074313,0.000048645907,0.00006544957,0.00016659002,0.0000037808552,0.00027624788,0.0030430777],"genre_scores_gemma":[0.99176764,0.0004488611,0.0073459465,0.000084532665,0.000060414113,0.0000089036,0.000007191734,0.000048186346,0.00022832371],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927014,0.000012316504,0.00013827742,0.00015917746,0.00014441619,0.0002756484],"domain_scores_gemma":[0.99967086,0.00004144562,0.000023419065,0.00011779059,0.00003593551,0.000110556706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000039152113,0.00017401834,0.00018320803,0.000066406144,0.00010978873,0.000021584383,0.000050043072,0.000074405456,0.000104844235],"category_scores_gemma":[0.0000059026906,0.0001395104,0.000020713764,0.00015738334,0.000057522637,0.00027763526,0.000009661653,0.00012377136,0.0000038604426],"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":[0.000051234343,0.0000083517125,0.0023305127,0.000010937189,0.000026989792,0.000015473472,0.00048191776,0.9942956,0.0015095205,0.00015106631,0.0007678577,0.0003505574],"study_design_scores_gemma":[0.0016022921,0.00011228667,0.005370116,0.00008839969,0.000011346335,0.00009350286,0.00007461763,0.9887193,0.0025861834,0.000012120837,0.0009627456,0.00036712573],"about_ca_topic_score_codex":0.0000098302535,"about_ca_topic_score_gemma":0.000003434826,"teacher_disagreement_score":0.5163425,"about_ca_system_score_codex":0.00005728446,"about_ca_system_score_gemma":0.000007736932,"threshold_uncertainty_score":0.5689069},"labels":[],"label_agreement":null},{"id":"W2110205247","doi":"10.1109/tvt.2009.2039235","title":"Performance Analysis of Scheduling Schemes for Rate-Adaptive MIMO OSFBC-OFDM Systems","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":26,"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 du Québec à Montréal; Polytechnique Montréal","funders":"","keywords":"Orthogonal frequency-division multiplexing; Link adaptation; MIMO; Spectral efficiency; Fading; Computer science; MIMO-OFDM; Bit error rate; Scheduling (production processes); Electronic engineering; Multipath propagation; Block Error Rate; Algorithm; Channel (broadcasting); Telecommunications link; Decoding methods; Mathematics; Telecommunications; Engineering; Mathematical optimization","score_opus":0.007527590451905704,"score_gpt":0.21440259010852958,"score_spread":0.20687499965662387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110205247","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":[0.39527577,0.00008032342,0.6035846,0.000018360113,0.00037091627,0.00023780705,0.000020514235,0.00038748988,0.000024233374],"genre_scores_gemma":[0.9639259,0.00014327622,0.035560098,0.0000049093182,0.00002294881,0.00025516222,0.0000112521675,0.000047661044,0.000028812237],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989963,0.000012802801,0.00034374685,0.00026029456,0.000105036335,0.0002818095],"domain_scores_gemma":[0.99919784,0.000081654696,0.000086788954,0.000420387,0.00017459286,0.00003876223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012905034,0.00020275274,0.0004078109,0.0009900428,0.00012468391,0.000010452918,0.0001985684,0.0004131474,0.000013077226],"category_scores_gemma":[0.000008704376,0.0002190049,0.00015771776,0.0017372747,0.00012019112,0.00013917331,0.0000012336088,0.00047421688,0.0000058212627],"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":[0.000020697207,0.00003477495,0.00005526983,0.000048846163,0.0006241065,7.0645075e-7,0.00001827761,0.94115335,0.049554747,0.0005362257,0.0000023904754,0.007950593],"study_design_scores_gemma":[0.00026665677,0.0000655715,0.000021272688,0.000028865852,0.00037886802,0.0000026743085,0.00006428001,0.8368061,0.16187602,0.000021072554,0.00029664536,0.00017194946],"about_ca_topic_score_codex":0.0000033595913,"about_ca_topic_score_gemma":0.00002950771,"teacher_disagreement_score":0.56865007,"about_ca_system_score_codex":0.00005296348,"about_ca_system_score_gemma":0.000016903072,"threshold_uncertainty_score":0.89307606},"labels":[],"label_agreement":null},{"id":"W2110210964","doi":"10.1109/tit.2009.2027557","title":"Achieving Long-Term Fairness and Optimum Multiuser Diversity Gain in Time-Varying Broadcast Channels","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo; Blackberry (Canada)","funders":"","keywords":"Fading; Base station; Scheduling (production processes); Telecommunications link; Computer science; Channel state information; Diversity gain; Channel (broadcasting); Computer network; Throughput; Term (time); Real-time computing; Telecommunications; Mathematics; Wireless; Mathematical optimization","score_opus":0.006580497590477079,"score_gpt":0.20306506775948485,"score_spread":0.19648457016900778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110210964","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":[0.15508562,0.000030476394,0.84368736,0.000016692587,0.00021294974,0.00022987506,0.000009196574,0.00028089402,0.00044692712],"genre_scores_gemma":[0.9983579,0.00016154176,0.0012541425,0.000106771244,0.000021894353,0.000013305144,0.000017915823,0.00001387917,0.000052672498],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919623,0.00004127618,0.0002810627,0.000104219456,0.00015394505,0.00022329003],"domain_scores_gemma":[0.9996191,0.00008209018,0.000050970226,0.00014912752,0.000032920034,0.000065754786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021080578,0.00017634458,0.00015305029,0.0003265227,0.00023400005,0.00006782122,0.00011955719,0.00011023081,0.00005689907],"category_scores_gemma":[0.0000041545923,0.000201256,0.00003887281,0.00027282798,0.000030562627,0.0020652828,0.0000034501966,0.00025078692,0.000051330633],"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":[0.000059011323,0.000022428483,0.00006667124,0.00002868553,0.000010663274,0.0000012269875,0.001733351,0.905474,0.00012789495,0.00004809809,0.0000051035686,0.09242283],"study_design_scores_gemma":[0.0014888311,0.000064769265,0.0027195716,0.00022884014,0.000024961348,0.000014066262,0.00016575036,0.9898123,0.004727809,0.0002635154,0.000017210361,0.00047233907],"about_ca_topic_score_codex":0.0000015639162,"about_ca_topic_score_gemma":0.0000011163314,"teacher_disagreement_score":0.84327227,"about_ca_system_score_codex":0.000120954704,"about_ca_system_score_gemma":0.0000054889233,"threshold_uncertainty_score":0.82069814},"labels":[],"label_agreement":null},{"id":"W2110318861","doi":"10.1109/icc.2006.255422","title":"Adaptive Rate Allocation for Multi-layered Video Transmission in Wireless Communication Systems","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Quality of service; Throughput; Channel (broadcasting); Scalability; Transmission (telecommunications); Wireless; Computer network; Adaptation (eye); Link adaptation; Video quality; Real-time computing; Transmission rate; Fading; Telecommunications; Engineering","score_opus":0.08722122320464445,"score_gpt":0.31903870898698466,"score_spread":0.2318174857823402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110318861","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":[0.005288837,0.0005294723,0.9825078,0.0011058557,0.00041521253,0.0011283648,0.00014673037,0.0003414668,0.0085362615],"genre_scores_gemma":[0.95494634,0.0014875415,0.04101874,0.00003692694,0.000064453896,0.0008760172,0.0011450405,0.000055968812,0.00036897263],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847984,0.00018180537,0.00064100913,0.0002534952,0.0001985916,0.0002452492],"domain_scores_gemma":[0.998067,0.00032017642,0.00017461726,0.00093023654,0.00045719347,0.000050781597],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030828337,0.00024481837,0.00023548586,0.0002900906,0.0001855602,0.000107569125,0.0010758081,0.00015613736,0.000013407743],"category_scores_gemma":[0.000019943282,0.00028336362,0.00006597324,0.0002977688,0.00009726568,0.00041393426,0.00004318588,0.00031881503,0.000025211823],"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":[0.000053461048,0.00020159029,0.000094351315,0.000014964611,0.00002988394,3.141491e-7,0.000100137084,0.8372818,0.0054972894,0.15024813,0.0005840904,0.0058939517],"study_design_scores_gemma":[0.001029333,0.00003154217,0.00049370795,0.000284549,0.000011094333,0.0000014741763,0.00013475561,0.99320114,0.0010312008,0.0017149204,0.0017884418,0.0002778469],"about_ca_topic_score_codex":0.000251952,"about_ca_topic_score_gemma":0.0007470683,"teacher_disagreement_score":0.9496575,"about_ca_system_score_codex":0.00037711233,"about_ca_system_score_gemma":0.000052569783,"threshold_uncertainty_score":0.99996185},"labels":[],"label_agreement":null},{"id":"W2110392972","doi":"10.1109/vetecs.2005.1543303","title":"Resource Allocation in HSDPA Using Best-Users Selection Under Code Constraints","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Fairness measure; Computer science; Throughput; Scheduling (production processes); Max-min fairness; Resource allocation; Maximum throughput scheduling; Selection (genetic algorithm); Resource management (computing); Interference (communication); Resource (disambiguation); Computer network; Channel (broadcasting); Distributed computing; Mathematical optimization; Dynamic priority scheduling; Quality of service; Wireless; Telecommunications; Round-robin scheduling","score_opus":0.01608705338580975,"score_gpt":0.24508912346428816,"score_spread":0.2290020700784784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110392972","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":[0.17176262,0.000044969955,0.8235042,0.000084003,0.000049801583,0.00013510771,7.3175306e-7,0.00026268227,0.004155851],"genre_scores_gemma":[0.93783134,0.000029924395,0.061785236,0.00007757003,0.00008732902,0.0000059571857,0.000012213761,0.000032393844,0.000138056],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938333,0.000017390641,0.00018735196,0.00013175598,0.00008738154,0.00019281085],"domain_scores_gemma":[0.9998107,0.00002476086,0.00002293287,0.000081177524,0.00002472186,0.00003570983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006970018,0.00010192095,0.00008691511,0.00011037167,0.00003526038,0.000016271204,0.00004486483,0.00008107267,0.00008627264],"category_scores_gemma":[0.000007803231,0.00012135341,0.000014333814,0.00032699667,0.000028024888,0.00025101748,0.0000073054916,0.00011541822,0.000019915544],"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":[0.0000031630457,0.000011278759,0.00038003596,0.0000054613033,0.000005551567,2.4608772e-7,0.00006512757,0.98506504,0.0034175364,0.00062402,0.000092971466,0.010329564],"study_design_scores_gemma":[0.0002568844,0.0000056593713,0.000245132,0.0000245075,0.0000049377436,0.0000065150107,0.00014376017,0.99484885,0.0034041426,0.00005056532,0.00087381515,0.00013521333],"about_ca_topic_score_codex":0.000009818088,"about_ca_topic_score_gemma":0.00030447013,"teacher_disagreement_score":0.7660687,"about_ca_system_score_codex":0.00036656045,"about_ca_system_score_gemma":0.000014509475,"threshold_uncertainty_score":0.49486485},"labels":[],"label_agreement":null},{"id":"W2110776229","doi":"10.1109/glocom.2005.1577688","title":"Spatio-ternporal schedulers in IEEE 802.16","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Base station; Computer network; Wireless broadband; Telecommunications link; Wireless; Mobile broadband; Scheduling (production processes); Broadband; Backhaul (telecommunications); WiMAX; Broadband networks; Wireless network; IEEE 802; Real-time computing; Telecommunications; Engineering","score_opus":0.019751528043394345,"score_gpt":0.25998545952447666,"score_spread":0.24023393148108232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110776229","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":[0.30718955,0.0036838811,0.51931304,0.0046001347,0.0029606142,0.0023723259,0.00056239375,0.0034338618,0.1558842],"genre_scores_gemma":[0.9215117,0.0023016839,0.07478786,0.00026560877,0.00021671089,0.00016531374,0.00036266653,0.00006643334,0.00032202827],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99700534,0.00016530702,0.0009918009,0.00048764257,0.0003376771,0.0010122138],"domain_scores_gemma":[0.9975482,0.000095108124,0.0001999984,0.0016714955,0.0002018639,0.00028331485],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026796633,0.00054927636,0.00054307096,0.00026557146,0.00024103209,0.00016419389,0.0014373462,0.00034217225,0.00045166528],"category_scores_gemma":[0.000036650723,0.0006654832,0.0001390571,0.001088718,0.00021233343,0.00086019374,0.00012611099,0.00066240336,0.0005817956],"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":[0.000018164397,0.00020204314,0.0038169243,0.000021997179,0.000062194995,0.0000039548036,0.00009808004,0.91246456,0.00009762946,0.0035599368,0.02099186,0.05866267],"study_design_scores_gemma":[0.0018048106,0.000050250987,0.0044806697,0.0001798698,0.00004698724,0.0000483267,0.0001599515,0.8800011,0.0006661554,0.0015162259,0.10982525,0.0012203954],"about_ca_topic_score_codex":0.00021586372,"about_ca_topic_score_gemma":0.010292713,"teacher_disagreement_score":0.6143221,"about_ca_system_score_codex":0.001548542,"about_ca_system_score_gemma":0.00019823908,"threshold_uncertainty_score":0.99957967},"labels":[],"label_agreement":null},{"id":"W2111031080","doi":"10.1109/glocom.2004.1379129","title":"Queuing analysis for radio link level scheduling in a multi-rate TDMA wireless network","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":28,"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 Manitoba","funders":"","keywords":"Computer science; Time division multiple access; Computer network; Queueing theory; Telecommunications link; Link adaptation; Scheduling (production processes); Wireless network; Network packet; Fading; Queue; Markov process; Radio Link Protocol; Channel (broadcasting); Wireless; Telecommunications; Engineering","score_opus":0.032503278871863446,"score_gpt":0.2594961601367914,"score_spread":0.22699288126492795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111031080","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":[0.051225558,0.000488055,0.9471921,0.000098840384,0.00013523313,0.00029685814,0.0000046582886,0.00039351996,0.00016519801],"genre_scores_gemma":[0.60783994,0.00013910915,0.39135253,0.00004735618,0.00033217628,0.000057441357,0.000036190784,0.00004835429,0.0001469011],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863756,0.000027815087,0.0004405732,0.0002858452,0.00008710219,0.0005211364],"domain_scores_gemma":[0.99941784,0.00015987638,0.00005709366,0.0002298829,0.000056740748,0.00007857443],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030178475,0.00022413829,0.00037669565,0.00024508807,0.000075227115,0.000043667882,0.00014276386,0.00014399282,0.000026278913],"category_scores_gemma":[0.000027526747,0.0002467332,0.00012719072,0.001323104,0.000015491565,0.00031136753,0.00001858006,0.00019103265,0.000009314343],"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":[0.000010738662,0.000012210316,0.0027957633,0.000019846048,0.00015219752,0.0000011559798,0.000117743424,0.9759719,0.0002777768,0.00032967035,0.000034737786,0.020276312],"study_design_scores_gemma":[0.0007268065,0.0000061008495,0.0021706335,0.00004282866,0.00007140763,5.1500854e-7,0.000029797182,0.9956402,0.0006047772,0.00003487881,0.00037163743,0.0003004138],"about_ca_topic_score_codex":0.000015273632,"about_ca_topic_score_gemma":0.0014236992,"teacher_disagreement_score":0.5566144,"about_ca_system_score_codex":0.00019511259,"about_ca_system_score_gemma":0.000013260967,"threshold_uncertainty_score":0.9999985},"labels":[],"label_agreement":null},{"id":"W2111336126","doi":"10.1109/tvt.2011.2158674","title":"Dynamic QoS-Based Bandwidth Allocation Framework for Broadband Wireless Networks","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":57,"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 Guelph; University of Toronto","funders":"","keywords":"Computer network; WiMAX; Quality of service; Computer science; Wireless broadband; Interoperability; Dynamic bandwidth allocation; Bandwidth allocation; Wireless network; Radio resource management; Broadband networks; Mobile broadband; Resource allocation; Wireless; Broadband; Telecommunications","score_opus":0.009180173617254643,"score_gpt":0.2187033384236196,"score_spread":0.20952316480636496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111336126","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":[0.016921872,0.0002347247,0.97934306,0.00008579261,0.0009764958,0.0006205065,0.000013545152,0.0017573939,0.00004661332],"genre_scores_gemma":[0.87893856,0.00017542737,0.12013222,0.000059233265,0.000030652798,0.0005156176,0.00002082283,0.00010598548,0.000021494412],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877554,0.000019138199,0.00030857054,0.00035476036,0.00011094434,0.00043103923],"domain_scores_gemma":[0.99917966,0.00008597763,0.000064647706,0.00051195925,0.0000942558,0.00006350318],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007353342,0.00028661036,0.00027448285,0.0003951735,0.000179981,0.000014123343,0.00024599707,0.00071674166,0.00003916255],"category_scores_gemma":[0.0000053396802,0.00032439025,0.00011641318,0.00073631137,0.00011900486,0.00011829772,7.7596576e-7,0.00053768675,0.000014146182],"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":[0.00004962358,0.00008319144,0.000010945186,0.000030912965,0.00006523533,0.0000030505514,0.00003392233,0.9520162,0.00074846373,0.0010754821,0.000016832892,0.045866158],"study_design_scores_gemma":[0.0005561652,0.00014175368,0.000021779679,0.000090884394,0.00006430276,0.000006311969,0.000029395796,0.95786273,0.03875047,0.0019129855,0.0002370597,0.0003261715],"about_ca_topic_score_codex":0.0000021521207,"about_ca_topic_score_gemma":0.000027663145,"teacher_disagreement_score":0.8620167,"about_ca_system_score_codex":0.00015242015,"about_ca_system_score_gemma":0.00001924134,"threshold_uncertainty_score":0.99992085},"labels":[],"label_agreement":null},{"id":"W2111527567","doi":"10.1109/lcn.2008.4664207","title":"Optimized resource allocation for the uplink of SFBC-CDMA systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Subcarrier; Telecommunications link; Bit error rate; Code division multiple access; Resource allocation; Base station; MIMO; Bandwidth (computing); Reduction (mathematics); Channel (broadcasting); Spectral efficiency; Computer network; Electronic engineering; Algorithm; Orthogonal frequency-division multiplexing; Engineering; Mathematics","score_opus":0.015324293204469767,"score_gpt":0.20646248477808785,"score_spread":0.19113819157361808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111527567","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":[0.0011645757,0.0007628154,0.99467826,0.00006451852,0.00017934511,0.00047536625,0.0000018945633,0.00021351653,0.0024597],"genre_scores_gemma":[0.9178622,0.0005434875,0.07984907,0.000024113015,0.00017277981,0.00016788048,0.00003396585,0.000052424242,0.0012940727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994846,0.00000975774,0.00021688576,0.00008328616,0.000082504856,0.00012297217],"domain_scores_gemma":[0.9994372,0.00022407033,0.00004470412,0.0002080248,0.00006521936,0.000020747191],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000093753195,0.00008244828,0.00012799741,0.000028541908,0.00007408624,0.000006135373,0.00010744094,0.000053435077,0.00000895632],"category_scores_gemma":[0.000022627422,0.00006148037,0.000038920272,0.00013177525,0.000030033534,0.00006952119,0.000009340302,0.00004757059,0.0000030001268],"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":[0.000014417156,0.0000045517895,0.000008602743,0.000028167484,0.00002172087,1.0983384e-7,0.00011262688,0.9940869,0.0001970483,0.001219837,0.0034443235,0.00086170016],"study_design_scores_gemma":[0.0003914333,0.000010731263,0.000025225409,0.000014858726,0.00001071838,0.0000033704953,0.00010172327,0.9937884,0.0010885943,0.00001220327,0.004479258,0.000073463554],"about_ca_topic_score_codex":0.0000043891096,"about_ca_topic_score_gemma":5.4546445e-7,"teacher_disagreement_score":0.9166976,"about_ca_system_score_codex":0.000030404151,"about_ca_system_score_gemma":0.000006871851,"threshold_uncertainty_score":0.25070968},"labels":[],"label_agreement":null},{"id":"W2111586256","doi":"10.1109/tmc.2010.41","title":"Channel Assignment for Multihop Cellular Networks: Minimum Delay","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":14,"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 Lethbridge; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Cellular network; Network packet; Code division multiple access; Benchmark (surveying); Heuristic; Channel (broadcasting); Duplex (building); Throughput; Transmission delay; Wireless; Telecommunications","score_opus":0.007393418480356151,"score_gpt":0.21856210153641858,"score_spread":0.21116868305606243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111586256","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":[0.030222062,0.00008276246,0.9645227,0.0000076004567,0.0036943117,0.0007649481,0.0000118665785,0.00063504744,0.000058668007],"genre_scores_gemma":[0.97008204,0.000037485268,0.029044893,0.000030108586,0.00040857203,0.00022612966,0.000014306922,0.00010141442,0.00005503349],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879557,0.000017873184,0.00032627667,0.00029668742,0.0001282698,0.00043529854],"domain_scores_gemma":[0.99923307,0.00025686616,0.000055760658,0.00028351962,0.000061279905,0.0001095054],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014227473,0.0002503566,0.00021193619,0.000105025385,0.0002774379,0.000039157294,0.00015362356,0.00017076137,0.000025377989],"category_scores_gemma":[0.0000025748732,0.0002852026,0.00012415615,0.00022161685,0.00003268134,0.00011346083,0.000001471354,0.00045234044,0.000011948976],"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":[0.000011215755,0.000058675247,0.0000010461782,0.000023500628,0.000032480162,0.0000015923671,0.00011712334,0.9495335,0.0066840807,0.000005461168,0.00009270027,0.04343861],"study_design_scores_gemma":[0.00052378466,0.00006932845,0.0000019549302,0.00003773702,0.00002478073,0.000004037601,0.000043796575,0.97203076,0.026233051,0.000016519158,0.00073140085,0.00028284706],"about_ca_topic_score_codex":0.000001601389,"about_ca_topic_score_gemma":0.000010323368,"teacher_disagreement_score":0.93986,"about_ca_system_score_codex":0.00007360083,"about_ca_system_score_gemma":0.000009745017,"threshold_uncertainty_score":0.99996},"labels":[],"label_agreement":null},{"id":"W2112097813","doi":"10.1109/twc.2009.080690","title":"Energy optimal scheduler for diversity fading channels with maximum delay constraints","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","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":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Scheduling (production processes); Fading; Computer science; Channel (broadcasting); Network packet; Computer network; Wireless; Diversity scheme; MIMO; Mathematical optimization; Telecommunications; Mathematics","score_opus":0.020042929845118705,"score_gpt":0.23476747527136904,"score_spread":0.21472454542625033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112097813","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":[0.00819219,0.00009691802,0.98951375,0.00031093232,0.0002062008,0.0003440798,0.00007341337,0.0006003461,0.00066219055],"genre_scores_gemma":[0.9286823,0.00062521256,0.070228584,0.00011394818,0.00003074124,0.00014691114,0.000050251274,0.000050531464,0.000071514834],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989165,0.000043188607,0.00026495807,0.00024382857,0.00016485358,0.00036668192],"domain_scores_gemma":[0.9985224,0.00019286705,0.000064151165,0.00094745675,0.0001463375,0.00012676077],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000791825,0.00026772628,0.0002479675,0.00019940775,0.0009969858,0.000047757134,0.00060231856,0.00014160843,0.000027016984],"category_scores_gemma":[0.0000014352179,0.0002936699,0.00010187196,0.0004251398,0.00020741613,0.0003650987,0.0000068488907,0.00031495583,0.0000071903096],"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":[0.0000400083,0.00013230403,0.0000032162845,0.0000082915885,0.0000780046,0.0000010176377,0.00027132247,0.9237061,0.00042332313,0.0015508753,0.000053357013,0.07373214],"study_design_scores_gemma":[0.0010029399,0.00015671039,0.000016815678,0.00010335867,0.00008375697,0.00001877119,0.00013688505,0.98968875,0.0073309527,0.00034955356,0.00066121935,0.00045027738],"about_ca_topic_score_codex":0.000007983855,"about_ca_topic_score_gemma":0.000050403527,"teacher_disagreement_score":0.92049015,"about_ca_system_score_codex":0.00016445901,"about_ca_system_score_gemma":0.000028206085,"threshold_uncertainty_score":0.99995154},"labels":[],"label_agreement":null},{"id":"W2112462783","doi":"10.1109/wcnc.2008.286","title":"A Novel Radio Resource Management Approach for QoS Provisioning in Multi-Service Multi-Slot OFDMA Systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"","keywords":"Computer science; Quality of service; Frame (networking); Provisioning; Resource management (computing); Frequency-division multiple access; Computer network; Resource allocation; Generalization; Service (business); Orthogonal frequency-division multiplexing; Distributed computing; Mathematics","score_opus":0.043803485391691446,"score_gpt":0.23677896559180436,"score_spread":0.1929754802001129,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112462783","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":[0.0027471834,0.00046073945,0.9929338,0.000013789391,0.00016165197,0.0018540828,0.0000069897865,0.00053633575,0.0012854103],"genre_scores_gemma":[0.19164854,0.000111782894,0.80564183,0.00004742153,0.00010039784,0.0009790643,0.00006993503,0.00011374491,0.0012872573],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986934,0.000016378404,0.00038986807,0.000344815,0.00015944452,0.0003961008],"domain_scores_gemma":[0.99949574,0.000048760296,0.00005487412,0.00028046715,0.000050763625,0.000069379814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013876957,0.00023343897,0.00026365955,0.00017640271,0.000101446945,0.000026391072,0.00020340162,0.000103783605,0.0000025884879],"category_scores_gemma":[0.000009731392,0.00023625714,0.000041974767,0.0004783849,0.000014345819,0.0001932044,0.000056303237,0.0001346528,0.000004265247],"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":[0.000017593498,0.000130632,0.00022008676,0.00047464945,0.00003328173,0.0000035376847,0.00043211857,0.9966757,0.0005251253,0.00022613686,0.00023425583,0.0010268675],"study_design_scores_gemma":[0.0025448708,0.000010659804,0.00059942383,0.00011450456,0.000010587501,0.00001120404,0.000493382,0.99412876,0.00012956711,2.9227928e-7,0.0016722342,0.00028450933],"about_ca_topic_score_codex":0.00005043098,"about_ca_topic_score_gemma":0.000026434982,"teacher_disagreement_score":0.18890136,"about_ca_system_score_codex":0.00016545028,"about_ca_system_score_gemma":0.0000067604765,"threshold_uncertainty_score":0.9634286},"labels":[],"label_agreement":null},{"id":"W2112755565","doi":"10.1109/tmm.2003.819745","title":"Link-Level Traffic Scheduling for Providing Predictive QoS in Wireless Multimedia Networks","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia; University of Manitoba","funders":"","keywords":"Computer science; Computer network; Time division multiple access; Quality of service; Scheduling (production processes); Wireless; Real-time computing; Telecommunications","score_opus":0.01685075312478021,"score_gpt":0.2351112498453533,"score_spread":0.2182604967205731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112755565","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":[0.04151614,0.00011968524,0.95285624,0.00005755043,0.003025214,0.0014980292,0.00008910456,0.00081375253,0.000024263472],"genre_scores_gemma":[0.8370274,0.00027290932,0.16105641,0.00002775202,0.00066412974,0.00072123745,0.000051324547,0.00015698839,0.000021840902],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99795705,0.000032167234,0.0005661709,0.0004968383,0.00024378388,0.0007039642],"domain_scores_gemma":[0.9989183,0.00042052416,0.000078299156,0.000289301,0.00009730562,0.00019625407],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017375496,0.00043128693,0.0004075846,0.00037149628,0.0001788545,0.000039836945,0.00021521735,0.00039128415,0.000013413384],"category_scores_gemma":[0.000019818475,0.00049759983,0.00015481892,0.00062956376,0.00008427146,0.00044191096,0.000001461459,0.00076016015,0.000018794126],"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":[0.00011728476,0.000117823234,0.0000060312827,0.000050683386,0.000053066047,0.0000053707104,0.0008615251,0.86565506,0.0010448046,0.0000035528237,0.000009960989,0.13207482],"study_design_scores_gemma":[0.0034975833,0.00010357592,0.000066269975,0.00030353633,0.000045603378,0.0000039343167,0.00012855857,0.9815309,0.013810066,0.00001588699,0.000026037338,0.0004680727],"about_ca_topic_score_codex":0.00001105149,"about_ca_topic_score_gemma":0.00020487086,"teacher_disagreement_score":0.79551125,"about_ca_system_score_codex":0.00054476585,"about_ca_system_score_gemma":0.000069404596,"threshold_uncertainty_score":0.9997476},"labels":[],"label_agreement":null},{"id":"W2112869036","doi":"10.1109/icc.2006.255539","title":"Delay-Based Admission Control Using Fuzzy Logic for OFDMA Broadband Wireless Networks","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Computer science; Wireless broadband; Computer network; Admission control; Queueing theory; Orthogonal frequency-division multiple access; Broadband networks; Fuzzy logic; Frequency-division multiple access; Network packet; Wireless network; Channel (broadcasting); Wireless; Orthogonal frequency-division multiplexing; Real-time computing; Quality of service; Broadband; Telecommunications","score_opus":0.05569923601809098,"score_gpt":0.3114964900403335,"score_spread":0.2557972540222425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112869036","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":[0.0061747627,0.0003233567,0.98381925,0.0007965228,0.0005975669,0.0004975657,0.00019806746,0.00030167354,0.007291248],"genre_scores_gemma":[0.97333276,0.0003245117,0.024888288,0.00022038353,0.0002558101,0.00023897813,0.0005372118,0.00005529293,0.00014678453],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880207,0.00005899849,0.0004352641,0.0002226211,0.0002076997,0.00027335616],"domain_scores_gemma":[0.99841803,0.0002702769,0.0001571454,0.0006533922,0.0004310086,0.000070169655],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000117218646,0.00023760703,0.00021681152,0.00016170024,0.0002467672,0.0000976305,0.0007974047,0.00015239658,0.00006671954],"category_scores_gemma":[0.000018080078,0.00025730726,0.00009586994,0.0001865644,0.00009439213,0.00019150178,0.0000320889,0.00026151724,0.000008825855],"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":[0.000043401298,0.00009551479,0.00029159003,0.000007962326,0.000033194534,5.831739e-7,0.000006323679,0.96031237,0.0024134533,0.033035323,0.0008201531,0.0029401593],"study_design_scores_gemma":[0.001016034,0.000026595835,0.00014505835,0.00013987972,0.000029551022,0.0000021637538,0.000011116365,0.9935698,0.00045650115,0.002582936,0.0017542408,0.00026610825],"about_ca_topic_score_codex":0.00003722007,"about_ca_topic_score_gemma":0.00009729408,"teacher_disagreement_score":0.96715796,"about_ca_system_score_codex":0.00021050379,"about_ca_system_score_gemma":0.00006487555,"threshold_uncertainty_score":0.9999879},"labels":[],"label_agreement":null},{"id":"W2113211994","doi":"10.1109/glocom.2007.961","title":"Admission Control Framework for Delay Bounded Traffic in Cellular Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Handover; Computer science; Admission control; Scheduling (production processes); Computer network; Quality of service; A priori and a posteriori; Bounded function; Cellular network; Interval (graph theory); Real-time computing; Distributed computing; Mathematical optimization; Mathematics","score_opus":0.005836397060299586,"score_gpt":0.2274153233451089,"score_spread":0.2215789262848093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113211994","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":[0.027917653,0.0006657211,0.96975845,0.000023930608,0.0004006451,0.00045342543,9.704878e-7,0.00039550746,0.00038369428],"genre_scores_gemma":[0.8581358,0.00005482878,0.14135425,0.0000832779,0.00022388979,0.000026655967,0.000018922854,0.00005300778,0.000049349026],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902254,0.000010124871,0.00029866732,0.00016554512,0.00007209309,0.00043105104],"domain_scores_gemma":[0.99936503,0.00031699872,0.000029155197,0.00015705603,0.000027439895,0.00010429695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024028585,0.00015387282,0.00018331542,0.00008659073,0.000045791337,0.000019842542,0.00008980523,0.00023974584,0.00004727312],"category_scores_gemma":[0.00003976724,0.0001559014,0.00004968306,0.00027687085,0.000013325121,0.000107464846,0.0000061096525,0.00021213313,0.00000392629],"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":[0.00005594069,0.000015482567,0.00008517913,0.000012380928,0.000008780955,0.00000520931,0.00003435901,0.9797842,0.000119636,0.0036762014,0.00018438691,0.016018271],"study_design_scores_gemma":[0.0008059643,0.000024942288,0.00007132656,0.000046036468,0.000007103556,0.0000010349677,0.00002358594,0.99548095,0.0004753426,0.0014854759,0.0013872258,0.00019100748],"about_ca_topic_score_codex":8.388118e-7,"about_ca_topic_score_gemma":0.00003698157,"teacher_disagreement_score":0.8302182,"about_ca_system_score_codex":0.00010231061,"about_ca_system_score_gemma":0.0000075038174,"threshold_uncertainty_score":0.6357475},"labels":[],"label_agreement":null},{"id":"W2113676251","doi":"10.1109/ccece.2004.1345043","title":"A coordinated location-based downlink scheduling scheme (CLDSS) in a cellular CDMA network with partitioned cells","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Telecommunications link; Base station; Computer science; Scheduling (production processes); Cellular network; Code division multiple access; Interference (communication); Computer network; Power control; Enhanced Data Rates for GSM Evolution; Transmitter power output; Transmission (telecommunications); Real-time computing; Electronic engineering; Power (physics); Telecommunications; Engineering; Channel (broadcasting); Transmitter","score_opus":0.004418094397872532,"score_gpt":0.17578897469369484,"score_spread":0.17137088029582231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113676251","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":[0.111347444,0.00021924489,0.8869215,0.000096978976,0.000106003215,0.000359824,0.0000016243301,0.0005979987,0.0003493726],"genre_scores_gemma":[0.7992934,0.000013750021,0.20029414,0.00008173196,0.00008456127,0.00006430534,0.00009325851,0.00005718184,0.000017673718],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880266,0.000019500354,0.00032170923,0.00026227813,0.00015728548,0.00043654247],"domain_scores_gemma":[0.9994281,0.000047802685,0.000051943876,0.00026773755,0.00011224534,0.000092149756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010927865,0.00023241447,0.0002199329,0.00008887404,0.000075763994,0.000037609792,0.00011111692,0.0001268922,0.000075141696],"category_scores_gemma":[0.0000100808,0.00023126605,0.000027589153,0.0013293275,0.000040512234,0.00022940148,0.000011687578,0.00022309409,0.000053682536],"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":[0.000029871815,0.0000426157,0.000911411,0.000040966104,0.00001606368,0.000010436494,0.000029834331,0.99611783,0.001910354,0.00074219436,0.000026398162,0.00012205082],"study_design_scores_gemma":[0.001901569,0.00003147128,0.00023043125,0.00024030005,0.000010079732,5.813014e-7,0.00002398292,0.9807211,0.016123256,0.0003065342,0.000074575255,0.0003360932],"about_ca_topic_score_codex":0.000021783862,"about_ca_topic_score_gemma":0.00013184191,"teacher_disagreement_score":0.68794596,"about_ca_system_score_codex":0.00021886213,"about_ca_system_score_gemma":0.000069444766,"threshold_uncertainty_score":0.9430756},"labels":[],"label_agreement":null},{"id":"W2113876301","doi":"10.1109/icc.2006.254801","title":"Novel Scheduling Algorithms for Multimedia Service in OFDM Broadband Wireless Systems","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Link adaptation; Wireless broadband; Orthogonal frequency-division multiplexing; Scheduling (production processes); Algorithm; Wireless; Spectral efficiency; Computer network; WiMAX; Time division multiple access; Broadband networks; Broadband; Wireless network; Fading; Channel (broadcasting); Decoding methods; Telecommunications; Mathematical optimization","score_opus":0.0690371081040146,"score_gpt":0.3127174330668064,"score_spread":0.2436803249627918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113876301","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":[0.014121418,0.0002946024,0.9694317,0.0008909001,0.0012144814,0.00074148923,0.00035597768,0.00032682647,0.012622582],"genre_scores_gemma":[0.91852325,0.0003254567,0.079459205,0.000060051527,0.00021773229,0.00042609975,0.0007148286,0.000049217113,0.00022414928],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988553,0.0000263856,0.00046715353,0.0002084794,0.00020733861,0.00023536714],"domain_scores_gemma":[0.9985693,0.00025868282,0.000108496606,0.0005990874,0.0004212099,0.00004322638],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001358017,0.00019433419,0.00019487584,0.0002153784,0.00010184004,0.00010076778,0.00086010626,0.000117993295,0.000014712023],"category_scores_gemma":[0.000018903647,0.00022995967,0.00004174721,0.00028361077,0.000049678772,0.0002582197,0.000050981358,0.00026361117,0.000026780912],"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":[0.000010887792,0.00012318193,0.00016835064,0.000021242031,0.000021978562,3.254548e-7,0.00006673064,0.9678684,0.0055296943,0.023578925,0.00018908468,0.0024211823],"study_design_scores_gemma":[0.00079948327,0.000009780237,0.00043496315,0.00020250668,0.000006852876,0.0000031456402,0.00008848465,0.99583155,0.00044957653,0.00036658774,0.0015786213,0.00022846204],"about_ca_topic_score_codex":0.00036292887,"about_ca_topic_score_gemma":0.0011537019,"teacher_disagreement_score":0.90440184,"about_ca_system_score_codex":0.00022195143,"about_ca_system_score_gemma":0.000042613134,"threshold_uncertainty_score":0.9377483},"labels":[],"label_agreement":null},{"id":"W2114157974","doi":"10.1109/wcnc.2007.292","title":"A Joint Channel and Queue-Aware Scheduling for IEEE 802.16 Wireless Metropolitan Area Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","funders":"","keywords":"Computer science; Computer network; Scheduling (production processes); Queue; Base station; IEEE 802; Quality of service; Real-time computing; Mathematical optimization; Mathematics","score_opus":0.016913933412123085,"score_gpt":0.23150545529674682,"score_spread":0.21459152188462374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114157974","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":[0.028752046,0.0006823017,0.96786153,0.0000410933,0.0005091508,0.0004026597,0.000005448965,0.0005845821,0.0011612041],"genre_scores_gemma":[0.9568395,0.00031491806,0.04200958,0.00008761993,0.00045143897,0.00004251359,0.000034434303,0.000099779936,0.0001202334],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986584,0.00000876176,0.00034538307,0.0002767096,0.000114498565,0.0005962319],"domain_scores_gemma":[0.9992823,0.00012958754,0.000052819356,0.0002730723,0.00009207618,0.0001701234],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002538492,0.00025580826,0.00029087486,0.00013897104,0.0001223131,0.000040855688,0.00011503695,0.00017336618,0.000012923406],"category_scores_gemma":[0.000024533856,0.00025731447,0.0000638302,0.00027658304,0.00004145193,0.00021188473,0.00003567975,0.0001807739,0.0000018825369],"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":[0.00001978743,0.000010437802,0.000060466024,0.00006020335,0.000038265454,0.0000023889424,0.000047382102,0.991451,0.00024970638,0.0023105515,0.00046721584,0.0052825967],"study_design_scores_gemma":[0.00047905743,0.00003422041,0.000047717236,0.00007041399,0.00001850771,0.0000069664134,0.00051014684,0.9945732,0.0031991317,0.00061390776,0.0001290254,0.00031771805],"about_ca_topic_score_codex":0.000020585541,"about_ca_topic_score_gemma":0.00017387644,"teacher_disagreement_score":0.9280874,"about_ca_system_score_codex":0.00032573508,"about_ca_system_score_gemma":0.0000080462,"threshold_uncertainty_score":0.9999879},"labels":[],"label_agreement":null},{"id":"W2114555191","doi":"10.1109/icc.2009.5198947","title":"Downlink Resource Allocation for OFDMA-Based Multiservice Networks with Imperfect CSI","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Quality of service; Computer network; Resource allocation; Orthogonal frequency-division multiplexing; Telecommunications link; Resource management (computing); Orthogonal frequency-division multiple access; Frequency-division multiple access; Call Admission Control; Channel state information; Channel allocation schemes; Channel (broadcasting); Wireless network; Telecommunications; Wireless","score_opus":0.004106629123933301,"score_gpt":0.19698537239738587,"score_spread":0.19287874327345256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114555191","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":[0.0045934,0.00031118616,0.99269235,0.0003043315,0.000055329994,0.00051458064,0.00000278855,0.0007725596,0.0007534954],"genre_scores_gemma":[0.87465954,0.00004907007,0.12409193,0.0005927293,0.0002005278,0.00009507087,0.000164625,0.000052830193,0.00009369066],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924755,0.000012254972,0.00017339346,0.00019453425,0.00009460523,0.00027763544],"domain_scores_gemma":[0.9995006,0.00009186416,0.000037140573,0.00022501759,0.00007990418,0.00006547761],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007217921,0.0001759488,0.00014702068,0.00005312479,0.00007029963,0.000028414684,0.00010664856,0.00009993685,0.00001723701],"category_scores_gemma":[0.000006705767,0.00015629448,0.000034745008,0.0002797582,0.000010528319,0.00014558558,0.000004212342,0.00010114085,0.0000028794616],"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":[0.000057912504,0.00001600009,0.00007735087,0.000020132127,0.0000111223435,4.3837645e-7,0.000020363916,0.9679,0.0003058248,0.0001229214,0.000733047,0.030734925],"study_design_scores_gemma":[0.00086367974,0.00009837234,0.00053465506,0.00005045079,0.000020900703,8.4608513e-7,0.000010870901,0.9942529,0.0018731204,0.000017740764,0.0020509022,0.00022552058],"about_ca_topic_score_codex":0.0000033885074,"about_ca_topic_score_gemma":0.000031756714,"teacher_disagreement_score":0.8700661,"about_ca_system_score_codex":0.00006272808,"about_ca_system_score_gemma":0.000009624558,"threshold_uncertainty_score":0.6373504},"labels":[],"label_agreement":null},{"id":"W2114703162","doi":"10.1109/lcomm.2006.1613746","title":"Optimal downlink resource allocation for non-realtime traffic in cellular CDMA/TDMA networks","year":2006,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":24,"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":"Time division multiple access; Computer science; Cellular network; Computer network; Telecommunications link; Base station; Code division multiple access; Scheduling (production processes); Resource allocation; Network packet; Mathematical optimization","score_opus":0.009276069348611304,"score_gpt":0.2182251940281604,"score_spread":0.2089491246795491,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114703162","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":[0.101429395,0.0006657012,0.89433086,0.0019710811,0.00016477877,0.0007295825,0.000010051307,0.00037407508,0.00032448722],"genre_scores_gemma":[0.9011648,0.00018258125,0.09691254,0.00025595378,0.00018433963,0.00036741683,0.0008104402,0.00008387631,0.00003802025],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987626,0.000067584624,0.00047799564,0.00022073695,0.000087862594,0.00038321977],"domain_scores_gemma":[0.99830174,0.0002827505,0.00009084687,0.001232344,0.000045245026,0.000047073438],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021128412,0.0002158034,0.00021714137,0.00019060214,0.00017845299,0.00004581817,0.00068490714,0.00013699682,0.0000036091428],"category_scores_gemma":[0.0000089229,0.00027239945,0.00007668819,0.0005048481,0.000096997755,0.00021149931,0.00004274768,0.00032649166,0.000011473335],"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":[0.000009159238,0.000044202978,0.00004657864,0.000015927702,0.000011676459,6.7595664e-7,0.00009957986,0.9845657,0.004841447,0.00009918624,0.0072419997,0.0030238654],"study_design_scores_gemma":[0.00054081343,0.000010651117,0.00022522942,0.000051077637,0.00001672386,0.0000014122286,0.000023058003,0.9916396,0.0006042116,0.000013504544,0.0066043744,0.00026934908],"about_ca_topic_score_codex":0.000029076014,"about_ca_topic_score_gemma":0.00015778537,"teacher_disagreement_score":0.7997354,"about_ca_system_score_codex":0.00023049627,"about_ca_system_score_gemma":0.000011964195,"threshold_uncertainty_score":0.9999728},"labels":[],"label_agreement":null},{"id":"W2115065691","doi":"10.1109/wcnc.2004.1311358","title":"An efficient bit allocation algorithm for multicarrier modulation","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Throughput; Computer science; Computational complexity theory; Bit error rate; Algorithm; Bit (key); Constraint (computer-aided design); Mathematics; Wireless; Decoding methods; Telecommunications; Computer network","score_opus":0.006384795317989342,"score_gpt":0.23071504026256798,"score_spread":0.22433024494457865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115065691","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":[0.024637101,0.000018812036,0.97421783,0.000019906252,0.00017627994,0.00032350086,0.000004217112,0.00045989145,0.00014247745],"genre_scores_gemma":[0.58390176,0.0000045141846,0.41586983,0.000011952338,0.00006859095,0.000038053222,0.000071981936,0.000021400514,0.00001188709],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99952996,0.0000039630063,0.00012599825,0.00012446022,0.0000761641,0.00013946314],"domain_scores_gemma":[0.99972624,0.0000126828945,0.000014457766,0.00013708205,0.000060820534,0.0000487139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046786,0.000083978695,0.000063969484,0.000034868146,0.00004600191,0.000016520042,0.00004527883,0.00005283965,0.000009465813],"category_scores_gemma":[0.0000056149415,0.00008785151,0.000019938063,0.00011908091,0.000009066025,0.0001409291,0.000003235533,0.000031436048,0.000007823951],"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":[0.0000012565624,0.000016351336,0.0000034355705,0.0000043649075,0.0000042596234,7.702683e-8,0.00006704986,0.918572,0.0015225864,0.0011617223,0.0000070459487,0.078639835],"study_design_scores_gemma":[0.00045144552,0.000021096466,0.00019171424,0.0000060523303,0.0000049929213,4.941546e-7,0.000020617174,0.992513,0.0062032854,0.0003772546,0.0000954018,0.00011462829],"about_ca_topic_score_codex":0.0000031393106,"about_ca_topic_score_gemma":0.0000044076396,"teacher_disagreement_score":0.55926466,"about_ca_system_score_codex":0.00010698641,"about_ca_system_score_gemma":0.000006282377,"threshold_uncertainty_score":0.35824805},"labels":[],"label_agreement":null},{"id":"W2115353956","doi":"10.11648/j.wcmc.20140202.11","title":"Optimal Load Balancing Algorithm for Multi-Cell LTE Networks","year":2014,"lang":"en","type":"article","venue":"International Journal of Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Handover; Load balancing (electrical power); Latency (audio); Computer network; Network packet; Bandwidth (computing); LTE Advanced; Algorithm; Distributed computing; Telecommunications link; Telecommunications; Mathematics; Grid","score_opus":0.011289238741396689,"score_gpt":0.2675107536138493,"score_spread":0.2562215148724526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115353956","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":[0.02563896,0.002687066,0.9706617,0.00003865228,0.00065211934,0.00014559865,0.0000055425203,0.00005920866,0.00011116425],"genre_scores_gemma":[0.6228011,0.001487455,0.37534666,0.000027393446,0.0002792047,0.0000089475625,0.000014599408,0.000024643894,0.000009975499],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895626,0.000048246,0.0005338984,0.00010425045,0.00018167643,0.00017566931],"domain_scores_gemma":[0.9983357,0.00038111833,0.00028841276,0.00026395248,0.0006553865,0.00007542001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044199778,0.00014119137,0.00022239846,0.000107170796,0.00014514517,0.00008784287,0.0006720846,0.00006745579,0.0000020472887],"category_scores_gemma":[0.000023359285,0.0001488046,0.00008406859,0.00009139942,0.000059236376,0.0002076397,0.00018080435,0.00027088044,6.9842764e-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":[0.000003586826,0.000035316327,0.0000762014,0.000006065673,0.00003768928,4.9585907e-7,0.00015407593,0.6358771,0.00014818592,0.000077700795,0.00004951771,0.36353412],"study_design_scores_gemma":[0.0010101526,0.000055863908,0.000056992536,0.00013539485,0.000017437076,0.000038128568,0.00011231251,0.9917737,0.00017162829,0.000014761478,0.0064710197,0.00014258845],"about_ca_topic_score_codex":0.000003033039,"about_ca_topic_score_gemma":0.000002826322,"teacher_disagreement_score":0.5971621,"about_ca_system_score_codex":0.00012660354,"about_ca_system_score_gemma":0.000025795862,"threshold_uncertainty_score":0.60680753},"labels":[],"label_agreement":null},{"id":"W2115428863","doi":"10.1109/cdc.2008.4739401","title":"Transmission control in cognitive radio systems with latency constraints as a switching control dynamic game","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Nash equilibrium; Computer science; Cognitive radio; Markov decision process; Mathematical optimization; Markov process; Game theory; Fading; Sequential game; Transmission (telecommunications); Channel (broadcasting); Computer network; Mathematics; Mathematical economics; Telecommunications; Wireless","score_opus":0.0044442419400245,"score_gpt":0.1975316423504605,"score_spread":0.193087400410436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115428863","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":[0.11493638,0.0006603526,0.88053024,0.000023515026,0.00008400648,0.00078019896,0.000007894855,0.0003745878,0.002602803],"genre_scores_gemma":[0.9982115,0.00027779478,0.0011929985,0.000051727133,0.000026057363,0.00007781831,0.000014288645,0.000060931623,0.00008687172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988046,0.00005339906,0.00034355544,0.0002423479,0.00018554476,0.00037053417],"domain_scores_gemma":[0.99948454,0.00018092718,0.000052106287,0.00010624298,0.00006293918,0.000113224305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000091009046,0.00024769455,0.00038946184,0.00013339023,0.00005686417,0.000018623537,0.00007640391,0.00011573632,0.0000574109],"category_scores_gemma":[0.000013433528,0.00021197106,0.000037482907,0.0002390495,0.00007025771,0.00026319377,0.0000026688876,0.00026387267,0.000016837357],"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":[0.0001495364,0.000026075277,0.001325694,0.000035705907,0.000062802064,0.00016306412,0.00045425323,0.9914803,0.0011982897,0.0000936191,0.0000059273884,0.005004756],"study_design_scores_gemma":[0.0065787104,0.00007824719,0.0010907631,0.0003925198,0.000026710735,0.0002459489,0.00019110447,0.991005,0.000052284933,0.000025772919,0.000019456329,0.00029349164],"about_ca_topic_score_codex":0.000030446527,"about_ca_topic_score_gemma":0.000018873445,"teacher_disagreement_score":0.88327515,"about_ca_system_score_codex":0.000122025485,"about_ca_system_score_gemma":0.000042688836,"threshold_uncertainty_score":0.8643929},"labels":[],"label_agreement":null},{"id":"W2115457591","doi":"10.1109/pacrim.2007.4313287","title":"A Cost Minimization Algorithm for a Multiuser OFDM Cognitive Radio System","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Cognitive radio; Orthogonal frequency-division multiplexing; Computer science; Transmitter power output; Base station; Interference (communication); Resource allocation; Electronic engineering; Minification; Algorithm; Computer network; Transmitter; Telecommunications; Engineering; Wireless; Channel (broadcasting)","score_opus":0.013521261805663948,"score_gpt":0.2471476083523074,"score_spread":0.23362634654664344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115457591","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":[0.0006005533,0.00010356713,0.99511206,0.0000034212696,0.00034823944,0.00093911524,0.000026259011,0.00077028037,0.0020964888],"genre_scores_gemma":[0.43722042,0.00003060492,0.5616014,0.00003306694,0.0002949818,0.0001639297,0.0002047985,0.00008991707,0.00036089856],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923235,0.000007587217,0.00023669015,0.00015526022,0.00009399925,0.00027413582],"domain_scores_gemma":[0.9994719,0.00019521215,0.000036266923,0.00008674346,0.00013914095,0.000070727656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011656476,0.00013833736,0.00014741257,0.00008805554,0.000056088866,0.000018005636,0.00004976457,0.00009332427,0.00001340516],"category_scores_gemma":[0.000022303855,0.00014455982,0.00003927608,0.00022166883,0.000014974466,0.00016802961,0.000007947446,0.000055772012,0.000015416268],"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":[0.000025468622,0.000018508617,0.00005713896,0.00008269668,0.000050076636,0.000004466382,0.00023389446,0.7266679,0.000078913225,0.0003490845,0.0006736158,0.27175826],"study_design_scores_gemma":[0.0010365178,0.000017747843,0.00009756021,0.00007127937,0.000021744649,0.0000065036625,0.00053479156,0.9937083,0.0033787354,0.000004449718,0.0009409251,0.00018141509],"about_ca_topic_score_codex":0.0000022765012,"about_ca_topic_score_gemma":0.000013364362,"teacher_disagreement_score":0.43661988,"about_ca_system_score_codex":0.00015089873,"about_ca_system_score_gemma":0.0000066324187,"threshold_uncertainty_score":0.5894978},"labels":[],"label_agreement":null},{"id":"W2115774703","doi":"10.1109/icbn.2005.1589642","title":"Adaptive BCPM downlink resource allocation strategies for multiuser OFDM in cellular systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"McGill University","funders":"","keywords":"Orthogonal frequency-division multiplexing; Telecommunications link; Computer science; Fading; Bandwidth (computing); Resource allocation; Transmission (telecommunications); Network packet; Bandwidth allocation; Minification; Interference (communication); Computer network; Electronic engineering; Mathematical optimization; Telecommunications; Mathematics; Engineering; Channel (broadcasting)","score_opus":0.011321696845865314,"score_gpt":0.21126920673404115,"score_spread":0.19994750988817583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115774703","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":[0.009754812,0.00070137135,0.9851589,0.000045172143,0.00009869112,0.000564346,0.000004314745,0.0003470805,0.0033252677],"genre_scores_gemma":[0.95463663,0.000037565827,0.044381376,0.000018437986,0.0002199912,0.00013891091,0.000055386234,0.00004212254,0.0004695833],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992634,0.00001717808,0.0002543938,0.00015962796,0.00008711437,0.00021830673],"domain_scores_gemma":[0.9996649,0.00006822167,0.000032401687,0.00015352778,0.000046765825,0.00003420409],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009715295,0.0001338425,0.00014042936,0.00008456932,0.000028991928,0.00003628467,0.00008269638,0.000098599805,0.000011948353],"category_scores_gemma":[0.000006787614,0.00013777566,0.000025088808,0.00015916319,0.000012852875,0.00036301775,0.000009154528,0.00008823789,0.000020069645],"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":[0.0000129299415,0.000011952988,0.000015024062,0.00003215991,0.000008966205,3.854734e-7,0.00028369413,0.9914064,0.0011020554,0.0039075427,0.00053895393,0.002679932],"study_design_scores_gemma":[0.00041648498,0.00001638285,0.0000314649,0.000037885966,0.00000467976,4.5535364e-7,0.0010762609,0.98913205,0.0014884085,0.00006101537,0.0075700157,0.00016490286],"about_ca_topic_score_codex":0.00001788934,"about_ca_topic_score_gemma":0.00009416714,"teacher_disagreement_score":0.9448818,"about_ca_system_score_codex":0.00014067335,"about_ca_system_score_gemma":0.000012228813,"threshold_uncertainty_score":0.56183285},"labels":[],"label_agreement":null},{"id":"W2116262251","doi":"10.1109/istel.2008.4651311","title":"An efficient scheduling scheme for heterogeneous traffic in IEEE 802.16 wireless metropolitan area networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Scheduling (production processes); IEEE 802; Queue; Quality of service; Base station; Schedule; Real-time computing; Engineering","score_opus":0.015527916176203698,"score_gpt":0.23389045956870702,"score_spread":0.21836254339250333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116262251","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":[0.49137083,0.00027726337,0.5073626,0.000003921812,0.0002185191,0.00026742113,0.000002485726,0.00038850357,0.00010844022],"genre_scores_gemma":[0.9377797,0.00017279024,0.061507866,0.000034930446,0.00021632128,0.0000984572,0.0000527024,0.000114847615,0.00002234383],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983903,0.000025378664,0.00041839876,0.00036787032,0.00013970662,0.0006583073],"domain_scores_gemma":[0.99930036,0.00008724272,0.000047138543,0.00034024534,0.000063976644,0.00016105901],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011474146,0.0002969839,0.00033576242,0.0001899743,0.0001297872,0.000024935402,0.00020292768,0.00017954406,0.000021211423],"category_scores_gemma":[0.000010017398,0.00031764238,0.00008969003,0.0004744841,0.000054402975,0.00014992579,0.000012703518,0.00020594975,0.000004334663],"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":[0.000025225441,0.00006984202,0.0001599073,0.000020925047,0.000019471263,0.00001016217,0.00006753738,0.9970157,0.00041052603,0.0002164388,0.000046075467,0.0019381687],"study_design_scores_gemma":[0.0006966694,0.00006002409,0.000023681252,0.00003368301,0.000006941572,0.00002170793,0.000099153585,0.99635124,0.0022931045,0.000012138111,0.000034047418,0.0003675867],"about_ca_topic_score_codex":0.000008657232,"about_ca_topic_score_gemma":0.000113686794,"teacher_disagreement_score":0.44640893,"about_ca_system_score_codex":0.00057440944,"about_ca_system_score_gemma":0.00001796246,"threshold_uncertainty_score":0.9999276},"labels":[],"label_agreement":null},{"id":"W2116393553","doi":"10.1109/mwc.2009.5281258","title":"Downlink scheduling for multimedia multicast/broadcast over mobile wimax: connection-oriented multistate adaptation","year":2009,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Computer network; WiMAX; Multimedia Broadcast Multicast Service; Multicast; Link adaptation; Quality of service; Scheduling (production processes); Digital multimedia broadcasting; Distributed computing; Telecommunications; Fading; Wireless","score_opus":0.02078327591785398,"score_gpt":0.2814209818153356,"score_spread":0.2606377058974816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116393553","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":[0.08007475,0.00080136146,0.9156739,0.0001295013,0.0005028805,0.0013373849,0.00012462326,0.0010309746,0.00032458603],"genre_scores_gemma":[0.7496362,0.001117147,0.24781346,0.000059099148,0.00011628054,0.00054414844,0.00060267036,0.00007056795,0.00004045978],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833643,0.00007411523,0.0006184731,0.00032754056,0.00019294179,0.00045050596],"domain_scores_gemma":[0.9975373,0.00054300827,0.00016371564,0.0012819443,0.0003230129,0.00015098663],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016017158,0.00032576977,0.0003258046,0.00019159203,0.0004799974,0.00006675899,0.00051826914,0.00018181404,0.000016020484],"category_scores_gemma":[0.00006906416,0.00038963972,0.00012140713,0.0005327239,0.00013004498,0.00053465413,0.00004040064,0.000377421,0.0000317311],"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":[0.000028281429,0.00013996269,0.00003662178,0.000022111439,0.000040134502,5.4127514e-7,0.0008625369,0.8887631,0.008448085,0.0010169491,0.00010064846,0.10054102],"study_design_scores_gemma":[0.0014297944,0.00006513379,0.00028183544,0.000090112146,0.000042659292,0.0000037668506,0.00041725332,0.9904317,0.0019796297,0.0001574717,0.00469015,0.0004104419],"about_ca_topic_score_codex":0.000014626256,"about_ca_topic_score_gemma":0.000071714974,"teacher_disagreement_score":0.6695614,"about_ca_system_score_codex":0.00022384952,"about_ca_system_score_gemma":0.00003443632,"threshold_uncertainty_score":0.9998556},"labels":[],"label_agreement":null},{"id":"W2116525964","doi":"10.1109/tmm.2006.876227","title":"Opportunistic scheduling for streaming multimedia users in high-speed downlink packet access (HSDPA)","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":27,"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":"Simon Fraser University; Sharif University of Technology","keywords":"Computer science; Link adaptation; Quality of service; Telecommunications link; Network packet; Robustness (evolution); Scheduling (production processes); Computer network; Real-time computing; Distributed computing; Fading; Channel (broadcasting); Mathematical optimization; Mathematics","score_opus":0.020007289529344045,"score_gpt":0.25895053686530695,"score_spread":0.2389432473359629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116525964","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":[0.08468491,0.00004399996,0.91197145,0.00005736005,0.0014679505,0.0008409548,0.00023186063,0.0006086939,0.00009281113],"genre_scores_gemma":[0.8772413,0.000122046265,0.12169181,0.00002575653,0.00024918202,0.00019125675,0.0002529413,0.0001338877,0.00009177829],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980851,0.000033670713,0.0005869366,0.00043631304,0.00024843213,0.00060956477],"domain_scores_gemma":[0.99879277,0.00054267404,0.0000899508,0.00033190544,0.00008690235,0.00015580867],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013890123,0.000393009,0.00038993356,0.00044617383,0.00014471811,0.000076423894,0.00026217353,0.00026085207,0.00007206043],"category_scores_gemma":[0.000021391634,0.00045566825,0.00012177215,0.00053664926,0.00007451483,0.00055324024,0.0000019547801,0.00043352257,0.000027756467],"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":[0.00005423561,0.00012242667,0.00016389883,0.00006342121,0.000031359847,0.000010715697,0.00010376529,0.9522181,0.0038296075,0.00000888174,0.00007152765,0.043322045],"study_design_scores_gemma":[0.0021856516,0.00003377377,0.0007676642,0.00011221758,0.000043320557,0.0000022161769,0.000059601378,0.9828664,0.013287756,0.00009655046,0.00008003876,0.00046482414],"about_ca_topic_score_codex":0.00013054766,"about_ca_topic_score_gemma":0.0005981799,"teacher_disagreement_score":0.7925564,"about_ca_system_score_codex":0.0002927559,"about_ca_system_score_gemma":0.00004297366,"threshold_uncertainty_score":0.9997895},"labels":[],"label_agreement":null},{"id":"W2117005746","doi":"10.1145/1185373.1185441","title":"Opportunistic fair scheduling for the downlink of <i>IEEE</i> 802.16 wireless metropolitan area networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":40,"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":"Computer science; IEEE 802; Computer network; Telecommunications link; Scheduling (production processes); Metropolitan area; Wireless; Inter-Access Point Protocol; Wireless network; Wi-Fi; Telecommunications; Engineering; Geography","score_opus":0.012514742885217789,"score_gpt":0.21528495781857776,"score_spread":0.20277021493335998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117005746","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":[0.0028075576,0.0006813269,0.9877036,0.00006143663,0.0004197133,0.00041982025,0.000022992814,0.0003543098,0.007529241],"genre_scores_gemma":[0.9762377,0.0002829627,0.02254714,0.000055199635,0.00037417727,0.00007256619,0.000116266405,0.000075352014,0.00023861602],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987864,0.000014694514,0.00044769485,0.00019436784,0.00015162524,0.00040522928],"domain_scores_gemma":[0.99896693,0.00041626624,0.00009806416,0.00034614894,0.000112634894,0.000059945818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015880493,0.00022453794,0.00028145,0.00006162351,0.0001204246,0.000027314118,0.00022836615,0.000121280376,0.00003080036],"category_scores_gemma":[0.000014970587,0.00017528898,0.00011252168,0.0003218123,0.000083556915,0.00012701727,0.000022148877,0.00015646951,0.0000018081736],"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":[0.000010880624,0.000015363596,0.00011324613,0.00003807033,0.00003804697,6.4986614e-7,0.0000042324605,0.95588803,0.00036802876,0.03865675,0.0015937886,0.0032729204],"study_design_scores_gemma":[0.00032891182,0.000021019838,0.000028112014,0.000035311856,0.000051115658,0.0000022404524,0.00012807052,0.99529374,0.0015975927,0.0011179064,0.0011843492,0.00021161215],"about_ca_topic_score_codex":0.00005106404,"about_ca_topic_score_gemma":0.00010407355,"teacher_disagreement_score":0.97343016,"about_ca_system_score_codex":0.00018576295,"about_ca_system_score_gemma":0.000022289676,"threshold_uncertainty_score":0.7148077},"labels":[],"label_agreement":null},{"id":"W2117144501","doi":"10.1049/iet-com.2008.0340","title":"Multiuser scheduling in high speed downlink packet access","year":2009,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Computer science; Telecommunications link; Scheduling (production processes); Network packet; Channel state information; Computer network; Distributed computing; Real-time computing; Wireless; Mathematical optimization; Telecommunications; Mathematics","score_opus":0.027568153097256836,"score_gpt":0.298303040692188,"score_spread":0.27073488759493114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117144501","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":[0.68142945,0.0037441412,0.28491166,0.0072592637,0.00051414943,0.001172286,0.000042036896,0.002423657,0.018503344],"genre_scores_gemma":[0.9073556,0.0015846256,0.09070524,0.00012953853,0.00003882815,0.0000140210095,0.00012723982,0.00002306514,0.000021839596],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930197,0.000042605174,0.0002623379,0.000112420894,0.0000787476,0.00020194425],"domain_scores_gemma":[0.9985935,0.00010797202,0.00003854992,0.001165372,0.000047953494,0.00004665626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008875548,0.000120144156,0.00014098515,0.000118825854,0.00009045696,0.000053867792,0.0008193039,0.00008130574,0.000022637283],"category_scores_gemma":[0.000036824953,0.00014038735,0.000028195353,0.00052947435,0.00003470711,0.00042830393,0.000102912614,0.00031309007,0.00003292752],"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":[0.0000022417105,0.000042796935,0.0009994387,0.0000037647828,0.0000058080172,5.674676e-7,0.00014619158,0.98830205,0.00042952475,0.0016298961,0.00014148258,0.008296219],"study_design_scores_gemma":[0.00041645378,0.00000744069,0.019686136,0.000060028287,0.000006475939,0.0000011166668,0.000035276324,0.9758429,0.00035128978,0.0020234191,0.0013675633,0.00020188831],"about_ca_topic_score_codex":0.000017790298,"about_ca_topic_score_gemma":0.00013628701,"teacher_disagreement_score":0.22592613,"about_ca_system_score_codex":0.00009011254,"about_ca_system_score_gemma":0.000010526812,"threshold_uncertainty_score":0.572483},"labels":[],"label_agreement":null},{"id":"W2117270077","doi":"10.1155/wcn/2006/80493","title":"Opportunistic Nonorthogonal Packet Scheduling in Fixed Broadband Wireless Access Networks","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Memorial University of Newfoundland; Carleton University; Communications Research Centre Canada","funders":"","keywords":"Computer science; Computer network; Scheduling (production processes); Base station; Network packet; Spectral efficiency; Telecommunications link; Wireless broadband; Wireless network; Wireless; Real-time computing; Channel (broadcasting); Telecommunications","score_opus":0.02762050193162682,"score_gpt":0.26649168394903855,"score_spread":0.23887118201741173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117270077","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":[0.5718565,0.012570992,0.40767625,0.00040326556,0.001217948,0.0005011252,0.000012421045,0.00040755063,0.005353969],"genre_scores_gemma":[0.96706647,0.028313894,0.0033995127,0.000105037856,0.00081871985,0.000034704182,0.000118139586,0.00010934113,0.00003420481],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976314,0.00023507667,0.00092338846,0.00029565507,0.00026289554,0.0006516426],"domain_scores_gemma":[0.9980999,0.0005482141,0.0003088963,0.0007417935,0.000106154585,0.00019500815],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00056557084,0.00039969513,0.00047626038,0.00033108634,0.0005671895,0.0004563788,0.0008681548,0.00019360821,0.000012650669],"category_scores_gemma":[0.000007998143,0.00042574792,0.00009234622,0.0008007571,0.0001662348,0.00057650916,0.00023853964,0.0013618307,0.0000026670116],"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":[0.000030623927,0.00007197232,0.02302761,0.000017102539,0.00003041555,0.000031171887,0.000044436278,0.874748,0.00008268353,0.0016318796,0.00016622651,0.100117885],"study_design_scores_gemma":[0.00077355554,0.00003523259,0.006386667,0.0006445957,0.000024893461,0.00010805817,0.000034234083,0.98762804,0.000013807875,0.000490887,0.0033949872,0.00046502677],"about_ca_topic_score_codex":0.000013096353,"about_ca_topic_score_gemma":0.00020675537,"teacher_disagreement_score":0.40427673,"about_ca_system_score_codex":0.00018503197,"about_ca_system_score_gemma":0.000041185507,"threshold_uncertainty_score":0.99981946},"labels":[],"label_agreement":null},{"id":"W2117518715","doi":"10.1109/tvt.2009.2028430","title":"Subchannel Power-Loading Schemes in Multiuser OFDM Systems","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Scheme (mathematics); Power (physics); Multiplexing; Resource allocation; Electronic engineering; Max-min fairness; Algorithm; Computer network; Mathematics; Telecommunications; Engineering; Channel (broadcasting)","score_opus":0.005569981757099179,"score_gpt":0.20527513795590202,"score_spread":0.19970515619880283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117518715","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":[0.19195063,0.0005109962,0.80518746,0.00014315385,0.00045345892,0.00027294926,0.000004031279,0.001356608,0.00012068101],"genre_scores_gemma":[0.9953878,0.00023832035,0.004154979,0.000028696455,0.000017526121,0.000076507546,0.0000025839076,0.00004635158,0.000047261936],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988884,0.000018454106,0.00030285295,0.00027675575,0.00012488948,0.00038866975],"domain_scores_gemma":[0.99950045,0.00002421565,0.000034145036,0.0003555683,0.000040759962,0.000044852168],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000067419795,0.00022701937,0.00026702226,0.0007483564,0.0000763903,0.000017406148,0.0001821632,0.00041377224,0.000011586656],"category_scores_gemma":[0.000004450113,0.00025852563,0.000058912494,0.0009936361,0.000043936954,0.00017036492,7.3888435e-7,0.00053730514,0.000041477582],"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":[0.000007996592,0.00005766689,0.000014705886,0.000011949741,0.000019353465,0.000024168456,0.000037914808,0.9789804,0.013794389,0.00046512045,0.000015852254,0.006570441],"study_design_scores_gemma":[0.000733503,0.00011514976,0.00003742423,0.0001489512,0.000015307574,0.000038880917,0.0001480645,0.9021871,0.09496175,0.00023580992,0.0009945804,0.0003834644],"about_ca_topic_score_codex":0.000003436801,"about_ca_topic_score_gemma":0.000011686764,"teacher_disagreement_score":0.8034371,"about_ca_system_score_codex":0.00018283317,"about_ca_system_score_gemma":0.00000836431,"threshold_uncertainty_score":0.9999867},"labels":[],"label_agreement":null},{"id":"W2117532109","doi":"10.1109/lcn.2009.5355027","title":"Packet scheduling scheme with quality of service support for mobile WiMAX networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Guelph","funders":"","keywords":"WiMAX; Computer network; Computer science; Quality of service; Interoperability; Scheduling (production processes); Network packet; Mobile QoS; Admission control; Wireless; Service (business); Service provider; Telecommunications","score_opus":0.01345871400521143,"score_gpt":0.26390664267791736,"score_spread":0.25044792867270593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117532109","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":[0.05400426,0.00010264681,0.9433049,0.000036275404,0.00005253226,0.00038067988,0.00000531435,0.0003196167,0.0017937983],"genre_scores_gemma":[0.70399606,0.000033487908,0.29555935,0.00016294446,0.000070444694,0.000035175883,0.00006546828,0.000028090248,0.000048989365],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991766,0.000008873647,0.00029737758,0.00015492487,0.000108673354,0.00025351017],"domain_scores_gemma":[0.99944055,0.00006167077,0.00006671242,0.00022807899,0.00014629612,0.00005668017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014339839,0.00014496414,0.00023458425,0.000032452284,0.00003228967,0.000010909306,0.000097500844,0.00008259052,0.000044698067],"category_scores_gemma":[0.000007639445,0.00013346392,0.000035337627,0.00029655016,0.000012926436,0.00020013431,0.000008787599,0.000090206864,0.0000020498132],"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":[0.00004390224,0.000019859926,0.0003005451,0.00006238073,0.000018212617,2.3104275e-7,0.000038612987,0.99439186,0.0006824838,0.0012000214,0.00009981875,0.0031420542],"study_design_scores_gemma":[0.00055338035,0.000110565474,0.00038789338,0.00003228761,0.000009129339,0.0000011560911,0.00006906747,0.99623555,0.0020045089,0.00015452273,0.00024545813,0.00019646845],"about_ca_topic_score_codex":0.0000035593275,"about_ca_topic_score_gemma":0.000026264926,"teacher_disagreement_score":0.6499918,"about_ca_system_score_codex":0.000030615403,"about_ca_system_score_gemma":0.000013522918,"threshold_uncertainty_score":0.5442501},"labels":[],"label_agreement":null},{"id":"W2117584696","doi":"10.11575/prism/30625","title":"Fair and Efficient Scheduling in Wireless Networks with Successive Interference Cancellation","year":2010,"lang":"en","type":"article","venue":"Open MIND","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Calgary","funders":"","keywords":"Maximum throughput scheduling; Proportionally fair; Computer science; Round-robin scheduling; Fair-share scheduling; Scheduling (production processes); Dynamic priority scheduling; Rate-monotonic scheduling; Job shop scheduling; Greedy algorithm; Distributed computing; Computer network; Mathematical optimization; Algorithm; Mathematics; Quality of service","score_opus":0.007689169303635924,"score_gpt":0.23364514851736165,"score_spread":0.22595597921372573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117584696","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":[0.698267,0.000034923247,0.3003215,0.000009713226,0.00010771734,0.00018928516,9.318837e-7,0.000005279575,0.0010636842],"genre_scores_gemma":[0.9742592,0.000022929135,0.025601892,0.0000030571746,0.000042336404,0.000016774495,0.000010893564,0.000019866646,0.000023028479],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994386,0.00000945441,0.00013735726,0.00019043387,0.000055717028,0.00016843916],"domain_scores_gemma":[0.9997167,0.000046327517,0.00004025091,0.00012185276,0.000029251942,0.000045610155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008056487,0.00010992109,0.00012469017,0.000046532597,0.00003877024,0.0000939959,0.00013738552,0.000067401445,0.0000614643],"category_scores_gemma":[0.000006392062,0.00010341498,0.0000051783145,0.00020324912,0.000036895235,0.00018597551,0.000057292993,0.0002495617,0.000004013931],"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":[0.00001788519,0.000005954215,0.0023037582,0.0000040300456,0.0000034519119,0.0000033893928,0.00021376222,0.9386433,0.00092593965,0.000026828006,0.0000010001711,0.057850745],"study_design_scores_gemma":[0.00033874338,0.0000134523925,0.0010199579,0.0001073936,0.0000036384363,0.0000028469863,0.000076187076,0.99630696,0.0019385983,0.000004442492,0.00004528796,0.00014248304],"about_ca_topic_score_codex":0.000019535997,"about_ca_topic_score_gemma":0.0014867539,"teacher_disagreement_score":0.27599224,"about_ca_system_score_codex":0.00003145268,"about_ca_system_score_gemma":0.000015375444,"threshold_uncertainty_score":0.42171404},"labels":[],"label_agreement":null},{"id":"W2117764384","doi":"10.1109/glocom.2005.1578462","title":"Queue-aware uplink bandwidth allocation for polling services in 802.16 broadband wireless networks","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Winnipeg; University of Manitoba","funders":"","keywords":"Polling; Computer network; Computer science; Wireless broadband; Telecommunications link; Quality of service; Bandwidth allocation; Queueing theory; Scheduling (production processes); Broadband networks; Queue; Bandwidth (computing); Wireless; IEEE 802; Call Admission Control; Broadband; Wireless network; Telecommunications; Engineering","score_opus":0.01320950270994596,"score_gpt":0.25245193554416656,"score_spread":0.23924243283422061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117764384","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":[0.024779463,0.0030917483,0.963236,0.001010112,0.0006709175,0.0013964995,0.0001696836,0.0008860644,0.004759527],"genre_scores_gemma":[0.95617193,0.0059514814,0.035398528,0.00029881077,0.00033146708,0.00043817496,0.0011633992,0.00008698821,0.00015919999],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996962,0.00012396899,0.0010808004,0.00055891095,0.00024043643,0.0010338745],"domain_scores_gemma":[0.9975676,0.0002012214,0.00027028247,0.0013675062,0.00035098882,0.00024239272],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003488219,0.0005786934,0.000607839,0.00021944022,0.00040480026,0.00023229061,0.0013369118,0.00045477485,0.00008782809],"category_scores_gemma":[0.000015617845,0.0006900496,0.00014896154,0.0009703481,0.00011407438,0.0008566489,0.0001257528,0.00052162574,0.000048396658],"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":[0.000034516306,0.00012922609,0.001077594,0.00006904613,0.00006447696,6.6398917e-7,0.00011014727,0.9103729,0.00005509163,0.0033218635,0.0025205472,0.082243934],"study_design_scores_gemma":[0.0013099475,0.000033188466,0.0008675119,0.00026060632,0.000047806403,0.000013244581,0.00015317125,0.9741042,0.00023460595,0.00072530255,0.02156695,0.0006834193],"about_ca_topic_score_codex":0.00022323462,"about_ca_topic_score_gemma":0.010882258,"teacher_disagreement_score":0.9313925,"about_ca_system_score_codex":0.0011431435,"about_ca_system_score_gemma":0.0001551485,"threshold_uncertainty_score":0.99955505},"labels":[],"label_agreement":null},{"id":"W2117956838","doi":"10.1109/vtc.2001.956492","title":"A combined rate/power, time and sector allocation in high data rate CDMA systems based on an information-theoretic approach","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Resource allocation; Channel (broadcasting); Power (physics); Transmission (telecommunications); Code division multiple access; Power budget; Real-time computing; Transmitter power output; Focus (optics); Wireless; Resource management (computing); Computer network; Power control; Telecommunications; Transmitter","score_opus":0.009949255417795889,"score_gpt":0.18582395807344332,"score_spread":0.17587470265564742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117956838","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":[0.110332035,0.00007859367,0.87881494,0.00010113825,0.00029280302,0.0012541066,0.00006605318,0.0008448042,0.008215527],"genre_scores_gemma":[0.993597,0.00003844169,0.004782819,0.000064524625,0.000022836,0.00003950782,0.001351448,0.00002971816,0.000073710085],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914896,0.00009027065,0.0002949134,0.00018066524,0.00010548295,0.00017967919],"domain_scores_gemma":[0.99925005,0.0000912491,0.000049694634,0.000509847,0.00003547142,0.000063679916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027590603,0.00016161152,0.00016902485,0.00015842685,0.000036877464,0.000092763024,0.00017272714,0.000084374304,0.000104519495],"category_scores_gemma":[0.000032665135,0.00015844284,0.000006926429,0.0003043724,0.000023849409,0.0011215085,0.000024008536,0.00010521509,0.00005743066],"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":[0.000016054095,0.00003478331,0.000050176575,0.00005716674,0.000005449782,4.4542875e-7,0.00009604989,0.99685013,0.00006991499,0.0020663997,0.0004760987,0.00027730182],"study_design_scores_gemma":[0.00093144836,0.00005607485,0.00033143576,0.000031928324,0.000005552342,7.881868e-7,0.000030715404,0.9982574,0.00005024139,0.0000323947,0.00008515077,0.00018686407],"about_ca_topic_score_codex":0.000011539283,"about_ca_topic_score_gemma":0.000003192987,"teacher_disagreement_score":0.88326496,"about_ca_system_score_codex":0.00006482537,"about_ca_system_score_gemma":0.000005742223,"threshold_uncertainty_score":0.64611113},"labels":[],"label_agreement":null},{"id":"W2118058487","doi":"10.1109/icc.2006.255763","title":"Downlink Joint Base-station Assignment and Packet Scheduling Algorithm for Cellular CDMA/TDMA Networks","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Time division multiple access; Base station; Computer science; Network packet; Computer network; Transmission delay; Telecommunications link; Scheduling (production processes); Cellular network; Code division multiple access; Optimization problem; Real-time computing; Algorithm; Mathematical optimization; Mathematics","score_opus":0.05015300850426564,"score_gpt":0.27860984354282886,"score_spread":0.22845683503856323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118058487","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":[0.0013622041,0.00031388493,0.9916267,0.0008781936,0.00048210545,0.00042218744,0.00018922746,0.00022328038,0.0045022345],"genre_scores_gemma":[0.77648145,0.0010009609,0.22009197,0.00008212186,0.000262307,0.00025703496,0.0015796865,0.00004404647,0.00020039415],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988471,0.00005095251,0.00043584028,0.00023453594,0.00019947402,0.00023205958],"domain_scores_gemma":[0.9987808,0.00019005647,0.00013375391,0.0005430446,0.00029027104,0.00006207099],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018293163,0.00021309585,0.00017581905,0.00014694504,0.00021248385,0.00012921655,0.00040314844,0.00011357305,0.000047733967],"category_scores_gemma":[0.00001817534,0.00024341799,0.00005744486,0.00013260942,0.00008985217,0.00024291169,0.0000579502,0.0002617112,0.000013038038],"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":[0.0000060042657,0.00007140938,0.000043896205,0.0000074831805,0.00003814615,5.752225e-7,0.000032594355,0.9360316,0.0020521635,0.026607161,0.0010892078,0.034019783],"study_design_scores_gemma":[0.00046649747,0.00002888499,0.00012090234,0.0000863663,0.000018018829,0.0000018308876,0.000053843618,0.9920307,0.0015105418,0.0034765669,0.001963003,0.00024284062],"about_ca_topic_score_codex":0.00003009737,"about_ca_topic_score_gemma":0.000069013084,"teacher_disagreement_score":0.77511925,"about_ca_system_score_codex":0.00019173852,"about_ca_system_score_gemma":0.00002651548,"threshold_uncertainty_score":0.99262977},"labels":[],"label_agreement":null},{"id":"W2118426586","doi":"10.1109/glocom.2009.5426297","title":"A Graph-Based Resource Allocation Algorithm for Downlink MIMO-OFDMA Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"","keywords":"Computer science; Orthogonal frequency-division multiplexing; Telecommunications link; Orthogonal frequency-division multiple access; MIMO; Resource allocation; Graph coloring; Algorithm; MIMO-OFDM; Frequency-division multiple access; Throughput; Frame (networking); Graph; Mathematical optimization; Computer network; Theoretical computer science; Mathematics; Wireless; Telecommunications","score_opus":0.005627964591812275,"score_gpt":0.20803561048774194,"score_spread":0.20240764589592966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118426586","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":[0.00018267523,0.00047558473,0.9967384,0.00031312383,0.00014687706,0.00041769407,0.000005226491,0.0008710108,0.0008494141],"genre_scores_gemma":[0.2312633,0.00022150073,0.76573855,0.0010593305,0.000677698,0.0001902038,0.00045570362,0.000088803135,0.00030494464],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991668,0.000013248603,0.00022367893,0.00019537765,0.000098775636,0.00030213685],"domain_scores_gemma":[0.99954623,0.000073186064,0.000036077607,0.00020993997,0.000062468185,0.000072105984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000090914815,0.00017069552,0.00014892215,0.00009150595,0.00007415763,0.000029534087,0.000112627,0.00012877116,0.000021949563],"category_scores_gemma":[0.000007493463,0.00017703667,0.00007031349,0.0003445315,0.0000147216215,0.00012458322,0.000004426323,0.000105784056,0.000003344936],"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":[0.000005419599,0.00001258666,0.000004494272,0.000004666826,0.0000072448274,2.9477715e-7,0.000007787703,0.7093118,0.000064749926,0.0002551751,0.0028802636,0.28744555],"study_design_scores_gemma":[0.00052050385,0.000048118403,0.00008606019,0.000026819676,0.00001530714,5.852825e-7,0.0000075083026,0.9909901,0.00076165353,0.000364082,0.006961099,0.00021818545],"about_ca_topic_score_codex":0.0000012550357,"about_ca_topic_score_gemma":0.0000036559495,"teacher_disagreement_score":0.28722736,"about_ca_system_score_codex":0.00005057248,"about_ca_system_score_gemma":0.0000073560177,"threshold_uncertainty_score":0.72193456},"labels":[],"label_agreement":null},{"id":"W2118546815","doi":"10.1142/s1793830912500401","title":"OPTIMIZING DATA THROUGHPUT IN CLIENT/SERVER SYSTEMS BY KEEPING QUEUE SIZES BALANCED","year":2012,"lang":"en","type":"article","venue":"Discrete Mathematics Algorithms and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Carleton University","funders":"","keywords":"Server; Computer science; Computer network; Throughput; Queue; Client–server model; Server farm; Network packet; Service (business); Operating system; Wireless","score_opus":0.01945101131439236,"score_gpt":0.2631627647524371,"score_spread":0.24371175343804474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118546815","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":[0.0023478428,0.004620809,0.9906779,0.000028139744,0.000088344,0.0006224181,0.00013174477,0.00019053227,0.0012922478],"genre_scores_gemma":[0.6582942,0.0028624486,0.33634388,0.000036215268,0.0003903352,0.00080562016,0.0010380419,0.00013443767,0.00009481201],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988893,0.000013115302,0.00038720787,0.00023487092,0.00013517507,0.0003403213],"domain_scores_gemma":[0.9990993,0.000104594845,0.00008557379,0.00059238804,0.000023354041,0.0000947524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002142363,0.00018705241,0.00025301398,0.00004861193,0.00010091769,0.00008034346,0.00025292858,0.00008080621,0.0000060998213],"category_scores_gemma":[0.000010798521,0.0001890614,0.000018836625,0.00023912774,0.000037537942,0.0005136575,0.00012547913,0.00013516069,0.00001156464],"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":[0.000002133931,0.00019955581,0.00049183314,0.0008094679,0.00009328487,5.3609523e-7,0.002123838,0.93722594,0.0009116852,0.044522453,0.0010608863,0.012558369],"study_design_scores_gemma":[0.00020283958,0.0000030364588,0.00003253939,0.00008968621,0.000018860263,0.000003585539,0.0005433572,0.99425304,0.0000965635,0.0003966055,0.0041202153,0.00023966283],"about_ca_topic_score_codex":0.000011269926,"about_ca_topic_score_gemma":0.0000035727667,"teacher_disagreement_score":0.6559464,"about_ca_system_score_codex":0.000047719604,"about_ca_system_score_gemma":0.0000051692045,"threshold_uncertainty_score":0.77097},"labels":[],"label_agreement":null},{"id":"W2118549179","doi":"10.1109/icc.2000.853067","title":"A fuzzy resource controller for non-real-time traffic in wireless networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer network; Computer science; Wireless network; Fading; Wireless; Fuzzy logic; Controller (irrigation); Channel (broadcasting); Wireline; Resource allocation; Wi-Fi array; Real-time computing; Telecommunications","score_opus":0.006572140981630661,"score_gpt":0.19211181334991337,"score_spread":0.1855396723682827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118549179","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":[0.10559789,0.00039943313,0.825923,0.0001325119,0.00025077115,0.001825505,0.000007868084,0.0015012322,0.064361766],"genre_scores_gemma":[0.991279,0.00026585453,0.0061732875,0.000058579222,0.00021683819,0.00016777865,0.000023736591,0.00009341847,0.0017214762],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989564,0.000015598253,0.00030268412,0.00021291192,0.00007489261,0.0004375118],"domain_scores_gemma":[0.9995188,0.00018349176,0.000031786392,0.00016792468,0.000024604502,0.00007337481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009239423,0.00019786003,0.00030098518,0.0000977533,0.00004296871,0.00002443481,0.00012073833,0.00014795907,0.000088138455],"category_scores_gemma":[0.000007731874,0.00020369203,0.00006540383,0.00031583308,0.000020560345,0.0001238436,0.00001194346,0.00013172827,0.000037177128],"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":[0.000023255494,0.000023627157,0.000016332737,0.0000130038,0.000014623846,0.0000018692214,0.00008109203,0.9660622,0.00017885746,0.00017765719,0.008632732,0.024774771],"study_design_scores_gemma":[0.001711275,0.000026022035,0.000048258513,0.000032901644,0.0000076046526,0.0000015169725,0.000018380313,0.99684805,0.00002992983,0.000027428343,0.0010108751,0.0002377867],"about_ca_topic_score_codex":0.0000022878767,"about_ca_topic_score_gemma":0.000024793497,"teacher_disagreement_score":0.88568115,"about_ca_system_score_codex":0.000082686696,"about_ca_system_score_gemma":0.0000020368348,"threshold_uncertainty_score":0.83063203},"labels":[],"label_agreement":null},{"id":"W2118762829","doi":"10.1109/icc.2010.5502487","title":"Proportional Fair Scheduling in Multi-Carrier Networks Using Channel Predictions","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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","funders":"","keywords":"Computer science; Proportionally fair; Maximum throughput scheduling; Scheduling (production processes); Fairness measure; Channel (broadcasting); Wireless network; Processor scheduling; Distributed computing; Throughput; Round-robin scheduling; Wireless; Fair-share scheduling; Computer network; Mathematical optimization; Quality of service; Resource (disambiguation); Telecommunications","score_opus":0.0167943151948522,"score_gpt":0.24404790416446556,"score_spread":0.22725358896961337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118762829","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":[0.1016191,0.00005052476,0.89663166,0.000011822736,0.00081828947,0.00017753735,0.0000031540835,0.00039610622,0.00029180077],"genre_scores_gemma":[0.85396075,0.000021248969,0.1456318,0.000013060651,0.00024127834,0.000027318494,0.000023350758,0.000038811995,0.000042389038],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923676,0.0000070641445,0.0002380648,0.00015959768,0.000095733994,0.0002627744],"domain_scores_gemma":[0.9997038,0.00001699934,0.000027610866,0.00013619041,0.000046006884,0.0000693578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008418433,0.00012666904,0.00010778746,0.00010698848,0.00007337034,0.000020074096,0.000068814654,0.00014233605,0.00007667077],"category_scores_gemma":[0.000020388075,0.0001353161,0.000028589317,0.00031752605,0.000030786363,0.0002946225,0.000022010556,0.00040711943,0.000003222307],"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":[0.0000018487208,0.000016995218,0.0019524784,0.0000055106,0.0000071442164,0.0000016478207,0.000034968492,0.9963195,0.0010196978,0.00024814004,0.000015069363,0.0003770007],"study_design_scores_gemma":[0.00026821857,0.000003078803,0.0017123355,0.00001927058,0.0000038053242,0.0000068678482,0.000031858435,0.9975111,0.00018129643,0.000050474908,0.00006554774,0.00014614833],"about_ca_topic_score_codex":0.000008333141,"about_ca_topic_score_gemma":0.00017619717,"teacher_disagreement_score":0.7523416,"about_ca_system_score_codex":0.0000540031,"about_ca_system_score_gemma":0.00001779728,"threshold_uncertainty_score":0.5518031},"labels":[],"label_agreement":null},{"id":"W2118934664","doi":"10.1109/tcst.2011.2181975","title":"Rate Assignment in Wireless Networks: Stability Analysis and Controller Design","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Control Systems Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; McGill University","funders":"","keywords":"Computer science; Telecommunications link; Controller (irrigation); Stability (learning theory); Control theory (sociology); Interference (communication); Wireless network; Control engineering; Wireless; Control (management); Engineering; Computer network; Channel (broadcasting)","score_opus":0.009298883580854424,"score_gpt":0.20188366557616316,"score_spread":0.19258478199530873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118934664","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":[0.022559324,0.0010118305,0.97424394,0.000049969236,0.0005274829,0.00096752605,0.000012596897,0.00060431665,0.000023015225],"genre_scores_gemma":[0.998275,0.00024586346,0.0006323621,0.000016354064,0.000042631178,0.0007318165,0.0000015625075,0.000041866617,0.000012581651],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99831045,0.00022679941,0.00050993543,0.00028533494,0.000114157825,0.0005533408],"domain_scores_gemma":[0.9990916,0.00036065804,0.0000825644,0.00032110384,0.00004671365,0.00009735832],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006044738,0.0002708265,0.00066884287,0.0006954663,0.00008909911,0.000025138994,0.000115690105,0.0003716536,0.000011111791],"category_scores_gemma":[0.0000061285173,0.00027270717,0.00007636822,0.0010917822,0.00008751394,0.00020698334,0.0000010081071,0.00039335073,0.000005806534],"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":[0.000075371645,0.00007444921,0.0014802801,0.000016264674,0.00044490135,0.0000016236118,0.000034853554,0.99005014,0.0022897488,0.000111868525,0.000005203378,0.005415278],"study_design_scores_gemma":[0.0017356125,0.00005155241,0.0003311811,0.000024777562,0.00024515516,0.0000044262783,0.00008102355,0.9953503,0.0018913657,0.000021072588,0.00002458715,0.00023895048],"about_ca_topic_score_codex":0.000019497547,"about_ca_topic_score_gemma":0.00008319734,"teacher_disagreement_score":0.97571564,"about_ca_system_score_codex":0.00028739666,"about_ca_system_score_gemma":0.000008347881,"threshold_uncertainty_score":0.9999725},"labels":[],"label_agreement":null},{"id":"W2119039041","doi":"10.1109/tcomm.2009.07.070157","title":"Resource allocation in an OFDM-based cognitive radio system","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":175,"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","funders":"","keywords":"Cognitive radio; Subcarrier; Knapsack problem; Orthogonal frequency-division multiplexing; Resource allocation; Greedy algorithm; Computer science; Frequency allocation; Mathematical optimization; Resource management (computing); Simple (philosophy); Electronic engineering; Algorithm; Telecommunications; Computer network; Mathematics; Engineering; Wireless","score_opus":0.019338298893964344,"score_gpt":0.2548390433945764,"score_spread":0.23550074450061206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119039041","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":[0.006824803,0.00016191298,0.9888587,0.00032717138,0.00008312259,0.00040515466,0.000025193234,0.0007822999,0.0025316277],"genre_scores_gemma":[0.9888472,0.000119035,0.010619006,0.00008709291,0.00001753048,0.00014847307,0.00009981686,0.000036958063,0.00002486521],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990404,0.00015227804,0.00031262313,0.00017247349,0.00012684979,0.00019537797],"domain_scores_gemma":[0.9986104,0.00020682988,0.00004408649,0.0009851253,0.0000770286,0.00007653256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012219985,0.0001622986,0.00015752921,0.00027639908,0.00022275721,0.000032337797,0.00037619716,0.000106321415,0.000008778045],"category_scores_gemma":[0.0000034547472,0.00020234467,0.000047017922,0.0006511869,0.000054465978,0.00028908162,7.307393e-7,0.0003723071,0.000024453526],"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":[0.000020328658,0.00017615229,0.0000063229236,0.000010200003,0.000008402037,6.116858e-7,0.00023321263,0.9735663,0.0004589221,0.00034708268,0.000017317107,0.02515515],"study_design_scores_gemma":[0.0005892654,0.00007597193,0.0003787722,0.0001930922,0.000026155996,0.0000027704339,0.00035359847,0.9947898,0.0031200023,0.00003023505,0.00023179816,0.00020857785],"about_ca_topic_score_codex":0.00000763944,"about_ca_topic_score_gemma":0.00019068364,"teacher_disagreement_score":0.9820224,"about_ca_system_score_codex":0.00029365864,"about_ca_system_score_gemma":0.000026529555,"threshold_uncertainty_score":0.8251377},"labels":[],"label_agreement":null},{"id":"W2119309906","doi":"10.1109/.2005.1467101","title":"Optimal Downlink Data Transmission Scheduling in Next Generation Wireless Systems.","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Polytechnique Montréal","funders":"","keywords":"Computer science; Scheduling (production processes); Wireless; Base station; Telecommunications link; Power control; Optimal control; Mathematical optimization; Quadratic equation; Skew; Quadratic programming; Job shop scheduling; Scalability; Distributed computing; Computer network; Power (physics); Mathematics; Telecommunications","score_opus":0.04542798698368662,"score_gpt":0.25401644211702423,"score_spread":0.20858845513333762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119309906","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":[0.124723084,0.0012222349,0.8727484,0.00007363418,0.00015674668,0.00020133596,0.0000044488206,0.0003422189,0.0005279423],"genre_scores_gemma":[0.7829602,0.00065664214,0.215489,0.00001881051,0.0004499644,0.000013464266,0.00031552653,0.00003870003,0.000057736837],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895984,0.000024583676,0.0003506761,0.00027226898,0.00014369765,0.0002489607],"domain_scores_gemma":[0.9994806,0.00002298148,0.000026506119,0.0003794717,0.000024837806,0.00006561852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015614368,0.00015696837,0.00016698548,0.00010040972,0.00004513583,0.000072098686,0.00023494501,0.00011873134,0.000047123835],"category_scores_gemma":[0.0000038811563,0.00015954378,0.000015252956,0.00024786853,0.00001022274,0.0011177748,0.000034009245,0.00017109122,0.000029049752],"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":[0.000003551733,0.000012888189,0.000024773819,0.00002684808,0.0000052982696,0.0000016254552,0.00005600676,0.92713594,0.009826877,0.0001965047,0.00020983115,0.06249986],"study_design_scores_gemma":[0.0003236349,0.0000053302606,0.000013287972,0.00006009692,0.0000051421994,0.0000039869865,0.00004436569,0.9940554,0.0021977571,0.0000014437609,0.0030959584,0.00019359477],"about_ca_topic_score_codex":0.000009957499,"about_ca_topic_score_gemma":0.000030825555,"teacher_disagreement_score":0.6582371,"about_ca_system_score_codex":0.00010796655,"about_ca_system_score_gemma":0.0000145876475,"threshold_uncertainty_score":0.6506007},"labels":[],"label_agreement":null},{"id":"W2120019718","doi":"10.1109/icc.2007.849","title":"Adaptive Power Loading for OFDM-Based Cognitive Radio Systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Subcarrier; Orthogonal frequency-division multiplexing; Cognitive radio; Telecommunications link; Computer science; Interference (communication); Transmitter power output; Electronic engineering; Transmission (telecommunications); Air interface; Power (physics); Computer network; Telecommunications; Engineering; Transmitter; Wireless; Base station","score_opus":0.011337129281824789,"score_gpt":0.22869060369666744,"score_spread":0.21735347441484265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120019718","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":[0.0035917985,0.00032935519,0.98421234,0.000003996969,0.00046559988,0.0005428229,0.000012173261,0.0004827932,0.010359131],"genre_scores_gemma":[0.9742976,0.0000054190527,0.025190169,0.00003246806,0.00011615807,0.000045233624,0.000026849124,0.000056590095,0.00022955766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992607,0.000007131777,0.00019447863,0.00014397023,0.0000935754,0.00030012862],"domain_scores_gemma":[0.9993673,0.0003438129,0.000032017655,0.00008200583,0.00010688852,0.000067982204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015376296,0.00013645584,0.00014991597,0.00008845385,0.00004928148,0.000017939272,0.000050915387,0.00007812797,0.000023226383],"category_scores_gemma":[0.000027054431,0.00014043051,0.00004281833,0.00017392763,0.000018751454,0.00012955902,0.000005022467,0.00007263416,0.000014854786],"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":[0.000057100508,0.0000087677845,0.00006218047,0.00002514222,0.00003247231,0.0000029754042,0.000069603826,0.99617445,0.00025279308,0.0015989294,0.0004584047,0.0012571902],"study_design_scores_gemma":[0.00073562795,0.000057443667,0.000076084194,0.00009252581,0.000015001589,0.0000019275467,0.00041718272,0.9925023,0.0052040145,0.000025744033,0.00065750343,0.0002147016],"about_ca_topic_score_codex":0.0000025659526,"about_ca_topic_score_gemma":0.0000055083124,"teacher_disagreement_score":0.97070575,"about_ca_system_score_codex":0.00012018092,"about_ca_system_score_gemma":0.000009310198,"threshold_uncertainty_score":0.57265896},"labels":[],"label_agreement":null},{"id":"W2120198850","doi":"10.1109/icassp.2007.366756","title":"On Optimality of Monotone Channel-Aware Transmission Policies: A Constrained Markov Decision Process Approach","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Markov decision process; Computer science; Lagrange multiplier; Markov process; Fading; Mathematical optimization; Network packet; Transmission (telecommunications); Channel (broadcasting); Channel state information; Constraint (computer-aided design); Buffer overflow; Transmission delay; Wireless; Computer network; Mathematics; Telecommunications; Statistics","score_opus":0.008190102650428192,"score_gpt":0.25422380952230145,"score_spread":0.24603370687187326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120198850","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":[0.035615925,0.000059944865,0.9550382,0.000010267864,0.00008682038,0.00037486892,0.000007754023,0.0003233028,0.008482926],"genre_scores_gemma":[0.8874161,0.000055258977,0.11233725,0.00002350582,0.000051043422,0.000014021603,0.000029282151,0.000040593168,0.000032931435],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877286,0.000011701264,0.00040653025,0.00022816703,0.00026604187,0.00031469885],"domain_scores_gemma":[0.99938065,0.00013961985,0.000056505145,0.00021558318,0.00009052514,0.000117134565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025785159,0.00020686108,0.00026026682,0.00016192367,0.000046429985,0.00000906421,0.0001428559,0.00014546442,0.00006017179],"category_scores_gemma":[0.000018181869,0.00018523633,0.00005964411,0.0003989047,0.00005602527,0.00013665893,0.000011033161,0.00014315052,0.0000026275643],"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":[0.00013852293,0.00007736559,0.00001113584,0.000123218,0.000013409052,0.000001385223,0.00029108784,0.9806012,0.00028415426,0.00028336377,0.00013980661,0.01803536],"study_design_scores_gemma":[0.0006109953,0.000060685994,0.00014048956,0.000101034755,0.000007882219,0.0000046822242,0.00022274553,0.98840487,0.009602121,0.0006058064,0.000030462455,0.00020820348],"about_ca_topic_score_codex":0.0000049805935,"about_ca_topic_score_gemma":0.0000014146327,"teacher_disagreement_score":0.8518002,"about_ca_system_score_codex":0.00006013543,"about_ca_system_score_gemma":0.000014723933,"threshold_uncertainty_score":0.7553718},"labels":[],"label_agreement":null},{"id":"W2120637842","doi":"10.1109/infcom.2007.166","title":"Balancing Interruption Frequency and Buffering Penalties in VBR Video Streaming","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Toronto","funders":"","keywords":"Jitter; Computer science; Variable bitrate; Real-time computing; Channel (broadcasting); Markov process; Computer network; Transmission (telecommunications); Fading; Video server; Telecommunications; Bit rate","score_opus":0.00790891459476322,"score_gpt":0.22998164271217136,"score_spread":0.22207272811740814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120637842","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":[0.5188781,0.0002904898,0.47674584,0.0000053494746,0.000100796184,0.000055834873,2.1782125e-7,0.00018017714,0.0037432096],"genre_scores_gemma":[0.97310674,0.00016929032,0.026590493,0.000012581329,0.00006046711,0.0000037564294,0.000004337784,0.000023030612,0.000029316572],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939424,0.0000055124606,0.00020461061,0.00011625159,0.00006266606,0.00021669296],"domain_scores_gemma":[0.99980205,0.000055365337,0.00001758462,0.0000757265,0.000012579819,0.000036696772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014547701,0.00010171221,0.00010261316,0.00013309668,0.000025129051,0.000019931034,0.000037996397,0.00004988207,0.000020347294],"category_scores_gemma":[0.000017212,0.000109374596,0.000010543402,0.00014932976,0.000012683785,0.0003154519,0.000019361418,0.00011304325,0.0000027147057],"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":[0.0000071857035,0.00000719329,0.043654818,0.00008691957,0.000009120645,0.0000143491,0.0008854176,0.863244,0.020202389,0.0013278521,0.000013233319,0.070547536],"study_design_scores_gemma":[0.00044579126,0.000022163147,0.0681201,0.00026353408,0.000004991811,0.000015119336,0.0009968976,0.9217413,0.0073140333,0.0006649718,0.000060918257,0.00035019446],"about_ca_topic_score_codex":0.000047809554,"about_ca_topic_score_gemma":0.00066980056,"teacher_disagreement_score":0.45422864,"about_ca_system_score_codex":0.0001272958,"about_ca_system_score_gemma":0.0000023534456,"threshold_uncertainty_score":0.44601667},"labels":[],"label_agreement":null},{"id":"W2121100117","doi":"10.1109/iwcmc.2008.141","title":"Performance Analysis for Polling Service in IEEE 802.16 Networks Under PMP Mode","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Polling; Computer network; Computer science; Quality of service; Base station; Service (business); Queueing theory; IEEE 802; Polling system","score_opus":0.016358897595273935,"score_gpt":0.2227967637704357,"score_spread":0.20643786617516177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121100117","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":[0.23750885,0.0001086273,0.761247,0.000022098095,0.00009963841,0.00012826071,0.0000014963202,0.00019443518,0.0006896492],"genre_scores_gemma":[0.9735737,0.0006696581,0.025193455,0.00015007211,0.000117062285,0.00004162286,0.000046679364,0.000041970827,0.00016581609],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916726,0.0000073816886,0.00024332573,0.00017486054,0.00008648647,0.00032067942],"domain_scores_gemma":[0.9996283,0.000057170095,0.000027968345,0.00018823126,0.000051122875,0.00004720766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000054667256,0.0001479807,0.0002207066,0.00018292875,0.00007513751,0.000009363878,0.00010532918,0.000096951546,0.000025277473],"category_scores_gemma":[0.0000019453682,0.00015665921,0.000059837406,0.0013303938,0.000009747138,0.00025392824,0.000010240068,0.00011374049,0.000004806772],"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":[0.000009727242,0.0000074413974,0.004920926,0.00001834177,0.00007072011,4.4701255e-7,0.0000690019,0.99421525,0.00003117189,0.000056214045,0.00007581537,0.00052497245],"study_design_scores_gemma":[0.00028443188,0.000006395222,0.0019599507,0.00001256264,0.000037337468,0.0000012963923,0.000025001405,0.99717385,0.00023361934,0.000025544085,0.000047835583,0.0001921733],"about_ca_topic_score_codex":0.000038507766,"about_ca_topic_score_gemma":0.00065649376,"teacher_disagreement_score":0.7360648,"about_ca_system_score_codex":0.0001377902,"about_ca_system_score_gemma":0.0000083680225,"threshold_uncertainty_score":0.6388377},"labels":[],"label_agreement":null},{"id":"W2121420937","doi":"10.1109/icwmc.2007.39","title":"Efficient Guard Band Based Admission Control in Heterogeneous Wireless Overlay Networks Using Generally Distributed Cell Residence Time","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Polytechnique Montréal","funders":"","keywords":"Computer science; Computer network; Wireless network; Wireless; Handover; Quality of service; Heterogeneous network; Overlay; Bandwidth (computing); Distributed computing; Heterogeneous wireless network; Bandwidth allocation; Guard (computer science); Telecommunications","score_opus":0.004890144914072207,"score_gpt":0.2038464050318931,"score_spread":0.1989562601178209,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121420937","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":[0.36978564,0.00026509486,0.62924343,0.0000073455167,0.00012233594,0.00023765005,0.000007317878,0.00021373574,0.00011744487],"genre_scores_gemma":[0.9892813,0.000019176234,0.010328523,0.00009733336,0.00011362568,0.0000063442235,0.00005005375,0.00006986917,0.0000337628],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99825054,0.000050354436,0.00049830443,0.00032465364,0.0002461935,0.0006299668],"domain_scores_gemma":[0.9992046,0.00017722187,0.000079889214,0.00028762646,0.000065733395,0.00018495736],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003030003,0.00028426538,0.00030203388,0.00013290936,0.00007820796,0.000037555317,0.00015468737,0.0001978493,0.00009645544],"category_scores_gemma":[0.000015500826,0.00028998195,0.000063896136,0.00047906625,0.000027532209,0.00006857096,0.000020169316,0.00021723636,0.000008449962],"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":[0.000095128096,0.000036238733,0.0005258663,0.00001706502,0.0000059140725,0.00006555707,0.000010867563,0.9602557,0.03822345,0.0000026220691,0.00011530037,0.00064629695],"study_design_scores_gemma":[0.001209525,0.000025608566,0.00044240378,0.00009955138,0.00001262129,0.0000059736176,0.0000034614231,0.9789947,0.018838812,0.000002525213,0.000034810793,0.00032996797],"about_ca_topic_score_codex":0.00001547949,"about_ca_topic_score_gemma":0.000027027385,"teacher_disagreement_score":0.6194957,"about_ca_system_score_codex":0.00033613428,"about_ca_system_score_gemma":0.000030201347,"threshold_uncertainty_score":0.99995524},"labels":[],"label_agreement":null},{"id":"W2121719312","doi":"10.1109/t-wc.2008.070378","title":"Two dimensional cross-layer optimization for packet transmission over fading channel","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Fading; Computer science; Network packet; Channel (broadcasting); Link adaptation; Physical layer; Transmission (telecommunications); Optimization problem; Buffer overflow; Wireless; Algorithm; Computer network; Telecommunications","score_opus":0.03364243926365365,"score_gpt":0.28806612302979445,"score_spread":0.2544236837661408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121719312","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":[0.02333261,0.00026208026,0.97391534,0.00015112983,0.00042740136,0.000685581,0.000119661396,0.00076154474,0.00034466368],"genre_scores_gemma":[0.9125561,0.0018265421,0.08444569,0.000083426756,0.00005842748,0.00051601836,0.000189848,0.00013957586,0.0001843808],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984219,0.000072005816,0.0005180094,0.00032491743,0.0002576648,0.00040548807],"domain_scores_gemma":[0.9980649,0.00039581588,0.000089016045,0.0010904191,0.00020093613,0.00015892684],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000121961195,0.0003378291,0.00029835934,0.00026391866,0.0012845461,0.000045110282,0.0005087846,0.00018576048,0.00010274855],"category_scores_gemma":[0.0000041079747,0.00038365836,0.00019330347,0.0005569296,0.00020304523,0.0005776939,0.000004756894,0.0004273291,0.000017040087],"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":[0.000049043887,0.0001748949,0.0000111120735,0.000026283253,0.00005829993,7.786502e-7,0.0003276608,0.99086094,0.001596191,0.00014237454,0.00017477233,0.006577625],"study_design_scores_gemma":[0.0013484044,0.00004267939,0.00004341467,0.00009141908,0.000039849892,0.000016576794,0.000017471411,0.9874525,0.009963353,0.0000895428,0.0004927847,0.00040197003],"about_ca_topic_score_codex":0.000012262527,"about_ca_topic_score_gemma":0.00002269858,"teacher_disagreement_score":0.8894696,"about_ca_system_score_codex":0.00020261487,"about_ca_system_score_gemma":0.00004670572,"threshold_uncertainty_score":0.99986154},"labels":[],"label_agreement":null},{"id":"W2121882162","doi":"10.1109/wcnc.2005.1424632","title":"Adaptive modulation and coding with multicodes over nakagami fading channels","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Fading; Link adaptation; Computer science; Nakagami distribution; Channel state information; Bit error rate; Channel (broadcasting); Electronic engineering; Coding (social sciences); Channel code; Granularity; Spectral efficiency; Transmission (telecommunications); Algorithm; Modulation (music); Telecommunications; Decoding methods; Statistics; Mathematics; Wireless; Engineering; Physics","score_opus":0.009074637149296077,"score_gpt":0.20281162219616142,"score_spread":0.19373698504686535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121882162","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":[0.15472405,0.00008228833,0.8434615,0.0000140734855,0.000038484824,0.00010808144,7.7353644e-7,0.00026751505,0.0013031986],"genre_scores_gemma":[0.9090442,0.000072418494,0.09062767,0.000018711444,0.000104027975,0.000008543476,0.0000043797672,0.000027675678,0.00009238354],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995778,0.00000513544,0.00008929599,0.0001150756,0.0000708958,0.0001417966],"domain_scores_gemma":[0.9998309,0.000031853768,0.000017225748,0.00006282974,0.000020127953,0.000037041864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000026793401,0.00010198468,0.00008648272,0.000050591676,0.000047078163,0.000022826967,0.000023097904,0.000037072285,0.000020580195],"category_scores_gemma":[0.0000033926508,0.000092455186,0.000007866,0.00009580464,0.000015383132,0.0004128204,0.000009883594,0.000056530364,0.000003427586],"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":[0.000006828221,0.0000029255482,0.00024011233,0.0000066779407,0.000011337341,4.8087696e-7,0.0002442692,0.9841144,0.0008969295,0.0006597972,0.000019082448,0.013797151],"study_design_scores_gemma":[0.00029513935,0.000012893635,0.0009980587,0.000035809247,0.000005032999,0.0000024194305,0.00004589758,0.9966537,0.0017015638,0.000037639646,0.00007643004,0.0001354361],"about_ca_topic_score_codex":0.00000247393,"about_ca_topic_score_gemma":0.000015689955,"teacher_disagreement_score":0.75432014,"about_ca_system_score_codex":0.00005525932,"about_ca_system_score_gemma":0.0000017143752,"threshold_uncertainty_score":0.3770213},"labels":[],"label_agreement":null},{"id":"W2121921168","doi":"10.1109/tvt.2007.907029","title":"A Fast Subcarrier, Bit, and Power Allocation Algorithm for Multiuser OFDM-Based Systems","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"PQ Corporation (Canada)","funders":"","keywords":"Subcarrier; Orthogonal frequency-division multiplexing; Bit error rate; Computer science; Transmitter power output; Telecommunications link; Algorithm; Base station; Transmission (telecommunications); Electronic engineering; Power (physics); Channel (broadcasting); Computational complexity theory; Real-time computing; Telecommunications; Engineering; Transmitter","score_opus":0.006905822380963327,"score_gpt":0.19972242067354487,"score_spread":0.19281659829258155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121921168","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":[0.040681176,0.00043674855,0.95657265,0.000088151595,0.00045287737,0.0006148529,0.00003835586,0.0011033089,0.000011887262],"genre_scores_gemma":[0.949072,0.00020301284,0.05003031,0.00002540814,0.000021369216,0.00050420075,0.000014986854,0.00007400298,0.000054701835],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907804,0.000016495875,0.00023985816,0.0002786509,0.00011093134,0.00027600004],"domain_scores_gemma":[0.99944913,0.000047161102,0.000040660667,0.00029860545,0.000110085435,0.000054351265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005300795,0.00021100199,0.00022694422,0.0004093394,0.00019782226,0.000011584775,0.00010185415,0.0003595035,0.0000047267263],"category_scores_gemma":[0.0000036040626,0.0002332082,0.000058428468,0.0004701793,0.00012623124,0.00011284586,7.3748214e-7,0.00024131872,0.0000073699184],"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":[0.000009339785,0.000044232074,0.000009594126,0.000026345719,0.000046930327,0.000006686127,0.000032739776,0.97190356,0.004660152,0.000046491925,0.000035798646,0.023178102],"study_design_scores_gemma":[0.0008839442,0.00011360428,0.000011714383,0.000034812012,0.000027075319,0.00005054203,0.00005368052,0.94812435,0.049173724,0.000021716125,0.0012740826,0.00023073872],"about_ca_topic_score_codex":0.0000051803427,"about_ca_topic_score_gemma":0.000007721145,"teacher_disagreement_score":0.9083908,"about_ca_system_score_codex":0.000097017735,"about_ca_system_score_gemma":0.000019224275,"threshold_uncertainty_score":0.95099545},"labels":[],"label_agreement":null},{"id":"W2121947415","doi":"10.1109/glocom.2008.ecp.823","title":"User Capacity of Rician and Nakagami Fading Broadcast Channels","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Rician fading; Nakagami distribution; Fading; Computer science; Topology (electrical circuits); Mathematics; Algorithm; Discrete mathematics; Statistics; Combinatorics","score_opus":0.014928324032489247,"score_gpt":0.192782808803891,"score_spread":0.17785448477140176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121947415","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":[0.6168938,0.00016541012,0.37933597,0.0000060738494,0.00011538926,0.00006381674,0.0000017199137,0.00015203372,0.003265793],"genre_scores_gemma":[0.98526376,0.00028406957,0.014188737,0.000017801618,0.00004924528,0.000002904566,0.000002180008,0.000019336563,0.00017198503],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996138,0.0000053762146,0.00011566594,0.000079856356,0.000060327395,0.00012494352],"domain_scores_gemma":[0.9998207,0.000020143909,0.00001763337,0.000082859086,0.000022040675,0.00003660231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002249682,0.00007781949,0.00011170633,0.000047591882,0.000036430258,0.0000035106277,0.000035225763,0.000042108055,0.00002237407],"category_scores_gemma":[0.000006610974,0.0000794182,0.000014466678,0.00013193341,0.000035825484,0.00014381699,0.000012932813,0.000054731925,0.0000033833937],"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":[0.0000013788971,0.0000048099396,0.0014923834,0.000020919282,0.00000934082,0.0000017471687,0.00035267178,0.9943338,0.0017491056,0.00029179594,0.00028087426,0.0014611651],"study_design_scores_gemma":[0.000320188,0.000019307741,0.003946273,0.00003610545,0.0000065429554,0.000029535839,0.000059130878,0.97131413,0.022121174,0.0001080982,0.0017998099,0.0002397207],"about_ca_topic_score_codex":0.000009441721,"about_ca_topic_score_gemma":0.0000037279945,"teacher_disagreement_score":0.36836994,"about_ca_system_score_codex":0.000017534885,"about_ca_system_score_gemma":0.0000019688177,"threshold_uncertainty_score":0.32385802},"labels":[],"label_agreement":null},{"id":"W2121972227","doi":"10.1109/ictta.2008.4530221","title":"On the Capacity of MIMO Channels and Its Effect on Network Performance","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Computer science; MIMO; Physical layer; Computer network; Channel (broadcasting); Channel capacity; Queueing theory; Buffer overflow; Transmission (telecommunications); Capacity planning; Coverage probability; Wireless network; Wireless; Telecommunications; Mathematics; Statistics","score_opus":0.01209514171491441,"score_gpt":0.18307472332975436,"score_spread":0.17097958161483995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121972227","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":[0.9879235,0.00010062074,0.006470282,0.000018937284,0.00016938844,0.00017316012,6.6691734e-7,0.00009462657,0.0050488287],"genre_scores_gemma":[0.9991498,0.00032403704,0.00025739963,0.000047585287,0.000093322495,0.000013157462,0.000001208801,0.000016389937,0.00009708162],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995927,0.000018983545,0.000087191744,0.00007928578,0.00008196808,0.00013982508],"domain_scores_gemma":[0.9996335,0.0002005553,0.000017912103,0.000112058275,0.000013303662,0.000022704211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007637831,0.00009636256,0.00010817596,0.000018092382,0.000073624265,0.0000027141882,0.00005100437,0.00003851348,0.000020776668],"category_scores_gemma":[0.000014526342,0.00006389916,0.00001581747,0.00012504516,0.000022829096,0.000055626526,0.0000090418,0.00010137251,0.000011240279],"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":[0.000012962414,0.000003557191,0.00018757774,0.000021344253,0.0000074590016,3.5125777e-7,0.00004764375,0.9969981,0.00011337327,0.001347531,0.0006576768,0.000602471],"study_design_scores_gemma":[0.00015225228,0.00018387976,0.001232386,0.000064588625,0.000002898427,0.0000032244607,0.0000012282399,0.9781006,0.020026876,0.000040191262,0.00010187951,0.00009001835],"about_ca_topic_score_codex":6.0783924e-7,"about_ca_topic_score_gemma":6.2834107e-7,"teacher_disagreement_score":0.019913502,"about_ca_system_score_codex":0.000013756079,"about_ca_system_score_gemma":0.0000016513703,"threshold_uncertainty_score":0.26057324},"labels":[],"label_agreement":null},{"id":"W2121982005","doi":"10.1109/twc.2006.256974","title":"POMDP-Based Coding Rate Adaptation for Type-I Hybrid ARQ Systems over Fading Channels with Memory","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":40,"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","funders":"","keywords":"Partially observable Markov decision process; Fading; Computer science; Heuristics; Markov decision process; Scheduling (production processes); Markov process; Mathematical optimization; Channel state information; Markov chain; Algorithm; Wireless; Markov model; Decoding methods; Mathematics; Statistics; Telecommunications","score_opus":0.029279209008956118,"score_gpt":0.24849729171173332,"score_spread":0.2192180827027772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121982005","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":[0.014310108,0.000254211,0.98252285,0.000105415056,0.000653376,0.00093335944,0.00009547031,0.00074624806,0.00037896616],"genre_scores_gemma":[0.98444366,0.0002820012,0.013912038,0.000032978132,0.00008104974,0.0007139601,0.00021505458,0.00013413657,0.00018514045],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871945,0.00009831211,0.00041568733,0.00025515357,0.00017171477,0.00033968748],"domain_scores_gemma":[0.998072,0.00053021294,0.00012411589,0.0009851396,0.00021820546,0.00007032411],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001684249,0.0002875322,0.00027899563,0.0002715506,0.0005936501,0.000100275465,0.0003798972,0.000096753516,0.000009632341],"category_scores_gemma":[0.0000033021772,0.00031424547,0.00008276265,0.000547536,0.000094951574,0.00035755796,0.0000020830362,0.00030380677,0.000011841758],"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":[0.000052157262,0.00009168577,0.0000032186524,0.00007080315,0.00005027657,7.3796303e-7,0.00007893378,0.99409604,0.0023309686,0.00070918124,0.00015436363,0.0023616338],"study_design_scores_gemma":[0.000919784,0.00006397496,0.000013247956,0.00022721359,0.000072942974,0.0000045930237,0.00010525848,0.98565495,0.011973123,0.000040871157,0.0005680384,0.00035598603],"about_ca_topic_score_codex":0.00008397381,"about_ca_topic_score_gemma":0.00018292667,"teacher_disagreement_score":0.97013354,"about_ca_system_score_codex":0.00026469748,"about_ca_system_score_gemma":0.000053976677,"threshold_uncertainty_score":0.999931},"labels":[],"label_agreement":null},{"id":"W2121982806","doi":"10.1109/cnsr.2011.37","title":"Towards QoS Assurance with Revenue Maximization of LTE Uplink Scheduling","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Quality of service; Computer science; Telecommunications link; Computer network; Scheduling (production processes); Maximization; Network packet; Bandwidth allocation; Bandwidth (computing); Mathematical optimization","score_opus":0.013007256141109048,"score_gpt":0.18830141673510534,"score_spread":0.1752941605939963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121982806","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":[0.01616579,0.00012454441,0.97528625,0.000006842411,0.000126789,0.00010995629,0.0000024707838,0.00017620822,0.008001155],"genre_scores_gemma":[0.59036213,0.00011004165,0.40935284,0.000006771674,0.00003806433,0.000007952845,0.0000063549965,0.000026511858,0.00008932043],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99952894,0.0000067655874,0.00015926432,0.00009933629,0.00008185192,0.00012384431],"domain_scores_gemma":[0.99968815,0.000010213083,0.00004585966,0.00015801693,0.00006915854,0.000028595518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046922196,0.00009306962,0.00012098673,0.00004349897,0.000018684368,0.0000042277165,0.00007156762,0.000049238082,0.00006255338],"category_scores_gemma":[0.000011976789,0.00008593524,0.00001617443,0.00023003142,0.000019913745,0.00018646769,0.000009467617,0.000066903565,0.0000063027887],"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":[0.000012742968,0.000007817463,0.00081123825,0.000045915203,0.000014990941,0.0000010571115,0.00016503676,0.99287033,0.00039848214,0.0006476916,0.000047632806,0.0049770554],"study_design_scores_gemma":[0.00029566447,0.000032369884,0.0017397129,0.00011363921,0.000013461296,0.0000030348597,0.00002319365,0.9757606,0.021472033,0.0002778952,0.000095355535,0.00017307354],"about_ca_topic_score_codex":0.000008810809,"about_ca_topic_score_gemma":0.000014680527,"teacher_disagreement_score":0.57419634,"about_ca_system_score_codex":0.000020633614,"about_ca_system_score_gemma":0.000011680617,"threshold_uncertainty_score":0.3504337},"labels":[],"label_agreement":null},{"id":"W2122482858","doi":"10.1109/tnet.2009.2020820","title":"Resequencing Analysis of Stop-and-Wait ARQ for Parallel Multichannel Communications","year":2009,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Automatic repeat request; Hybrid automatic repeat request; Selective Repeat ARQ; Real-time computing; Channel (broadcasting); Go-Back-N ARQ; Computer network; Algorithm; Telecommunications link","score_opus":0.039136945375168285,"score_gpt":0.28321959936349017,"score_spread":0.24408265398832188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122482858","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":[0.005354727,0.0007478868,0.99268794,0.00016373169,0.00025280184,0.00034569492,0.000024108042,0.0002515932,0.00017151654],"genre_scores_gemma":[0.8797308,0.0016841439,0.11828216,0.000054719243,0.00008019086,0.00006693216,0.0000344794,0.0000335358,0.000033022858],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887127,0.000040038714,0.00042018696,0.00022855283,0.00013340748,0.00030656633],"domain_scores_gemma":[0.9984563,0.00046687748,0.00009308217,0.0008268209,0.00008237313,0.00007457255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017618606,0.0001946176,0.0003608522,0.00039384514,0.00025971892,0.000025092348,0.00032001358,0.000118046504,0.0000058143296],"category_scores_gemma":[0.000011331089,0.00022573747,0.0001686844,0.0010979698,0.00005641376,0.00015683642,0.0000037485438,0.00024172154,8.14679e-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":[0.000024022942,0.000034144043,0.000024346013,0.00001152484,0.0002995789,3.2193486e-7,0.00033299852,0.9438025,0.0005372032,0.00013200917,0.000016771495,0.05478462],"study_design_scores_gemma":[0.0003677083,0.000051905605,0.00020938671,0.00008560336,0.00050609733,0.0000011259988,0.00008116843,0.9969184,0.0004259654,0.00085050595,0.0002930614,0.00020911345],"about_ca_topic_score_codex":0.000008622987,"about_ca_topic_score_gemma":0.00010718647,"teacher_disagreement_score":0.8744058,"about_ca_system_score_codex":0.0000992847,"about_ca_system_score_gemma":0.000010394432,"threshold_uncertainty_score":0.92053074},"labels":[],"label_agreement":null},{"id":"W2122554472","doi":"10.1109/twc.2008.080798","title":"PHY-aware distributed scheduling for ad hoc communications with physical interference model","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":30,"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":"Computer science; Scheduling (production processes); PHY; Computer network; Fading; Wireless ad hoc network; Channel (broadcasting); Throughput; Stochastic geometry; Code rate; Distributed computing; Physical layer; Wireless; Decoding methods; Algorithm; Mathematical optimization; Telecommunications; Mathematics","score_opus":0.028551845521580837,"score_gpt":0.2749219027397032,"score_spread":0.24637005721812236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122554472","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":[0.0050118035,0.0002981746,0.9912507,0.0011063695,0.000066073226,0.00070982357,0.00042683134,0.00094292825,0.00018732416],"genre_scores_gemma":[0.8959931,0.0022094056,0.10067868,0.00007801783,0.00001812543,0.00058006245,0.00033107624,0.00007525869,0.00003622824],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986981,0.00006557082,0.00038528387,0.00029333847,0.00017175626,0.0003859091],"domain_scores_gemma":[0.9960899,0.00038360324,0.00009876467,0.0030262284,0.00026321312,0.0001382946],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007654826,0.00034918103,0.00034716513,0.00016337715,0.0007897066,0.000076586635,0.0014772033,0.00012866159,0.0000034884772],"category_scores_gemma":[0.0000036106305,0.00036880895,0.00014033435,0.000659528,0.00024351019,0.00044480013,0.000009866803,0.000694567,0.000011772114],"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":[0.00004801404,0.00040380462,7.1384255e-7,0.000017660659,0.000059608483,1.3891659e-7,0.00042231978,0.9464306,0.0010943171,0.0009883902,0.000037095884,0.050497312],"study_design_scores_gemma":[0.0006580698,0.00015251346,0.0000074060986,0.00018210366,0.00009001381,0.0000035950948,0.00016460662,0.9947591,0.0026581017,0.0006839876,0.00023457075,0.0004059352],"about_ca_topic_score_codex":0.0000016441887,"about_ca_topic_score_gemma":0.00010541779,"teacher_disagreement_score":0.8909813,"about_ca_system_score_codex":0.00022467061,"about_ca_system_score_gemma":0.00006189652,"threshold_uncertainty_score":0.9998764},"labels":[],"label_agreement":null},{"id":"W2123009797","doi":"10.1109/wts.2005.1524764","title":"Novel pilot-free adaptive modulation for wireless OFDM systems","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Communications Research Centre Canada","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Link adaptation; Electronic engineering; Bit error rate; Wireless; Channel (broadcasting); Digital audio broadcasting; Modulation (music); Computer network; Telecommunications; Fading; Engineering","score_opus":0.014782571219649007,"score_gpt":0.1987410807826715,"score_spread":0.18395850956302248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123009797","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":[0.0055368464,0.00009041,0.98783094,0.000012635545,0.00040757525,0.0005284265,0.000030349804,0.00061688473,0.004945927],"genre_scores_gemma":[0.9346043,0.00000676607,0.06400073,0.0000064196797,0.00034599804,0.00021084324,0.00007805017,0.00006117881,0.0006857228],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928457,0.0000050526337,0.00022749031,0.00015553758,0.00011264406,0.00021472963],"domain_scores_gemma":[0.9995461,0.000061544255,0.000040077965,0.00023851485,0.000085149186,0.000028607574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051292398,0.00014104544,0.00014756955,0.00005877712,0.00005171534,0.000026980011,0.00011268427,0.00006156943,0.000006084668],"category_scores_gemma":[0.000006375523,0.00014742119,0.000029605864,0.00015136275,0.000012891257,0.00022838335,0.00001650374,0.000049777158,0.0000057765255],"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":[0.000014980314,0.000018752282,0.000023910472,0.000029852155,0.000010612588,1.4321131e-7,0.0000063190437,0.9474291,0.004345862,0.045043133,0.0023459275,0.0007313997],"study_design_scores_gemma":[0.00072472275,0.00004002275,0.00034772794,0.000023517367,0.000007688129,0.0000017938748,0.000019153644,0.9965273,0.0007657109,0.0009807637,0.00037620007,0.00018540904],"about_ca_topic_score_codex":0.00006992743,"about_ca_topic_score_gemma":0.00006386856,"teacher_disagreement_score":0.92906743,"about_ca_system_score_codex":0.000107789834,"about_ca_system_score_gemma":0.000005684164,"threshold_uncertainty_score":0.6011662},"labels":[],"label_agreement":null},{"id":"W2123080146","doi":"10.1155/2012/680318","title":"Analytical Evaluation of the Performance of Proportional Fair Scheduling in OFDMA‐Based Wireless Systems","year":2012,"lang":"en","type":"article","venue":"Journal of Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Subcarrier; Orthogonal frequency-division multiplexing; Computer science; Orthogonal frequency-division multiple access; Scheduling (production processes); Maximum throughput scheduling; Proportionally fair; Frequency-division multiple access; Wireless; Fairness measure; Max-min fairness; Computer network; Electronic engineering; Throughput; Round-robin scheduling; Real-time computing; Resource allocation; Dynamic priority scheduling; Mathematical optimization; Engineering; Channel (broadcasting); Telecommunications; Mathematics; Quality of service","score_opus":0.010425264271551596,"score_gpt":0.21269383499308453,"score_spread":0.20226857072153293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123080146","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":[0.74199945,0.0010726771,0.25665346,0.0000062208655,0.00019288693,0.00006549528,2.575339e-7,0.00000654525,0.000003012596],"genre_scores_gemma":[0.9960895,0.00005891085,0.0036564555,0.0000019781671,0.00017927287,0.000003055116,3.9507404e-7,0.000010040269,3.9245532e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990057,0.000025508987,0.0004402364,0.00004317126,0.00033948084,0.00014593448],"domain_scores_gemma":[0.99955255,0.00005998186,0.00013231936,0.000053427102,0.00015794236,0.000043761338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004353305,0.00008136531,0.00020852317,0.000141886,0.0000106559155,0.000005617435,0.000077417244,0.00004735599,0.0000012423623],"category_scores_gemma":[0.000016400812,0.000060753897,0.00004406844,0.00038249238,0.0000117018135,0.00016584624,0.00001233582,0.00019612949,4.583289e-8],"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":[0.000007759296,0.000029565981,0.02185246,0.00009558707,0.000021610165,1.7744057e-7,0.000020913003,0.97216487,0.0009596063,0.00022492914,0.0000023468262,0.0046201716],"study_design_scores_gemma":[0.00031894198,0.000040242176,0.034734055,0.0002382911,0.000029851704,0.000012969413,0.000001587176,0.96238416,0.0021738824,0.000002436074,0.0000046289356,0.0000589507],"about_ca_topic_score_codex":4.9145655e-7,"about_ca_topic_score_gemma":6.45131e-8,"teacher_disagreement_score":0.25409007,"about_ca_system_score_codex":0.000079854944,"about_ca_system_score_gemma":0.000031662275,"threshold_uncertainty_score":0.2477472},"labels":[],"label_agreement":null},{"id":"W2123298077","doi":"10.1109/ccece.2003.1226207","title":"A channel-based mobile-assisted fairly-shared packet scheduling scheme for nonreal-time applications in CDMA networks","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Computer network; Computer science; Network packet; Scheduling (production processes); Base station; Code division multiple access; Throughput; Cellular network; Channel (broadcasting); Maximum throughput scheduling; Real-time computing; Round-robin scheduling; Wireless; Fair-share scheduling; Quality of service; Telecommunications; Engineering","score_opus":0.009058014352637552,"score_gpt":0.23130712188602084,"score_spread":0.22224910753338328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123298077","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":[0.007587946,0.00021893068,0.9892116,0.00005396416,0.00007408399,0.0016699585,0.000024675459,0.00083785533,0.0003209604],"genre_scores_gemma":[0.74805945,0.00003905137,0.24818344,0.000050738283,0.0001407119,0.0026341681,0.0007378151,0.00010905122,0.000045585843],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99865144,0.000012075559,0.0003930938,0.00033746948,0.00011236022,0.0004935572],"domain_scores_gemma":[0.99926156,0.0001289304,0.00006269774,0.00034067032,0.0000913552,0.00011480627],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010782006,0.0002723463,0.0002910761,0.0001656576,0.00009767891,0.000047462243,0.00017837975,0.0001995624,0.000042894957],"category_scores_gemma":[0.000016055414,0.00030071486,0.00008854965,0.00075621996,0.00002958356,0.00022839473,0.000021529955,0.00018086142,0.000022161505],"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":[0.000015539192,0.00007607687,0.000046251083,0.000048082813,0.000016605727,9.1501477e-7,0.000032766628,0.9978553,0.0007328719,0.00023075198,0.00006891865,0.00087588653],"study_design_scores_gemma":[0.0015300907,0.000038969036,0.00013729528,0.00009822889,0.000010887795,0.0000010720858,0.00004503278,0.9960795,0.001168337,0.00020576149,0.0003440007,0.00034084168],"about_ca_topic_score_codex":0.000007198037,"about_ca_topic_score_gemma":0.000050050614,"teacher_disagreement_score":0.7410282,"about_ca_system_score_codex":0.00026635747,"about_ca_system_score_gemma":0.000038237344,"threshold_uncertainty_score":0.9999445},"labels":[],"label_agreement":null},{"id":"W2123301306","doi":"10.1109/iswcs.2008.4726079","title":"Using efficient backlog estimation to achieve near-optimal throughput for integrated multimedia wireless cellular access","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Aloha; Computer network; Throughput; Time division multiple access; Network packet; Wireless; Protocol stack; Cellular network; Wireless network; Encoder; Access control; Telecommunications; Wireless sensor network","score_opus":0.03272644634565082,"score_gpt":0.2810515989687299,"score_spread":0.24832515262307908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123301306","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":[0.34827557,0.000030912834,0.6501365,0.00001933939,0.0003302688,0.0006188512,0.000011592078,0.0004312658,0.00014574215],"genre_scores_gemma":[0.5307522,0.000011095966,0.46887395,0.00003366673,0.00007183637,0.00005086006,0.00010039315,0.00006636886,0.00003964343],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863243,0.000020946723,0.0003706738,0.0003311356,0.0001963428,0.00044848426],"domain_scores_gemma":[0.999274,0.00010845742,0.00005698529,0.00026184085,0.00015800174,0.0001406754],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009116062,0.0002894708,0.00028568372,0.00010806033,0.0002354379,0.00007700112,0.00023771026,0.00014207672,0.000048479527],"category_scores_gemma":[0.000040967323,0.00028908678,0.00006999515,0.0005889027,0.00006074826,0.00034566093,0.00006421882,0.000150057,0.000032319753],"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":[0.00004830476,0.00003266528,0.000044063338,0.000030643092,0.0000204791,0.0000039085103,0.00039518153,0.98730236,0.0050770165,0.000056174016,0.00035332958,0.00663585],"study_design_scores_gemma":[0.00050553074,0.000044552948,0.00005113987,0.000042926604,0.000016904762,0.000007068211,0.000034972985,0.9758152,0.022935824,0.000012733331,0.00019537687,0.00033780214],"about_ca_topic_score_codex":0.000026082682,"about_ca_topic_score_gemma":0.000007729593,"teacher_disagreement_score":0.18247664,"about_ca_system_score_codex":0.0002339473,"about_ca_system_score_gemma":0.000045726032,"threshold_uncertainty_score":0.99995613},"labels":[],"label_agreement":null},{"id":"W2123783703","doi":"10.1109/icc.2008.837","title":"New Channel Model for Wireless Communications: Finite-State Phase-Type Semi-Markov Channel Model","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Manitoba","funders":"","keywords":"Fading; Computer science; Channel (broadcasting); Markov model; Wireless; Flexibility (engineering); Markov chain; Finite state; Channel state information; Markov process; Algorithm; Mathematical optimization; Mathematics; Computer network; Telecommunications; Statistics; Machine learning","score_opus":0.047366695285431894,"score_gpt":0.2739163236876402,"score_spread":0.2265496284022083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123783703","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":[0.0014331102,0.0006941915,0.99443287,0.00015871493,0.00016754336,0.00064070383,0.000062060826,0.00090815633,0.0015026259],"genre_scores_gemma":[0.73534393,0.00633109,0.2514046,0.00020820896,0.000101665435,0.00017208695,0.00040153772,0.00017809133,0.0058587976],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985722,0.000015808573,0.00043794207,0.00029910597,0.0001729139,0.0005020825],"domain_scores_gemma":[0.9984565,0.00018254622,0.0000790559,0.00090478186,0.00018721969,0.00018989653],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009100575,0.000330031,0.00033647288,0.0001411466,0.0002633789,0.00002395419,0.00053485896,0.00014867568,0.0000114640625],"category_scores_gemma":[0.000033148342,0.00036617726,0.000091186856,0.00040044147,0.00005642326,0.00047001385,0.0001050384,0.00022451286,0.000018336204],"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":[0.00005028865,0.000057367306,7.352135e-7,0.00003389812,0.00003598556,0.0000011203678,0.0008163305,0.98636764,0.0002004215,0.0004112483,0.008603885,0.003421057],"study_design_scores_gemma":[0.0014126522,0.000036272497,2.6752804e-7,0.00003793879,0.00001809677,0.0000053157537,0.00002959845,0.99385333,0.00064765656,0.0032961264,0.00023405628,0.00042867722],"about_ca_topic_score_codex":0.000010215374,"about_ca_topic_score_gemma":0.000037158366,"teacher_disagreement_score":0.7430283,"about_ca_system_score_codex":0.00011270226,"about_ca_system_score_gemma":0.00009187529,"threshold_uncertainty_score":0.999879},"labels":[],"label_agreement":null},{"id":"W2124158303","doi":"10.1109/twc.2010.061810.091283","title":"Congestion-Based Pricing Resource Management in Broadband Wireless Networks","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University","funders":"","keywords":"Computer science; Computer network; Quality of service; Network congestion; Network traffic control; Wireless broadband; Wireless network; Fairness measure; Provisioning; Bandwidth allocation; Wireless; Network packet; Telecommunications; Throughput","score_opus":0.010993917982084881,"score_gpt":0.23407756575536545,"score_spread":0.22308364777328057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124158303","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":[0.05036456,0.00010865168,0.9440916,0.00024150532,0.00047931948,0.00062635617,0.000015140399,0.0007440873,0.003328737],"genre_scores_gemma":[0.9835369,0.00083913596,0.014746459,0.000106150575,0.0000366128,0.0004640646,0.000054832646,0.00010928309,0.00010654736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983963,0.00010845123,0.00052383234,0.00031794,0.00021935816,0.00043415138],"domain_scores_gemma":[0.9974266,0.00043540387,0.00008220123,0.0018598282,0.000067653586,0.00012827825],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002123047,0.0003176079,0.0002827551,0.00043259302,0.00040735118,0.00006820094,0.0008147266,0.00023488996,0.000040412793],"category_scores_gemma":[0.0000023641066,0.00038616496,0.000092196446,0.0010682136,0.00019826429,0.00022330908,0.0000074059944,0.0013258436,0.000022395408],"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":[0.000019415776,0.00018166371,0.00007397707,0.000025485677,0.000037882255,0.0000026722257,0.00009567444,0.9154293,0.00059429655,0.00087739155,0.000049429324,0.08261279],"study_design_scores_gemma":[0.00084159145,0.000018027433,0.00054698525,0.0001468971,0.000038840528,0.0000037048683,0.000085240106,0.99475783,0.0015457262,0.000040008188,0.0015889044,0.00038627224],"about_ca_topic_score_codex":0.000020754285,"about_ca_topic_score_gemma":0.00089684734,"teacher_disagreement_score":0.93317235,"about_ca_system_score_codex":0.00017393258,"about_ca_system_score_gemma":0.000023666986,"threshold_uncertainty_score":0.99985904},"labels":[],"label_agreement":null},{"id":"W2124464026","doi":"10.1109/iswcs.2008.4726121","title":"Power-Congestion-Distortion optimized scheduling in Wireless Video Sensor Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Scheduling (production processes); Latency (audio); Wireless sensor network; Computer network; Real-time computing; Energy consumption; Power consumption; Wireless; Power (physics); Mathematical optimization; Engineering; Telecommunications","score_opus":0.007787778762063948,"score_gpt":0.20178423566176837,"score_spread":0.19399645689970443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124464026","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":[0.3054873,0.00022184318,0.69096494,0.000023836425,0.00036254426,0.00017929389,7.156831e-7,0.0005897233,0.0021698137],"genre_scores_gemma":[0.9233952,0.00074484106,0.075430036,0.000038534934,0.00010998861,0.000036729696,0.000032152984,0.00006630329,0.00014622675],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987965,0.000033342058,0.00039704982,0.0002514437,0.0001495151,0.00037212425],"domain_scores_gemma":[0.9994923,0.00008508798,0.00004960568,0.00022884979,0.000055181757,0.00008899739],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010319018,0.0002191453,0.00026647793,0.00014876616,0.00008757928,0.000015846746,0.00009978081,0.00017474288,0.0001133859],"category_scores_gemma":[0.000026749542,0.00024546313,0.000052766754,0.00046860796,0.00004445816,0.00033774538,0.000020380468,0.000280387,0.000026545255],"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":[0.0000251092,0.000017110564,0.0015817367,0.0000074420964,0.000010481133,0.00002201696,0.00008085068,0.99673086,0.00023474843,0.00014789026,0.00012457719,0.0010171446],"study_design_scores_gemma":[0.000773571,0.000011524822,0.0026097635,0.000046306912,0.0000040730024,0.00002243104,0.000033912518,0.9957441,0.00037366778,0.000017157332,0.00007625768,0.00028723772],"about_ca_topic_score_codex":0.000009571946,"about_ca_topic_score_gemma":0.000016235981,"teacher_disagreement_score":0.6179079,"about_ca_system_score_codex":0.00020958507,"about_ca_system_score_gemma":0.000014373602,"threshold_uncertainty_score":0.99999976},"labels":[],"label_agreement":null},{"id":"W2124623546","doi":"10.1109/icc.2011.5963050","title":"Adaptive Localized Resource Allocation with Access Point Coordination in Cellular Networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Telecommunications link; Resource allocation; Computer network; Channel allocation schemes; Spectral efficiency; Resource management (computing); Transmission (telecommunications); Cellular network; Channel (broadcasting); Enhanced Data Rates for GSM Evolution; Scheme (mathematics); Orthogonal frequency-division multiplexing; Distributed computing; Wireless; Telecommunications; Mathematics","score_opus":0.015315513512797316,"score_gpt":0.19975796897587852,"score_spread":0.18444245546308122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124623546","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":[0.007362099,0.00010075825,0.9790601,0.00002414537,0.000049975017,0.00029898356,3.1583193e-7,0.00032180824,0.012781804],"genre_scores_gemma":[0.97922385,0.000022684546,0.020414297,0.00003903766,0.0000380332,0.000053235042,0.000035750556,0.000046421832,0.0001267178],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926347,0.000033177977,0.00020514178,0.00017892783,0.000105548505,0.00021376803],"domain_scores_gemma":[0.999654,0.000027966693,0.000043928747,0.00017437596,0.00005344768,0.000046270263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000104763865,0.00014489576,0.00013802259,0.00011180993,0.000027998925,0.000020222375,0.00013351877,0.000087536435,0.00008048877],"category_scores_gemma":[0.000005416457,0.00013541649,0.000015125045,0.00049722387,0.000027356285,0.00047995072,0.000025260957,0.00013778562,0.000005567981],"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":[0.00007040407,0.000018959568,0.0005519782,0.00000656982,0.000011019872,0.0000044345397,0.00020305056,0.9937628,0.000044574677,0.001414128,0.00025113154,0.0036609294],"study_design_scores_gemma":[0.00054188224,0.00003868618,0.00078079675,0.00004342569,0.000007475362,0.0000012755837,0.00012368655,0.99555355,0.0023216961,0.00021136459,0.00018680697,0.00018934306],"about_ca_topic_score_codex":0.000045322224,"about_ca_topic_score_gemma":0.00015370225,"teacher_disagreement_score":0.9718617,"about_ca_system_score_codex":0.00011721412,"about_ca_system_score_gemma":0.0000070851793,"threshold_uncertainty_score":0.5522124},"labels":[],"label_agreement":null},{"id":"W2124630138","doi":"10.1109/ccece.2001.933770","title":"Performance analysis of wireless ATM/AAL2 over a burst error channel","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Communications Research Centre Canada; University of Ottawa","funders":"","keywords":"Asynchronous Transfer Mode; ATM adaptation layer; Computer science; Computer network; Channel (broadcasting); Wireless broadband; Broadband networks; Wireless network; Wireless; Asynchronous communication; Frame (networking); Broadband; Telecommunications","score_opus":0.012671264154811578,"score_gpt":0.20539273769261815,"score_spread":0.19272147353780658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124630138","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":[0.89961284,0.0001385137,0.08403293,0.000010913638,0.00011569634,0.00009432097,0.0000073608903,0.00029697063,0.015690438],"genre_scores_gemma":[0.9968596,0.0007538099,0.0016011564,0.00001380377,0.000039680574,0.000012051955,0.000017866745,0.000030292378,0.0006717031],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992716,0.0000065882255,0.00022886653,0.00013846853,0.00014382311,0.00021068142],"domain_scores_gemma":[0.9996071,0.000023579674,0.000043630065,0.00023902227,0.00003927817,0.000047418544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000034368226,0.00013437113,0.0002643977,0.00020993702,0.000030776348,0.0000070639294,0.00010543919,0.00006580033,0.0006587718],"category_scores_gemma":[0.0000025438749,0.0001332166,0.000084040905,0.0012246954,0.000025129784,0.00020260943,0.000017924229,0.00006997972,0.000020623707],"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":[0.000002403141,0.000017375318,0.004082625,0.000026641756,0.0002294325,6.27942e-7,0.00015693088,0.9921413,0.00020647589,0.00008508089,0.00024622798,0.0028048805],"study_design_scores_gemma":[0.00015190808,0.000012986833,0.009271925,0.000013116048,0.0001440432,3.4394955e-7,0.000023890798,0.9896099,0.0005381888,0.0000025730637,0.0000783505,0.00015279202],"about_ca_topic_score_codex":0.000009380723,"about_ca_topic_score_gemma":0.000028736471,"teacher_disagreement_score":0.09724678,"about_ca_system_score_codex":0.00004649598,"about_ca_system_score_gemma":0.0000014497749,"threshold_uncertainty_score":0.7213089},"labels":[],"label_agreement":null},{"id":"W2124715093","doi":"10.1109/tsp.2009.2027735","title":"Monotonicity of Constrained Optimal Transmission Policies in Correlated Fading Channels With ARQ","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":66,"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","funders":"","keywords":"Markov decision process; Monotonic function; Monotone polygon; Mathematical optimization; Fading; Scheduling (production processes); Dynamic programming; Channel state information; Computer science; Channel (broadcasting); Mathematics; Markov process; Wireless; Computer network; Statistics; Telecommunications","score_opus":0.00890911092742783,"score_gpt":0.22456428881564205,"score_spread":0.21565517788821423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124715093","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":[0.18169644,0.00009236515,0.81748873,0.00003452302,0.000034895493,0.00018775377,0.0000034423313,0.00021196023,0.00024986832],"genre_scores_gemma":[0.98688644,0.00005753773,0.012954718,0.000021016327,0.000015636148,0.000012523005,0.0000029625455,0.000033725348,0.000015423326],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989676,0.00002040363,0.0003474073,0.00019377138,0.00017843043,0.00029240854],"domain_scores_gemma":[0.99968046,0.000042495773,0.00006709798,0.00008207925,0.000058303056,0.000069569614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000072727365,0.00021713974,0.00027051268,0.0002804262,0.000103051316,0.000025734176,0.00008692844,0.00012261982,0.00002139597],"category_scores_gemma":[6.453487e-7,0.00020979723,0.000044903543,0.00070447405,0.00006712544,0.00037212975,2.1899082e-7,0.00034052494,9.832938e-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":[0.00011536467,0.000067412744,0.000004960638,0.000046590216,0.000010566594,0.00000458182,0.0009037179,0.8830137,0.02543915,0.0000051885586,8.74813e-7,0.09038789],"study_design_scores_gemma":[0.000714832,0.00015617412,0.000044410055,0.00053043175,0.00001958609,0.000012841062,0.00011830134,0.85947144,0.13869566,0.000029456154,0.000005185587,0.00020166521],"about_ca_topic_score_codex":0.0000044646904,"about_ca_topic_score_gemma":0.0000028217594,"teacher_disagreement_score":0.80519,"about_ca_system_score_codex":0.00008950223,"about_ca_system_score_gemma":0.000042310163,"threshold_uncertainty_score":0.8555283},"labels":[],"label_agreement":null},{"id":"W2124977877","doi":"10.1109/wpmc.2002.1088350","title":"Scheduling of multimedia traffic in interference-limited broadband wireless access networks","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Computer network; Wireless broadband; Broadband networks; Quality of service; Base station; Network packet; Scheduling (production processes); Broadband; Packet loss; Wireless network; Wireless; Transmission delay; Real-time computing; Telecommunications; Engineering","score_opus":0.014187689458209692,"score_gpt":0.23942612083127926,"score_spread":0.22523843137306956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124977877","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":[0.48314336,0.00027295738,0.5143103,0.0000023027362,0.00022483976,0.0001394613,6.2789877e-7,0.00015851954,0.0017476107],"genre_scores_gemma":[0.98168045,0.00041094597,0.017758135,0.00001145738,0.000031484193,0.000018144441,0.000013394026,0.000042706128,0.000033288503],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990063,0.000036320296,0.00039296906,0.00018436556,0.000079585385,0.0003004746],"domain_scores_gemma":[0.99954176,0.00011384089,0.000051694973,0.00018447428,0.000046579,0.000061664694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010355895,0.00017765873,0.0002655694,0.00017085059,0.000014270835,0.000025556143,0.0001850785,0.00013429798,0.000077327844],"category_scores_gemma":[0.000033514545,0.00018414072,0.00003542764,0.00067476643,0.00003716747,0.0003119895,0.000021812057,0.00022658474,0.0000027180592],"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":[0.000009404274,0.000025536761,0.0023673435,0.000027679318,0.000012543635,0.0000019195918,0.000107718544,0.97773015,0.00022599433,0.0001563956,0.000025275718,0.019310039],"study_design_scores_gemma":[0.0005736295,0.000011402505,0.00054757204,0.00011075875,0.0000052600794,0.0000015085161,0.00006400521,0.99594474,0.0025056903,0.000023892128,0.000019327583,0.00019219126],"about_ca_topic_score_codex":0.0000042536085,"about_ca_topic_score_gemma":0.00009055165,"teacher_disagreement_score":0.4985371,"about_ca_system_score_codex":0.000055409942,"about_ca_system_score_gemma":0.00001218119,"threshold_uncertainty_score":0.7509041},"labels":[],"label_agreement":null},{"id":"W2124982716","doi":"10.1007/s11590-008-0076-7","title":"Comments on “Dual methods for nonconvex spectrum optimization of multicarrier systems”","year":2008,"lang":"en","type":"article","venue":"Optimization Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Mitacs","keywords":"Convexity; Property (philosophy); Dual (grammatical number); Duality (order theory); Scope (computer science); Mathematics; Computational intelligence; Spectrum (functional analysis); Mathematical optimization; Mathematical economics; Optimization problem; Applied mathematics; Computer science; Pure mathematics; Economics; Artificial intelligence; Physics","score_opus":0.016784445877630002,"score_gpt":0.27271200015331154,"score_spread":0.25592755427568153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124982716","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":[0.00077458634,0.00008541365,0.996471,0.00028253888,0.00084911415,0.0008418464,0.00003015452,0.00028592814,0.0003794062],"genre_scores_gemma":[0.063832745,0.0002697341,0.9346568,0.00039696632,0.00018277596,0.0001540264,0.00032081213,0.00012979977,0.000056340625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859536,0.00009632308,0.0005347735,0.00027046673,0.0001917544,0.00031131314],"domain_scores_gemma":[0.9990571,0.00024582678,0.0001779533,0.0003269759,0.0001060558,0.00008605275],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017380022,0.0002595534,0.00035714873,0.00021705397,0.00014010604,0.000023289396,0.00013834915,0.00012576685,0.0000489623],"category_scores_gemma":[0.000070913506,0.0002904178,0.00008553027,0.00037473298,0.000075872835,0.0002885056,0.000019085552,0.00011776836,0.0000032897697],"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":[0.000038638245,0.000031479438,0.000070827555,0.00006855976,0.000057255624,0.0000013559091,0.00014791517,0.9968805,0.0004975481,0.00014090985,0.0017596168,0.000305395],"study_design_scores_gemma":[0.0010088366,0.000049414113,0.000016110793,0.000056968947,0.000029385006,0.00000675389,0.000022016335,0.99550444,0.0024370647,0.0000029733458,0.00059680553,0.00026920592],"about_ca_topic_score_codex":0.00000290252,"about_ca_topic_score_gemma":1.756173e-7,"teacher_disagreement_score":0.06305816,"about_ca_system_score_codex":0.00015653939,"about_ca_system_score_gemma":0.0000147475175,"threshold_uncertainty_score":0.9999548},"labels":[],"label_agreement":null},{"id":"W2125138326","doi":"10.1109/vetecf.2008.262","title":"A Distributed Algorithm for Resource Allocation in OFDM Cognitive Radio Systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Orthogonal frequency-division multiplexing; Cognitive radio; Resource allocation; Resource management (computing); Throughput; Resource (disambiguation); Optimization problem; Distributed computing; Mathematical optimization; Algorithm; Computer network; Wireless; Telecommunications; Mathematics","score_opus":0.010784364282907686,"score_gpt":0.2117313070372763,"score_spread":0.2009469427543686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125138326","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":[0.004570719,0.00031129763,0.9936416,0.0000116521405,0.000092867405,0.00051881425,0.000045357796,0.00028736817,0.0005203093],"genre_scores_gemma":[0.9720575,0.00012396189,0.026356656,0.000013298621,0.00012218104,0.00026139888,0.00078317244,0.000043290598,0.0002385112],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941456,0.000014813048,0.00019020935,0.00012607862,0.0000746237,0.00017972967],"domain_scores_gemma":[0.9996975,0.00011013312,0.000023903383,0.000076803015,0.00005634534,0.0000353133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005595573,0.00009837005,0.00013291894,0.00006160075,0.000040346615,0.000008370788,0.00004558736,0.00006540531,0.0000034320612],"category_scores_gemma":[0.000024346551,0.000106651896,0.000020495454,0.0002533099,0.000017933073,0.00011699108,0.0000062367926,0.00006214544,0.000004856416],"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":[0.00000660211,0.000012266045,0.00008281727,0.000018142207,0.000011666528,0.000002989394,0.00011554449,0.9894979,0.000028841016,0.00011186246,0.0010507263,0.009060637],"study_design_scores_gemma":[0.0006651669,0.000015718046,0.0003255801,0.00004719595,0.0000048293246,0.000011003612,0.00016003798,0.9967141,0.00034845455,0.000010921072,0.0015673216,0.00012968222],"about_ca_topic_score_codex":0.000009278187,"about_ca_topic_score_gemma":0.000005995189,"teacher_disagreement_score":0.9674868,"about_ca_system_score_codex":0.0001135792,"about_ca_system_score_gemma":0.000008347661,"threshold_uncertainty_score":0.4349138},"labels":[],"label_agreement":null},{"id":"W2125161617","doi":"10.1109/icsmc.2004.1400909","title":"Scheduling bursty data at WCDMA downlink using fuzzy inference","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Telecommunications link; Scheduling (production processes); Code division multiple access; Maximum throughput scheduling; Fuzzy logic; Computer network; Distributed computing; Wireless; Wireless network; Dynamic priority scheduling; Mathematical optimization; Round-robin scheduling; Quality of service; Artificial intelligence","score_opus":0.046609707348122704,"score_gpt":0.2897950099036064,"score_spread":0.2431853025554837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125161617","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":[0.09630609,0.00044993055,0.8971538,0.000044564462,0.00019017344,0.000100888385,0.000011144107,0.00062161667,0.0051218094],"genre_scores_gemma":[0.6278146,0.00017773606,0.37145504,0.00004272214,0.00027696433,0.0000017268454,0.00009897198,0.000030935535,0.000101320744],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991333,0.000009161369,0.00021574805,0.00024135527,0.00012457331,0.00027587652],"domain_scores_gemma":[0.9992057,0.000050507704,0.000029873649,0.0006112751,0.00003115,0.00007148754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008029453,0.0001493001,0.00013170352,0.00005085739,0.000085472275,0.000031818436,0.00029114736,0.000081842794,0.00017082793],"category_scores_gemma":[0.00003400475,0.00015369002,0.000016342656,0.00020475473,0.000021543063,0.0006801607,0.00023089138,0.00013533015,0.00010862149],"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":[0.0000020641053,0.0000039613137,0.0003128423,0.000010440124,0.000009942121,0.0000014425525,0.00002648743,0.98319536,0.0015129285,0.00021358399,0.00013446467,0.014576486],"study_design_scores_gemma":[0.00015207627,0.0000025687277,0.000056377157,0.000027671329,0.000009252145,0.000006314649,0.00000987117,0.9950364,0.0011076172,0.000051844574,0.0033412634,0.00019871733],"about_ca_topic_score_codex":0.0000067109354,"about_ca_topic_score_gemma":0.00006437892,"teacher_disagreement_score":0.53150845,"about_ca_system_score_codex":0.00022624125,"about_ca_system_score_gemma":0.000016018046,"threshold_uncertainty_score":0.6267297},"labels":[],"label_agreement":null},{"id":"W2125338056","doi":"10.1109/icdcsw.2007.84","title":"Towards Guaranteed QoS in Mesh Networks: EmulatingWiMAX Mesh over WiFi Hardware","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Toronto","funders":"","keywords":"Computer science; Wireless mesh network; Computer network; IEEE 802.11s; Switched mesh; Network packet; Mesh networking; Shared mesh; Order One Network Protocol; Padding; Time division multiple access; Bandwidth (computing); Wireless network; Wireless; Operating system","score_opus":0.007641764997969277,"score_gpt":0.23432455912875794,"score_spread":0.22668279413078865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125338056","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":[0.03702134,0.00030559758,0.93130463,0.000015052211,0.0010141465,0.0003134021,0.0000027194037,0.0008438387,0.029179297],"genre_scores_gemma":[0.97370434,0.00013334607,0.02472791,0.00016981484,0.0006272148,0.000015087817,0.000033071585,0.0000987975,0.00049043354],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984292,0.000017401495,0.0004775522,0.00026383364,0.00021815683,0.00059388875],"domain_scores_gemma":[0.99945617,0.00007866552,0.0000467638,0.00028392594,0.000044083707,0.000090410664],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002601273,0.00026305753,0.00028354087,0.00021321826,0.000045824796,0.000034731303,0.00016602484,0.00018081818,0.0002832544],"category_scores_gemma":[0.000032074353,0.00027422488,0.000065771106,0.00083484827,0.000026439593,0.00028654825,0.000043490953,0.00028167668,0.000022617252],"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":[0.000021315378,0.000011508232,0.0023064122,0.000019142406,0.000017487682,0.000019421159,0.00016155842,0.9839808,0.00015417031,0.00236493,0.0022681605,0.008675136],"study_design_scores_gemma":[0.00066182273,0.000014605099,0.0062049166,0.00007192191,0.0000074394425,0.0000043435657,0.000072845,0.9900055,0.0005657917,0.000106467276,0.0019341733,0.00035019417],"about_ca_topic_score_codex":0.000023312528,"about_ca_topic_score_gemma":0.00016284987,"teacher_disagreement_score":0.936683,"about_ca_system_score_codex":0.00024168807,"about_ca_system_score_gemma":0.000013252644,"threshold_uncertainty_score":0.999971},"labels":[],"label_agreement":null},{"id":"W2125360243","doi":"10.1109/twc.2005.850272","title":"Downlink resource management for packet transmission in OFDM wireless communication systems","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":74,"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":"Orthogonal frequency-division multiplexing; Subcarrier; Computer science; Computer network; Telecommunications link; Scheduling (production processes); Resource allocation; Wireless; Network packet; Real-time computing; Channel (broadcasting); Telecommunications; Engineering","score_opus":0.016873393199859775,"score_gpt":0.25095157664205126,"score_spread":0.23407818344219147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125360243","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":[0.0051767365,0.0017519535,0.9867464,0.0009913506,0.00015284414,0.0016773709,0.00008726673,0.0007500882,0.002666003],"genre_scores_gemma":[0.9413233,0.010352862,0.04575882,0.000072279334,0.0000374039,0.0017635695,0.0002027147,0.00013085708,0.00035819077],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979121,0.00021750649,0.0008127745,0.00034101895,0.00025657125,0.0004600319],"domain_scores_gemma":[0.9968115,0.00048380485,0.00011741343,0.002353776,0.000099661804,0.00013382829],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003537268,0.00036296825,0.00038724442,0.00047023012,0.0005386224,0.00008124707,0.0011643893,0.00023888185,0.00001674289],"category_scores_gemma":[0.0000014810163,0.0004251159,0.00014441763,0.0008244681,0.00014117215,0.00043138472,0.000009275482,0.0006262776,0.000031546937],"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":[0.00004208773,0.00026829416,0.000004644537,0.0000911304,0.00005995578,3.5644294e-7,0.00044988233,0.8100653,0.0002294775,0.0025130338,0.0003472917,0.18592852],"study_design_scores_gemma":[0.0013408818,0.000033799817,0.000037010646,0.0004724434,0.000066238186,0.0000046090836,0.00043994238,0.9624252,0.0016501722,0.00008854714,0.032996293,0.00044487222],"about_ca_topic_score_codex":0.000022948561,"about_ca_topic_score_gemma":0.0002696874,"teacher_disagreement_score":0.9409876,"about_ca_system_score_codex":0.00048598665,"about_ca_system_score_gemma":0.000021127897,"threshold_uncertainty_score":0.99982005},"labels":[],"label_agreement":null},{"id":"W2125384169","doi":"10.1145/1454630.1454647","title":"Distributed resource allocation for multiuser OFDM wireless systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Knapsack problem; Greedy algorithm; Orthogonal frequency-division multiplexing; Resource allocation; Wireless; Distributed computing; Wireless network; Distributed algorithm; Wireless ad hoc network; Computer network; Mathematical optimization; Algorithm; Mathematics; Telecommunications; Channel (broadcasting)","score_opus":0.01309251491690844,"score_gpt":0.20415357885450397,"score_spread":0.19106106393759553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125384169","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":[0.033063866,0.0001479253,0.964744,0.000025393885,0.00019096157,0.0004249304,0.00002404681,0.0007370348,0.00064188725],"genre_scores_gemma":[0.990284,0.00007966308,0.008277447,0.000015713062,0.00014528136,0.00014490221,0.00042370087,0.00005306297,0.0005762224],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993367,0.00001077238,0.00020705377,0.00014074212,0.00009731524,0.00020740775],"domain_scores_gemma":[0.9995869,0.000071495284,0.00003027364,0.00018568145,0.00007309215,0.000052598218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046820165,0.00012150955,0.00013728604,0.000038246308,0.000091001,0.000012902952,0.00008484229,0.00008159266,0.0000057508014],"category_scores_gemma":[0.000014525192,0.00012371635,0.000031319625,0.00017280215,0.000020199803,0.0001388374,0.000009513048,0.000056343917,0.000011809007],"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":[0.000007985804,0.000009315321,0.00012413203,0.00003955398,0.000013800906,8.063747e-7,0.00006014717,0.98986775,0.0005874561,0.00071684504,0.007902642,0.000669564],"study_design_scores_gemma":[0.00037326492,0.000010268492,0.00019227032,0.000019006724,0.0000056367194,0.0000064417313,0.00005462986,0.9783937,0.0015433687,0.0000071157156,0.019236008,0.0001583094],"about_ca_topic_score_codex":0.000006202008,"about_ca_topic_score_gemma":0.0000043790155,"teacher_disagreement_score":0.95722014,"about_ca_system_score_codex":0.00008660858,"about_ca_system_score_gemma":0.000006473367,"threshold_uncertainty_score":0.5045007},"labels":[],"label_agreement":null},{"id":"W2125582716","doi":"10.1109/isit.2006.261921","title":"V-BLAST Power and Rate Control under Delay Constraints in Markovian Fading Channels - Optimality of Monotonic Policies","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Fading; Markov decision process; Computer science; Markov process; Mathematical optimization; Quality of service; Channel (broadcasting); Power control; Transmission (telecommunications); Constraint (computer-aided design); Channel state information; Wireless; Power (physics); Control theory (sociology); Computer network; Control (management); Mathematics; Telecommunications","score_opus":0.004781015772020278,"score_gpt":0.20477041652821673,"score_spread":0.19998940075619645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125582716","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":[0.47753543,0.00015008757,0.51466,0.000048159076,0.000072574156,0.00021762525,0.000010248286,0.000102740705,0.007203128],"genre_scores_gemma":[0.9965141,0.00004284957,0.0032891098,0.000037791775,0.000020500498,0.0000110711935,0.000005232071,0.000024539348,0.00005479667],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992399,0.00002830912,0.0002826884,0.00013364453,0.00006090124,0.00025451797],"domain_scores_gemma":[0.9997044,0.00008602423,0.000041734827,0.000103932485,0.000027531354,0.000036360594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012593553,0.0001401127,0.00022064926,0.000106913394,0.000022143342,0.000017707804,0.0000506795,0.00007415072,0.000057811754],"category_scores_gemma":[0.0000073617907,0.00014438726,0.000024129393,0.00016681358,0.000107098414,0.00016408187,0.000015122055,0.00008721033,0.000001476724],"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":[0.000010676011,0.000010689136,0.0017293321,0.000014766639,0.000013281388,0.000001918398,0.00006077141,0.99201506,0.0021691152,0.0037232772,0.000027724871,0.00022337296],"study_design_scores_gemma":[0.0012039854,0.00001934066,0.01711388,0.00004446725,0.000007881418,0.0000063737543,0.00013750605,0.9781623,0.0022596978,0.00079846504,0.00002370889,0.00022241601],"about_ca_topic_score_codex":0.000071954535,"about_ca_topic_score_gemma":0.00008598262,"teacher_disagreement_score":0.51897866,"about_ca_system_score_codex":0.00006563873,"about_ca_system_score_gemma":0.000008495915,"threshold_uncertainty_score":0.5887942},"labels":[],"label_agreement":null},{"id":"W2125758823","doi":"10.1109/iwcmc.2008.83","title":"Delay-Aware Rate Control for Multi-User Scalable Video Streaming Over Mobile Wireless Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Computer network; Scalability; Real-time computing; Network packet; Packet loss; Wireless network; Session (web analytics); Video streaming; Wireless; Telecommunications","score_opus":0.009906189187121179,"score_gpt":0.22528226841095234,"score_spread":0.21537607922383115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125758823","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":[0.055441815,0.0003783295,0.94201416,0.0000047787594,0.0003587946,0.0008624246,0.000020674694,0.0007496781,0.00016931696],"genre_scores_gemma":[0.9738096,0.0004261208,0.023389807,0.00012080549,0.00025345877,0.00047281053,0.00007459951,0.00014321921,0.001309584],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986515,0.000025137733,0.00034791869,0.00030454292,0.000107879896,0.00056303665],"domain_scores_gemma":[0.9992196,0.00020498948,0.000058328184,0.00028405123,0.00011066982,0.00012237506],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009688184,0.00028997473,0.0003362812,0.00006576176,0.00019322228,0.00002961108,0.00014500823,0.00018220232,0.000095977084],"category_scores_gemma":[0.0000107941805,0.0002923869,0.000095940326,0.00023658478,0.000042880336,0.00040246043,0.000023777155,0.00016999451,0.000014181554],"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":[0.00003121815,0.000029448986,0.0013803513,0.000025704583,0.000051955587,0.000007161672,0.000040841067,0.99203324,0.00025494778,0.00009188458,0.0022738494,0.0037794088],"study_design_scores_gemma":[0.002291753,0.00003320512,0.0005766012,0.000034745248,0.000021814149,0.000006684493,0.000036042933,0.994163,0.00067669293,0.0000072207445,0.0017952188,0.0003570643],"about_ca_topic_score_codex":0.000016648206,"about_ca_topic_score_gemma":0.000050321003,"teacher_disagreement_score":0.9186244,"about_ca_system_score_codex":0.00012707835,"about_ca_system_score_gemma":0.00001555141,"threshold_uncertainty_score":0.99995285},"labels":[],"label_agreement":null},{"id":"W2125828703","doi":"10.1109/glocom.2005.1578464","title":"Queueing analysis of OFDM/TDMA systems","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":30,"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 Manitoba","funders":"","keywords":"Queueing theory; Time division multiple access; Computer science; Layered queueing network; Rayleigh fading; Computer network; Queue; Orthogonal frequency-division multiplexing; Fading; Channel (broadcasting)","score_opus":0.01721836265690664,"score_gpt":0.2579243439454483,"score_spread":0.24070598128854165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125828703","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":[0.08487624,0.007176418,0.797732,0.00073484174,0.0011937306,0.0011652706,0.00084146456,0.0018251097,0.104454935],"genre_scores_gemma":[0.9648917,0.0027488852,0.03144381,0.00005763214,0.000106434956,0.000089598245,0.00036268402,0.000040748746,0.0002585517],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99737483,0.00017021845,0.0010999999,0.00036208576,0.00033965064,0.0006532215],"domain_scores_gemma":[0.9971058,0.00014742502,0.00031918215,0.0018497385,0.00036841494,0.00020944297],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027906144,0.00041071317,0.00079460285,0.0004251514,0.00021871361,0.00011708562,0.0012509133,0.00025424245,0.00021001497],"category_scores_gemma":[0.00003653247,0.0004745571,0.00024956366,0.0024956292,0.00015671877,0.00050147984,0.00012888125,0.00033149438,0.00009491984],"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":[0.0000068467643,0.000096960415,0.0012705949,0.000027652904,0.0007320942,8.89759e-7,0.00008563712,0.9701742,0.00016171904,0.008639576,0.005228016,0.013575808],"study_design_scores_gemma":[0.0003730252,0.000019295865,0.0021551463,0.000076964054,0.0004890592,0.0000100494335,0.00013693186,0.962796,0.00019017862,0.00011213117,0.033179138,0.00046209103],"about_ca_topic_score_codex":0.00029377994,"about_ca_topic_score_gemma":0.0023717333,"teacher_disagreement_score":0.88001543,"about_ca_system_score_codex":0.00061283034,"about_ca_system_score_gemma":0.00011770757,"threshold_uncertainty_score":0.99977064},"labels":[],"label_agreement":null},{"id":"W2126266444","doi":"10.1109/vetecf.2004.1404737","title":"Underground experiments of video transmission over an IEEE 802.11 infrastructure","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Université du Québec en Abitibi-Témiscamingue; Université Laval","funders":"","keywords":"Computer science; Codec; Quality of service; Computer network; Software deployment; Transmission (telecommunications); Wireless; Wireless network; Wi-Fi; Real-time computing; Telecommunications","score_opus":0.007142499745025477,"score_gpt":0.24090865842060308,"score_spread":0.2337661586755776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126266444","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":[0.29847088,0.00014991172,0.69882596,0.000009069386,0.00011682974,0.00008947476,0.0000014053372,0.00020211675,0.0021343653],"genre_scores_gemma":[0.9284867,0.0000966261,0.07107758,0.000038192422,0.000112239075,0.0000045928214,0.000013651943,0.000037973805,0.0001324423],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993712,0.000010620441,0.00019801411,0.00012805387,0.00013352348,0.0001586233],"domain_scores_gemma":[0.9996958,0.000012948854,0.000025523224,0.00017454074,0.000019074,0.000072119314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000022192327,0.00013178319,0.00012758897,0.00005056599,0.000025157315,0.000010538942,0.0000900356,0.000093370676,0.00051647646],"category_scores_gemma":[0.0000011347704,0.00012441112,0.000028816588,0.00012513301,0.000017085571,0.00046594566,0.000005920271,0.00007067827,0.0000036806439],"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":[0.0000071223812,0.00001627935,0.00020705114,0.000011806567,0.000009228257,3.093954e-7,0.00021742114,0.946783,0.03405331,0.00019653069,0.00075607427,0.017741842],"study_design_scores_gemma":[0.0005661574,0.000028911718,0.0013621557,0.000030999432,0.000007985584,0.0000019955787,0.00005730821,0.87591827,0.11661678,0.0002484483,0.0049459394,0.00021502351],"about_ca_topic_score_codex":0.0000051645766,"about_ca_topic_score_gemma":0.00001465352,"teacher_disagreement_score":0.63001585,"about_ca_system_score_codex":0.0000699091,"about_ca_system_score_gemma":0.000007635561,"threshold_uncertainty_score":0.5655055},"labels":[],"label_agreement":null},{"id":"W2126279047","doi":"10.1109/twc.2008.060507","title":"An optimization framework for balancing throughput and fairness in wireless networks with QoS support","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Computer science; Throughput; Maximum throughput scheduling; Quality of service; Fairness measure; Computer network; Max-min fairness; Wireless network; Resource allocation; Provisioning; Wireless broadband; Wireless; Radio resource management; Resource management (computing); Distributed computing; Dynamic priority scheduling; Telecommunications","score_opus":0.01685526415569001,"score_gpt":0.25251645209313117,"score_spread":0.23566118793744117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126279047","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":[0.023441277,0.000110864756,0.9745918,0.00011435864,0.00024482768,0.0008072432,0.00003715156,0.0005480391,0.00010442241],"genre_scores_gemma":[0.8021274,0.0037102462,0.19319545,0.000060344955,0.000051730753,0.0006149249,0.000106043466,0.00012042149,0.000013447393],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984649,0.000095744705,0.0004659081,0.00037209873,0.00017544632,0.00042593625],"domain_scores_gemma":[0.9978709,0.0004612134,0.000097219854,0.0012957929,0.00013537881,0.00013948904],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013846108,0.00033889856,0.0003759844,0.00023992105,0.0006445313,0.000052657182,0.0004908376,0.00026058574,0.000014533611],"category_scores_gemma":[0.000003481215,0.00037343407,0.00005500521,0.00078429905,0.0002524133,0.00070396083,0.000004814247,0.00061968964,0.0000018418407],"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":[0.000056623318,0.00018768631,0.00024309686,0.00003170474,0.000037000194,0.0000022262645,0.00067594566,0.98934263,0.00006434803,0.0012258303,0.0000147826195,0.008118118],"study_design_scores_gemma":[0.000798322,0.00013253553,0.00022662598,0.00016888414,0.000029959685,0.00003096356,0.00020444531,0.9972413,0.0005957668,0.00008844112,0.000053113534,0.00042960898],"about_ca_topic_score_codex":0.00002218984,"about_ca_topic_score_gemma":0.00036567132,"teacher_disagreement_score":0.7813964,"about_ca_system_score_codex":0.00017206432,"about_ca_system_score_gemma":0.000052556257,"threshold_uncertainty_score":0.99987173},"labels":[],"label_agreement":null},{"id":"W2126467939","doi":"10.1109/infcom.2009.5061955","title":"Structured Admission Control Policy in Heterogeneous Wireless Networks with Mesh Underlay","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Computer science; Burstiness; Queueing theory; Computer network; Overlay; Wireless network; Markov process; Markov decision process; Distributed computing; Wireless mesh network; Admission control; Handover; Underlay; Wireless; Signal-to-noise ratio (imaging); Mathematics; Telecommunications","score_opus":0.0033365266411775987,"score_gpt":0.20533404421710083,"score_spread":0.20199751757592324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126467939","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":[0.06605189,0.0002629834,0.9311013,0.00015296006,0.000081311795,0.0003271745,0.0000016577238,0.000555661,0.001465014],"genre_scores_gemma":[0.99507266,0.00014213707,0.0041682036,0.00031410463,0.00017859084,0.000008999839,0.000015883352,0.000045123244,0.00005428946],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990304,0.00002405818,0.00022295915,0.00020140091,0.00012895263,0.00039221768],"domain_scores_gemma":[0.999575,0.000029975386,0.00003356018,0.00021567717,0.000023266235,0.00012252567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000034729663,0.0002224136,0.00024186386,0.00013211368,0.000037639278,0.000027866063,0.0001133947,0.00013261585,0.000034652974],"category_scores_gemma":[0.0000051717984,0.00018570782,0.000027864913,0.000448319,0.000016409671,0.00013986198,0.000006657869,0.000182319,0.0000019125084],"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":[0.0000529469,0.000010590915,0.00028183009,0.0000045706174,0.0000119413435,0.000015867488,0.0000304462,0.97541255,0.00034760154,0.00064080075,0.00006940852,0.02312142],"study_design_scores_gemma":[0.0011970064,0.0000759199,0.0014070158,0.000038905982,0.000006172561,0.00002040619,0.000009705283,0.99592453,0.00068800343,0.0003021464,0.00008171832,0.00024844793],"about_ca_topic_score_codex":0.000009444068,"about_ca_topic_score_gemma":0.00011977426,"teacher_disagreement_score":0.92902076,"about_ca_system_score_codex":0.00014880842,"about_ca_system_score_gemma":0.00002069248,"threshold_uncertainty_score":0.7572945},"labels":[],"label_agreement":null},{"id":"W2126524517","doi":"10.1109/glocom.2008.ecp.117","title":"Optimal Cell Size in Multi-Hop Cellular Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Queen's University","funders":"","keywords":"Computer science; Hop (telecommunications); Cellular network; Computer network; Context (archaeology); Small cell; Distributed computing","score_opus":0.009735187687416878,"score_gpt":0.19285125939522849,"score_spread":0.1831160717078116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126524517","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":[0.12466284,0.00055679725,0.8703094,0.0000057195393,0.00019130365,0.00013219964,5.021743e-7,0.0003915835,0.0037496497],"genre_scores_gemma":[0.8481921,0.0005252213,0.15018684,0.000027214313,0.000071257215,0.000013877632,0.000008514177,0.000048914062,0.000926055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921495,0.000013364688,0.00021148915,0.00016113423,0.00008119409,0.00031787876],"domain_scores_gemma":[0.99966073,0.0000653436,0.000017785145,0.00017514947,0.000018157154,0.000062825726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004067065,0.00015275038,0.00015281266,0.00004615971,0.0000387014,0.000007329339,0.00010137391,0.0001096287,0.00014053607],"category_scores_gemma":[0.000008210377,0.00016581255,0.000033619133,0.00028491582,0.000024217437,0.00015204679,0.000024140463,0.00019250132,0.00003943535],"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":[0.0000035453265,0.000024650688,0.0008291901,0.0000067339533,0.0000027369674,0.000034256653,0.00008259931,0.9973762,0.0008736756,0.000011397751,0.0005147748,0.00024023985],"study_design_scores_gemma":[0.000537715,0.000007974766,0.0005966588,0.00000740062,0.0000018711465,0.0000033390322,0.000020820919,0.99469346,0.0034914846,0.0000018929172,0.00043977893,0.00019760015],"about_ca_topic_score_codex":0.000006523187,"about_ca_topic_score_gemma":0.000011810092,"teacher_disagreement_score":0.7235293,"about_ca_system_score_codex":0.00006127844,"about_ca_system_score_gemma":0.0000060758402,"threshold_uncertainty_score":0.676164},"labels":[],"label_agreement":null},{"id":"W2126624451","doi":"10.1109/icassp.2008.4517813","title":"Joint media-channel aware unequal error protection for wireless scalable video streaming","year":2008,"lang":"en","type":"article","venue":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Computer science; Computer network; Channel (broadcasting); Coding (social sciences); Network packet; Link adaptation; Scalability; Joint (building); Decoding methods; Video quality; Wireless; Real-time computing; Scalable Video Coding; Coding tree unit; Channel code; Algorithm; Telecommunications; Engineering; Fading","score_opus":0.05602525416569993,"score_gpt":0.2561150496788482,"score_spread":0.20008979551314826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126624451","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":[0.36092612,0.000069793365,0.6355937,0.00027053605,0.00080636604,0.0007145238,0.00005782606,0.00025133204,0.0013098116],"genre_scores_gemma":[0.9945143,0.00015626478,0.0046061426,0.000034581542,0.00043018576,0.00007153248,0.000009632313,0.000055939865,0.000121437544],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984602,0.000005062654,0.00045637027,0.00032574288,0.0004605419,0.00029209792],"domain_scores_gemma":[0.99852145,0.00005114318,0.00028953614,0.0000625216,0.0009961302,0.000079205114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017779425,0.0002733279,0.0002882416,0.00016414616,0.00029853577,0.000096547636,0.0002943015,0.00014470484,0.000012269329],"category_scores_gemma":[0.00009429138,0.0002386096,0.000071232156,0.0001817725,0.000172118,0.0004929856,0.00004822981,0.0003046941,0.0000012148607],"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":[0.00030661968,0.00014594333,0.00019404331,0.0012127247,0.000112572096,0.00000314588,0.0019239656,0.650327,0.2810103,0.0011399208,0.00050549005,0.063118264],"study_design_scores_gemma":[0.00046336782,0.00006665684,0.00013201302,0.00074722077,0.000028432924,0.000021731426,0.0007141988,0.9277115,0.06703242,0.0028166214,0.000011076399,0.00025479047],"about_ca_topic_score_codex":0.000009027098,"about_ca_topic_score_gemma":0.0000027310548,"teacher_disagreement_score":0.6335882,"about_ca_system_score_codex":0.00013036646,"about_ca_system_score_gemma":0.00006280548,"threshold_uncertainty_score":0.97302175},"labels":[],"label_agreement":null},{"id":"W2126897670","doi":"10.1109/tvt.2004.832413","title":"Finite-State Markov Modeling of Correlated Rician-Fading Channels","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University","funders":"","keywords":"Fading; Rician fading; Fading distribution; Markov model; Channel state information; Markov chain; Channel (broadcasting); Markov process; Computer science; Algorithm; Hidden Markov model; Mathematics; Rayleigh fading; Electronic engineering; Statistical physics; Statistics; Telecommunications; Engineering; Speech recognition; Physics; Wireless","score_opus":0.007208699521522155,"score_gpt":0.19963661143034933,"score_spread":0.1924279119088272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126897670","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":[0.09772812,0.00021975947,0.90007615,0.00007417858,0.0005041602,0.0002024874,0.000009552088,0.0010779381,0.00010766457],"genre_scores_gemma":[0.98752606,0.00046689657,0.011828153,0.000015331852,0.000012078065,0.000050410683,0.000005205428,0.00006927991,0.000026573438],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989534,0.000010928354,0.0003539116,0.00022801232,0.0001280952,0.00032566983],"domain_scores_gemma":[0.9994877,0.000030952888,0.00005297282,0.0003091077,0.00007770691,0.000041573807],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000058060097,0.00021211612,0.0002666122,0.0006307859,0.00009701241,0.0000072846774,0.00016847462,0.00032701824,0.000013315329],"category_scores_gemma":[0.0000064093388,0.0002453172,0.00008345778,0.0010840258,0.00006727049,0.0001337184,0.000001493048,0.000501197,0.000024164185],"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":[0.000012875152,0.000043927703,9.090003e-7,0.000023126315,0.000060870054,0.00001989945,0.00008557531,0.98431295,0.0030370373,0.000088913075,0.0000013500145,0.01231256],"study_design_scores_gemma":[0.0005493749,0.000061369,2.71204e-7,0.00011490451,0.000028472112,0.000021005202,0.000037719077,0.922178,0.075385265,0.0013944352,0.000027356895,0.00020185145],"about_ca_topic_score_codex":0.000007087252,"about_ca_topic_score_gemma":0.000009994887,"teacher_disagreement_score":0.8897979,"about_ca_system_score_codex":0.00015207373,"about_ca_system_score_gemma":0.000016304797,"threshold_uncertainty_score":0.9999999},"labels":[],"label_agreement":null},{"id":"W2126901436","doi":"10.1109/wcnc.2008.502","title":"Threshold-Based Rate Control for Multimedia Transport over Markovian Wireless Channels","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Queue; Queueing theory; Encoder; Real-time computing; Markov process; Computer network; Network packet; Throughput; Markovian arrival process; Packet loss; Channel (broadcasting); Wireless; Algorithm; Mathematics; Telecommunications; Statistics","score_opus":0.009623623439153834,"score_gpt":0.2068024842614961,"score_spread":0.1971788608223423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126901436","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":[0.08343293,0.000071028524,0.9139118,0.000047303165,0.00045506205,0.000700855,0.0000365384,0.00063161226,0.00071286684],"genre_scores_gemma":[0.98433477,0.00006575611,0.01430077,0.00023769363,0.0002248242,0.00020736756,0.00011852265,0.000096967044,0.0004133249],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999005,0.000009359712,0.00026307485,0.00021990019,0.00011780418,0.00038481536],"domain_scores_gemma":[0.9994797,0.000114186616,0.000032619024,0.00020510412,0.000057743044,0.000110649285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008259836,0.00022698933,0.00026862274,0.00007585394,0.00008795509,0.0000072753173,0.00011356478,0.00012017479,0.00013927641],"category_scores_gemma":[0.000005642963,0.00022663269,0.000100128986,0.00015638628,0.0000458191,0.00018085015,0.0000025516956,0.000100776866,0.000010713656],"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":[0.000076677745,0.000022323711,0.00124362,0.00003633748,0.000035183984,0.000009596663,0.00005688717,0.994837,0.0016516229,0.000089722285,0.00088136975,0.0010596754],"study_design_scores_gemma":[0.0028910006,0.000026704165,0.0019759277,0.00001820813,0.000019933874,0.0000016480312,0.000004718912,0.989297,0.0047045196,0.000033407894,0.0007387327,0.00028822207],"about_ca_topic_score_codex":0.000004077386,"about_ca_topic_score_gemma":0.00001584497,"teacher_disagreement_score":0.90090185,"about_ca_system_score_codex":0.000058002395,"about_ca_system_score_gemma":0.000021207788,"threshold_uncertainty_score":0.9241813},"labels":[],"label_agreement":null},{"id":"W2128050865","doi":"10.1109/glocom.2008.ecp.271","title":"Optimizing a Playout Buffer with Queueing Performance Metrics for One-Way Streaming Video","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"University of British Columbia","funders":"","keywords":"Queueing theory; Computer science; Function (biology); Queueing system; Algorithm; Computer network","score_opus":0.01684428249705967,"score_gpt":0.1989730471592064,"score_spread":0.18212876466214675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128050865","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":[0.19195545,0.00025991263,0.80371416,0.000008131338,0.00008731928,0.0002792641,0.0000023052462,0.0005290095,0.0031644523],"genre_scores_gemma":[0.66757566,0.0003164175,0.33166295,0.000022266435,0.00008514218,0.000053432705,0.000014840935,0.00006731957,0.00020195982],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989681,0.0000063471934,0.00023122152,0.00022147226,0.0001802967,0.00039251498],"domain_scores_gemma":[0.9994499,0.00014194955,0.000044966877,0.00020350513,0.00008375164,0.000075902455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007190147,0.00021047519,0.00022686982,0.0001798917,0.00019518772,0.000025338422,0.00011402205,0.00008021506,0.000018712164],"category_scores_gemma":[0.000022840915,0.0001972863,0.00003739203,0.00051415217,0.000028420216,0.00053962844,0.000021365338,0.00014127576,0.0000059055074],"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":[0.000023851828,0.0000117976215,0.0011873498,0.000066299275,0.00003620761,0.0000026286143,0.0002784089,0.9930175,0.00020586043,0.00013173628,0.00013503557,0.0049033593],"study_design_scores_gemma":[0.0006069358,0.00007308188,0.00042980388,0.000088277025,0.00001929799,0.000015058139,0.00006359488,0.9912406,0.006714305,0.000005992614,0.00043019588,0.00031284578],"about_ca_topic_score_codex":0.0000058212577,"about_ca_topic_score_gemma":0.000010551101,"teacher_disagreement_score":0.47562024,"about_ca_system_score_codex":0.00012663688,"about_ca_system_score_gemma":0.00001633824,"threshold_uncertainty_score":0.8045102},"labels":[],"label_agreement":null},{"id":"W2128349800","doi":"10.1109/vtcf.2006.178","title":"On Rate Assignment Schemes for the Reverse Packet Data Channel in cdma2000 1xEV-DV","year":2006,"lang":"en","type":"article","venue":"IEEE Vehicular Technology Conference","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"CDMA2000; Computer network; Computer science; Throughput; Network packet; Channel (broadcasting); Wireless; Real-time computing; Telecommunications; Code division multiple access","score_opus":0.02219962030249082,"score_gpt":0.23730287800167257,"score_spread":0.21510325769918176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128349800","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":[0.06772689,0.00073364883,0.92779773,0.0014328259,0.000424383,0.00086440047,0.000065446264,0.00069026824,0.000264389],"genre_scores_gemma":[0.99616504,0.00031330093,0.0029350596,0.00006898528,0.00006337725,0.00023688549,0.00008045826,0.000041057854,0.0000958295],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988193,0.00002994738,0.00025673327,0.0003801864,0.00013571736,0.0003781075],"domain_scores_gemma":[0.9987263,0.00013796038,0.000062858846,0.0009812798,0.00007082701,0.000020742193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029876147,0.00021843486,0.00021464855,0.00018264637,0.00008556031,0.000025398402,0.0006730498,0.00026985465,0.000013237867],"category_scores_gemma":[0.00007328859,0.00018559759,0.000026459953,0.00042994972,0.00013067726,0.00014018617,0.000072744544,0.00033280367,0.000021833472],"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":[0.000013608063,0.000036400277,0.000054138956,0.000018280647,0.000029059445,0.000011326984,0.000011093754,0.9751387,0.004169947,0.007828704,0.0031734738,0.009515265],"study_design_scores_gemma":[0.0006917618,0.000032380973,0.00006278741,0.00009194155,0.000025042222,0.0000034361105,0.00004258791,0.9566541,0.02133826,0.009498432,0.011312375,0.0002469123],"about_ca_topic_score_codex":0.0000124032995,"about_ca_topic_score_gemma":0.00011182986,"teacher_disagreement_score":0.9284382,"about_ca_system_score_codex":0.000098137556,"about_ca_system_score_gemma":0.000031923315,"threshold_uncertainty_score":0.756845},"labels":[],"label_agreement":null},{"id":"W2128625163","doi":"10.1109/ictel.2010.5478738","title":"Performance analysis of greedy subcarrier allocation schemes for OFDMA systems with adaptive modulation","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Subcarrier; Computer science; Orthogonal frequency-division multiplexing; Link adaptation; Telecommunications link; Resource allocation; Overhead (engineering); Modulation (music); Frequency-division multiple access; Scheme (mathematics); Greedy algorithm; Orthogonal frequency-division multiple access; Computer network; Mathematical optimization; Algorithm; Fading; Mathematics","score_opus":0.007038034792025418,"score_gpt":0.19709871731115797,"score_spread":0.19006068251913255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128625163","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":[0.44869888,0.000017751541,0.55077136,0.000002861739,0.00006782164,0.00017565802,0.000005346486,0.00007157878,0.00018872268],"genre_scores_gemma":[0.97083515,0.000021998676,0.028810663,0.000001715583,0.000044405242,0.00009949425,0.0000798122,0.000022049993,0.00008474172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994861,0.0000042538572,0.00018020114,0.00011294872,0.000108882916,0.000107600295],"domain_scores_gemma":[0.99949634,0.000030290861,0.000068492074,0.00015889952,0.00021998819,0.000025987498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006561767,0.00009416714,0.0001724305,0.0001662403,0.000031465184,0.000009059438,0.00005401339,0.00006194388,0.000012580996],"category_scores_gemma":[0.0000055318746,0.00008198642,0.00003234446,0.0006012657,0.000020535745,0.0002692684,0.0000044760536,0.000056139124,5.025562e-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":[0.00002248616,0.0000055880587,0.009497543,0.00003877929,0.00026347113,1.888096e-8,0.000051508658,0.98125887,0.0040507405,0.001357174,0.000008730421,0.003445065],"study_design_scores_gemma":[0.00017140018,0.000030322228,0.009670324,0.000013376415,0.00018871132,2.0273636e-7,0.000038105733,0.986319,0.0034000676,0.000003902519,0.000059775215,0.0001047903],"about_ca_topic_score_codex":0.000010983735,"about_ca_topic_score_gemma":0.00007997929,"teacher_disagreement_score":0.5221362,"about_ca_system_score_codex":0.000021831142,"about_ca_system_score_gemma":0.000007985334,"threshold_uncertainty_score":0.33433092},"labels":[],"label_agreement":null},{"id":"W2128744749","doi":"10.1109/glocom.2004.1379007","title":"Delay constrained rate and power adaptation over correlated fading channels","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":31,"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","funders":"","keywords":"Fading; Computer science; Markov decision process; Automatic repeat request; Power control; Channel (broadcasting); Markov process; Channel state information; Wireless; Control theory (sociology); Mathematical optimization; Power (physics); Computer network; Hybrid automatic repeat request; Control (management); Telecommunications; Telecommunications link; Mathematics; Statistics","score_opus":0.006838678567460416,"score_gpt":0.1997989429678833,"score_spread":0.19296026440042288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128744749","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":[0.16757202,0.00017393561,0.82607365,0.000037872847,0.00021206302,0.00012272308,0.00000165118,0.00042106377,0.005385022],"genre_scores_gemma":[0.9855947,0.00010094992,0.013802597,0.0000709622,0.000050907573,0.0000060277443,0.000016001773,0.0000275871,0.00033027952],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995323,0.000010070579,0.00014248013,0.000108843546,0.00004941006,0.00015691262],"domain_scores_gemma":[0.99979866,0.000043574448,0.000020983172,0.00006360476,0.000024627569,0.00004854639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005179166,0.000105371146,0.000090067195,0.000053357526,0.000037600104,0.000023078479,0.000025499852,0.00006701623,0.00022215654],"category_scores_gemma":[0.000010021965,0.00010867316,0.000012931229,0.00012496683,0.000019965792,0.00029447972,0.0000081733015,0.000078739424,0.00002028076],"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":[0.0000045039956,0.000002835806,0.000036316353,0.0000029596629,0.000012689141,0.0000014557093,0.0002928866,0.9915747,0.00084324833,0.00079536607,0.00022501824,0.006208019],"study_design_scores_gemma":[0.00039045175,0.000009688942,0.0001983384,0.00001489432,0.000005673672,0.000006444701,0.00005006337,0.99777347,0.00058379845,0.000054731878,0.00077565043,0.00013678907],"about_ca_topic_score_codex":0.0000014050987,"about_ca_topic_score_gemma":0.0000060717744,"teacher_disagreement_score":0.81802267,"about_ca_system_score_codex":0.000037806316,"about_ca_system_score_gemma":0.0000039837446,"threshold_uncertainty_score":0.44315627},"labels":[],"label_agreement":null},{"id":"W2128847308","doi":"10.1109/icc.2004.1313351","title":"Adaptive downlink multi-carrier resource allocation for real-time multimedia traffic in cellular systems","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Computer science; Quality of service; Telecommunications link; Resource allocation; Spectral efficiency; Computer network; Channel (broadcasting); Interference (communication); Multimedia; Mobile QoS; Real-time computing; Service (business); Service delivery framework","score_opus":0.01098071196907182,"score_gpt":0.21066182916887868,"score_spread":0.19968111719980686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128847308","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":[0.040965892,0.00028930738,0.95595044,0.000025633486,0.00020009937,0.0012349898,0.000021084965,0.00070068944,0.0006118354],"genre_scores_gemma":[0.8576592,0.00008076434,0.1411474,0.000009216687,0.00015656713,0.00024790425,0.00019221118,0.0000914474,0.00041524536],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892163,0.000024446377,0.00035671453,0.00026181282,0.00010865586,0.0003267418],"domain_scores_gemma":[0.99946713,0.000112230264,0.000049352882,0.00021890432,0.00006849599,0.00008389255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001472405,0.00020452485,0.00023322502,0.00013195888,0.000042944408,0.000023823051,0.0001123943,0.00017060702,0.000010222169],"category_scores_gemma":[0.00003597482,0.00021678345,0.00004701924,0.00027551453,0.000025199744,0.00020816759,0.000011235383,0.00011920162,0.000031145257],"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":[0.00002170286,0.00003132873,0.0000047196836,0.000034399734,0.000015254526,0.0000023358496,0.00052218314,0.9922029,0.0048827096,0.0002000697,0.000108409426,0.0019740334],"study_design_scores_gemma":[0.0013996862,0.00003289121,0.000033272976,0.000093329145,0.000010512782,0.0000010855222,0.0002496564,0.9956629,0.0018948176,0.00001251963,0.00035787988,0.0002514301],"about_ca_topic_score_codex":0.00003707755,"about_ca_topic_score_gemma":0.00006042353,"teacher_disagreement_score":0.81669337,"about_ca_system_score_codex":0.00032327615,"about_ca_system_score_gemma":0.000021085838,"threshold_uncertainty_score":0.8840172},"labels":[],"label_agreement":null},{"id":"W2128933849","doi":"10.1109/ccece.2005.1556893","title":"Total power constraint equality in integer bit loading algorithms for multicarrier systems","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rounding; Bit (key); Constraint (computer-aided design); Algorithm; Integer (computer science); Power (physics); Computer science; Bit error rate; Mathematical optimization; Mathematics; Decoding methods","score_opus":0.01234030696697811,"score_gpt":0.24339101791963808,"score_spread":0.23105071095265997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128933849","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":[0.02374093,0.00015351352,0.968032,0.000012711834,0.000526683,0.0004389904,0.000020692167,0.0003018911,0.0067725736],"genre_scores_gemma":[0.9698196,0.0000029893238,0.029540807,0.000009068924,0.00010636221,0.000077188735,0.000028999953,0.00003789067,0.00037711574],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990659,0.000015738102,0.00035102907,0.00017412726,0.000091455986,0.0003017837],"domain_scores_gemma":[0.99963593,0.00011396581,0.00002789875,0.00013139006,0.00004792757,0.00004286086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015197015,0.0001461053,0.00019499092,0.00007845317,0.000025342772,0.000034967783,0.00005463228,0.00009874341,0.00006219152],"category_scores_gemma":[0.00002151284,0.00014502308,0.000043043652,0.00015387098,0.000032394248,0.00015298536,0.00001362788,0.000103081555,0.000008031178],"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":[0.0000042921283,0.0000129224445,0.00021217714,0.00003251322,0.000009036669,0.0000017872584,0.000056695182,0.9899669,0.00077411626,0.007878064,0.00019563448,0.0008558292],"study_design_scores_gemma":[0.0004761693,0.000010421725,0.00014844244,0.000043080836,0.000003718027,0.0000049154933,0.00020987315,0.99733526,0.00085792685,0.0001337341,0.00057607365,0.00020036817],"about_ca_topic_score_codex":0.00006552811,"about_ca_topic_score_gemma":0.000024551982,"teacher_disagreement_score":0.94607866,"about_ca_system_score_codex":0.00015950565,"about_ca_system_score_gemma":0.000008318959,"threshold_uncertainty_score":0.591387},"labels":[],"label_agreement":null},{"id":"W2129431522","doi":"10.1109/glocom.2006.673","title":"WLC10-6: Higher Layer Performance Study of Power-Controlled Hierarchical Constellation-Based Multi-user Opportunistic Scheduling","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Scheduling (production processes); Round-robin scheduling; Network packet; Computer network; Real-time computing; Queueing theory; Fair-share scheduling; Distributed computing; Mathematical optimization; Mathematics; Quality of service","score_opus":0.014775687259093546,"score_gpt":0.23286438515197744,"score_spread":0.2180886978928839,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129431522","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":[0.8442007,0.00012934045,0.15120772,0.000019304103,0.00040545414,0.00065342715,0.000009769492,0.000305244,0.0030690888],"genre_scores_gemma":[0.9861031,0.000007917979,0.013481535,0.000023312003,0.00008310183,0.000021310512,0.000037775044,0.00004770937,0.0001942422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871904,0.00004883799,0.00053032127,0.00020963406,0.00021879212,0.00027340348],"domain_scores_gemma":[0.9993125,0.00014941437,0.00010962353,0.00028118552,0.000083653154,0.00006360811],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012836292,0.00021520033,0.00039285255,0.000111567555,0.00007755168,0.000021827263,0.00013114,0.00009387504,0.0001807334],"category_scores_gemma":[0.000012910755,0.00021511289,0.00006264925,0.00024127483,0.0000440463,0.000116474796,0.000020827922,0.00017397395,0.000015794498],"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":[0.00008307736,0.00021696027,0.023891933,0.000027311587,0.00003567829,0.0000050098465,0.000031286607,0.974508,0.00037847913,0.00024738425,0.00007410344,0.0005008046],"study_design_scores_gemma":[0.0066317488,0.00008463971,0.017190771,0.000038032762,0.00003872207,8.4622627e-7,0.000030532847,0.97511077,0.00021948572,0.000017789163,0.0003979236,0.00023872296],"about_ca_topic_score_codex":0.000014967252,"about_ca_topic_score_gemma":0.000018888475,"teacher_disagreement_score":0.14190245,"about_ca_system_score_codex":0.000070305934,"about_ca_system_score_gemma":0.00003113007,"threshold_uncertainty_score":0.8772049},"labels":[],"label_agreement":null},{"id":"W2129843857","doi":"10.1109/glocom.2004.1379083","title":"Combined adaptive modulation and truncated ARQ for packet data transmission in MIMO systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Link adaptation; Automatic repeat request; Hybrid automatic repeat request; Space–time block code; Computer science; Spectral efficiency; Physical layer; MIMO; Fading; Algorithm; Network packet; Bit error rate; Block Error Rate; Go-Back-N ARQ; Transmission (telecommunications); Computer network; Electronic engineering; Channel (broadcasting); Wireless; Telecommunications; Telecommunications link; Engineering","score_opus":0.026310082125990918,"score_gpt":0.23758172638551428,"score_spread":0.21127164425952336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129843857","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":[0.034696292,0.00036188617,0.9638112,0.00005207853,0.000053494026,0.0005081444,0.000020722799,0.00019018963,0.0003059522],"genre_scores_gemma":[0.95034593,0.00012249372,0.04904129,0.0000062710283,0.000047003294,0.000027680591,0.0003207896,0.000026428012,0.00006210937],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942005,0.000016425689,0.00018935715,0.00016770144,0.00007406198,0.00013238963],"domain_scores_gemma":[0.99969053,0.000050377417,0.000019986683,0.00017285172,0.000029225126,0.00003702283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012409313,0.00009758997,0.00012628656,0.000059640875,0.000023495346,0.00001565319,0.000070804264,0.0000662284,0.000005374875],"category_scores_gemma":[0.000005922355,0.000094890696,0.0000074521013,0.00012582816,0.000007995318,0.0003785094,0.000011206172,0.000048970174,0.0000012534249],"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":[0.00003229623,0.000010949491,0.00006385634,0.000025879504,0.000007823586,1.2767133e-7,0.000071261675,0.96318537,0.00044814154,0.00035254136,0.00032473935,0.03547702],"study_design_scores_gemma":[0.0010577514,0.000019943504,0.00065868517,0.000046024572,0.000008853032,5.7906846e-7,0.000043925396,0.99682635,0.00020461732,0.00009561438,0.00092084997,0.00011677924],"about_ca_topic_score_codex":0.000009632287,"about_ca_topic_score_gemma":0.00003652068,"teacher_disagreement_score":0.91564965,"about_ca_system_score_codex":0.000052999494,"about_ca_system_score_gemma":0.000005146964,"threshold_uncertainty_score":0.38695303},"labels":[],"label_agreement":null},{"id":"W2130102990","doi":"10.1109/glocom.2009.5425863","title":"Effective Cell Size Scheme in Multi-Hop Cellular Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Cell size; Computer science; Throughput; Hop (telecommunications); Reachability; Cellular network; Heuristic; Small cell; Computer network; Algorithm; Wireless; Telecommunications; Biology","score_opus":0.004098477491658325,"score_gpt":0.19830108886202824,"score_spread":0.19420261137036993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130102990","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":[0.04274044,0.00068632764,0.9499211,0.000013919347,0.00015883823,0.00035059068,3.6883876e-7,0.00046268696,0.0056657447],"genre_scores_gemma":[0.92424643,0.00012437109,0.07517835,0.00007092925,0.000075487056,0.000018791126,0.000007015541,0.000031091553,0.00024755413],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925745,0.000020685606,0.00017473724,0.00017454782,0.000070395035,0.00030218076],"domain_scores_gemma":[0.9996371,0.000100285746,0.000019132962,0.00016750126,0.000020298416,0.000055679928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000066208646,0.00016413086,0.00016476198,0.000048705326,0.00002282701,0.000014590654,0.00008677918,0.000118656535,0.00005006523],"category_scores_gemma":[0.000015759417,0.00017343514,0.000034145152,0.00033594665,0.000010233754,0.00015335386,0.000012048085,0.00021783351,0.000026275688],"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":[0.0000054377983,0.000032287233,0.0003008362,0.000007173185,0.0000029735197,0.000007967791,0.000042112744,0.98802495,0.0064349542,0.00006389989,0.000151368,0.0049260235],"study_design_scores_gemma":[0.00066240795,0.00002302917,0.001991814,0.000018955468,0.0000025934144,4.0195127e-7,0.000013414109,0.9862675,0.010613156,0.000044920045,0.0001595274,0.00020227418],"about_ca_topic_score_codex":0.0000027957587,"about_ca_topic_score_gemma":0.000009924121,"teacher_disagreement_score":0.88150597,"about_ca_system_score_codex":0.00009340564,"about_ca_system_score_gemma":0.0000028473241,"threshold_uncertainty_score":0.707248},"labels":[],"label_agreement":null},{"id":"W2130126171","doi":"10.1109/vetecs.2003.1207867","title":"SS-OFDM-F/TA system packet size and structure for high mobility cellular environments","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":7,"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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Orthogonal frequency-division multiplexing; Computer science; Network packet; Throughput; Computer network; Transmission (telecommunications); Disjoint sets; Transmission delay; Wireless; Telecommunications; Channel (broadcasting)","score_opus":0.0028145301819481883,"score_gpt":0.16362706031543126,"score_spread":0.16081253013348307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130126171","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":[0.32852513,0.00016298448,0.67026037,0.000012974834,0.00025191854,0.00042039092,0.000040355393,0.00021551106,0.00011035262],"genre_scores_gemma":[0.9630036,0.000033528297,0.036661353,0.000012233129,0.0000759999,0.000027914944,0.000040854535,0.000039463324,0.00010508428],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993368,0.0000072949456,0.0001669183,0.00020356789,0.00008663079,0.00019880563],"domain_scores_gemma":[0.99964595,0.000045494653,0.000024943749,0.00021428114,0.000007443542,0.00006186386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038213802,0.00015209643,0.00015771954,0.00001538214,0.000052653904,0.000016711236,0.00006108019,0.00010106421,0.000027656191],"category_scores_gemma":[0.0000089176665,0.00014487372,0.00002149472,0.00005437592,0.000024794246,0.00012529077,0.000021071597,0.00006771221,0.0000033022898],"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":[0.0000068690492,0.0000074115783,0.000098345554,0.00013127635,0.00001746307,0.0000010942013,0.000035993657,0.9867933,0.010574376,0.0019310147,0.00003137639,0.00037147765],"study_design_scores_gemma":[0.0068060607,0.00021153677,0.006630504,0.00021102549,0.00014376697,0.000020967193,0.0005298391,0.7220775,0.24582759,0.013035945,0.0028418163,0.0016634795],"about_ca_topic_score_codex":0.0000049956684,"about_ca_topic_score_gemma":0.000005831344,"teacher_disagreement_score":0.63447845,"about_ca_system_score_codex":0.00016596439,"about_ca_system_score_gemma":0.00000361783,"threshold_uncertainty_score":0.5907779},"labels":[],"label_agreement":null},{"id":"W2130609588","doi":"10.1109/twc.2008.070277","title":"Dynamic Bandwidth Allocation for QoS Provisioning in IEEE 802.16 Networks with ARQ-SA","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba; University of Waterloo","funders":"","keywords":"Computer science; Computer network; Quality of service; Bandwidth (computing); Automatic repeat request; Bandwidth allocation; Acknowledgement; Provisioning; Protocol data unit; Dynamic bandwidth allocation; Selective Repeat ARQ; Real-time computing; Hybrid automatic repeat request; Network packet; Telecommunications link","score_opus":0.014514802361817793,"score_gpt":0.23771150123657658,"score_spread":0.2231966988747588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130609588","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":[0.025642436,0.00027400808,0.9716579,0.00020682886,0.0003458183,0.0010484193,0.00002712912,0.00054390216,0.00025360985],"genre_scores_gemma":[0.95051414,0.0036186678,0.04410261,0.00004969681,0.0000328099,0.0012902254,0.00012087804,0.00013133445,0.00013966001],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99846584,0.00008470014,0.0005073314,0.00032228246,0.00019318683,0.00042665255],"domain_scores_gemma":[0.9978801,0.0004351929,0.000105777224,0.001328962,0.00014823335,0.00010173241],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013877796,0.00031699843,0.00031369305,0.0003261912,0.0006653401,0.00003560475,0.00057442184,0.00019057127,0.000011630726],"category_scores_gemma":[0.000004108173,0.0003456926,0.0000916535,0.0008969937,0.00018331241,0.00044064873,0.0000035319276,0.00060618605,0.000009314155],"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":[0.00005682639,0.0001814261,0.000038803337,0.000027495656,0.00004599732,0.0000010031499,0.00034181727,0.9785623,0.00037784092,0.000083417166,0.000091244074,0.02019184],"study_design_scores_gemma":[0.0010632398,0.00009197479,0.00015205496,0.00021315923,0.000035348385,0.00001846636,0.00009353322,0.996155,0.0014016504,0.000037116926,0.00034471744,0.00039368885],"about_ca_topic_score_codex":0.000031500953,"about_ca_topic_score_gemma":0.0015567284,"teacher_disagreement_score":0.92755526,"about_ca_system_score_codex":0.00043145168,"about_ca_system_score_gemma":0.00007012762,"threshold_uncertainty_score":0.9998995},"labels":[],"label_agreement":null},{"id":"W2131199936","doi":"10.1109/mcom.2008.4644119","title":"Improved VoIP capacity in mobile WiMAX systems using persistent resource allocation","year":2008,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":39,"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":"Voice over IP; WiMAX; Computer science; Computer network; Mobile communications over IP; Wireless broadband; IEEE 802; Overhead (engineering); Mobile broadband; Resource allocation; Wireless; Mobile telephony; Telecommunications; Mobile radio; Wireless network; The Internet; Quality of service; Public land mobile network","score_opus":0.0518988625697324,"score_gpt":0.24650211458051485,"score_spread":0.19460325201078246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131199936","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":[0.6893209,0.010045981,0.2918175,0.00014504947,0.00067140575,0.0017126584,0.000032523403,0.0009792815,0.0052747126],"genre_scores_gemma":[0.97508377,0.0015328887,0.022814862,0.000015183376,0.00007044462,0.0001908344,0.00008461514,0.00005509149,0.00015231366],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998931,0.000108967375,0.00041532228,0.00017331065,0.0001223058,0.00024910516],"domain_scores_gemma":[0.9982432,0.0000927833,0.00008756653,0.001402626,0.00011046746,0.00006334971],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016117665,0.00017322849,0.00021438078,0.00017312604,0.00020681688,0.000022536024,0.0004969202,0.00010040584,0.0000046110476],"category_scores_gemma":[0.000022415063,0.00020933905,0.000057071422,0.00057768764,0.00013215271,0.0002604076,0.000070156966,0.0002977053,0.000023550128],"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":[0.000004085559,0.000055777582,0.00021545382,0.00002891968,0.000016589102,7.395248e-7,0.0005468342,0.9850673,0.0132706575,0.000048323698,0.00031901782,0.00042631332],"study_design_scores_gemma":[0.00031295864,0.00001913306,0.00023058226,0.000066286375,0.000013918266,0.00003292791,0.0001245277,0.98954606,0.00023272257,0.00000545341,0.009209387,0.00020606535],"about_ca_topic_score_codex":0.00006227772,"about_ca_topic_score_gemma":0.000114809634,"teacher_disagreement_score":0.28576288,"about_ca_system_score_codex":0.00044356528,"about_ca_system_score_gemma":0.000024671976,"threshold_uncertainty_score":0.85365987},"labels":[],"label_agreement":null},{"id":"W2131204153","doi":"10.1109/icc.2007.701","title":"Hybrid Flow-Control for CDMA2000","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Bottleneck; Computer science; CDMA2000; Queue; Computer network; Network packet; Network congestion; Queueing theory; Flow control (data); Active queue management; Weighted round robin; Real-time computing; Quality of service; Round-robin scheduling; Dynamic priority scheduling","score_opus":0.00382088310965746,"score_gpt":0.19959738863437648,"score_spread":0.19577650552471904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131204153","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":[0.0028270027,0.00009909546,0.98648745,0.000013434508,0.0002646933,0.00020360979,0.000005275805,0.00048517398,0.0096142525],"genre_scores_gemma":[0.8553307,0.000012984396,0.1436479,0.00009705758,0.00024712537,0.000018061342,0.000015805292,0.00003669394,0.00059366727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953127,0.0000015296356,0.00012382568,0.000077751945,0.000046633122,0.00021897978],"domain_scores_gemma":[0.9997569,0.00007252099,0.000008644515,0.00009577207,0.000023431692,0.000042729935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008619804,0.00007501892,0.00007928267,0.00003513134,0.000034311004,0.000011411077,0.000046743917,0.000026110323,0.00005304181],"category_scores_gemma":[0.000009456161,0.00007577757,0.000030158613,0.000050599283,0.000008241598,0.00008636355,0.0000027444767,0.00003766068,0.000022936994],"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":[0.000010843236,0.0000031388522,0.000020213734,0.0000070008314,0.000008556533,9.873664e-7,0.00000856488,0.94430107,0.00016882706,0.0006438633,0.0023512242,0.052475683],"study_design_scores_gemma":[0.0004924975,0.000008618682,0.000047590303,0.0000033878084,0.0000049539117,0.0000017275381,0.00000362271,0.97520685,0.0042312853,0.0004854785,0.019410426,0.00010354478],"about_ca_topic_score_codex":7.09405e-7,"about_ca_topic_score_gemma":0.0000075684998,"teacher_disagreement_score":0.8525037,"about_ca_system_score_codex":0.000035957313,"about_ca_system_score_gemma":0.000003208344,"threshold_uncertainty_score":0.30901197},"labels":[],"label_agreement":null},{"id":"W2131603610","doi":"10.1109/pimrc.2012.6362810","title":"Energy-efficient resource and power allocation for uplink multi-user OFDM systems","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Telecommunications link; Orthogonal frequency-division multiplexing; Computer science; Transmitter power output; Multiplexing; Algorithm; Mathematical optimization; Mathematics; Channel (broadcasting); Computer network; Telecommunications; Transmitter","score_opus":0.009274405057076565,"score_gpt":0.21295897962183521,"score_spread":0.20368457456475864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131603610","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":[0.006879674,0.0014743117,0.989866,0.000013254389,0.00029677624,0.00020691233,0.0000018004976,0.00026621664,0.0009950218],"genre_scores_gemma":[0.9709336,0.000037668477,0.027103262,0.000029091398,0.000116332594,0.00008059004,0.000026112204,0.000044158765,0.001629145],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994658,0.000008447576,0.00014530733,0.00010050466,0.000060075643,0.00021981419],"domain_scores_gemma":[0.9996934,0.000049342438,0.000023326584,0.00012821266,0.000034518653,0.000071181654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009477831,0.00010091948,0.00009321033,0.000042322386,0.000044460576,0.000018676406,0.00003901299,0.00006906822,0.000006380225],"category_scores_gemma":[0.000008036812,0.00009574204,0.00001649771,0.000078292745,0.000010734169,0.00010058898,0.000013956758,0.00003428765,0.0000039209394],"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":[0.0000035743692,0.000016570446,0.00009894181,0.000028087208,0.000009623096,3.543664e-8,0.000121361474,0.9903974,0.0004488697,0.007019987,0.00094743865,0.00090811955],"study_design_scores_gemma":[0.00025225698,0.000007283123,0.00011195219,0.000014607249,0.0000065436325,0.0000015627784,0.00008574563,0.9517993,0.0008598469,0.0000016666837,0.046736643,0.00012261422],"about_ca_topic_score_codex":0.0000033699912,"about_ca_topic_score_gemma":0.0000010977067,"teacher_disagreement_score":0.964054,"about_ca_system_score_codex":0.00004542825,"about_ca_system_score_gemma":0.0000020580621,"threshold_uncertainty_score":0.39042473},"labels":[],"label_agreement":null},{"id":"W2131955292","doi":"10.1109/lcomm.2011.031411.101672","title":"A QoE-Oriented Strategy for OFDMA Radio Resource Allocation Based on Min-MOS Maximization","year":2011,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":40,"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":"Computer science; Maximization; Resource allocation; Novelty; Resource management (computing); Resource (disambiguation); Computer network; Mathematical optimization","score_opus":0.04031740105178782,"score_gpt":0.24239542213875495,"score_spread":0.20207802108696712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131955292","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":[0.0073018484,0.00013838764,0.98836106,0.0012671361,0.00018949111,0.00076748704,0.000028811788,0.000534076,0.0014116935],"genre_scores_gemma":[0.8771162,0.00014299034,0.12040667,0.0008401233,0.000076622804,0.00071256346,0.00056022516,0.00010018767,0.000044386783],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989805,0.00009126263,0.0003355457,0.00020817194,0.00013432816,0.0002501771],"domain_scores_gemma":[0.99813396,0.00019625216,0.00010904212,0.0013972583,0.00009863025,0.00006486745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013486945,0.00020073488,0.00016125254,0.00019359156,0.00021611399,0.000026102238,0.0005514538,0.00009477955,0.000019612016],"category_scores_gemma":[0.000031039537,0.00023875573,0.00006628064,0.0004299067,0.000086627966,0.00020806736,0.000021538219,0.00018567863,0.0000131420675],"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":[0.00003519718,0.00007426873,0.000088807225,0.000024419662,0.000026606298,2.742963e-7,0.0002822445,0.9852528,0.003751391,0.00073252455,0.0042000636,0.005531426],"study_design_scores_gemma":[0.0006049604,0.00004004534,0.00032675732,0.00006860463,0.000035236037,7.7998016e-7,0.000049191884,0.9870017,0.004034127,0.000041713538,0.0075433645,0.0002534729],"about_ca_topic_score_codex":0.00000943941,"about_ca_topic_score_gemma":0.00001890579,"teacher_disagreement_score":0.8698144,"about_ca_system_score_codex":0.00016521459,"about_ca_system_score_gemma":0.000018429366,"threshold_uncertainty_score":0.9736176},"labels":[],"label_agreement":null},{"id":"W2132128535","doi":"10.1109/tmc.2007.1051","title":"Optimal and Approximate Mobility-Assisted Opportunistic Scheduling in Cellular Networks","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Scheduling (production processes); Macrocell; Dynamic priority scheduling; Round-robin scheduling; Fair-share scheduling; Distributed computing; Algorithm; Computer network; Mathematical optimization; Quality of service; Base station; Mathematics","score_opus":0.011444725564159252,"score_gpt":0.23036018100810307,"score_spread":0.2189154554439438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132128535","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":[0.33837488,0.0001353129,0.6604739,0.0000018847774,0.00033568253,0.00028147025,0.00000200585,0.00031904964,0.00007582049],"genre_scores_gemma":[0.95386636,0.000090953305,0.04585167,0.000013001767,0.000072077244,0.000024345964,0.000008944586,0.000063197665,0.000009474224],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853927,0.000033217442,0.00048235033,0.00033418313,0.00012911823,0.00048185396],"domain_scores_gemma":[0.9993123,0.00025002332,0.000055187804,0.00022448518,0.000029549974,0.00012847374],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00043960885,0.00024380485,0.00025995137,0.0002140082,0.00017042572,0.000040632218,0.000097769545,0.00015104038,0.000011336475],"category_scores_gemma":[0.0000030683188,0.00029523522,0.000052277268,0.00048782866,0.000059340346,0.00013285436,0.0000027663039,0.0005111469,0.0000023677162],"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":[0.000019118628,0.000068274836,0.000046970104,0.00004953577,0.0000147794435,0.000020092397,0.00012467836,0.9405582,0.00092493196,0.000017988754,5.5802934e-7,0.05815489],"study_design_scores_gemma":[0.0004251016,0.000042655953,0.0001374071,0.00011695182,0.000015054828,0.000013759579,0.00015164002,0.99621207,0.002597444,0.000008995394,0.000014287826,0.00026465146],"about_ca_topic_score_codex":0.000004687817,"about_ca_topic_score_gemma":0.00001398591,"teacher_disagreement_score":0.61549145,"about_ca_system_score_codex":0.00015397996,"about_ca_system_score_gemma":0.000010777189,"threshold_uncertainty_score":0.99995},"labels":[],"label_agreement":null},{"id":"W2132153974","doi":"10.1109/lcn.2008.4664261","title":"Scheduling optimization in multiuser detection based MAC design for Ad-Hoc networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Scheduling (production processes); Quality of service; Maximum throughput scheduling; Computer network; Wireless ad hoc network; Distributed computing; Queueing theory; Round-robin scheduling; Network packet; Fair-share scheduling; Dynamic priority scheduling; Wireless; Mathematical optimization","score_opus":0.01842109403717711,"score_gpt":0.21369625955680233,"score_spread":0.1952751655196252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132153974","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":[0.0029639092,0.0004303142,0.9951055,0.000009600788,0.00025339797,0.000606739,7.170042e-7,0.0005675495,0.00006225542],"genre_scores_gemma":[0.4665141,0.00035982413,0.5328379,0.00002730203,0.000052170024,0.00011481575,0.000020675596,0.00005205547,0.000021080914],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991586,0.000027134618,0.00025911813,0.00019389282,0.00008087165,0.000280377],"domain_scores_gemma":[0.9995734,0.00014504854,0.00003562082,0.00013751669,0.000060943337,0.000047448346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011579729,0.00016038804,0.00014721265,0.00014521969,0.000091674956,0.00001366287,0.00006554384,0.00014644382,0.00002779488],"category_scores_gemma":[0.000035998768,0.00018174901,0.000038360995,0.00039937723,0.00001538738,0.00026721193,0.0000068666054,0.00012175519,0.0000027740125],"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":[0.000054564058,0.0000130759745,0.000066000386,0.000012477338,0.0000053209283,0.000001379923,0.000025959322,0.9915563,0.0002369999,0.000004070599,0.000027346838,0.007996498],"study_design_scores_gemma":[0.0009478173,0.000031474512,0.0000661978,0.000024587715,0.000005160879,0.0000019546142,0.000010055635,0.9952615,0.0033409183,0.000009634548,0.00009226763,0.00020841853],"about_ca_topic_score_codex":0.0000011582772,"about_ca_topic_score_gemma":0.000021760881,"teacher_disagreement_score":0.4635502,"about_ca_system_score_codex":0.00014236038,"about_ca_system_score_gemma":0.00001222137,"threshold_uncertainty_score":0.7411509},"labels":[],"label_agreement":null},{"id":"W2133040873","doi":"10.1109/icc.2005.1494968","title":"Dynamic resource allocation for delay-tolerant services in downlink OFDM wireless cellular systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Telecommunications link; Computer science; Orthogonal frequency-division multiplexing; Scheduling (production processes); Spectral efficiency; Computer network; Resource allocation; Wireless; Degradation (telecommunications); Distributed computing; Engineering; Telecommunications","score_opus":0.0039011518160025327,"score_gpt":0.1964111947693094,"score_spread":0.19251004295330687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133040873","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":[0.20054802,0.0009399313,0.79667324,0.00008558627,0.00014919449,0.00057580776,0.0000065112504,0.00040217288,0.00061955693],"genre_scores_gemma":[0.9839414,0.00010996599,0.0151535785,0.00004465943,0.000113589194,0.00009995928,0.0002012092,0.000064187756,0.0002714735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989743,0.00001927263,0.00037314536,0.00021544551,0.00012245993,0.00029536264],"domain_scores_gemma":[0.9995698,0.00005472876,0.000050024708,0.00022700537,0.00004780095,0.000050658397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013270965,0.00017515337,0.00020162929,0.00011653209,0.000043821336,0.00003753038,0.00015059987,0.00012910135,0.000007667296],"category_scores_gemma":[0.0000016143975,0.00018399858,0.000033793393,0.00023037234,0.0000102704,0.00025796777,0.000015325482,0.00010333762,0.000018005792],"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":[0.0000113395145,0.00001601813,0.000038963306,0.00020105738,0.000010775721,9.465505e-7,0.00021604437,0.98913443,0.0026435421,0.00043973848,0.000053279135,0.007233874],"study_design_scores_gemma":[0.0004730871,0.000011119171,0.000034861583,0.000107818465,0.000008224197,0.0000022638735,0.0001920403,0.99261695,0.0010863907,0.000018535487,0.005236926,0.00021176375],"about_ca_topic_score_codex":0.000022576956,"about_ca_topic_score_gemma":0.0003345039,"teacher_disagreement_score":0.7833933,"about_ca_system_score_codex":0.00021006339,"about_ca_system_score_gemma":0.0000073517936,"threshold_uncertainty_score":0.7503244},"labels":[],"label_agreement":null},{"id":"W2133050102","doi":"10.1109/eit.2009.5189624","title":"IP mobility scheme for multi-hop WiMAX","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Windsor","funders":"","keywords":"WiMAX; Computer network; Computer science; Mobile IP; Encapsulation (networking); The Internet; Mobile computing; IMT Advanced; Wireless; Internet Protocol; Mobile telephony; Mobile radio; Telecommunications; Mobile Web; Mobile technology; World Wide Web","score_opus":0.02062385402690113,"score_gpt":0.2648851644627979,"score_spread":0.24426131043589677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133050102","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":[0.0099971555,0.000116821386,0.98725706,0.000040517883,0.00009833878,0.0002688301,0.0000027161534,0.00062251923,0.0015960525],"genre_scores_gemma":[0.48625606,0.00002598158,0.51323074,0.000074050935,0.000059748796,0.000023494407,0.000014000987,0.00001606688,0.00029987612],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995402,0.0000029000607,0.000121643825,0.00011747214,0.000044413035,0.0001733667],"domain_scores_gemma":[0.99973863,0.000020443227,0.000010626716,0.00015508778,0.00003588107,0.000039319923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000044271255,0.00008897385,0.000092169495,0.000021116726,0.000029068931,0.000009685431,0.000059379603,0.00005148612,0.00003531865],"category_scores_gemma":[0.00002033188,0.00008953197,0.000032930897,0.00009530961,0.000008117477,0.00013798826,0.0000048531515,0.000050705283,0.000012159888],"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":[0.0000060318166,0.000029681674,0.00006822062,0.000013655564,0.0000053175518,2.0476133e-7,0.000021981334,0.9736552,0.00189848,0.001011506,0.0010779097,0.02221181],"study_design_scores_gemma":[0.00034317942,0.000017835482,0.00077667134,0.0000050845892,0.0000023982836,3.6958892e-7,0.000008618433,0.99297804,0.003514676,0.00028439742,0.001953631,0.000115102164],"about_ca_topic_score_codex":6.052845e-7,"about_ca_topic_score_gemma":0.0000037510467,"teacher_disagreement_score":0.4762589,"about_ca_system_score_codex":0.00004317334,"about_ca_system_score_gemma":0.0000033040044,"threshold_uncertainty_score":0.36510077},"labels":[],"label_agreement":null},{"id":"W2133216448","doi":"10.1109/tnet.2009.2033058","title":"Broadcasting Video Streams Encoded With Arbitrary Bit Rates in Energy-Constrained Mobile TV Networks","year":2009,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Broadcasting (networking); Computer network; Bit rate; Mobile telephony; Energy (signal processing); Energy consumption; Mobile radio; Telecommunications; Real-time computing; Electrical engineering","score_opus":0.007655420271796784,"score_gpt":0.2123924308660398,"score_spread":0.204737010594243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133216448","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":[0.02538804,0.0011287994,0.970051,0.00003757683,0.0007820399,0.00039087186,0.0000064528745,0.00094298087,0.0012722409],"genre_scores_gemma":[0.9772047,0.0012230499,0.020465054,0.00016752955,0.0005855446,0.00014927857,0.00003694369,0.00012336098,0.00004458561],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976313,0.000075610806,0.0006111311,0.0005457004,0.0002632929,0.000872964],"domain_scores_gemma":[0.9987834,0.00033476765,0.00011410167,0.0005481502,0.000052317453,0.0001672265],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015613149,0.00053076196,0.00047190484,0.000339895,0.0002497261,0.00009976382,0.00031202953,0.00026613465,0.00004675125],"category_scores_gemma":[0.000003965076,0.0005586622,0.000112545786,0.0014903105,0.00007347982,0.00045153568,0.000003263984,0.0007676394,0.0000037779128],"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":[0.00006956693,0.00006518174,0.0000955266,0.000009181178,0.000038269398,0.000033462595,0.0000965551,0.74623734,0.00022469452,0.000023676936,0.00003060479,0.25307596],"study_design_scores_gemma":[0.0009989537,0.00021342111,0.00007163501,0.00059331075,0.00004020326,0.000036893074,0.00008246065,0.9945333,0.0019338244,0.00040864557,0.00046634438,0.0006209801],"about_ca_topic_score_codex":0.00002502944,"about_ca_topic_score_gemma":0.00020252146,"teacher_disagreement_score":0.9518166,"about_ca_system_score_codex":0.00023897547,"about_ca_system_score_gemma":0.000041141175,"threshold_uncertainty_score":0.9996865},"labels":[],"label_agreement":null},{"id":"W2133698374","doi":"10.1109/glocom.2009.5425820","title":"Competitive Wireless Access for Data Streaming over Vehicle-to-Roadside Communications","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"Nanyang Technological University","keywords":"Computer science; Wireless; Computer network; Quality of service; Reservation; Wireless distribution system; Wi-Fi array; Wireless network; Telecommunications","score_opus":0.047537366400726935,"score_gpt":0.33216758410177044,"score_spread":0.2846302177010435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133698374","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":[0.011205666,0.00013499553,0.9700465,0.000525624,0.0001184472,0.00063574925,0.00008130449,0.00063983747,0.016611876],"genre_scores_gemma":[0.90959626,0.00018812736,0.088914886,0.00037030058,0.000082908846,0.00003592348,0.00065425807,0.000036867685,0.0001204726],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992069,0.000014558874,0.00021345908,0.00022709805,0.000093456154,0.00024455294],"domain_scores_gemma":[0.9982666,0.00019256848,0.00003114739,0.0013640885,0.000064636355,0.00008095596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007514929,0.00014196546,0.00016101068,0.00007042503,0.00009318353,0.00007779389,0.0011824206,0.000052625815,0.000018947509],"category_scores_gemma":[0.000026420843,0.00015541558,0.000022234066,0.00027391687,0.00002278558,0.00068057294,0.00025873492,0.00010556545,0.000010130911],"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":[0.000012584491,0.000043110755,0.00031935776,0.000012597668,0.000028201559,5.628334e-7,0.00008787045,0.86592287,0.0010332622,0.030964268,0.004553609,0.09702173],"study_design_scores_gemma":[0.0003133111,0.000018523733,0.00195362,0.000045238954,0.0000128826105,5.784665e-7,0.000046328867,0.98553383,0.0005568233,0.00031504154,0.010998727,0.00020508489],"about_ca_topic_score_codex":0.000011974322,"about_ca_topic_score_gemma":0.00022999456,"teacher_disagreement_score":0.8983906,"about_ca_system_score_codex":0.00006554321,"about_ca_system_score_gemma":0.000010997329,"threshold_uncertainty_score":0.6337663},"labels":[],"label_agreement":null},{"id":"W2133822874","doi":"10.1109/vetecs.2011.5956739","title":"On the Delay-Fairness through Scheduling for Wireless OFDMA Networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Queuing delay; Proportionally fair; Computer science; Scheduling (production processes); Fairness measure; Weighted fair queueing; Fair queuing; Max-min fairness; Quality of service; Generalized processor sharing; Queueing theory; Network packet; Maximum throughput scheduling; Network delay; Asymptotically optimal algorithm; Computer network; Wireless network; Wireless; Mathematical optimization; Round-robin scheduling; Resource allocation; Dynamic priority scheduling; Mathematics; Algorithm; Throughput; Telecommunications","score_opus":0.02716930953345961,"score_gpt":0.2168284805862294,"score_spread":0.18965917105276978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133822874","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":[0.024540793,0.00018485484,0.96511745,0.000042150106,0.0004313687,0.00038631287,0.000002172268,0.00048347143,0.008811398],"genre_scores_gemma":[0.95556015,0.00023025158,0.043371465,0.00022663097,0.00019302318,0.00021888183,0.0000091770235,0.00007929869,0.000111101544],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999216,0.000014541621,0.00019223364,0.00017240962,0.00008686929,0.0003179407],"domain_scores_gemma":[0.99939775,0.00021641399,0.00003566024,0.0002615356,0.00005417814,0.000034443554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000093797404,0.0001774759,0.00014510455,0.000021251131,0.0001274439,0.000020505295,0.00019952591,0.000105646344,0.00014285356],"category_scores_gemma":[0.000013488549,0.00012876485,0.00006011317,0.00019251822,0.000032931333,0.00018480755,0.000022903387,0.0001579623,0.000012717675],"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":[0.000018077775,0.000012236852,0.000028965696,0.000011084899,0.000028214497,6.018096e-7,0.00016329362,0.8733766,0.000020061228,0.122068055,0.0005582564,0.0037145726],"study_design_scores_gemma":[0.00020210801,0.000022301254,0.000024722318,0.000045401164,0.000013388688,0.0000010725714,0.0000823768,0.9908445,0.0017086916,0.0066404617,0.0002269029,0.00018808525],"about_ca_topic_score_codex":0.000005140208,"about_ca_topic_score_gemma":0.000009585573,"teacher_disagreement_score":0.93101937,"about_ca_system_score_codex":0.00003552055,"about_ca_system_score_gemma":0.0000052575756,"threshold_uncertainty_score":0.5250878},"labels":[],"label_agreement":null},{"id":"W2134298603","doi":"10.1109/tmc.2008.74","title":"Utility-Based Rate-Controlled Parallel Wireless Transmission of Multimedia Streams with Multiple Importance Levels","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Quality of service; Wireless; Computer network; Reliability (semiconductor); Resource allocation; Exploit; Multimedia; Distributed computing; Power (physics); Telecommunications","score_opus":0.013158122243363756,"score_gpt":0.21928404000324997,"score_spread":0.2061259177598862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134298603","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":[0.37059206,0.00007422725,0.62817603,0.0000038208427,0.0001289766,0.00064061646,0.0000172224,0.00033233906,0.000034690525],"genre_scores_gemma":[0.9315337,0.00007001918,0.068137854,0.000014109105,0.000034315046,0.00009047721,0.000014757602,0.00008172045,0.000023070308],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982839,0.00008154386,0.00062281475,0.0003650408,0.00025905183,0.00038762263],"domain_scores_gemma":[0.9986635,0.0005860421,0.00014892536,0.00034996468,0.00012090656,0.00013067375],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013594203,0.00035250085,0.00058765674,0.00015390427,0.00024289142,0.000010165212,0.00016383117,0.00013946561,0.000052082134],"category_scores_gemma":[0.0000037935326,0.00032505972,0.00016197834,0.00044644714,0.00011848372,0.00015651976,7.445647e-7,0.00035786274,0.0000036646816],"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":[0.0004228062,0.00018947698,0.00068872946,0.000072440926,0.00007499282,0.000011054642,0.00027993767,0.94238657,0.004618467,6.0409934e-7,0.0000062182285,0.0512487],"study_design_scores_gemma":[0.0063465154,0.00013432802,0.0006846789,0.00017741918,0.000041514704,0.0000067321207,0.000046853092,0.94775724,0.04447831,0.0000022389931,0.000019488705,0.00030465057],"about_ca_topic_score_codex":0.000010634116,"about_ca_topic_score_gemma":0.000023266333,"teacher_disagreement_score":0.56094164,"about_ca_system_score_codex":0.00006390906,"about_ca_system_score_gemma":0.0000643213,"threshold_uncertainty_score":0.9999201},"labels":[],"label_agreement":null},{"id":"W2134539842","doi":"10.1109/isit.2011.6033860","title":"On the stability region of multi-queue multi-server queueing systems with stationary channel distribution","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Queueing theory; Queue; Polytope; Stability (learning theory); Computer science; Channel (broadcasting); Stationary distribution; Layered queueing network; Network packet; Bulk queue; Applied mathematics; Mathematical optimization; Mathematics; Computer network; Discrete mathematics","score_opus":0.047032050325231396,"score_gpt":0.2092437801537135,"score_spread":0.16221172982848212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134539842","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":[0.13972822,0.00006540416,0.8592227,0.0000105950185,0.000108418964,0.0004244599,0.000017045071,0.00019664205,0.00022651572],"genre_scores_gemma":[0.9958279,0.000033459906,0.003908336,0.000008525973,0.00001659896,0.00006251118,0.00007172609,0.000029346069,0.00004158928],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923587,0.00005985814,0.0002396183,0.00016059534,0.0001380809,0.0001659555],"domain_scores_gemma":[0.99936366,0.00010128485,0.00008082067,0.000290326,0.00012810918,0.000035823472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013827524,0.00014279936,0.00013798937,0.000026108959,0.00006212421,0.000008307949,0.00009660034,0.00006266226,0.000018159679],"category_scores_gemma":[0.000029962504,0.000096147596,0.000026100386,0.00019015056,0.000050340805,0.00021542466,0.000014976073,0.0001125652,0.0000040659434],"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":[0.000045186585,0.00007492271,0.000984841,0.00007892799,0.000024460744,0.0000021487276,0.0004495633,0.9923915,0.00006907975,0.0056904955,0.000061969244,0.0001268891],"study_design_scores_gemma":[0.00035777764,0.000049586142,0.004180145,0.00009834853,0.0000084572275,0.0000026777277,0.0005667065,0.9916757,0.0028579265,0.000057187513,0.000008574673,0.00013691101],"about_ca_topic_score_codex":0.00015706298,"about_ca_topic_score_gemma":0.000089819136,"teacher_disagreement_score":0.85609967,"about_ca_system_score_codex":0.0001091601,"about_ca_system_score_gemma":0.000010416599,"threshold_uncertainty_score":0.39207852},"labels":[],"label_agreement":null},{"id":"W2134615796","doi":"10.1109/icc.2008.432","title":"Optimal Power Control over Fading Channel with Cross-Layer Performance Constraint","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Computer science; Fading; Markov decision process; Mathematical optimization; Transmission (telecommunications); Power control; Base station; Constraint (computer-aided design); Power (physics); Channel (broadcasting); Network packet; Correctness; Minification; Range (aeronautics); Linear programming; Optimal control; Markov process; Control theory (sociology); Computer network; Algorithm; Control (management); Mathematics; Telecommunications; Engineering","score_opus":0.007871611249600395,"score_gpt":0.206883523813807,"score_spread":0.1990119125642066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134615796","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":[0.51823074,0.00004616095,0.4737346,0.000005932295,0.00009801984,0.000121216064,0.0000029284743,0.00031909705,0.0074413563],"genre_scores_gemma":[0.9886741,0.00007463017,0.010696896,0.00007966519,0.000070297814,0.0000145329195,0.000005841058,0.000052812677,0.00033122834],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991603,0.000005240299,0.00017397913,0.00016934093,0.00014788282,0.00034329246],"domain_scores_gemma":[0.99965334,0.000027917542,0.000028427638,0.00015699166,0.00005637443,0.00007697613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000040778912,0.0001860373,0.00017298791,0.000052667896,0.00011839202,0.00002305415,0.00008000874,0.00007150273,0.00028374355],"category_scores_gemma":[0.0000039965516,0.00015946367,0.000029007504,0.00014219614,0.000112357644,0.00040540143,0.000010931739,0.00015038114,0.00003334468],"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":[0.000031459673,0.000008176958,0.0039974004,0.00000893006,0.00002976214,0.000014166248,0.00017252557,0.9951295,0.00022578811,0.00008749991,0.00016006861,0.0001346934],"study_design_scores_gemma":[0.0012334713,0.000057158126,0.006634213,0.00002330776,0.0000054160196,0.00008372818,0.00002648527,0.98985064,0.001587273,0.0000017969539,0.00022950003,0.00026702785],"about_ca_topic_score_codex":0.0000011866351,"about_ca_topic_score_gemma":0.0000010144328,"teacher_disagreement_score":0.4704434,"about_ca_system_score_codex":0.00006067634,"about_ca_system_score_gemma":0.000014215818,"threshold_uncertainty_score":0.650274},"labels":[],"label_agreement":null},{"id":"W2134724996","doi":"10.1109/glocom.2004.1378487","title":"Two-best user scheduling for high-speed downlink multicode CDMA with code constraint","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Telecommunications link; Computer science; Code division multiple access; Scheduling (production processes); Network packet; Link adaptation; Code rate; Throughput; Real-time computing; Constraint (computer-aided design); Computer network; Algorithm; Wireless; Fading; Decoding methods; Telecommunications; Mathematical optimization; Channel (broadcasting); Engineering; Mathematics","score_opus":0.011054079247888503,"score_gpt":0.23663896969113546,"score_spread":0.22558489044324695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134724996","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":[0.063754864,0.00008146492,0.93256134,0.00018583366,0.00012892939,0.00046421067,0.000022930706,0.0006456509,0.0021547913],"genre_scores_gemma":[0.5277019,0.00002524372,0.47165018,0.00006858568,0.00020151402,0.000023330163,0.0000355413,0.00005153292,0.00024215202],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901617,0.0000074277687,0.0002574339,0.00023066958,0.00011790085,0.0003704098],"domain_scores_gemma":[0.9994459,0.0001073125,0.00003976672,0.00021601602,0.00009372369,0.00009726111],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006576669,0.00021890072,0.0002135195,0.000061153,0.00007322866,0.000040484185,0.00010637852,0.00008223577,0.00011156519],"category_scores_gemma":[0.000016693099,0.00019478434,0.00003404563,0.00013616333,0.00005495265,0.00026657814,0.000015260981,0.00014015283,0.000041412368],"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":[0.000025968358,0.00002516418,0.0001005313,0.000021918584,0.000038604325,0.0000014330293,0.000050359497,0.9852877,0.0016261494,0.0055369255,0.00011296238,0.007172234],"study_design_scores_gemma":[0.001961469,0.000036400597,0.00002240472,0.00005265642,0.000026312917,0.000006913246,0.000088097586,0.9836597,0.011512664,0.000049690974,0.0022740113,0.0003096787],"about_ca_topic_score_codex":0.000008340345,"about_ca_topic_score_gemma":0.00023513232,"teacher_disagreement_score":0.46394706,"about_ca_system_score_codex":0.00010380988,"about_ca_system_score_gemma":0.000016627642,"threshold_uncertainty_score":0.79430753},"labels":[],"label_agreement":null},{"id":"W2134815783","doi":"10.1109/glocom.2007.903","title":"Performance Analysis of ARQ with Opportunistic Scheduling in IEEE 802.16 Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Goodput; Computer science; Computer network; Selective Repeat ARQ; IEEE 802; Hybrid automatic repeat request; Automatic repeat request; Media access control; Wireless broadband; Scheduling (production processes); Physical layer; Wireless; Wireless network; Telecommunications; Engineering; Quality of service","score_opus":0.008540789348448853,"score_gpt":0.20999740931282793,"score_spread":0.20145661996437908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134815783","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":[0.3733076,0.000039428756,0.62384593,0.0000012889852,0.00004028758,0.000047842695,4.3950223e-7,0.00007134406,0.0026458495],"genre_scores_gemma":[0.97141755,0.00020730312,0.02822239,0.000012245074,0.00003414031,0.0000034470363,0.000026697038,0.000023683204,0.00005253262],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992125,0.000005204231,0.00029555004,0.00012278472,0.0001118871,0.0002520867],"domain_scores_gemma":[0.99962264,0.00006081261,0.000050162467,0.0001732368,0.000039979757,0.00005317143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001855925,0.000115388386,0.000238741,0.0003292018,0.000018563887,0.000005654987,0.00007571096,0.00006243233,0.000042159118],"category_scores_gemma":[0.0000045106276,0.000106524545,0.000030330151,0.0016265112,0.000025653551,0.00013273758,0.000007315909,0.00012267777,0.0000010266072],"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":[0.000017285474,0.000009118633,0.032240372,0.000016793281,0.00010316491,0.0000035754833,0.00002593472,0.9612237,0.000055659115,0.00008787292,0.0000043472805,0.0062121437],"study_design_scores_gemma":[0.00016207404,0.000017618519,0.010176623,0.00003821524,0.000091660724,8.067259e-7,0.000041687887,0.9890776,0.00024931986,0.0000021270582,0.000010953519,0.00013129268],"about_ca_topic_score_codex":0.000007919148,"about_ca_topic_score_gemma":0.00029799095,"teacher_disagreement_score":0.59810996,"about_ca_system_score_codex":0.0000798205,"about_ca_system_score_gemma":0.000007858851,"threshold_uncertainty_score":0.43439448},"labels":[],"label_agreement":null},{"id":"W2134948485","doi":"10.1109/icc.2006.255410","title":"Optimal and Approximate Mobility Assisted Opportunistic Scheduling in Cellular Data Networks","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","funders":"University of British Columbia","keywords":"Computer science; Scheduling (production processes); Constraint (computer-aided design); Dynamic priority scheduling; Mobility model; Mathematical optimization; Fair-share scheduling; Distributed computing; Computer network; Algorithm; Mathematics; Quality of service","score_opus":0.10293129158668685,"score_gpt":0.31475729204383396,"score_spread":0.2118260004571471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134948485","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":[0.039616518,0.00034432329,0.9399432,0.0005096996,0.00033934292,0.00033249025,0.00021916941,0.00027571616,0.018419573],"genre_scores_gemma":[0.95804256,0.00084794644,0.03875142,0.00002424579,0.00007229737,0.00005543107,0.002097045,0.000027161104,0.00008189364],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988983,0.000063689775,0.0004083206,0.00027207655,0.00016117797,0.0001964081],"domain_scores_gemma":[0.9982858,0.00014798401,0.00008550638,0.0013149676,0.00011639344,0.000049392704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023396383,0.00016865447,0.00016284936,0.00012983134,0.00009985749,0.00009856395,0.0011095399,0.000093793846,0.000040461982],"category_scores_gemma":[0.000030312704,0.0001988917,0.000018936704,0.0001856085,0.00013381145,0.00031221015,0.00023595885,0.00035914758,0.0000069419734],"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":[0.000007802411,0.00010437829,0.0005683247,0.0000071736577,0.0000141830515,0.0000022111944,0.000013248513,0.976139,0.0005083783,0.020594254,0.00011438819,0.0019266475],"study_design_scores_gemma":[0.00025501673,0.00000726133,0.0013857693,0.000074798765,0.000008273344,0.0000033311908,0.000035613208,0.9969716,0.000048602975,0.00060068676,0.00042940516,0.00017961157],"about_ca_topic_score_codex":0.00007241197,"about_ca_topic_score_gemma":0.00031047722,"teacher_disagreement_score":0.91842604,"about_ca_system_score_codex":0.000111513014,"about_ca_system_score_gemma":0.00003071442,"threshold_uncertainty_score":0.81105685},"labels":[],"label_agreement":null},{"id":"W2135089263","doi":"10.1109/vetecs.2004.1389024","title":"Increasing the rate of wireless link when multiple QoS traffics are considered","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"Megabit; Computer science; Link adaptation; Computer network; Quality of service; Wireless; Fading; Channel (broadcasting); Real-time computing; Electronic engineering; Telecommunications; Engineering","score_opus":0.010823180023994712,"score_gpt":0.19706381381067498,"score_spread":0.18624063378668027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135089263","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":[0.63810545,0.00041390533,0.35809925,0.0006710272,0.00022890708,0.00034242612,0.000008740369,0.0005755121,0.0015547938],"genre_scores_gemma":[0.9669187,0.00013591556,0.032437686,0.000110133435,0.00026354037,0.000009927828,0.000009520296,0.0000429163,0.00007166455],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928284,0.000052521526,0.00027304672,0.000115516035,0.000081080914,0.00019497372],"domain_scores_gemma":[0.9992058,0.0003803907,0.00007189687,0.00023480102,0.000065900575,0.000041193165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015306997,0.00013588039,0.0001811252,0.000037836577,0.00005951217,0.000018197477,0.00011829223,0.000076956465,0.00005215511],"category_scores_gemma":[0.00006676987,0.00010806797,0.00004050744,0.00013008303,0.000050991453,0.00015516253,0.000022572376,0.00013948708,0.000011506763],"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":[0.000012129704,0.000008812257,0.0007192476,0.000018769848,0.000021620966,8.4332834e-7,0.00029337723,0.97868454,0.0018644796,0.00020518657,0.0007286664,0.017442305],"study_design_scores_gemma":[0.00039985607,0.0000047302965,0.00064555067,0.000044385863,0.00001155187,0.0000051090487,0.00016438572,0.98630726,0.010373887,0.000057220146,0.0018469243,0.00013914774],"about_ca_topic_score_codex":0.0000129671735,"about_ca_topic_score_gemma":0.00019827997,"teacher_disagreement_score":0.32881325,"about_ca_system_score_codex":0.00003351419,"about_ca_system_score_gemma":0.000010568929,"threshold_uncertainty_score":0.4406884},"labels":[],"label_agreement":null},{"id":"W2135260820","doi":"10.1109/tsp.2010.2049108","title":"How Much Multiuser Diversity is Required for Energy Limited Multiuser Systems?","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Alberta","funders":"","keywords":"Scheduling (production processes); Computer science; Telecommunications link; Fading; Diversity gain; Bit error rate; Channel state information; Wireless; Mathematical optimization; Real-time computing; Distributed computing; Channel (broadcasting); Computer network; Telecommunications; Mathematics","score_opus":0.01830725162337541,"score_gpt":0.21961073812993348,"score_spread":0.20130348650655808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135260820","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":[0.015430425,0.00012324171,0.9824538,0.00007971402,0.0008108532,0.0002962735,0.000049731785,0.00068579416,0.00007012091],"genre_scores_gemma":[0.98449934,0.000030185627,0.014428549,0.00007106779,0.00018543571,0.000114125905,0.000012516136,0.00009888646,0.00055988727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874175,0.000019549478,0.0002411348,0.00035512954,0.00024822218,0.00039421738],"domain_scores_gemma":[0.99922115,0.000110935325,0.00008247397,0.00022095736,0.00023394977,0.00013051742],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000084790634,0.00029094287,0.0002515309,0.00020021683,0.00067118305,0.00017802803,0.00019467823,0.00025830197,0.000020948062],"category_scores_gemma":[0.0000039663187,0.0003111691,0.00011036595,0.00036704438,0.000057047946,0.0008631294,0.0000028243098,0.00034622723,0.0000045205716],"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":[0.00007249637,0.00006844222,0.000012428422,0.00017165378,0.00005576755,0.0000022876457,0.00043104534,0.9034111,0.03803222,0.000017834538,0.00020847899,0.057516236],"study_design_scores_gemma":[0.00079194375,0.000034337998,0.0000067485344,0.00008879148,0.00005726124,0.0000052336236,0.00015425903,0.9124949,0.08445794,0.000042539163,0.0015151387,0.00035092968],"about_ca_topic_score_codex":0.0000138848345,"about_ca_topic_score_gemma":0.000053068725,"teacher_disagreement_score":0.96906894,"about_ca_system_score_codex":0.00008948667,"about_ca_system_score_gemma":0.000023980401,"threshold_uncertainty_score":0.999934},"labels":[],"label_agreement":null},{"id":"W2135381110","doi":"10.1109/tit.2009.2016058","title":"Fairness in Multiuser Systems With Polymatroid Capacity Region","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Blackberry (Canada); University of Waterloo","funders":"","keywords":"Computer science; Channel capacity; Mathematics; Telecommunications","score_opus":0.005846899715241029,"score_gpt":0.17508205607595353,"score_spread":0.1692351563607125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135381110","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":[0.021619974,0.00002411565,0.9754939,0.000019347532,0.00032269827,0.00031224464,0.0000078302,0.00046420709,0.0017356885],"genre_scores_gemma":[0.99862224,0.000044476514,0.001117544,0.00007307945,0.000020058687,0.000054292563,0.000008702509,0.000015993779,0.0000436414],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921703,0.000040676663,0.00031295186,0.00007948979,0.00015169836,0.00019814997],"domain_scores_gemma":[0.9995872,0.00004885405,0.00005901122,0.0002048078,0.00005029767,0.00004984746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011507062,0.00016302417,0.00014294346,0.00029886892,0.00007785315,0.00004423307,0.0000840685,0.0000994363,0.000009519418],"category_scores_gemma":[0.000001875031,0.00015341767,0.00003011908,0.00037990313,0.000027350092,0.0016254738,1.7979376e-7,0.00022895737,0.000041871488],"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":[0.00008627138,0.000020142636,0.0000056970407,0.000028410044,0.00000882712,8.4768146e-7,0.0007473324,0.9811226,0.000035689063,0.0019049271,0.00001969067,0.016019529],"study_design_scores_gemma":[0.001449112,0.0001238744,0.00045124989,0.00022364095,0.00001745964,0.000046431727,0.00074633834,0.9903137,0.005233158,0.0006676326,0.00028486358,0.00044255666],"about_ca_topic_score_codex":0.0000064814867,"about_ca_topic_score_gemma":0.000007986127,"teacher_disagreement_score":0.97700226,"about_ca_system_score_codex":0.00017282032,"about_ca_system_score_gemma":0.000010328099,"threshold_uncertainty_score":0.6256191},"labels":[],"label_agreement":null},{"id":"W2135500117","doi":"10.1109/tvt.2009.2037969","title":"Packet Scheduling and Fairness for Multiuser MIMO Systems","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":28,"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 du Québec à Montréal","funders":"","keywords":"Fairness measure; Computer science; Fair queuing; Computer network; Network scheduler; Network packet; Scheduling (production processes); Quality of service; Telecommunications link; Max-min fairness; Maximum throughput scheduling; Base station; Proportionally fair; Transmission delay; Processing delay; MIMO; Real-time computing; Round-robin scheduling; Wireless; Resource allocation; Channel (broadcasting); Throughput; Fair-share scheduling; Engineering; Telecommunications","score_opus":0.007220586631696357,"score_gpt":0.21607308187587876,"score_spread":0.2088524952441824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135500117","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":[0.09021974,0.0005702852,0.9070521,0.0001943342,0.0003505706,0.00042882425,0.000011335478,0.0011524758,0.00002030257],"genre_scores_gemma":[0.97369266,0.00025723566,0.025772836,0.0000247064,0.000030916668,0.00014786003,0.0000044353715,0.000040850937,0.000028489885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992168,0.00000962307,0.00019839162,0.00023507584,0.000071236915,0.00026888415],"domain_scores_gemma":[0.99958974,0.000037353813,0.000028105402,0.00024488967,0.000057020883,0.000042879547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053028667,0.00017971359,0.00021264558,0.00028716878,0.00012645156,0.000021239164,0.00009715114,0.00032478597,0.0000021714188],"category_scores_gemma":[0.0000043408245,0.00019449221,0.000045424174,0.00034261835,0.00004890747,0.00011690793,4.791709e-7,0.000249408,0.000005538303],"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":[0.000010418399,0.000026501368,0.0000039439133,0.00003271182,0.000029202936,0.0000029379412,0.000019457355,0.9601267,0.0068358504,0.0006353251,0.000012411991,0.03226452],"study_design_scores_gemma":[0.0006123158,0.000101917314,0.000010196291,0.000068026966,0.000032978493,0.000026725582,0.0000879044,0.9611882,0.03641794,0.00046745225,0.0007542705,0.00023210119],"about_ca_topic_score_codex":0.0000010243928,"about_ca_topic_score_gemma":0.0000042466836,"teacher_disagreement_score":0.8834729,"about_ca_system_score_codex":0.00005808176,"about_ca_system_score_gemma":0.0000056115855,"threshold_uncertainty_score":0.7931162},"labels":[],"label_agreement":null},{"id":"W2135802165","doi":"10.1109/icc.2005.1494859","title":"Coding rate adaptation for hybrid ARQ systems over time varying fading channels with partially observable state","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Partially observable Markov decision process; Computer science; Fading; Automatic repeat request; Markov process; Markov decision process; Network packet; Channel (broadcasting); Coding (social sciences); Markov chain; Observable; Heuristic; Channel state information; Buffer overflow; Algorithm; Mathematical optimization; Wireless; Markov model; Computer network; Hybrid automatic repeat request; Mathematics; Telecommunications link; Telecommunications; Statistics","score_opus":0.017104551081782937,"score_gpt":0.20673580415747048,"score_spread":0.18963125307568754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135802165","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":[0.036484733,0.00012512197,0.9612236,0.000022692248,0.00024182665,0.00060023944,0.000011042324,0.00063785544,0.0006529095],"genre_scores_gemma":[0.95783424,0.0000720792,0.040107,0.00003773092,0.00028600564,0.00014037735,0.000077521334,0.0000994832,0.0013455842],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893624,0.000020345828,0.00029198843,0.00022069928,0.00012467947,0.0004060565],"domain_scores_gemma":[0.9995032,0.00012224342,0.0000776939,0.00014413365,0.00007951302,0.00007320065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018492098,0.00020183534,0.00022121341,0.000070046364,0.0001172281,0.00011138737,0.00007868551,0.00003517692,0.0000297726],"category_scores_gemma":[0.000012007757,0.00019513494,0.000030236695,0.00016193783,0.00001013828,0.0008309915,0.000012050032,0.000077071425,0.000028246874],"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":[0.00003629119,0.0000059836784,0.000016017166,0.000070027505,0.00004000334,0.0000018712238,0.00020152901,0.99415845,0.0031140156,0.00020797137,0.00036375647,0.0017841146],"study_design_scores_gemma":[0.0006355282,0.00003337166,0.000008693806,0.00013088797,0.000018044944,0.0000039740944,0.000021780723,0.98986024,0.00764944,0.000035744342,0.001325143,0.00027716171],"about_ca_topic_score_codex":0.0000082312445,"about_ca_topic_score_gemma":0.000011412581,"teacher_disagreement_score":0.92134947,"about_ca_system_score_codex":0.0001497749,"about_ca_system_score_gemma":0.000015793363,"threshold_uncertainty_score":0.7957372},"labels":[],"label_agreement":null},{"id":"W2136121040","doi":"10.1109/twc.2007.360353","title":"Multi-User Opportunistic Scheduling using Power Controlled Hierarchical Constellations","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Constellation; Scheduling (production processes); Transmitter power output; Queueing theory; Network packet; Computer network; Real-time computing; Power control; Channel (broadcasting); Power (physics); Transmitter; Mathematical optimization; Mathematics","score_opus":0.0368500307624463,"score_gpt":0.2893020899085962,"score_spread":0.2524520591461499,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136121040","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":[0.019756362,0.00020618788,0.97629744,0.00011197286,0.0005420997,0.00071506016,0.0000571757,0.0008178907,0.0014958369],"genre_scores_gemma":[0.8220818,0.00047181203,0.17699444,0.00007145479,0.000028474487,0.00006440306,0.000032019285,0.00010023369,0.0001553432],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99800426,0.0001251541,0.0008187377,0.0002847767,0.00026009878,0.00050696253],"domain_scores_gemma":[0.9969296,0.0010103039,0.0001249885,0.0014870055,0.00019464681,0.00025349623],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038100898,0.00034531712,0.00045121586,0.0004363329,0.00084172067,0.00006766514,0.0005885335,0.00023421351,0.000103292085],"category_scores_gemma":[0.000016953827,0.00039385204,0.00020000146,0.00073292135,0.00033915375,0.0002921712,0.00000772898,0.00086303113,0.00004465914],"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":[0.00006178895,0.00026333256,0.000024563797,0.000011733491,0.0001364801,0.0000034985687,0.00020729426,0.9822132,0.009303359,0.0023248713,0.000009028504,0.005440874],"study_design_scores_gemma":[0.0023090693,0.000024716699,0.000045541852,0.00009699394,0.000103355356,0.000020019665,0.00021477799,0.99456716,0.0015852058,0.00004468968,0.00057579123,0.00041270722],"about_ca_topic_score_codex":0.0000097133825,"about_ca_topic_score_gemma":0.00012494031,"teacher_disagreement_score":0.8023254,"about_ca_system_score_codex":0.00027689812,"about_ca_system_score_gemma":0.000081969054,"threshold_uncertainty_score":0.99985135},"labels":[],"label_agreement":null},{"id":"W2136662549","doi":"10.1109/tmm.2008.2004915","title":"Channel Aware Multiuser Scalable Video Streaming Over Lossy Under-Provisioned Channels: Modeling and Analysis","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":24,"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","funders":"Aristotle University of Thessaloniki","keywords":"Computer science; Computer network; Scalability; Packet loss; Network packet; Real-time computing; Channel (broadcasting); Forward error correction; Wireless network; Lossy compression; Latency (audio); Wireless; Decoding methods; Algorithm; Telecommunications","score_opus":0.01811287303732982,"score_gpt":0.22929125145983964,"score_spread":0.2111783784225098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136662549","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":[0.13032672,0.00016750576,0.86822885,0.000019719708,0.00045059487,0.00024200225,0.000043211727,0.0004980533,0.000023366481],"genre_scores_gemma":[0.9871864,0.0010443203,0.011309536,0.000034445246,0.00009241805,0.000068975816,0.00003901057,0.00009365964,0.00013127693],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998463,0.00003200091,0.00035964116,0.00044037335,0.00027990236,0.00042510722],"domain_scores_gemma":[0.99919146,0.00014951036,0.000045540906,0.00033245562,0.00008394465,0.00019710488],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007228024,0.00033867042,0.00038267867,0.0005233958,0.00035843378,0.000034889836,0.000111915346,0.00020773581,0.00007650695],"category_scores_gemma":[0.000005283555,0.00036568634,0.0001463207,0.0009210727,0.000067068104,0.00047870248,0.000002330223,0.00035164537,0.000023928837],"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":[0.000024346444,0.0000588002,0.000028171436,0.000021965057,0.00027048404,0.0000072352427,0.0005998351,0.9915446,0.00035360944,3.0858982e-7,0.000013346061,0.0070772804],"study_design_scores_gemma":[0.00083115575,0.000024537767,0.00014141112,0.00004843059,0.00019857068,0.0000055454207,0.00013522271,0.9952767,0.0029450185,0.000015712314,0.000006222519,0.0003714888],"about_ca_topic_score_codex":0.00008407082,"about_ca_topic_score_gemma":0.00010419098,"teacher_disagreement_score":0.8569193,"about_ca_system_score_codex":0.00013160743,"about_ca_system_score_gemma":0.000016772941,"threshold_uncertainty_score":0.99987954},"labels":[],"label_agreement":null},{"id":"W2136735727","doi":"10.1109/softcom.2007.4446073","title":"Technical capability of the radio access technology 1xEV-DO","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Throughput; Computer network; Mobile telephony; Cellular network; Remote radio head; Radio access network; Mobile radio; Radio access technology; UMTS Terrestrial Radio Access Network; Access technology; Cellular radio; Telecommunications; Base station; Mobile station; Cognitive radio; Wireless; User equipment","score_opus":0.0063338251368745165,"score_gpt":0.24334954522377963,"score_spread":0.2370157200869051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136735727","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":[0.09741117,0.00015592697,0.8903698,0.000109563036,0.00019526665,0.00020902605,0.0000010491079,0.0005621435,0.010986049],"genre_scores_gemma":[0.9832037,0.00002413973,0.016678803,0.0000107186825,0.000026502727,0.0000060815637,6.5034294e-7,0.000016141461,0.000033246208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994148,0.000006019813,0.00021199876,0.000105291896,0.00008963364,0.00017223225],"domain_scores_gemma":[0.9994762,0.000054657936,0.000028300079,0.00038178734,0.00003776867,0.000021265118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014736144,0.000077752986,0.000113305694,0.00006520917,0.000025711743,0.000005112824,0.00033136265,0.00013223437,0.00004402023],"category_scores_gemma":[0.0000542692,0.000056952835,0.00003296804,0.0006581823,0.00011787841,0.00008832904,0.000085170555,0.00016378822,0.0000021868827],"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":[0.000007150247,0.000028514722,0.020513283,0.000031950356,0.000009644602,9.209393e-7,0.000017936733,0.93352073,0.009916683,0.0105522545,0.0005045069,0.024896398],"study_design_scores_gemma":[0.0010895522,0.0000661833,0.10566602,0.00011515745,0.00004704112,0.000058871843,0.00015771527,0.24080908,0.62423885,0.019272113,0.0076331277,0.0008462757],"about_ca_topic_score_codex":0.000002313043,"about_ca_topic_score_gemma":0.00003957847,"teacher_disagreement_score":0.88579255,"about_ca_system_score_codex":0.0000685436,"about_ca_system_score_gemma":0.0000066407815,"threshold_uncertainty_score":0.23224692},"labels":[],"label_agreement":null},{"id":"W2136762313","doi":"10.1109/tsp.2007.897859","title":"MIMO Transmission Control in Fading Channels—A Constrained Markov Decision Process Formulation With Monotone Randomized Policies","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":111,"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","funders":"","keywords":"Markov decision process; Mathematical optimization; MIMO; Fading; Markov process; Power control; Computer science; Control theory (sociology); Optimal control; Channel (broadcasting); Mathematics; Power (physics); Computer network; Statistics","score_opus":0.006940660203204731,"score_gpt":0.24240335916740624,"score_spread":0.23546269896420152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136762313","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":[0.065149434,0.00019761972,0.932851,0.000032456246,0.00009858393,0.00096227945,0.000004133374,0.00038853052,0.000315928],"genre_scores_gemma":[0.98531127,0.000057525718,0.014298784,0.000050456176,0.000060083665,0.00011181206,0.0000064129613,0.00008762766,0.000016032602],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980313,0.000046587465,0.00069146947,0.00032527413,0.00038708042,0.00051826116],"domain_scores_gemma":[0.9990257,0.00047059936,0.00012317627,0.00011050107,0.00013751537,0.00013252426],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00060558884,0.000360626,0.0005580169,0.00059815997,0.00025031198,0.00007867124,0.000113564725,0.00019006741,0.00003032309],"category_scores_gemma":[0.000005327587,0.0003165854,0.00009480259,0.0009193429,0.00009416697,0.0007815815,3.801292e-7,0.00039949146,0.0000022710933],"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":[0.011484736,0.000053322306,0.000008088029,0.00010086876,0.000024002024,0.0000070721317,0.0009683198,0.7826972,0.0033931232,0.000006162305,6.412515e-7,0.20125644],"study_design_scores_gemma":[0.03689453,0.00006487649,0.000014784095,0.00083178893,0.000056446097,0.00001915784,0.00020601174,0.9312594,0.029995602,0.00028683335,0.0000083487275,0.00036223585],"about_ca_topic_score_codex":0.000006626705,"about_ca_topic_score_gemma":0.000024560177,"teacher_disagreement_score":0.92016184,"about_ca_system_score_codex":0.00017943588,"about_ca_system_score_gemma":0.000051137977,"threshold_uncertainty_score":0.9999286},"labels":[],"label_agreement":null},{"id":"W2136896203","doi":"10.1109/icas-icns.2005.45","title":"Effect of channel estimation and prediction errors on Adaptive M-PSK systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"Fading; Rayleigh fading; Channel state information; Channel (broadcasting); Computer science; Phase-shift keying; Bit error rate; Modulation (music); Link adaptation; Algorithm; Fading distribution; SIGNAL (programming language); Electronic engineering; Telecommunications; Engineering; Wireless; Physics; Acoustics","score_opus":0.004352185778554285,"score_gpt":0.20060915198045093,"score_spread":0.19625696620189664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136896203","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":[0.1358008,0.00016934681,0.861798,0.000006688439,0.00017975701,0.00029101988,0.0000050545573,0.00026761214,0.0014817552],"genre_scores_gemma":[0.99707687,0.00004496525,0.0027103184,0.0000023105042,0.00007156885,0.00002713096,0.00001257796,0.000017834303,0.000036440822],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996008,0.000021648204,0.0001298068,0.00008409865,0.00008133166,0.000082312865],"domain_scores_gemma":[0.99979097,0.00006666685,0.000028536371,0.00007186433,0.000016384063,0.000025580883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008375523,0.00008791442,0.00011179358,0.00006190204,0.000019679614,0.000004947786,0.000020399586,0.00005184072,0.0000029603939],"category_scores_gemma":[0.000010582353,0.00007821344,0.000011781756,0.00008578245,0.000011607196,0.00016381302,0.000004824968,0.00004958262,0.000005297561],"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":[0.000024096695,0.0000036712465,0.00002780621,0.00005204613,0.000009701417,9.601998e-8,0.00005957561,0.9821857,0.00014031267,0.00030527814,0.00008758934,0.017104108],"study_design_scores_gemma":[0.00026182403,0.0002251789,0.00017390502,0.00007052481,0.000010418993,0.0000016744431,0.000013717237,0.9954374,0.003717034,0.000010539325,0.000020244073,0.000057582398],"about_ca_topic_score_codex":0.0000028369025,"about_ca_topic_score_gemma":0.0000012593348,"teacher_disagreement_score":0.86127603,"about_ca_system_score_codex":0.000048456994,"about_ca_system_score_gemma":0.0000012809272,"threshold_uncertainty_score":0.31894514},"labels":[],"label_agreement":null},{"id":"W2137106574","doi":"10.1109/tit.2005.850045","title":"A Generalized Framework for Distributed Power Control in Wireless Networks","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":173,"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","funders":"","keywords":"Computer science; Power control; Throughput; Wireless; Computer network; Transmitter power output; Signal-to-interference ratio; Coding (social sciences); Transmission (telecommunications); Interference (communication); Wireless network; Code rate; Power (physics); Real-time computing; Algorithm; Telecommunications; Mathematics; Decoding methods; Transmitter; Channel (broadcasting)","score_opus":0.004185315579633416,"score_gpt":0.21034552537403284,"score_spread":0.20616020979439942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137106574","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":[0.003505663,0.00003285825,0.9944865,0.00007578375,0.000567313,0.00060461625,0.00014392217,0.0004214439,0.00016189828],"genre_scores_gemma":[0.9837596,0.000088044246,0.01530447,0.00039191832,0.0000637873,0.00026871383,0.00007598328,0.00003178668,0.00001572698],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904764,0.000039905543,0.0004136642,0.00009278934,0.000112772665,0.00029323332],"domain_scores_gemma":[0.9993044,0.00029826217,0.00007012503,0.00019895367,0.00006541502,0.00006281431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002038623,0.00018818321,0.00019657785,0.00019189334,0.00010128383,0.000043688982,0.00011004689,0.00020286994,0.000100252146],"category_scores_gemma":[0.00000818657,0.00020323094,0.00008650623,0.0003293608,0.00002946504,0.000971788,3.8933734e-7,0.00028814047,0.000032951186],"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":[0.00020469664,0.00002870417,0.0000012431273,0.000013280742,0.000027971537,1.0980022e-7,0.00025741963,0.93987966,0.000010099783,0.015147829,0.00012933141,0.044299647],"study_design_scores_gemma":[0.0016138452,0.000025999709,0.000017276334,0.00004824018,0.000015188004,0.0000016489419,0.0000837804,0.9940129,0.0007194087,0.0018966723,0.0013420017,0.00022302408],"about_ca_topic_score_codex":6.2223177e-7,"about_ca_topic_score_gemma":0.0000045320153,"teacher_disagreement_score":0.98025393,"about_ca_system_score_codex":0.00019692285,"about_ca_system_score_gemma":0.000012216689,"threshold_uncertainty_score":0.82875174},"labels":[],"label_agreement":null},{"id":"W2137463408","doi":"10.1109/vetecs.2009.5073846","title":"Short-Term Power Allocation for Slowly Fading Channels Based on Markov Prediction","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Fading; Computer science; Channel state information; Channel (broadcasting); Predictability; Probabilistic logic; Term (time); Algorithm; Markov process; Power (physics); Transmission (telecommunications); Mathematical optimization; Markov chain; Mathematics; Wireless; Telecommunications; Statistics","score_opus":0.008594180661001483,"score_gpt":0.22366159225806084,"score_spread":0.21506741159705936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137463408","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":[0.009323472,0.000018115994,0.9837276,0.00008546661,0.0005012013,0.00043380863,0.0000062909007,0.000681187,0.005222876],"genre_scores_gemma":[0.97427636,0.000015964968,0.02502122,0.00012947929,0.00017090914,0.000056960926,0.00013970431,0.000034032546,0.00015536469],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993271,0.0000071280947,0.00017579709,0.00017152286,0.000111108835,0.00020729749],"domain_scores_gemma":[0.99969214,0.00003687939,0.000016959108,0.00015952307,0.000046336794,0.000048181137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000075214855,0.00013727017,0.0001022325,0.00010164979,0.000058108,0.0000263022,0.000060975242,0.00008610178,0.000030782558],"category_scores_gemma":[0.0000131939105,0.00014480062,0.00004318624,0.00014294281,0.00000536525,0.00020807804,0.000002589017,0.000066473534,0.0000052673618],"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":[0.000023281282,0.000018458975,0.00006536891,0.000010006551,0.0000051941424,3.007692e-7,0.000030876843,0.97888356,0.0014100797,0.00039364927,0.0010017975,0.018157406],"study_design_scores_gemma":[0.00027302877,0.00011503769,0.0018420641,0.000041707222,0.0000074285927,5.3512895e-7,0.0000054544175,0.9934957,0.0036637115,0.00010803991,0.00030485733,0.0001424331],"about_ca_topic_score_codex":1.2690134e-7,"about_ca_topic_score_gemma":4.777765e-7,"teacher_disagreement_score":0.9649529,"about_ca_system_score_codex":0.00011227261,"about_ca_system_score_gemma":0.000004509945,"threshold_uncertainty_score":0.5904798},"labels":[],"label_agreement":null},{"id":"W2137594086","doi":"10.1109/twc.2009.080399","title":"User capacity scaling laws for fading multiple-access channels","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo; University of Manitoba","funders":"","keywords":"Rician fading; Fading; Nakagami distribution; Computer science; Scaling law; Rayleigh fading; Scheduling (production processes); Fading distribution; Scaling; Telecommunications; Computer network; Mathematical optimization; Mathematics; Channel (broadcasting)","score_opus":0.04541074348868844,"score_gpt":0.28554726826083815,"score_spread":0.2401365247721497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137594086","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":[0.024301283,0.0001048395,0.97248435,0.00040062232,0.00053121976,0.00073090865,0.00008760884,0.00096359424,0.00039558427],"genre_scores_gemma":[0.95955706,0.000810863,0.03883019,0.00012333514,0.00006898298,0.0004117988,0.000046970625,0.000077802004,0.00007302411],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986861,0.000060711256,0.00043025584,0.0002624912,0.0001538547,0.00040659175],"domain_scores_gemma":[0.99789107,0.00047598637,0.00007791773,0.0012888896,0.00014326772,0.00012289532],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013215996,0.00028434125,0.00028779375,0.0002298135,0.00075339887,0.00012544834,0.0009191594,0.00016723109,0.000013126111],"category_scores_gemma":[0.000009183034,0.00033945846,0.0001550407,0.00056177966,0.00009255826,0.000672427,0.0000042409206,0.00044384433,0.000013647456],"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":[0.000015518674,0.00012963572,0.000008181589,0.000021767566,0.00003852182,1.6786502e-7,0.00025782923,0.96129274,0.003329046,0.0006891983,0.00010324466,0.034114126],"study_design_scores_gemma":[0.0006101478,0.000034836234,0.000061326806,0.00011751348,0.0000406092,0.000003281975,0.000048779155,0.973146,0.023560291,0.00036865167,0.0016308865,0.00037762852],"about_ca_topic_score_codex":0.000014162014,"about_ca_topic_score_gemma":0.00014467335,"teacher_disagreement_score":0.93525577,"about_ca_system_score_codex":0.00019358624,"about_ca_system_score_gemma":0.000017012373,"threshold_uncertainty_score":0.99990577},"labels":[],"label_agreement":null},{"id":"W2137999817","doi":"10.1109/ict.2014.6845075","title":"Unified Radio Access Network operation for Multi-Radio Access Technology cellular systems","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Radio access network; Computer science; Radio resource management; Computer network; Cellular network; Scalability; Remote radio head; Resource allocation; Radio frequency; Distributed computing; Cognitive radio; Telecommunications; Base station; Wireless; Wireless network; Operating system","score_opus":0.02479532622201766,"score_gpt":0.2666675356245602,"score_spread":0.24187220940254253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137999817","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":[0.0033699698,0.0005939983,0.99142724,0.00006778451,0.0012068053,0.0010215411,0.0000034530665,0.0013932732,0.0009159604],"genre_scores_gemma":[0.9382724,0.00013432071,0.059576795,0.000038447673,0.0008077767,0.00041462836,0.00016551268,0.00012713703,0.0004629413],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986797,0.000037441216,0.00038918754,0.00032246864,0.000110420595,0.00046076154],"domain_scores_gemma":[0.99925256,0.00008481775,0.0000747386,0.00041821753,0.000094867435,0.000074777374],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020483743,0.00025168265,0.00033325856,0.00016270381,0.00016244025,0.00023990787,0.0005555604,0.0002821702,0.000017426195],"category_scores_gemma":[0.000034486755,0.000253216,0.00004576033,0.0005333997,0.000034459234,0.00071943074,0.0000797017,0.00016183978,0.000011906523],"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":[0.000008222736,0.000011045582,0.00036238597,0.00008778253,0.000031145475,6.3139845e-7,0.000011238319,0.9827051,0.0005202695,0.011044562,0.0025424166,0.0026751806],"study_design_scores_gemma":[0.00073957857,0.000025082374,0.00005118687,0.000042565098,0.000020056917,0.0000028684472,0.00001571793,0.98350585,0.003707789,0.00017689446,0.011402282,0.0003101587],"about_ca_topic_score_codex":0.000008532662,"about_ca_topic_score_gemma":0.000027155977,"teacher_disagreement_score":0.9349025,"about_ca_system_score_codex":0.000117327596,"about_ca_system_score_gemma":0.000013003086,"threshold_uncertainty_score":0.999992},"labels":[],"label_agreement":null},{"id":"W2138129180","doi":"10.1109/vetecf.2005.1557498","title":"Delay statistics in multi-rate wireless networks with ARQ and weighted round-robin scheduling","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Computer science; Computer network; Scheduling (production processes); Hybrid automatic repeat request; Automatic repeat request; Wireless network; Wireless; Telecommunications; Mathematics; Mathematical optimization","score_opus":0.005579098838536332,"score_gpt":0.19836159652197552,"score_spread":0.1927824976834392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138129180","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":[0.17771587,0.0002707579,0.82135034,0.0000057976526,0.00006408132,0.0001530429,0.0000043377895,0.00023216991,0.00020359],"genre_scores_gemma":[0.6653419,0.00019572634,0.33419412,0.000013866598,0.000041392293,0.000013759559,0.00006052024,0.00004915105,0.00008957338],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991115,0.000023796374,0.0002563073,0.00020581855,0.00007625667,0.0003263271],"domain_scores_gemma":[0.9996565,0.00008289291,0.000038393468,0.00012767882,0.000043738848,0.000050773648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007937669,0.00020070089,0.00019450548,0.00008357457,0.000049321137,0.00005253703,0.0000572696,0.0000981046,0.000010893135],"category_scores_gemma":[0.0000027052736,0.00018725976,0.000008412838,0.0003249444,0.000039373357,0.00020895332,0.000017610446,0.00019918162,0.0000026838418],"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":[0.000012193167,0.000023915647,0.0042139324,0.000017911878,0.000009955367,0.000021975153,0.000020710293,0.99182534,0.000109556226,0.0018783885,0.000043555723,0.0018225627],"study_design_scores_gemma":[0.0008472934,0.000016374894,0.0034792693,0.00005768633,0.00000840536,0.0000065234863,0.000019651803,0.9949889,0.00015904926,0.00011075147,0.00004210313,0.00026395734],"about_ca_topic_score_codex":0.000081485225,"about_ca_topic_score_gemma":0.0015698125,"teacher_disagreement_score":0.48762602,"about_ca_system_score_codex":0.000079064186,"about_ca_system_score_gemma":0.000009114133,"threshold_uncertainty_score":0.7636232},"labels":[],"label_agreement":null},{"id":"W2138242868","doi":"10.1109/wcnc.2008.333","title":"Adaptive Cross Layer Scheduling with Flow Multiplexing","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Quality of service; Computer network; Scheduling (production processes); Multiplexing; OSI model; Physical layer; Service layer; Interconnection; Wireless; Wireless network; Network layer; Media access control; Application layer; Distributed computing; Layer (electronics); Telecommunications; Engineering","score_opus":0.02070762353780024,"score_gpt":0.22271257198093522,"score_spread":0.202004948443135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138242868","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":[0.13116428,0.00009325006,0.8635574,0.0000040759637,0.000075425254,0.00008725099,0.0000014928909,0.00060618034,0.0044106618],"genre_scores_gemma":[0.62160957,0.00002982981,0.3780878,0.000014736421,0.000064355845,0.000008783381,0.00000501109,0.0000325329,0.0001473984],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942225,0.0000052607666,0.00011315609,0.00013535257,0.00010450775,0.00021945915],"domain_scores_gemma":[0.999726,0.000031453397,0.000015249529,0.00012588545,0.000050529874,0.00005088714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000023459412,0.0001249687,0.00010567619,0.000036047866,0.00010807079,0.000013540405,0.000059019796,0.000048929927,0.000049361395],"category_scores_gemma":[0.000006602831,0.000110153305,0.00001922105,0.00017628595,0.000039901122,0.00028405132,0.000013304181,0.00011720149,0.000032374708],"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":[0.0000146417515,0.000004689553,0.0017275797,0.000004584505,0.000015873311,0.000012722406,0.00018693083,0.99667376,0.00024243841,0.000083671956,0.00003062089,0.0010024922],"study_design_scores_gemma":[0.00036618172,0.000015329613,0.00075594435,0.00002060128,0.0000020134066,0.000018274019,0.000035542893,0.9946065,0.003874043,0.000012275035,0.00012170848,0.00017157679],"about_ca_topic_score_codex":0.000003394182,"about_ca_topic_score_gemma":0.000012723798,"teacher_disagreement_score":0.4904453,"about_ca_system_score_codex":0.00004657784,"about_ca_system_score_gemma":0.000008498502,"threshold_uncertainty_score":0.44919214},"labels":[],"label_agreement":null},{"id":"W2138382726","doi":"10.1109/twc.2010.04.090256","title":"Enhancing cell-edge performance: a downlink dynamic interference avoidance scheme with inter-cell coordination","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":307,"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":"Throughput; Computer science; Enhanced Data Rates for GSM Evolution; Interference (communication); Telecommunications link; Base station; Computer network; Reuse; Radio resource management; Distributed computing; Wireless network; Wireless; Telecommunications; Engineering; Channel (broadcasting)","score_opus":0.007356751230398854,"score_gpt":0.2206405502834897,"score_spread":0.21328379905309083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138382726","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":[0.26515236,0.00006226055,0.7320825,0.000110021516,0.00038011605,0.00032239466,0.00002263234,0.00054974685,0.0013179941],"genre_scores_gemma":[0.9499811,0.0009316158,0.048155762,0.00003258674,0.000023288116,0.00035519365,0.000054633772,0.00010211511,0.00036368874],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985959,0.00005969671,0.00046042755,0.00032341966,0.00018474142,0.00037581136],"domain_scores_gemma":[0.997626,0.00021065165,0.00012800065,0.0017117993,0.00020254767,0.000120978264],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001376449,0.0003539792,0.00026746903,0.00027738488,0.0005314637,0.00008329598,0.00091095443,0.00019090222,0.000059459308],"category_scores_gemma":[0.000002607796,0.00037378396,0.000074404175,0.00067337026,0.00022124211,0.00063967507,0.000011218787,0.001521293,0.00009345551],"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":[0.000059432085,0.00051634974,0.00009697887,0.00022549467,0.00005688213,0.0000011927764,0.001270686,0.64187026,0.3068521,0.00012127572,0.00004065747,0.04888869],"study_design_scores_gemma":[0.00060282013,0.00009613617,0.000058268644,0.00020748781,0.000033092194,0.000010107113,0.00015175506,0.85809493,0.14001115,0.000012365453,0.00029461534,0.00042730052],"about_ca_topic_score_codex":0.000008395626,"about_ca_topic_score_gemma":0.0008140186,"teacher_disagreement_score":0.68482876,"about_ca_system_score_codex":0.00018491132,"about_ca_system_score_gemma":0.000056732646,"threshold_uncertainty_score":0.99987143},"labels":[],"label_agreement":null},{"id":"W2138410336","doi":"10.1109/tcomm.2009.08.070350","title":"Optimality of threshold policies for transmission scheduling in correlated fading channels","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":60,"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","funders":"","keywords":"Fading; Computer science; Network packet; Scheduling (production processes); Channel state information; Computer network; Transmission (telecommunications); Channel (broadcasting); Upper and lower bounds; Mathematical optimization; Dynamic priority scheduling; Wireless; Real-time computing; Mathematics; Telecommunications; Quality of service","score_opus":0.03317226548997994,"score_gpt":0.29012426326394336,"score_spread":0.25695199777396344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138410336","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":[0.01642876,0.0003364682,0.9814417,0.0003870788,0.00012384656,0.00041685117,0.000020418,0.00022590105,0.0006190287],"genre_scores_gemma":[0.9438459,0.0011731273,0.054799207,0.000026794445,0.000009495183,0.00007516582,0.000019400712,0.000025644607,0.00002522408],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991773,0.000028884779,0.0003906482,0.00011995695,0.000084168096,0.00019905053],"domain_scores_gemma":[0.9990449,0.00018284626,0.000050087427,0.0006101049,0.00006482254,0.000047269605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012455115,0.00013973676,0.00020171049,0.00023900424,0.000169366,0.000013096651,0.00032586342,0.00011466155,0.0000077110335],"category_scores_gemma":[0.0000036504373,0.00016293064,0.00008532351,0.0005464197,0.000051011906,0.00020297577,9.94447e-7,0.0002938379,0.0000015219945],"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":[0.000020517971,0.00012305197,0.00000399083,0.000017244085,0.000013509553,6.74362e-8,0.0005415949,0.9814939,0.00586767,0.00060043886,0.0000064606797,0.011311548],"study_design_scores_gemma":[0.0004643603,0.000051743686,0.00006121842,0.00016716028,0.000019701176,0.0000011275213,0.000074494965,0.97880006,0.019188736,0.00093897205,0.00008783821,0.00014460564],"about_ca_topic_score_codex":0.000007731162,"about_ca_topic_score_gemma":0.000016481603,"teacher_disagreement_score":0.92741716,"about_ca_system_score_codex":0.00009085635,"about_ca_system_score_gemma":0.000015547337,"threshold_uncertainty_score":0.66441184},"labels":[],"label_agreement":null},{"id":"W2138511162","doi":"10.1109/glocom.2006.952","title":"WSN11-1: Distributed Cross-Layer Optimization of Wireless Sensor Networks: A Game Theoretic Approach","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":59,"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":"Cross-layer optimization; Computer science; Mathematical optimization; Nash equilibrium; Physical layer; Layer (electronics); Optimization problem; Dual (grammatical number); Distributed computing; Wireless sensor network; Process (computing); Stability (learning theory); Set (abstract data type); Distributed algorithm; Wireless; Wireless network; Computer network; Mathematics; Algorithm; Telecommunications","score_opus":0.00556253653233551,"score_gpt":0.20820420437680368,"score_spread":0.20264166784446816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138511162","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":[0.044567425,0.0003770996,0.9515205,0.000008660206,0.00023320445,0.00027901545,0.000062962994,0.0004665314,0.0024845987],"genre_scores_gemma":[0.9597121,0.00013859435,0.03892887,0.000010722581,0.00021973113,0.000031623844,0.00082378875,0.000077126555,0.00005745145],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998624,0.00004274828,0.000476135,0.0002636241,0.00018954808,0.00040393506],"domain_scores_gemma":[0.9992787,0.000060045946,0.0001249246,0.00035378133,0.000121210986,0.0000613262],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000104189494,0.00025992948,0.00031899856,0.00006843193,0.000058180918,0.00005367286,0.000185074,0.0001828304,0.00005848366],"category_scores_gemma":[0.000013039856,0.0002732769,0.00008328145,0.0005587356,0.00012012619,0.0002069493,0.00003960553,0.00016151731,0.000006002929],"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":[0.000021370322,0.000051820232,0.0017293934,0.000060269198,0.000022195642,0.0000021448184,0.00002103724,0.99497133,0.000079273465,0.0021869722,0.00040786352,0.0004463169],"study_design_scores_gemma":[0.00053146563,0.000013597927,0.0013958889,0.000032081472,0.00002374512,0.000007423576,0.000016508779,0.996861,0.00045109677,0.00024110706,0.00015242171,0.00027367583],"about_ca_topic_score_codex":0.000016280432,"about_ca_topic_score_gemma":0.0000036548067,"teacher_disagreement_score":0.9151447,"about_ca_system_score_codex":0.00011407741,"about_ca_system_score_gemma":0.000011180609,"threshold_uncertainty_score":0.9999719},"labels":[],"label_agreement":null},{"id":"W2138536693","doi":"10.1109/icfin.2009.5339577","title":"Transporting voice using MBS in a WiMAX multi-hop relay environment","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"WiMAX; Computer network; Relay; Computer science; Multicast; Quality of service; Architecture; Hop (telecommunications); Telecommunications; Wireless","score_opus":0.013371840286940415,"score_gpt":0.22139112249621615,"score_spread":0.20801928220927574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138536693","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":[0.27275527,0.00022001463,0.72617966,0.000019775305,0.000040254854,0.000115966686,4.25395e-7,0.00018167861,0.00048694893],"genre_scores_gemma":[0.78502774,0.00011757454,0.21470803,0.00003491299,0.000027774482,0.0000030392275,0.0000036899764,0.000023098268,0.000054105985],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923027,0.000008528577,0.00028179737,0.00014998335,0.000086470056,0.00024297436],"domain_scores_gemma":[0.9997863,0.000013884346,0.000029105144,0.00012533707,0.000004178791,0.000041176143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006797722,0.00012502566,0.00013268237,0.00006586371,0.00002714664,0.000007806341,0.000056645156,0.00006435024,0.000033255834],"category_scores_gemma":[0.0000047272465,0.00013747536,0.000027304255,0.00014899136,0.000008738648,0.00019263908,0.0000040816285,0.00013202413,0.000011548962],"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":[0.0000028610907,0.000020354597,0.0013971714,0.000005910115,0.0000026766775,0.00000838023,0.00018160355,0.98598886,0.0061132233,0.00002595521,0.0000037644982,0.006249266],"study_design_scores_gemma":[0.00036752212,0.000009213246,0.0058261203,0.00003435543,0.0000048413476,0.0000022249676,0.000039074417,0.99180883,0.0014568182,0.00002044169,0.00026238794,0.00016818011],"about_ca_topic_score_codex":0.0000078181165,"about_ca_topic_score_gemma":0.000019460693,"teacher_disagreement_score":0.5122725,"about_ca_system_score_codex":0.00014386076,"about_ca_system_score_gemma":0.00000322958,"threshold_uncertainty_score":0.56060827},"labels":[],"label_agreement":null},{"id":"W2138922897","doi":"10.1109/wcnc.2003.1200646","title":"Modeling and analysis of WAP performance over wireless links","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Goodput; Wireless Application Protocol; Computer science; Wireless; Channel (broadcasting); Rayleigh fading; Computer network; Network packet; General Packet Radio Service; Fading; Wireless network; Throughput; Telecommunications","score_opus":0.006099423714051451,"score_gpt":0.20125593461613786,"score_spread":0.1951565109020864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138922897","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":[0.5266798,0.00007428598,0.47281113,0.0000025256431,0.000015320213,0.000020705414,7.55448e-7,0.000060361635,0.00033505916],"genre_scores_gemma":[0.98631346,0.0006280421,0.012991096,0.000011330454,0.000013892309,0.0000025422694,0.000010928141,0.000014179884,0.000014499608],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995878,0.0000019478766,0.00014834643,0.00008691199,0.000071423405,0.00010358406],"domain_scores_gemma":[0.9998213,0.000007485769,0.000013083997,0.0001064563,0.00002442264,0.000027267608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029850671,0.00007385126,0.00015191511,0.00012603715,0.000019625239,0.000005750269,0.00003783867,0.00007163336,0.000015871314],"category_scores_gemma":[0.0000014362297,0.00007247093,0.000028006172,0.00044447143,0.0000120591785,0.00015138666,0.000012819037,0.000086478634,7.785471e-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":[0.0000019645418,0.0000037150407,0.0014118757,0.000021832631,0.00009496968,1.6278803e-7,0.000081864295,0.9944615,0.0003603606,0.0003282915,7.8407527e-7,0.0032326824],"study_design_scores_gemma":[0.00015707806,0.000005859555,0.0010304706,0.000015286521,0.00008364276,2.4194182e-7,0.000011581838,0.99732846,0.001243668,0.00003688118,0.0000024892258,0.00008431501],"about_ca_topic_score_codex":0.000010490307,"about_ca_topic_score_gemma":0.000019721881,"teacher_disagreement_score":0.45982006,"about_ca_system_score_codex":0.000027199198,"about_ca_system_score_gemma":0.0000035232617,"threshold_uncertainty_score":0.29552788},"labels":[],"label_agreement":null},{"id":"W2139072526","doi":"10.1109/twc.2003.819028","title":"Dynamic Fair Scheduling With QoS Constraints in Multimedia Wideband CDMA Cellular Networks","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":79,"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":"Computer science; Computer network; Code division multiple access; Scheduling (production processes); Quality of service; Time division multiple access; Generalized processor sharing; Cellular network; Wideband; Telecommunications link; Fairness measure; Dynamic priority scheduling; Distributed computing; Round-robin scheduling; Throughput; Wireless; Telecommunications; Mathematical optimization; Electronic engineering","score_opus":0.009197710111339486,"score_gpt":0.22203098572632413,"score_spread":0.21283327561498463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139072526","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":[0.043352943,0.00036262407,0.9543504,0.00019742562,0.00029399252,0.00052698184,0.00002310121,0.0005735065,0.0003189885],"genre_scores_gemma":[0.90912455,0.0017026359,0.08868612,0.000037754075,0.00001811309,0.0002488351,0.000059861868,0.000103626226,0.000018473367],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985333,0.00007152189,0.00046802437,0.00029621072,0.00019166268,0.00043927238],"domain_scores_gemma":[0.9981868,0.00023642556,0.000077039826,0.0012840037,0.00008113171,0.00013456594],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011405779,0.00033291883,0.0003157331,0.0002980448,0.00032366998,0.000048510046,0.00058469863,0.00020382197,0.000026014457],"category_scores_gemma":[0.0000031521056,0.00036698228,0.00007516341,0.00089591276,0.00039670191,0.0003584846,0.0000049759196,0.0009396084,0.000026331212],"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":[0.00002043126,0.00018712823,0.0000274065,0.000016832717,0.000052415173,0.000006064617,0.0003427434,0.97680026,0.0016414007,0.00015235119,0.0000017127786,0.020751262],"study_design_scores_gemma":[0.0015767395,0.000040803072,0.00007751773,0.0003447851,0.000035363257,0.000012142167,0.00021609427,0.9936969,0.0034917325,0.000063975196,0.000034039353,0.00040990312],"about_ca_topic_score_codex":0.00003401953,"about_ca_topic_score_gemma":0.0016069786,"teacher_disagreement_score":0.86577165,"about_ca_system_score_codex":0.00040586424,"about_ca_system_score_gemma":0.000066273686,"threshold_uncertainty_score":0.9998782},"labels":[],"label_agreement":null},{"id":"W2139194315","doi":"10.1109/isit.2003.1228049","title":"Adaptive OFDM with space-time coding and antenna selection for broadband wireless communications","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Concordia University","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Link adaptation; Coding (social sciences); Electronic engineering; Adaptive coding; Spectral efficiency; Wireless; Broadband; Antenna (radio); Space–time code; Wireless broadband; Telecommunications; Block code; Decoding methods; Engineering; Wireless network; Algorithm; Fading; Mathematics; Channel (broadcasting); Data compression","score_opus":0.011288456717133353,"score_gpt":0.21266095102751667,"score_spread":0.20137249431038332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139194315","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":[0.010421309,0.0002369273,0.98423594,0.000036176996,0.000025274572,0.00035721736,0.000003948087,0.0002763943,0.004406791],"genre_scores_gemma":[0.8445786,0.00033534228,0.15450944,0.0000131066945,0.000014897138,0.000057097473,0.000012968629,0.000038686714,0.0004398597],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995258,0.000019639978,0.00010847338,0.00012498318,0.000051593142,0.00016950381],"domain_scores_gemma":[0.9995685,0.00010783475,0.000029149214,0.00017209661,0.000077559846,0.00004481474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006128947,0.00011813268,0.00013029952,0.000054635766,0.00014439921,0.000025224319,0.000057993442,0.000049759623,0.000011988214],"category_scores_gemma":[0.000009641436,0.00011181079,0.000013725886,0.0002232395,0.000048188303,0.00020113746,0.000010192016,0.000081495,0.0000024288515],"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":[0.00010038919,0.00006116018,0.0022813103,0.00008446312,0.00018736447,5.1560676e-7,0.0005104353,0.9057543,0.019078854,0.06299752,0.0008926979,0.008050985],"study_design_scores_gemma":[0.00047550307,0.00006033652,0.0001001992,0.00003730117,0.000019300707,0.000010818403,0.00010399904,0.99564445,0.0023879316,0.00017245971,0.0008202612,0.00016744081],"about_ca_topic_score_codex":0.0000034607044,"about_ca_topic_score_gemma":0.000051720115,"teacher_disagreement_score":0.8341573,"about_ca_system_score_codex":0.000051652107,"about_ca_system_score_gemma":0.000010141637,"threshold_uncertainty_score":0.45595118},"labels":[],"label_agreement":null},{"id":"W2139368955","doi":"10.1109/icc.2009.5199322","title":"Performance Evaluation of Interactive Data Services Under Sharing and Preemptive Scheduling Disciplines","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; University of Waterloo","funders":"","keywords":"Computer science; File transfer; UMTS frequency bands; Scheduling (production processes); Data as a service; Wireless; Computer network; File sharing; Mobile telephony; Distributed computing; Service (business); Mobile radio; Transfer (computing); World Wide Web; Operating system; The Internet","score_opus":0.03627580024653851,"score_gpt":0.3072447082998637,"score_spread":0.2709689080533252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139368955","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":[0.9136669,0.000248182,0.08428808,0.00001768329,0.000052350893,0.00013903982,0.0000027751964,0.00008087259,0.0015040992],"genre_scores_gemma":[0.9852598,0.00016530236,0.0144419065,0.000007779931,0.000041370316,0.0000033900574,0.00006163821,0.000009790467,0.00000905202],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999454,0.000007887841,0.00014287018,0.00016500808,0.00014130087,0.000088918205],"domain_scores_gemma":[0.99959296,0.000019555968,0.00004126527,0.00023444353,0.000092310904,0.000019474075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016380294,0.00008348159,0.00009116183,0.000046419005,0.00003061595,0.000016876067,0.0001391449,0.000028841698,0.000013418451],"category_scores_gemma":[0.0000067660644,0.00007811879,0.000005873794,0.00011308687,0.000010931257,0.001058385,0.00008484766,0.00005971141,0.0000010525247],"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":[0.0000072295106,0.0000061521123,0.0024219125,0.000023143348,0.000016448137,2.6251035e-8,0.00027124767,0.9784784,0.0005288172,0.00006283582,0.0000010584995,0.018182762],"study_design_scores_gemma":[0.00019618995,0.000014228243,0.02283134,0.00012266218,0.00003183842,6.7744844e-7,0.00033544493,0.9748364,0.0012338755,0.00031323193,8.6398524e-7,0.0000832113],"about_ca_topic_score_codex":0.0000025292024,"about_ca_topic_score_gemma":0.000022343014,"teacher_disagreement_score":0.07159285,"about_ca_system_score_codex":0.00003194513,"about_ca_system_score_gemma":0.000005174129,"threshold_uncertainty_score":0.3185592},"labels":[],"label_agreement":null},{"id":"W2139439080","doi":"10.1109/icc.2013.6655582","title":"Equivalent capacity analysis of LTE-Advanced systems with carrier aggregation","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"LTE Advanced; Telecommunications link; Computer science; Throughput; System-level simulation; Bandwidth (computing); Computer network; Explosive material; Term (time); Simulation; Telecommunications; Wireless","score_opus":0.008098059542623446,"score_gpt":0.18888425254464455,"score_spread":0.18078619300202112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139439080","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":[0.35985145,0.00013268543,0.6370892,0.000005168499,0.00008017377,0.00018389302,0.000009083333,0.00016586814,0.0024824622],"genre_scores_gemma":[0.9864871,0.000058124362,0.013088999,0.0000049993564,0.000016702761,0.000049695187,0.000035814966,0.00002229481,0.00023629046],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993077,0.000015863441,0.00022587739,0.00013160687,0.00016429755,0.00015466497],"domain_scores_gemma":[0.999416,0.000031749663,0.00006430903,0.000243062,0.00019275887,0.000052115123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000033311062,0.00011335683,0.00024297679,0.00013570186,0.000021290904,0.000016740032,0.000055525416,0.000047112804,0.00012114772],"category_scores_gemma":[0.00000807237,0.00009608401,0.000042569012,0.0008710127,0.00002393056,0.00028893456,0.000008952077,0.000053741478,0.0000077466075],"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":[0.0000024224232,0.000005995799,0.0016240753,0.000038141497,0.0002947776,3.1456563e-7,0.000062776526,0.9940242,0.0016772923,0.00043758468,0.000044691627,0.0017877116],"study_design_scores_gemma":[0.00016308326,0.000014472566,0.0019988245,0.000025364645,0.00017558908,7.620996e-7,0.000085752086,0.9918901,0.005423292,0.000028436052,0.0000653679,0.00012896009],"about_ca_topic_score_codex":0.000065461936,"about_ca_topic_score_gemma":0.00006884398,"teacher_disagreement_score":0.6266356,"about_ca_system_score_codex":0.00007561328,"about_ca_system_score_gemma":0.0000063743887,"threshold_uncertainty_score":0.39181924},"labels":[],"label_agreement":null},{"id":"W2140020721","doi":"10.1109/wcnc.2008.443","title":"Code Allocation Policy Optimization in HSDPA Networks Using FSMC Channel Model","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Telecommunications link; Channel (broadcasting); Markov decision process; Dynamic programming; Throughput; Network packet; Channel allocation schemes; Markov chain; Markov process; Computer network; Mathematical optimization; Wireless; Algorithm; Telecommunications; Mathematics","score_opus":0.02341453537830118,"score_gpt":0.2383286718308033,"score_spread":0.21491413645250212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140020721","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":[0.00697367,0.0001261669,0.990638,0.000039038343,0.0001026844,0.00022379695,0.0000016605076,0.0003983124,0.0014966449],"genre_scores_gemma":[0.84672505,0.0008667052,0.15190323,0.00008051912,0.0001756114,0.00001985701,0.000060862127,0.00006618473,0.00010201455],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990678,0.000016881606,0.0002900647,0.0001877841,0.00011769888,0.00031979807],"domain_scores_gemma":[0.9996409,0.000017998163,0.00004046881,0.00018385344,0.00005484077,0.00006194797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006156741,0.0001723619,0.00016113021,0.00023884967,0.00007989035,0.000013128981,0.00009473758,0.00013737312,0.000010973966],"category_scores_gemma":[0.000015978772,0.00020223374,0.000026573234,0.0007244368,0.000026164129,0.00043775432,0.000022995202,0.00013541966,0.0000028569734],"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":[0.0000054004254,0.000013716818,0.00006360427,0.000007271712,0.0000048985,0.000001648909,0.00015063882,0.99899423,0.00006900839,0.00033664194,0.00007969476,0.0002732554],"study_design_scores_gemma":[0.0003100106,0.0000047280455,0.00003718403,0.000020858433,0.0000033619287,0.000009150336,0.0000143001525,0.99917126,0.00012503257,0.0000881739,0.0000060789744,0.00020987316],"about_ca_topic_score_codex":0.00003838018,"about_ca_topic_score_gemma":0.00004434689,"teacher_disagreement_score":0.83975136,"about_ca_system_score_codex":0.00032139986,"about_ca_system_score_gemma":0.000042320542,"threshold_uncertainty_score":0.8246853},"labels":[],"label_agreement":null},{"id":"W2140102464","doi":"10.1109/wpmc.2002.1088153","title":"An adaptive downlink spread spectrum OFDM packet data system with two-dimensional radio resource allocation: performance in low-mobility cellular environments","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Retransmission; Computer science; Orthogonal frequency-division multiplexing; Throughput; Computer network; Telecommunications link; Fading; Network packet; Time diversity; Multipath propagation; Channel (broadcasting); Resource allocation; Real-time computing; Telecommunications; Wireless","score_opus":0.00901396944806337,"score_gpt":0.19139763098082188,"score_spread":0.1823836615327585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140102464","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":[0.57596403,0.0002555108,0.41995624,0.000014738469,0.000110682224,0.0006586083,0.000029105608,0.00030645577,0.002704654],"genre_scores_gemma":[0.98291713,0.000018584877,0.016487166,0.0000132419445,0.00006446464,0.000027849308,0.00035466172,0.000055071534,0.00006184188],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982758,0.00012668295,0.0003398814,0.00053281453,0.00036696572,0.00035782298],"domain_scores_gemma":[0.99857825,0.00004040925,0.0000636341,0.0011844946,0.000015290669,0.00011793078],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004391176,0.00026392477,0.00024078309,0.00007244595,0.00007358487,0.000020697289,0.0002984746,0.00008385879,0.00005796784],"category_scores_gemma":[0.0000059073923,0.0002468808,0.000015063033,0.00027691296,0.000064276894,0.0006479657,0.00004498984,0.00022246732,0.000033068416],"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":[0.000052527113,0.00007725609,0.0019461785,0.000041571155,0.000021315025,0.000008006605,0.00005059331,0.99676955,0.00036315015,0.00041800167,0.000026549342,0.00022530663],"study_design_scores_gemma":[0.0008880976,0.00007748354,0.002118772,0.000120600795,0.000014441968,0.000014225426,0.00013644263,0.9890138,0.0070468043,0.000007650287,0.00025127165,0.00031042838],"about_ca_topic_score_codex":0.000012208689,"about_ca_topic_score_gemma":0.000067491055,"teacher_disagreement_score":0.4069531,"about_ca_system_score_codex":0.00041278225,"about_ca_system_score_gemma":0.000030844527,"threshold_uncertainty_score":0.99999833},"labels":[],"label_agreement":null},{"id":"W2140264163","doi":"10.1109/vtcf.2006.266","title":"Branch-and-Bound Approach to OFDMA Radio Resource Allocation","year":2006,"lang":"en","type":"article","venue":"IEEE Vehicular Technology Conference","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Lakehead University","funders":"","keywords":"Orthogonal frequency-division multiple access; Computer science; Computational complexity theory; Orthogonal frequency-division multiplexing; Resource allocation; Frequency-division multiple access; Mathematical optimization; Upper and lower bounds; Algorithm; Channel (broadcasting); Channel allocation schemes; Wireless; Mathematics; Computer network; Telecommunications","score_opus":0.0067104505783642425,"score_gpt":0.18902863669300982,"score_spread":0.18231818611464556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140264163","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":[0.34671175,0.0006939536,0.6492739,0.00040232274,0.00008162474,0.0002609372,0.0000026252785,0.0010093462,0.0015635369],"genre_scores_gemma":[0.98376775,0.00010915763,0.015655397,0.00004281372,0.00007563432,0.000145464,0.000023071596,0.00004235508,0.00013837715],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990185,0.000017312219,0.00021727622,0.00032858033,0.00011825279,0.00030007688],"domain_scores_gemma":[0.99947727,0.000017957478,0.000038707356,0.00034530886,0.00007386567,0.00004689934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000071773706,0.00019624193,0.00021130819,0.00026783918,0.00008396696,0.00003669148,0.00022672639,0.00029660919,0.0000042238657],"category_scores_gemma":[0.0000140484735,0.00021794872,0.000022469709,0.0006039551,0.00012479312,0.000104548366,0.000033087406,0.00024518868,0.000017912804],"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":[0.000004082823,0.000024384704,0.0005300579,0.000032234053,0.000019944213,0.0000026762634,0.00004112818,0.9156429,0.050172806,0.015570045,0.0006373964,0.01732233],"study_design_scores_gemma":[0.00054645736,0.000041719035,0.0014237502,0.00009384254,0.00003729866,0.00004959467,0.000056490448,0.9019256,0.07616594,0.0053823884,0.013644094,0.00063279015],"about_ca_topic_score_codex":0.000010222228,"about_ca_topic_score_gemma":0.0000122347865,"teacher_disagreement_score":0.637056,"about_ca_system_score_codex":0.000060361013,"about_ca_system_score_gemma":0.0000138871,"threshold_uncertainty_score":0.8887691},"labels":[],"label_agreement":null},{"id":"W2140425963","doi":"10.1109/glocom.2007.990","title":"Multicell Downlink OFDM Subchannel Allocations Using Dynamic Intercell Coordination","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":26,"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; Telecommunications link; Orthogonal frequency-division multiplexing; Quality of service; Computer network; Throughput; Channel allocation schemes; Interference (communication); Channel (broadcasting); Wireless; Telecommunications","score_opus":0.008493860169159763,"score_gpt":0.24550897681719708,"score_spread":0.23701511664803732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140425963","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":[0.10758894,0.00008369799,0.88857114,0.000022638125,0.00035588295,0.0001728493,0.000001808821,0.0004703575,0.0027327],"genre_scores_gemma":[0.91168123,0.00003666589,0.087605275,0.000028610524,0.000060620638,0.0000027323704,0.000056829966,0.000044223663,0.0004838322],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992112,0.000008953911,0.0002657685,0.0001526422,0.00010063176,0.00026083397],"domain_scores_gemma":[0.9995685,0.00006624709,0.00003704662,0.00017243272,0.00009129645,0.00006444151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001244769,0.00013883997,0.000105960695,0.00015495556,0.00007416831,0.000021163902,0.00009461032,0.00009056073,0.00006174062],"category_scores_gemma":[0.000015429812,0.00015483834,0.00003321382,0.00033047106,0.000022317943,0.00025006363,0.000020593472,0.00012183674,0.000046875408],"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":[0.0000035746207,0.00001673436,0.000047303976,0.000016277367,0.000009613962,0.0000013339427,0.00012344177,0.9814877,0.013611124,0.00026386685,0.000054598637,0.0043644463],"study_design_scores_gemma":[0.00022333028,0.0000071783184,0.00019661066,0.000019682762,0.000012121759,0.0000025140941,0.00013068707,0.9938656,0.0049025947,0.00007571181,0.0003852934,0.00017864189],"about_ca_topic_score_codex":0.000012040764,"about_ca_topic_score_gemma":0.00014058952,"teacher_disagreement_score":0.8040923,"about_ca_system_score_codex":0.00024120304,"about_ca_system_score_gemma":0.0000067980186,"threshold_uncertainty_score":0.63141245},"labels":[],"label_agreement":null},{"id":"W2140429239","doi":"10.1109/wimob.2008.47","title":"Maximizing Network Stability in a Mobile WiMax/802.16 Mesh Centralized Scheduling","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Wireless mesh network; Computer network; WiMAX; Backhaul (telecommunications); Shared mesh; Switched mesh; Computer science; Mesh networking; Order One Network Protocol; Femtocell; Scheduling (production processes); IEEE 802.11s; Wireless network; Wireless; Base station; Telecommunications; Engineering","score_opus":0.015167290709224951,"score_gpt":0.21521995764724236,"score_spread":0.2000526669380174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140429239","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":[0.4815591,0.0013623873,0.5113134,0.000013438095,0.00032033664,0.00047097963,0.0000018791458,0.0008234194,0.004135083],"genre_scores_gemma":[0.88849026,0.0012679978,0.109875455,0.000036666712,0.00013247614,0.00007672953,0.000021256374,0.000056658526,0.000042510634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850607,0.00004430699,0.00041221702,0.0002746542,0.00015983009,0.000602914],"domain_scores_gemma":[0.99944043,0.000088369794,0.00003792256,0.00029702697,0.000037224527,0.00009902511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001676282,0.00021691092,0.00030367824,0.00006122181,0.00009211125,0.000016610995,0.0001322352,0.00011251813,0.0003331847],"category_scores_gemma":[0.000025375308,0.00023415044,0.000061022118,0.0005885099,0.00004601103,0.0003185437,0.0000416473,0.00024941712,0.000019521527],"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":[0.000018282373,0.00002327553,0.009303584,0.000024663128,0.000010728425,0.00000922661,0.00020070306,0.98790896,0.00020903838,0.0001996359,0.00018163864,0.0019102643],"study_design_scores_gemma":[0.00086460257,0.0000159916,0.0011351551,0.000057235793,0.0000055933606,0.000010372173,0.000121335856,0.9942813,0.0015211564,0.0003590616,0.0012667611,0.00036142804],"about_ca_topic_score_codex":0.00001760229,"about_ca_topic_score_gemma":0.0000853944,"teacher_disagreement_score":0.40693116,"about_ca_system_score_codex":0.00030337868,"about_ca_system_score_gemma":0.000021695807,"threshold_uncertainty_score":0.9548378},"labels":[],"label_agreement":null},{"id":"W2140468967","doi":"10.1109/ccece.2011.6030586","title":"Adaptive modulation for OFDM system with varying speed receiver","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"","keywords":"Computer science; Orthogonal frequency-division multiplexing; Fading; Link adaptation; Channel (broadcasting); Electronic engineering; Modulation (music); Bit error rate; Signal-to-noise ratio (imaging); Noise (video); Control theory (sociology); Telecommunications; Engineering; Acoustics; Physics","score_opus":0.024982941640490964,"score_gpt":0.18964502657325444,"score_spread":0.16466208493276346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140468967","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":[0.0046014693,0.000016460272,0.96422184,0.0000013120584,0.000107037704,0.00032760735,0.0000020909802,0.0005157357,0.03020644],"genre_scores_gemma":[0.8104847,0.0000035743697,0.18927701,0.000003702167,0.0000464736,0.00001846658,0.000009864764,0.00003319674,0.00012298794],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995888,0.0000053206477,0.00010574266,0.00010913722,0.000058484875,0.00013254049],"domain_scores_gemma":[0.9997643,0.000019729874,0.000025822465,0.00010200466,0.000059352737,0.000028740596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003204604,0.00009225613,0.00009434753,0.000039306058,0.00003525821,0.0000057953084,0.0000401068,0.00004130164,0.000020018302],"category_scores_gemma":[0.0000020459972,0.00008078113,0.00001622263,0.000107495114,0.000007981857,0.00022175445,0.000004747762,0.000035005178,0.000008575547],"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":[0.00004914622,0.0000035089117,0.000068970614,0.000031569678,0.000022490776,6.505316e-7,0.00019424793,0.9941691,0.000186498,0.0029664962,0.000052450025,0.0022548817],"study_design_scores_gemma":[0.0003156601,0.000039761755,0.0002793041,0.000047267335,0.000010091645,0.000002226012,0.00009132748,0.9969649,0.0020426936,0.000066145934,0.000018520806,0.0001221465],"about_ca_topic_score_codex":0.000007852825,"about_ca_topic_score_gemma":0.000005069362,"teacher_disagreement_score":0.8058832,"about_ca_system_score_codex":0.00007772542,"about_ca_system_score_gemma":0.000003559257,"threshold_uncertainty_score":0.3294159},"labels":[],"label_agreement":null},{"id":"W2140544378","doi":"10.1109/tit.2007.901250","title":"On the Capacity of Time-Varying Channels With Periodic Feedback","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Transmitter; Codebook; Channel capacity; Channel state information; Additive white Gaussian noise; Fading; Channel (broadcasting); Multiplexing; Binary erasure channel; Gaussian; Computer science; Control theory (sociology); Mathematics; Telecommunications; Algorithm; Wireless; Physics","score_opus":0.006388680630493221,"score_gpt":0.1829608959703504,"score_spread":0.17657221533985717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140544378","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":[0.062372312,0.0000047735293,0.93047005,0.000020459334,0.00023553967,0.00023171985,0.000014588762,0.00019551872,0.0064550294],"genre_scores_gemma":[0.9985656,0.00001856759,0.0011602358,0.00012446563,0.000019378715,0.000022670498,0.0000060205302,0.00001863043,0.000064422806],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926853,0.000026499702,0.00027999232,0.000057099474,0.00019330962,0.00017458276],"domain_scores_gemma":[0.9993136,0.0002912894,0.00007785092,0.00020872931,0.000069202986,0.000039328268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003485742,0.00013754191,0.00011241452,0.00017187941,0.00016264593,0.00002355136,0.00010044228,0.00006801261,0.00021437643],"category_scores_gemma":[0.0000057311854,0.000102255304,0.000044013654,0.0003172554,0.00008268639,0.000605394,4.0317846e-7,0.00022496146,0.00013737268],"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":[0.00012563,0.000013963457,3.7385044e-7,0.00002379724,0.000028583625,1.2897675e-7,0.0014255092,0.9853494,0.00024688855,0.0024616148,0.00003741207,0.01028666],"study_design_scores_gemma":[0.0011800792,0.00029166698,0.00004604877,0.00029456732,0.000052488824,0.00001870691,0.000977081,0.7570311,0.23661834,0.0024790117,0.00048823594,0.0005227245],"about_ca_topic_score_codex":0.0000013488973,"about_ca_topic_score_gemma":0.0000013614947,"teacher_disagreement_score":0.9361933,"about_ca_system_score_codex":0.00007590547,"about_ca_system_score_gemma":0.0000098578685,"threshold_uncertainty_score":0.41698503},"labels":[],"label_agreement":null},{"id":"W2140585387","doi":"10.1109/twc.2006.1687732","title":"Analysis of throughput and fairness with downlink scheduling in WCDMA networks","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":41,"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":"Maximum throughput scheduling; Rayleigh fading; Computer science; Scheduling (production processes); Telecommunications link; Fading; Throughput; Proportionally fair; Fairness measure; Computer network; Path loss; Code division multiple access; Round-robin scheduling; Wireless; Mathematical optimization; Telecommunications; Mathematics; Channel (broadcasting); Dynamic priority scheduling; Quality of service","score_opus":0.009700696747090055,"score_gpt":0.22665460776638613,"score_spread":0.21695391101929606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140585387","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":[0.1539482,0.00042128869,0.8448593,0.000059886417,0.000040882474,0.0001751912,0.000019481633,0.00015872727,0.0003170097],"genre_scores_gemma":[0.97658694,0.0017948402,0.021396805,0.000010079573,0.000010289061,0.00009384444,0.000054542197,0.000039457504,0.0000132089435],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990011,0.00006308842,0.00041036223,0.00019068578,0.00012526977,0.00020949829],"domain_scores_gemma":[0.9986255,0.0002605339,0.00007999876,0.0009190133,0.00007578208,0.000039167593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009505402,0.00018678844,0.0003523919,0.0004870223,0.00015408773,0.000023520617,0.000293386,0.00011601318,0.0000085828615],"category_scores_gemma":[8.689972e-7,0.00019638866,0.000067590154,0.002201608,0.00018128901,0.00022655283,0.000003844625,0.0003672902,8.7925815e-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":[0.0000142300105,0.00011576981,0.0011799106,0.000014325801,0.00018447492,5.292254e-7,0.00011923618,0.98932594,0.00015215584,0.0006824044,0.0000013172929,0.008209722],"study_design_scores_gemma":[0.00037744569,0.000018482193,0.0033613476,0.00008011505,0.00025318182,0.0000014847056,0.000091341746,0.99498916,0.0005691872,0.00004344196,0.000017564475,0.00019725173],"about_ca_topic_score_codex":0.000148674,"about_ca_topic_score_gemma":0.004072098,"teacher_disagreement_score":0.82346255,"about_ca_system_score_codex":0.00008181367,"about_ca_system_score_gemma":0.000014281815,"threshold_uncertainty_score":0.80084974},"labels":[],"label_agreement":null},{"id":"W2140796206","doi":"10.1109/glocom.1993.318360","title":"Comparison of ARQ protocols for asynchronous data transmission over Rayleigh fading channels","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Bell (Canada)","funders":"","keywords":"Selective Repeat ARQ; Hybrid automatic repeat request; Automatic repeat request; Computer science; Go-Back-N ARQ; Rayleigh fading; Error detection and correction; Asynchronous communication; Throughput; Transmission (telecommunications); Sliding window protocol; Computer network; Fading; Channel (broadcasting); Algorithm; Wireless; Telecommunications","score_opus":0.0851588303700123,"score_gpt":0.3415677386651388,"score_spread":0.25640890829512647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140796206","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":[0.00086232333,0.00018311232,0.9907139,0.000014919269,0.00006881787,0.006425267,0.000016912716,0.00023545123,0.0014792928],"genre_scores_gemma":[0.86400366,0.000042215772,0.13378048,0.000009051176,0.00012888547,0.0017334669,0.00010046531,0.00005965203,0.00014214632],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914837,0.000008884082,0.0003178486,0.00019436644,0.00011505086,0.0002154576],"domain_scores_gemma":[0.9994383,0.00006787233,0.000053491978,0.00036172377,0.000027833456,0.000050781873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000067435154,0.0001353749,0.00025302163,0.00005305345,0.000043446023,0.00001517615,0.00024385093,0.000079186895,0.00031365015],"category_scores_gemma":[0.000008055163,0.00012994897,0.000032069154,0.00014033933,0.00001499998,0.00030794958,0.000026348063,0.00007461643,0.0000047711474],"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":[0.000010128787,0.000048845635,0.00012826904,0.00018215064,0.000015606309,1.8437999e-7,0.00019072059,0.9451439,0.0021707758,0.00011312434,0.0039150207,0.048081312],"study_design_scores_gemma":[0.00057169166,0.000052617524,0.000020136747,0.00011022479,0.000009078785,5.2224067e-7,0.000013317316,0.9659068,0.018189995,0.00005078508,0.014923324,0.00015152294],"about_ca_topic_score_codex":0.0000010832744,"about_ca_topic_score_gemma":0.0000011506819,"teacher_disagreement_score":0.8631413,"about_ca_system_score_codex":0.000033695393,"about_ca_system_score_gemma":0.0000030358515,"threshold_uncertainty_score":0.5299165},"labels":[],"label_agreement":null},{"id":"W2141075051","doi":"10.1007/978-1-4020-6129-5_5","title":"Downlink Scheduling for Multiple Antenna Multi-Carrier Systems with Dirty Paper Coding Via Genetic Algorithms","year":2007,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Alberta","funders":"","keywords":"Subcarrier; Computer science; MIMO; Orthogonal frequency-division multiplexing; Scheduling (production processes); Fading; Telecommunications link; Algorithm; Broadband; Coding (social sciences); Electronic engineering; Distributed computing; Computer network; Mathematical optimization; Decoding methods; Engineering; Mathematics; Telecommunications","score_opus":0.02305252434394721,"score_gpt":0.22763520730472853,"score_spread":0.2045826829607813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141075051","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":[0.000017470982,0.0031623023,0.9840291,0.000003861377,0.00089847605,0.0016004846,0.000107547465,0.0008907881,0.0092899585],"genre_scores_gemma":[0.020983117,0.0015755022,0.92084426,0.000073201176,0.0014627499,0.0002209349,0.0005035434,0.00092173606,0.05341494],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976848,0.000007517204,0.0007081033,0.000625161,0.00032190242,0.00065254775],"domain_scores_gemma":[0.998614,0.00020725503,0.00019290442,0.00050198747,0.00028305326,0.00020079898],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014840427,0.00076568266,0.00072961475,0.00022934402,0.00015503401,0.00007866646,0.00021983989,0.00065436226,0.0000636974],"category_scores_gemma":[0.000016582107,0.0006866936,0.00014503849,0.00007765703,0.00007279714,0.00021857602,0.000044373905,0.0004891011,0.000024030127],"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":[0.000033081305,0.0000085164265,0.00003375044,0.00036307494,0.00023388656,0.000021686341,0.000043401524,0.9891762,0.00033969936,0.0006746983,0.000033234548,0.009038747],"study_design_scores_gemma":[0.0012486917,0.000049640796,0.000012767362,0.0006673181,0.00011209128,0.000029956267,0.000024867908,0.98663515,0.000062589184,0.00003766145,0.010154172,0.00096507836],"about_ca_topic_score_codex":0.000012783626,"about_ca_topic_score_gemma":0.00008279156,"teacher_disagreement_score":0.063184835,"about_ca_system_score_codex":0.0002593297,"about_ca_system_score_gemma":0.000026266749,"threshold_uncertainty_score":0.99955845},"labels":[],"label_agreement":null},{"id":"W2141473525","doi":"10.1109/tbc.2007.903611","title":"Queuing Models for Dimensioning Interactive and Streaming Services in High-Speed Downlink Packet Access Networks","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Broadcasting","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Université du Québec à Montréal","funders":"","keywords":"Computer science; Computer network; Dimensioning; Network packet; Queueing theory; Quality of service; Real-time computing; Queuing delay; Packet loss; Engineering","score_opus":0.013160661705341263,"score_gpt":0.2530687381643283,"score_spread":0.239908076458987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141473525","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":[0.27183142,0.00010604967,0.72703624,0.000007371673,0.00040516458,0.00028287727,0.000007552282,0.0002309334,0.0000923976],"genre_scores_gemma":[0.9779429,0.00011889434,0.021661114,0.00003416521,0.00011094562,0.000027419313,0.000014259497,0.00007850259,0.000011827736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863636,0.00002155986,0.00042061976,0.00033015411,0.0001168562,0.00047447314],"domain_scores_gemma":[0.99895626,0.0006572637,0.000089995905,0.00014189366,0.00006747495,0.00008711593],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023957388,0.00025987852,0.00026006263,0.00030039807,0.00021398584,0.00009947456,0.00011223516,0.0001417732,0.000004287675],"category_scores_gemma":[0.000004958614,0.00029781545,0.000046244455,0.00042367564,0.000023077635,0.0010846414,0.0000039299257,0.00041204743,6.888705e-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":[0.000084790976,0.000020675547,0.00006189637,0.00006609447,0.000026883112,0.0000045566608,0.00058826496,0.8967413,0.00079496234,0.000013024431,0.0000011593937,0.10159641],"study_design_scores_gemma":[0.0007127391,0.000030597617,0.00016450942,0.00059428776,0.000023685892,0.000007556429,0.00037410072,0.9931151,0.0045507075,0.00014724692,0.0000049028695,0.00027455483],"about_ca_topic_score_codex":0.00006588578,"about_ca_topic_score_gemma":0.00040581517,"teacher_disagreement_score":0.70611143,"about_ca_system_score_codex":0.00017649494,"about_ca_system_score_gemma":0.000006706541,"threshold_uncertainty_score":0.99994737},"labels":[],"label_agreement":null},{"id":"W2141684199","doi":"10.1109/49.957316","title":"Link adaptation and power control for streaming services in EGPRS wireless networks","year":2001,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Victoria","funders":"","keywords":"Computer science; Throughput; Network packet; Power control; Error detection and correction; Packet radio; Frame (networking); Quality of service; Real-time computing; Computer network; Bit error rate; Link adaptation; Word error rate; Wireless; Power (physics); Algorithm; Fading; Telecommunications; Speech recognition","score_opus":0.014740480010574243,"score_gpt":0.250597028134996,"score_spread":0.23585654812442178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141684199","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":[0.34345913,0.0022624196,0.6520658,0.00070050044,0.00028150628,0.00061389076,0.000010351468,0.00017079487,0.00043556077],"genre_scores_gemma":[0.98577434,0.0068091736,0.0070878323,0.00008631485,0.00010038646,0.00005096417,0.000038119546,0.000045757162,0.000007113391],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989005,0.000122031364,0.00046147584,0.000125122,0.00010438181,0.0002864897],"domain_scores_gemma":[0.9986299,0.0006194322,0.00013225552,0.00035810855,0.00018514945,0.000075140575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022823918,0.00016521353,0.00022286414,0.00028746956,0.00017655767,0.00007201084,0.00032455387,0.0001297465,0.0000036627048],"category_scores_gemma":[0.00003140121,0.00018173608,0.000028636987,0.0007125983,0.000031410622,0.00032564191,0.000015865226,0.00062675704,8.0241097e-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":[0.000054721917,0.00004808263,0.0035872634,0.000007701961,0.000022777356,0.0000025558768,0.0004267837,0.9730287,0.0001377559,0.00017820527,0.000017672297,0.02248775],"study_design_scores_gemma":[0.0013253032,0.000050042774,0.011101495,0.0002871509,0.000012153341,0.00003122201,0.00021220211,0.98608047,0.000015311001,0.00032418335,0.00039143857,0.00016900263],"about_ca_topic_score_codex":0.000011120016,"about_ca_topic_score_gemma":0.0010520449,"teacher_disagreement_score":0.644978,"about_ca_system_score_codex":0.00019450652,"about_ca_system_score_gemma":0.000025806483,"threshold_uncertainty_score":0.74109817},"labels":[],"label_agreement":null},{"id":"W2141946107","doi":"10.1109/icc.2008.649","title":"Performance Analysis of Weighted Proportional Fairness Scheduling in IEEE 802.16 Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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":"Computer science; Computer network; Scheduling (production processes); IEEE 802; Maximum throughput scheduling; Max-min fairness; Spectral efficiency; Quality of service; Resource allocation; Dynamic priority scheduling; Round-robin scheduling; Mathematical optimization","score_opus":0.008884240454516048,"score_gpt":0.20069032495414935,"score_spread":0.1918060844996333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141946107","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":[0.53252244,0.00006706949,0.46652886,0.0000025265208,0.0000646998,0.000057735502,6.590049e-7,0.00008706003,0.00066893955],"genre_scores_gemma":[0.98131365,0.0005301516,0.01793292,0.0000070604096,0.000051599833,0.000015921207,0.000059573245,0.000020644358,0.00006849179],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911296,0.00001064415,0.00037074107,0.0001430457,0.00015720267,0.0002054002],"domain_scores_gemma":[0.999662,0.00002772764,0.000057606107,0.00014946608,0.00006738858,0.00003580884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000074183525,0.00011977744,0.00026184265,0.00032305304,0.00003811203,0.0000033348895,0.00008533819,0.00008196253,0.0001052204],"category_scores_gemma":[0.000003953016,0.00011878264,0.000058744743,0.0018527497,0.000038713777,0.00022525372,0.0000106455245,0.00012854201,0.0000025107245],"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":[0.00000779023,0.00001682954,0.07695011,0.000013779838,0.00009744308,0.0000019105642,0.000037360067,0.92143726,0.000058811245,0.00006647946,0.000018558985,0.0012936931],"study_design_scores_gemma":[0.00017416035,0.0000071240606,0.03256714,0.000019433513,0.00004114062,0.0000018310201,0.000011096283,0.96637434,0.00065500784,0.0000066137127,0.000009896827,0.00013219626],"about_ca_topic_score_codex":0.000007438087,"about_ca_topic_score_gemma":0.00004285991,"teacher_disagreement_score":0.44879118,"about_ca_system_score_codex":0.00008905285,"about_ca_system_score_gemma":0.0000140152015,"threshold_uncertainty_score":0.48438156},"labels":[],"label_agreement":null},{"id":"W2142000303","doi":"10.1109/twc.2010.07.091551","title":"Joint Routing and Scheduling in WiMAX-Based Mesh Networks","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; WiMAX; Scheduling (production processes); Computer network; Wireless mesh network; Telecommunications link; Schedule; Distributed computing; Mathematical optimization; Wireless network; Wireless; Mathematics; Telecommunications","score_opus":0.01632068281877121,"score_gpt":0.23835122505072087,"score_spread":0.22203054223194965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142000303","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":[0.10741605,0.000100939564,0.8908802,0.0002452781,0.00031863636,0.00025493404,0.000007787048,0.0004341834,0.00034199402],"genre_scores_gemma":[0.94855344,0.00075011625,0.050357718,0.000060955765,0.0000281661,0.00015389045,0.00001631815,0.00006857113,0.000010847771],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989066,0.00006495055,0.00039770626,0.0002133842,0.00011317685,0.00030414175],"domain_scores_gemma":[0.9984361,0.00028522007,0.000057987174,0.0010666327,0.000055497174,0.00009858875],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019923697,0.00021626306,0.00022619129,0.0002417239,0.00033775662,0.00005702637,0.00034442564,0.00018182665,0.000019406627],"category_scores_gemma":[0.000006832442,0.00026150508,0.000056982248,0.000556438,0.00015787395,0.00024058636,0.000005020353,0.0012367538,0.000006631704],"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":[0.0000054215666,0.00007348512,0.0000955446,0.000011161639,0.000013139083,6.2004824e-7,0.00011480835,0.9682477,0.0034271234,0.0008202033,0.0000034660454,0.027187295],"study_design_scores_gemma":[0.000454463,0.000012190514,0.00030594104,0.00010033011,0.000015704782,0.0000038252006,0.00005859769,0.9955984,0.0030926536,0.00005056982,0.000058303027,0.00024905495],"about_ca_topic_score_codex":0.000025779076,"about_ca_topic_score_gemma":0.0010180918,"teacher_disagreement_score":0.84113735,"about_ca_system_score_codex":0.000076722405,"about_ca_system_score_gemma":0.000026758069,"threshold_uncertainty_score":0.9999837},"labels":[],"label_agreement":null},{"id":"W2142007865","doi":"10.1109/wcnc.2008.362","title":"Virtual Partitioning for Connection Admission Control in Cellular/WLAN Interworking","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"University of British Columbia","funders":"","keywords":"Handover; Computer network; Blocking (statistics); Computer science; Admission control; Quality of service; Call blocking; Call Admission Control; Service (business); Wireless; Wi-Fi; Wireless network; Shared resource; Local area network; Cellular network; Wireless lan; Telecommunications","score_opus":0.011678944450630311,"score_gpt":0.20728366827642236,"score_spread":0.19560472382579205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142007865","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":[0.09173756,0.000081522216,0.9068255,0.000023494424,0.0002981355,0.00021803264,0.0000011948396,0.0002912834,0.000523306],"genre_scores_gemma":[0.9940817,0.0000478271,0.0054355334,0.00004897057,0.00014676471,0.00006583339,0.000031146927,0.000030129904,0.000112092115],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994164,0.000013666544,0.0002007968,0.00012210809,0.000058614383,0.00018841962],"domain_scores_gemma":[0.99974424,0.000089956,0.000024113828,0.00007434022,0.00002384509,0.000043510205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006600318,0.000095911564,0.00012176611,0.000080924656,0.00007490209,0.000009687123,0.000039283794,0.0000655179,0.000045229794],"category_scores_gemma":[0.000028271223,0.00010256278,0.00003085357,0.00013435993,0.0000118642165,0.00016861418,0.000005847278,0.00008640663,0.000006241567],"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":[0.000027054954,0.000009504579,0.0014593643,0.0000074995974,0.000005747901,0.0000026316072,0.000120993354,0.988801,0.0065214834,0.00039202874,0.00021622614,0.002436463],"study_design_scores_gemma":[0.0009264842,0.000038814524,0.00023985625,0.000054392796,0.0000032150174,0.000004370346,0.00006512102,0.99202716,0.005291577,0.000119239594,0.0011003516,0.00012939703],"about_ca_topic_score_codex":0.0000025118015,"about_ca_topic_score_gemma":0.000023132006,"teacher_disagreement_score":0.90234417,"about_ca_system_score_codex":0.00008227665,"about_ca_system_score_gemma":0.0000066716025,"threshold_uncertainty_score":0.41823885},"labels":[],"label_agreement":null},{"id":"W2142067607","doi":"10.1109/twc.2006.1638666","title":"Resource allocation with service differentiation for wireless video transmission","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Computer network; Quality of service; Provisioning; Wireless network; Wireless; Protocol stack; Network packet; Differentiated services; Application layer; Scheduling (production processes); Resource allocation; Service layer; Distributed computing; Telecommunications; Wireless sensor network","score_opus":0.012173007980442477,"score_gpt":0.22334832157466541,"score_spread":0.21117531359422292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142067607","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":[0.022067538,0.00014243323,0.9739799,0.0010780157,0.000116448486,0.0009630783,0.00006874403,0.00096796604,0.00061590347],"genre_scores_gemma":[0.9712783,0.00043371003,0.026324218,0.00009556666,0.00005922007,0.000985209,0.00048183306,0.00015288957,0.00018904576],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842626,0.00009308065,0.00050533575,0.00033698208,0.00027001387,0.0003683456],"domain_scores_gemma":[0.9978698,0.0003606688,0.000119549564,0.0013020299,0.00025052624,0.000097446056],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011431318,0.00035335604,0.0002894973,0.0002454506,0.0006956613,0.00007645804,0.0005871283,0.00019715805,0.000018486022],"category_scores_gemma":[9.62246e-7,0.00036579143,0.00010302438,0.0008395175,0.00009037363,0.00040636054,0.0000029229316,0.00037487497,0.0000150272235],"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":[0.0000840571,0.0002496772,0.00000869861,0.00008988557,0.000052983007,1.8960004e-7,0.00019221919,0.93647456,0.0097549725,0.0011920132,0.00021264619,0.051688116],"study_design_scores_gemma":[0.0011748138,0.00007148278,0.00014194546,0.00020377847,0.00011666022,0.0000052423143,0.00008921976,0.9592844,0.032931134,0.00021195502,0.0053053442,0.00046396855],"about_ca_topic_score_codex":0.000052420677,"about_ca_topic_score_gemma":0.00071390026,"teacher_disagreement_score":0.94921076,"about_ca_system_score_codex":0.00022184673,"about_ca_system_score_gemma":0.00003765,"threshold_uncertainty_score":0.9998794},"labels":[],"label_agreement":null},{"id":"W2142145488","doi":"10.1109/icc.2006.255418","title":"Optimal Packet Scheduling using Adaptive M-QAM and Orthogonal STBC in MIMO Nakagami-m Fading Channels","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":6,"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":"Nakagami distribution; Computer science; Fading; Space–time block code; Channel state information; Network packet; Algorithm; Hybrid automatic repeat request; Automatic repeat request; Computer network; Channel (broadcasting); Telecommunications link; Wireless; Telecommunications","score_opus":0.07366207296990472,"score_gpt":0.31033938229154173,"score_spread":0.236677309321637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142145488","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":[0.5843911,0.00048717056,0.39772746,0.0005833091,0.0006197199,0.00037001213,0.00011868059,0.0002654963,0.0154370265],"genre_scores_gemma":[0.93096215,0.00043955384,0.0681386,0.00003140197,0.00013001909,0.000046178495,0.00014359089,0.000036292673,0.000072235656],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998863,0.00006122898,0.000389013,0.00022746793,0.00021156251,0.00024776236],"domain_scores_gemma":[0.99911124,0.00014768545,0.00009925983,0.0004078332,0.00018272738,0.000051257106],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001360716,0.0002091069,0.00018409925,0.00029013943,0.00014331017,0.00009940433,0.00049429364,0.000101685706,0.00002861827],"category_scores_gemma":[0.000020534828,0.00025344169,0.000037745176,0.00025345126,0.00012056211,0.00038401945,0.00010022536,0.00038258787,0.000010279966],"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":[0.000013407329,0.000051448347,0.0006170599,0.000004252729,0.000021016442,0.0000022134257,0.00010320656,0.9600203,0.0017403809,0.036380336,0.00003976273,0.0010065985],"study_design_scores_gemma":[0.0003596649,0.000016627338,0.00078675296,0.0001884558,0.000007558412,0.000008347291,0.0001399703,0.9962224,0.00043539138,0.001393025,0.00019805657,0.00024378646],"about_ca_topic_score_codex":0.00008270777,"about_ca_topic_score_gemma":0.0003195198,"teacher_disagreement_score":0.346571,"about_ca_system_score_codex":0.00021986013,"about_ca_system_score_gemma":0.00004231702,"threshold_uncertainty_score":0.9999918},"labels":[],"label_agreement":null},{"id":"W2142352495","doi":"10.1109/t-wc.2009.070676","title":"Exploiting platform diversity for GoS improvement for users with different High Altitude Platform availability","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":30,"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":"York University","keywords":"Effects of high altitude on humans; Computer science; Diversity (politics); Telecommunications; Geography; Meteorology","score_opus":0.029922680765233738,"score_gpt":0.24366024880825532,"score_spread":0.21373756804302158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142352495","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":[0.21042262,0.000025413307,0.78689045,0.00021277514,0.00015991282,0.0015294665,0.0002009169,0.00048940425,0.00006907056],"genre_scores_gemma":[0.96204966,0.00041274956,0.03625547,0.000087962086,0.00003288395,0.0009099231,0.00014588125,0.000058810012,0.000046656474],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986309,0.000013781954,0.0004162226,0.0003102694,0.00019998656,0.00042888767],"domain_scores_gemma":[0.9979043,0.00043514877,0.00011079867,0.0012529257,0.00016858723,0.00012822413],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00012220914,0.00032698427,0.0003277784,0.00013712632,0.0013114191,0.00005090489,0.00064078195,0.00013068154,0.000012254657],"category_scores_gemma":[0.000004046983,0.00032475006,0.00014756144,0.0002393614,0.0000993285,0.0005061557,0.000010427335,0.0003269702,0.0000027420474],"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":[0.00021348156,0.00047381158,0.00005223036,0.00008523304,0.00015347224,1.6470631e-7,0.0005826585,0.9225171,0.0012375815,0.0015641046,0.00006866821,0.07305148],"study_design_scores_gemma":[0.00377093,0.0008769526,0.00084887346,0.00019387745,0.00023989638,0.0000023714142,0.0005792922,0.9538504,0.036980536,0.0014477639,0.00035332513,0.0008558135],"about_ca_topic_score_codex":0.000026575468,"about_ca_topic_score_gemma":0.00057673873,"teacher_disagreement_score":0.751627,"about_ca_system_score_codex":0.0004949824,"about_ca_system_score_gemma":0.000024673254,"threshold_uncertainty_score":0.99998873},"labels":[],"label_agreement":null},{"id":"W2142743095","doi":"10.1109/glocom.2006.711","title":"WLC17-3: Performance of IEEE802.16 Random Access Protocol - Transient Queueing Analysis","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Retransmission; Random access; Exponential backoff; Queueing theory; Orthogonal frequency-division multiple access; Code division multiple access; Queue; Real-time computing; Orthogonal frequency-division multiplexing; Throughput; Network packet; Wireless; Telecommunications; Channel (broadcasting)","score_opus":0.005882493184886254,"score_gpt":0.23656939638632618,"score_spread":0.23068690320143992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142743095","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":[0.24970633,0.00005904614,0.7301901,0.000013354841,0.00011544234,0.012585884,0.000011574302,0.00032767878,0.006990615],"genre_scores_gemma":[0.9892152,0.000015813192,0.0034845367,0.000008581081,0.00008524339,0.0070609646,0.000034942004,0.000029109942,0.000065604494],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989749,0.000021511787,0.00040791993,0.00017027966,0.00017752398,0.00024782927],"domain_scores_gemma":[0.9995502,0.000029453362,0.00008498574,0.00024346948,0.0000547283,0.00003715934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009516657,0.00016454984,0.00033256842,0.00017419794,0.000050756138,0.000025637093,0.00018420476,0.000066647175,0.00011643736],"category_scores_gemma":[0.000003262818,0.00016440434,0.00012183026,0.00097151235,0.000027883922,0.00035122197,0.00001975125,0.000092938724,0.0000050336535],"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":[0.000056971963,0.000024633267,0.009919379,0.00012104629,0.00008525481,8.912787e-7,0.000024857645,0.98571974,0.00023439094,0.000041645613,0.00031437047,0.0034567968],"study_design_scores_gemma":[0.0015333918,0.0000212229,0.0136277145,0.000049132093,0.000118139,9.623789e-7,0.0000051047873,0.9738042,0.0076654796,0.000035595767,0.0029145074,0.0002245593],"about_ca_topic_score_codex":0.000091488764,"about_ca_topic_score_gemma":0.00018510214,"teacher_disagreement_score":0.73950887,"about_ca_system_score_codex":0.000097605,"about_ca_system_score_gemma":0.000011158506,"threshold_uncertainty_score":0.6704214},"labels":[],"label_agreement":null},{"id":"W2142828909","doi":"10.1109/vetecs.2009.5073378","title":"An Asymptotically Fair Subcarrier Allocation Algorithm in OFDM Systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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":"Subcarrier; Computer science; Orthogonal frequency-division multiplexing; Max-min fairness; Fairness measure; Greedy algorithm; Throughput; Algorithm; Mathematical optimization; Channel allocation schemes; Index (typography); Resource allocation; Channel (broadcasting); Computer network; Mathematics; Wireless; Telecommunications","score_opus":0.0035442914875594036,"score_gpt":0.20975621636370342,"score_spread":0.206211924876144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142828909","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":[0.010143809,0.00012482825,0.9846717,0.00003704123,0.00018857089,0.00018630661,0.0000012163457,0.0005219719,0.0041245716],"genre_scores_gemma":[0.9538959,0.00005230374,0.045735434,0.000047039248,0.000109111556,0.000011859969,0.000039149218,0.000022886197,0.00008631907],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992713,0.000023134364,0.00022508438,0.0001502648,0.00012023921,0.0002100068],"domain_scores_gemma":[0.9996569,0.000015800553,0.000015680685,0.00019749592,0.000043067907,0.00007102001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009598252,0.00011514819,0.00012695318,0.000084255684,0.000018750283,0.000034744364,0.00009237443,0.00009337881,0.00001618526],"category_scores_gemma":[0.0000065396584,0.000120277626,0.000014291094,0.0002716534,0.000008591668,0.000356836,0.0000035051687,0.00009988096,0.000016718188],"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":[0.0000015379826,0.000016829908,0.00010495387,0.000005160744,0.0000026240975,0.0000023288305,0.000044832315,0.9598574,0.00055677287,0.0032443856,0.00007577472,0.03608737],"study_design_scores_gemma":[0.00017874902,0.00003796012,0.0024650178,0.00001778141,0.0000023432917,0.0000026596201,0.00004679873,0.9964071,0.00029941002,0.00021694007,0.00017595621,0.00014931952],"about_ca_topic_score_codex":0.0000068181143,"about_ca_topic_score_gemma":0.000011722421,"teacher_disagreement_score":0.9437521,"about_ca_system_score_codex":0.000098558485,"about_ca_system_score_gemma":0.0000082747565,"threshold_uncertainty_score":0.49047792},"labels":[],"label_agreement":null},{"id":"W2143082264","doi":"10.1109/glocom.2006.224","title":"MMC05-4: On the Optimality of Threshold Scheduling Policies for Video Transmission in Markovian Fading Wireless Channels with Channel-Aware ARQ","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Fading; Rayleigh fading; Scheduling (production processes); Network packet; Markov decision process; Computer network; Markov process; Hybrid automatic repeat request; Wireless; Channel (broadcasting); Mathematical optimization; Automatic repeat request; Transmission (telecommunications); Real-time computing; Mathematics; Telecommunications","score_opus":0.01158624219229102,"score_gpt":0.22072065439865168,"score_spread":0.20913441220636067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143082264","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":[0.41111186,0.00020653753,0.5868736,0.0002990506,0.00012131421,0.0006019314,0.000024304816,0.00015390865,0.00060750183],"genre_scores_gemma":[0.99572986,0.000045714947,0.003815899,0.00005482379,0.00014185344,0.00009602778,0.000032619173,0.00006078778,0.00002240742],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882966,0.000023344619,0.0003396839,0.00022973276,0.00017787374,0.00039969827],"domain_scores_gemma":[0.9994344,0.00014102679,0.00008515676,0.00024253842,0.00005319086,0.000043664193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020002245,0.00024079204,0.00029304,0.000121256875,0.000103145845,0.000029625422,0.0001992262,0.000092392576,0.000009470391],"category_scores_gemma":[0.0000069260695,0.00018568442,0.00006644424,0.0003953719,0.00005019273,0.0001623627,0.000017202217,0.00017627161,9.796605e-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":[0.00007521481,0.000033462267,0.00032157922,0.00011354377,0.000014591413,0.0000018366061,0.00021468541,0.99647987,0.00046852752,0.0013084899,0.000085772495,0.00088242977],"study_design_scores_gemma":[0.00061567815,0.00006025328,0.00053506537,0.00045738873,0.000012106063,0.0000023817477,0.00018122634,0.9864803,0.010448918,0.0008171741,0.00014868646,0.00024080888],"about_ca_topic_score_codex":0.00007539246,"about_ca_topic_score_gemma":0.00009817379,"teacher_disagreement_score":0.58461803,"about_ca_system_score_codex":0.00010882641,"about_ca_system_score_gemma":0.000015573933,"threshold_uncertainty_score":0.7571991},"labels":[],"label_agreement":null},{"id":"W2143675089","doi":"10.1109/glocom.2007.657","title":"Optimal Scheduling for Wireless Links Under Per-User Maximum Delay QoS Constraints","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer science; Quality of service; Scheduling (production processes); Network packet; Piecewise; Mathematical optimization; Wireless; Iterative method; Computer network; Real-time computing; Control theory (sociology); Algorithm; Mathematics; Control (management)","score_opus":0.011188845725114934,"score_gpt":0.24372434227545803,"score_spread":0.23253549655034308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143675089","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":[0.08535641,0.00011877786,0.9097819,0.00004423922,0.0005731069,0.00036032705,0.000005378757,0.0006277976,0.0031320998],"genre_scores_gemma":[0.61205184,0.000034262135,0.38716036,0.000107120286,0.00029859107,0.000020121342,0.000029436951,0.000074769014,0.00022352084],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987271,0.000006713978,0.00033835915,0.00024635985,0.00013200917,0.0005494518],"domain_scores_gemma":[0.99939877,0.00015968262,0.000038956827,0.00019785791,0.00007364228,0.00013110158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017427489,0.00022864275,0.00020479731,0.000097762866,0.00009679008,0.000038335867,0.00013647278,0.00031883747,0.0001646519],"category_scores_gemma":[0.000009953847,0.0002409658,0.00007532581,0.00016267633,0.00007618826,0.00022061454,0.000025518939,0.0003078921,0.000029362602],"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":[0.000021853755,0.000014731746,0.00009339679,0.000030336352,0.000038862585,0.0000036385215,0.000057965906,0.9776941,0.0019004646,0.0038768495,0.00011797842,0.016149856],"study_design_scores_gemma":[0.00079589733,0.000027446195,0.000078723504,0.000035561683,0.00001946821,0.000016830827,0.0003612185,0.9890083,0.0077505806,0.00022770863,0.0012891353,0.00038914068],"about_ca_topic_score_codex":5.9997365e-7,"about_ca_topic_score_gemma":0.000007678477,"teacher_disagreement_score":0.52669543,"about_ca_system_score_codex":0.000080604645,"about_ca_system_score_gemma":0.000017510043,"threshold_uncertainty_score":0.98263},"labels":[],"label_agreement":null},{"id":"W2143968970","doi":"10.1109/vtcfall.2013.6692082","title":"Adaptive Modulation for MIMO Systems with Decision-Feedback Equalizer","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"MIMO; Rayleigh fading; Fading; Computer science; Control theory (sociology); Transmitter; Spectral efficiency; Adaptive equalizer; Multipath propagation; Interference (communication); Signal-to-noise ratio (imaging); Algorithm; Equalization (audio); Channel (broadcasting); Telecommunications","score_opus":0.011308753507106396,"score_gpt":0.20933330985643084,"score_spread":0.19802455634932445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143968970","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":[0.007650374,0.00010553477,0.9882591,0.000011151835,0.00019907992,0.0008073133,0.0000031400816,0.00031997374,0.0026443556],"genre_scores_gemma":[0.7891651,0.0000133188505,0.20999886,0.000011034335,0.000079656216,0.00024469796,0.00001803667,0.000043916752,0.00042538974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938667,0.0000069323796,0.0001752498,0.00013657908,0.00011366108,0.00018090657],"domain_scores_gemma":[0.9994879,0.00014162413,0.000029786846,0.0001521664,0.00013828691,0.000050244726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003838016,0.000121424964,0.00012917796,0.000046919016,0.000039042014,0.000041423,0.000057235276,0.000062199535,0.000064833606],"category_scores_gemma":[0.000009333003,0.00009593855,0.00002068809,0.00013916746,0.000010985776,0.00037689408,0.000007575366,0.000040555205,0.000071783266],"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":[0.000013541556,0.0000041703142,0.00003714382,0.000014249426,0.00001770921,1.0782867e-7,0.000031595966,0.9846195,0.000077381344,0.0031777204,0.0022046936,0.009802176],"study_design_scores_gemma":[0.00039589248,0.000039563656,0.00027007458,0.0000466008,0.0000056466024,0.0000013394514,0.00008943798,0.9975352,0.000089776266,0.0009783637,0.00039468287,0.00015340759],"about_ca_topic_score_codex":0.000015215062,"about_ca_topic_score_gemma":0.000009343719,"teacher_disagreement_score":0.7815147,"about_ca_system_score_codex":0.000060276816,"about_ca_system_score_gemma":0.000006149735,"threshold_uncertainty_score":0.39122605},"labels":[],"label_agreement":null},{"id":"W2143979055","doi":"10.1109/glocom.2009.5426180","title":"Dynamic Power Allocation over Block-Fading Channels with Delay Constraint","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"University of Alberta","funders":"","keywords":"Computer science; Fading; Channel (broadcasting); Mathematical optimization; Quality of service; Transmission (telecommunications); Power (physics); Constraint (computer-aided design); Transmitter; Dynamic demand; Channel state information; Dynamic programming; Power control; Algorithm; Real-time computing; Wireless; Computer network; Mathematics; Telecommunications","score_opus":0.0033562302725117107,"score_gpt":0.2000414567102467,"score_spread":0.19668522643773498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143979055","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":[0.10958641,0.00008371252,0.87972265,0.00007925495,0.00013218123,0.00017297393,0.0000010478948,0.0005742785,0.009647481],"genre_scores_gemma":[0.97727567,0.00003862108,0.02234277,0.00011025826,0.000022225366,0.0000064238666,0.000015395372,0.000026682743,0.00016194832],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999402,0.000005566301,0.00013526235,0.00013971592,0.00010404338,0.00021343755],"domain_scores_gemma":[0.99973583,0.000015879203,0.000023035733,0.0001382549,0.000035122273,0.000051876876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037019217,0.00013687235,0.000105574145,0.00006270202,0.00003716121,0.000024266119,0.000057996866,0.00005940632,0.00008933045],"category_scores_gemma":[0.0000034445768,0.00012412434,0.000018057639,0.00018592946,0.00001906362,0.00019593256,0.000004597873,0.00009158948,0.000013815642],"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":[0.000004731754,0.000008402623,0.000019572342,0.0000029727846,0.000012566902,0.000004051344,0.000095291856,0.9941853,0.0013456091,0.0011427614,0.00010948277,0.00306921],"study_design_scores_gemma":[0.00028087295,0.000050183477,0.00040467488,0.000035176254,0.0000072887765,0.000022465365,0.000033337034,0.99778324,0.00081280334,0.00016185766,0.00020303532,0.0002050626],"about_ca_topic_score_codex":8.5683007e-7,"about_ca_topic_score_gemma":0.0000064072474,"teacher_disagreement_score":0.86768925,"about_ca_system_score_codex":0.00009134271,"about_ca_system_score_gemma":0.00000770134,"threshold_uncertainty_score":0.5061644},"labels":[],"label_agreement":null},{"id":"W2144002806","doi":"10.1109/icip.2002.1038933","title":"A scheduling scheme for multiplexing of VBR sources in digital TV systems","year":2003,"lang":"en","type":"article","venue":"Proceedings - International Conference on Image Processing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Statistical time division multiplexing; Computer science; Multiplexing; Jitter; Variable bitrate; Network packet; Scheduling (production processes); Computer network; Real-time computing; Channel (broadcasting); Transmission (telecommunications); Bit rate; Telecommunications; Engineering","score_opus":0.025640250336481006,"score_gpt":0.270910649153481,"score_spread":0.245270398817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144002806","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":[0.30347362,0.00049875147,0.6690156,0.00005041385,0.0003844219,0.000597341,0.000029590135,0.0003304523,0.025619814],"genre_scores_gemma":[0.92975676,0.000037661215,0.069882184,0.000008180675,0.00008279551,0.00011273317,0.000019089024,0.000050181854,0.000050386836],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868816,0.0000025499908,0.00046868648,0.00028515933,0.00027162782,0.00028381837],"domain_scores_gemma":[0.99897236,0.000047454498,0.00019777313,0.00005026582,0.00068115327,0.000050968243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018017122,0.00021516629,0.00024059435,0.0002797301,0.00006156786,0.00038645978,0.00022470724,0.00008401075,0.00001233149],"category_scores_gemma":[0.00043935198,0.00023613528,0.000044428445,0.00026074908,0.000056543147,0.0013655192,0.000023149298,0.00019088261,0.0000027136875],"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":[0.0002014758,0.00021862875,0.015059564,0.0024513681,0.000114340284,0.0000037530835,0.0028337643,0.7168076,0.13098617,0.113448605,0.000054445813,0.017820261],"study_design_scores_gemma":[0.00062351,0.000021775693,0.00003615587,0.0010006593,0.000004121542,0.0000059162394,0.0012400311,0.9831107,0.011987955,0.0015927857,0.00013349325,0.00024289562],"about_ca_topic_score_codex":0.0000017979371,"about_ca_topic_score_gemma":5.5863507e-7,"teacher_disagreement_score":0.62628317,"about_ca_system_score_codex":0.00012615055,"about_ca_system_score_gemma":0.00004507529,"threshold_uncertainty_score":0.9629317},"labels":[],"label_agreement":null},{"id":"W2144371592","doi":"10.1145/1631272.1631329","title":"On statistical multiplexing of variable-bit-rate video streams in mobile systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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":"Computer science; Variable bitrate; Testbed; Real-time computing; Broadcasting (networking); Bandwidth (computing); Energy consumption; Base station; Computer network; Algorithm; Bit rate","score_opus":0.005124390758527084,"score_gpt":0.21707091885817822,"score_spread":0.21194652809965114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144371592","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":[0.033426575,0.00012276886,0.9602587,0.0000024043495,0.00014795097,0.0002763788,0.000018199575,0.000191565,0.0055554355],"genre_scores_gemma":[0.9681508,0.000043557735,0.031632826,0.000013992471,0.000029311355,0.00002174882,0.000032141666,0.000019707242,0.000055917877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992493,0.000027487597,0.00029703727,0.00013341795,0.0000950131,0.00019778477],"domain_scores_gemma":[0.9995275,0.0002255597,0.000029617382,0.00015103184,0.000024558276,0.000041742926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000103034945,0.00011546672,0.00019717455,0.00007883348,0.0000125666975,0.0000118372955,0.00006141763,0.00006419475,0.00004304557],"category_scores_gemma":[0.000034799843,0.00011340322,0.000011609756,0.00022706564,0.000011014925,0.000100910125,0.0000059341096,0.0001047381,0.000008112477],"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":[0.000014454019,0.00003064599,0.00006543461,0.000030914987,0.000004749538,0.0000034498555,0.000033405136,0.96664387,0.0013468646,0.026927445,0.00013837755,0.004760379],"study_design_scores_gemma":[0.00037276186,0.00007511235,0.00028389457,0.00010550245,0.0000024082824,7.318875e-7,0.00003622522,0.9973881,0.00076190603,0.0007836654,0.00007366856,0.00011601483],"about_ca_topic_score_codex":0.000021977525,"about_ca_topic_score_gemma":0.0000059285053,"teacher_disagreement_score":0.9347242,"about_ca_system_score_codex":0.0000759616,"about_ca_system_score_gemma":0.000006845851,"threshold_uncertainty_score":0.4624449},"labels":[],"label_agreement":null},{"id":"W2144496466","doi":"10.1109/icccn.2007.4317811","title":"Adaptive Bit Loading for Coded MIMO-OFDM","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Orthogonal frequency-division multiplexing; MIMO; Bit error rate; MIMO-OFDM; Computer science; Electronic engineering; Coding (social sciences); Decoding methods; Computer network; Telecommunications; Engineering; Mathematics; Beamforming","score_opus":0.013550060217215764,"score_gpt":0.23380492594167904,"score_spread":0.22025486572446326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144496466","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":[0.0026225348,0.000112098984,0.98237747,0.000010232128,0.0002333005,0.0002151367,0.0000028749919,0.0004800798,0.013946295],"genre_scores_gemma":[0.75717014,0.000020165784,0.24201664,0.000040057224,0.00014882318,0.000014698362,0.000012250831,0.000040400097,0.00053682155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944884,0.0000021760663,0.00014033171,0.00010367127,0.000057495283,0.00024747133],"domain_scores_gemma":[0.999694,0.00011121136,0.000016250495,0.00009134157,0.000037730526,0.000049469232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009144435,0.00009377595,0.000094019866,0.00005693698,0.000039114733,0.0000090109015,0.00005422171,0.00005636373,0.000037782225],"category_scores_gemma":[0.000012339811,0.00009731944,0.000030452233,0.00014897512,0.000010441763,0.000122913,0.000008239515,0.0000536447,0.00001809655],"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":[0.000018666078,0.0000046904133,0.000033657157,0.000010903279,0.000015776202,0.0000011071762,0.00006771078,0.9805259,0.0023124984,0.0042084213,0.0016051228,0.01119553],"study_design_scores_gemma":[0.00032208228,0.000023537574,0.00004491549,0.000014575199,0.000006382798,0.0000012556006,0.00009319984,0.966337,0.028886788,0.00045619236,0.0036531764,0.00016089424],"about_ca_topic_score_codex":0.0000015451528,"about_ca_topic_score_gemma":0.00002581505,"teacher_disagreement_score":0.7545476,"about_ca_system_score_codex":0.00006739269,"about_ca_system_score_gemma":0.0000032054588,"threshold_uncertainty_score":0.39685714},"labels":[],"label_agreement":null},{"id":"W2144534788","doi":"10.1109/icbn.2005.1589640","title":"Efficient scheduling for the downlink of CDMA cellular networks using base station selection diversity","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Maximum throughput scheduling; Scheduling (production processes); Base station; Computer network; Fairness measure; Telecommunications link; Fading; Wireless network; Cellular network; Wireless; Network packet; Diversity combining; Round-robin scheduling; Dynamic priority scheduling; Channel (broadcasting); Quality of service; Throughput; Mathematical optimization; Telecommunications; Mathematics","score_opus":0.013068005988215585,"score_gpt":0.21330021981236372,"score_spread":0.20023221382414813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144534788","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":[0.21349871,0.00018064372,0.78582054,0.000014854838,0.000112915804,0.00023057158,0.0000021967967,0.000103272076,0.000036311547],"genre_scores_gemma":[0.8515284,0.000027364986,0.14824575,0.000012324316,0.00014414976,0.000004543403,0.000013150005,0.000015390406,0.000008897281],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947727,0.000011575263,0.00016097925,0.000099123696,0.00009444068,0.00015661561],"domain_scores_gemma":[0.9996477,0.00010718858,0.000050246137,0.00008691152,0.00008427527,0.0000237254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014378726,0.0000855279,0.00008429339,0.000042633765,0.00021715184,0.0000101487985,0.000060881957,0.00005384869,0.00001903579],"category_scores_gemma":[0.000011530063,0.000074414114,0.00004010579,0.00022363824,0.000015575746,0.00007598028,0.000029821154,0.00007654642,8.1038826e-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":[0.000012354095,0.000010470471,0.00012311885,0.000014367355,0.00001646435,4.3706944e-8,0.000079804486,0.99199754,0.0024877815,0.00023500015,0.000016183596,0.0050068568],"study_design_scores_gemma":[0.00024244424,0.000009151882,0.00004971273,0.000012344512,0.000031649502,3.5545833e-7,0.000055169832,0.99099493,0.008467177,0.000010845869,0.000043094868,0.00008314405],"about_ca_topic_score_codex":0.000009475425,"about_ca_topic_score_gemma":0.000017934335,"teacher_disagreement_score":0.6380297,"about_ca_system_score_codex":0.00011294953,"about_ca_system_score_gemma":0.000006270431,"threshold_uncertainty_score":0.30345196},"labels":[],"label_agreement":null},{"id":"W2144774445","doi":"10.1109/glocom.2005.1578203","title":"Connection admission control algorithms for OFDM wireless networks","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":44,"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 Winnipeg; University of Manitoba","funders":"","keywords":"Connection (principal bundle); Queueing theory; Computer science; Admission control; Queue; Computer network; Orthogonal frequency-division multiplexing; Network packet; Wireless; Scheme (mathematics); Wireless network; Algorithm; Real-time computing; Mathematics; Telecommunications; Channel (broadcasting); Quality of service","score_opus":0.018893301785923838,"score_gpt":0.2675074850987157,"score_spread":0.24861418331279186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144774445","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":[0.003412089,0.0014897516,0.98350996,0.001263376,0.001163413,0.0013648288,0.0003063493,0.0012932596,0.0061969454],"genre_scores_gemma":[0.9272644,0.003033514,0.06715282,0.0003781421,0.00061663217,0.0005333462,0.00063913036,0.00009000764,0.0002920356],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99711776,0.00015488738,0.0009371032,0.0005162248,0.0002700999,0.0010039544],"domain_scores_gemma":[0.9972666,0.00027467337,0.00026473816,0.001359891,0.0004543202,0.00037981017],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003320568,0.0005687528,0.0006161152,0.00014470414,0.0005945424,0.0001823295,0.00105246,0.00045039027,0.00019180393],"category_scores_gemma":[0.00005512241,0.000646062,0.00021468593,0.0006550168,0.00014678796,0.0006652264,0.00008295925,0.00048877596,0.00008605223],"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":[0.000047213805,0.00013185707,0.00012481572,0.000020250325,0.00010736491,7.229769e-7,0.000028767266,0.81646335,0.00012903886,0.0036269154,0.028119175,0.15120055],"study_design_scores_gemma":[0.0019207856,0.00006732186,0.00024444333,0.000085368265,0.0000816964,0.000030294475,0.000056559013,0.89389825,0.00024450273,0.00054468197,0.10220956,0.00061655],"about_ca_topic_score_codex":0.000040788193,"about_ca_topic_score_gemma":0.0006969158,"teacher_disagreement_score":0.92385226,"about_ca_system_score_codex":0.00082107243,"about_ca_system_score_gemma":0.00015524212,"threshold_uncertainty_score":0.99959904},"labels":[],"label_agreement":null},{"id":"W2144975547","doi":"10.1109/tvt.2007.897209","title":"Cooperative Fair Scheduling for the Downlink of CDMA Cellular Networks","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":56,"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","keywords":"Telecommunications link; Scheduling (production processes); Computer science; Code division multiple access; Computer network; Base station; Proportionally fair; Cellular network; Maximum throughput scheduling; Distributed computing; Quality of service; Round-robin scheduling; Fair-share scheduling; Mathematical optimization; Mathematics","score_opus":0.0066820934212884495,"score_gpt":0.2165305698037418,"score_spread":0.20984847638245335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144975547","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":[0.022199238,0.00086466176,0.9751713,0.00014926803,0.00045768527,0.000550773,0.000009133418,0.000554596,0.000043291755],"genre_scores_gemma":[0.97614515,0.00031097248,0.023277605,0.000027395648,0.000049608443,0.000109781584,0.000005844219,0.00005277861,0.000020843614],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903065,0.000011284012,0.00032550236,0.0001995224,0.00009893987,0.00033409704],"domain_scores_gemma":[0.99920195,0.00022348222,0.000055962068,0.00035815648,0.00012830383,0.00003216284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019172179,0.00018719568,0.00022193331,0.00023631236,0.00019212729,0.000007945991,0.00021753655,0.0003651546,0.000011657517],"category_scores_gemma":[0.000007645284,0.0001611709,0.0001024309,0.0007547533,0.00016055103,0.00007257475,0.0000013994088,0.00046634913,0.000004183073],"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":[0.000025721636,0.000029943034,0.0000030412662,0.000014667367,0.00009738316,0.0000025446839,0.000028090057,0.9561195,0.012409618,0.0009747927,0.0000083306395,0.030286372],"study_design_scores_gemma":[0.0003264818,0.00007005082,0.0000026805124,0.000026922013,0.000043856482,0.000004583061,0.00012127987,0.7320497,0.26656356,0.00011840083,0.00054456893,0.0001279203],"about_ca_topic_score_codex":0.0000012972072,"about_ca_topic_score_gemma":0.000024735376,"teacher_disagreement_score":0.95394593,"about_ca_system_score_codex":0.000069546906,"about_ca_system_score_gemma":0.000011171462,"threshold_uncertainty_score":0.65723586},"labels":[],"label_agreement":null},{"id":"W2145273166","doi":"10.1109/vetecf.2002.1040354","title":"Scheduling algorithms for the cdma2000 packet data evolution","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":45,"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":"Computer science; Scheduling (production processes); Network packet; Proportionally fair; Real-time computing; Round-robin scheduling; Computer network; Algorithm; Fair-share scheduling; Quality of service; Mathematical optimization","score_opus":0.038830713495837776,"score_gpt":0.26666092287480864,"score_spread":0.22783020937897086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145273166","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":[0.00024810113,0.0011958934,0.9950041,0.000037922266,0.00038309814,0.00023694953,0.00001491602,0.00026403693,0.0026149822],"genre_scores_gemma":[0.5029907,0.0002786393,0.49586427,0.000039635608,0.00024351568,0.00005225687,0.00009647114,0.00005652168,0.00037797907],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999454,0.000012802153,0.00011645794,0.00013871575,0.00009403975,0.0001839494],"domain_scores_gemma":[0.9993451,0.00011453175,0.0000149129855,0.0004599102,0.0000402349,0.000025310617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002489625,0.00008530645,0.00006557811,0.000019957073,0.0000957432,0.00002258412,0.00018208942,0.000042950276,0.00004695491],"category_scores_gemma":[0.00007911441,0.000065344575,0.000016547388,0.00015085537,0.000014576252,0.00024186501,0.000019149187,0.00006688875,0.000013913365],"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":[9.63935e-7,0.000003280539,0.00001814202,0.0000052594605,0.000014865165,6.479569e-8,0.000009796824,0.9798206,0.000038596634,0.0050793905,0.001399074,0.013609983],"study_design_scores_gemma":[0.00019757845,0.0000035205276,0.000022591481,0.0000056966596,0.00001807633,0.0000017333122,0.00006330288,0.981511,0.00027975935,0.0008262368,0.016977027,0.00009348576],"about_ca_topic_score_codex":0.0000025806771,"about_ca_topic_score_gemma":0.000013330493,"teacher_disagreement_score":0.5027426,"about_ca_system_score_codex":0.00005699176,"about_ca_system_score_gemma":0.000013608796,"threshold_uncertainty_score":0.26646742},"labels":[],"label_agreement":null},{"id":"W2145296449","doi":"10.1109/lsp.2009.2016449","title":"Proportional Fair Multiuser Scheduling in LTE","year":2009,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":249,"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","funders":"","keywords":"Telecommunications link; Computer science; Scheduling (production processes); Maximum throughput scheduling; Proportionally fair; Fairness measure; Throughput; Computer network; Mathematical optimization; Round-robin scheduling; Real-time computing; Fair-share scheduling; Distributed computing; Mathematics; Telecommunications; Quality of service; Wireless","score_opus":0.008065413057944063,"score_gpt":0.21871355088665861,"score_spread":0.21064813782871455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145296449","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":[0.34948376,0.00017230338,0.64918274,0.00042733364,0.00010394456,0.000120455465,7.0994014e-7,0.0003506367,0.00015812462],"genre_scores_gemma":[0.96024626,0.000007747381,0.03863633,0.0007979979,0.00024360705,0.000012740522,0.000009917054,0.00003537875,0.000009985755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989467,0.000013132008,0.00028332978,0.00021761328,0.00020682559,0.00033235183],"domain_scores_gemma":[0.99976283,0.000016214579,0.000053297317,0.00008235012,0.00003256944,0.000052750474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009458774,0.00017626036,0.00015352559,0.00014578662,0.00006692105,0.000052831296,0.00011230802,0.0000684232,0.000012042471],"category_scores_gemma":[0.0000057600537,0.00019153312,0.00003189396,0.00035786332,0.000031976044,0.0004999571,0.0000044565054,0.00026750955,0.000012653833],"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":[0.000008944564,0.000015792442,0.00028803776,0.000029913906,0.0000032083428,0.000017170318,0.00011653709,0.88017553,0.08472091,0.000007389348,0.00012265333,0.034493938],"study_design_scores_gemma":[0.00034299874,0.00001148237,0.0012562618,0.00017332977,0.000004489006,0.0000058552428,0.000013477793,0.98943794,0.00824967,0.00015129834,0.00008858913,0.0002646233],"about_ca_topic_score_codex":0.00000102739,"about_ca_topic_score_gemma":0.0000016793412,"teacher_disagreement_score":0.61076254,"about_ca_system_score_codex":0.00011776923,"about_ca_system_score_gemma":0.000020545025,"threshold_uncertainty_score":0.78104943},"labels":[],"label_agreement":null},{"id":"W2145752182","doi":"10.1109/mwc.2007.4396949","title":"Scheduling schemes for multimedia service in wireless OFDM systems","year":2007,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":26,"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; Innovation, Science and Economic Development Canada","funders":"","keywords":"Computer science; Link adaptation; Computer network; Orthogonal frequency-division multiplexing; Scheduling (production processes); Quality of service; Time division multiple access; Wireless broadband; Fairness measure; Fading; WiMAX; Maximum throughput scheduling; Proportionally fair; Wireless; Network packet; Spectral efficiency; Round-robin scheduling; Real-time computing; Throughput; Wireless network; Dynamic priority scheduling; Channel (broadcasting); Telecommunications","score_opus":0.028647708220239265,"score_gpt":0.2826422684051674,"score_spread":0.2539945601849281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145752182","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":[0.2313603,0.0015251543,0.76392853,0.00013996637,0.0006479676,0.00095548347,0.0000305392,0.00065394444,0.00075810583],"genre_scores_gemma":[0.9164499,0.00085934764,0.08178744,0.000053315856,0.00014883452,0.00038116632,0.0001710487,0.000115134775,0.00003379515],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99825406,0.000051995507,0.0007031582,0.00025500052,0.00018113574,0.00055463857],"domain_scores_gemma":[0.9972659,0.0007882274,0.00012722942,0.001433014,0.0002596854,0.0001259417],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00050794403,0.00027553077,0.00035982562,0.00027300144,0.0002188238,0.000057801222,0.0009872771,0.00022580194,0.0000027647009],"category_scores_gemma":[0.000031801024,0.0003365582,0.00006390709,0.00095832505,0.00008424102,0.00036511276,0.00009372843,0.0004214302,0.000023672601],"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":[0.000021725358,0.000107295746,0.0010598423,0.00023300914,0.00004829466,0.0000015170577,0.0006241297,0.9599729,0.011752961,0.005247141,0.00006761524,0.02086358],"study_design_scores_gemma":[0.00075037644,0.000008355604,0.00030465276,0.00027053783,0.000015694593,0.000003677992,0.00044855126,0.99179465,0.0032144971,0.000055537104,0.002774436,0.0003590141],"about_ca_topic_score_codex":0.000058005768,"about_ca_topic_score_gemma":0.00090403267,"teacher_disagreement_score":0.68508965,"about_ca_system_score_codex":0.00025680967,"about_ca_system_score_gemma":0.000039107676,"threshold_uncertainty_score":0.9999086},"labels":[],"label_agreement":null},{"id":"W2145835133","doi":"10.1109/lcn.2006.322074","title":"An Adaptive Non-preemptive Scheduling Framework for Delay Bounded Traffic in Cellular Networks","year":2006,"lang":"en","type":"article","venue":"Conference on Local Computer Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Scheduling (production processes); Provisioning; Traffic generation model; Wireless network; Software deployment; Distributed computing; Cellular network; Online algorithm; Wireless","score_opus":0.012440546789555933,"score_gpt":0.2294168713468777,"score_spread":0.21697632455732174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145835133","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":[0.024404772,0.00039200106,0.97267526,0.000015550675,0.0010418589,0.00080057635,0.0000050969256,0.0004828462,0.00018201224],"genre_scores_gemma":[0.79968405,0.000058479134,0.19840124,0.0000913346,0.001364057,0.00012460112,0.00016273648,0.00010829116,0.000005208677],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99755454,0.00008801117,0.0005809041,0.0006848509,0.00017736111,0.0009143321],"domain_scores_gemma":[0.99874204,0.00033720606,0.000115726754,0.0004764265,0.00015301238,0.00017558174],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020350881,0.00053777744,0.0005517644,0.00016548116,0.00015595411,0.0001688124,0.00044310107,0.0005886738,0.000014879544],"category_scores_gemma":[0.000004033312,0.0006049485,0.00011838225,0.00053262094,0.000140103,0.00033415348,0.000049916096,0.00095359545,0.0000068248155],"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":[0.0001491239,0.000085289124,0.000037142174,0.000013640973,0.000025172283,0.000018807634,0.000083926985,0.9280791,0.0000047551052,0.020079887,0.00010707593,0.05131604],"study_design_scores_gemma":[0.0007962537,0.0004069866,0.00014670553,0.00042600936,0.000014847448,0.000002254518,0.00005050447,0.991371,0.000039332877,0.006058686,0.000034447326,0.0006530049],"about_ca_topic_score_codex":0.00001126108,"about_ca_topic_score_gemma":0.00011475665,"teacher_disagreement_score":0.7752793,"about_ca_system_score_codex":0.00026454794,"about_ca_system_score_gemma":0.000038222843,"threshold_uncertainty_score":0.99964017},"labels":[],"label_agreement":null},{"id":"W2145975143","doi":"10.1109/glocom.2006.128","title":"CTH16-6: Adaptive Coding and Modulation for Hybrid ARQ Systems over Partially Observable Nakagami-m Fading Channels","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Link adaptation; Computer science; Fading; Hybrid automatic repeat request; Channel state information; Observable; Algorithm; Automatic repeat request; Adaptive coding; Transmitter; Coding (social sciences); Telecommunications link; Markov process; Channel (broadcasting); Decoding methods; Computer network; Wireless; Mathematics; Telecommunications; Statistics","score_opus":0.014154824316424909,"score_gpt":0.20651242688273236,"score_spread":0.19235760256630746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145975143","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":[0.13531627,0.0006249743,0.86187994,0.000014687392,0.0008726668,0.00048928795,0.000035462428,0.00032373407,0.00044299947],"genre_scores_gemma":[0.9922028,0.000055173157,0.0068095084,0.000011291635,0.00051283976,0.000088650326,0.00009907307,0.00005303112,0.000167629],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906933,0.000015783264,0.00026317968,0.00022047419,0.000111011956,0.0003202265],"domain_scores_gemma":[0.9996195,0.00007640816,0.000069244,0.00013070226,0.00005514304,0.00004902193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010189761,0.00017719151,0.00021196858,0.000054988242,0.000120579214,0.00008457914,0.000062005805,0.000072876304,0.0000048081474],"category_scores_gemma":[0.00001127481,0.00020507307,0.000036335816,0.00011781626,0.000015407779,0.00038480424,0.000020928563,0.00007314165,0.000003720796],"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":[0.000012596782,0.000006284158,0.00044623239,0.00006201959,0.000017484545,0.0000017333127,0.000030555962,0.99344224,0.0007232647,0.0030542084,0.0012031965,0.0010002151],"study_design_scores_gemma":[0.00044880054,0.00002110804,0.0011266386,0.00008687734,0.000015538337,0.0000044194226,0.00001958761,0.994527,0.0007084771,0.00085742486,0.0019568382,0.0002272791],"about_ca_topic_score_codex":0.00006348722,"about_ca_topic_score_gemma":0.000028235772,"teacher_disagreement_score":0.8568865,"about_ca_system_score_codex":0.00014028815,"about_ca_system_score_gemma":0.0000071163804,"threshold_uncertainty_score":0.8362637},"labels":[],"label_agreement":null},{"id":"W2146000509","doi":"10.1109/icc.2009.5198735","title":"An Interior Point Penalty Method for Utility Maximization Problems in OFDMA Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Resource allocation; Mathematical optimization; Orthogonal frequency-division multiple access; Quality of service; Convexity; Frequency-division multiple access; Optimization problem; Provisioning; Channel allocation schemes; Channel (broadcasting); Transmission (telecommunications); Penalty method; Orthogonal frequency-division multiplexing; Computer network; Wireless; Algorithm; Mathematics; Telecommunications","score_opus":0.01093755339012598,"score_gpt":0.26883317458375994,"score_spread":0.25789562119363396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146000509","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":[0.0028194755,0.00012027324,0.99527866,0.00009083444,0.0001374254,0.00064149156,0.0000031153604,0.00041552176,0.0004932349],"genre_scores_gemma":[0.67469746,0.00009374265,0.32485524,0.00009856889,0.000069317386,0.000070822294,0.00006364912,0.000026290334,0.000024946623],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990563,0.000040932886,0.00032917486,0.00023017112,0.000066796136,0.0002766404],"domain_scores_gemma":[0.99958605,0.000042414555,0.000040698145,0.00021111313,0.00005701,0.000062702544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002775318,0.00015579828,0.00019811845,0.000082208346,0.000031658736,0.00003245319,0.000114995586,0.00010716075,0.00007055368],"category_scores_gemma":[0.000016871722,0.00015705076,0.000037746813,0.0002807054,0.000007902342,0.00040791824,0.00000878665,0.00011867676,9.2587317e-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":[0.000017030216,0.00002424937,0.00025215806,0.000018349028,0.0000038821017,2.2758843e-7,0.0000772473,0.8888041,0.00036622002,0.0002943184,0.000121450386,0.11002078],"study_design_scores_gemma":[0.0003987838,0.000064037544,0.002597351,0.00003712804,0.0000058003357,0.0000012198796,0.00002105653,0.9945141,0.00052056747,0.0015291295,0.00013492072,0.00017589748],"about_ca_topic_score_codex":0.000007846567,"about_ca_topic_score_gemma":0.00010305767,"teacher_disagreement_score":0.671878,"about_ca_system_score_codex":0.00007951359,"about_ca_system_score_gemma":0.0000062859117,"threshold_uncertainty_score":0.64043444},"labels":[],"label_agreement":null},{"id":"W2146237580","doi":"10.1109/glocom.2004.1379126","title":"Opportunistic scheduling for streaming users in high-speed downlink packet access (HSDPA)","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":22,"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; Link adaptation; Quality of service; Telecommunications link; Scheduling (production processes); Computer network; Network packet; Code division multiple access; Coding (social sciences); Real-time computing; Fading; Channel (broadcasting); Mathematical optimization; Mathematics","score_opus":0.024202637962221198,"score_gpt":0.2716577733280267,"score_spread":0.24745513536580552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146237580","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":[0.19889812,0.000065952474,0.7985659,0.00017921698,0.00022276527,0.00039982397,0.000015398704,0.00049668073,0.0011561393],"genre_scores_gemma":[0.8606965,0.000117725256,0.13855219,0.000069716996,0.00022404866,0.000030092926,0.00012460514,0.000059255566,0.00012589278],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990016,0.000009048211,0.00031392605,0.00021138326,0.00010101466,0.0003629835],"domain_scores_gemma":[0.99952817,0.00011778542,0.00004147656,0.00018797147,0.00003999727,0.00008457364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010093207,0.00017850967,0.00020343477,0.00014314342,0.000047166784,0.00006280734,0.00017917193,0.000099296194,0.00007351853],"category_scores_gemma":[0.00004376663,0.00019381483,0.00003627844,0.00025988993,0.000016477275,0.0005815222,0.00003314168,0.00012983724,0.000009571542],"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":[0.000009143047,0.000013896179,0.0010704191,0.000038348233,0.000011460995,0.0000021031183,0.000034962926,0.976453,0.00044942016,0.0011597228,0.00014727398,0.020610265],"study_design_scores_gemma":[0.0006796981,0.000010428089,0.00065074867,0.000047859307,0.000008058447,0.0000010530187,0.000049817612,0.9961622,0.0013278625,0.00023745088,0.00057557126,0.00024925693],"about_ca_topic_score_codex":0.000007830273,"about_ca_topic_score_gemma":0.00017600591,"teacher_disagreement_score":0.66179836,"about_ca_system_score_codex":0.00016529777,"about_ca_system_score_gemma":0.00001774729,"threshold_uncertainty_score":0.79035395},"labels":[],"label_agreement":null},{"id":"W2146413297","doi":"10.1109/icccn.2008.ecp.98","title":"Maximum Network Lifetime in Interference-Aware WiMax/802.16 Mesh Centralized Scheduling","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Concordia University","funders":"","keywords":"Wireless mesh network; WiMAX; Computer network; Computer science; Mesh networking; Software deployment; Scheduling (production processes); Wireless broadband; Wireless network; Wireless; Engineering; Telecommunications","score_opus":0.012018215986451043,"score_gpt":0.2106935955064506,"score_spread":0.19867537951999956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146413297","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":[0.05530201,0.00064639293,0.9345541,0.00006314719,0.00058289466,0.0002863102,0.0000024717322,0.00091759395,0.0076450678],"genre_scores_gemma":[0.945612,0.0013377344,0.05224157,0.000089032226,0.00025039032,0.000027391485,0.000044799697,0.00007295923,0.00032412587],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985443,0.000033658427,0.00040614116,0.00026227642,0.00014573972,0.00060791976],"domain_scores_gemma":[0.99948704,0.000060364153,0.00004122277,0.0002550192,0.00004027097,0.00011606905],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008000901,0.00025452187,0.00031125665,0.00009645341,0.000074254815,0.000021748478,0.00019341362,0.00014194862,0.00048018622],"category_scores_gemma":[0.000017901366,0.0002670547,0.00005812682,0.0005469051,0.000043001142,0.0002928354,0.000054415752,0.00029029825,0.000081072205],"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":[0.000021492082,0.000015099912,0.004359086,0.000017125958,0.00001698481,0.000018771249,0.00012535586,0.99102175,0.000046021694,0.00027357152,0.0016752228,0.0024095383],"study_design_scores_gemma":[0.0008358712,0.000019973077,0.00084914564,0.00015107275,0.000006461286,0.000017968463,0.000054733486,0.99535185,0.00044917793,0.0006689535,0.0011884784,0.0004063008],"about_ca_topic_score_codex":0.000017352559,"about_ca_topic_score_gemma":0.00006870142,"teacher_disagreement_score":0.89031,"about_ca_system_score_codex":0.00019444896,"about_ca_system_score_gemma":0.000022302063,"threshold_uncertainty_score":0.9999782},"labels":[],"label_agreement":null},{"id":"W2146745654","doi":"10.1109/jsac.2006.881628","title":"Fair Allocation of Subcarrier and Power in an OFDMA Wireless Mesh Network","year":2006,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":118,"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","funders":"","keywords":"Wireless mesh network; Computer science; Subcarrier; Mesh networking; Scheduling (production processes); Switched mesh; Orthogonal frequency-division multiple access; Shared mesh; Computer network; Integer programming; Mathematical optimization; Distributed computing; Wireless; Wireless network; Orthogonal frequency-division multiplexing; Algorithm; Telecommunications; Mathematics","score_opus":0.010715356699834356,"score_gpt":0.24599905267313998,"score_spread":0.23528369597330562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146745654","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":[0.98250514,0.00097450893,0.015160398,0.00019836494,0.00014653876,0.00019940603,0.0000058928445,0.000085341526,0.0007244139],"genre_scores_gemma":[0.9923187,0.002235635,0.005231163,0.000023402246,0.00007588381,0.00002822796,0.000037849266,0.00003961521,0.000009530864],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987371,0.00020037843,0.00055559655,0.00011627722,0.00014993691,0.00024071019],"domain_scores_gemma":[0.9988649,0.00019629051,0.00015372771,0.0005137347,0.00021087425,0.00006045792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023977058,0.00014995244,0.00022944574,0.0002656773,0.00010415034,0.000034816396,0.0003735806,0.00011593914,0.000009022176],"category_scores_gemma":[0.000021080976,0.00016593434,0.000023420911,0.0011176984,0.00006742075,0.00034536826,0.000025764393,0.00057835015,7.6557086e-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":[0.000025360134,0.00013152407,0.029572466,0.0000067697893,0.00001336969,0.0000017118653,0.00018951834,0.96253914,0.002328944,0.0025804942,0.00024247423,0.0023682194],"study_design_scores_gemma":[0.00087657827,0.00007320577,0.20739156,0.0003622007,0.000015502348,0.00002525164,0.00007844404,0.7874026,0.0010477499,0.0021309115,0.00029514264,0.00030085657],"about_ca_topic_score_codex":0.00002193217,"about_ca_topic_score_gemma":0.0010424587,"teacher_disagreement_score":0.17781909,"about_ca_system_score_codex":0.00016130538,"about_ca_system_score_gemma":0.000042545005,"threshold_uncertainty_score":0.6766606},"labels":[],"label_agreement":null},{"id":"W2147045567","doi":"10.1109/twc.2012.020712.101398","title":"Dynamic Parameter Adaptation for M-LWDF/M-LWWF Scheduling","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Dynamic priority scheduling; Scheduling (production processes); Queue; Mathematical optimization; Bandwidth (computing); Control theory (sociology); Dynamic bandwidth allocation; Mathematics; Computer network; Quality of service; Control (management)","score_opus":0.030831935796820885,"score_gpt":0.27293900262893317,"score_spread":0.24210706683211228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147045567","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":[0.013950067,0.00057617034,0.98297644,0.00016814678,0.00067007175,0.00060501456,0.00005867536,0.00070693897,0.00028846238],"genre_scores_gemma":[0.7833206,0.0011036049,0.2145339,0.00004752672,0.000030339,0.00070598524,0.00007874501,0.00008947872,0.000089835434],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987986,0.00006540164,0.00038628734,0.00017120219,0.00014401787,0.00043449207],"domain_scores_gemma":[0.9979113,0.00063105434,0.00007320255,0.0011435513,0.00010614404,0.00013477061],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016001846,0.0002433575,0.00021737092,0.00020255602,0.00047300835,0.000040069823,0.00043158693,0.00015549245,0.000023796621],"category_scores_gemma":[0.000009217032,0.000287879,0.00013644791,0.00041817166,0.00009317371,0.0006063652,0.0000031775292,0.0003767515,0.00005843415],"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":[0.0000131084935,0.00014159505,0.000007316588,0.000027163669,0.000058589998,3.847245e-8,0.0004750259,0.9265116,0.0011474747,0.0005913199,0.000023026483,0.07100376],"study_design_scores_gemma":[0.00039044765,0.00002677128,0.000037589056,0.000057513178,0.00006658507,0.000003038097,0.0002140324,0.99466956,0.0028830909,0.00016209514,0.0011843984,0.00030487575],"about_ca_topic_score_codex":0.000004802211,"about_ca_topic_score_gemma":0.000062893996,"teacher_disagreement_score":0.76937056,"about_ca_system_score_codex":0.00022392868,"about_ca_system_score_gemma":0.000021287044,"threshold_uncertainty_score":0.9999573},"labels":[],"label_agreement":null},{"id":"W2147446656","doi":"10.1109/wts.2009.5068970","title":"An efficient multiuser scheduling scheme for MIMO-CDMA wireless systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 du Québec à Montréal","funders":"","keywords":"Computer science; Base station; Scheduling (production processes); Beamforming; Computational complexity theory; Telecommunications link; MIMO; Code division multiple access; Wireless; Wireless network; Time division multiple access; Mathematical optimization; Distributed computing; Algorithm; Computer network; Mathematics; Telecommunications","score_opus":0.009099855626399742,"score_gpt":0.2403178486546603,"score_spread":0.23121799302826057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147446656","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":[0.23470107,0.00021969732,0.76306367,0.000015941563,0.00035561656,0.00041601658,0.0000033949002,0.0008144666,0.00041013965],"genre_scores_gemma":[0.8426527,0.00001925372,0.15688784,0.000033373777,0.00022324666,0.000041460535,0.00003156257,0.000047120575,0.00006347845],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990183,0.000010985969,0.00025962768,0.0002322177,0.00012716863,0.00035167806],"domain_scores_gemma":[0.9994522,0.00004128229,0.000034015826,0.000279205,0.00008625957,0.00010709069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001024954,0.00018630618,0.0001947601,0.000074431744,0.00008462379,0.00006167439,0.00014105267,0.000107390755,0.000007805336],"category_scores_gemma":[0.000010377813,0.00018522578,0.00004445622,0.00018421329,0.0000113596425,0.00017815323,0.000006262145,0.00009321755,0.000012787275],"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":[0.000009420443,0.000035537,0.000032507927,0.000036720063,0.000009486297,7.638518e-7,0.0000639458,0.9848747,0.008700975,0.0027833036,0.00007716182,0.0033754245],"study_design_scores_gemma":[0.0004754459,0.000042946318,0.00006329816,0.00005012123,0.0000065833365,0.0000017598829,0.00009746838,0.99534166,0.003292501,0.000015989708,0.00036063595,0.00025161958],"about_ca_topic_score_codex":0.0000024204642,"about_ca_topic_score_gemma":0.0000020202149,"teacher_disagreement_score":0.6079516,"about_ca_system_score_codex":0.0000805255,"about_ca_system_score_gemma":0.000007797028,"threshold_uncertainty_score":0.75532883},"labels":[],"label_agreement":null},{"id":"W2147627977","doi":"10.1109/tsp.2007.911284","title":"Optimal Channel-Aware ALOHA Protocol for Random Access in WLANs With Multipacket Reception and Decentralized Channel State Information","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Computer network; Aloha; Computer science; Channel (broadcasting); Random access; Channel state information; Protocol (science); State (computer science); Telecommunications; Throughput; Wireless; Algorithm","score_opus":0.024127991192802165,"score_gpt":0.27228050088440897,"score_spread":0.2481525096916068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147627977","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":[0.0076938057,0.000008982105,0.96664965,0.000022778775,0.000043909567,0.025255563,0.000030297473,0.0002802142,0.000014820133],"genre_scores_gemma":[0.9299351,0.000055530454,0.0065805106,0.000032059157,0.000028522483,0.06326761,0.000031844982,0.00005672566,0.000012064968],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988326,0.000027882224,0.00038631549,0.00020744749,0.00019451507,0.00035124924],"domain_scores_gemma":[0.99952567,0.000060094735,0.00010626174,0.0000826596,0.00013807298,0.00008721987],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000109030494,0.00025931318,0.00025276744,0.00027829423,0.00027430986,0.00010261917,0.00009198401,0.000102085905,0.000012128131],"category_scores_gemma":[0.0000022320157,0.00024561913,0.000035522455,0.00043278688,0.000058795904,0.0024257333,0.0000011072501,0.00022495376,0.0000019788022],"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":[0.001634622,0.000048982496,0.000010128285,0.0003363963,0.000015061649,0.0000018891759,0.0014118379,0.9728924,0.00008815147,1.1944226e-7,0.000017281423,0.023543099],"study_design_scores_gemma":[0.00818898,0.00012103045,0.000050662187,0.00038577378,0.000012808312,0.000021245469,0.000110948895,0.9804307,0.010256455,0.000018609724,0.000098403645,0.00030437423],"about_ca_topic_score_codex":0.0000061312594,"about_ca_topic_score_gemma":0.000031890788,"teacher_disagreement_score":0.9600691,"about_ca_system_score_codex":0.00011982396,"about_ca_system_score_gemma":0.000050003986,"threshold_uncertainty_score":0.9999996},"labels":[],"label_agreement":null},{"id":"W2147758080","doi":"10.1109/wcl.2014.022314.130796","title":"Dynamic Spectrum Management in Multi-Radio Access Technology (RAT) Cellular Systems","year":2014,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Toronto","funders":"","keywords":"Computer science; Spectrum management; Frequency allocation; Radio resource management; Computer network; Cognitive radio; Spectrum (functional analysis); Access technology; Resource management (computing); Distributed computing; Telecommunications; Wireless; Wireless network","score_opus":0.013920787295434176,"score_gpt":0.24663566402053802,"score_spread":0.23271487672510385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147758080","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":[0.118936665,0.0007638012,0.8760788,0.0017556242,0.00062780845,0.00060675485,0.000003811247,0.000829931,0.00039682843],"genre_scores_gemma":[0.97686183,0.0014256296,0.021016805,0.000095872434,0.000022646334,0.0003829317,0.00006002718,0.000093593386,0.000040671563],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985374,0.00012249578,0.00047295212,0.0002860029,0.00014527098,0.00043586607],"domain_scores_gemma":[0.9975493,0.00008484043,0.00010013047,0.0021871023,0.000023525079,0.00005509738],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001764209,0.00026475225,0.00031314907,0.0006332014,0.00015058898,0.00008986013,0.0018389195,0.0001395454,0.0000027328854],"category_scores_gemma":[0.000004843658,0.0003231359,0.000045372202,0.0010643133,0.000165315,0.00030881344,0.00022551623,0.00046050083,0.00004226477],"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":[0.000002157796,0.000048804744,0.00047901116,0.000070267975,0.000040470368,0.0000053161793,0.000055471497,0.98822236,0.0059646075,0.0019564661,0.00019007624,0.0029649634],"study_design_scores_gemma":[0.0005374366,0.000005521659,0.00034244888,0.00012955556,0.000016992124,0.0000046131786,0.000060654922,0.9956766,0.0008329335,0.0000625044,0.0019981074,0.0003326736],"about_ca_topic_score_codex":0.00002367891,"about_ca_topic_score_gemma":0.0001817886,"teacher_disagreement_score":0.8579252,"about_ca_system_score_codex":0.0003888719,"about_ca_system_score_gemma":0.0000056625986,"threshold_uncertainty_score":0.9999221},"labels":[],"label_agreement":null},{"id":"W2147837057","doi":"10.1145/1577222.1577232","title":"Uplink scheduling for supporting real time voice traffic in IEEE 802.16 networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer network; Computer science; Network packet; Dynamic bandwidth allocation; Telecommunications link; Scheduling (production processes); Bandwidth allocation; Bandwidth (computing); Base station; Byte; Network traffic control; Real-time computing; Operating system","score_opus":0.007557732571367523,"score_gpt":0.24624476773854972,"score_spread":0.2386870351671822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147837057","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":[0.19402787,0.00006611192,0.8028859,0.000012544391,0.0002755515,0.00029557227,6.793386e-7,0.0005824819,0.0018533211],"genre_scores_gemma":[0.86162627,0.00007804569,0.13739514,0.000029413668,0.00044998183,0.000020633954,0.000050664476,0.00008592689,0.00026391557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985734,0.0000073335095,0.00049901154,0.00022283281,0.000073927935,0.0006234946],"domain_scores_gemma":[0.9994256,0.00023947936,0.00005321125,0.00015499057,0.00004182276,0.00008491752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051980396,0.00018163079,0.00021521651,0.00011919626,0.000055146636,0.000022634824,0.00010972943,0.00017285549,0.0000342221],"category_scores_gemma":[0.00002971237,0.0002040389,0.000054333977,0.00036028924,0.000014537677,0.00020640157,0.000011796639,0.00020011027,0.000020361393],"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":[0.000018742972,0.000010277613,0.00008684401,0.000021929603,0.00000892109,0.0000032921157,0.00005581726,0.96720517,0.0005023128,0.00007747889,0.0002028403,0.031806376],"study_design_scores_gemma":[0.0004448391,0.000017248074,0.00007238108,0.00003951458,0.000007071511,0.0000030229307,0.000042195774,0.99834746,0.00064994814,0.000035390833,0.000104226565,0.00023668149],"about_ca_topic_score_codex":0.0000061148885,"about_ca_topic_score_gemma":0.00014405459,"teacher_disagreement_score":0.6675984,"about_ca_system_score_codex":0.00017476983,"about_ca_system_score_gemma":0.000010729548,"threshold_uncertainty_score":0.83204645},"labels":[],"label_agreement":null},{"id":"W2148704738","doi":"10.1109/wcnc.1999.796943","title":"Scheduling for integrated services in next generation packet broadcast networks","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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","funders":"","keywords":"Computer science; Computer network; Jitter; Quality of service; Network packet; Scheduling (production processes); Token bucket; Leaky bucket; Time division multiple access; Telecommunications link; Wireless network; Packet switching; Processing delay; Time-division multiplexing; Transmission delay; Real-time computing; Wireless; Multiplexing; Telecommunications","score_opus":0.019681112954288125,"score_gpt":0.22591499381549776,"score_spread":0.20623388086120964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148704738","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":[0.07583818,0.00062489416,0.9219686,0.000008048056,0.00030669055,0.0002504537,0.0000012489558,0.00022279195,0.00077909074],"genre_scores_gemma":[0.84645844,0.0002551024,0.15282759,0.000057952428,0.00011928902,0.000056860063,0.00013231335,0.00004051684,0.00005195507],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999344,0.000018778403,0.00021208216,0.0001464519,0.000048091308,0.000230584],"domain_scores_gemma":[0.99974966,0.000033674958,0.000023010934,0.00011006385,0.00004767002,0.0000358951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009836684,0.00013033379,0.00012230352,0.000069225425,0.00003825908,0.000052516825,0.00005377061,0.00010033024,0.00004056178],"category_scores_gemma":[0.000011616634,0.00013264266,0.000022854667,0.00032465268,0.0000063219313,0.00033389454,0.000004730736,0.00010138198,0.0000041852836],"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":[0.000003286215,0.000006715172,0.0002284508,0.000018881141,0.0000060535426,3.8402425e-7,0.000047363937,0.98723054,0.0013141788,0.0012094174,0.00007783005,0.009856893],"study_design_scores_gemma":[0.00032220286,0.000009149097,0.000018809975,0.000029231845,0.000003485701,0.0000010944766,0.00012282406,0.99585766,0.0019153479,0.00008713748,0.0014861085,0.0001469354],"about_ca_topic_score_codex":0.0000056141002,"about_ca_topic_score_gemma":0.00020059555,"teacher_disagreement_score":0.7706202,"about_ca_system_score_codex":0.000068821864,"about_ca_system_score_gemma":0.0000072823846,"threshold_uncertainty_score":0.54090106},"labels":[],"label_agreement":null},{"id":"W2148886334","doi":"10.1109/tvt.2009.2027331","title":"Efficient Resource Allocation for OFDMA Multicast Systems With Spectrum-Sharing Control","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University; University of Saskatchewan; University of Alberta","funders":"","keywords":"Subcarrier; Multicast; Computer science; Computer network; Resource allocation; Throughput; Bandwidth (computing); Frequency-division multiple access; Orthogonal frequency-division multiple access; Spectral efficiency; Maximization; Base station; Orthogonal frequency-division multiplexing; Power control; Bandwidth allocation; Distributed computing; Mathematical optimization; Wireless; Power (physics); Mathematics; Telecommunications; Channel (broadcasting)","score_opus":0.004713638808440682,"score_gpt":0.19629429035175014,"score_spread":0.19158065154330944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148886334","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":[0.052260417,0.00021588572,0.94464904,0.0005074107,0.00016223452,0.0008413998,0.000014420705,0.0013072927,0.00004187097],"genre_scores_gemma":[0.99441236,0.000027645558,0.005048541,0.00003308838,0.00003944259,0.0003483458,0.000005320222,0.000051990064,0.000033260036],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989871,0.000010708335,0.00024154625,0.00030145468,0.0001265778,0.0003326354],"domain_scores_gemma":[0.9994417,0.00004024057,0.000050744064,0.00035951132,0.000062176914,0.000045660894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000695033,0.00020674766,0.00023535738,0.00034118482,0.00014956841,0.000023217957,0.0001615957,0.00023717438,0.0000033620884],"category_scores_gemma":[0.0000030644917,0.00020288074,0.000052599065,0.00048507977,0.000050652976,0.000041595333,4.266031e-7,0.00027626997,0.000007477955],"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":[0.00005313773,0.00007019247,0.0000037123623,0.000028105385,0.000057262365,0.0000037346483,0.00002234538,0.98713654,0.005628497,0.00064114295,0.000007499746,0.0063478155],"study_design_scores_gemma":[0.0011534559,0.00021241164,0.000010971364,0.00010193681,0.000063810985,0.000025557169,0.000053314903,0.9716343,0.026088031,0.000044527664,0.00039495697,0.0002167125],"about_ca_topic_score_codex":0.0000017855928,"about_ca_topic_score_gemma":0.000004649688,"teacher_disagreement_score":0.94215196,"about_ca_system_score_codex":0.00015816941,"about_ca_system_score_gemma":0.000007892274,"threshold_uncertainty_score":0.8273237},"labels":[],"label_agreement":null},{"id":"W2149080044","doi":"10.1109/isit.2006.261694","title":"Using Polymatroid Structures to Provide Fairness in Multiuser Systems","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Facet (psychology); Point (geometry); Mathematics; Mathematical optimization; Time-sharing; Class (philosophy); Scheme (mathematics); Computer science; Topology (electrical circuits); Combinatorics; Mathematical analysis; Geometry; Artificial intelligence","score_opus":0.009888678850882167,"score_gpt":0.22569565827840463,"score_spread":0.21580697942752247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149080044","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":[0.29272583,0.00021081066,0.705393,0.0000053922054,0.00024346936,0.00026956858,0.0000018180618,0.000286922,0.0008631611],"genre_scores_gemma":[0.9554678,0.0000017280289,0.04419724,0.000010510562,0.00013632364,0.000016871078,0.0000062372064,0.000041107054,0.0001221562],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993395,0.000010840031,0.00020465486,0.00012997311,0.000090385845,0.00022460903],"domain_scores_gemma":[0.9997861,0.000015372485,0.000016448073,0.000130133,0.000018740142,0.00003325228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002823549,0.000119797136,0.0001291879,0.000116968586,0.000020930784,0.000034861725,0.000069542155,0.00005514879,0.0000086484315],"category_scores_gemma":[0.0000043728937,0.00011753489,0.000014053978,0.00026720337,0.000005946459,0.00016208689,0.000016322258,0.000060629747,0.0000058568944],"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":[0.0000028629524,0.0000033078431,0.0019391006,0.00002939394,0.0000021696392,0.000002707248,0.000031083742,0.98760504,0.008632065,0.0013357233,0.0001080524,0.000308527],"study_design_scores_gemma":[0.00018500948,0.0000031912264,0.001777791,0.000031664065,0.0000020982368,0.000004033152,0.000054505716,0.9931316,0.0042193667,0.00012166638,0.00029759342,0.00017148348],"about_ca_topic_score_codex":0.0005288301,"about_ca_topic_score_gemma":0.00029812424,"teacher_disagreement_score":0.662742,"about_ca_system_score_codex":0.00013385151,"about_ca_system_score_gemma":0.0000059146096,"threshold_uncertainty_score":0.47929338},"labels":[],"label_agreement":null},{"id":"W2149172516","doi":"10.1109/newcas.2008.4606324","title":"Scheduling of turbo decoding on a multiprocessor platform to manage its processing effort variability","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure; Polytechnique Montréal","funders":"","keywords":"Computer science; Decoding methods; Scheduling (production processes); Multiprocessing; Fair-share scheduling; Dynamic priority scheduling; MPSoC; Rate-monotonic scheduling; Parallel computing; Two-level scheduling; Turbo; Embedded system; Real-time computing; Distributed computing; Quality of service; Algorithm; Computer network; Engineering","score_opus":0.019669684482131224,"score_gpt":0.23581298289897096,"score_spread":0.21614329841683974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149172516","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":[0.5208968,0.00003345212,0.47267884,0.000005075016,0.000067062574,0.0002455933,0.0000012738325,0.0003294734,0.005742406],"genre_scores_gemma":[0.8467241,0.000029308705,0.15304087,0.00002963558,0.000045575427,0.0000264762,0.0000060227067,0.000041063344,0.00005694104],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894357,0.0000057035168,0.00033207162,0.00024375417,0.00019009528,0.00028481628],"domain_scores_gemma":[0.99949515,0.00008514635,0.000048391554,0.00018900375,0.000091700866,0.000090636524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018981325,0.00018173916,0.00023408432,0.0001271282,0.0000949308,0.000011699377,0.0001368124,0.00008438476,0.000022442115],"category_scores_gemma":[0.000106155334,0.0001793102,0.000037330214,0.00047923974,0.000017366283,0.00034822305,0.00003487823,0.00013972272,0.00001531938],"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":[0.00002952659,0.000024615565,0.0007957129,0.00031865286,0.000009793881,0.000002934885,0.00038844795,0.9890564,0.001567986,0.00018981556,0.000005400909,0.0076107127],"study_design_scores_gemma":[0.000273593,0.00002492747,0.0007306523,0.00019116435,0.0000060981847,0.000004331475,0.00003650794,0.9537378,0.044676982,0.00006908944,0.000038423925,0.0002104189],"about_ca_topic_score_codex":0.0000015092937,"about_ca_topic_score_gemma":0.0000027319568,"teacher_disagreement_score":0.3258273,"about_ca_system_score_codex":0.00010925152,"about_ca_system_score_gemma":0.00001343198,"threshold_uncertainty_score":0.73120576},"labels":[],"label_agreement":null},{"id":"W2149291566","doi":"10.1109/ciss.2006.286460","title":"Scheduling and Codeword Length Optimization in Time Varying Wireless Networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Fading; Computer science; Scheduling (production processes); Channel state information; Code word; Algorithm; Decoding methods; Real-time computing; Wireless; Mathematics; Telecommunications; Mathematical optimization","score_opus":0.0038388871983893436,"score_gpt":0.18279426698808202,"score_spread":0.17895537978969267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149291566","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":[0.062886454,0.00042346845,0.93285674,0.000017188248,0.000081769314,0.00014902567,6.0635483e-7,0.00044083467,0.0031439078],"genre_scores_gemma":[0.87908506,0.00035536283,0.12018875,0.000020375197,0.00012677979,0.000013502056,0.00005140653,0.000054551914,0.0001041888],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917173,0.000017215592,0.00025836824,0.00018558369,0.00009664638,0.00027044944],"domain_scores_gemma":[0.9997374,0.000061438695,0.000029322784,0.00011274782,0.000022017908,0.00003707484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000094020266,0.00015742838,0.00016811716,0.000106956984,0.00005033655,0.000052624557,0.00007130637,0.00011713484,0.000040595663],"category_scores_gemma":[0.000004623584,0.0001783315,0.00001531674,0.00035495154,0.000021289312,0.0003113676,0.000028825889,0.00015792093,0.0000046745513],"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":[0.000005191578,0.000009621782,0.0015596754,0.000010949457,0.0000040756872,0.000002538258,0.000012196209,0.99494165,0.00011117937,0.00034406385,0.000039735023,0.0029590938],"study_design_scores_gemma":[0.00036650398,0.0000049278547,0.0002510724,0.000051304574,0.0000045663437,0.0000030754957,0.0000050073772,0.99887216,0.00013796221,0.0000775886,0.000021811697,0.00020402714],"about_ca_topic_score_codex":0.00001555139,"about_ca_topic_score_gemma":0.000019210844,"teacher_disagreement_score":0.81619865,"about_ca_system_score_codex":0.00006516964,"about_ca_system_score_gemma":0.0000041166973,"threshold_uncertainty_score":0.7272147},"labels":[],"label_agreement":null},{"id":"W2149402509","doi":"10.1109/mcom.2007.4290319","title":"IPTV over WiMAX: Key Success Factors, Challenges, and Solutions [Advances in Mobile Multimedia]","year":2007,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":160,"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":"WiMAX; IPTV; Computer science; Computer network; Interoperability; Wireless broadband; Multicast; Telecommunications; Internet access; The Internet; Multimedia; Wireless; Wireless network; World Wide Web","score_opus":0.02681136384571854,"score_gpt":0.27837120495860523,"score_spread":0.2515598411128867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149402509","genre_codex":"review","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":[0.15073775,0.56913644,0.25099397,0.0004600398,0.0014115497,0.0017590655,0.00008187033,0.0016492698,0.023770051],"genre_scores_gemma":[0.80512536,0.16916503,0.025387162,0.0000109729845,0.00006205058,0.000082088554,0.00008021988,0.000045357498,0.000041759522],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891365,0.00004826372,0.00036382195,0.00019168395,0.00012071285,0.0003618673],"domain_scores_gemma":[0.99831504,0.00048180818,0.00006338899,0.0009836357,0.00006183688,0.00009431458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002590607,0.00019655626,0.00021637842,0.00022081146,0.00013883672,0.00001818315,0.0004363206,0.00010806388,0.000013904014],"category_scores_gemma":[0.000042011652,0.00021898918,0.000029063965,0.0003676518,0.00016868759,0.0006509014,0.00012545295,0.00032196168,0.000010683578],"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":[0.000031165884,0.00059040065,0.008635798,0.00020752066,0.000068914545,0.000007721929,0.003973374,0.61361384,0.0030557518,0.0073311087,0.0010395927,0.36144477],"study_design_scores_gemma":[0.002196786,0.00009065066,0.11356018,0.0003022446,0.00004881331,0.000014463618,0.0006006488,0.60902685,0.00073443964,0.0030639777,0.26905397,0.0013069551],"about_ca_topic_score_codex":0.0000065146305,"about_ca_topic_score_gemma":0.0023113817,"teacher_disagreement_score":0.6543876,"about_ca_system_score_codex":0.00012974234,"about_ca_system_score_gemma":0.000010075197,"threshold_uncertainty_score":0.893012},"labels":[],"label_agreement":null},{"id":"W2149443466","doi":"10.1109/icassp.2006.1661085","title":"Stochastic Learning Algorithms for Adaptive Modulation","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Link adaptation; Convexity; Fading; Modulation (music); Coding (social sciences); Wireless; Tracking error; Optimization problem; Algorithm; Artificial intelligence; Control (management); Mathematics; Decoding methods; Telecommunications","score_opus":0.010460542898167051,"score_gpt":0.2140258148462042,"score_spread":0.20356527194803714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149443466","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":[0.0018130677,0.000047182733,0.9955428,0.0000055188693,0.000109958535,0.00018404452,0.0000013778138,0.00048936,0.0018066396],"genre_scores_gemma":[0.85376793,0.0000018672165,0.14542747,0.000002750777,0.0001724807,0.000039011218,0.000048082078,0.000028638497,0.0005117932],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996273,0.00000391984,0.00009969649,0.0000856898,0.00005204859,0.00013136848],"domain_scores_gemma":[0.9998405,0.000048110996,0.000015816819,0.00004542855,0.000035546902,0.000014607477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000027007338,0.0000729376,0.00006591952,0.00003618223,0.000046855104,0.000009850315,0.000024558056,0.00003718283,0.000012593742],"category_scores_gemma":[0.0000066064185,0.00007882313,0.000020220838,0.00008918139,0.000006432839,0.00011891616,0.000004166729,0.000049836468,0.0000070149867],"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":[0.0000031032516,0.000002732081,0.0000076274923,0.000003292529,0.0000036958804,7.9337504e-8,0.000010584117,0.9821183,0.00019816407,0.002141662,0.00015026018,0.015360494],"study_design_scores_gemma":[0.00018628345,0.000017480386,0.0001942476,0.000005581645,0.0000038722687,4.738451e-7,0.000014715522,0.9975422,0.00023327295,0.0015352994,0.00016827144,0.000098299686],"about_ca_topic_score_codex":0.0000045589322,"about_ca_topic_score_gemma":0.000006009024,"teacher_disagreement_score":0.8519549,"about_ca_system_score_codex":0.000046412337,"about_ca_system_score_gemma":0.000002225541,"threshold_uncertainty_score":0.32143137},"labels":[],"label_agreement":null},{"id":"W2149585730","doi":"10.1109/qshine.2004.33","title":"On robust allocation policies in wireless heterogeneous networks","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Ottawa; Queen's University","funders":"","keywords":"Computer science; Wireless network; Resource management (computing); Resource allocation; Wireless; Radio resource management; Computer network; Resource (disambiguation); Heterogeneous network; Work (physics); Distributed computing; Risk analysis (engineering); Telecommunications; Business; Engineering","score_opus":0.007781827648172298,"score_gpt":0.20121441149369346,"score_spread":0.19343258384552117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149585730","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":[0.24928053,0.00007357271,0.7480908,0.000049635633,0.00015245302,0.00012477716,4.1548716e-7,0.00034935726,0.0018784513],"genre_scores_gemma":[0.9961615,0.00022415938,0.0032910528,0.00012529091,0.00008237712,0.000023426224,0.00002004715,0.00004141641,0.000030732524],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936646,0.00000803955,0.00017245572,0.00012897927,0.000083094994,0.00024095621],"domain_scores_gemma":[0.9997477,0.000024999132,0.00001677427,0.00015514232,0.00001563909,0.000039738316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000032687352,0.00013004344,0.000110881956,0.00009291868,0.000026914766,0.00001832589,0.00007971625,0.000083814964,0.000015537984],"category_scores_gemma":[0.000004217172,0.00013678543,0.000021121747,0.0002784862,0.000015365938,0.00010443127,0.000010966129,0.000116472125,0.000018180484],"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":[0.000004770885,0.000016730133,0.00006186157,0.000004958571,0.000004488748,0.0000033136484,0.000048350583,0.99114674,0.0000832217,0.0062297755,0.000037733014,0.0023580638],"study_design_scores_gemma":[0.00033791878,0.000021413422,0.00032404,0.000040717972,0.0000017350128,0.000003873791,0.00001138873,0.9968359,0.001687424,0.00055450335,0.000019325393,0.00016178824],"about_ca_topic_score_codex":0.000030952626,"about_ca_topic_score_gemma":0.0002945451,"teacher_disagreement_score":0.74688095,"about_ca_system_score_codex":0.00020206562,"about_ca_system_score_gemma":0.0000058810497,"threshold_uncertainty_score":0.5577948},"labels":[],"label_agreement":null},{"id":"W2149814880","doi":"10.1109/vetecs.2003.1207793","title":"High throughput downlink cellular packet data access with multiple antennas and multiuser diversity","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Alberta","funders":"","keywords":"Computer science; Precoding; Computer network; Telecommunications link; MIMO; Channel state information; Throughput; Base station; Network packet; Transmitter; Diversity gain; Fading; Transmit diversity; Scheduling (production processes); Channel (broadcasting); Electronic engineering; Telecommunications; Wireless; Engineering","score_opus":0.02419374668681163,"score_gpt":0.22242837904247753,"score_spread":0.1982346323556659,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149814880","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":[0.35603836,0.00013621566,0.6429388,0.000052339983,0.00009704536,0.0001735551,0.00004185072,0.00037271684,0.00014915167],"genre_scores_gemma":[0.9313028,0.00029058364,0.06802959,0.000045762525,0.000066223874,0.000002828555,0.00020348931,0.000032671574,0.000026058602],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916047,0.00000992663,0.000116566225,0.0003119238,0.00017122517,0.00022989945],"domain_scores_gemma":[0.9992768,0.000031917276,0.000026820298,0.0005384758,0.000050469203,0.00007548308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006647782,0.00017298001,0.0001599966,0.00003766025,0.0001479617,0.000054724358,0.0003646022,0.00006916991,0.000027074699],"category_scores_gemma":[0.000012590557,0.00014598141,0.000010163769,0.00018117044,0.000056604687,0.0011377243,0.0006845326,0.00012218856,0.000009240106],"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":[0.000016206535,0.000021889247,0.0120143555,0.000023066723,0.000039248203,0.000014862286,0.00011656308,0.9862228,0.00022812805,0.00011153858,0.0001628505,0.001028479],"study_design_scores_gemma":[0.0039305654,0.000035385317,0.011057296,0.000071653274,0.00007601663,0.000008079327,0.00011970049,0.9768548,0.0064065675,0.00038251284,0.00046803648,0.0005893666],"about_ca_topic_score_codex":0.00028888226,"about_ca_topic_score_gemma":0.0006707185,"teacher_disagreement_score":0.57526445,"about_ca_system_score_codex":0.000052634598,"about_ca_system_score_gemma":0.000008706168,"threshold_uncertainty_score":0.5952949},"labels":[],"label_agreement":null},{"id":"W2150115251","doi":"10.1109/wimob.2008.72","title":"Impact of Wireless Channel on VoIP QoS and Admission Regions in IEEE 802.11g WLANs","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer network; Computer science; Voice over IP; Physical layer; Wireless network; Quality of service; Wireless; Link adaptation; Network packet; Wireless Multimedia Extensions; Channel (broadcasting); IEEE 802.11; IEEE 802; Network allocation vector; Wi-Fi array; Fading; Telecommunications","score_opus":0.016849629569446915,"score_gpt":0.24416564329840815,"score_spread":0.22731601372896124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150115251","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":[0.90833473,0.0000735072,0.089694306,0.000023728573,0.00010642583,0.00015113968,0.0000045854013,0.00014103473,0.0014705556],"genre_scores_gemma":[0.9979724,0.000941377,0.0008131203,0.000010190338,0.00006132707,0.000008489927,0.000008813918,0.000031914944,0.00015232542],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939626,0.00001326728,0.0001786722,0.00013356144,0.00009008604,0.00018812994],"domain_scores_gemma":[0.99965984,0.000047789734,0.000029175804,0.00015724958,0.000021227317,0.00008472673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000030297968,0.00013429993,0.00018007668,0.00013329776,0.000032694013,0.000003109527,0.00005600846,0.0000840118,0.000018437915],"category_scores_gemma":[0.000010091966,0.000117320975,0.000036251357,0.0002495732,0.00002815999,0.00011638715,0.000009779337,0.00011790636,0.0000034725765],"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":[0.000022946831,0.00003318726,0.0025885068,0.000015999234,0.000008534783,0.000008079035,0.00028347646,0.9935463,0.0015508971,0.00006811248,0.0011562007,0.0007177765],"study_design_scores_gemma":[0.0006516537,0.0001317865,0.021557156,0.00013419037,0.0000039581096,0.00001896245,0.000036026904,0.97370833,0.0034244654,0.000085647735,0.000032661,0.00021518677],"about_ca_topic_score_codex":0.00003799968,"about_ca_topic_score_gemma":0.000030680494,"teacher_disagreement_score":0.08963773,"about_ca_system_score_codex":0.000069751884,"about_ca_system_score_gemma":0.00001470111,"threshold_uncertainty_score":0.47842106},"labels":[],"label_agreement":null},{"id":"W2150156233","doi":"10.1109/icc.2008.32","title":"Downlink Performance for Mixed Web/VoIP Traffic in 1xEVDO Revision A Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"","keywords":"Computer science; Computer network; Quality of service; Voice over IP; Telecommunications link; Web traffic; Scheduling (production processes); Traffic generation model; Network packet; Queue; Queueing theory; Erlang (programming language); Distributed computing; Real-time computing; Engineering; The Internet","score_opus":0.00950993197167136,"score_gpt":0.20156151329578997,"score_spread":0.19205158132411862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150156233","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":[0.5166951,0.0007048056,0.48062992,0.000026280906,0.00031592703,0.00043636872,0.0000015629658,0.00046413546,0.0007259493],"genre_scores_gemma":[0.96430826,0.0037871231,0.031357396,0.00003421079,0.00017710308,0.000052630952,0.000043342923,0.000048568967,0.00019135147],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991259,0.000011077318,0.0002857561,0.0001799161,0.000072726936,0.00032462395],"domain_scores_gemma":[0.99963766,0.00007368228,0.00002714176,0.0001784343,0.00003199502,0.000051076764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009798209,0.00015849604,0.00019706055,0.000092104914,0.00006962215,0.000008820132,0.00010337313,0.00011732829,0.000027656237],"category_scores_gemma":[0.00001280545,0.00015643174,0.00004550349,0.0003539375,0.000020755097,0.00022544138,0.000013715886,0.00015266467,0.000012797363],"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":[0.000017191496,0.000010956651,0.0002622407,0.00003621085,0.000003759866,0.0000016336468,0.000044439097,0.9528784,0.000024283267,0.00003063044,0.002335372,0.044354863],"study_design_scores_gemma":[0.0006387962,0.000033109212,0.0006701428,0.00006984321,0.0000031332113,0.0000074474397,0.0000084253925,0.9940148,0.0000910711,0.00000423981,0.0042615565,0.00019746224],"about_ca_topic_score_codex":4.587459e-7,"about_ca_topic_score_gemma":0.000016990052,"teacher_disagreement_score":0.4492725,"about_ca_system_score_codex":0.00007711017,"about_ca_system_score_gemma":0.000010681215,"threshold_uncertainty_score":0.63791007},"labels":[],"label_agreement":null},{"id":"W2150539462","doi":"10.1109/wcnc.2007.411","title":"Queue-Aware Power Allocation for Space-Time Block Coded MIMO Systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia; University of Manitoba","funders":"","keywords":"Computer science; Retransmission; Link adaptation; Hybrid automatic repeat request; Network packet; Computer network; MIMO; Queue; Transmitter power output; Automatic repeat request; Queueing theory; Quality of service; Space–time block code; Real-time computing; Fading; Queue management system; Channel (broadcasting); Telecommunications link; Transmitter","score_opus":0.005578205897447283,"score_gpt":0.2129457594729135,"score_spread":0.2073675535754662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150539462","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":[0.006645877,0.0002151831,0.9865277,0.000041741856,0.0004794597,0.00057678844,0.0000066296952,0.0007700322,0.0047365795],"genre_scores_gemma":[0.9774626,0.000023621635,0.019148337,0.000026794554,0.00016490412,0.000044519827,0.000072525916,0.00007432039,0.0029823708],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991787,0.000007121346,0.0002452187,0.00015912084,0.0001140407,0.0002958047],"domain_scores_gemma":[0.9994785,0.0000980237,0.000038662925,0.00019682397,0.00011578506,0.000072158364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016037031,0.0001481167,0.00015595327,0.000075637385,0.00004854477,0.000027185572,0.00008001789,0.00011675274,0.000033985234],"category_scores_gemma":[0.000016305421,0.00015316122,0.000037590984,0.0001781876,0.000011153203,0.00014843345,0.0000095778,0.00006226293,0.00006523629],"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":[0.000012206594,0.000009269655,0.000020308365,0.00004219783,0.000020772828,7.390536e-7,0.000060660284,0.98916525,0.0034505858,0.0011240081,0.0058128876,0.00028110016],"study_design_scores_gemma":[0.0003379975,0.000024381763,0.000035721532,0.0000348788,0.000010211999,0.0000039174115,0.00009961232,0.98561984,0.005639841,0.000026284453,0.007953431,0.00021389991],"about_ca_topic_score_codex":0.0000068785084,"about_ca_topic_score_gemma":0.000015887232,"teacher_disagreement_score":0.97081673,"about_ca_system_score_codex":0.00012019913,"about_ca_system_score_gemma":0.000008190213,"threshold_uncertainty_score":0.62457335},"labels":[],"label_agreement":null},{"id":"W2150588967","doi":"10.1109/lcomm.2009.081471","title":"Resource allocation for non-real-time services in OFDM-based cognitive radio systems","year":2009,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":51,"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","funders":"","keywords":"Cognitive radio; Orthogonal frequency-division multiplexing; Computer science; Resource allocation; Throughput; Resource management (computing); Real-time computing; Computer network; Telecommunications; Wireless; Channel (broadcasting)","score_opus":0.011015170029863467,"score_gpt":0.24081327119715937,"score_spread":0.2297981011672959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150588967","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":[0.112559415,0.00057173846,0.8781585,0.0038079838,0.0001686635,0.0019199966,0.00005595429,0.000715802,0.0020419494],"genre_scores_gemma":[0.98052096,0.00014138213,0.017788207,0.0005124793,0.00006370637,0.00028950555,0.0006263299,0.000042374173,0.000015060638],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999146,0.00007357802,0.00031348295,0.00015701573,0.00008555116,0.00022435823],"domain_scores_gemma":[0.9986641,0.00036429593,0.000083389416,0.0007766657,0.00006877492,0.000042766704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015903037,0.00015714273,0.00018874562,0.00018167803,0.000117805626,0.00004538071,0.00049237505,0.00007519634,0.0000013690649],"category_scores_gemma":[0.000009517199,0.00019461139,0.00004122093,0.0003756977,0.000043323635,0.000204811,0.000013082592,0.00014357561,0.000014129758],"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":[0.000012870827,0.000035055462,0.00007148144,0.000043886645,0.000013554694,2.3013969e-7,0.00027228618,0.973536,0.023351183,0.00010555343,0.00061261974,0.0019452474],"study_design_scores_gemma":[0.0006876343,0.000018963277,0.00058643287,0.00027309195,0.000019603855,6.2633615e-7,0.000074870215,0.99599415,0.000979907,0.00001881879,0.0011441443,0.00020173482],"about_ca_topic_score_codex":0.0000260373,"about_ca_topic_score_gemma":0.000023543847,"teacher_disagreement_score":0.8679615,"about_ca_system_score_codex":0.00017115992,"about_ca_system_score_gemma":0.000012572095,"threshold_uncertainty_score":0.7936022},"labels":[],"label_agreement":null},{"id":"W2150590285","doi":"10.1109/isit.2008.4595087","title":"Is it possible to achieve the optimum throughput and fairness simultaneously in a MIMO Broadcast Channel?","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"University of Waterloo","funders":"","keywords":"MIMO; Throughput; Computer science; Scheduling (production processes); Constraint (computer-aided design); Metric (unit); Performance metric; Channel (broadcasting); Fairness measure; Maximum throughput scheduling; Mathematical optimization; Computer network; Mathematics; Wireless; Telecommunications; Quality of service; Dynamic priority scheduling; Engineering","score_opus":0.018447649886502354,"score_gpt":0.24028502240998043,"score_spread":0.22183737252347807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150590285","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":[0.30151603,0.0006184119,0.6831768,0.002430151,0.0002755134,0.0008123757,0.0000109187,0.0004128045,0.010747001],"genre_scores_gemma":[0.9876397,0.0007435897,0.009468305,0.0006961909,0.00008541304,0.000035185636,0.000004847261,0.000048567217,0.0012781468],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910635,0.000016419084,0.00020213771,0.00022783375,0.000126681,0.0003205749],"domain_scores_gemma":[0.9995344,0.00010408934,0.000018002554,0.00023430395,0.000034883204,0.000074286385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000056595574,0.00018537774,0.00017517964,0.000071999086,0.00010414634,0.00002705467,0.00014513682,0.00007947095,0.00005350748],"category_scores_gemma":[0.000016834487,0.00014629029,0.000023973897,0.0004626491,0.00004348089,0.00019107091,0.00006424678,0.00015426801,0.00004216898],"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":[0.000018279357,0.000012054462,0.00012210482,0.000011946272,0.000009008947,0.000019040419,0.0036492767,0.9913819,0.00006404586,0.000053496686,0.00204778,0.0026110855],"study_design_scores_gemma":[0.00033850104,0.00005157195,0.00022824304,0.000035122248,0.0000038118424,0.000051946598,0.00050130225,0.9956531,0.00059324375,0.00011309737,0.002183111,0.00024694155],"about_ca_topic_score_codex":0.00004700758,"about_ca_topic_score_gemma":0.00012106093,"teacher_disagreement_score":0.6861237,"about_ca_system_score_codex":0.000053461736,"about_ca_system_score_gemma":0.000010180555,"threshold_uncertainty_score":0.59655446},"labels":[],"label_agreement":null},{"id":"W2150639054","doi":"10.1109/icbn.2005.1589651","title":"Opportunistic performance enhancement of reservation multiple access protocols of wireless broadband networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University","funders":"","keywords":"Computer science; Reservation; Computer network; Frame (networking); Resource allocation; Throughput; Controller (irrigation); Wireless broadband; Broadband networks; Access control; Transmission (telecommunications); Distributed computing; Broadband; Wireless network; Wireless; Telecommunications","score_opus":0.03153711983972721,"score_gpt":0.27664881792591545,"score_spread":0.24511169808618824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150639054","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":[0.18105489,0.000029251003,0.8133546,0.000012147418,0.000051054652,0.0034550575,0.000002501402,0.00009828739,0.0019421871],"genre_scores_gemma":[0.9857042,0.00022231117,0.01227945,0.00001268097,0.00007675294,0.0014599778,0.000043910855,0.000029872432,0.00017085172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989653,0.000013574503,0.0005021533,0.00013281823,0.00018655311,0.00019957726],"domain_scores_gemma":[0.99935895,0.00005304197,0.00014979187,0.00025905395,0.00013425147,0.00004488353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001237001,0.00013416751,0.00022429791,0.00006784757,0.000029976318,0.000011979431,0.00020991913,0.00007207073,0.00009883304],"category_scores_gemma":[0.000012785264,0.00013440834,0.00002837364,0.00028109868,0.00003775899,0.0005205519,0.00004548468,0.00008743584,0.0000015612198],"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":[0.00003780555,0.0000433221,0.0050587174,0.00021066418,0.000014576591,1.2269219e-7,0.00003291042,0.9509158,0.0038946217,0.0001293741,0.0002627647,0.0393993],"study_design_scores_gemma":[0.0004296215,0.000045413864,0.0015613429,0.0001698512,0.0000055889536,3.2556756e-7,0.0000051685843,0.91348165,0.08359075,0.0000067123983,0.0005802597,0.0001232813],"about_ca_topic_score_codex":0.0000051996444,"about_ca_topic_score_gemma":0.000018760635,"teacher_disagreement_score":0.8046493,"about_ca_system_score_codex":0.0000577553,"about_ca_system_score_gemma":0.00001728643,"threshold_uncertainty_score":0.5481013},"labels":[],"label_agreement":null},{"id":"W2150773600","doi":"10.1109/twc.2009.070995","title":"A flexible resource allocation and scheduling framework for non-real-time polling service in IEEE 802.16 networks","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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":"Goodput; Computer science; Polling; Computer network; Network packet; Scheduling (production processes); IEEE 802.11; IEEE 802; Distributed computing; Throughput; Real-time computing; Quality of service; Wireless","score_opus":0.017451634185412714,"score_gpt":0.2645289371755316,"score_spread":0.2470773029901189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150773600","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":[0.019778732,0.0002810402,0.9769712,0.0010984452,0.00014024261,0.00076428213,0.000019524516,0.00059977314,0.00034677816],"genre_scores_gemma":[0.85939467,0.0031065627,0.13674043,0.00022387931,0.00006656768,0.00028209502,0.000062511106,0.00008304047,0.000040258205],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984821,0.000076446544,0.00053227844,0.00032757453,0.00014469042,0.00043692553],"domain_scores_gemma":[0.9977482,0.00071634597,0.00010296371,0.0011863734,0.00012133931,0.00012477218],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023439732,0.00031131794,0.00033983839,0.00031391848,0.00050671527,0.00008218825,0.0005256712,0.00030979118,0.0000075325506],"category_scores_gemma":[0.0000071414947,0.0003937978,0.00007776312,0.0011376723,0.00006459195,0.00036319625,0.0000042187403,0.0006846195,0.0000097255825],"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":[0.00004132899,0.00011981372,0.0000047223934,0.0000303021,0.00002822216,1.9252906e-7,0.00042301795,0.96184117,0.0024542669,0.0013143749,0.000019787565,0.033722833],"study_design_scores_gemma":[0.00058160006,0.000050773077,0.00006708019,0.00044103243,0.000042191245,0.000003222516,0.0001513593,0.9940907,0.003211238,0.0008469023,0.00014560203,0.00036829637],"about_ca_topic_score_codex":0.000035806057,"about_ca_topic_score_gemma":0.0001927754,"teacher_disagreement_score":0.84023076,"about_ca_system_score_codex":0.00026269685,"about_ca_system_score_gemma":0.00003244135,"threshold_uncertainty_score":0.9998514},"labels":[],"label_agreement":null},{"id":"W2150859918","doi":"10.1109/cnsr.2011.48","title":"Credit-Based Flow Control for Multihop Wireless Networks and Stochastic Petri Nets Analysis","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Petri net; Computer network; Wireless network; Stochastic Petri net; Wireless; Flow control (data); Distributed computing; Control (management); Telecommunications; Artificial intelligence","score_opus":0.009918858983346024,"score_gpt":0.19671090689137455,"score_spread":0.18679204790802853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150859918","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":[0.0038487017,0.00026444957,0.9946403,0.000010322852,0.000234754,0.000421243,0.000018320941,0.0004009056,0.00016103685],"genre_scores_gemma":[0.93801415,0.000020474337,0.061507437,0.00006761806,0.00012491862,0.00011096425,0.00006803048,0.000052247786,0.000034129065],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905276,0.000016326434,0.00025246182,0.00024342234,0.00009300027,0.00034205551],"domain_scores_gemma":[0.9992817,0.00024638168,0.00004723269,0.00021796755,0.000084157844,0.00012257324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000095964366,0.00021080505,0.0003385989,0.00018671059,0.00007293961,0.00002357154,0.00009476865,0.000119974284,0.00006892507],"category_scores_gemma":[0.000023654091,0.00020884928,0.00009893611,0.00047779814,0.00003789542,0.00012948077,0.000010183701,0.00010095647,0.0000019524857],"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":[0.000057795867,0.000016121296,0.00039450754,0.000013838352,0.00024278103,0.0000010895208,0.00003516005,0.99252,0.000018384037,0.00009018487,0.00019390005,0.006416267],"study_design_scores_gemma":[0.0014232319,0.000038760612,0.00084083696,0.00001056505,0.0003485749,4.877371e-7,0.000014489556,0.9969646,0.000056132565,0.000027953456,0.000029127777,0.00024528478],"about_ca_topic_score_codex":0.000010565944,"about_ca_topic_score_gemma":0.00007602588,"teacher_disagreement_score":0.9341655,"about_ca_system_score_codex":0.000036249043,"about_ca_system_score_gemma":0.000007566741,"threshold_uncertainty_score":0.85166264},"labels":[],"label_agreement":null},{"id":"W2150907023","doi":"10.1109/ccece.2009.5090232","title":"Frequency-time scheduling algorithm for OFDMA systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Orthogonal frequency-division multiple access; Frequency-division multiple access; Scheduling (production processes); Algorithm; Orthogonal frequency-division multiplexing; Fairness measure; Exploit; Wireless; Diversity scheme; Real-time computing; Computer network; Throughput; Fading; Mathematical optimization; Decoding methods; Mathematics; Telecommunications","score_opus":0.005728064073968303,"score_gpt":0.20613461860620297,"score_spread":0.20040655453223466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150907023","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":[0.0009671501,0.000985024,0.9940459,0.000033774497,0.00029383667,0.00028581303,0.0000074077607,0.00080799893,0.0025730678],"genre_scores_gemma":[0.09743362,0.00014479028,0.901023,0.000051100986,0.00046106058,0.00006488722,0.00003985117,0.000047857524,0.0007338854],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994203,0.000004701452,0.0001693358,0.000118365664,0.00007014206,0.00021714841],"domain_scores_gemma":[0.99973375,0.000030952986,0.000019943847,0.00011988071,0.000048564165,0.00004690444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005107802,0.00011207424,0.00013713546,0.00004504729,0.00004153583,0.000029122457,0.000075750984,0.00007016902,0.000027029402],"category_scores_gemma":[0.0000065703575,0.00011344688,0.00003317805,0.00012947309,0.0000054029692,0.00017373993,0.0000033924307,0.00005452584,0.000028951608],"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":[3.8837388e-7,0.0000046214454,0.0000031436682,0.000010006567,0.000009359762,5.029502e-7,0.000010392027,0.92677397,0.002441556,0.00096347753,0.00032867453,0.069453895],"study_design_scores_gemma":[0.0001817946,0.000016626213,0.000010086133,0.000033076656,0.000006960353,0.0000019394206,0.000010193291,0.9976753,0.0011680903,0.00045034772,0.00029749234,0.00014809675],"about_ca_topic_score_codex":0.0000016275578,"about_ca_topic_score_gemma":2.2931745e-7,"teacher_disagreement_score":0.09646647,"about_ca_system_score_codex":0.000051599185,"about_ca_system_score_gemma":0.0000054610687,"threshold_uncertainty_score":0.4626229},"labels":[],"label_agreement":null},{"id":"W2150919096","doi":"10.1109/twc.2011.021611.101864","title":"QoS, Channel and Energy-Aware Packet Scheduling over Multiple Channels","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Computer science; Network packet; Quality of service; Scheduling (production processes); Computer network; Robustness (evolution); Efficient energy use; Channel (broadcasting); Link adaptation; Distributed computing; Fading; Mathematical optimization","score_opus":0.031067643463632014,"score_gpt":0.2322690933870598,"score_spread":0.2012014499234278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150919096","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":[0.01355372,0.00045725156,0.98365945,0.00006609906,0.00060839346,0.0001587833,0.00006176464,0.00072393235,0.00071061094],"genre_scores_gemma":[0.98291373,0.0054364814,0.011001597,0.00006929696,0.00005390747,0.0002703245,0.000037513808,0.00010371141,0.000113421695],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988724,0.000070950904,0.00033282995,0.0002567494,0.0001388544,0.00032822968],"domain_scores_gemma":[0.9983158,0.00019047655,0.00006358443,0.0012009903,0.000081555976,0.00014755393],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000077280834,0.00028376587,0.0002436997,0.00022059714,0.0004758782,0.000039154336,0.00046027484,0.00017319713,0.000046599067],"category_scores_gemma":[0.000002311448,0.00032983275,0.00007884947,0.00042341047,0.00016236067,0.0003895439,0.000009767846,0.0004036352,0.00001610918],"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":[0.000026666263,0.00025110136,0.000039424147,0.000032708405,0.00012639731,0.000001666966,0.0015125696,0.95506424,0.000774963,0.0009956731,0.00008242755,0.04109219],"study_design_scores_gemma":[0.00046656872,0.000031401258,0.000068473666,0.000101700534,0.000038030852,0.0000067036462,0.0001981221,0.9905122,0.007512288,0.00019034548,0.00050737854,0.00036682386],"about_ca_topic_score_codex":0.00007398118,"about_ca_topic_score_gemma":0.00031000955,"teacher_disagreement_score":0.97265786,"about_ca_system_score_codex":0.00008469938,"about_ca_system_score_gemma":0.000016362916,"threshold_uncertainty_score":0.99991536},"labels":[],"label_agreement":null},{"id":"W2151455170","doi":"10.1109/glocom.1998.775996","title":"First-order Markov modeling for the Rayleigh fading channel","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University","funders":"","keywords":"Fading; Markov chain; Channel state information; Rayleigh fading; Autocorrelation; Fading distribution; Markov model; Metric (unit); Markov process; Computer science; Variable-order Markov model; Channel (broadcasting); Statistical physics; Algorithm; Markov property; Mathematics; Statistics; Telecommunications; Engineering; Physics; Wireless","score_opus":0.020636349352949664,"score_gpt":0.20261114687415568,"score_spread":0.18197479752120602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151455170","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":[0.0003369259,0.00088162994,0.9939051,0.00024169352,0.0002921155,0.0002703523,0.0000016356647,0.00036444623,0.0037060755],"genre_scores_gemma":[0.93907315,0.000973409,0.058441583,0.000086881635,0.00025926347,0.0001225004,0.0000048828942,0.00006352079,0.00097483274],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944746,0.0000030585375,0.00013320161,0.000112401176,0.00006800313,0.0002358711],"domain_scores_gemma":[0.99963766,0.00012428386,0.00001214413,0.0001581794,0.000039725714,0.000028017887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052567255,0.00011131835,0.00008698139,0.000031251366,0.00015495584,0.000024890465,0.000106566076,0.000049164937,0.00015782341],"category_scores_gemma":[0.000019671716,0.000085670465,0.000036755773,0.0001633525,0.0000078852545,0.00014115899,0.000015472408,0.00007266607,0.00001610958],"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":[0.0000016159838,0.0000031083905,0.000002151541,0.000015456788,0.000014570224,1.5507544e-7,0.00012561069,0.99467576,0.000011068472,0.00026865813,0.0017386986,0.0031431268],"study_design_scores_gemma":[0.00019278124,0.0000046554205,8.5863974e-7,0.000013114541,0.000008763433,0.0000011217376,0.000049091464,0.99734426,0.00005120897,0.00022487933,0.0019849613,0.0001242863],"about_ca_topic_score_codex":0.0000020574248,"about_ca_topic_score_gemma":0.0000120217255,"teacher_disagreement_score":0.9387362,"about_ca_system_score_codex":0.000033781518,"about_ca_system_score_gemma":8.693189e-7,"threshold_uncertainty_score":0.34935403},"labels":[],"label_agreement":null},{"id":"W2151523666","doi":"10.1109/surv.2009.090307","title":"Radio Resource Allocation Algorithms for the Downlink of Multiuser OFDM Communication Systems","year":2009,"lang":"en","type":"article","venue":"IEEE Communications Surveys & Tutorials","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":270,"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":"Computer science; Telecommunications link; Orthogonal frequency-division multiplexing; Resource allocation; Transmitter power output; Spectral efficiency; Algorithm; Wireless; Resource management (computing); Constraint (computer-aided design); Throughput; Mathematical optimization; Distributed computing; Computer network; Transmitter; Telecommunications; Mathematics; Channel (broadcasting)","score_opus":0.04478977894019657,"score_gpt":0.2929825962200351,"score_spread":0.24819281727983852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151523666","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":[0.0020211183,0.012625308,0.9792687,0.0008661305,0.0013294991,0.002247306,0.00013305938,0.0005290444,0.000979794],"genre_scores_gemma":[0.9599469,0.0050815837,0.03343637,0.000026801574,0.00035321945,0.00039926398,0.0005755366,0.00006104454,0.00011928869],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972549,0.0011432447,0.0009050968,0.00018830007,0.00024279246,0.00026563977],"domain_scores_gemma":[0.9922628,0.0033070468,0.0003463385,0.0035271663,0.00049956696,0.00005710465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034377535,0.00023354194,0.00039606803,0.00011999634,0.00042617254,0.00007371192,0.0016584465,0.00018416776,0.0000031819898],"category_scores_gemma":[0.0003109972,0.00021359607,0.0001075168,0.0005650369,0.00019148589,0.0003042072,0.00006370711,0.0002565633,0.0000071403624],"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":[0.000012118615,0.000078320256,0.000031027415,0.000024122506,0.000081911574,3.5136566e-8,0.00050487876,0.9677663,0.0029880665,0.005696986,0.0027733594,0.020042868],"study_design_scores_gemma":[0.0008547352,0.00005184594,0.001467601,0.00012971845,0.000095875446,0.0000025431978,0.00022911743,0.9277842,0.0020090071,0.0004216322,0.06660746,0.00034623055],"about_ca_topic_score_codex":0.00007882636,"about_ca_topic_score_gemma":0.00005987864,"teacher_disagreement_score":0.9579258,"about_ca_system_score_codex":0.000175657,"about_ca_system_score_gemma":0.00004151998,"threshold_uncertainty_score":0.8710195},"labels":[],"label_agreement":null},{"id":"W2152262955","doi":"10.1109/wcnc.2008.150","title":"Haar Compression for Efficient CQI Feedback Signaling in 3GPP LTE Systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"InterDigital (Canada)","funders":"","keywords":"Computer science; Telecommunications link; Scheduling (production processes); Computer network; Overhead (engineering); Real-time computing; Throughput; Base station; Channel (broadcasting); Wireless; Engineering; Telecommunications","score_opus":0.015297349751050677,"score_gpt":0.21113496643285554,"score_spread":0.19583761668180485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152262955","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":[0.18466172,0.00050524133,0.8126711,0.0000064518645,0.00037499383,0.00040797942,0.0000027237957,0.00029926375,0.0010705132],"genre_scores_gemma":[0.9829989,0.000057830424,0.016521877,0.0000093424105,0.000096652475,0.00005816364,0.000018824707,0.000040641968,0.00019778065],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992553,0.00001278556,0.00024526383,0.00014505874,0.00010598568,0.00023560117],"domain_scores_gemma":[0.9996843,0.00008381891,0.000027483735,0.00012574575,0.00003464242,0.000044014465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000067240595,0.000120144105,0.00016800984,0.000078296136,0.00006358974,0.000011977952,0.000075227894,0.00006661903,0.000010984315],"category_scores_gemma":[0.000008640835,0.000115538765,0.000029935984,0.00018085247,0.0000138015475,0.00007001555,0.000014685239,0.00007705697,0.000013403859],"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":[0.000009175613,0.000014071248,0.00014584625,0.000057300822,0.000004252107,0.0000024328476,0.00011348866,0.9949301,0.0037710515,0.00017960063,0.0005080684,0.00026463522],"study_design_scores_gemma":[0.0004899656,0.000011222142,0.0000942613,0.00011848272,0.0000022675051,0.000004162062,0.00005060992,0.9945621,0.0038223637,0.000007991721,0.00069085456,0.00014573247],"about_ca_topic_score_codex":0.0000072476714,"about_ca_topic_score_gemma":0.0000025768122,"teacher_disagreement_score":0.79833716,"about_ca_system_score_codex":0.000086136475,"about_ca_system_score_gemma":0.000005879294,"threshold_uncertainty_score":0.4711534},"labels":[],"label_agreement":null},{"id":"W2152313510","doi":"10.1002/wcm.807","title":"An efficient scheduling scheme with diverse traffic demands in IEEE 802.16 networks","year":2009,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer network; Computer science; Link adaptation; Rayleigh fading; Scheduling (production processes); Spectral efficiency; Fading; Channel (broadcasting); Engineering","score_opus":0.00917447228476516,"score_gpt":0.24259953356510622,"score_spread":0.23342506128034105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152313510","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":[0.6279541,0.0012827107,0.37011516,0.000013104586,0.000039468523,0.00021902786,8.217714e-7,0.00025825863,0.0001173376],"genre_scores_gemma":[0.9453649,0.0010403271,0.05340781,0.000029264855,0.000053784217,0.00002510807,0.000043727043,0.00003349097,0.0000016242984],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894226,0.0000628968,0.00031958503,0.0002406936,0.00010004222,0.000334532],"domain_scores_gemma":[0.9988797,0.000105516,0.00007463302,0.000782842,0.00005812968,0.00009923252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019608665,0.00020740816,0.00024221331,0.0001314075,0.00032132483,0.0000700083,0.00039591087,0.00009495327,0.0000017641868],"category_scores_gemma":[0.0000025321235,0.00021552695,0.000025185172,0.00050318986,0.00008985928,0.00015450132,0.000066382956,0.00037435297,9.269151e-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":[0.0000065462127,0.000086876644,0.00048424868,0.000009409754,0.0000075863313,0.0000013073724,0.0004735994,0.8795448,0.00011551412,0.0002716342,0.000002320561,0.11899619],"study_design_scores_gemma":[0.000535144,0.00008154816,0.00057130377,0.00020552763,0.000009062196,0.000007502733,0.0005010257,0.99773556,0.000025058003,0.0000057276447,0.00006124435,0.00026128942],"about_ca_topic_score_codex":0.000005134007,"about_ca_topic_score_gemma":0.000043802927,"teacher_disagreement_score":0.31741077,"about_ca_system_score_codex":0.00009999834,"about_ca_system_score_gemma":0.000013519051,"threshold_uncertainty_score":0.87889344},"labels":[],"label_agreement":null},{"id":"W2152413159","doi":"10.1109/glocom.2005.1578286","title":"AQuA: aggregated queueing algorithm for CDMA2000 base station controll","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Queueing theory; Base station; Network packet; Queue; Channel (broadcasting); CDMA2000; Buffer (optical fiber); Buffer overflow; Algorithm; Distributed computing; Telecommunications","score_opus":0.01595413676409905,"score_gpt":0.2582083014631412,"score_spread":0.24225416469904218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152413159","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":[0.002654138,0.0018072807,0.98039544,0.0010114,0.0006225568,0.0014002004,0.0009542547,0.0013347531,0.009819991],"genre_scores_gemma":[0.5214986,0.0028763688,0.47203666,0.0003847955,0.00035136828,0.0005639809,0.0015819513,0.00010371832,0.00060256507],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971357,0.0001591516,0.0009797339,0.0004800309,0.00029034232,0.0009550185],"domain_scores_gemma":[0.99736327,0.00026101968,0.0002882694,0.0012967568,0.0004979263,0.00029276326],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00031788633,0.0005421606,0.0005713121,0.0001868428,0.0004906719,0.00020770852,0.00096389116,0.00030763072,0.00018346062],"category_scores_gemma":[0.00007017591,0.000641409,0.00018047878,0.0007378069,0.00013931564,0.00087116373,0.000079390615,0.00039061176,0.00018135819],"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":[0.000022781502,0.00012975655,0.00003972857,0.00001906996,0.000115596005,0.0000014552365,0.000072342664,0.551084,0.00011883648,0.0028361168,0.019680286,0.42588004],"study_design_scores_gemma":[0.0019646455,0.000049517505,0.000098036784,0.000083150175,0.000074852585,0.000019036881,0.000082358754,0.89298433,0.0005417658,0.0010895699,0.10240802,0.0006047403],"about_ca_topic_score_codex":0.00014702987,"about_ca_topic_score_gemma":0.0019062695,"teacher_disagreement_score":0.5188444,"about_ca_system_score_codex":0.00094493595,"about_ca_system_score_gemma":0.00021920411,"threshold_uncertainty_score":0.99960375},"labels":[],"label_agreement":null},{"id":"W2152831210","doi":"10.1109/wcnc.2011.5779129","title":"Queue-aware adaptive resource allocation for OFDMA systems supporting mixed services","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"","keywords":"Computer science; Queue; Resource allocation; Distributed computing; Upper and lower bounds; Queueing theory; Set (abstract data type); Resource management (computing); Throughput; Mathematical optimization; Computer network; Wireless; Telecommunications; Mathematics","score_opus":0.019496637271568085,"score_gpt":0.21224152471192378,"score_spread":0.1927448874403557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152831210","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":[0.013498264,0.00023326967,0.98071223,0.000012055023,0.00028959563,0.000547593,0.000011760554,0.0007514385,0.003943792],"genre_scores_gemma":[0.97946495,0.00002618139,0.019628301,0.000022264165,0.00013148884,0.00021868988,0.00008341759,0.00006325066,0.00036143628],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991941,0.000016540745,0.00028139434,0.00017231175,0.000088334236,0.00024733503],"domain_scores_gemma":[0.9995444,0.00004754847,0.000087752785,0.00016296165,0.00010394537,0.000053416097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011144132,0.00014003985,0.00014925245,0.00005501781,0.000062192186,0.000019809213,0.00011636656,0.00008736257,0.000027027727],"category_scores_gemma":[0.0000052705486,0.00014164715,0.000033194523,0.00013497779,0.00000949879,0.0002491154,0.000017600982,0.000057931033,0.000009833891],"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":[0.000020062877,0.000009868754,0.00019230683,0.0002197936,0.00003635086,5.8291533e-7,0.0007285391,0.9917667,0.00027373596,0.0023983433,0.0005063233,0.0038474204],"study_design_scores_gemma":[0.00018758966,0.000026316364,0.00015411114,0.00008832794,0.000017797334,0.0000013242056,0.001758609,0.9927995,0.0034216458,0.00007319176,0.0012911916,0.00018035535],"about_ca_topic_score_codex":0.00006300409,"about_ca_topic_score_gemma":0.00007614072,"teacher_disagreement_score":0.9659667,"about_ca_system_score_codex":0.000054639255,"about_ca_system_score_gemma":0.0000067490305,"threshold_uncertainty_score":0.5776203},"labels":[],"label_agreement":null},{"id":"W2152904689","doi":"10.1109/spawc.2005.1506241","title":"Stochastic learning algorithms for adaptive modulation","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Link adaptation; Computer science; Modulation (music); Adaptive coding; Coding (social sciences); Wireless; Algorithm; Stochastic approximation; Mathematics; Fading; Decoding methods; Telecommunications","score_opus":0.01451742492764197,"score_gpt":0.23231572367949824,"score_spread":0.21779829875185627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152904689","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":[0.0012728901,0.000055922003,0.99682486,0.000019210891,0.00008336256,0.00018334015,0.000001024866,0.0004784514,0.0010809101],"genre_scores_gemma":[0.7454804,0.0000056302474,0.25385556,0.000008325608,0.000204126,0.00003448785,0.000017720136,0.000025381574,0.0003683379],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996274,0.0000039131514,0.00009641539,0.000086097614,0.00005207524,0.00013408561],"domain_scores_gemma":[0.9998278,0.000048051235,0.000014531088,0.000049734583,0.000033990014,0.00002587351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000032367592,0.00007307154,0.00006602533,0.000035944053,0.0000450288,0.00000867646,0.000028780496,0.000037390244,0.000027006969],"category_scores_gemma":[0.000012196087,0.00007875735,0.00002007287,0.00007677974,0.000005762717,0.00018119797,0.000005018037,0.000060123923,0.00001730759],"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":[0.000003314689,0.0000023072462,0.0000018071072,0.0000021936166,0.0000057126035,2.7482761e-8,0.000046695237,0.86921716,0.00010172569,0.00063869375,0.00008461362,0.12989575],"study_design_scores_gemma":[0.00019868388,0.000019265779,0.000041226147,0.000005891901,0.0000038699486,5.369113e-7,0.00002515482,0.9984937,0.00025141216,0.00018900713,0.0006727074,0.00009855318],"about_ca_topic_score_codex":4.833496e-7,"about_ca_topic_score_gemma":0.00000347753,"teacher_disagreement_score":0.74420756,"about_ca_system_score_codex":0.00006326149,"about_ca_system_score_gemma":0.0000025241422,"threshold_uncertainty_score":0.32116318},"labels":[],"label_agreement":null},{"id":"W2153089754","doi":"10.1109/aiccsa.2006.205116","title":"Performance Evaluation of Reservation Medium Access Control in IEEE 802.16 Networks","year":2006,"lang":"en","type":"article","venue":"IEEE International Conference on Computer Systems and Applications, 2006.","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":28,"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":"Computer science; Computer network; Reservation; Inter-Access Point Protocol; IEEE 802.11s; IEEE 802.11b-1999; Throughput; Protocol (science); Access control; Network allocation vector; IEEE 802; IEEE 802.1X; IEEE 802.11e-2005; IEEE 802.11; Quality of service; Wireless; Wireless network; Telecommunications; Wi-Fi; Wireless mesh network","score_opus":0.03837616016100308,"score_gpt":0.2907732811045759,"score_spread":0.2523971209435728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153089754","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":[0.08533011,0.00020409308,0.90938014,0.0000916661,0.0012622231,0.00087106775,0.000025482454,0.00008522286,0.0027500119],"genre_scores_gemma":[0.9974531,0.00025310018,0.00042622595,0.000030937823,0.0010991587,0.000552493,0.00011923244,0.000020756168,0.000045015993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998514,0.000060915463,0.0005607613,0.0002550541,0.0004490247,0.0001602775],"domain_scores_gemma":[0.99897736,0.00007267678,0.00019354312,0.00020544874,0.00051780423,0.000033139633],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041929632,0.00016685727,0.00021500773,0.00020133825,0.000045073026,0.00009909252,0.00028134522,0.00010259222,0.000011187584],"category_scores_gemma":[0.000002820672,0.0001757676,0.000023937475,0.00023745329,0.000036559573,0.00037836868,0.000015771908,0.00013745548,0.0000041035946],"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":[0.000013099565,0.000034277124,0.0042292103,0.000029986926,0.000015519114,1.726904e-7,0.000008371865,0.9788784,0.00015527703,0.004179501,0.001260372,0.01119586],"study_design_scores_gemma":[0.0007626122,0.000019383246,0.009769593,0.00017780239,0.000010603175,0.0000025226457,0.000006175707,0.9879045,0.00014385373,0.00020803155,0.0008392896,0.00015563561],"about_ca_topic_score_codex":0.000116816176,"about_ca_topic_score_gemma":0.00008479546,"teacher_disagreement_score":0.91212296,"about_ca_system_score_codex":0.00018409367,"about_ca_system_score_gemma":0.000034183726,"threshold_uncertainty_score":0.71675944},"labels":[],"label_agreement":null},{"id":"W2153578293","doi":"10.1109/glocom.2006.821","title":"WLC35-5: User-Aided Adaptive TDMA for Real-Time Services in an OFDM Based Cellular System","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Time division multiple access; Computer science; Orthogonal frequency-division multiplexing; Computer network; Channel (broadcasting); Channel allocation schemes; Spectral efficiency; Cellular network; Resource allocation; Real-time computing; Scheme (mathematics); Link adaptation; Distributed computing; Fading; Wireless; Telecommunications; Mathematics","score_opus":0.004712355726665208,"score_gpt":0.18881867967896956,"score_spread":0.18410632395230436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153578293","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":[0.5177224,0.00022305717,0.4761184,0.00002341082,0.000330248,0.0010049016,0.00010876809,0.0012862359,0.0031826058],"genre_scores_gemma":[0.9520507,0.0000055948985,0.047084052,0.0000145074255,0.00019790798,0.000103087244,0.00036693498,0.000079669364,0.00009753872],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988888,0.000038734604,0.00033288635,0.00026306577,0.00012223153,0.00035429027],"domain_scores_gemma":[0.999446,0.00006463168,0.00006927117,0.00029650712,0.00006404451,0.000059545237],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001052123,0.00021638983,0.00027452686,0.00010458462,0.000053456573,0.00003667115,0.00017582907,0.0001294114,0.000017151353],"category_scores_gemma":[0.0000018395881,0.00024775774,0.000051957704,0.00027167954,0.0000120124605,0.0003072833,0.000015946262,0.00007607381,0.00003128617],"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":[0.000036926354,0.000027983315,0.0006453588,0.00017914375,0.0000071571644,0.00000810607,0.000032812302,0.99379504,0.003958063,0.0007736366,0.00022116551,0.0003145836],"study_design_scores_gemma":[0.0007997724,0.00004676542,0.001148334,0.00013867175,0.000014219718,8.084699e-7,0.00008610234,0.9932156,0.003694222,0.00010078157,0.0004958,0.00025887246],"about_ca_topic_score_codex":0.0002738827,"about_ca_topic_score_gemma":0.00065109745,"teacher_disagreement_score":0.43432832,"about_ca_system_score_codex":0.00025941423,"about_ca_system_score_gemma":0.00001518466,"threshold_uncertainty_score":0.9999975},"labels":[],"label_agreement":null},{"id":"W2153592208","doi":"10.1109/iswcs.2007.4392344","title":"Joint Adaptive Modulation, Diversity Combining, and Power Control for Uplink Transmission in Two-cell Wireless Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Norges Forskningsråd; Qatar Foundation","keywords":"Telecommunications link; Spectral efficiency; Computer science; Power control; Transmitter power output; Fading; Transmission (telecommunications); Link adaptation; Electronic engineering; Wireless; Transmitter; Bandwidth (computing); Computer network; Interference (communication); Wireless network; Power (physics); Channel (broadcasting); Telecommunications; Engineering","score_opus":0.008451105274506453,"score_gpt":0.21005266609873627,"score_spread":0.2016015608242298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153592208","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":[0.075023204,0.00019078451,0.92317396,0.000016347656,0.000113487644,0.00046688798,0.0000013877863,0.00015711196,0.0008568089],"genre_scores_gemma":[0.977416,0.000064914704,0.022347732,0.000044965545,0.00003176077,0.0000056886197,0.000014165514,0.000030616833,0.00004420468],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991729,0.000012064221,0.00025134702,0.00019066223,0.00008300492,0.00029002494],"domain_scores_gemma":[0.99959624,0.00012668596,0.00004007505,0.000091717964,0.00005606834,0.00008922432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024165977,0.00015412967,0.00020494862,0.00008675221,0.000110928006,0.0000116582805,0.00005478064,0.00009284282,0.000014992962],"category_scores_gemma":[0.0000032262592,0.00016128276,0.00003492119,0.00014762527,0.000025201372,0.00018001848,0.000025348814,0.0001395033,6.3666766e-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":[0.0000980694,0.000022645194,0.0021186713,0.000011134818,0.000010703774,0.0000018168088,0.0003009346,0.9867643,0.0002575217,0.0006746969,0.0000678826,0.00967163],"study_design_scores_gemma":[0.0030461522,0.00004360163,0.0048142485,0.000030121819,0.000010670518,7.079927e-7,0.0000782833,0.9910481,0.00034577356,0.000359113,0.000030101079,0.00019313567],"about_ca_topic_score_codex":0.000013462205,"about_ca_topic_score_gemma":0.000030306956,"teacher_disagreement_score":0.90239275,"about_ca_system_score_codex":0.00007594091,"about_ca_system_score_gemma":0.00000409155,"threshold_uncertainty_score":0.657692},"labels":[],"label_agreement":null},{"id":"W2153665435","doi":"10.1109/ecrts.2007.22","title":"On Dominating Set Allocation Policies in Real-Time Wide-Area Distributed Systems","year":2007,"lang":"en","type":"article","venue":"Proceedings - Euromicro Workshop on Real-Time Systems/Proceedings","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Heuristics; Computer science; Scheduling (production processes); Distributed computing; Workload; Resource allocation; Multiprocessing; Processor scheduling; Set (abstract data type); Time allocation; Mathematical optimization; Resource (disambiguation); Computer network; Parallel computing","score_opus":0.011899172797027822,"score_gpt":0.2363390851595883,"score_spread":0.22443991236256047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153665435","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":[0.9384745,0.00020656765,0.002469346,0.00014528431,0.0008366737,0.002846602,0.000098557284,0.003294398,0.05162812],"genre_scores_gemma":[0.995189,0.00062364666,0.0010497072,0.000055426688,0.00063715427,0.00031729147,0.00030046384,0.00056877726,0.0012585236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9927633,0.000025629039,0.0023916592,0.0015501847,0.0011201132,0.0021491337],"domain_scores_gemma":[0.996336,0.0007660859,0.0010301403,0.00035412377,0.0009733424,0.00054031826],"candidate_categories":["metaepi_narrow"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0022986296,0.0014390064,0.0015946019,0.0014898485,0.00039235898,0.00093769724,0.0008955651,0.0008261693,0.000031246796],"category_scores_gemma":[0.00067525904,0.0015692082,0.00021562,0.003179098,0.00016140274,0.0012942691,0.00018088885,0.0011011056,0.00032930993],"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":[0.0010570626,0.00038470057,0.0049508596,0.0027498563,0.0003102767,0.000056644505,0.0046566688,0.51186883,0.39500898,0.01309176,0.06507976,0.00078457984],"study_design_scores_gemma":[0.0041086874,0.00050064985,0.004908511,0.010340087,0.00019589241,0.0002637268,0.006770228,0.9526224,0.013465691,0.00016849893,0.0026852388,0.003970379],"about_ca_topic_score_codex":0.0001743543,"about_ca_topic_score_gemma":0.000004270914,"teacher_disagreement_score":0.44075358,"about_ca_system_score_codex":0.002117399,"about_ca_system_score_gemma":0.000043639837,"threshold_uncertainty_score":0.99983597},"labels":[],"label_agreement":null},{"id":"W2153831243","doi":"10.1155/2009/891367","title":"Suboptimal Rate Adaptive Resource Allocation for Downlink OFDMA Systems","year":2009,"lang":"en","type":"article","venue":"International Journal of Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":26,"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":"Subcarrier; Telecommunications link; Computer science; Resource allocation; Orthogonal frequency-division multiple access; Mathematical optimization; Transmitter power output; Throughput; Orthogonal frequency-division multiplexing; Frequency-division multiple access; Bandwidth (computing); Bandwidth allocation; Real-time computing; Computer network; Telecommunications; Mathematics; Wireless; Transmitter","score_opus":0.006518998515402043,"score_gpt":0.23030708397530694,"score_spread":0.2237880854599049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153831243","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":[0.078430615,0.002242997,0.9150232,0.0028697546,0.00086664327,0.00022059234,0.0000116058445,0.00020045115,0.0001341384],"genre_scores_gemma":[0.97969687,0.00037221092,0.01934351,0.00007108803,0.00042969218,0.000016616992,0.000017566397,0.000023423258,0.000028999035],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902123,0.000020468135,0.00046531248,0.000112516245,0.0002107467,0.00016974132],"domain_scores_gemma":[0.99882555,0.00005451302,0.000264502,0.00011232736,0.0007051545,0.000037932194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021278927,0.00013272278,0.00021341648,0.0004635481,0.00003115774,0.000030862913,0.00040994183,0.00019311487,0.0000040006244],"category_scores_gemma":[0.00007944327,0.00013098681,0.000086187836,0.00020499046,0.00003682358,0.00021233474,0.0000163141,0.0002506314,0.0000030381875],"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":[0.00008383301,0.000028718456,0.000037737358,0.0000045098486,0.00014975153,0.000026561414,0.00002149729,0.9580765,0.011468423,0.008773826,0.0006259148,0.020702763],"study_design_scores_gemma":[0.0011371376,0.00031983206,0.00019709214,0.00017353692,0.000049351376,0.00025176303,0.00011070693,0.9649911,0.012852992,0.0031279766,0.016582532,0.0002059604],"about_ca_topic_score_codex":4.863501e-7,"about_ca_topic_score_gemma":4.994248e-7,"teacher_disagreement_score":0.9012663,"about_ca_system_score_codex":0.0001884331,"about_ca_system_score_gemma":0.000023163584,"threshold_uncertainty_score":0.5341487},"labels":[],"label_agreement":null},{"id":"W2153867167","doi":"10.1109/infcom.2013.6566982","title":"A (min, &amp;#x00D7;) network calculus for multi-hop fading channels","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":45,"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; Fading; Rayleigh fading; Wireless network; Network calculus; Markov chain; Markov process; Algorithm; Wireless; Channel (broadcasting); Hop (telecommunications); Computer network; Theoretical computer science; Mathematics; Telecommunications; Quality of service; Machine learning; Statistics","score_opus":0.02697515780926038,"score_gpt":0.25258880481663676,"score_spread":0.22561364700737638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153867167","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":[0.0032661601,0.0003116329,0.9925923,0.000054172106,0.000850709,0.0007646407,0.0000027876474,0.000816275,0.0013413558],"genre_scores_gemma":[0.43401623,0.00010046283,0.5601686,0.0001326643,0.0008393753,0.000615705,0.000059775397,0.00013070693,0.003936481],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891645,0.000009452084,0.00024695892,0.00020694171,0.00008258268,0.000537598],"domain_scores_gemma":[0.999468,0.000081349855,0.000031584903,0.00022075449,0.00008829341,0.00011000207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000065811226,0.00020196132,0.00020347426,0.000052076404,0.00010436965,0.000056909095,0.00012590562,0.00011354177,0.00022305295],"category_scores_gemma":[0.000029052864,0.00020037469,0.000069311594,0.00024448364,0.000017714145,0.00030507345,0.000030876232,0.000102686456,0.000207577],"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":[0.000001914528,0.000009944879,0.000030237641,0.000026295134,0.000021768066,2.2043471e-7,0.000107102904,0.97713757,0.00031685666,0.00055582146,0.0150923915,0.0066998685],"study_design_scores_gemma":[0.00040052403,0.000012574605,0.000022476263,0.000028782788,0.000008611699,0.0000015638616,0.000020268919,0.980126,0.00028215113,0.0002939533,0.018538453,0.00026462603],"about_ca_topic_score_codex":0.000016448139,"about_ca_topic_score_gemma":0.000041050553,"teacher_disagreement_score":0.43242368,"about_ca_system_score_codex":0.000072395946,"about_ca_system_score_gemma":0.000005110799,"threshold_uncertainty_score":0.8171043},"labels":[],"label_agreement":null},{"id":"W2154188754","doi":"10.1109/tcomm.2008.060106","title":"Cross-Layer Rate and Power Adaptation Strategies for IR-HARQ Systems over Fading Channels with Memory: A SMDP-Based Approach","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Hybrid automatic repeat request; Computer science; Fading; Rayleigh fading; Markov decision process; Link adaptation; Physical layer; Transmitter; Automatic repeat request; Block Error Rate; Markov process; Telecommunications link; Channel (broadcasting); Computer network; Wireless; Telecommunications; Mathematics","score_opus":0.04680008209293217,"score_gpt":0.2642501974351741,"score_spread":0.2174501153422419,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154188754","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":[0.018229328,0.00034741816,0.97908056,0.00004160878,0.00019923064,0.00082975236,0.00007003823,0.00042715832,0.00077488937],"genre_scores_gemma":[0.9659235,0.00033125107,0.032446213,0.00002544133,0.000019726098,0.00095222285,0.00006194915,0.000080602025,0.00015910166],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990731,0.00006978427,0.00027313305,0.00022145538,0.00012461991,0.00023790031],"domain_scores_gemma":[0.99865544,0.00028686094,0.000074255695,0.0007623399,0.00014710063,0.00007397616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000120427525,0.00022709354,0.00021131936,0.00017527658,0.0007170739,0.00012241135,0.00023865544,0.00010795797,0.000008320765],"category_scores_gemma":[0.0000027992126,0.000231969,0.00005258744,0.00035406358,0.00017422943,0.0005882479,0.0000018717908,0.00025385784,0.0000029446257],"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":[0.000044107637,0.000076367636,0.0000073495767,0.00005081417,0.000057960464,3.4812e-7,0.00095197564,0.99768335,0.00040072572,0.0003330805,0.000028396036,0.0003655305],"study_design_scores_gemma":[0.0009682403,0.00007244838,0.00006921456,0.000063171174,0.000038676866,0.000011203645,0.0005792136,0.9969729,0.00065997965,0.000029643386,0.0002712233,0.00026404703],"about_ca_topic_score_codex":0.000028323984,"about_ca_topic_score_gemma":0.00003315459,"teacher_disagreement_score":0.9476942,"about_ca_system_score_codex":0.000100785954,"about_ca_system_score_gemma":0.00006395461,"threshold_uncertainty_score":0.94594216},"labels":[],"label_agreement":null},{"id":"W2154650924","doi":"10.1109/wncmf.1994.529428","title":"A protocol for random multiple access of packets with mixed priorities in wireless networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Aloha; Computer science; Network packet; Lambda; Random access; Computer network; Protocol (science); Poisson distribution; Population; Wireless; Throughput; Class (philosophy); Computation; Construct (python library); Wireless network; Distributed computing; Algorithm; Mathematics; Telecommunications; Statistics; Artificial intelligence","score_opus":0.027644908507635943,"score_gpt":0.26146722852300525,"score_spread":0.2338223200153693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154650924","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":[0.010954876,0.000014449176,0.90013635,0.000009475139,0.00004795796,0.0877641,0.0000030534595,0.00020733081,0.0008624254],"genre_scores_gemma":[0.7994044,0.00001249155,0.010682648,0.000007746045,0.00005206647,0.18971366,0.000005510881,0.00005086383,0.000070621376],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999202,0.000016990043,0.00028746756,0.0001430017,0.00009512462,0.0002554026],"domain_scores_gemma":[0.9994991,0.00019345619,0.000057514797,0.00015531345,0.000059298065,0.00003533496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006443593,0.00015668187,0.00027266573,0.00007785318,0.000024522795,0.000024019884,0.00013325216,0.000078002886,0.00003642789],"category_scores_gemma":[0.00001411636,0.00013175634,0.000031544445,0.00027955757,0.00003312677,0.0003106589,0.000019177458,0.00008641121,4.958753e-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":[0.00024228044,0.000033411543,0.0046281046,0.00019700032,0.000014270999,0.0000010601674,0.000067689354,0.9867862,0.000036730657,0.00010313897,0.0003759428,0.0075142025],"study_design_scores_gemma":[0.0074740453,0.00004328584,0.0005133239,0.00016050598,0.000003942297,0.0000011356328,0.000022897973,0.9893438,0.0019983759,0.00003335364,0.00023002434,0.00017529025],"about_ca_topic_score_codex":0.0000052320743,"about_ca_topic_score_gemma":0.00025602258,"teacher_disagreement_score":0.8894537,"about_ca_system_score_codex":0.000036681522,"about_ca_system_score_gemma":0.000004671079,"threshold_uncertainty_score":0.5372868},"labels":[],"label_agreement":null},{"id":"W2155280140","doi":"10.1109/icc.2006.255766","title":"A Cooperative Game Framework for Bandwidth Allocation in 4G Heterogeneous Wireless Networks","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":139,"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 Manitoba","funders":"","keywords":"Computer science; Computer network; Bandwidth allocation; Shapley value; Wireless network; Channel allocation schemes; Bandwidth (computing); Resource allocation; Wireless; Distributed computing; Resource management (computing); Game theory; Telecommunications; Mathematics","score_opus":0.040451775504140045,"score_gpt":0.30733397768872517,"score_spread":0.26688220218458514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155280140","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":[0.008565409,0.00021952175,0.98216033,0.00085226697,0.0005562679,0.00057690166,0.00008546687,0.00023448406,0.006749352],"genre_scores_gemma":[0.9748745,0.001010269,0.022266153,0.00012585311,0.00020379366,0.00058513886,0.0007193376,0.00005181451,0.00016315942],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879164,0.000064942375,0.00046095907,0.00024122425,0.00017738176,0.0002638311],"domain_scores_gemma":[0.99847585,0.00035906743,0.00010758724,0.00067863986,0.00033439245,0.000044448916],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000115158415,0.0002240556,0.00020553377,0.0001831346,0.000108874854,0.000101639074,0.00078821834,0.00016679181,0.000058377267],"category_scores_gemma":[0.000031995765,0.00026003728,0.000060521477,0.00028305114,0.00009520568,0.00021591132,0.000046809408,0.0003601047,0.000020517644],"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":[0.000022726208,0.00009416401,0.00013894458,0.000004390002,0.00002230069,6.039497e-7,0.000052579406,0.8387671,0.0002472017,0.15714948,0.00036951393,0.0031309833],"study_design_scores_gemma":[0.0004102809,0.000031843934,0.0002825673,0.00014856002,0.0000074825193,0.0000027529195,0.00002874936,0.9867768,0.0005711357,0.010122788,0.0013624296,0.00025457275],"about_ca_topic_score_codex":0.000045218934,"about_ca_topic_score_gemma":0.0008946942,"teacher_disagreement_score":0.9663091,"about_ca_system_score_codex":0.0002658592,"about_ca_system_score_gemma":0.00003844802,"threshold_uncertainty_score":0.99998516},"labels":[],"label_agreement":null},{"id":"W2155598485","doi":"10.1109/wowmom.2009.5347411","title":"An efficient scheduling algorithm for downlink multi-antenna CDMA systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 du Québec à Montréal","funders":"","keywords":"Telecommunications link; Computer science; Computational complexity theory; Beamforming; Orthogonality; Scheduling (production processes); Mathematical optimization; Algorithm; Mathematics; Computer network","score_opus":0.011247048815600201,"score_gpt":0.24844673406017906,"score_spread":0.23719968524457885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155598485","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":[0.0050334255,0.00046029792,0.9923261,0.000011080964,0.0006416095,0.0004705341,0.000009706678,0.0009229466,0.00012431302],"genre_scores_gemma":[0.48070487,0.000026697475,0.5189201,0.000023248102,0.00018909715,0.000025546982,0.000038605864,0.000028317896,0.00004347586],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991435,0.000010024647,0.00023960789,0.00020137074,0.000098126904,0.0003073908],"domain_scores_gemma":[0.9995405,0.0000285492,0.000029395165,0.00021822,0.00009057217,0.000092781534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009889321,0.00015971193,0.00017211854,0.00006959697,0.00007233891,0.000055898698,0.00011252104,0.00008835441,0.000004777117],"category_scores_gemma":[0.000009140827,0.00015371156,0.0000428812,0.00015775034,0.000008687913,0.00014407892,0.000005027795,0.00008410613,0.00001138861],"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":[0.0000020452408,0.000035134588,0.0000042190673,0.000013062145,0.0000074065383,0.0000010562296,0.000044180673,0.9520946,0.0016812917,0.0002742798,0.000018502775,0.045824196],"study_design_scores_gemma":[0.0005013988,0.000048923586,0.000042261385,0.000035224883,0.000008141294,0.000002688066,0.00008465908,0.99839795,0.00052894314,0.0000096243375,0.00013123566,0.000208961],"about_ca_topic_score_codex":0.0000022200475,"about_ca_topic_score_gemma":0.0000010210251,"teacher_disagreement_score":0.47567144,"about_ca_system_score_codex":0.00006890799,"about_ca_system_score_gemma":0.000005814206,"threshold_uncertainty_score":0.6268176},"labels":[],"label_agreement":null},{"id":"W2155694821","doi":"10.1109/isit.2007.4557653","title":"Optimal Order of Decoding for Max-Min Fairness in K-User Memoryless Interference Channels","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Decodes; Decoding methods; Transmitter; Interference (communication); Channel (broadcasting); Greedy algorithm; Order (exchange)","score_opus":0.012502237579793398,"score_gpt":0.2518505373761261,"score_spread":0.2393482997963327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155694821","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":[0.18978393,0.000050234223,0.8086354,0.000007644383,0.00026313463,0.00022302328,0.0000017817277,0.000098402255,0.0009364067],"genre_scores_gemma":[0.8528874,0.000021583095,0.14676562,0.0000093024055,0.00005045405,0.000024786943,0.000008383891,0.000034618915,0.00019789196],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991483,0.000005684861,0.00032500405,0.00015107944,0.000072780065,0.0002971577],"domain_scores_gemma":[0.99958634,0.000121446,0.000038040307,0.00013130001,0.00008323326,0.000039611226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020719503,0.00013127102,0.00019805635,0.00015480354,0.000016106673,0.000010188441,0.00013295177,0.00008279869,0.000049194245],"category_scores_gemma":[0.00003159756,0.00013765582,0.000027378865,0.00034417407,0.000020308698,0.0001938066,0.000030010182,0.00008376574,0.0000023905834],"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":[0.000032156644,0.000015812207,0.0003381928,0.00006801368,0.000008135576,0.000001506906,0.00025503573,0.985914,0.0015234873,0.0011224009,0.000038937545,0.010682338],"study_design_scores_gemma":[0.00053583924,0.00002492771,0.0002019708,0.00008507207,0.0000041946946,0.0000015697044,0.00034546407,0.938359,0.060048476,0.000104243416,0.00009889321,0.00019035314],"about_ca_topic_score_codex":0.0000062821864,"about_ca_topic_score_gemma":0.00010741859,"teacher_disagreement_score":0.66310346,"about_ca_system_score_codex":0.00006217428,"about_ca_system_score_gemma":0.0000073472174,"threshold_uncertainty_score":0.56134415},"labels":[],"label_agreement":null},{"id":"W2155718283","doi":"10.1109/icc.2011.5962569","title":"Energy Efficient Resource Allocation in SC-FDMA Uplink with Synchronous HARQ Constraints","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Telecommunications link; Computer science; Hybrid automatic repeat request; Resource allocation; Scheduling (production processes); Frequency-division multiple access; Mathematical optimization; Orthogonal frequency-division multiplexing; Computer network; Channel (broadcasting); Mathematics","score_opus":0.006956775787465236,"score_gpt":0.17160381126825913,"score_spread":0.1646470354807939,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155718283","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":[0.040186252,0.00008329878,0.92665815,0.000009362416,0.00005189238,0.00010908374,6.030277e-7,0.00031038673,0.03259094],"genre_scores_gemma":[0.9701919,0.000024294515,0.02954039,0.00003656214,0.000025977546,0.000026350448,0.000017356611,0.00003685742,0.00010030334],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932104,0.000012568639,0.0001797857,0.0001709396,0.0000896187,0.00022606966],"domain_scores_gemma":[0.99968594,0.000022017533,0.00002720316,0.00018296533,0.000028471179,0.00005341602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057282352,0.00013097013,0.00011581856,0.00009512645,0.000025704074,0.00000954842,0.00008510616,0.00006651192,0.00014082456],"category_scores_gemma":[0.0000039762226,0.000122049794,0.000013065475,0.00024469636,0.00006227317,0.00006742488,0.000014075474,0.00008224339,0.00001542193],"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":[0.000013184419,0.000027364831,0.0002359568,0.0000092080245,0.000008767725,0.000006621153,0.0002607395,0.97942495,0.0001412859,0.0027313398,0.000053301177,0.017087264],"study_design_scores_gemma":[0.00037003082,0.00003096724,0.0007189356,0.00005014248,0.000004753961,0.000008652108,0.00007898796,0.99369174,0.0045356997,0.000025194382,0.0002994029,0.00018548178],"about_ca_topic_score_codex":0.00002593571,"about_ca_topic_score_gemma":0.00006116618,"teacher_disagreement_score":0.93000567,"about_ca_system_score_codex":0.00010366707,"about_ca_system_score_gemma":0.000014816958,"threshold_uncertainty_score":0.49770463},"labels":[],"label_agreement":null},{"id":"W2156225562","doi":"10.1109/icc.2011.5963460","title":"Power Allocation and Scheduling for Broadband Wireless Networks Considering Mutual Interference","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Maximum throughput scheduling; Scheduling (production processes); Wireless network; Computer network; Power control; Wireless; Broadband networks; Channel allocation schemes; Distributed computing; Radio resource management; Dynamic priority scheduling; Mathematical optimization; Round-robin scheduling; Power (physics); Broadband; Quality of service; Telecommunications; Mathematics","score_opus":0.018109444636501913,"score_gpt":0.21431564528853636,"score_spread":0.19620620065203445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156225562","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":[0.12549049,0.0002498909,0.8717951,0.0000053002514,0.00021464139,0.0001869287,7.4760504e-7,0.00027024708,0.0017866483],"genre_scores_gemma":[0.91579753,0.00017358095,0.08384152,0.000026844291,0.00004598902,0.000034121524,0.0000072556472,0.000035525652,0.000037623566],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940157,0.000006633321,0.00018004462,0.00016427466,0.00003915475,0.00020831174],"domain_scores_gemma":[0.99968916,0.000064086904,0.000027485527,0.00011240891,0.000050148286,0.000056727047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000062887986,0.00013109982,0.00012641572,0.00004374021,0.00005201525,0.00002538229,0.000057871748,0.000080021564,0.000042107207],"category_scores_gemma":[0.00001350324,0.00013804076,0.000018138959,0.00007818428,0.000035956786,0.00024225123,0.000024748377,0.00008770705,0.0000020844548],"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":[0.000029472705,0.0000091686725,0.0008064621,0.000034753008,0.000031378328,8.081513e-7,0.0006527539,0.97981876,0.000955778,0.004923683,0.00007028746,0.012666712],"study_design_scores_gemma":[0.0002703538,0.000028885415,0.00023416441,0.000048378246,0.000007376367,0.000004714621,0.00013723073,0.99542385,0.0033360987,0.0002670808,0.000062023515,0.00017982937],"about_ca_topic_score_codex":0.0000020866114,"about_ca_topic_score_gemma":0.000011565853,"teacher_disagreement_score":0.79030704,"about_ca_system_score_codex":0.000023638968,"about_ca_system_score_gemma":0.0000051912725,"threshold_uncertainty_score":0.5629139},"labels":[],"label_agreement":null},{"id":"W2156238030","doi":"10.1109/allerton.2009.5394771","title":"On channel access delay of CSMA policies in wireless networks with primary interference constraints","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Computer network; Computer science; Bipartite graph; Exponential backoff; Scheduling (production processes); Wireless network; Channel (broadcasting); Simple (philosophy); Limit (mathematics); Interference (communication); Channel access method; Wireless; Distributed computing; Topology (electrical circuits); Throughput; Mathematics; Telecommunications; Theoretical computer science; Mathematical optimization; Graph","score_opus":0.009352710143012779,"score_gpt":0.22688707305611655,"score_spread":0.21753436291310377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156238030","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":[0.23984876,0.00004391439,0.7409902,0.00003125609,0.00006492452,0.00017841448,0.0000020649904,0.00016377284,0.018676694],"genre_scores_gemma":[0.998065,0.00014696819,0.0015183899,0.00017296264,0.000030577867,0.000008941781,0.00001405162,0.000021941643,0.000021198137],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922943,0.000013938746,0.00024254514,0.000150142,0.00010228856,0.00026164923],"domain_scores_gemma":[0.9996345,0.00006402935,0.000049110502,0.00016851268,0.000038423717,0.000045420835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047183137,0.00016978497,0.0002372957,0.00013518763,0.00001601211,0.000020297832,0.0001990432,0.00007929193,0.000021547112],"category_scores_gemma":[0.0000042026945,0.00014767637,0.000018305096,0.0003831471,0.00007623233,0.00023636354,0.00002133813,0.00017387074,0.000001148915],"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":[0.000046170506,0.000030628595,0.00036250908,0.000015957812,0.000008352089,0.00000495588,0.00009251757,0.97519135,0.00007176028,0.0020821677,0.00005795772,0.022035692],"study_design_scores_gemma":[0.0005610159,0.0001654989,0.007912611,0.00035039376,0.0000048025577,0.000007766375,0.00004723651,0.9889015,0.0014354038,0.00035403043,0.0000022073775,0.0002575435],"about_ca_topic_score_codex":0.00000861075,"about_ca_topic_score_gemma":0.00005147881,"teacher_disagreement_score":0.7582162,"about_ca_system_score_codex":0.000070128124,"about_ca_system_score_gemma":0.000012877933,"threshold_uncertainty_score":0.60220677},"labels":[],"label_agreement":null},{"id":"W2156323494","doi":"10.1109/glocomw.2010.5700440","title":"Joint admission control and resource allocation with GoS and QoS in LTE uplink","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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":"Quality of service; Telecommunications link; Computer science; Admission control; Computer network; Resource allocation; Blocking (statistics); Resource management (computing); Scheme (mathematics); Resource (disambiguation); Service (business); Call Admission Control; Joint (building); Telecommunications; Engineering; Wireless; Mathematics","score_opus":0.0028604757492227593,"score_gpt":0.1731364676202069,"score_spread":0.17027599187098413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156323494","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":[0.4633702,0.00013940991,0.534105,0.00030354958,0.0000697975,0.00029414936,5.4073047e-7,0.00018452738,0.0015328102],"genre_scores_gemma":[0.98015,0.000055686472,0.019564178,0.000046400215,0.000064159925,0.000014006321,0.000004956625,0.000020017365,0.00008060707],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996277,0.0000064460487,0.0001035554,0.00011291104,0.000046749592,0.00010263724],"domain_scores_gemma":[0.99979025,0.000026698106,0.000016327385,0.00009156409,0.000014599786,0.000060546176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006419846,0.0000802479,0.0000895063,0.00004784019,0.000022951997,0.000016475695,0.000019497797,0.000058858914,0.000012207979],"category_scores_gemma":[0.000014093337,0.00006624076,0.000003868261,0.000074995834,0.000019251975,0.00011279908,0.00000839706,0.00013957538,0.0000010731319],"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":[0.00005430212,0.000013893052,0.0052910587,0.00004499692,0.000010125106,0.0000032738635,0.00023942163,0.91865784,0.0419659,0.001046355,0.0002988129,0.032374006],"study_design_scores_gemma":[0.0008786455,0.000023392782,0.007271334,0.00003164521,0.0000044292838,0.0000070140823,0.000026976986,0.98898876,0.001366534,0.000040416435,0.0012499206,0.00011093969],"about_ca_topic_score_codex":0.00000466223,"about_ca_topic_score_gemma":0.00007397348,"teacher_disagreement_score":0.5167798,"about_ca_system_score_codex":0.000010500203,"about_ca_system_score_gemma":0.000004209648,"threshold_uncertainty_score":0.270122},"labels":[],"label_agreement":null},{"id":"W2156434064","doi":"10.1110/twc.2010.11.100045","title":"Joint Resource Allocation for Parallel Multi-Radio Access in Heterogeneous Wireless Networks","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":125,"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 Hospital","funders":"","keywords":"Computer science; Computer network; Cognitive radio; Heterogeneous network; Wireless network; Resource allocation; Radio access technology; Radio resource management; Wireless; Air interface; Heterogeneous wireless network; Joint (building); Base station; Telecommunications; User equipment; Engineering","score_opus":0.0334767909271064,"score_gpt":0.27569142558725174,"score_spread":0.24221463466014534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156434064","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":[0.03246948,0.0001716982,0.964347,0.00036308696,0.0005886811,0.0012138912,0.00004806325,0.00067103474,0.00012708026],"genre_scores_gemma":[0.95884925,0.0014692012,0.037373565,0.00008350264,0.00007108404,0.0017675536,0.00014628435,0.00016481214,0.00007472673],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99803925,0.00011319128,0.00072546594,0.00040667664,0.00018334575,0.0005320495],"domain_scores_gemma":[0.9971252,0.0004114007,0.00013463057,0.0020266636,0.00013945706,0.0001626322],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025218545,0.00038708877,0.0003984291,0.0003760047,0.0004900072,0.00012566191,0.0012519964,0.0003516271,0.00002001881],"category_scores_gemma":[0.0000083418245,0.000467613,0.00017084688,0.00073900993,0.00019211454,0.0004751572,0.00001352296,0.0011388793,0.000011602622],"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":[0.000033818033,0.00029893653,0.000029124887,0.000032196385,0.000048053116,8.1679207e-7,0.00018949006,0.96162355,0.0025218644,0.00037012523,0.00007275068,0.034779266],"study_design_scores_gemma":[0.0011555732,0.00003087878,0.00019986587,0.000086032574,0.00003495333,0.000011004914,0.000041137824,0.99235386,0.00451398,0.000060962626,0.0010503503,0.00046140852],"about_ca_topic_score_codex":0.00004105544,"about_ca_topic_score_gemma":0.0035486538,"teacher_disagreement_score":0.9269734,"about_ca_system_score_codex":0.0002070132,"about_ca_system_score_gemma":0.0000424208,"threshold_uncertainty_score":0.99977756},"labels":[],"label_agreement":null},{"id":"W2156442063","doi":"10.1109/icc.2006.255759","title":"Delay-aware Power Adaptation for Incremental Redundancy Hybrid ARQ over Fading Channels with Memory","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Hybrid automatic repeat request; Fading; Automatic repeat request; Redundancy (engineering); Markov chain; Channel (broadcasting); Transmitter; Markov decision process; Network packet; Markov process; Computer network; Selective Repeat ARQ; Buffer overflow; Transmitter power output; Telecommunications link; Mathematics","score_opus":0.04341137406392314,"score_gpt":0.28607921947629794,"score_spread":0.2426678454123748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156442063","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":[0.03262115,0.00011655788,0.9311079,0.00068261876,0.0007737175,0.0006906089,0.00031485088,0.0003973932,0.033295244],"genre_scores_gemma":[0.97860193,0.0001429103,0.019015374,0.00007730004,0.00014938372,0.0003214883,0.0011409206,0.000057762612,0.0004928994],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892575,0.000031838892,0.0003421869,0.00021520282,0.00026281303,0.00022219407],"domain_scores_gemma":[0.99880385,0.00012803078,0.00012975343,0.0005606721,0.00033237666,0.000045310262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009058387,0.00021194274,0.00015289347,0.00017798922,0.00020858666,0.00010124101,0.000599531,0.00005852037,0.00012186263],"category_scores_gemma":[0.000011166435,0.00022934117,0.000054227978,0.0001424863,0.000082114166,0.0004135509,0.000044367483,0.00020528493,0.000023042574],"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":[0.00004506595,0.0000898601,0.00008498086,0.000008368022,0.000059744783,0.0000013535573,0.00012551568,0.9706179,0.0010913081,0.023290334,0.0027849455,0.0018006552],"study_design_scores_gemma":[0.00071793876,0.000060604478,0.00018550859,0.00014049442,0.000016656533,0.000009215061,0.00014265018,0.9923412,0.0019569825,0.0017902781,0.0023452106,0.0002932475],"about_ca_topic_score_codex":0.00007200399,"about_ca_topic_score_gemma":0.00027848736,"teacher_disagreement_score":0.9459808,"about_ca_system_score_codex":0.00026173255,"about_ca_system_score_gemma":0.0000439996,"threshold_uncertainty_score":0.93522614},"labels":[],"label_agreement":null},{"id":"W2156770151","doi":"10.1109/wcnc.2009.4917702","title":"Efficient Scheduling Algorithms for Multi-Service Multi-Slot OFDMA Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"","keywords":"Computer science; Scheduling (production processes); Quality of service; Distributed computing; Frequency-division multiple access; Algorithm; Limiting; Orthogonal frequency-division multiplexing; Computer network; Mathematical optimization; Engineering; Mathematics","score_opus":0.03251393190186467,"score_gpt":0.27750751317693195,"score_spread":0.2449935812750673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156770151","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":[0.005997279,0.0008616001,0.99086154,0.00009728453,0.00048592256,0.00055399217,0.0000053308463,0.0010229037,0.00011417978],"genre_scores_gemma":[0.2935637,0.00009642156,0.7055441,0.0003072001,0.00024035,0.000060326292,0.000032125026,0.000058645503,0.00009711784],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988308,0.000010096325,0.00030107007,0.00027311023,0.00010907787,0.00047586253],"domain_scores_gemma":[0.99943197,0.00005650774,0.00004350452,0.00022534197,0.00013254574,0.00011014972],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001013335,0.00024275716,0.00021965479,0.00007145736,0.00011022615,0.000037565016,0.00016631607,0.00014472804,0.000020528392],"category_scores_gemma":[0.000017355016,0.0002475863,0.00006827683,0.00038203233,0.000010135873,0.00008260268,0.00001974569,0.00016022078,0.000013115584],"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":[0.00000816764,0.00006467721,0.000017264649,0.000019158735,0.00001616112,7.893809e-7,0.000061074985,0.9666613,0.0005375175,0.00017579246,0.00004369503,0.03239442],"study_design_scores_gemma":[0.0012172845,0.000022638036,0.00031814777,0.00004889761,0.00001658813,0.0000013360483,0.000036556172,0.9970693,0.00075135933,0.000007457429,0.00019929883,0.0003111237],"about_ca_topic_score_codex":0.0000044109506,"about_ca_topic_score_gemma":0.000019981422,"teacher_disagreement_score":0.28756642,"about_ca_system_score_codex":0.00007877048,"about_ca_system_score_gemma":0.000007559197,"threshold_uncertainty_score":0.9999976},"labels":[],"label_agreement":null},{"id":"W2157168920","doi":"10.1109/pacrim.2009.5291352","title":"Performance of enhanced proportional fair scheduling in HSDPA for multimedia service streaming","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Proportionally fair; Scheduling (production processes); Computer network; Round-robin scheduling; Multimedia; Fair-share scheduling; Quality of service; Dynamic priority scheduling; Real-time computing; Distributed computing","score_opus":0.006835205182610853,"score_gpt":0.22056715617141712,"score_spread":0.21373195098880626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157168920","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":[0.6755605,0.000026073472,0.32356596,0.000020491078,0.00005033661,0.00022027984,0.0000016439642,0.00010140459,0.00045334478],"genre_scores_gemma":[0.7734478,0.000028437404,0.22638305,0.000019277828,0.000040653296,0.000021180904,0.000028563576,0.000012214924,0.000018822593],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99935716,0.0000029783616,0.0002617522,0.00011288703,0.00008838572,0.00017682451],"domain_scores_gemma":[0.99973327,0.000032975466,0.000042203475,0.00008714227,0.000078827085,0.000025576745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059278278,0.000096506454,0.00013102534,0.00007270823,0.0000187873,0.000003855288,0.00006572806,0.000053248605,0.000014885867],"category_scores_gemma":[0.000014917697,0.00010100754,0.000019243751,0.00024732176,0.0000067499923,0.00023613118,0.0000058099236,0.00006635738,0.000002055939],"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":[0.000016634644,0.000017109289,0.0004383394,0.00007113612,0.0000032793732,1.1294576e-7,0.00011667313,0.9493745,0.021881212,0.00005453789,0.0000029606458,0.02802349],"study_design_scores_gemma":[0.0003984737,0.0000313253,0.0040555797,0.00007305561,0.000002444199,3.36826e-7,0.000043269418,0.93288237,0.062360775,0.00004105573,0.000007282286,0.00010405654],"about_ca_topic_score_codex":0.0000016287039,"about_ca_topic_score_gemma":0.00001900048,"teacher_disagreement_score":0.09788735,"about_ca_system_score_codex":0.00005001938,"about_ca_system_score_gemma":0.0000146354405,"threshold_uncertainty_score":0.4118968},"labels":[],"label_agreement":null},{"id":"W2157415531","doi":"10.1109/icc.2008.872","title":"User Capacity of Fading Multi-User Channels with a Minimum Rate Constraint","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Telecommunications link; Fading; Channel (broadcasting); Computer science; Channel state information; Rayleigh fading; Interference (communication); Algorithm; Topology (electrical circuits); Mathematics; Combinatorics; Computer network; Wireless; Telecommunications","score_opus":0.021206273130706964,"score_gpt":0.20944024088052976,"score_spread":0.1882339677498228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157415531","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":[0.3912579,0.00001666585,0.60748076,0.000006221757,0.000078872814,0.00012424336,0.000003231238,0.0001762008,0.0008559215],"genre_scores_gemma":[0.9126906,0.00005019642,0.08659404,0.00002028467,0.000032658223,0.000012442351,0.0000044571257,0.000034437187,0.00056089705],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993803,0.000013938189,0.00018355034,0.00012994416,0.000081914586,0.00021036378],"domain_scores_gemma":[0.9996549,0.00004197525,0.00003854837,0.00014535527,0.000062647356,0.00005656265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004722925,0.00014043765,0.00018647431,0.0000579531,0.000040511262,0.0000051661964,0.00006459603,0.00005870621,0.00006303178],"category_scores_gemma":[0.000010157601,0.00012195393,0.000026640775,0.00018116747,0.00011050251,0.00017041288,0.000011562467,0.00009376202,0.000007867932],"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":[0.00000805515,0.000015736374,0.0008984605,0.000023808088,0.000029646906,0.0000073082088,0.00045162262,0.99232566,0.0055498295,0.00046014477,0.00013056926,0.000099149256],"study_design_scores_gemma":[0.0011196826,0.00004084377,0.0007380202,0.00007396158,0.000011718498,0.000036322715,0.00015880841,0.9341301,0.06293115,0.000017287623,0.00042584114,0.00031629202],"about_ca_topic_score_codex":0.000008649883,"about_ca_topic_score_gemma":0.000016877548,"teacher_disagreement_score":0.5214327,"about_ca_system_score_codex":0.000033190096,"about_ca_system_score_gemma":0.000010241996,"threshold_uncertainty_score":0.4973137},"labels":[],"label_agreement":null},{"id":"W2157528396","doi":"10.1109/49.963806","title":"A centralized TDMA-based scheme for fair bandwidth allocation in wireless IP networks","year":2001,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":21,"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; University of Manitoba","funders":"","keywords":"Computer science; Time division multiple access; Computer network; Dynamic bandwidth allocation; Network packet; Burstiness; Bandwidth (computing); Throughput; Statistical time division multiplexing; Real-time computing; Bandwidth allocation; Wireless network; Wireless; Multiplexing; Telecommunications","score_opus":0.02196277399214083,"score_gpt":0.273256167998865,"score_spread":0.2512933940067242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157528396","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":[0.1305145,0.00076923514,0.86563474,0.0010495386,0.0003726192,0.0008457126,0.000008560992,0.00030485308,0.0005002181],"genre_scores_gemma":[0.96603423,0.003963778,0.029267378,0.00013656766,0.00012927348,0.00021153627,0.00016223182,0.00007475839,0.000020259018],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99826974,0.00020376827,0.0006800641,0.00017731331,0.0001802778,0.0004888459],"domain_scores_gemma":[0.99814546,0.00056662917,0.00017174242,0.00071131135,0.0002846282,0.00012025108],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034003917,0.00023804356,0.0003034937,0.0004218871,0.00021203051,0.00007370359,0.0006633837,0.00018268256,0.000015007115],"category_scores_gemma":[0.00010444787,0.00026700634,0.00007185183,0.0016747069,0.000048350117,0.00028703222,0.000019271623,0.00088898547,0.0000033363938],"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":[0.00011884908,0.0002027879,0.004231535,0.000009573826,0.000023899529,0.0000033077192,0.000074041665,0.987685,0.00058853,0.00037715345,0.0005500262,0.0061352737],"study_design_scores_gemma":[0.0021907089,0.00004814547,0.0047643185,0.00032699815,0.000011942036,0.000019489604,0.000023378538,0.9901803,0.00031195706,0.00026191963,0.0015916051,0.00026922417],"about_ca_topic_score_codex":0.0000078051135,"about_ca_topic_score_gemma":0.00058333913,"teacher_disagreement_score":0.83636737,"about_ca_system_score_codex":0.00061181554,"about_ca_system_score_gemma":0.00010085067,"threshold_uncertainty_score":0.9999782},"labels":[],"label_agreement":null},{"id":"W2158424206","doi":"10.1109/icc.1995.524442","title":"Rate control of VBR H.261 video on frame relay networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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":"Instituto de Telecomunicações","keywords":"Variable bitrate; Computer science; Codec; Real-time computing; Computer network; Quantization (signal processing); Frame Relay; Network congestion; Quality of service; Constant bitrate; Frame (networking); Algorithm; Computer hardware; Network packet","score_opus":0.005428157308990076,"score_gpt":0.17189497252344654,"score_spread":0.16646681521445647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158424206","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":[0.0033642813,0.00055370585,0.9798751,0.00006592977,0.0002872389,0.00015762023,0.0000019524693,0.0003703628,0.0153238],"genre_scores_gemma":[0.9940751,0.00039422832,0.004530456,0.00019871979,0.00013155739,0.000013359642,0.000004243709,0.000045561752,0.00060677866],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931365,0.000023812665,0.00023213074,0.00012657807,0.00008590196,0.00021789677],"domain_scores_gemma":[0.999492,0.00015606442,0.000040543826,0.00022792704,0.000031888423,0.000051610103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006568171,0.00013326127,0.00019055755,0.000048633476,0.000024948893,0.000011417154,0.000085428226,0.00011046252,0.00048428102],"category_scores_gemma":[0.000023054856,0.00012723409,0.000043585056,0.00019317826,0.000021612823,0.000103828526,0.000007643193,0.00017280033,0.000068081616],"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":[0.000009040008,0.000013284914,0.0000856421,0.0000068074896,0.000022082377,0.0000017341846,0.000021122694,0.99045664,0.0001793184,0.0015333373,0.0033522544,0.0043187165],"study_design_scores_gemma":[0.000514148,0.00003617153,0.00011235547,0.00002941157,0.000008629327,7.3599426e-7,0.0000043403948,0.9965849,0.00040332339,0.000058071226,0.0021151924,0.00013270776],"about_ca_topic_score_codex":0.0000014012784,"about_ca_topic_score_gemma":0.0000018738308,"teacher_disagreement_score":0.9907108,"about_ca_system_score_codex":0.000036986905,"about_ca_system_score_gemma":0.0000010969108,"threshold_uncertainty_score":0.5302537},"labels":[],"label_agreement":null},{"id":"W2158685876","doi":"10.1109/glocom.2005.1578267","title":"Delay limited optimal and suboptimal power and bit loading algorithms for OFDM systems over correlated fading channels","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"Orthogonal frequency-division multiplexing; Fading; Markov decision process; Computer science; Algorithm; Dynamic programming; Transmitter power output; Mathematical optimization; Transmission (telecommunications); Power (physics); Markov process; Mathematics; Telecommunications; Channel (broadcasting); Transmitter; Decoding methods","score_opus":0.019591539596354585,"score_gpt":0.2583814134103958,"score_spread":0.23878987381404118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158685876","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":[0.22465187,0.0076203886,0.7576935,0.0004614051,0.0013824389,0.0019148382,0.00054151326,0.0012480862,0.004485912],"genre_scores_gemma":[0.9163439,0.0029066138,0.07975875,0.00007783641,0.00015272347,0.000207906,0.00026790006,0.00007802378,0.0002063459],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99746364,0.00009707476,0.00079908577,0.00052812917,0.00021874189,0.0008933494],"domain_scores_gemma":[0.99811786,0.00024351422,0.00022094071,0.0008069355,0.0002821481,0.00032857672],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002898283,0.000549108,0.00058723456,0.000223911,0.0005052869,0.0003623707,0.0005667922,0.0003918617,0.00005327421],"category_scores_gemma":[0.00004897533,0.0006319329,0.00009489865,0.0005759373,0.0001940803,0.00080532394,0.0001706523,0.00042318393,0.000023386767],"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":[0.000037338486,0.00007600022,0.00037456784,0.000046100926,0.00018490365,0.000002824891,0.0002250149,0.9796525,0.00024423588,0.0031144267,0.0053167623,0.010725285],"study_design_scores_gemma":[0.0013418634,0.000081024125,0.0004082744,0.00016387715,0.00008526975,0.00013763676,0.00015210459,0.97555405,0.00010663616,0.00007560391,0.021227468,0.0006662186],"about_ca_topic_score_codex":0.000057268844,"about_ca_topic_score_gemma":0.000087434804,"teacher_disagreement_score":0.69169205,"about_ca_system_score_codex":0.00045242166,"about_ca_system_score_gemma":0.00007233211,"threshold_uncertainty_score":0.9996132},"labels":[],"label_agreement":null},{"id":"W2158805056","doi":"10.1109/wcnc.2007.376","title":"Minimum Selection GSC with Adaptive Modulation and Post-Combining Power Control","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":6,"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":"Natural Sciences and Engineering Research Council of Canada; Norges Forskningsråd; Qatar Foundation","keywords":"Computer science; Spectral efficiency; Power control; Fading; Quadrature amplitude modulation; Diversity combining; Telecommunications link; Transmit diversity; Bit error rate; Transmitter power output; Link adaptation; Electronic engineering; Bandwidth (computing); Interference (communication); Transmission (telecommunications); Signal-to-noise ratio (imaging); Modulation (music); Power (physics); Channel (broadcasting); Telecommunications; Engineering; Transmitter","score_opus":0.0033160230766996063,"score_gpt":0.1835008827620029,"score_spread":0.1801848596853033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158805056","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":[0.2003793,0.0000365413,0.7965844,0.0000117405325,0.00005465171,0.00014082818,6.253971e-7,0.00025877866,0.0025331033],"genre_scores_gemma":[0.9715595,0.0000056581607,0.02825368,0.0000424169,0.000030807816,0.0000031050135,0.0000062530225,0.000029331653,0.000069245725],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995012,0.000006772948,0.000118529475,0.00011835743,0.0000836619,0.00017143723],"domain_scores_gemma":[0.99974763,0.000052426152,0.000024617231,0.00005224201,0.00007812539,0.000044929275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007663859,0.00010387774,0.00009303634,0.00007235285,0.000047340724,0.000014494727,0.000018912868,0.000056298246,0.000019208339],"category_scores_gemma":[0.0000057416632,0.0000957676,0.000009201933,0.00016292524,0.000015075775,0.00024872544,0.0000036772892,0.00007945603,0.000002848013],"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":[0.00009625119,0.000006050436,0.0012271894,0.0000031162836,0.000023490004,0.0000011508307,0.00016130171,0.9878509,0.004970247,0.00055922207,0.000016683456,0.0050843707],"study_design_scores_gemma":[0.0007118396,0.00013397381,0.014958498,0.000012827486,0.000008911556,0.000009553362,0.00015119009,0.98287416,0.0009226359,0.000057022724,0.00002005512,0.00013934795],"about_ca_topic_score_codex":0.0000045947118,"about_ca_topic_score_gemma":0.000028930615,"teacher_disagreement_score":0.7711802,"about_ca_system_score_codex":0.00005086217,"about_ca_system_score_gemma":0.000004177855,"threshold_uncertainty_score":0.39052895},"labels":[],"label_agreement":null},{"id":"W2158816875","doi":"10.1109/iscas.2008.4541853","title":"An optimized link adaptation scheme for efficient delivery of scalable H.264 Video over IEEE 802.11n","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Scalable Video Coding; PHY; Scalability; Video quality; Computer network; Real-time computing; Wireless network; Channel (broadcasting); Throughput; Physical layer; Wireless; Telecommunications","score_opus":0.015871260357091497,"score_gpt":0.2261332801914164,"score_spread":0.2102620198343249,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158816875","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":[0.23610607,0.00013687296,0.7625362,0.0000077977165,0.00019687475,0.00032846406,0.000008000843,0.00027995653,0.000399737],"genre_scores_gemma":[0.6206815,0.00014863498,0.37880945,0.000020094418,0.00009788162,0.000041422973,0.000045107994,0.0000457023,0.00011018576],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990246,0.000014685771,0.00033277652,0.00020453402,0.00016911139,0.00025426646],"domain_scores_gemma":[0.9993613,0.00009639555,0.00006530325,0.00024896683,0.00015177968,0.00007626241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009126776,0.00016283261,0.0002313448,0.000100207726,0.000076575874,0.000009830915,0.00010786988,0.00011069684,0.000070446615],"category_scores_gemma":[0.000016228301,0.00017066221,0.000069502385,0.00022286114,0.00003646535,0.00025767006,0.000009744399,0.00007726108,0.000007918142],"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":[0.00007031371,0.000037577498,0.000029183087,0.000035879253,0.00002130875,7.401973e-7,0.00013176071,0.9892897,0.008084324,0.000121934994,0.00054648676,0.0016307898],"study_design_scores_gemma":[0.0012313646,0.000057180034,0.000086921464,0.000026112382,0.00001245364,0.0000018922369,0.000030354136,0.9750491,0.023072738,0.0000177883,0.00022363695,0.00019046913],"about_ca_topic_score_codex":0.000012840781,"about_ca_topic_score_gemma":0.000005299175,"teacher_disagreement_score":0.38457546,"about_ca_system_score_codex":0.0000759505,"about_ca_system_score_gemma":0.00002511139,"threshold_uncertainty_score":0.6959403},"labels":[],"label_agreement":null},{"id":"W2158900064","doi":"10.1109/icc.2009.5199167","title":"Markov Modeling for Data Block Transmission of OFDM Systems over Fading Channels","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Victoria","funders":"","keywords":"Fading; Orthogonal frequency-division multiplexing; Computer science; Nakagami distribution; Electronic engineering; Bit error rate; Channel (broadcasting); Algorithm; Computer network; Engineering","score_opus":0.02682323400074338,"score_gpt":0.25513357082626964,"score_spread":0.22831033682552626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158900064","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":[0.005088736,0.00064729457,0.9927727,0.000015613048,0.00019389579,0.00031031447,0.000012293852,0.0002031964,0.00075594423],"genre_scores_gemma":[0.94780135,0.00020362367,0.051644586,0.000008970984,0.000114062575,0.000006483502,0.00008197742,0.000028810702,0.000110157285],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927694,0.000006391858,0.00026541328,0.00016761605,0.00010019337,0.00018342707],"domain_scores_gemma":[0.99956185,0.000032555487,0.00002807598,0.00030025528,0.00003453681,0.000042718326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001069353,0.000112558744,0.00017811725,0.000058271224,0.000030509807,0.000014293698,0.00017831553,0.00006965447,0.00000696776],"category_scores_gemma":[0.0000070114515,0.00010866298,0.000026706588,0.00011706147,0.0000035186329,0.00027817683,0.000012526984,0.000050739964,4.627703e-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":[0.000010295849,0.00000738206,0.000001685502,0.00009255682,0.000010135567,1.9999878e-7,0.000041980034,0.98663807,0.0033432564,0.00018981897,0.0003957425,0.009268895],"study_design_scores_gemma":[0.00028760062,0.000018024903,0.0000010813116,0.00013747926,0.000012773521,0.0000012727604,0.000017117303,0.997797,0.0010735453,0.000087168584,0.0004408372,0.00012609112],"about_ca_topic_score_codex":0.0000041412322,"about_ca_topic_score_gemma":4.0049062e-7,"teacher_disagreement_score":0.9427126,"about_ca_system_score_codex":0.000024395476,"about_ca_system_score_gemma":0.0000048592933,"threshold_uncertainty_score":0.44311476},"labels":[],"label_agreement":null},{"id":"W2159018930","doi":"10.1109/icme.2005.1521479","title":"A client-driven scalable cross-layer retransmission scheme for 3G video streaming","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"","keywords":"Retransmission; Computer science; Computer network; Network packet; Scalability; Quality of service; Real-time computing; Wireless; Application layer; Video quality; Bandwidth (computing); Fading; Wireless network; Lossy compression; Channel (broadcasting); Telecommunications; Software deployment","score_opus":0.012658140207344038,"score_gpt":0.2654276974839236,"score_spread":0.25276955727657957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159018930","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":[0.07817568,0.00020484049,0.9150402,0.000068698675,0.00014635584,0.0003122557,0.000005949719,0.0006458026,0.0054002274],"genre_scores_gemma":[0.6478089,0.00009512506,0.3500766,0.000047376205,0.00022708108,0.000040907493,0.000031223914,0.00006026782,0.0016125327],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990621,0.0000052653936,0.00024997705,0.0002153354,0.00012096778,0.00034633625],"domain_scores_gemma":[0.9995703,0.00005204092,0.000026651716,0.00019524906,0.00006247906,0.00009324782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006500217,0.00015839042,0.00014647993,0.000057562607,0.0001029735,0.00004872553,0.00010569113,0.00011870003,0.00022377438],"category_scores_gemma":[0.0000180523,0.00015661275,0.000059580776,0.00017273886,0.000018906665,0.00044997022,0.000016578333,0.00010620683,0.000039424194],"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":[0.000014653924,0.000015191408,0.0008355031,0.000040101324,0.000011997069,3.4517936e-7,0.000044435277,0.963348,0.013372779,0.0002921621,0.0015833857,0.020441463],"study_design_scores_gemma":[0.0005951549,0.000017562716,0.00022749354,0.000049625924,0.0000061252595,0.0000012071554,0.000010466932,0.94335854,0.026633408,0.000055388435,0.028848913,0.00019610458],"about_ca_topic_score_codex":0.0000016183573,"about_ca_topic_score_gemma":0.000009022066,"teacher_disagreement_score":0.56963325,"about_ca_system_score_codex":0.00010699611,"about_ca_system_score_gemma":0.000008661199,"threshold_uncertainty_score":0.6386483},"labels":[],"label_agreement":null},{"id":"W2159055195","doi":"10.1109/twc.2006.1611068","title":"Optimal and suboptimal packet scheduling over correlated time varying flat fading channels","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":40,"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","funders":"","keywords":"Scheduling (production processes); Fading; Markov decision process; Computer science; Mathematical optimization; Network packet; Upper and lower bounds; Markov process; Channel (broadcasting); Mathematics; Computer network","score_opus":0.012200098584177655,"score_gpt":0.22893351542877058,"score_spread":0.21673341684459294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159055195","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":[0.22935331,0.00043721223,0.7677908,0.00009454094,0.00027323441,0.00029589655,0.000036904832,0.0008781922,0.0008399339],"genre_scores_gemma":[0.95812887,0.0009851872,0.040242013,0.000024377103,0.000060266004,0.00011359921,0.0000910076,0.00012339465,0.00023129024],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985181,0.00008046692,0.00047440242,0.0003053549,0.00019105822,0.00043062883],"domain_scores_gemma":[0.9984404,0.0003235275,0.00008706012,0.0009540816,0.00008247068,0.00011248144],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012611735,0.00034322438,0.0003133095,0.00029193226,0.0007130029,0.000113390524,0.00040807723,0.00022013696,0.00007459845],"category_scores_gemma":[0.00000287248,0.0004189337,0.00009590348,0.00063810847,0.00017794615,0.0005481023,0.0000107425285,0.0006846749,0.00006600657],"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":[0.00001649099,0.00006463871,0.000018912151,0.000017458555,0.000056733246,0.00000171706,0.00018603397,0.98594314,0.009284942,0.00019149874,0.000055075747,0.0041633314],"study_design_scores_gemma":[0.0005995244,0.00002618648,0.000048026923,0.00013521907,0.000062097184,0.000018333409,0.000028642968,0.99096304,0.0074800085,0.000058642272,0.00016307562,0.0004171885],"about_ca_topic_score_codex":0.00003240522,"about_ca_topic_score_gemma":0.000021220072,"teacher_disagreement_score":0.72877556,"about_ca_system_score_codex":0.0001696729,"about_ca_system_score_gemma":0.00002069396,"threshold_uncertainty_score":0.99982625},"labels":[],"label_agreement":null},{"id":"W2159507789","doi":"10.1109/glocom.2007.993","title":"QoS-Based Resource Management Scheme for Multimedia Traffic in High-Speed Wireless Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Guelph; Queen's University","funders":"","keywords":"Computer science; Computer network; Quality of service; Network packet; Wireless network; Wireless; Scheduling (production processes); Mobile QoS; Multi-frequency network; Resource allocation; Cellular network; Radio resource management; Distributed computing; Heterogeneous network; Multimedia; Service provider; Service (business); Telecommunications; Engineering","score_opus":0.006171635967197223,"score_gpt":0.21422184400892766,"score_spread":0.20805020804173044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159507789","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":[0.07467508,0.00011814407,0.92204314,0.00003156951,0.0003192395,0.00072256883,0.0000019400861,0.00063697115,0.0014513349],"genre_scores_gemma":[0.78813887,0.000035218844,0.21097757,0.00009838892,0.0002478467,0.000047587124,0.00012342894,0.00009092841,0.00024013611],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867034,0.000010806989,0.00037289347,0.0002634432,0.0001252789,0.00055721996],"domain_scores_gemma":[0.9994075,0.00018752509,0.00003866664,0.0002462528,0.00002712143,0.00009297274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002905757,0.00021832183,0.0002171467,0.00020014153,0.000042601452,0.000019412802,0.00015792547,0.0001447617,0.000026943906],"category_scores_gemma":[0.000006002011,0.00023965885,0.000050904036,0.000492506,0.000026054515,0.0000949945,0.00001905395,0.00015975785,0.000007036406],"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":[0.000068082016,0.00003432277,0.00010125016,0.000051982755,0.000017054825,0.000009475096,0.000026341038,0.9430497,0.000058489568,0.0004444351,0.0011393462,0.05499947],"study_design_scores_gemma":[0.0018957966,0.000018855566,0.000568063,0.00005664574,0.000008736212,3.2444652e-7,0.00006594656,0.99399644,0.0005023074,0.000009685405,0.002597787,0.00027939817],"about_ca_topic_score_codex":0.0000025867566,"about_ca_topic_score_gemma":0.00010361807,"teacher_disagreement_score":0.7134638,"about_ca_system_score_codex":0.00016876128,"about_ca_system_score_gemma":0.000003909996,"threshold_uncertainty_score":0.97730047},"labels":[],"label_agreement":null},{"id":"W2160068061","doi":"10.1109/vetecf.2002.1040655","title":"An efficient scheduling algorithm for packet cellular networks","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Scheduling (production processes); Network packet; Quality of service; Wireless network; Round-robin scheduling; Wireless broadband; Maximum throughput scheduling; Wireless; Weighted round robin; Distributed computing; Fair-share scheduling; Algorithm; Mathematical optimization","score_opus":0.006124536858182524,"score_gpt":0.21137773404233373,"score_spread":0.20525319718415122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160068061","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":[0.0051437174,0.00039289516,0.9923733,0.0000027246522,0.00044314013,0.00025566868,0.0000020795437,0.0004884132,0.0008980943],"genre_scores_gemma":[0.41822162,0.000032089116,0.5814315,0.000019701529,0.00014189504,0.00003100649,0.00003378277,0.00004949366,0.000038902977],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992851,0.0000151189,0.00015764215,0.0001665002,0.00007121607,0.00030444414],"domain_scores_gemma":[0.9996206,0.0000394192,0.000017957762,0.00019505157,0.000041677973,0.00008527218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012029862,0.00013340403,0.000117733885,0.00003787219,0.00007041706,0.00002824271,0.0000690499,0.00008352958,0.00004159741],"category_scores_gemma":[0.000008206585,0.00013859369,0.00003707312,0.00016762396,0.00001172928,0.00008251778,0.0000041727562,0.00008263321,0.0000056670006],"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":[8.4944526e-7,0.00001665793,0.000009317131,0.0000056028007,0.000007825885,6.781781e-7,0.000016063883,0.97714454,0.00018449407,0.0016007746,0.000073273404,0.020939918],"study_design_scores_gemma":[0.0002664294,0.000020029214,0.0000025124255,0.000007802622,0.0000072900307,0.0000010457907,0.00003593366,0.9932636,0.0049640257,0.0000942577,0.0011533678,0.00018369741],"about_ca_topic_score_codex":4.153662e-7,"about_ca_topic_score_gemma":8.967013e-7,"teacher_disagreement_score":0.41307792,"about_ca_system_score_codex":0.000043261698,"about_ca_system_score_gemma":0.000005510451,"threshold_uncertainty_score":0.5651687},"labels":[],"label_agreement":null},{"id":"W2160105039","doi":"10.1109/vetecf.2008.395","title":"Fairness Assessment of the Adaptive Token Bank Fair Queuing Scheduling Algorithm","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Communications Research Centre Canada; Carleton University","funders":"","keywords":"Computer science; Quality of service; Weighted fair queueing; Scheduling (production processes); Security token; Maximum throughput scheduling; Queueing theory; Throughput; Fair queuing; Proportionally fair; Computer network; Algorithm; Wireless; Selection algorithm; Fairness measure; Selection (genetic algorithm); Dynamic priority scheduling; Round-robin scheduling; Mathematical optimization; Telecommunications; Mathematics","score_opus":0.011304141845717994,"score_gpt":0.222371022513287,"score_spread":0.211066880667569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160105039","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":[0.02358415,0.00010069657,0.96844035,0.000017517972,0.0002726078,0.00017103697,0.0000029440212,0.00022311883,0.0071875644],"genre_scores_gemma":[0.7184156,0.00007433487,0.28129482,0.000013134186,0.000058410817,0.000012470218,0.0000028741852,0.000024894485,0.0001034367],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992387,0.000023766363,0.0002231453,0.00012893521,0.00019524072,0.00019018675],"domain_scores_gemma":[0.9995738,0.000051987503,0.00005040146,0.00021920663,0.00007108658,0.00003348287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006465547,0.00013062643,0.00016011583,0.00003942935,0.00009428553,0.000006160609,0.00015948198,0.000059478894,0.000042683754],"category_scores_gemma":[0.000007636036,0.00010300162,0.000056388155,0.00029341952,0.00004748734,0.00020164125,0.000055061744,0.0001633051,0.0000024937249],"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":[8.116566e-7,0.000008928649,0.0005054318,0.000008639723,0.000021517199,0.0000014699672,0.00011552092,0.99064016,0.00036415254,0.0010470933,0.0000478817,0.007238363],"study_design_scores_gemma":[0.00017559963,0.00000975807,0.0036447279,0.00004017628,0.0000068671657,0.000006122476,0.00014977333,0.99191767,0.0037565748,0.00008727472,0.000077029064,0.00012845284],"about_ca_topic_score_codex":0.000011933592,"about_ca_topic_score_gemma":0.000007102297,"teacher_disagreement_score":0.6948315,"about_ca_system_score_codex":0.00010424802,"about_ca_system_score_gemma":0.00002947888,"threshold_uncertainty_score":0.42002842},"labels":[],"label_agreement":null},{"id":"W2160394107","doi":"10.1109/icassp.2005.1415800","title":"Dense Wireless Sensor Networks with Mobile Sinks","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Toronto","funders":"","keywords":"Wireless sensor network; Computer science; Computer network; Key distribution in wireless sensor networks; Energy consumption; Sink (geography); Network packet; Scheduling (production processes); Wireless; Mobile radio; Sensor node; Mobile telephony; Base station; Node (physics); Data transmission; Distributed computing; Wireless network; Telecommunications; Engineering","score_opus":0.0022083702628047444,"score_gpt":0.16581021389063283,"score_spread":0.1636018436278281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160394107","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":[0.13371864,0.00020165462,0.85578585,0.000006221393,0.00010975164,0.00019430093,0.0000011675694,0.00090620236,0.009076216],"genre_scores_gemma":[0.95899415,0.00006563671,0.03953514,0.000028842358,0.00024959366,0.000046453777,0.00003337552,0.000076245364,0.00097055867],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927604,0.000009509379,0.0001607654,0.00015707951,0.00010399757,0.00029261247],"domain_scores_gemma":[0.9996562,0.00003852936,0.000022612621,0.00019621683,0.000040735486,0.00004570363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000028008908,0.00016566824,0.00015230507,0.000038834678,0.00004917871,0.000028360642,0.00006343366,0.00009153365,0.000066171],"category_scores_gemma":[6.802244e-7,0.00014424244,0.000023787585,0.00025099135,0.000030460058,0.0001241077,0.000010813793,0.00013151986,0.000022053311],"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":[0.000008318128,0.000011240682,0.00056193356,0.000008879594,0.000009582468,0.000012000316,0.0000082811075,0.99521,0.00018654426,0.00021967638,0.0013452558,0.002418267],"study_design_scores_gemma":[0.00027102503,0.00002424528,0.000275034,0.000017602999,0.000008999691,0.000014533128,0.000022174847,0.99650854,0.001048565,0.00001846393,0.0015576262,0.00023319905],"about_ca_topic_score_codex":0.000013387325,"about_ca_topic_score_gemma":0.00007510323,"teacher_disagreement_score":0.82527554,"about_ca_system_score_codex":0.000050373717,"about_ca_system_score_gemma":0.0000046321557,"threshold_uncertainty_score":0.5882036},"labels":[],"label_agreement":null},{"id":"W2160458237","doi":"10.1109/vetecf.2005.1558207","title":"An efficient QoS-based scheduling algorithm for MIMO wireless systems","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Time division multiple access; Quality of service; Scheduling (production processes); Base station; Computer network; MIMO; Real-time computing; Space-division multiple access; Wireless; Channel (broadcasting); Distributed computing; Mathematical optimization; Telecommunications; Mathematics","score_opus":0.005620950636322444,"score_gpt":0.2154653257347927,"score_spread":0.20984437509847026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160458237","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":[0.026029438,0.0002509487,0.97114104,0.00000615772,0.0007385665,0.00044952653,0.000014521408,0.00093794375,0.0004318532],"genre_scores_gemma":[0.6749129,0.0000030779577,0.3242703,0.000010470486,0.00046613038,0.00010059308,0.00011492011,0.000066026456,0.000055576893],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908566,0.00001264667,0.00025177613,0.00020634099,0.0001298358,0.0003137568],"domain_scores_gemma":[0.99954647,0.000060133174,0.00003452201,0.00021836133,0.00007983915,0.000060693932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009576802,0.00016767226,0.00017235911,0.00007809416,0.00008114268,0.00005822441,0.00010603662,0.00009000113,0.0000066843168],"category_scores_gemma":[0.0000022836207,0.0001722301,0.000043749333,0.0001907908,0.000015902866,0.00008993278,0.0000049733626,0.00006605479,0.000007346331],"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":[0.0000026607108,0.000033101434,0.00001976635,0.000047299967,0.0000055526093,9.5039536e-7,0.000005804407,0.98992294,0.0008679242,0.00095176284,0.000121249344,0.008020986],"study_design_scores_gemma":[0.0004878277,0.000024298348,0.000015819674,0.000037182046,0.000009021728,0.0000010233884,0.000033142493,0.9945422,0.0041973586,0.000011877641,0.0004112815,0.00022896024],"about_ca_topic_score_codex":0.000022275537,"about_ca_topic_score_gemma":0.000007474178,"teacher_disagreement_score":0.64888346,"about_ca_system_score_codex":0.00009678487,"about_ca_system_score_gemma":0.000012319474,"threshold_uncertainty_score":0.7023339},"labels":[],"label_agreement":null},{"id":"W2160543884","doi":"10.1109/twc.2010.101310.100587","title":"Exploiting Mobility Diversity in Sharing Wireless Access: A Game Theoretic Approach","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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 Manitoba","funders":"Nanyang Technological University; University of Manitoba","keywords":"Computer science; Computer network; Wireless; Quality of service; Channel (broadcasting); Wireless network; Reservation; Game theory; Network packet; Wireless distribution system; Wi-Fi array; Telecommunications; Mathematics","score_opus":0.03643838303487753,"score_gpt":0.26759294070629214,"score_spread":0.2311545576714146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160543884","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":[0.4210903,0.0000328316,0.5752198,0.000056863355,0.00023905223,0.00040845084,0.000022993232,0.00057291414,0.0023568152],"genre_scores_gemma":[0.99117607,0.0008480297,0.0073409406,0.000034528126,0.000030655152,0.00041945017,0.00003187429,0.00008487059,0.000033565375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982452,0.00010311453,0.0005091672,0.00043626444,0.0002498413,0.00045645976],"domain_scores_gemma":[0.9970501,0.0003421576,0.000091393726,0.002279784,0.00009748301,0.00013907584],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003422466,0.00032543004,0.00034017567,0.0003484919,0.00053702877,0.00011437361,0.0020097876,0.0002324427,0.000044089666],"category_scores_gemma":[0.000008971114,0.00038907686,0.00012366658,0.0010193902,0.0003300813,0.0008463891,0.00008062436,0.0016256295,0.000019278212],"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":[0.00001912431,0.00049964205,0.0010419413,0.000073462485,0.000037662925,0.0000011364074,0.0013423605,0.9737681,0.0021526022,0.0035535211,0.0000072805356,0.017503142],"study_design_scores_gemma":[0.0005316199,0.000012697903,0.0007631503,0.00008231437,0.000030826497,0.0000064600217,0.0002942442,0.9938591,0.0029007979,0.0010607799,0.00003594517,0.00042205345],"about_ca_topic_score_codex":0.00010608584,"about_ca_topic_score_gemma":0.00090577285,"teacher_disagreement_score":0.57008576,"about_ca_system_score_codex":0.00021057419,"about_ca_system_score_gemma":0.000027552804,"threshold_uncertainty_score":0.9998561},"labels":[],"label_agreement":null},{"id":"W2160624927","doi":"10.1109/tmm.2008.2001364","title":"Effect of Delay and Buffering on Jitter-Free Streaming Over Random VBR Channels","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":57,"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":"Queensland Cyber Infrastructure Foundation","keywords":"Jitter; Computer science; Variable bitrate; Channel (broadcasting); Real-time computing; Computer network; Performance metric; Telecommunications; Bit rate","score_opus":0.005886804516660743,"score_gpt":0.21132228290115698,"score_spread":0.20543547838449625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160624927","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":[0.49056306,0.000066096276,0.50837433,0.0000044567396,0.00050757604,0.00022890295,0.000016478776,0.00016751718,0.000071565904],"genre_scores_gemma":[0.99567163,0.00042417133,0.0036439402,0.000009758534,0.00008233889,0.000058437094,0.000004800935,0.00006198056,0.000042923784],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991179,0.000046712164,0.00022568987,0.0002024589,0.00017717922,0.000230049],"domain_scores_gemma":[0.999029,0.00055872847,0.000037556216,0.00026928095,0.000019664913,0.00008580827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008466608,0.0002335745,0.0002964879,0.00017146696,0.00010134491,0.000007768319,0.00008730706,0.0001107505,0.00003389671],"category_scores_gemma":[0.0000119006545,0.0002273567,0.00007499472,0.0001707202,0.000063520296,0.0001582957,0.0000012331549,0.00024126562,0.000008177639],"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":[0.00020862404,0.000028171105,0.00004043319,0.000056554454,0.000048657723,0.00000975768,0.00035504473,0.9536114,0.0044884835,4.345169e-7,0.00003436993,0.041118104],"study_design_scores_gemma":[0.004025266,0.00023934187,0.00023680176,0.00012717223,0.0000383456,0.0000134983375,0.0000067593214,0.8497004,0.14537446,0.0000027066749,0.000025544598,0.00020970833],"about_ca_topic_score_codex":0.000013113416,"about_ca_topic_score_gemma":0.000008968448,"teacher_disagreement_score":0.5051086,"about_ca_system_score_codex":0.000058598198,"about_ca_system_score_gemma":0.000004736975,"threshold_uncertainty_score":0.9271337},"labels":[],"label_agreement":null},{"id":"W2160794106","doi":"10.1109/pacrim.2009.5291306","title":"Sub-channel and power allocation for multiuser OFDM with rate constraints using Genetic Algorithm","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Orthogonal frequency-division multiplexing; Mathematical optimization; Resource allocation; Genetic algorithm; Computer science; Channel (broadcasting); Transmission (telecommunications); Power (physics); Throughput; Channel allocation schemes; Fitness function; Algorithm; Wireless; Mathematics; Telecommunications; Computer network","score_opus":0.007957055735733947,"score_gpt":0.2127630956205413,"score_spread":0.20480603988480736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160794106","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":[0.060829535,0.000118836244,0.9384122,0.000019650046,0.00005281808,0.0003075022,0.0000035462201,0.00014696406,0.0001089566],"genre_scores_gemma":[0.62844914,0.00004449436,0.37138006,0.00004988572,0.000025262369,0.000006915572,0.000008997336,0.000020208285,0.000015044208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99952066,0.0000063336283,0.00011776274,0.00013755464,0.000047586498,0.00017009699],"domain_scores_gemma":[0.9997614,0.000023794993,0.000022731614,0.00008406074,0.00006171099,0.00004628838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003842323,0.00011758966,0.0000998576,0.000042814623,0.000042888387,0.000020927544,0.000027551392,0.000049301958,0.0000063631037],"category_scores_gemma":[0.000004670966,0.00010901846,0.000011277965,0.0000881628,0.000031158586,0.0001365729,0.0000036045108,0.00003884627,9.470376e-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":[0.000006769849,0.0000068484705,0.000011025631,0.0000067004867,0.000010777992,0.0000010570081,0.000059825248,0.9642111,0.003095941,0.000060535556,0.000020364365,0.03250903],"study_design_scores_gemma":[0.00055840984,0.0000475721,0.00087037124,0.000022764078,0.000011693544,0.000010369638,0.00003539068,0.9930465,0.005069108,0.0001495082,0.000020560794,0.00015772128],"about_ca_topic_score_codex":0.0000010499017,"about_ca_topic_score_gemma":0.0000022120878,"teacher_disagreement_score":0.56761956,"about_ca_system_score_codex":0.000029132583,"about_ca_system_score_gemma":0.0000075299217,"threshold_uncertainty_score":0.44456437},"labels":[],"label_agreement":null},{"id":"W2160829317","doi":"10.7840/kics.2013.38a.12.1125","title":"Distributed BS Transmit Power Control for Utility Maximization in Small-Cell Networks","year":2013,"lang":"en","type":"article","venue":"The Journal of Korean Institute of Communications and Information Sciences","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Kootenay Association for Science & Technology","funders":"","keywords":"Throughput; Computer science; Enhanced Data Rates for GSM Evolution; Scheduling (production processes); Transmitter power output; Power control; Computer network; Base station; Femtocell; Distributed computing; Algorithm; Real-time computing; Power (physics); Mathematical optimization; Wireless; Mathematics; Telecommunications","score_opus":0.014579924674413528,"score_gpt":0.22401845879325186,"score_spread":0.20943853411883834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160829317","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":[0.04507503,0.0005412784,0.95237297,0.0004316806,0.00008577547,0.0003034014,0.000011420955,0.000010829355,0.0011675921],"genre_scores_gemma":[0.98409563,0.0027876585,0.013037545,0.0000453822,0.00000698023,0.000006731132,0.00001689375,0.0000024910325,6.823726e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991775,0.000037595524,0.00057553075,0.000023667571,0.00008953176,0.000096172495],"domain_scores_gemma":[0.9990406,0.0001672005,0.00028758048,0.00020365728,0.00027024184,0.00003071064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007209196,0.00006647999,0.0001323398,0.00011731186,0.00015917247,0.000048995436,0.000441357,0.000035806122,0.000006334693],"category_scores_gemma":[0.00003875335,0.00004713906,0.000028175285,0.00036535462,0.00029649193,0.002630188,0.000021340784,0.000110054374,3.7850532e-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":[0.000012486004,0.000014762354,0.00035227268,0.00001475434,0.000007016221,6.8900534e-9,0.0006195401,0.98589003,0.000035389665,0.0017844399,0.000090971764,0.011178328],"study_design_scores_gemma":[0.00054035126,0.000052843854,0.0021855237,0.0000390977,0.000012302763,0.0000035483247,0.00052440853,0.99442166,0.00010756197,0.0005522528,0.0015066416,0.000053788222],"about_ca_topic_score_codex":0.000015370646,"about_ca_topic_score_gemma":0.000023296343,"teacher_disagreement_score":0.93933547,"about_ca_system_score_codex":0.00001925,"about_ca_system_score_gemma":0.000032879143,"threshold_uncertainty_score":0.19222751},"labels":[],"label_agreement":null},{"id":"W2160876140","doi":"10.1109/glocom.2008.ecp.452","title":"Channel and Delay Margin Aware Bandwidth Allocation for Future Generation Wireless Networks","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Scheduling (production processes); Queuing delay; Queueing theory; Telecommunications link; Network packet; Bandwidth (computing); Queue; Base station; Channel (broadcasting); Bandwidth allocation; Wireless; Wireless network; Channel allocation schemes; Real-time computing; Telecommunications; Engineering","score_opus":0.011572405596431244,"score_gpt":0.1964715250601729,"score_spread":0.18489911946374166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160876140","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":[0.033339437,0.00069256226,0.9643942,0.00009256435,0.0007272308,0.0003562767,0.0000039563024,0.0002989489,0.00009478875],"genre_scores_gemma":[0.982254,0.0028170303,0.012157092,0.00008623545,0.0019692949,0.00012081669,0.00032864575,0.000055831297,0.00021100194],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993639,0.000010140137,0.00016638581,0.00018116327,0.00007300266,0.00020542857],"domain_scores_gemma":[0.9996931,0.000026780877,0.000028170844,0.00012210042,0.00007118238,0.00005864224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000049520586,0.00015172426,0.00013136686,0.000046795296,0.00015763487,0.000018127275,0.000047985635,0.00013500705,0.00000908367],"category_scores_gemma":[0.0000027928222,0.00015294598,0.000024712304,0.00013728622,0.00001843713,0.00024425343,0.0000102452605,0.00007845586,0.0000013809544],"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":[0.0000070621345,0.0000055621786,0.000059649254,0.000017348091,0.000012431075,8.85449e-7,0.000109992354,0.98741245,0.00012423252,0.00035364812,0.0050598476,0.0068368753],"study_design_scores_gemma":[0.00035353113,0.00001868828,0.000253852,0.000009289896,0.000007936933,0.000014862,0.00003566385,0.99743545,0.000522265,0.000020371908,0.0011412979,0.0001867786],"about_ca_topic_score_codex":0.0000020051114,"about_ca_topic_score_gemma":0.000038581173,"teacher_disagreement_score":0.9522371,"about_ca_system_score_codex":0.000044730463,"about_ca_system_score_gemma":0.000007426738,"threshold_uncertainty_score":0.6236956},"labels":[],"label_agreement":null},{"id":"W2160880670","doi":"10.1109/icccn.2007.4317788","title":"A New Perspective of Cross-layer Optimization for Wireless Communication over Fading Channel","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Computer science; Cross-layer optimization; Fading; Link adaptation; Physical layer; Queueing theory; Transmission (telecommunications); Optimization problem; Channel (broadcasting); Network packet; Computer network; Wireless; Coding (social sciences); Algorithm; Wireless network; Telecommunications; Mathematics","score_opus":0.01598114364886979,"score_gpt":0.2953275696894323,"score_spread":0.27934642604056253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160880670","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":[0.008114074,0.00024939622,0.9855048,0.000023097322,0.00011929453,0.00035779798,0.0000039707234,0.00023400111,0.0053935405],"genre_scores_gemma":[0.7854109,0.00012161918,0.21407177,0.000014640714,0.00007480258,0.000011501626,0.000032332693,0.000044943637,0.00021749748],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927515,0.000007207161,0.00027296832,0.00013415645,0.00010230673,0.0002081936],"domain_scores_gemma":[0.99927074,0.00012727341,0.00007699204,0.00023435279,0.00023543277,0.000055216788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016288113,0.00012477538,0.00015323504,0.00011001534,0.000066605775,0.00002283463,0.00012863331,0.00009973284,0.00006408627],"category_scores_gemma":[0.000029122319,0.00013861818,0.000049888124,0.0002832335,0.000027811837,0.00039448464,0.0000236691,0.000076773424,0.0000012265343],"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":[0.000033140015,0.00001014601,0.00009583941,0.000021541544,0.000022626466,9.136461e-8,0.0005816539,0.9843946,0.00068006385,0.012103856,0.00023453611,0.0018218778],"study_design_scores_gemma":[0.00062529877,0.000018575645,0.00025253772,0.000034343175,0.000010388222,7.642817e-7,0.0002827208,0.9857756,0.011742376,0.0010453688,0.000060147177,0.00015188371],"about_ca_topic_score_codex":0.000034814297,"about_ca_topic_score_gemma":0.00004124027,"teacher_disagreement_score":0.77729684,"about_ca_system_score_codex":0.00018119693,"about_ca_system_score_gemma":0.00001337861,"threshold_uncertainty_score":0.5652685},"labels":[],"label_agreement":null},{"id":"W2160956890","doi":"10.1109/cnsr.2005.52","title":"Rayleigh Flat Fading Channels&amp;#146; Capacity","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":50,"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":"Rayleigh fading; Fading; Fading distribution; Channel state information; Additive white Gaussian noise; Channel capacity; Channel (broadcasting); Independent and identically distributed random variables; Computer science; Rayleigh scattering; Transmission (telecommunications); Mathematics; Telecommunications; Topology (electrical circuits); Statistics; Electronic engineering; Random variable; Physics; Engineering; Wireless; Combinatorics; Optics","score_opus":0.017766360265641903,"score_gpt":0.21078397781433322,"score_spread":0.19301761754869132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160956890","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":[0.11268359,0.00014281405,0.8589925,0.00007673961,0.00043601802,0.00011280673,0.0000015751335,0.0010735852,0.026480373],"genre_scores_gemma":[0.90976316,0.000107692686,0.08814194,0.000070221235,0.0005233872,0.000011958088,0.000012315404,0.000044761626,0.0013245927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930245,0.00000809167,0.0001625919,0.0001418003,0.00010228261,0.00028278684],"domain_scores_gemma":[0.9996757,0.000028009208,0.000016843846,0.00018182289,0.0000245737,0.00007307431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051630606,0.00014313987,0.0001277683,0.00006258004,0.000058604946,0.000024531773,0.00009067894,0.00007809566,0.00039762497],"category_scores_gemma":[0.000010017541,0.00014745348,0.00003591824,0.00018701669,0.000016340653,0.0003182075,0.000018232005,0.0001290337,0.00031441823],"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":[0.0000012242127,0.0000032940156,0.000048176502,0.000008412112,0.000009388956,3.0230626e-7,0.00015459537,0.9895355,0.0019165319,0.00071720587,0.0019523399,0.005653036],"study_design_scores_gemma":[0.00020310773,0.0000045044303,0.000040288985,0.00001615903,0.0000054099264,0.000005401876,0.000010452066,0.93009907,0.01235589,0.00019880636,0.056803994,0.00025693778],"about_ca_topic_score_codex":0.0000032399373,"about_ca_topic_score_gemma":0.00003683083,"teacher_disagreement_score":0.79707956,"about_ca_system_score_codex":0.00011011588,"about_ca_system_score_gemma":0.0000026841976,"threshold_uncertainty_score":0.60129786},"labels":[],"label_agreement":null},{"id":"W2161141478","doi":"10.1155/2008/323048","title":"Multiuser Scheduling on the Downlink of an LTE Cellular System","year":2008,"lang":"en","type":"article","venue":"Journal of Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":104,"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":"Telecommunications link; Scheduling (production processes); Computer science; LTE Advanced; Computer network; Engineering; Operations management","score_opus":0.006013657413213124,"score_gpt":0.16161522822059377,"score_spread":0.15560157080738063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161141478","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":[0.44528192,0.00038446396,0.55411494,0.000007802498,0.00013131245,0.000030514333,1.8635055e-7,0.00003624631,0.000012613084],"genre_scores_gemma":[0.96605325,0.00012908649,0.033433758,0.00000889778,0.0003521602,9.376461e-7,4.176286e-7,0.000020161924,0.0000013397733],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930996,0.000015519876,0.00030615897,0.000065728964,0.00015424032,0.00014840697],"domain_scores_gemma":[0.99959636,0.000113957685,0.00007157931,0.00008811549,0.000058391975,0.00007162529],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000103685634,0.00011328628,0.00021327782,0.000104172475,0.00003766878,0.000011004223,0.000114801274,0.000049440503,8.673837e-7],"category_scores_gemma":[0.00000848887,0.00008054342,0.000051835123,0.00021183443,0.000009913173,0.0001149252,0.0000118703065,0.00028356386,5.1460944e-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":[0.00000865512,0.000013707718,0.000029864408,0.000027386328,0.000031797532,0.000025974758,0.000049570008,0.99354845,0.003142576,0.0008746575,0.000008595787,0.002238735],"study_design_scores_gemma":[0.00022209073,0.00013294703,0.00026473816,0.00009328698,0.000009439752,0.00010664249,0.0000036617444,0.99338204,0.005610841,0.000006329494,0.000082026294,0.000085981694],"about_ca_topic_score_codex":2.1619007e-7,"about_ca_topic_score_gemma":2.6741459e-8,"teacher_disagreement_score":0.5207713,"about_ca_system_score_codex":0.000039398463,"about_ca_system_score_gemma":0.000006712751,"threshold_uncertainty_score":0.32844654},"labels":[],"label_agreement":null},{"id":"W2161219661","doi":"10.1109/glocom.2009.5425586","title":"Maintaining Utility Fairness Using Weighting Factors in Wireless Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Weighting; Computer science; Fairness measure; Scheduling (production processes); Orthogonal frequency-division multiple access; Wireless; Computer network; Wireless network; Computation; Frequency-division multiple access; Orthogonal frequency-division multiplexing; Maximum throughput scheduling; Distributed computing; Scheme (mathematics); Mathematical optimization; Channel (broadcasting); Dynamic priority scheduling; Round-robin scheduling; Algorithm; Telecommunications; Quality of service; Mathematics","score_opus":0.013673124319286706,"score_gpt":0.23055431313891994,"score_spread":0.21688118881963322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161219661","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":[0.45073846,0.00004737108,0.54659724,0.000005107414,0.00012996304,0.000085267304,3.4187056e-7,0.00032879366,0.002067456],"genre_scores_gemma":[0.9898326,0.000037253347,0.009925232,0.000027394823,0.000114361996,0.0000021987287,0.000014955001,0.000035779216,0.000010273255],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988005,0.00003094778,0.00034051223,0.00022901958,0.000117983844,0.00048099886],"domain_scores_gemma":[0.99959946,0.00006992457,0.00004074587,0.00019170034,0.000025591085,0.00007255457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014963302,0.0002180824,0.00024543077,0.00011256717,0.00007274559,0.0000354481,0.0001234993,0.00013453238,0.000048588743],"category_scores_gemma":[0.000012035038,0.0002253875,0.0000404801,0.00050997734,0.000019063942,0.0003530401,0.000021108237,0.00028011133,0.0000012738888],"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":[0.0000040767222,0.000010020537,0.01505358,0.0000051248553,0.0000041774856,0.000005185788,0.00009293115,0.9718957,0.00025350778,0.0010234817,0.0000069839552,0.011645219],"study_design_scores_gemma":[0.000184984,0.000007694328,0.010357091,0.000057888985,0.000003833108,0.0000018955632,0.00017294445,0.9878779,0.00075552,0.00031601326,0.000015710646,0.0002485203],"about_ca_topic_score_codex":0.000016879707,"about_ca_topic_score_gemma":0.000036736794,"teacher_disagreement_score":0.5390941,"about_ca_system_score_codex":0.00017831127,"about_ca_system_score_gemma":0.000008925554,"threshold_uncertainty_score":0.91910356},"labels":[],"label_agreement":null},{"id":"W2161272050","doi":"10.1109/tcomm.2006.877962","title":"Dual methods for nonconvex spectrum optimization of multicarrier systems","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":1634,"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":"Mathematical optimization; Optimization problem; Duality gap; Convexity; Duality (order theory); Computer science; Strong duality; Dual (grammatical number); Convex optimization; Maximization; Mathematics; Algorithm; Regular polygon","score_opus":0.020313368459116538,"score_gpt":0.299815892806152,"score_spread":0.2795025243470355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161272050","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":[0.00008436061,0.0004501577,0.99652135,0.00010842874,0.0004913521,0.00061980257,0.00009510941,0.00032804382,0.0013014108],"genre_scores_gemma":[0.52192646,0.00033456422,0.47718492,0.0000047053436,0.000033245007,0.00028592194,0.000054182747,0.00004752609,0.00012846144],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904025,0.00010085202,0.00044891555,0.0001382537,0.0000859161,0.00018579344],"domain_scores_gemma":[0.99824154,0.0005492182,0.00008619122,0.000959687,0.00012144582,0.00004192969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016617517,0.00015627919,0.00021957983,0.00017304039,0.00021095738,0.000023132721,0.00027231933,0.000111797475,0.000019659768],"category_scores_gemma":[0.000005818642,0.00018184801,0.000097344455,0.00038851475,0.00009675462,0.00017621617,0.0000020502441,0.00017623973,0.0000037134505],"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":[0.000008887155,0.00008808684,0.0000017473441,0.000032210282,0.000039883,3.9965407e-8,0.00005218201,0.994113,0.00112448,0.0013024001,0.000074780626,0.003162259],"study_design_scores_gemma":[0.0004013477,0.00002791545,0.0000068759487,0.00003490519,0.0000610657,0.000002509287,0.00004946493,0.9869511,0.010558909,0.00018580971,0.001557707,0.00016237437],"about_ca_topic_score_codex":0.000034609762,"about_ca_topic_score_gemma":0.000039703664,"teacher_disagreement_score":0.5218421,"about_ca_system_score_codex":0.0001062164,"about_ca_system_score_gemma":0.000020552294,"threshold_uncertainty_score":0.7415547},"labels":[],"label_agreement":null},{"id":"W2161689558","doi":"10.1109/glocom.2007.989","title":"Packet-Level Channel Model for Wireless OFDM Systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Victoria","funders":"","keywords":"Orthogonal frequency-division multiplexing; Subcarrier; Fading; Computer science; Channel state information; Channel (broadcasting); Frequency domain; Bit error rate; Electronic engineering; Network packet; Wireless; Computer network; Telecommunications; Engineering","score_opus":0.03349684120164982,"score_gpt":0.24155250800688993,"score_spread":0.20805566680524012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161689558","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":[0.005049622,0.00016497946,0.99033034,0.000009081555,0.00047090164,0.00041103625,0.000021618098,0.0006025607,0.0029398794],"genre_scores_gemma":[0.9618999,0.000059873782,0.03563546,0.000029561414,0.00021505216,0.000062703504,0.000041396816,0.00008001473,0.0019760535],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991125,0.0000031472603,0.00024706294,0.00015375804,0.00010998167,0.0003735771],"domain_scores_gemma":[0.99957174,0.00006579081,0.000028936049,0.00017822694,0.00007289261,0.00008239116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016535565,0.00015327941,0.0001679822,0.000071908005,0.00005164057,0.000020325693,0.000098985176,0.00010859921,0.0000034258962],"category_scores_gemma":[0.000006955428,0.00015472725,0.00004108477,0.00014283994,0.000012610398,0.00016200427,0.000013092248,0.0000701847,0.000009701617],"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":[0.000009535298,0.000007718504,0.000006489909,0.00007310008,0.000014435097,6.5313145e-7,0.00009041836,0.9890124,0.00035299466,0.00539622,0.0015402246,0.0034957875],"study_design_scores_gemma":[0.00030491603,0.000008597476,0.000013194468,0.000025325726,0.000006334697,0.0000021516694,0.00010901334,0.9977132,0.0011329537,0.00029854427,0.00018156183,0.00020416941],"about_ca_topic_score_codex":0.000003571926,"about_ca_topic_score_gemma":0.000032075517,"teacher_disagreement_score":0.95685023,"about_ca_system_score_codex":0.00008450363,"about_ca_system_score_gemma":0.0000074317854,"threshold_uncertainty_score":0.63095945},"labels":[],"label_agreement":null},{"id":"W2161865670","doi":"10.1109/access.2015.2461007","title":"Generalized Queue-Aware Resource Management and Scheduling for Wireless Communications","year":2015,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":7,"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; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Mathematical optimization; Integer programming; Algorithm; Mathematics","score_opus":0.056122260958492244,"score_gpt":0.309308637692208,"score_spread":0.25318637673371575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161865670","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":[0.054296244,0.0010619893,0.9419893,0.00014083093,0.00022274963,0.0004744158,0.0000100867355,0.00037271623,0.0014316719],"genre_scores_gemma":[0.9103615,0.0007331099,0.08808888,0.00011062309,0.00014271401,0.00025635146,0.00007705051,0.00006666757,0.00016305073],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993854,0.000021536129,0.00017375508,0.00014580156,0.00009031908,0.00018316993],"domain_scores_gemma":[0.99930835,0.000050639,0.000038288683,0.00045432145,0.00006283961,0.00008553415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010457447,0.0001180774,0.00013398998,0.000067562156,0.00009646399,0.000090362395,0.00040823605,0.000054145316,0.0000014222735],"category_scores_gemma":[0.0000055306527,0.00013133265,0.000020487718,0.00018066775,0.000035501776,0.000305772,0.00011181411,0.00007845189,0.000002209979],"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":[0.000012491794,0.000009408675,0.00019617996,0.000069274276,0.000031999945,7.9324184e-7,0.000111255795,0.98534477,0.000042626856,0.001540709,0.002633901,0.010006602],"study_design_scores_gemma":[0.0007753698,0.000007158288,0.000049516893,0.000050263625,0.000024147897,0.0000015438455,0.00010672895,0.9826026,0.0006318947,0.00075851876,0.014807562,0.0001847131],"about_ca_topic_score_codex":0.0000062500076,"about_ca_topic_score_gemma":0.00002119457,"teacher_disagreement_score":0.85606533,"about_ca_system_score_codex":0.000061716346,"about_ca_system_score_gemma":0.0000060166426,"threshold_uncertainty_score":0.53555906},"labels":[],"label_agreement":null},{"id":"W2162065127","doi":"10.1109/wcnc.2005.1424704","title":"Dynamic downlink OFDM resource allocation with interference mitigation and macro diversity for multimedia services in wireless cellular systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Computer science; Spectral efficiency; Orthogonal frequency-division multiplexing; Telecommunications link; Resource allocation; Computer network; Quality of service; Macro; Wireless; Interference (communication); Bandwidth (computing); Channel allocation schemes; Diversity scheme; Real-time computing; Telecommunications; Channel (broadcasting)","score_opus":0.00360842911860751,"score_gpt":0.1811599019484152,"score_spread":0.17755147282980768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162065127","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":[0.5040383,0.000108882334,0.49535185,0.000033073986,0.000022721357,0.00026012407,0.000004425082,0.00010726842,0.00007335071],"genre_scores_gemma":[0.9744769,0.00007020736,0.025193995,0.000016807131,0.000029378121,0.00002609698,0.00010736971,0.000019540299,0.00005973856],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994344,0.00001609387,0.00014664697,0.00016187111,0.00007306104,0.00016789313],"domain_scores_gemma":[0.99972326,0.00005247997,0.000038962706,0.00010073069,0.000040536124,0.000044038632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008902366,0.000113806134,0.000116710005,0.00007011161,0.000059560385,0.00002784715,0.00008325839,0.00007472632,0.0000024221201],"category_scores_gemma":[0.0000020680889,0.000112754315,0.000009144988,0.00011795057,0.000021675092,0.0002663404,0.000035805464,0.00007495177,0.0000014845514],"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":[0.000027162596,0.000009659326,0.0026762167,0.00020101662,0.000009364828,5.718719e-7,0.0009965979,0.9864207,0.0027756293,0.000078398654,0.000008510077,0.0067961942],"study_design_scores_gemma":[0.00051394047,0.000019772946,0.0012741872,0.00014249976,0.000009362876,0.0000016315191,0.00040834706,0.99564093,0.0017814755,0.0000131879315,0.00005851331,0.00013615377],"about_ca_topic_score_codex":0.000047178637,"about_ca_topic_score_gemma":0.0006660607,"teacher_disagreement_score":0.47043857,"about_ca_system_score_codex":0.00015554023,"about_ca_system_score_gemma":0.000005075579,"threshold_uncertainty_score":0.45979875},"labels":[],"label_agreement":null},{"id":"W2162104643","doi":"10.1109/tcomm.2005.863788","title":"Service differentiation in multirate wireless networks with weighted round-robin scheduling and ARQ-based error control","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":47,"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 Manitoba","funders":"","keywords":"Computer science; Scheduling (production processes); Fading; Computer network; Link adaptation; Wireless network; Automatic repeat request; Hybrid automatic repeat request; Wireless; Physical layer; Weighted round robin; Round-robin scheduling; Quality of service; Channel (broadcasting); Fair-share scheduling; Telecommunications; Telecommunications link; Mathematical optimization; Mathematics","score_opus":0.010117588710305284,"score_gpt":0.2130373673373874,"score_spread":0.2029197786270821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162104643","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":[0.11291401,0.00022392692,0.88557047,0.00033714436,0.00008437056,0.00042332764,0.000020815638,0.00034487533,0.00008106058],"genre_scores_gemma":[0.9739401,0.00022666105,0.02528983,0.000078999255,0.0000203707,0.00026826555,0.000096510645,0.000066180866,0.00001308967],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896103,0.000110286084,0.00035031233,0.0002060722,0.00011545627,0.0002568448],"domain_scores_gemma":[0.99877757,0.00027300903,0.00007686092,0.000715235,0.00010286055,0.000054450706],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008264472,0.00023279995,0.0002239179,0.0002161707,0.0002918191,0.000060338967,0.00024429892,0.00013214166,0.000008256416],"category_scores_gemma":[6.6386144e-7,0.00024705162,0.000032899654,0.0007256467,0.00006951126,0.0002753107,0.0000019425718,0.00046557683,0.000004197955],"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":[0.00004168296,0.00015582713,0.00023225021,0.000019741154,0.000025971529,5.2073005e-7,0.00005132544,0.99542373,0.00082057464,0.000084899024,0.0000027259655,0.003140745],"study_design_scores_gemma":[0.0018760873,0.000024499597,0.0013301406,0.0001423594,0.000049307047,0.0000019286756,0.000045325476,0.9953789,0.0008184806,0.000038958035,0.000029015642,0.00026501072],"about_ca_topic_score_codex":0.00019207505,"about_ca_topic_score_gemma":0.007891961,"teacher_disagreement_score":0.8610261,"about_ca_system_score_codex":0.00015347882,"about_ca_system_score_gemma":0.000021671367,"threshold_uncertainty_score":0.99999815},"labels":[],"label_agreement":null},{"id":"W2162125608","doi":"10.1109/wowmom.2010.5534907","title":"Fair scheduling for real-time multimedia support in IEEE 802.16 wireless access networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"University of British Columbia","funders":"","keywords":"Computer science; Computer network; WiMAX; Wireless Multimedia Extensions; Wireless broadband; Scheduling (production processes); IEEE 802; Quality of service; Network packet; Broadband networks; IEEE 802.11e-2005; Proportionally fair; Round-robin scheduling; Wireless network; Access network; Multimedia; Wireless; Dynamic priority scheduling; Broadband; Wi-Fi array; Telecommunications","score_opus":0.009050022509773761,"score_gpt":0.25374503350079713,"score_spread":0.24469501099102337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162125608","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":[0.14127128,0.000013573951,0.8514727,0.000030054236,0.0012885826,0.0006289103,0.000007382095,0.0008290326,0.0044585313],"genre_scores_gemma":[0.8949459,0.0001711418,0.103288636,0.00004180199,0.0006144086,0.00018001861,0.0001278279,0.00013819805,0.00049203995],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984992,0.000012560189,0.00042986043,0.0003297703,0.00013463272,0.0005939452],"domain_scores_gemma":[0.99910873,0.00027584235,0.0000630601,0.0003349675,0.00007905281,0.00013836024],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021702253,0.00027329638,0.000324644,0.00014977259,0.000049558712,0.00007332963,0.00034685727,0.00029583764,0.00024449712],"category_scores_gemma":[0.00003970073,0.00029085283,0.000068442256,0.0003781941,0.000041361505,0.0006223161,0.000046432237,0.00040345945,0.000031272146],"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":[0.000018766139,0.000021231665,0.00092873396,0.000030991556,0.000013785014,0.0000030176748,0.000043113097,0.97549075,0.00579585,0.0001290033,0.001488798,0.016035946],"study_design_scores_gemma":[0.00061130413,0.000014987166,0.00029322872,0.000031752814,0.0000088389415,0.0000026505775,0.000014404587,0.9947008,0.0035639436,0.000092760434,0.00030993967,0.00035542238],"about_ca_topic_score_codex":0.000028576074,"about_ca_topic_score_gemma":0.00042262007,"teacher_disagreement_score":0.7536746,"about_ca_system_score_codex":0.0000866995,"about_ca_system_score_gemma":0.000026332447,"threshold_uncertainty_score":0.99995434},"labels":[],"label_agreement":null},{"id":"W2162189707","doi":"10.1109/surv.2011.090710.00042","title":"Congestion Pricing in Wireless Cellular Networks","year":2010,"lang":"en","type":"article","venue":"IEEE Communications Surveys & Tutorials","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University; University of Guelph","funders":"","keywords":"Computer science; Network congestion; Computer network; Quality of service; Wireless network; Radio resource management; Congestion pricing; Wireless; Revenue; Network traffic control; Telecommunications; Traffic congestion; Business; Finance; Engineering","score_opus":0.017538298309741157,"score_gpt":0.250697427154842,"score_spread":0.23315912884510084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162189707","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":[0.3389815,0.0005963712,0.648823,0.0000843074,0.00785747,0.00063675345,0.000012610238,0.0007718704,0.0022360599],"genre_scores_gemma":[0.9898797,0.0010154898,0.0080713,0.0000108710465,0.0006181333,0.00012282914,0.00016757671,0.000075408854,0.000038685084],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99804896,0.0006630619,0.0005829463,0.00020836065,0.00015292523,0.00034373478],"domain_scores_gemma":[0.9970638,0.0008864161,0.000115552415,0.0017066323,0.00014712848,0.0000804687],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0021482974,0.00021870318,0.00031838025,0.00016664242,0.00016405246,0.00006428879,0.0007757759,0.0002636278,0.000021400878],"category_scores_gemma":[0.00014263489,0.0002629384,0.000046508114,0.00071144185,0.00013950384,0.00034057934,0.00008881029,0.000755028,0.000026094292],"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":[0.000003073798,0.000050651463,0.0025992657,0.0000114387685,0.000016653015,0.0000012939646,0.00016034792,0.93453515,0.047717586,0.0020535225,0.00019495815,0.012656085],"study_design_scores_gemma":[0.00055808784,0.000011628728,0.007131427,0.00007484437,0.000017956407,0.0000028063055,0.000032037886,0.9821978,0.0056453124,0.00033239092,0.0035123753,0.00048328566],"about_ca_topic_score_codex":0.0000948128,"about_ca_topic_score_gemma":0.0014855949,"teacher_disagreement_score":0.6508982,"about_ca_system_score_codex":0.00011919169,"about_ca_system_score_gemma":0.00003213025,"threshold_uncertainty_score":0.9999823},"labels":[],"label_agreement":null},{"id":"W2162555653","doi":"10.1109/ict.2014.6845136","title":"Effect of Inter-Cell Inter-Radio Access Technology (RAT) interference on the performance of multi-RAT cellular systems","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Interference (communication); Computer science; Radio spectrum; Frequency allocation; Radio resource management; GSM; Wireless; Cellular network; Radio frequency; Computer network; Spectrum management; Frequency band; Adjacent-channel interference; Communications system; Telecommunications; Cognitive radio; Wireless network; Bandwidth (computing)","score_opus":0.006989379239352787,"score_gpt":0.21451184913977328,"score_spread":0.2075224699004205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162555653","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":[0.52133435,0.00010676565,0.47695437,0.000009811695,0.00045432325,0.00026584737,8.5658354e-7,0.00014780351,0.00072585576],"genre_scores_gemma":[0.9990694,0.00007103868,0.00055286486,0.0000055928795,0.00003125865,0.000054149386,0.000003777761,0.00003829312,0.00017360685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990519,0.00008778227,0.00038030086,0.00018270359,0.00009049971,0.00020680527],"domain_scores_gemma":[0.9990046,0.00027471784,0.00012951548,0.0004980104,0.00006626265,0.000026912929],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026482594,0.00021367848,0.00035019877,0.00017637644,0.000027191307,0.000018853487,0.00059530605,0.0001301281,0.000021365353],"category_scores_gemma":[0.000045775865,0.00014311583,0.00004767868,0.00032576095,0.00009827432,0.00015489108,0.00012028073,0.00025303438,0.0000154715],"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":[0.000041704905,0.000029325189,0.0017402451,0.0006881942,0.000023168594,4.3150678e-7,0.00007651431,0.94727343,0.042762883,0.00040751568,0.000155311,0.006801263],"study_design_scores_gemma":[0.00019623832,0.0003239147,0.0000036261831,0.00023961165,0.0000073131746,8.731859e-7,0.000018508312,0.5636702,0.4353984,0.0000017068622,0.00006133368,0.00007826221],"about_ca_topic_score_codex":0.000005740018,"about_ca_topic_score_gemma":0.000004430998,"teacher_disagreement_score":0.47773504,"about_ca_system_score_codex":0.00005153988,"about_ca_system_score_gemma":0.000004225762,"threshold_uncertainty_score":0.58360946},"labels":[],"label_agreement":null},{"id":"W2162757058","doi":"10.1109/cdc.2007.4434998","title":"Optimality of Monotone Policies for Transmission Control with Switching Costs","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Transmission (telecommunications); Markov decision process; Computer science; Mathematical optimization; Monotone polygon; Markov process; Markov chain; Channel (broadcasting); Mode (computer interface); Control theory (sociology); Latency (audio); Control (management); Mathematics; Computer network; Telecommunications","score_opus":0.004726272956899796,"score_gpt":0.2276656667461261,"score_spread":0.2229393937892263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162757058","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":[0.05167555,0.0000811378,0.94622993,0.000023767283,0.00004038897,0.00033380688,0.0000031652864,0.00016995372,0.0014423226],"genre_scores_gemma":[0.7628719,0.000013489027,0.23700616,0.000017995284,0.000039464787,0.00000891824,0.000004156185,0.000021346015,0.000016539214],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945796,0.000003987043,0.00019047005,0.0000821205,0.000078719684,0.00018673718],"domain_scores_gemma":[0.99967515,0.00010067606,0.00003084369,0.00009379062,0.000050647526,0.00004890457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013551193,0.000094443654,0.0001519958,0.000046167275,0.0000298117,0.0000051279458,0.000049421233,0.000045210767,0.0000065739036],"category_scores_gemma":[0.0000047596245,0.00007695024,0.000027346658,0.00010632234,0.0000132394325,0.00010907006,0.0000023498822,0.00004863463,2.6972552e-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":[0.00012997491,0.00001121094,0.0002233553,0.0000394018,0.00001926251,2.974194e-7,0.00009639307,0.9688968,0.010571121,0.0010137216,0.000022389895,0.018976048],"study_design_scores_gemma":[0.0010990932,0.00005890725,0.00066890003,0.000041996773,0.000014396211,0.0000014264475,0.000053325286,0.96074134,0.036863405,0.000080132515,0.00025829615,0.00011875531],"about_ca_topic_score_codex":0.000016429769,"about_ca_topic_score_gemma":0.000015507938,"teacher_disagreement_score":0.71119636,"about_ca_system_score_codex":0.00004352149,"about_ca_system_score_gemma":0.0000050902654,"threshold_uncertainty_score":0.31379396},"labels":[],"label_agreement":null},{"id":"W2162835436","doi":"10.1109/ciss.2006.286421","title":"Rate Control and Dynamic Dimensioning of Multihop Wireless Networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer network; Computer science; Wireless network; Wireless WAN; Wireless; Dimensioning; Municipal wireless network; Wi-Fi array; Heterogeneous network; Distributed computing; Wireless distribution system; Key distribution in wireless sensor networks; Telecommunications; Engineering","score_opus":0.0013739135441636356,"score_gpt":0.16629598012217964,"score_spread":0.164922066578016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162835436","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":[0.21719944,0.0005217556,0.781339,0.000007604932,0.00008547742,0.00009985397,0.0000012229348,0.00017401105,0.0005716279],"genre_scores_gemma":[0.9925408,0.00014241283,0.0071344823,0.00001326251,0.000029984712,0.0000063616317,0.000012431818,0.000030279274,0.00009000248],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947745,0.00001496294,0.00019315207,0.00010435498,0.000046684436,0.00016339099],"domain_scores_gemma":[0.9997231,0.0000897567,0.000034696048,0.00009739711,0.000029351853,0.000025696103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057284906,0.00010631356,0.00016268222,0.00003801551,0.000030101304,0.000008761608,0.00003363835,0.00005871127,0.000007316641],"category_scores_gemma":[0.0000030619524,0.00010368169,0.000017990527,0.00011256462,0.00002506057,0.00009503272,0.000011181758,0.0000712973,0.0000012884689],"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":[0.0000072788434,0.000004847777,0.00064301625,0.000011218375,0.000009507263,0.0000011592384,0.000005971478,0.98805463,0.007312363,0.00047381016,0.000052949337,0.0034232407],"study_design_scores_gemma":[0.0005886892,0.0000072834314,0.0025360603,0.000025362298,0.0000092798655,0.0000014471767,0.000006355224,0.9961279,0.000480897,0.0000791309,0.000026689464,0.00011087816],"about_ca_topic_score_codex":0.000013192699,"about_ca_topic_score_gemma":0.000050026036,"teacher_disagreement_score":0.77534133,"about_ca_system_score_codex":0.000022682532,"about_ca_system_score_gemma":0.000002014344,"threshold_uncertainty_score":0.42280164},"labels":[],"label_agreement":null},{"id":"W2163350162","doi":"10.1109/aina.2007.32","title":"An Application-Driven MAC-layer Buffer Management with Active Dropping for Real-time Video Streaming in 802.16 Networks","year":2007,"lang":"en","type":"article","venue":"Proceedings","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Retransmission; Computer science; Computer network; Frame (networking); Real-time computing; Application layer; Network allocation vector; Data link layer; Layer (electronics); Transmission (telecommunications); Base station; Time division multiple access; Physical layer; Wireless; Wireless network; Network packet; IEEE 802.11; Telecommunications","score_opus":0.004519061971771568,"score_gpt":0.22390092948436552,"score_spread":0.21938186751259395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163350162","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":[0.13193165,0.000024010293,0.85984737,0.00001636092,0.00003665969,0.0010187452,0.0000020257858,0.00041886512,0.0067042965],"genre_scores_gemma":[0.9369605,0.00010198607,0.062195074,0.000023260392,0.00019020391,0.0003228151,0.00004683831,0.000098307784,0.00006097692],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878293,0.0000021072549,0.000258402,0.00035085971,0.00014096817,0.00046474978],"domain_scores_gemma":[0.999577,0.00004192185,0.00008301429,0.000108787186,0.00010166301,0.00008763578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016315121,0.00021898872,0.00019556149,0.00017229046,0.00007965779,0.000044710454,0.00015649348,0.000099238125,0.0000066258062],"category_scores_gemma":[0.0000041877265,0.00022832915,0.000024320074,0.00046950325,0.000021919119,0.00051789585,0.000025317888,0.00014045692,0.0000037760508],"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":[0.000118522505,0.00003329456,0.001569081,0.00011291568,0.000045611436,0.0000017640848,0.00040963473,0.92609197,0.0057592043,0.001233653,0.00010635653,0.06451797],"study_design_scores_gemma":[0.0006274566,0.000053214862,0.0025817044,0.00014652971,0.00002792222,0.0000024667852,0.0003996684,0.992403,0.0028328828,0.0001950047,0.00040752484,0.0003226613],"about_ca_topic_score_codex":0.000009651349,"about_ca_topic_score_gemma":0.000024904759,"teacher_disagreement_score":0.8050289,"about_ca_system_score_codex":0.00034412224,"about_ca_system_score_gemma":0.000004002178,"threshold_uncertainty_score":0.9310993},"labels":[],"label_agreement":null},{"id":"W2163521536","doi":"10.1109/icc.2007.84","title":"Optimal Scheduling Policy Determination for High Speed Downlink Packet Access","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Granularity; Telecommunications link; Scheduling (production processes); Network packet; Dynamic priority scheduling; Computational complexity theory; Dynamic programming; Mathematical optimization; Heuristic; Bellman equation; Distributed computing; Computer network; Quality of service; Algorithm; Mathematics","score_opus":0.015054896719296662,"score_gpt":0.2977755658789145,"score_spread":0.28272066915961785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163521536","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":[0.12952553,0.000025568248,0.86785823,0.0000716017,0.0002282168,0.0002749977,0.000005105943,0.0004705998,0.0015401774],"genre_scores_gemma":[0.6863732,0.000028711589,0.3127945,0.000052535997,0.0005334139,0.000008221988,0.000060556486,0.00004129369,0.00010758379],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913335,0.0000044977273,0.00025023834,0.0001588422,0.00010428215,0.0003488033],"domain_scores_gemma":[0.9995442,0.00011151952,0.000041263418,0.0001453361,0.000084871484,0.0000727775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015972316,0.00014472664,0.00013149076,0.00019138557,0.00006551172,0.000060512513,0.0001488587,0.000106471474,0.00003177774],"category_scores_gemma":[0.0000616149,0.00015308471,0.000038348782,0.00033726828,0.000016086593,0.00049890566,0.000028954575,0.000084502615,0.000009282641],"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":[0.00001533111,0.000007366699,0.00008415623,0.000027381782,0.000008013581,0.0000011253281,0.000030117752,0.9550397,0.0011479843,0.0023231842,0.00006502851,0.04125065],"study_design_scores_gemma":[0.00048302257,0.000019970325,0.0007023581,0.000016248812,0.000008276795,0.000002630515,0.00002139543,0.96566707,0.031982616,0.0005995274,0.0002836042,0.00021326831],"about_ca_topic_score_codex":0.000008474159,"about_ca_topic_score_gemma":0.000018300208,"teacher_disagreement_score":0.55684763,"about_ca_system_score_codex":0.00014075825,"about_ca_system_score_gemma":0.000013939011,"threshold_uncertainty_score":0.6242613},"labels":[],"label_agreement":null},{"id":"W2163693360","doi":"10.1109/vtcf.2006.196","title":"Broadband Wireless Access Interference and Capacity Estimation","year":2006,"lang":"en","type":"article","venue":"IEEE Vehicular Technology Conference","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Ericsson (Canada)","funders":"","keywords":"Computer science; Computer network; Orthogonal frequency-division multiplexing; Interference (communication); Broadband networks; Throughput; Telecommunications link; Wireless broadband; Base station; Soft handover; Transmitter power output; Wireless network; Broadband; Orthogonal frequency-division multiple access; Frequency-division multiple access; Wireless; Telecommunications; Transmitter; Channel (broadcasting)","score_opus":0.011622141096426421,"score_gpt":0.21969595296988753,"score_spread":0.2080738118734611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163693360","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":[0.5168719,0.00013746,0.48170492,0.000059341524,0.00011152171,0.00011374244,0.0000031319423,0.00064785965,0.0003501142],"genre_scores_gemma":[0.992096,0.00016180013,0.007573021,0.000012287649,0.000031544103,0.00005391912,0.000013962869,0.000028338158,0.000029096796],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907017,0.000015959868,0.00024099054,0.00029238875,0.00009840776,0.0002821073],"domain_scores_gemma":[0.99950594,0.00002671425,0.00006155925,0.00026634388,0.00010310656,0.00003635991],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052521013,0.00021594296,0.00022695141,0.00023227112,0.00006770513,0.000081784114,0.00029137506,0.000295623,0.000009391312],"category_scores_gemma":[0.0000139705,0.00023220904,0.00001939372,0.00043331087,0.0002564679,0.00038167913,0.00005550209,0.00030432947,0.000010759473],"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":[0.000007672958,0.000032722688,0.0072659547,0.00010479925,0.000031867312,0.00001834641,0.000043725748,0.8648259,0.044407386,0.01572309,0.00023929194,0.06729921],"study_design_scores_gemma":[0.000252695,0.000020278247,0.0012572727,0.00009316202,0.0000143860425,0.000030582367,0.000009417452,0.9034686,0.08295702,0.011513774,0.00010332572,0.0002794612],"about_ca_topic_score_codex":0.000022146425,"about_ca_topic_score_gemma":0.000054368382,"teacher_disagreement_score":0.47522414,"about_ca_system_score_codex":0.000053407395,"about_ca_system_score_gemma":0.000013927995,"threshold_uncertainty_score":0.946921},"labels":[],"label_agreement":null},{"id":"W2163777394","doi":"10.1109/vetecf.2002.1040360","title":"Adaptive filterbank multicarrier wireless systems for indoor environments","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Subcarrier; Cyclic prefix; Orthogonal frequency-division multiplexing; Computer science; Equalization (audio); Electronic engineering; Link adaptation; Filter bank; Bit error rate; Interference (communication); Wireless; Modulation (music); Fading; Channel (broadcasting); Telecommunications; Engineering; Acoustics","score_opus":0.010957965091950557,"score_gpt":0.199342578386409,"score_spread":0.18838461329445846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163777394","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":[0.005665859,0.00033080755,0.9896875,0.00000237808,0.0004249447,0.0005602915,0.00001556596,0.0001780633,0.0031345643],"genre_scores_gemma":[0.97338796,0.000110228255,0.02514081,0.000016518416,0.000050107654,0.00023656164,0.000018002962,0.00006325415,0.0009765623],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927443,0.000018772991,0.00018421563,0.00016594338,0.00009609277,0.0002605238],"domain_scores_gemma":[0.9996469,0.00007418271,0.000025824056,0.00017066636,0.000012715906,0.000069730304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000055534758,0.00015149597,0.00015470538,0.000034077704,0.00004763277,0.000017480412,0.00006691049,0.000082824045,0.00004084913],"category_scores_gemma":[0.0000125976985,0.0001512559,0.000035933725,0.00007503303,0.000020585925,0.00014254448,0.0000074957143,0.00006626546,0.000026533187],"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":[0.000009240235,0.000011032958,0.00008731711,0.000018404739,0.000035257704,7.493331e-7,0.000048404585,0.9935382,0.0005459996,0.003950802,0.00049615547,0.0012584311],"study_design_scores_gemma":[0.0005410753,0.00003133533,0.000026506039,0.000017574232,0.000011721317,0.0000019341826,0.00010444048,0.9844772,0.0036224271,0.0000566498,0.010903453,0.00020566348],"about_ca_topic_score_codex":0.0000014162657,"about_ca_topic_score_gemma":8.269413e-7,"teacher_disagreement_score":0.9677221,"about_ca_system_score_codex":0.0000925582,"about_ca_system_score_gemma":0.000004563642,"threshold_uncertainty_score":0.61680365},"labels":[],"label_agreement":null},{"id":"W2163919934","doi":"10.1109/icn.2007.44","title":"Heuristic Approach of Optimal Code Allocation in High Speed Downlink Packet Access Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Telecommunications link; Markov decision process; Computer science; Heuristic; Dynamic programming; Network packet; Scheduling (production processes); Bellman equation; Mathematical optimization; Markov process; Reduction (mathematics); Distributed computing; Computer network; Algorithm; Mathematics","score_opus":0.012681305090994148,"score_gpt":0.24797325453623204,"score_spread":0.23529194944523787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163919934","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":[0.09246225,0.00012142559,0.9032656,0.000008890516,0.00015448825,0.0002261308,0.0000025062834,0.00019082965,0.0035678577],"genre_scores_gemma":[0.9283996,0.0001447348,0.07109305,0.000017415789,0.00011568677,0.000005527653,0.00014059468,0.000038348873,0.000045016743],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893844,0.000016075956,0.0004214882,0.00018135272,0.00013713214,0.00030552148],"domain_scores_gemma":[0.999523,0.00008876916,0.00006324693,0.00021241642,0.000055591998,0.000056983055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002506213,0.00015285701,0.00021727095,0.00014189343,0.000017973382,0.000018950528,0.00019180792,0.00013270456,0.0000312004],"category_scores_gemma":[0.000019310211,0.00016031861,0.000026604372,0.0005761175,0.000032623673,0.0002607955,0.000038102975,0.00017724236,0.0000027168944],"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":[0.000025848292,0.000035886525,0.0017287716,0.000037380752,0.000011038057,0.0000020353423,0.00004124493,0.99337274,0.00010503902,0.0010601024,0.00016797296,0.0034119613],"study_design_scores_gemma":[0.00040741454,0.000012192289,0.0083014835,0.000022201884,0.0000074060285,0.0000018503968,0.00003118454,0.98998344,0.00096397725,0.00007221018,0.000029369166,0.00016726892],"about_ca_topic_score_codex":0.000023111348,"about_ca_topic_score_gemma":0.000055897777,"teacher_disagreement_score":0.8359374,"about_ca_system_score_codex":0.0000894109,"about_ca_system_score_gemma":0.000007641088,"threshold_uncertainty_score":0.6537603},"labels":[],"label_agreement":null},{"id":"W2164066032","doi":"10.1109/wcnc.2008.325","title":"An Optimal Admission Control Policy for CDMA Multiple Antenna Systems with QoS Constraints","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Retransmission; Quality of service; Automatic repeat request; Computer science; Computer network; Throughput; Hybrid automatic repeat request; Admission control; Code division multiple access; Physical layer; Wireless; Telecommunications; Telecommunications link","score_opus":0.009024932775171983,"score_gpt":0.22160158078028,"score_spread":0.212576648005108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164066032","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":[0.026673764,0.00009880186,0.9710973,0.000023832861,0.00015482033,0.00074002595,0.00003462087,0.0006082686,0.000568597],"genre_scores_gemma":[0.9513031,0.000044005625,0.047910925,0.000037703394,0.0003778134,0.00009962449,0.000044701723,0.00006485113,0.000117231975],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991369,0.000016054406,0.00020843552,0.00019257299,0.00011438431,0.00033161836],"domain_scores_gemma":[0.99939644,0.00008182561,0.000040053666,0.0002032042,0.000097178025,0.00018127469],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046819267,0.00018406997,0.00022578645,0.000088005545,0.00011290496,0.000021016835,0.00009685762,0.00008633873,0.00002106235],"category_scores_gemma":[0.00003170526,0.00015242265,0.000030985797,0.00015065144,0.00007113199,0.00027088544,0.0000047252784,0.00007501007,0.000005276722],"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":[0.000114004426,0.000024089577,0.00065974443,0.00003244332,0.000027079,0.000007787981,0.00007653023,0.99489987,0.0026334566,0.00021958623,0.00024044892,0.0010649773],"study_design_scores_gemma":[0.002261557,0.00014093642,0.0002326955,0.000043981196,0.000008417012,0.0000756535,0.00010164513,0.9958554,0.00060115004,0.0000018637072,0.00045601412,0.00022070519],"about_ca_topic_score_codex":0.000013069212,"about_ca_topic_score_gemma":0.000004800654,"teacher_disagreement_score":0.9246294,"about_ca_system_score_codex":0.00007023413,"about_ca_system_score_gemma":0.000048108865,"threshold_uncertainty_score":0.6215615},"labels":[],"label_agreement":null},{"id":"W2164421150","doi":"10.1109/ccece.2011.6030641","title":"Interoperability between WiMAX and WiFi in a testbed environment","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Toronto Metropolitan University","funders":"","keywords":"WiMAX; Testbed; Computer network; Interoperability; Software deployment; Computer science; Throughput; Core network; Wireless; Telecommunications; Operating system","score_opus":0.01884861772258727,"score_gpt":0.16490912799978555,"score_spread":0.14606051027719827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164421150","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":[0.80281776,0.000077488374,0.18962517,0.000008040327,0.000024174105,0.00012670021,0.0000011677836,0.00012850345,0.0071910084],"genre_scores_gemma":[0.97022915,0.00007273815,0.029599082,0.0000075353473,0.000012831255,0.000010501146,0.0000027751116,0.0000134901165,0.000051894214],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99962866,0.000009429557,0.00012023576,0.00010441397,0.000032460113,0.00010478672],"domain_scores_gemma":[0.9998391,0.0000125030265,0.0000068197864,0.00010697743,0.0000023708865,0.00003220638],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004691336,0.00007020743,0.00008636512,0.000036286885,0.000007930328,0.0000036381505,0.000036998506,0.000032081076,0.00010145222],"category_scores_gemma":[0.0000040690675,0.00006629351,0.0000069000503,0.000057708585,0.000025643834,0.0001029892,0.000024245262,0.000064750166,0.000012894159],"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":[0.000015824959,0.000063460764,0.6798911,0.000056568468,0.000027550243,0.0000049152322,0.0023646415,0.20584626,0.000919869,0.00062636356,0.000076161115,0.110107265],"study_design_scores_gemma":[0.0007949534,0.00008230389,0.70198417,0.000042786316,0.000012273594,0.0000021530566,0.0001444128,0.28895828,0.0047752536,0.0017719236,0.00096585916,0.00046563934],"about_ca_topic_score_codex":0.000009396387,"about_ca_topic_score_gemma":0.000008776101,"teacher_disagreement_score":0.1674114,"about_ca_system_score_codex":0.000043129123,"about_ca_system_score_gemma":9.82088e-7,"threshold_uncertainty_score":0.2703371},"labels":[],"label_agreement":null},{"id":"W2164557595","doi":"10.1109/wcnc.2009.4917663","title":"Design and Analysis of a Splitting Algorithm for a Multi-packet Reception ALOHA System","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Aloha; Retransmission; Computer science; Network packet; Throughput; Algorithm; Interference (communication); Base station; Real-time computing; Computer network; Wireless; Channel (broadcasting); Telecommunications","score_opus":0.020136016015114114,"score_gpt":0.25048394228990084,"score_spread":0.23034792627478673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164557595","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":[0.0023495879,0.00013133192,0.9969087,0.0000038907847,0.000029601975,0.00028573716,0.000005149336,0.00022421438,0.00006173879],"genre_scores_gemma":[0.24115321,0.00004378351,0.75870776,0.000004901506,0.000017015418,0.000013974912,0.000026827196,0.000010675634,0.000021852818],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947846,0.000016109794,0.00020998123,0.00011950626,0.00005362454,0.00012232791],"domain_scores_gemma":[0.9997186,0.000060135375,0.00004635514,0.000093821465,0.00005114421,0.000029932999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014886406,0.00008721702,0.00021186362,0.00015310565,0.000027239163,0.000010464479,0.000031596952,0.000052663672,0.0000032631092],"category_scores_gemma":[0.000008535117,0.00008731058,0.000043022566,0.00044318542,0.000006762031,0.000099428435,0.0000036785511,0.000028642404,3.9949705e-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":[0.0000034675113,0.0000059274685,0.000023008935,0.000023426703,0.00009636407,1.6146424e-7,0.00007948039,0.84158313,0.0008714414,0.00009788696,0.000017674343,0.15719806],"study_design_scores_gemma":[0.00026893674,0.000028594326,0.00031776505,0.000028054701,0.00018476372,7.258159e-7,0.00008484338,0.9975905,0.001387951,0.00001080438,0.000007521765,0.00008953887],"about_ca_topic_score_codex":0.0000014303681,"about_ca_topic_score_gemma":0.0000012758538,"teacher_disagreement_score":0.23880363,"about_ca_system_score_codex":0.000046018835,"about_ca_system_score_gemma":0.0000023415832,"threshold_uncertainty_score":0.3560422},"labels":[],"label_agreement":null},{"id":"W2164752097","doi":"10.1109/wcnc.2007.563","title":"Joint Rate Control and Resource Allocation in OFDMA Wireless Mesh Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Manitoba","funders":"","keywords":"Subcarrier; Computer science; Computer network; Wireless mesh network; Resource allocation; Power control; Orthogonal frequency-division multiple access; Throughput; Transmitter power output; Orthogonal frequency-division multiplexing; Transmission (telecommunications); Resource management (computing); Wireless network; Node (physics); Interference (communication); Frequency-division multiple access; Wireless; Distributed computing; Power (physics); Transmitter; Engineering; Telecommunications; Channel (broadcasting)","score_opus":0.0053785728967046115,"score_gpt":0.19495909354005989,"score_spread":0.1895805206433553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164752097","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":[0.111231215,0.00029068755,0.8862042,0.00008712189,0.00008219912,0.00020264363,4.8361636e-7,0.00022857911,0.0016728987],"genre_scores_gemma":[0.99745286,0.0003853527,0.001751448,0.00014955277,0.00010136734,0.000015617243,0.000010211765,0.00003419036,0.0000994265],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923855,0.000023854813,0.00026231055,0.00014624212,0.000065244014,0.0002637688],"domain_scores_gemma":[0.9996758,0.00009156805,0.000031156545,0.000115536444,0.000024396406,0.000061556704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036197255,0.00012210074,0.00015685167,0.00008946964,0.000027878485,0.000018403645,0.00004462975,0.00009594537,0.000012679111],"category_scores_gemma":[0.000009610501,0.00012657596,0.000014516102,0.00023586277,0.00002217739,0.00013145027,0.000012295528,0.00014189494,0.0000020981918],"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":[0.000018898148,0.000006495039,0.001023064,0.000010516152,0.000008647735,0.0000033966535,0.00005656447,0.97105974,0.0013648072,0.0017443586,0.00020749783,0.024496019],"study_design_scores_gemma":[0.00066721503,0.0000081731305,0.009623468,0.000035088797,0.000005111513,0.0000016337376,0.000050309645,0.98837924,0.0007549673,0.000048853984,0.00028051995,0.00014539136],"about_ca_topic_score_codex":0.000010074471,"about_ca_topic_score_gemma":0.00014590612,"teacher_disagreement_score":0.88622165,"about_ca_system_score_codex":0.00006977913,"about_ca_system_score_gemma":0.0000031049372,"threshold_uncertainty_score":0.5161618},"labels":[],"label_agreement":null},{"id":"W2165020744","doi":"10.1007/s11276-008-0154-x","title":"Performance analysis of the cumulative ARQ in IEEE 802.16 networks","year":2008,"lang":"en","type":"article","venue":"Wireless Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Computer science; Goodput; Retransmission; Protocol data unit; Automatic repeat request; Protocol (science); Computer network; Real-time computing; Hybrid automatic repeat request; Throughput; Telecommunications; Wireless; Network packet","score_opus":0.009621500378044687,"score_gpt":0.20172417466518736,"score_spread":0.19210267428714267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165020744","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":[0.69204456,0.0005348492,0.30549404,0.000008418942,0.0005433149,0.00023792032,0.000003318821,0.00013755348,0.0009960277],"genre_scores_gemma":[0.9965226,0.0026269138,0.0003428448,0.00004295925,0.00021662751,0.000042057105,0.000036137153,0.00006665817,0.00010319961],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99817187,0.0000834558,0.00062559725,0.0003011306,0.00027356713,0.00054439576],"domain_scores_gemma":[0.9989237,0.0001704975,0.0001815731,0.00057206687,0.00007966914,0.00007246214],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016534857,0.0003091104,0.00060166896,0.00025801975,0.00014297677,0.000010243294,0.00039228314,0.00024825297,0.00003011024],"category_scores_gemma":[0.000007782355,0.00026848586,0.00020673285,0.0038683105,0.00017803979,0.00023951141,0.000060859667,0.0005396005,0.0000020985422],"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":[0.000021372573,0.00002376958,0.06894735,0.0000119706465,0.0002191673,0.0000030985923,0.00020585455,0.92527914,0.000011690433,0.00004165003,0.00027702353,0.0049579325],"study_design_scores_gemma":[0.00032895277,0.000012303705,0.07151006,0.00008702985,0.00012050969,0.0000029174605,0.000018730918,0.92750067,0.000089423,0.0000057790903,0.000061001974,0.00026264833],"about_ca_topic_score_codex":0.000024940358,"about_ca_topic_score_gemma":0.0002419215,"teacher_disagreement_score":0.3051512,"about_ca_system_score_codex":0.00020559317,"about_ca_system_score_gemma":0.00001892326,"threshold_uncertainty_score":0.99997675},"labels":[],"label_agreement":null},{"id":"W2165196225","doi":"10.1109/wcnc.2003.1200352","title":"Adaptive modulation, adaptive coding, and power control for fixed cellular broadband wireless systems: some new insights","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":39,"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":"Link adaptation; Wireless; Computer science; Broadband; Coding (social sciences); Power control; Modulation (music); Adaptive control; Wireless broadband; Electronic engineering; Broadband networks; Adaptive coding; Power (physics); Telecommunications; Computer network; Control (management); Wireless network; Decoding methods; Engineering; Fading; Mathematics; Physics; Algorithm; Acoustics","score_opus":0.00936511040837832,"score_gpt":0.19401622792057754,"score_spread":0.18465111751219923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165196225","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":[0.029595103,0.0017399665,0.96651673,0.000027109298,0.00039494905,0.0010128759,0.000015647518,0.00036710288,0.00033050257],"genre_scores_gemma":[0.98901147,0.00013610524,0.0101318,0.000040092422,0.00022940944,0.000051854022,0.000025345884,0.000073875075,0.00030005546],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893117,0.00001812941,0.00031394095,0.0002929808,0.00015034892,0.0002934403],"domain_scores_gemma":[0.99938184,0.00009630729,0.00007576002,0.00017439485,0.00012401215,0.00014766988],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000051666982,0.000263068,0.0003323732,0.000099028104,0.00010985617,0.0000532619,0.00008020049,0.00016839223,0.0000073207834],"category_scores_gemma":[0.000011001957,0.00025688653,0.000046315457,0.00014314616,0.000038516748,0.00054181716,0.000013842255,0.00011267154,0.0000057071516],"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":[0.00006224754,0.000012038433,0.00001866792,0.000023434319,0.00007901548,0.0000021879966,0.00040154965,0.94280005,0.0015700639,0.05444907,0.00024259796,0.00033905808],"study_design_scores_gemma":[0.0032448622,0.000121920435,0.00013677926,0.00009737659,0.000032323125,0.000002694297,0.00019355187,0.9900922,0.0019518139,0.0034917034,0.00028326918,0.00035150966],"about_ca_topic_score_codex":0.000041833388,"about_ca_topic_score_gemma":0.000021400738,"teacher_disagreement_score":0.9594164,"about_ca_system_score_codex":0.0001705769,"about_ca_system_score_gemma":0.0000348659,"threshold_uncertainty_score":0.9999883},"labels":[],"label_agreement":null},{"id":"W2165384047","doi":"10.1109/wowmom.2010.5534959","title":"Using time-of-day and location-based mobility profiles to improve scanning during handovers","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Carleton University","funders":"","keywords":"Handover; WiMAX; Computer science; Computer network; Mobility model; Channel (broadcasting); Real-time computing; Mobility management; Telecommunications; Wireless","score_opus":0.005226221117219455,"score_gpt":0.2174627177213674,"score_spread":0.21223649660414795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165384047","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":[0.6294921,0.000015376045,0.36979923,0.0000056899644,0.00009895665,0.00019738253,0.0000023150053,0.00012217704,0.00026676946],"genre_scores_gemma":[0.92227405,0.0000010036305,0.077602215,0.0000078582325,0.000043185184,0.000014439154,0.0000040085747,0.000024273706,0.00002894349],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994528,0.000007850041,0.00016255809,0.0001518601,0.0000763024,0.00014861794],"domain_scores_gemma":[0.9995912,0.000055112305,0.000029579069,0.00016860681,0.00009074305,0.000064762375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009894784,0.00010289197,0.000118591845,0.000067732675,0.00005206386,0.000016110738,0.00004918682,0.00005377992,0.00003684654],"category_scores_gemma":[0.00007124541,0.00010761431,0.000012922484,0.00024517125,0.000031564075,0.00014266222,0.000019324874,0.000092253555,0.0000028220163],"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":[0.000005339717,0.000004651131,0.0010984754,0.00005557596,0.0000042802317,1.3641207e-7,0.00005528998,0.7361604,0.26161557,0.000021827696,0.0000034728646,0.00097494863],"study_design_scores_gemma":[0.0001783679,0.000006179197,0.0019181968,0.000025691621,0.000004626542,3.7245616e-7,0.000015245741,0.7591101,0.23862867,0.0000107024725,0.0000056480626,0.00009618229],"about_ca_topic_score_codex":0.00001886155,"about_ca_topic_score_gemma":0.000013567666,"teacher_disagreement_score":0.29278198,"about_ca_system_score_codex":0.000036607235,"about_ca_system_score_gemma":0.00002050928,"threshold_uncertainty_score":0.43883842},"labels":[],"label_agreement":null},{"id":"W2165575242","doi":"10.1109/sarnof.2008.4520075","title":"Guaranteed Bandwidth Allocation and QoS support for Mobile Telemedicine Traffic","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":15,"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":"Telemedicine; Computer science; Computer network; Testbed; Bandwidth (computing); Quality of service; Wireless; Wireless network; Telecommunications; Health care","score_opus":0.007929463550844933,"score_gpt":0.21411540331293538,"score_spread":0.20618593976209046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165575242","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":[0.24046852,0.0002819479,0.75673383,0.00003137341,0.00023028623,0.0006706438,0.000004486833,0.00049014436,0.0010887345],"genre_scores_gemma":[0.97830504,0.0005109062,0.020194607,0.000063331376,0.00017118387,0.00014143645,0.00007105757,0.000032238422,0.0005102011],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995054,0.000003251784,0.00015914024,0.00011526365,0.0000658902,0.00015107461],"domain_scores_gemma":[0.99977905,0.00004088596,0.00001596991,0.00009098627,0.00003169438,0.00004140564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000045625748,0.000095518866,0.00012035399,0.000046556484,0.000054394222,0.0000040133477,0.00003575157,0.000043948545,0.000058600504],"category_scores_gemma":[0.000008025997,0.00008953541,0.000016870921,0.000098770666,0.00002940468,0.00009723576,0.000004448845,0.00004060668,0.0000042310044],"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":[0.000011032543,0.0000104290075,0.00011721815,0.0000332147,0.000010861327,0.0000013007522,0.00021421899,0.979632,0.00070583815,0.00008396448,0.004981084,0.014198809],"study_design_scores_gemma":[0.00087834214,0.00011198176,0.0003213557,0.000009520911,0.00000850788,0.000030292766,0.000058641926,0.98037046,0.0013751981,0.000012279905,0.016681595,0.00014182535],"about_ca_topic_score_codex":7.2279073e-7,"about_ca_topic_score_gemma":0.000005452905,"teacher_disagreement_score":0.73783654,"about_ca_system_score_codex":0.000020419133,"about_ca_system_score_gemma":0.000007743757,"threshold_uncertainty_score":0.3651148},"labels":[],"label_agreement":null},{"id":"W2166257010","doi":"10.1109/icc.2005.1494496","title":"Virtual queuing: an efficient algorithm for bandwidth management in resilient packet rings","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Fair queuing; Fairness measure; Throughput; Queueing theory; Bandwidth (computing); Packet loss; Network packet; Algorithm; Computer network; Distributed computing; Computational complexity theory; Dynamic priority scheduling; Quality of service; Round-robin scheduling; Wireless","score_opus":0.0060329365651158855,"score_gpt":0.2284684824121992,"score_spread":0.2224355458470833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166257010","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":[0.025208788,0.00006888831,0.9711782,0.000039468418,0.00014621101,0.00046875208,0.000003697515,0.00033353176,0.0025524863],"genre_scores_gemma":[0.5300083,0.000092547954,0.46882308,0.00006880426,0.00015217344,0.00012853082,0.000039299004,0.000057710895,0.00062953256],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909556,0.000009958962,0.00023112936,0.00022325662,0.00012739137,0.00031268763],"domain_scores_gemma":[0.9996767,0.00002523518,0.000019303327,0.00019043266,0.000019922734,0.000068372705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012794773,0.0001443303,0.00012503623,0.00012898467,0.000036102483,0.000023127677,0.00010351105,0.000049965358,0.000034124445],"category_scores_gemma":[0.000002421102,0.00015023688,0.000027807093,0.00018798707,0.0000123009795,0.00013432081,0.00001997528,0.00007052961,0.000013187384],"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":[0.0000054146253,0.00003817257,0.000008208586,0.000007362933,0.000006867915,0.0000012615756,0.00011488737,0.731646,0.00002023897,0.0019776633,0.0002815425,0.26589236],"study_design_scores_gemma":[0.000699812,0.00004154195,0.00016007423,0.000020604974,0.0000055220826,7.7346397e-7,0.00012489865,0.9927689,0.0010883127,0.000075821416,0.0048238602,0.00018989516],"about_ca_topic_score_codex":0.0000019732606,"about_ca_topic_score_gemma":0.000036629826,"teacher_disagreement_score":0.50479954,"about_ca_system_score_codex":0.00017130055,"about_ca_system_score_gemma":0.0000033883252,"threshold_uncertainty_score":0.6126482},"labels":[],"label_agreement":null},{"id":"W2166303245","doi":"10.1109/glocom.2011.6133928","title":"Diverse QoS Support in Multimedia Communication with Multiple MAC Layer Queues Using FSMC","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Computer science; Quality of service; Queue; Computer network; Markov chain; Queueing theory; Physical layer; Queue management system; Markov process; Distributed computing; Wireless; Mathematics; Telecommunications","score_opus":0.03708656945760419,"score_gpt":0.22907819022444745,"score_spread":0.19199162076684326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166303245","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":[0.4958969,0.00014817058,0.49319434,0.000008275655,0.00018486494,0.00050397374,0.000006447661,0.00068859645,0.0093684085],"genre_scores_gemma":[0.7441993,0.000100036734,0.2555564,0.0000143163625,0.00001735457,0.0000123680975,0.000026029747,0.000030448457,0.00004374504],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99943435,0.000020994134,0.00016379669,0.00011326731,0.000081103266,0.00018648192],"domain_scores_gemma":[0.99958223,0.00003771211,0.000031273194,0.00026867475,0.000036132067,0.000043997476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005937214,0.00012072871,0.0001185094,0.00008280209,0.000035513258,0.0000083523655,0.0001197948,0.00006001669,0.00022717813],"category_scores_gemma":[0.000008030793,0.000113346265,0.0000144355745,0.00018008663,0.000035192992,0.00034650796,0.000039412218,0.00011687623,0.000022631857],"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":[0.000028714627,0.00003772748,0.040830955,0.000014490564,0.000015068511,0.0000068877016,0.0017348597,0.95052415,0.00075679034,0.00006438647,0.00012417581,0.005861816],"study_design_scores_gemma":[0.0005549329,0.000013094657,0.0038121112,0.000028843333,0.000006207002,0.0000025645447,0.00043325426,0.99023783,0.004571394,0.000015075287,0.00015269098,0.00017198722],"about_ca_topic_score_codex":0.00031797655,"about_ca_topic_score_gemma":0.001818073,"teacher_disagreement_score":0.24830239,"about_ca_system_score_codex":0.000076589415,"about_ca_system_score_gemma":0.000008677701,"threshold_uncertainty_score":0.46221265},"labels":[],"label_agreement":null},{"id":"W2167049739","doi":"10.1109/icc.2005.1495038","title":"Queueing analysis and admission control for multi-rate wireless networks with opportunistic scheduling and ARQ-based error control","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Manitoba","funders":"","keywords":"Computer science; Queueing theory; Scheduling (production processes); Hybrid automatic repeat request; Computer network; Automatic repeat request; Link adaptation; Queue; Wireless network; Real-time computing; Layered queueing network; Wireless; Fading; Channel (broadcasting); Mathematical optimization; Telecommunications; Telecommunications link; Mathematics","score_opus":0.012787793135099522,"score_gpt":0.23886301711480246,"score_spread":0.22607522397970292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167049739","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":[0.036008928,0.00039818158,0.96257865,0.000118658645,0.000031877546,0.0005343643,0.000013397506,0.0002925531,0.000023358805],"genre_scores_gemma":[0.835092,0.00007046022,0.16434766,0.00019833175,0.00008313555,0.00007296098,0.000041362935,0.000055198616,0.000038877795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889755,0.000035424564,0.00030561394,0.00031700617,0.00008721506,0.00035719623],"domain_scores_gemma":[0.9991449,0.0002769552,0.00009065996,0.00016615534,0.00009041533,0.00023087855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020957187,0.00026617787,0.00044324883,0.00016275386,0.0001503943,0.000069483,0.00005771124,0.00011846146,0.0000141445535],"category_scores_gemma":[0.000029574303,0.00022948376,0.000051480816,0.00029836543,0.00004907006,0.00020911741,0.000007758887,0.0001359299,3.306509e-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":[0.00015348752,0.000016497377,0.0035448335,0.000040765244,0.00026005032,0.0000027867068,0.000018398396,0.9855158,0.00044960066,0.000120516685,0.000005028736,0.00987224],"study_design_scores_gemma":[0.004540845,0.000048895094,0.0010479355,0.000065854205,0.00055308314,0.0000016382847,0.000029427261,0.99321485,0.00012765324,0.000003600192,0.000055394736,0.0003108358],"about_ca_topic_score_codex":0.0000069937078,"about_ca_topic_score_gemma":0.00019208503,"teacher_disagreement_score":0.7990831,"about_ca_system_score_codex":0.000048313348,"about_ca_system_score_gemma":0.000021694117,"threshold_uncertainty_score":0.9358076},"labels":[],"label_agreement":null},{"id":"W2167091338","doi":"10.1155/2008/546184","title":"An Analytical Model for Optimum Byte‐Level and Packet‐Level FEC Assignment Using Buffer Dynamics","year":2008,"lang":"en","type":"article","venue":"Journal of Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Byte; Computer science; Network packet; Buffer overflow; Forward error correction; Computer network; Packet loss; Channel (broadcasting); Real-time computing; Algorithm; Computer hardware; Decoding methods","score_opus":0.03368124424610104,"score_gpt":0.23713649283746388,"score_spread":0.20345524859136283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167091338","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":[0.18849148,0.0002907891,0.8109962,0.0000128756465,0.00009414777,0.00007035819,0.00000461609,0.000037533668,0.000002038999],"genre_scores_gemma":[0.6847319,0.00018881181,0.3148019,0.000015720781,0.0002202287,0.0000015546589,0.0000026332402,0.00003145537,0.0000057873203],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906147,0.000008340934,0.0003497175,0.0001352502,0.00015731015,0.00028789492],"domain_scores_gemma":[0.99950063,0.000081619575,0.000056969315,0.0000779602,0.00008173642,0.00020107425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000967042,0.00018926678,0.0003135466,0.00015532454,0.00006358257,0.000036483074,0.00008796845,0.00009406909,6.107564e-7],"category_scores_gemma":[0.000009578097,0.00017671242,0.00005924107,0.00016022679,0.000016924836,0.00027536464,0.000021360062,0.00024643054,6.373135e-8],"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":[0.00001872534,0.000027626364,0.00018243771,0.000024980916,0.00005268413,0.0000130514945,0.000043485896,0.9892422,0.00043158644,0.0004150577,0.000043631666,0.009504552],"study_design_scores_gemma":[0.00051601004,0.00017219744,0.00069711433,0.00003432955,0.000035228193,0.0003323875,0.0000017406477,0.9977978,0.000091923255,0.000098562676,0.000013655939,0.00020905436],"about_ca_topic_score_codex":4.922874e-7,"about_ca_topic_score_gemma":3.7849244e-7,"teacher_disagreement_score":0.4962404,"about_ca_system_score_codex":0.0001496912,"about_ca_system_score_gemma":0.000021155834,"threshold_uncertainty_score":0.72061235},"labels":[],"label_agreement":null},{"id":"W2167205037","doi":"10.1142/s0219265900000147","title":"LINK-STATE AWARE DYNAMIC TRAFFIC SCHEDULING FOR PROVIDING PREDICTIVE QoS IN WIRELESS MOBILE MULTIMEDIA NETWORKS","year":2000,"lang":"en","type":"article","venue":"Journal of Interconnection Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Time division multiple access; Quality of service; Burstiness; Scheduling (production processes); Call Admission Control; Real-time computing; Wireless broadband; Wireless; Wireless network; Network packet; Engineering; Telecommunications","score_opus":0.004322295544888888,"score_gpt":0.222165718609343,"score_spread":0.21784342306445412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167205037","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":[0.32130355,0.0008701728,0.67481214,0.000019784282,0.002302251,0.00052589213,0.0000038527733,0.00014204891,0.00002033364],"genre_scores_gemma":[0.9886093,0.0028256297,0.006235897,0.00003132624,0.0019835483,0.000121023215,0.000027129787,0.000119818935,0.000046326764],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978624,0.00008023965,0.0010912122,0.00025882415,0.00017869327,0.00052864675],"domain_scores_gemma":[0.9987526,0.00038452112,0.0003214775,0.00015919059,0.00023455561,0.00014764095],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004562383,0.0003274119,0.00052014465,0.00031476803,0.00010355537,0.00007398937,0.00022540537,0.00028816238,0.000054577198],"category_scores_gemma":[0.00003464471,0.00033677262,0.00021285839,0.0005350766,0.00004279526,0.00074901833,0.000016166157,0.0009796642,0.0000021615006],"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":[0.00031044026,0.000038053593,0.00005911206,0.00003155016,0.00007499469,0.000010484808,0.00039092745,0.7707997,0.00005564213,0.000001033939,0.00012392174,0.22810411],"study_design_scores_gemma":[0.0014959673,0.0003357797,0.00009329489,0.0007977761,0.000037923473,0.00007043306,0.00021736353,0.99627006,0.0001012811,0.000020121677,0.00025772015,0.00030229986],"about_ca_topic_score_codex":0.0000021354774,"about_ca_topic_score_gemma":0.00008558215,"teacher_disagreement_score":0.66857624,"about_ca_system_score_codex":0.000546456,"about_ca_system_score_gemma":0.000032494798,"threshold_uncertainty_score":0.99990845},"labels":[],"label_agreement":null},{"id":"W2167296097","doi":"10.1109/glocom.2008.ecp.988","title":"Minimizing Interference in WiMax/802.16 Based Mesh Networks with Centralized Scheduling","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Concordia University","funders":"","keywords":"WiMAX; Computer network; Wireless mesh network; Computer science; Shared mesh; Order One Network Protocol; Mesh networking; Switched mesh; Wireless broadband; Service set; Scheduling (production processes); IEEE 802.11s; Wireless network; Distributed computing; Wireless; Wi-Fi; Telecommunications; Engineering","score_opus":0.01133425962349264,"score_gpt":0.1983588758472983,"score_spread":0.18702461622380567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167296097","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":[0.068642125,0.00018211777,0.9280522,0.000024634503,0.00012359509,0.00017392091,5.4842025e-7,0.0004493861,0.002351502],"genre_scores_gemma":[0.8456959,0.00022931004,0.15381457,0.00007106115,0.000048884816,0.000022022634,0.000018895922,0.000050457147,0.0000488996],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989358,0.000025008681,0.0002734233,0.00022627861,0.000110797984,0.0004286684],"domain_scores_gemma":[0.99956363,0.00007909892,0.0000370096,0.00020137911,0.000036296664,0.00008260637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060360915,0.00021227605,0.00023849,0.000109523135,0.00005435418,0.000019246367,0.00013158677,0.00009026288,0.00010699416],"category_scores_gemma":[0.000013072995,0.0001976651,0.000029718403,0.00047690436,0.00004521105,0.00025058628,0.000018346926,0.00024211129,0.00000565454],"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":[0.000047963997,0.0000149040225,0.0055485843,0.000014169446,0.0000099200715,0.00001976968,0.00007752093,0.9930085,0.00007592102,0.000116324285,0.00008066448,0.0009857676],"study_design_scores_gemma":[0.0010180338,0.00002253455,0.00050017465,0.00016812503,0.000004987018,0.000008999972,0.000049124257,0.9970278,0.00087058655,0.000009237699,0.000055151566,0.0002652368],"about_ca_topic_score_codex":0.000013450859,"about_ca_topic_score_gemma":0.00009705124,"teacher_disagreement_score":0.7770538,"about_ca_system_score_codex":0.00015056242,"about_ca_system_score_gemma":0.000022770973,"threshold_uncertainty_score":0.8060549},"labels":[],"label_agreement":null},{"id":"W2167402528","doi":"10.1109/tvt.2010.2060215","title":"A Model-Based Downlink Resource Allocation Framework for IEEE 802.16e Mobile WiMAX Systems","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of British Columbia","funders":"","keywords":"WiMAX; Computer science; Computer network; Quality of service; IEEE 802; Queueing theory; Orthogonal frequency-division multiple access; Network packet; Scheduling (production processes); Resource allocation; Orthogonal frequency-division multiplexing; Channel (broadcasting); Wireless; Telecommunications; Engineering","score_opus":0.007678661975642329,"score_gpt":0.22950255590663074,"score_spread":0.22182389393098842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167402528","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":[0.032734193,0.00017372532,0.9623117,0.00020066567,0.0010819141,0.0011750214,0.00004718771,0.002241145,0.000034478042],"genre_scores_gemma":[0.8757003,0.000035422414,0.12188602,0.000050718572,0.000088759436,0.0020474494,0.000024675215,0.00012076128,0.00004588509],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855155,0.000019448522,0.00038263685,0.00042505865,0.00017748162,0.00044381034],"domain_scores_gemma":[0.9987715,0.00013567842,0.000081370614,0.00079103746,0.00013999933,0.00008039677],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012801435,0.00031194807,0.00031694572,0.0003982279,0.00022547037,0.00003383207,0.00031332593,0.0010284842,0.000009856803],"category_scores_gemma":[0.0000129786595,0.00035140643,0.00012781819,0.0007007145,0.00013152063,0.00012258688,8.3660103e-7,0.0010693325,0.000025692858],"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":[0.000026391783,0.00007840473,0.000001789377,0.000069354755,0.000044626282,0.0000017943827,0.000030891642,0.9635605,0.023141515,0.001528854,0.00007082914,0.011445013],"study_design_scores_gemma":[0.00045877727,0.00010354916,4.3525316e-7,0.0000733746,0.00005411144,0.000010462082,0.000044652505,0.9175976,0.07765573,0.00097517844,0.0027076977,0.0003184658],"about_ca_topic_score_codex":0.0000024169358,"about_ca_topic_score_gemma":0.000019625028,"teacher_disagreement_score":0.84296614,"about_ca_system_score_codex":0.00013110707,"about_ca_system_score_gemma":0.000038491748,"threshold_uncertainty_score":0.9998938},"labels":[],"label_agreement":null},{"id":"W2167526439","doi":"10.1109/wcnc.2004.1311418","title":"Optimal downlink scheduling schemes for CDMA networks","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Telecommunications link; Computer science; Transmitter power output; Scheduling (production processes); Code division multiple access; Nonlinear programming; Coding (social sciences); Computer network; Mathematical optimization; Cellular network; Nonlinear system; Transmitter; Mathematics","score_opus":0.007128887914019566,"score_gpt":0.21774370533821394,"score_spread":0.21061481742419438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167526439","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":[0.014213453,0.0005264059,0.9829058,0.000058409387,0.00031263017,0.00024157735,0.0000016892423,0.0008075175,0.0009324902],"genre_scores_gemma":[0.466324,0.0001090057,0.5330911,0.000041176623,0.0002781727,0.00003990324,0.00002893058,0.00004176886,0.000045900386],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927056,0.0000024941717,0.00018413698,0.00015761046,0.000067423374,0.00031777984],"domain_scores_gemma":[0.99968404,0.000036514368,0.00002035919,0.00015013068,0.00004442912,0.000064548956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053339227,0.0001473499,0.00013549978,0.000042942276,0.00007091765,0.000030499707,0.000096963595,0.00010639408,0.000027068972],"category_scores_gemma":[0.000014939227,0.0001519913,0.00005482779,0.00016889922,0.000018255374,0.00020723323,0.000017701617,0.00011742937,0.000012733771],"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":[0.0000068397776,0.00000697267,0.000015786547,0.000014474674,0.00001776707,6.727587e-7,0.000016717077,0.9888259,0.00014575325,0.0048585692,0.00007990201,0.006010654],"study_design_scores_gemma":[0.00062014826,0.000018076966,0.000008908568,0.000027974895,0.000008242318,0.0000022008674,0.000019857252,0.9938735,0.0024089913,0.00031832076,0.0024935592,0.00020022939],"about_ca_topic_score_codex":8.652841e-7,"about_ca_topic_score_gemma":0.0000028542079,"teacher_disagreement_score":0.45211056,"about_ca_system_score_codex":0.000076918586,"about_ca_system_score_gemma":0.000010421174,"threshold_uncertainty_score":0.61980253},"labels":[],"label_agreement":null},{"id":"W2167620763","doi":"10.1109/icc.2006.255412","title":"Per-user Throughput of Opportunistic Scheduling Scheme over Broadcast Fading Channels","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fading; Computer science; Scheduling (production processes); Throughput; Channel (broadcasting); Computer network; Transmission (telecommunications); Wireless; Real-time computing; Mathematical optimization; Mathematics; Telecommunications","score_opus":0.07149299120821652,"score_gpt":0.3182595882033603,"score_spread":0.2467665969951438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167620763","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":[0.0491986,0.0004430661,0.7943465,0.0010142219,0.0014788775,0.00042680456,0.00023354725,0.00053072034,0.15232767],"genre_scores_gemma":[0.9551996,0.00077417627,0.042640384,0.0000450788,0.00017049073,0.000050599785,0.00036181306,0.000042664982,0.00071519014],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988557,0.000035429497,0.0004618613,0.0001825848,0.0002604666,0.0002039292],"domain_scores_gemma":[0.9986781,0.00012757964,0.00015337608,0.0007612118,0.00023283552,0.000046908142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000084115956,0.00019293488,0.0001937325,0.00018080523,0.00010770307,0.00006312676,0.0008550939,0.0000945531,0.00027515794],"category_scores_gemma":[0.0000212735,0.00022504774,0.00006798306,0.00018780943,0.0001300804,0.000299896,0.000093381364,0.00028331464,0.00004483626],"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":[0.0000085060865,0.000102160106,0.00042809924,0.000014297163,0.000048257818,9.224219e-7,0.000081449754,0.7762862,0.014557827,0.20633626,0.0005496018,0.0015864327],"study_design_scores_gemma":[0.00030637134,0.000015975033,0.00026924704,0.00016927064,0.000011580395,0.0000035885405,0.00006279997,0.9895372,0.0017173894,0.0023016243,0.0053697624,0.00023521291],"about_ca_topic_score_codex":0.00003086313,"about_ca_topic_score_gemma":0.000025512081,"teacher_disagreement_score":0.90600103,"about_ca_system_score_codex":0.00010343187,"about_ca_system_score_gemma":0.00003818167,"threshold_uncertainty_score":0.91771805},"labels":[],"label_agreement":null},{"id":"W2167822064","doi":"10.1109/tvt.2009.2014383","title":"Energy Management Analysis and Enhancement in IEEE 802.16e WirelessMAN","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Sleep mode; Energy consumption; Computer science; IEEE 802; Energy management; Efficient energy use; Energy (signal processing); Power management; Wireless; Computer network; Power (physics); Reliability engineering; Power consumption; Engineering; Telecommunications; Electrical engineering","score_opus":0.0032614981815286253,"score_gpt":0.1950647030364311,"score_spread":0.19180320485490246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167822064","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":[0.108629115,0.00023129307,0.89001554,0.00017133736,0.00011981846,0.000140404,0.0000022183756,0.00046718976,0.00022310473],"genre_scores_gemma":[0.9881778,0.0022313949,0.009286706,0.00007058129,0.000009882786,0.00009985149,0.000005463968,0.000024418163,0.00009393099],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998895,0.000018181063,0.0002943659,0.00033744448,0.00013392798,0.00032111543],"domain_scores_gemma":[0.99952686,0.000012456356,0.00003440065,0.00036112746,0.000020961395,0.00004416939],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000054905693,0.00021934308,0.00030056926,0.0013813621,0.000072628856,0.000013564742,0.00013849481,0.00022623643,0.000020586884],"category_scores_gemma":[3.428053e-7,0.00025175503,0.00007000474,0.0020283945,0.000052342348,0.00009337271,0.0000011252519,0.00024919875,0.000006144379],"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":[0.0000075671846,0.000074527714,0.000016702908,0.0000089355735,0.00018889412,0.000024803385,0.00001821244,0.8035732,0.0031667182,0.00052126584,0.000008418492,0.19239078],"study_design_scores_gemma":[0.00069171644,0.00013881156,0.00026300448,0.000049421134,0.00027702254,0.000007754682,0.00005124974,0.85071355,0.14585851,0.00095838826,0.0005916307,0.00039895996],"about_ca_topic_score_codex":0.0000068601544,"about_ca_topic_score_gemma":0.0001460186,"teacher_disagreement_score":0.88072884,"about_ca_system_score_codex":0.00014653665,"about_ca_system_score_gemma":0.0000034927616,"threshold_uncertainty_score":0.99999344},"labels":[],"label_agreement":null},{"id":"W2167973273","doi":"10.1109/cwit.2013.6621601","title":"Distributed resource allocation in femtocell networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Femtocell; Computer science; Graph coloring; Computer network; Resource allocation; Distributed computing; Graph; Reuse; Telecommunications link; Theoretical computer science; Engineering; Base station","score_opus":0.004267586959612823,"score_gpt":0.1749221592568799,"score_spread":0.17065457229726708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167973273","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":[0.01833367,0.00011956537,0.9742591,0.00007375371,0.00006037372,0.00022997083,6.0338425e-7,0.0003886528,0.006534348],"genre_scores_gemma":[0.9947965,0.000056814428,0.0046557593,0.00004389718,0.00005622716,0.000056547615,0.00013010178,0.000024481566,0.00017965236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949765,0.000010791928,0.00015457858,0.00009627104,0.000052922584,0.00018775956],"domain_scores_gemma":[0.9997664,0.00003012635,0.000013522301,0.0001318815,0.00001953995,0.000038510505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000034815104,0.000084287305,0.0000769886,0.00003918913,0.000015596472,0.000021194963,0.00006718963,0.000066617715,0.00013728617],"category_scores_gemma":[0.0000066257994,0.000087325745,0.00001197386,0.0002946065,0.000009150403,0.00017135422,0.000012706143,0.000099212295,0.000061324885],"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":[8.3720477e-7,0.000005165763,0.0006437243,0.0000038020041,0.000001969015,3.2386032e-7,0.000013072123,0.98829776,0.00006914187,0.00019330972,0.005080541,0.0056903665],"study_design_scores_gemma":[0.00013624527,0.0000036338492,0.0038130288,0.000009703369,0.0000010360768,4.5202788e-7,0.000024760888,0.99381214,0.00015466151,0.000099932855,0.0018412321,0.00010315141],"about_ca_topic_score_codex":0.000015263357,"about_ca_topic_score_gemma":0.000022201753,"teacher_disagreement_score":0.97646284,"about_ca_system_score_codex":0.00006728267,"about_ca_system_score_gemma":0.0000018899592,"threshold_uncertainty_score":0.35610405},"labels":[],"label_agreement":null},{"id":"W2168144779","doi":"10.1109/wcnc.2004.1311419","title":"Downlink resource management with adaptive modulation and dynamic scheduling for OFDM wireless communication systems","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"University of Waterloo","funders":"","keywords":"Computer science; Orthogonal frequency-division multiplexing; Link adaptation; Telecommunications link; Scheduling (production processes); Wireless; Computer network; Real-time computing; Electronic engineering; Fading; Telecommunications; Channel (broadcasting); Engineering","score_opus":0.006071296273631403,"score_gpt":0.19878078923121598,"score_spread":0.19270949295758458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168144779","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":[0.044758286,0.000474753,0.95270854,0.0000398136,0.000027590031,0.00071265985,0.0000030507288,0.0003070247,0.0009682733],"genre_scores_gemma":[0.75973856,0.00018645056,0.23980087,0.0000073364345,0.000012337717,0.00010429803,0.000068487214,0.000033073535,0.00004856123],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994296,0.000011773368,0.00016683507,0.00015257702,0.00009107617,0.0001481703],"domain_scores_gemma":[0.999612,0.000033821558,0.00004637944,0.00022760256,0.000046087323,0.0000341139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007965904,0.00012513324,0.000121505895,0.000070089554,0.00010265543,0.000036714093,0.00007394064,0.00005396935,5.6572316e-7],"category_scores_gemma":[0.0000012971037,0.0001194305,0.000012437031,0.00014852519,0.000026020542,0.00020148681,0.000022395625,0.000070277754,0.0000011215468],"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":[0.000026682686,0.0000072425373,0.000015563044,0.000070863665,0.000035873567,3.3691265e-7,0.00011348476,0.9756182,0.00005201836,0.018024629,0.0000032179755,0.006031911],"study_design_scores_gemma":[0.00083872076,0.000032189306,0.00022217749,0.00020322732,0.000020186253,0.0000029029377,0.000594352,0.9974006,0.00004587993,0.00041635975,0.00006597629,0.00015742565],"about_ca_topic_score_codex":0.0000075065204,"about_ca_topic_score_gemma":0.000027488171,"teacher_disagreement_score":0.7149803,"about_ca_system_score_codex":0.00016246532,"about_ca_system_score_gemma":0.0000034843115,"threshold_uncertainty_score":0.48702344},"labels":[],"label_agreement":null},{"id":"W2168260430","doi":"10.1109/wcnc.2008.172","title":"Multiuser Scheduling for MIMO-OFDM Systems with Continuous-Rate Adaptive Modulation","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Université du Québec à Montréal; Polytechnique Montréal","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Scheduling (production processes); Link adaptation; Multipath propagation; Fading; MIMO; Spectral efficiency; MIMO-OFDM; Diversity scheme; Exploit; Electronic engineering; Channel (broadcasting); Control theory (sociology); Real-time computing; Computer network; Mathematical optimization; Mathematics; Engineering","score_opus":0.016067180737079214,"score_gpt":0.20100620058464616,"score_spread":0.18493901984756694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168260430","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":[0.09743554,0.00013652348,0.90041804,0.0000060688653,0.00018141004,0.0005626083,0.0000045737884,0.00050645013,0.00074880646],"genre_scores_gemma":[0.83243406,0.0000377178,0.16676404,0.000009517246,0.00012280254,0.00010508371,0.0000276279,0.00005806995,0.00044110927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993243,0.000012851303,0.00018746512,0.00016952869,0.000085751475,0.00022007481],"domain_scores_gemma":[0.99956024,0.000074345655,0.000045247678,0.00013623708,0.0001364234,0.000047494264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057447483,0.00015205845,0.00018054462,0.00005364339,0.000094751114,0.00001654067,0.00005138736,0.00007089131,0.0000049249297],"category_scores_gemma":[0.00001097224,0.00013504193,0.000025588351,0.0001447266,0.000021776783,0.00029458484,0.000006320361,0.00006835316,0.000008612249],"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":[0.00003750225,0.0000071065747,0.00035200777,0.000022512555,0.000031620988,0.0000018658595,0.000106779305,0.9978139,0.0005599322,0.00058534864,0.00009547043,0.00038598874],"study_design_scores_gemma":[0.00068089506,0.000045471916,0.00037384185,0.000047913898,0.000008977927,0.00000667103,0.00010897808,0.9974774,0.00080712436,0.00001547692,0.00022672504,0.00020048967],"about_ca_topic_score_codex":0.000010043277,"about_ca_topic_score_gemma":0.000011947133,"teacher_disagreement_score":0.73499846,"about_ca_system_score_codex":0.000062299165,"about_ca_system_score_gemma":0.000009409272,"threshold_uncertainty_score":0.550685},"labels":[],"label_agreement":null},{"id":"W2168618447","doi":"10.1109/tvt.2007.904547","title":"Efficiency and Goodput Analysis of Dly-ACK in IEEE 802.15.3","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Goodput; Computer science; Markov chain; Transmission (telecommunications); Electronic engineering; Channel (broadcasting); Wireless; Computer network; Algorithm; Throughput; Engineering; Telecommunications","score_opus":0.004732631084200243,"score_gpt":0.21628067977287216,"score_spread":0.2115480486886719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168618447","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":[0.3955517,0.00016843273,0.6037568,0.000022628068,0.00009930813,0.00009999581,0.0000047727517,0.00022665836,0.00006968615],"genre_scores_gemma":[0.9944162,0.00030960733,0.005195148,0.000010491804,0.000006443885,0.00001813506,0.000002766063,0.000027838352,0.000013379567],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989955,0.000012294592,0.00035225475,0.0002385497,0.0001154832,0.00028591696],"domain_scores_gemma":[0.99951535,0.000057673322,0.00004640287,0.00030361503,0.00003902809,0.00003794399],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013822434,0.00016090261,0.00033137988,0.0017585703,0.00004393538,0.0000046636806,0.00012711964,0.00030826824,0.00001596596],"category_scores_gemma":[0.000003943536,0.00018131237,0.00007580501,0.0033499477,0.00012747188,0.000074377574,0.0000010892218,0.0003265744,0.0000039843108],"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":[0.000010062501,0.000065153385,0.0002554511,0.000015407086,0.00014526112,0.00001109527,0.000049954026,0.9678883,0.011753955,0.000093339404,0.0000018772218,0.019710135],"study_design_scores_gemma":[0.0004334951,0.000080185986,0.0006996564,0.00003046864,0.00021394285,0.00000891302,0.000099284654,0.8573726,0.14066496,0.0000899478,0.000085117004,0.00022144383],"about_ca_topic_score_codex":0.00000845162,"about_ca_topic_score_gemma":0.00026570645,"teacher_disagreement_score":0.5988645,"about_ca_system_score_codex":0.000080208025,"about_ca_system_score_gemma":0.0000069676444,"threshold_uncertainty_score":0.7393704},"labels":[],"label_agreement":null},{"id":"W2168770805","doi":"10.1109/pacrim.2007.4313289","title":"Performance of Equal Power Subchannel Loading in Multiuser OFDM systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Orthogonal frequency-division multiplexing; Power (physics); Signal-to-noise ratio (imaging); Computer science; Simple (philosophy); Noise (video); Electronic engineering; Telecommunications; Engineering; Physics; Channel (broadcasting)","score_opus":0.007371447554627345,"score_gpt":0.20639537484548978,"score_spread":0.19902392729086243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168770805","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":[0.7104216,0.00012990931,0.28345343,7.994905e-7,0.00028317416,0.000100030025,5.5582467e-7,0.000111255555,0.005499197],"genre_scores_gemma":[0.9965691,0.000049136248,0.0031713946,0.000004011847,0.000035182773,0.0000039093006,0.0000029814473,0.00002685688,0.00013742359],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928725,0.0000052836567,0.00028423144,0.000088742694,0.00010102795,0.0002334413],"domain_scores_gemma":[0.99974513,0.000047070123,0.00002976216,0.00011425942,0.000031065818,0.000032735217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019217703,0.000092285096,0.0001370001,0.00012797577,0.00001169941,0.0000046873824,0.000066903616,0.00006594209,0.000019762987],"category_scores_gemma":[0.000007748496,0.0000936105,0.000015974214,0.00026351123,0.000011713893,0.0001913755,0.000013142106,0.000084641615,0.0000110925575],"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":[0.000010994562,0.000008308443,0.007792797,0.000056137003,0.0000043959117,0.0000017741532,0.00019488319,0.98871607,0.0024828203,0.00027951333,0.000025660309,0.00042664344],"study_design_scores_gemma":[0.00025619514,0.000017901404,0.002624453,0.000075793185,0.0000013229574,0.000001675294,0.00015924392,0.98861855,0.008063296,0.0000019454824,0.0000633777,0.000116227646],"about_ca_topic_score_codex":0.000011360404,"about_ca_topic_score_gemma":0.000019070236,"teacher_disagreement_score":0.28614748,"about_ca_system_score_codex":0.0000690288,"about_ca_system_score_gemma":0.0000031431061,"threshold_uncertainty_score":0.38173255},"labels":[],"label_agreement":null},{"id":"W2168982656","doi":"10.1109/wcnc.2011.5779163","title":"QoS-aware bit scheduling in multi-user OFDM systems","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Computer network; Quality of service; Multi-user; Scheduling (production processes); Jitter; Orthogonal frequency-division multiplexing; Network packet; Real-time computing; Channel (broadcasting)","score_opus":0.03359588858814794,"score_gpt":0.22347348635182057,"score_spread":0.18987759776367263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168982656","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":[0.04235006,0.00034455722,0.9522145,0.000002275582,0.00058671006,0.0001903866,0.0000012810704,0.0005633024,0.0037469508],"genre_scores_gemma":[0.9276094,0.000079614976,0.071583696,0.000010002077,0.00006373592,0.000029406265,0.0000061027185,0.00004800531,0.00057004276],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993654,0.000011581143,0.00020729417,0.00013125641,0.00006727794,0.00021722993],"domain_scores_gemma":[0.99972785,0.000015506286,0.000019427598,0.00016600627,0.000026391726,0.00004481235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000056495453,0.00011739204,0.00013320951,0.00009357871,0.000018065388,0.000012543429,0.00009053533,0.00008400034,0.000070333095],"category_scores_gemma":[0.000007687577,0.00011807062,0.000018941655,0.00022444989,0.0000093092385,0.00021077837,0.000019280098,0.00011504301,0.000073930845],"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":[0.0000020391515,0.000012321735,0.0029434713,0.00003668221,0.0000066189077,0.000004837649,0.0001849459,0.99568754,0.00015857883,0.0006383697,0.000054351,0.00027020983],"study_design_scores_gemma":[0.00028451358,0.0000048785914,0.0010142103,0.00006779993,0.000002481936,0.0000016929205,0.00022338502,0.99713844,0.00075235165,0.0000058730666,0.00034543668,0.00015896204],"about_ca_topic_score_codex":0.000051148552,"about_ca_topic_score_gemma":0.000070604416,"teacher_disagreement_score":0.88525933,"about_ca_system_score_codex":0.000060369624,"about_ca_system_score_gemma":0.000004466037,"threshold_uncertainty_score":0.481478},"labels":[],"label_agreement":null},{"id":"W2169032273","doi":"10.1109/glocom.2005.1578205","title":"Reactive cognitive radio algorithms for co-existence between IEEE 802.11b and 802.16a networks","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Nortel (Canada)","funders":"","keywords":"Cognitive radio; Computer science; Computer network; Throughput; Radio resource management; Interference (communication); Co-channel interference; Wireless; Frequency band; IEEE 802.11; Power control; Wireless network; Channel (broadcasting); Telecommunications; Power (physics); Bandwidth (computing)","score_opus":0.03399956503745423,"score_gpt":0.29820018840138446,"score_spread":0.26420062336393024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169032273","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":[0.016375545,0.0025554849,0.9601441,0.0006390682,0.00059826684,0.0019378825,0.0014008791,0.0009905136,0.015358252],"genre_scores_gemma":[0.894277,0.0041667386,0.09875664,0.00020165875,0.00066126353,0.00048268674,0.0011209985,0.000097949705,0.00023510013],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967887,0.00018394402,0.0009254439,0.0006871099,0.00029949102,0.0011153191],"domain_scores_gemma":[0.9969112,0.00071650045,0.00032123737,0.0011309593,0.0005049227,0.00041515628],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036697657,0.0006836803,0.00079045433,0.00016359065,0.0006390926,0.00022298755,0.0010261728,0.00046028008,0.000056639085],"category_scores_gemma":[0.00008230063,0.0008043111,0.00016886227,0.0006682728,0.00043610096,0.0008634228,0.00011909354,0.0006921151,0.00006742303],"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":[0.0001369616,0.00034095693,0.0033268766,0.00009109481,0.0008580809,0.0000061283854,0.0005179445,0.5287677,0.00011064718,0.004332026,0.030943535,0.43056804],"study_design_scores_gemma":[0.0024886893,0.00016454898,0.0036929408,0.00027512704,0.00028903768,0.000068628455,0.00034582042,0.9447983,0.00064330566,0.0012829187,0.04455959,0.0013910917],"about_ca_topic_score_codex":0.00006492568,"about_ca_topic_score_gemma":0.00045941854,"teacher_disagreement_score":0.87790143,"about_ca_system_score_codex":0.0007013607,"about_ca_system_score_gemma":0.00016382807,"threshold_uncertainty_score":0.9994408},"labels":[],"label_agreement":null},{"id":"W2169088364","doi":"10.1109/icc.1993.397416","title":"Fair-efficient call admission control policies for broadband networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Arbitration; Computer network; Blocking (statistics); Mathematical optimization; Throughput; Maximization; Nash equilibrium; Service (business); Scheme (mathematics); Admission control; Scalability; Markov decision process; Markov process; Operations research; Quality of service; Telecommunications; Mathematics; Law; Economics","score_opus":0.008665451604703056,"score_gpt":0.20586268415154177,"score_spread":0.1971972325468387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169088364","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":[0.0017579017,0.0009542163,0.9915685,0.000112201844,0.0002601037,0.00037203738,0.0000052646815,0.0005135498,0.00445622],"genre_scores_gemma":[0.9914021,0.00017554584,0.0066712685,0.00015420713,0.00024065629,0.000054659526,0.000011461737,0.000046991114,0.0012430935],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999276,0.000007971466,0.00018273499,0.00013321602,0.000082135135,0.0003179628],"domain_scores_gemma":[0.9996057,0.00008660344,0.000022880544,0.00014497066,0.00003915844,0.00010068014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003987546,0.00014112842,0.00015075711,0.000045667377,0.00007435815,0.000024201714,0.000077027835,0.00008819433,0.0001346769],"category_scores_gemma":[0.000017817763,0.00012770707,0.000050835104,0.0001314527,0.000016426173,0.000059654514,0.000009219623,0.00007572445,0.000011736928],"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":[0.0000066227717,0.000014602716,0.000039188086,0.000010388963,0.00001089243,3.617997e-7,0.000047168745,0.9756547,0.00012244322,0.00039675963,0.0162501,0.007446778],"study_design_scores_gemma":[0.00071523053,0.000024883006,0.00005190643,0.000015498083,0.000010054744,0.0000015873334,0.00000978395,0.9872807,0.0001964418,0.00001751007,0.011515359,0.00016104647],"about_ca_topic_score_codex":0.0000027130486,"about_ca_topic_score_gemma":0.0000044788226,"teacher_disagreement_score":0.9896442,"about_ca_system_score_codex":0.00005299003,"about_ca_system_score_gemma":0.000001813297,"threshold_uncertainty_score":0.5207743},"labels":[],"label_agreement":null},{"id":"W2169481897","doi":"10.1109/glocom.2008.ecp.819","title":"Cross-Layer Design of Optimal Adaptation Technique over Selection-Combining Diversity Nakagami-m Fading Channels","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Fading; Computer science; Nakagami distribution; Link adaptation; Transmission (telecommunications); Throughput; Channel (broadcasting); Markov process; Computer network; Bit error rate; Network packet; Markov decision process; Algorithm; Wireless; Telecommunications; Mathematics; Statistics","score_opus":0.03253235457403451,"score_gpt":0.2412529126411166,"score_spread":0.2087205580670821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169481897","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":[0.12505071,0.000028089407,0.8735859,0.0000013557194,0.00013797526,0.0002601192,0.0000012099893,0.00045421286,0.0004804785],"genre_scores_gemma":[0.8230425,0.00006594516,0.17662913,0.000006439919,0.000042194664,0.000022808219,0.0000063158845,0.000030053845,0.00015460572],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992013,0.000023388257,0.00022164341,0.00016697086,0.00016821275,0.0002184952],"domain_scores_gemma":[0.9996215,0.00006923347,0.000061846724,0.00010084481,0.00010222575,0.00004434394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011283499,0.0001477216,0.00016803922,0.0001369729,0.00024647405,0.000011936802,0.00010030066,0.00011580873,0.00011213159],"category_scores_gemma":[0.000018637525,0.00017087981,0.000041580122,0.00039208683,0.000041819658,0.0005209605,0.000060077567,0.00013474564,0.0000048952425],"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":[0.000017549919,0.000012741448,0.0023573744,0.000014580046,0.000021699214,0.0000024261833,0.00063352945,0.98820496,0.0082914345,0.00009598174,0.000097501405,0.0002502149],"study_design_scores_gemma":[0.00027448297,0.00003785128,0.0010973801,0.000021879552,0.000006947039,0.00001279337,0.000028135077,0.9423865,0.055897,0.00004794382,0.00001391419,0.0001751863],"about_ca_topic_score_codex":0.000023114166,"about_ca_topic_score_gemma":0.0000013124701,"teacher_disagreement_score":0.6979918,"about_ca_system_score_codex":0.00011589601,"about_ca_system_score_gemma":0.00001469852,"threshold_uncertainty_score":0.69682765},"labels":[],"label_agreement":null},{"id":"W2169949302","doi":"10.1109/icc.2011.5962512","title":"A Game Theory Approach for Inter-Cell Interference Management in OFDM Networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":24,"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); Scheme (mathematics); Game theory; Orthogonal frequency-division multiplexing; Channel (broadcasting); Power (physics); Transmitter power output; Wireless; Wireless network; Reuse; Radio resource management; Cooperative game theory; Cellular network; Adaptation (eye); Computer network; Transmitter; Telecommunications; Mathematics; Engineering","score_opus":0.01577314231930658,"score_gpt":0.19692037543226518,"score_spread":0.1811472331129586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169949302","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":[0.00051775534,0.00010289214,0.87792856,7.277595e-7,0.00011471791,0.00037777735,6.9621933e-7,0.00019694999,0.12075995],"genre_scores_gemma":[0.8165841,0.000110374625,0.1823536,0.00002760795,0.000025902515,0.0001770881,0.00001821627,0.000033853532,0.0006692398],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993437,0.000016097389,0.00019142764,0.00017262863,0.00003435359,0.00024181385],"domain_scores_gemma":[0.9997194,0.000028115808,0.000020680623,0.00018605532,0.000013356518,0.000032413285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001207671,0.00013142197,0.00012195965,0.00008463397,0.000009881674,0.000010188136,0.00016785471,0.000057354366,0.000052407766],"category_scores_gemma":[0.0000017833709,0.00012717638,0.000031284468,0.00014708149,0.000017662518,0.00011572915,0.000050782954,0.000100572,0.0000046727255],"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":[0.000042484215,0.000047744277,0.00008015312,0.00007570543,0.000017644441,0.0000012473253,0.0003315461,0.955616,0.0000051622937,0.009733212,0.00017652058,0.033872556],"study_design_scores_gemma":[0.00037098792,0.000023547547,0.000059768918,0.000028312284,0.00000766097,5.314272e-7,0.00022577644,0.99681526,0.00023528551,0.0019533054,0.00012383306,0.00015574275],"about_ca_topic_score_codex":0.0000014560786,"about_ca_topic_score_gemma":0.000004941395,"teacher_disagreement_score":0.8160664,"about_ca_system_score_codex":0.000048760852,"about_ca_system_score_gemma":0.0000012738803,"threshold_uncertainty_score":0.5186102},"labels":[],"label_agreement":null},{"id":"W2170338846","doi":"10.1109/twc.2013.022013.120266","title":"Proportional Fair Scheduling in Hierarchical Modulation Aided Wireless Networks","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":41,"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":"Computer science; Maximum throughput scheduling; Scheduling (production processes); Proportionally fair; Wireless network; Wireless; Greedy algorithm; Diversity gain; Computer network; Fair-share scheduling; Round-robin scheduling; Distributed computing; Mathematical optimization; Algorithm; Channel (broadcasting); MIMO; Mathematics; Quality of service; Telecommunications","score_opus":0.015894615196920415,"score_gpt":0.24058494210716544,"score_spread":0.22469032691024501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170338846","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":[0.13396336,0.0001045617,0.86319476,0.00043906207,0.00036811674,0.0007822603,0.000011827327,0.0006604421,0.00047561293],"genre_scores_gemma":[0.9751563,0.0012696689,0.02226051,0.00006868129,0.00006969813,0.0008753331,0.00012450345,0.00010649737,0.00006877948],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793017,0.00016294772,0.0007913167,0.00034063114,0.0002923384,0.0004825853],"domain_scores_gemma":[0.9979786,0.00033261924,0.000101424936,0.0012719559,0.00015711041,0.00015824682],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016878262,0.00033487528,0.00033675198,0.00040302594,0.00042934873,0.000087847635,0.00064985955,0.00026924035,0.00010743745],"category_scores_gemma":[0.0000054784614,0.00038930928,0.00011601611,0.0010363553,0.00020600768,0.00076009345,0.00000939963,0.0011207093,0.00008710205],"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":[0.000014096364,0.00018783634,0.00013298194,0.000016226628,0.00003311094,7.2064074e-7,0.00013371409,0.9268727,0.0009390923,0.0009444378,0.00003121816,0.070693925],"study_design_scores_gemma":[0.0005711942,0.000023692006,0.0016628103,0.000134558,0.000014030828,0.0000058796622,0.000066594424,0.9959163,0.00063678174,0.0005132707,0.00007441376,0.00038047915],"about_ca_topic_score_codex":0.00005838628,"about_ca_topic_score_gemma":0.00025473448,"teacher_disagreement_score":0.84119296,"about_ca_system_score_codex":0.00035653633,"about_ca_system_score_gemma":0.0000480157,"threshold_uncertainty_score":0.9998559},"labels":[],"label_agreement":null},{"id":"W2170514014","doi":"10.1109/wowmom.2009.5282466","title":"Joint routing and scheduling in WiMAX-based mesh networks: A column generation approach","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Concordia University","funders":"","keywords":"Column generation; WiMAX; Computer science; Telecommunications link; Scheduling (production processes); Wireless mesh network; Schedule; Computer network; Reuse; Mesh networking; Mathematical optimization; Wireless network; Distributed computing; Wireless; Engineering; Mathematics; Telecommunications","score_opus":0.014510104325817815,"score_gpt":0.2023194012345961,"score_spread":0.1878092969087783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170514014","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":[0.08041506,0.00023471682,0.91748923,0.00003348782,0.00005528781,0.00018866525,2.0862865e-7,0.00026153497,0.0013218155],"genre_scores_gemma":[0.7865611,0.000052772855,0.21309565,0.00010095912,0.00012327028,0.000011232614,0.000027197979,0.000017613846,0.000010252838],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992721,0.000019184045,0.00023064938,0.00017742034,0.00007607295,0.00022458869],"domain_scores_gemma":[0.99978894,0.000015294472,0.000027273554,0.000105040184,0.000019737725,0.000043712967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014351872,0.00012367572,0.00014657035,0.00007450414,0.00004941014,0.000051048813,0.000034950936,0.00008074123,0.000005250195],"category_scores_gemma":[0.000014472779,0.00013853755,0.000016829583,0.0002707095,0.000010307962,0.0001855438,0.00000700034,0.0001371698,6.838485e-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":[0.0000025019153,0.000011893682,0.00030377752,0.0000066876023,0.0000024613357,9.537296e-7,0.000040781477,0.98974526,0.00086709834,0.00079124136,0.000035108376,0.008192246],"study_design_scores_gemma":[0.00038430575,0.000014527452,0.00074124045,0.000026528196,0.0000035139806,0.00000155813,0.000028184526,0.9981398,0.00046027976,0.00003593385,0.000006531628,0.0001575851],"about_ca_topic_score_codex":0.0000040269592,"about_ca_topic_score_gemma":0.000017123508,"teacher_disagreement_score":0.706146,"about_ca_system_score_codex":0.00007564146,"about_ca_system_score_gemma":0.000007420906,"threshold_uncertainty_score":0.56493974},"labels":[],"label_agreement":null},{"id":"W2170577117","doi":"10.1109/cwit.2007.375727","title":"Throughput and Fairness maximization in Wireless Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Throughput; Constraint (computer-aided design); MIMO; Scheduling (production processes); Channel (broadcasting); Computer network; Maximum throughput scheduling; Wireless; Maximization; Wireless network; Algorithm; Mathematical optimization; Mathematics; Telecommunications; Dynamic priority scheduling","score_opus":0.003419626642000781,"score_gpt":0.1911571847450728,"score_spread":0.18773755810307202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170577117","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":[0.07704512,0.0002049464,0.91742027,0.000010698123,0.00016401728,0.00011414889,2.1050663e-7,0.0002701157,0.0047704517],"genre_scores_gemma":[0.98836917,0.0004875259,0.010929274,0.00003340919,0.000076857876,0.0000050841704,0.000014178375,0.000032418928,0.000052110132],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993728,0.000006908445,0.00018963717,0.00012968639,0.00006480131,0.0002361681],"domain_scores_gemma":[0.9997794,0.00004687972,0.000016454766,0.00009774581,0.000018172277,0.000041354026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001239633,0.00010690455,0.00011119791,0.00007575573,0.000024350498,0.000016692084,0.000045503235,0.00009348201,0.000017012777],"category_scores_gemma":[0.000004109275,0.00011343044,0.000009361706,0.00034360273,0.00002101251,0.00022562401,0.000017954839,0.00010384535,0.000002176953],"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":[0.000005349576,0.0000052459363,0.00509697,0.000010101709,0.0000028117997,0.000004087791,0.00005095175,0.9572206,0.00005072101,0.0028248208,0.00004888138,0.03467942],"study_design_scores_gemma":[0.0002605378,0.0000049863265,0.008264161,0.000019002524,0.000001923563,0.0000034906345,0.00005127389,0.99053496,0.00037899776,0.00023136292,0.000107078115,0.00014222195],"about_ca_topic_score_codex":0.0000068349,"about_ca_topic_score_gemma":0.00018275878,"teacher_disagreement_score":0.911324,"about_ca_system_score_codex":0.000052380852,"about_ca_system_score_gemma":0.0000021827618,"threshold_uncertainty_score":0.4625559},"labels":[],"label_agreement":null},{"id":"W2170717320","doi":"10.1109/tnet.2009.2017742","title":"On Stability Region and Delay Performance of Linear-Memory Randomized Scheduling for Time-Varying Networks","year":2009,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Toronto","funders":"","keywords":"Scheduling (production processes); Computer science; Ergodic theory; Mathematical optimization; Schedule; Mathematics","score_opus":0.014120889917670278,"score_gpt":0.22524018239270077,"score_spread":0.2111192924750305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170717320","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":[0.15237786,0.0004696361,0.8451712,0.000036438032,0.00064590503,0.0008204522,0.0000027214705,0.00031276667,0.00016298483],"genre_scores_gemma":[0.9644693,0.0013821257,0.0335277,0.0000746897,0.0003627925,0.00008107078,0.000013452046,0.00006686446,0.000021962185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983367,0.00008591361,0.00059904566,0.00036422422,0.00017555364,0.00043856277],"domain_scores_gemma":[0.99812454,0.0011044256,0.00014739156,0.00044371656,0.00008633785,0.000093572155],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004917382,0.00032468874,0.0006134233,0.00015382687,0.00031329674,0.000026266043,0.00016262881,0.00020727822,0.000008702507],"category_scores_gemma":[0.000028102531,0.00033868194,0.00017843161,0.00038292367,0.00008547086,0.00024175327,0.0000026531106,0.00042959655,0.0000014508574],"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":[0.0047985446,0.000040387462,0.0000069753205,0.000052894302,0.000051002036,8.9787005e-7,0.000105856365,0.90378743,0.0001762356,0.0000135385935,0.000009680577,0.09095657],"study_design_scores_gemma":[0.011247149,0.00017215405,0.000007646168,0.00045217513,0.00007988335,0.000006989379,0.000008788218,0.9851827,0.002263865,0.0002587215,0.000020639178,0.00029930408],"about_ca_topic_score_codex":0.0000012396448,"about_ca_topic_score_gemma":0.0000016428792,"teacher_disagreement_score":0.81209147,"about_ca_system_score_codex":0.00010549949,"about_ca_system_score_gemma":0.00001447298,"threshold_uncertainty_score":0.99990654},"labels":[],"label_agreement":null},{"id":"W2170744182","doi":"10.1109/icc.2007.345","title":"Optimal Pricing for Selfish Users and Prefetching in Heterogeneous Wireless Networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Nash equilibrium; Wireless network; Wireless; Computer network; Scheme (mathematics); Heterogeneous network; Heterogeneous wireless network; Control (management); Resource (disambiguation); Distributed computing; Mathematical optimization; Telecommunications","score_opus":0.005967895751218308,"score_gpt":0.21419314566679243,"score_spread":0.20822524991557412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170744182","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":[0.43442553,0.0001349672,0.5647987,0.0000034033535,0.00009044529,0.0001935412,4.023902e-7,0.00017272923,0.00018026984],"genre_scores_gemma":[0.9269849,0.0001360316,0.07264533,0.00003456414,0.00009869752,0.000017296652,0.000008846223,0.00005451776,0.0000198249],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999109,0.0000066036273,0.00024689265,0.00018309896,0.00006254774,0.00039184547],"domain_scores_gemma":[0.9996465,0.00013991227,0.000026176866,0.000101794925,0.000018756526,0.000066859924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019748975,0.00014535939,0.00015819406,0.00009040153,0.000047864163,0.000028531918,0.000062774874,0.00009928388,0.0000030435388],"category_scores_gemma":[0.0000070548076,0.00015923269,0.00002304975,0.00017604929,0.000013660432,0.00017999,0.000023531067,0.00012351356,3.2045205e-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":[0.00001930732,0.00000571231,0.001405547,0.000026184816,0.000010475771,0.0000041512244,0.00023283971,0.98233193,0.00015273767,0.00006912825,0.00002133017,0.015720641],"study_design_scores_gemma":[0.00040195402,0.000018404904,0.0005097103,0.00003576209,0.000005082407,0.000008762241,0.00008204109,0.99761456,0.0010132504,0.00001852929,0.00010556523,0.00018635612],"about_ca_topic_score_codex":0.000004427988,"about_ca_topic_score_gemma":0.00013005885,"teacher_disagreement_score":0.49255937,"about_ca_system_score_codex":0.00008241503,"about_ca_system_score_gemma":0.0000031813763,"threshold_uncertainty_score":0.64933205},"labels":[],"label_agreement":null},{"id":"W2171023011","doi":"10.1109/twc.2005.858026","title":"ORCA-MRT: an optimization-based approach for fair scheduling in multirate TDMA wireless networks","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Time division multiple access; Computer science; Scheduling (production processes); Proportionally fair; Wireless; Channel allocation schemes; Computer network; Wireless network; Round-robin scheduling; Dynamic priority scheduling; Mathematical optimization; Quality of service; Telecommunications; Mathematics","score_opus":0.022828837269036593,"score_gpt":0.25818480623149,"score_spread":0.2353559689624534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171023011","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":[0.0043154918,0.00023031764,0.9925229,0.00020427769,0.00022042125,0.0011583545,0.00006913465,0.00096628646,0.00031280317],"genre_scores_gemma":[0.633244,0.00056801084,0.36453968,0.00009219957,0.00006795628,0.0010307464,0.0002949438,0.00013779684,0.000024669203],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977538,0.00017555316,0.000777181,0.00048415735,0.00021371867,0.0005956061],"domain_scores_gemma":[0.99716836,0.0004534962,0.00013543731,0.0018479932,0.00020377348,0.00019093954],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028706092,0.00045314574,0.00043694576,0.00046186917,0.00062075834,0.00010609838,0.0009902458,0.0003388187,0.000024251764],"category_scores_gemma":[0.0000060475118,0.0005565074,0.00015569909,0.0011204937,0.0001689904,0.00078185793,0.0000061148394,0.0007801179,0.0000069551775],"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":[0.00004432966,0.000669523,0.000019659698,0.000037621292,0.00003876982,2.6608726e-7,0.00021830393,0.96253765,0.00019219898,0.00022925559,0.000011352713,0.0360011],"study_design_scores_gemma":[0.0015006968,0.000049567767,0.000011631066,0.00009669766,0.000043185893,0.000001928315,0.00015552643,0.99598897,0.0014145464,0.000009691099,0.00014826514,0.0005792839],"about_ca_topic_score_codex":0.000022203196,"about_ca_topic_score_gemma":0.00049476494,"teacher_disagreement_score":0.62892854,"about_ca_system_score_codex":0.00041205875,"about_ca_system_score_gemma":0.000072660696,"threshold_uncertainty_score":0.9996886},"labels":[],"label_agreement":null},{"id":"W2171031786","doi":"10.1109/icc.2008.272","title":"A Quadrature Markov Chain Model of the Rayleigh Fading Channel","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Fading; Rayleigh fading; Fading distribution; Markov chain; Channel state information; Markov model; Markov process; Computer science; Rayleigh scattering; Statistical physics; Mathematics; Channel (broadcasting); Electronic engineering; Statistics; Telecommunications; Physics; Engineering; Wireless; Optics","score_opus":0.010589164380891171,"score_gpt":0.17860020439452717,"score_spread":0.168011040013636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171031786","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":[0.050586823,0.00020702003,0.93783283,0.000060033082,0.00018243935,0.00015469047,0.0000042147094,0.00022096763,0.010750977],"genre_scores_gemma":[0.98554814,0.00016554934,0.013077111,0.00004132903,0.000048451173,0.00000931693,0.000002864634,0.000028584343,0.0010786552],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995294,0.000008530723,0.00012903725,0.00008392641,0.00010220265,0.00014689752],"domain_scores_gemma":[0.9997181,0.000017579325,0.000025456999,0.0001894687,0.000025095856,0.00002425203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000032209788,0.0000957098,0.000107191474,0.000031588275,0.000058472633,0.00000268326,0.00011954486,0.0000683294,0.000011576628],"category_scores_gemma":[0.0000085406,0.00007064341,0.00004402153,0.00022042994,0.000026540987,0.00008998901,0.00002547849,0.0001153221,0.0000018120965],"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":[0.0000023703208,0.000004194207,0.000043870285,0.000012488123,0.000006926315,3.945972e-7,0.0003084021,0.99629945,0.0015739304,0.0006665864,0.0009123534,0.0001690323],"study_design_scores_gemma":[0.00011785708,0.000002577421,0.000061774765,0.000018231794,0.000002752706,0.000003656977,0.000021468979,0.9947858,0.004615316,0.0002503854,0.000035087207,0.00008509822],"about_ca_topic_score_codex":0.0000016440722,"about_ca_topic_score_gemma":0.0000055631904,"teacher_disagreement_score":0.9349613,"about_ca_system_score_codex":0.000027715816,"about_ca_system_score_gemma":0.000008122538,"threshold_uncertainty_score":0.28807545},"labels":[],"label_agreement":null},{"id":"W2171300387","doi":"10.1109/ccece.2004.1345336","title":"Performance analysis of multiuser diversity in MIMO channels","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queen's University","funders":"","keywords":"Fading; Computer science; Time division multiple access; MIMO; Computer network; Multiuser detection; Throughput; Diversity scheme; Channel (broadcasting); Wireless; Randomness; Network packet; Telecommunications; Code division multiple access; Mathematics; Statistics","score_opus":0.01095165162383426,"score_gpt":0.2007844978529977,"score_spread":0.18983284622916344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171300387","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":[0.85632795,0.000019340107,0.14261533,0.0000042522447,0.00004375282,0.00003903452,0.000001027505,0.00006118118,0.0008881155],"genre_scores_gemma":[0.9934861,0.000110755434,0.00634766,0.0000062844288,0.000007022278,0.0000015296096,0.000007047819,0.0000055308096,0.000028034305],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967945,0.0000024262206,0.0000986797,0.0000641151,0.00006082056,0.00009450922],"domain_scores_gemma":[0.9998589,0.000007741571,0.0000131848565,0.000087223474,0.000016231039,0.00001670894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000292672,0.0000518095,0.00011912049,0.00019369306,0.000017564917,0.0000016622689,0.000058565132,0.00003004517,0.000033716948],"category_scores_gemma":[0.0000024206915,0.000054092856,0.000028871602,0.00082076073,0.000009563293,0.00013350007,0.000035470737,0.000038086207,0.0000034028199],"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":[0.000002219576,0.000009139697,0.042599045,0.000008303869,0.000049184957,4.409318e-7,0.00025599383,0.95643073,0.00007764912,0.000038771974,0.0000026748667,0.000525823],"study_design_scores_gemma":[0.00021840366,0.0000046868972,0.053767692,0.000007940898,0.000032617096,4.980484e-8,0.000021296293,0.94384545,0.0020246194,0.000010568209,0.0000051944457,0.0000614873],"about_ca_topic_score_codex":0.000041715324,"about_ca_topic_score_gemma":0.0001335504,"teacher_disagreement_score":0.13715817,"about_ca_system_score_codex":0.000054267126,"about_ca_system_score_gemma":0.0000018208037,"threshold_uncertainty_score":0.22058426},"labels":[],"label_agreement":null},{"id":"W2171423886","doi":"10.1109/twc.2006.1638671","title":"Opportunistic power scheduling for dynamic multi-server wireless systems","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":116,"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":"Computer science; Scheduling (production processes); Wireless; Subgradient method; Telecommunications link; Mathematical optimization; Stochastic optimization; Computer network; Stochastic process; Distributed computing; Telecommunications; Mathematics","score_opus":0.02532042892908349,"score_gpt":0.2639069141633982,"score_spread":0.2385864852343147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171423886","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":[0.019086042,0.00055341335,0.9767667,0.000114199174,0.00087360054,0.0009774084,0.00026690084,0.0010933868,0.00026832242],"genre_scores_gemma":[0.9605117,0.0008686332,0.03667676,0.000025030273,0.00003344629,0.0010092711,0.00024435748,0.00018432378,0.00044650704],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819744,0.00008679473,0.0006805841,0.00033841128,0.00021625274,0.00048052665],"domain_scores_gemma":[0.9973501,0.00040296259,0.00013087003,0.0017692134,0.00022319879,0.0001236397],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001692936,0.0003814863,0.0003836284,0.00026891282,0.0006928383,0.00010982705,0.00078049314,0.00023283195,0.00001676923],"category_scores_gemma":[0.0000036254398,0.0004546072,0.00018223017,0.0005141299,0.00016186007,0.000348418,0.000006025735,0.00048019653,0.000037665315],"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":[0.000013804718,0.0002699716,0.000011386005,0.000076444034,0.00007013204,9.362929e-7,0.000060469585,0.9897996,0.0033398578,0.0026517573,0.000062759565,0.0036428769],"study_design_scores_gemma":[0.00081163476,0.000032927837,0.000050868082,0.0001630482,0.0000735366,0.000008183176,0.00015635604,0.9965296,0.00084453577,0.00007128474,0.0007828042,0.00047525248],"about_ca_topic_score_codex":0.000054429696,"about_ca_topic_score_gemma":0.00038802202,"teacher_disagreement_score":0.9414256,"about_ca_system_score_codex":0.00033935125,"about_ca_system_score_gemma":0.000052036117,"threshold_uncertainty_score":0.99979055},"labels":[],"label_agreement":null},{"id":"W2174647461","doi":"10.1145/1185373.1185400","title":"An optimization framework for balancing throughput and fairness in wireless networks with QoS support","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Throughput; Fairness measure; Maximum throughput scheduling; Computer science; Max-min fairness; Quality of service; Resource allocation; Pareto principle; Wireless network; Pareto optimal; Mathematical optimization; Multi-objective optimization; Resource management (computing); Computer network; Distributed computing; Wireless; Mathematics; Dynamic priority scheduling; Telecommunications","score_opus":0.0033255532636505504,"score_gpt":0.2070820360604196,"score_spread":0.20375648279676906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2174647461","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":[0.019818883,0.000060057722,0.978666,0.000017719445,0.00015170273,0.0004243015,0.0000026927903,0.00037974812,0.00047890187],"genre_scores_gemma":[0.65640074,0.00005928065,0.34305084,0.0000270431,0.00020793226,0.00006607565,0.00011274292,0.000059948296,0.000015426867],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999061,0.000013289344,0.00024329325,0.00025928312,0.0000917375,0.0003314046],"domain_scores_gemma":[0.9995938,0.0000859336,0.000042172374,0.00018152356,0.00004751443,0.000049051567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000086941945,0.00019471515,0.0002131336,0.00007095006,0.000060463524,0.00005781635,0.00007548985,0.00015900821,0.000017863511],"category_scores_gemma":[0.0000040248988,0.00018711072,0.0000145942195,0.00031697255,0.000029880575,0.00048426143,0.000010379869,0.0001367597,3.4351348e-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":[0.000024057177,0.000018836208,0.0054727653,0.000031934418,0.000005560216,0.000002500302,0.000044618497,0.98526114,0.00001540459,0.0072208387,0.00007188689,0.0018304703],"study_design_scores_gemma":[0.00050467206,0.000055855184,0.0011159569,0.00006461304,0.000007343258,0.000004870655,0.00006197136,0.9971438,0.00015514487,0.00058215024,0.0000351242,0.00026846738],"about_ca_topic_score_codex":0.000019491154,"about_ca_topic_score_gemma":0.00019663642,"teacher_disagreement_score":0.63658184,"about_ca_system_score_codex":0.00006517172,"about_ca_system_score_gemma":0.00001019339,"threshold_uncertainty_score":0.7630154},"labels":[],"label_agreement":null},{"id":"W2176491727","doi":"10.1155/2015/460506","title":"A Gradient-Assisted Energy-Efficient Backpressure Scheduling Algorithm for Wireless Sensor Networks","year":2015,"lang":"en","type":"article","venue":"International Journal of Distributed Sensor Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Network packet; Wireless sensor network; Scheduling (production processes); Energy consumption; Efficient energy use; Computer network; Distributed computing; Throughput; Algorithm; Wireless; Real-time computing; Mathematical optimization; Telecommunications","score_opus":0.013528766630387065,"score_gpt":0.23868939807364897,"score_spread":0.2251606314432619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2176491727","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":[0.009321026,0.0016661452,0.9825404,0.00013222352,0.005683712,0.00020451675,0.00021100721,0.00017854013,0.00006242635],"genre_scores_gemma":[0.9030277,0.00038687183,0.09212424,0.00008712761,0.0034675784,0.000021548874,0.0007269225,0.00011961801,0.000038368657],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99709195,0.00009031843,0.0012092526,0.00028908564,0.00072791654,0.0005914933],"domain_scores_gemma":[0.9964697,0.0002878242,0.0006111107,0.00023235774,0.0019848605,0.00041418697],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00043016468,0.00040654806,0.0005535644,0.00022973781,0.00009491639,0.00016877569,0.00058430166,0.00031064713,0.000012679228],"category_scores_gemma":[0.00010183854,0.00040885265,0.00031430612,0.00043166743,0.00007494659,0.00025214505,0.00007155979,0.0005489822,0.0000019059221],"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":[0.00016882796,0.00010425041,0.00016144726,0.0000069703465,0.0004721032,0.000100214704,0.0000375979,0.94979155,0.000053065753,0.0001579843,0.0027784675,0.046167497],"study_design_scores_gemma":[0.0023365708,0.00008812816,0.00011174475,0.00018533223,0.00010974631,0.00030200594,0.00017330272,0.990985,0.00015376678,0.00005080327,0.005108406,0.00039519314],"about_ca_topic_score_codex":0.0000042631805,"about_ca_topic_score_gemma":0.000004364176,"teacher_disagreement_score":0.8937067,"about_ca_system_score_codex":0.0005347298,"about_ca_system_score_gemma":0.00005573179,"threshold_uncertainty_score":0.9998363},"labels":[],"label_agreement":null},{"id":"W2182378989","doi":"10.1109/pimrc.2015.7343450","title":"Min-max energy-efficiency analysis of multiuser wireless systems","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Mathematical optimization; Fractional programming; Computer science; Iterative method; Energy (signal processing); Power (physics); Efficient energy use; Convex optimization; Wireless; Wireless network; Parametric programming; Nonlinear programming; Parametric statistics; Multiuser detection; Linear programming; Geometric programming; Algorithm; Nonlinear system; Regular polygon; Mathematics; Computer network; Code division multiple access; Telecommunications; Engineering; Electrical engineering","score_opus":0.012484575152042744,"score_gpt":0.2120065672642627,"score_spread":0.19952199211221996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2182378989","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":[0.058932923,0.00047701487,0.93265927,0.0000033920999,0.0002870078,0.0000610377,0.0000056488566,0.00026887888,0.0073048114],"genre_scores_gemma":[0.9960878,0.00005385898,0.003217563,0.0000053569433,0.000038996484,0.000013036685,0.00003147893,0.000026514159,0.0005253935],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991672,0.000019749947,0.00029105798,0.00013962817,0.00020093795,0.00018143641],"domain_scores_gemma":[0.99942327,0.0000435737,0.00005137402,0.00026136523,0.0001282184,0.00009218504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008638466,0.00012289498,0.00029691588,0.00025795764,0.000014797893,0.000012846145,0.00012553943,0.000070575115,0.00001911183],"category_scores_gemma":[0.000011446849,0.00011498121,0.00006506848,0.0013026786,0.00002239224,0.00011948804,0.0000196694,0.000041641768,0.00000566745],"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":[0.0000027617102,0.000021539838,0.00052617176,0.000012311122,0.0001794354,0.0000011215283,0.00011928541,0.9954949,0.00024535137,0.0018580077,0.00040371472,0.0011353996],"study_design_scores_gemma":[0.00016360213,0.000012087566,0.000059010585,0.000009992297,0.00013315484,3.5458592e-7,0.0001402799,0.99781233,0.00089136395,0.00000775363,0.00063551794,0.0001345478],"about_ca_topic_score_codex":0.00009232812,"about_ca_topic_score_gemma":0.00005860645,"teacher_disagreement_score":0.9371549,"about_ca_system_score_codex":0.00006771088,"about_ca_system_score_gemma":0.000010798015,"threshold_uncertainty_score":0.46887976},"labels":[],"label_agreement":null},{"id":"W2183218540","doi":"","title":"A framework for efficient bandwidth management in broadband wireless access systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer network; Computer science; Quality of service; Bandwidth management; WiMAX; Wireless broadband; Bandwidth (computing); Interoperability; Broadband; Wireless network; Bandwidth allocation; Network packet; Telecommunications; Wireless","score_opus":0.013186357708048307,"score_gpt":0.26978833318722484,"score_spread":0.2566019754791765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2183218540","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":[0.026117723,0.0003606236,0.96638536,0.0000297907,0.000381812,0.00083798514,0.0000021537755,0.0003295774,0.0055549634],"genre_scores_gemma":[0.9675139,0.00016486442,0.031847443,0.000055635286,0.00008412589,0.00012831617,0.000010963666,0.000029508108,0.00016519538],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991298,0.000008781346,0.00024368236,0.00019443818,0.000117166244,0.0003061894],"domain_scores_gemma":[0.9996501,0.00005521591,0.000026638734,0.00019863753,0.000021276732,0.000048129503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000080677164,0.00014897855,0.00018170799,0.00012633116,0.00002680318,0.000081223756,0.00017704885,0.00008455174,0.0000071922796],"category_scores_gemma":[0.000004474495,0.00014703689,0.000030598556,0.00036400068,0.0000073973847,0.00011041312,0.000017608054,0.00009081903,0.0000041512008],"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":[0.00001441642,0.00002781087,0.00006542897,0.00007810469,0.000011534155,0.0000031733891,0.000042144355,0.9534849,0.000010840671,0.029518075,0.0003271531,0.01641645],"study_design_scores_gemma":[0.00047676574,0.000018089811,0.0007743171,0.00015562802,0.0000075895027,8.927238e-7,0.00004179571,0.99630004,0.00012983565,0.0013686153,0.000532488,0.00019393877],"about_ca_topic_score_codex":0.000002013989,"about_ca_topic_score_gemma":0.0000024864999,"teacher_disagreement_score":0.94139624,"about_ca_system_score_codex":0.00010865871,"about_ca_system_score_gemma":0.0000026300083,"threshold_uncertainty_score":0.59959906},"labels":[],"label_agreement":null},{"id":"W2184103913","doi":"10.1109/wimob.2015.7348046","title":"On efficient power allocation modeling in virtualized uplink 3GPP-LTE systems","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Computer science; Telecommunications link; 3rd Generation Partnership Project 2; Integer programming; Computer network; Scheduling (production processes); Optimization problem; Distributed computing; Mathematical optimization; Algorithm","score_opus":0.022442439590003912,"score_gpt":0.2288929889125941,"score_spread":0.2064505493225902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184103913","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":[0.1102454,0.00019155057,0.8832594,0.00001690083,0.00049987197,0.00022840599,4.5569647e-7,0.00035465078,0.005203373],"genre_scores_gemma":[0.99608994,0.000017203962,0.0036511263,0.000024415658,0.00003461853,0.000033812557,0.00001665009,0.000039881517,0.00009238374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991947,0.000021691154,0.00026391563,0.00015923548,0.0001685579,0.00019194112],"domain_scores_gemma":[0.9996244,0.00003152333,0.000021813737,0.00018794676,0.00006090202,0.00007343721],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001871886,0.00012671012,0.00013947123,0.00011807226,0.000016045817,0.000024527768,0.00007449478,0.00007742339,0.000008055861],"category_scores_gemma":[0.00003197695,0.00012490593,0.000017631679,0.00024011121,0.000005534429,0.000084436266,0.000013500667,0.00010431818,0.000070261696],"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":[0.000015536247,0.00001738646,0.0000063361153,0.00000793919,0.000004241408,0.000001093688,0.00025865756,0.99449545,0.00009911603,0.004738458,0.000121046716,0.00023471222],"study_design_scores_gemma":[0.0005532195,0.000020020774,0.0000021486085,0.000055026387,0.0000020217788,8.637939e-7,0.00013713732,0.9988354,0.00008779028,0.000108473134,0.000052354237,0.00014556083],"about_ca_topic_score_codex":0.000017116254,"about_ca_topic_score_gemma":0.000004888638,"teacher_disagreement_score":0.8858445,"about_ca_system_score_codex":0.0002314111,"about_ca_system_score_gemma":0.000012246717,"threshold_uncertainty_score":0.5093516},"labels":[],"label_agreement":null},{"id":"W2187284628","doi":"10.1109/iemcon.2015.7344448","title":"JPEG2000 image transmission over OFDM-based Cognitive Radio network","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Cognitive radio; Orthogonal frequency-division multiplexing; Computer science; Computer network; JPEG 2000; Bandwidth (computing); Transmission (telecommunications); Channel (broadcasting); Interference (communication); Quality of service; Multimedia; Electronic engineering; Telecommunications; Wireless; Image (mathematics); Image compression; Engineering; Image processing; Artificial intelligence","score_opus":0.009303791644908238,"score_gpt":0.22219977949510794,"score_spread":0.2128959878501997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2187284628","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":[0.0037610182,0.0006492599,0.9737055,0.000033227574,0.00021664928,0.00020521674,0.0000036799331,0.0007110966,0.020714374],"genre_scores_gemma":[0.90042543,0.0001053331,0.09814008,0.00023441171,0.0003975859,0.000028924498,0.00010332751,0.00010601301,0.00045889406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915653,0.00002678017,0.00017903517,0.0001653437,0.00016848832,0.00030381905],"domain_scores_gemma":[0.9995369,0.00006970743,0.000021431078,0.00012392308,0.0000682095,0.00017988392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009287861,0.00017179747,0.00016163109,0.000042121563,0.000048485083,0.000033146764,0.000071656235,0.00008942393,0.00031787294],"category_scores_gemma":[0.000011548502,0.00016542435,0.00004443134,0.00028641123,0.00003953837,0.00023424343,0.000005338326,0.00013042298,0.00006602238],"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":[0.000040759467,0.000012831255,0.000108852175,0.000011496246,0.000013240558,0.000006821097,0.00006939395,0.97360307,0.00015671822,0.000057544934,0.011523925,0.01439535],"study_design_scores_gemma":[0.0011916187,0.0000314621,0.00018514355,0.0000688766,0.00001843367,0.0000017052002,0.000020779638,0.98456126,0.0024849153,0.00019330932,0.010994272,0.00024822474],"about_ca_topic_score_codex":0.0000044359795,"about_ca_topic_score_gemma":0.0000038243397,"teacher_disagreement_score":0.8966644,"about_ca_system_score_codex":0.0000795751,"about_ca_system_score_gemma":0.00003571237,"threshold_uncertainty_score":0.67458093},"labels":[],"label_agreement":null},{"id":"W2190455466","doi":"10.1186/s13638-015-0486-z","title":"Cross-layer distributed power control: a repeated game formulation to improve the sum energy efficiency","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queue; Nash equilibrium; Efficient energy use; Network packet; Power (physics); Energy (signal processing); Performance metric; Work (physics)","score_opus":0.022108618647966812,"score_gpt":0.26900538585703876,"score_spread":0.24689676720907194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2190455466","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":[0.15847646,0.0036150306,0.8345278,0.000905646,0.00086456165,0.0003244877,0.000017646882,0.00025959732,0.0010087867],"genre_scores_gemma":[0.9968466,0.0017083228,0.0007854203,0.00023528108,0.00026625855,0.000024809438,0.000038145536,0.00005755925,0.00003757439],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985127,0.00017776621,0.00048490122,0.00018013906,0.00025519563,0.00038931074],"domain_scores_gemma":[0.9981177,0.00034047122,0.00019976468,0.0008248063,0.00027679553,0.00024047394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005794386,0.00023440563,0.00024189422,0.000108564316,0.0005642006,0.0003102912,0.00056657044,0.000097889635,0.0000043997507],"category_scores_gemma":[0.000039599974,0.00018423572,0.000065912966,0.00056388864,0.00007552652,0.00027899892,0.00012828858,0.00050495955,0.0000043032546],"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":[0.00007349165,0.00004296056,0.0010616658,0.000002433599,0.000046242494,0.0000031849363,0.00038577282,0.95167124,0.000279347,0.0014585003,0.00030596755,0.04466919],"study_design_scores_gemma":[0.00094683986,0.000121232326,0.0013384081,0.00010709844,0.000021844577,0.000044174823,0.00007215205,0.9674486,0.00008410851,0.0002278738,0.02933574,0.0002519635],"about_ca_topic_score_codex":0.0000059591766,"about_ca_topic_score_gemma":0.00001527718,"teacher_disagreement_score":0.8383702,"about_ca_system_score_codex":0.00018005757,"about_ca_system_score_gemma":0.000028784147,"threshold_uncertainty_score":0.75129145},"labels":[],"label_agreement":null},{"id":"W2203142848","doi":"10.1016/s0166-218x(02)00176-2","title":"Erratum to “Comparison of column generation models for channel assignment in cellular networks”","year":2002,"lang":"en","type":"erratum","venue":"Discrete Applied Mathematics","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Université de Montréal; Group for Research in Decision Analysis; Université du Québec à Montréal","funders":"","keywords":"Mathematics; Channel (broadcasting); Integer programming; Algorithm; Combinatorics; Computer science; Telecommunications","score_opus":0.030497037066046565,"score_gpt":0.24677255715757537,"score_spread":0.2162755200915288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2203142848","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":[0.000030723575,0.0010100335,0.98183924,0.000014862272,0.003048659,0.0022664135,0.00006285019,0.00015768356,0.01156953],"genre_scores_gemma":[0.37964547,0.0021077017,0.5817222,0.00010048911,0.0048939814,0.006711025,0.008159737,0.001566058,0.015093339],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975246,0.000011485304,0.0011241474,0.00041738024,0.00038254386,0.0005398444],"domain_scores_gemma":[0.99883133,0.00006907357,0.0003440832,0.00057055283,0.000071765826,0.00011320751],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017745346,0.00054286636,0.0010812304,0.00023810707,0.00005975087,0.00004804521,0.00032088594,0.0006407548,0.000012894208],"category_scores_gemma":[0.000013141129,0.00062378694,0.00012220797,0.00040134208,0.000026237218,0.00009443388,0.00007146925,0.00048973435,0.000005587977],"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":[0.0000051390857,0.00006335911,8.734301e-8,0.0006610067,0.000041609546,4.2470268e-7,0.0008761046,0.7477736,0.00036260168,0.0017494417,0.24810642,0.0003602271],"study_design_scores_gemma":[0.00033053898,0.000043314536,1.1965416e-7,0.00034906983,0.000075610405,2.2500586e-7,0.0001882961,0.9919813,0.0009130849,0.0035191681,0.002026259,0.0005729653],"about_ca_topic_score_codex":0.000001358845,"about_ca_topic_score_gemma":0.000026064272,"teacher_disagreement_score":0.40011704,"about_ca_system_score_codex":0.00027084633,"about_ca_system_score_gemma":0.000021124513,"threshold_uncertainty_score":0.99962133},"labels":[],"label_agreement":null},{"id":"W2204753431","doi":"10.1109/tmm.2015.2502067","title":"Energy-Aware and Bandwidth-Efficient Hybrid Video Streaming Over Mobile Networks","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multicast; Computer science; Unicast; Computer network; Xcast; Cellular network; Source-specific multicast; Distributed computing; Energy consumption","score_opus":0.007619853450722221,"score_gpt":0.20928318060148848,"score_spread":0.20166332715076626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2204753431","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":[0.024783213,0.00043985838,0.97255534,0.0000055300998,0.0014124668,0.00018622172,0.000024358354,0.00045558542,0.0001374102],"genre_scores_gemma":[0.9950064,0.00035435642,0.0041264053,0.000030248475,0.00014833156,0.00012219301,0.000022303017,0.00007479479,0.000114994225],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989637,0.000026544729,0.00022875068,0.00026562522,0.00019709107,0.00031830155],"domain_scores_gemma":[0.99931633,0.00012846862,0.00003241942,0.00023023451,0.00005296526,0.00023956274],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006757477,0.00023920955,0.00019827491,0.00012759953,0.00009870997,0.000033492528,0.0000805681,0.00010226695,0.000047287343],"category_scores_gemma":[0.0000018384025,0.0002549655,0.000050911956,0.00021403671,0.000056532703,0.0001524227,0.0000015124406,0.0002332304,0.000011648782],"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":[0.000018131763,0.00004250731,0.000009317729,0.0000066828657,0.000023818988,0.000005906911,0.0001295017,0.8697673,0.00007829901,0.0000010308592,0.00034828417,0.12956922],"study_design_scores_gemma":[0.00078085845,0.000048273276,0.000019405545,0.000040329687,0.000027677572,0.000008380539,0.00006821951,0.9946468,0.0033268323,0.000007026357,0.0007659118,0.00026027637],"about_ca_topic_score_codex":0.000020361666,"about_ca_topic_score_gemma":0.000028895585,"teacher_disagreement_score":0.9702232,"about_ca_system_score_codex":0.00013770182,"about_ca_system_score_gemma":0.00001537653,"threshold_uncertainty_score":0.9999903},"labels":[],"label_agreement":null},{"id":"W2206263511","doi":"10.1109/jsac.2015.2452586","title":"Resource Allocation for Heterogeneous Applications With Device-to-Device Communication Underlaying Cellular Networks","year":2015,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":64,"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":"Computer science; Cellular network; Quality of service; Resource allocation; Cellular traffic; Computer network; Distributed computing; Shared resource; Wireless; Wireless network; Resource management (computing); Heterogeneous network; Resource (disambiguation); Telecommunications","score_opus":0.035679893368485524,"score_gpt":0.27420961577958985,"score_spread":0.23852972241110432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2206263511","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":[0.012124036,0.002011033,0.9816463,0.0010911261,0.0000827419,0.0014133484,0.000008859765,0.0003704257,0.001252157],"genre_scores_gemma":[0.92034286,0.0007945024,0.07715379,0.0002980238,0.0001524094,0.0008296889,0.000278096,0.00012115145,0.000029475927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981354,0.00028304823,0.00065274653,0.00023452139,0.0002757028,0.0004185734],"domain_scores_gemma":[0.9964085,0.00064282044,0.00024265762,0.0016180123,0.0007938704,0.00029414357],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00053622446,0.00028227022,0.00029013766,0.00037564684,0.0005115085,0.00014376995,0.0011978096,0.00015965797,0.0000025779573],"category_scores_gemma":[0.00008598556,0.00029909157,0.000050299834,0.0017300487,0.00006737027,0.00028647934,0.00006645489,0.00079938024,0.0000126831665],"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":[0.000063691616,0.00011158517,0.00018298585,0.000010830799,0.000051888113,7.5729645e-7,0.0003310076,0.99197346,0.00029597545,0.0005527704,0.000762015,0.005663062],"study_design_scores_gemma":[0.0011534416,0.00016987593,0.00014330429,0.0003144413,0.000060914408,0.00006730865,0.00029106525,0.9578435,0.00080966344,0.00054136827,0.038128395,0.00047674493],"about_ca_topic_score_codex":0.0000072310527,"about_ca_topic_score_gemma":0.00032870885,"teacher_disagreement_score":0.90821886,"about_ca_system_score_codex":0.00075339526,"about_ca_system_score_gemma":0.00012203817,"threshold_uncertainty_score":0.9999461},"labels":[],"label_agreement":null},{"id":"W2206917860","doi":"10.5296/npa.v7i3.8229","title":"Channel Aware Scheduling Algorithm for LTE Uplink and Downlink","year":2015,"lang":"en","type":"article","venue":"Network Protocols and Algorithms","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Ottawa","funders":"","keywords":"Computer science; Telecommunications link; Algorithm; Scheduling (production processes); Computer network; Distributed computing; Mathematical optimization","score_opus":0.030797407837557862,"score_gpt":0.27922352326225897,"score_spread":0.2484261154247011,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2206917860","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":[0.00006361712,0.0009145078,0.9738848,0.000053095257,0.0002598415,0.024323849,0.000016990623,0.00038102598,0.00010228077],"genre_scores_gemma":[0.0021379036,0.00035029693,0.9076909,0.00012413331,0.0035607505,0.08567241,0.00010567668,0.00017606889,0.00018187788],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998638,0.000021163944,0.00031914806,0.00035711832,0.00014172222,0.0005228661],"domain_scores_gemma":[0.99926347,0.00007391698,0.00007177781,0.00018849752,0.00012958265,0.00027275813],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003409461,0.00029373483,0.00035032773,0.000060979764,0.00017416259,0.00011178857,0.00010231195,0.0001869273,0.000002801739],"category_scores_gemma":[0.000014826276,0.00028926425,0.000041387793,0.00028156626,0.000057594447,0.00026311947,0.00006984841,0.00021262551,0.0000026321077],"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":[0.000012226138,0.000009514028,0.000028760136,0.00007158066,0.000021487445,0.0000022311278,0.000065172746,0.66681826,0.0000019693891,0.00006476135,0.0006026426,0.33230138],"study_design_scores_gemma":[0.0015169284,0.00014707421,0.000018436032,0.00020725759,0.000013977702,0.000012551766,0.0000376809,0.98011094,0.000049174738,0.002645391,0.014884259,0.0003563476],"about_ca_topic_score_codex":0.000001688057,"about_ca_topic_score_gemma":0.0000013538263,"teacher_disagreement_score":0.33194503,"about_ca_system_score_codex":0.000043450873,"about_ca_system_score_gemma":0.000023768018,"threshold_uncertainty_score":0.99995595},"labels":[],"label_agreement":null},{"id":"W2217100688","doi":"10.1109/cjece.2015.2417858","title":"Queue-Aware Channel-Adapted Scheduling and Congestion Control for Best-Effort Services in LTE Networks","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":13,"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; Queue; Network congestion; Scheduling (production processes); Maximum throughput scheduling; Fairness measure; Computer network; Round-robin scheduling; Flow control (data); Fair-share scheduling; Channel (broadcasting); Real-time computing; Dynamic priority scheduling; Distributed computing; Throughput; Quality of service; Mathematical optimization; Network packet; Mathematics; Wireless; Telecommunications","score_opus":0.006960485841400145,"score_gpt":0.17909035041950827,"score_spread":0.17212986457810814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2217100688","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":[0.08461124,0.004595701,0.9103209,0.000040246312,0.0002815499,0.00012318631,0.0000016087059,0.00002261453,0.00000295818],"genre_scores_gemma":[0.9935006,0.0001322897,0.005936187,0.00003813342,0.00035742242,0.0000059172316,0.000003658359,0.000024600624,0.0000012204594],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993162,0.000006885312,0.00024129334,0.000090124646,0.00005455102,0.0002909046],"domain_scores_gemma":[0.9993417,0.00006707884,0.000040421073,0.00003926572,0.00009744373,0.00041409032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000120952674,0.00012968873,0.00022883549,0.00023464432,0.000027668271,0.000049294064,0.00006466871,0.00008850106,3.176199e-7],"category_scores_gemma":[0.000011743558,0.0001363301,0.000022390195,0.000202281,0.000008352007,0.00018519242,0.0000045368743,0.00021505299,8.7666855e-8],"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":[0.000010532916,0.000002081277,0.0007038421,0.00002788033,0.000020896225,0.000017994298,0.000058777245,0.9925764,0.0000057905504,0.00012721184,0.000013061252,0.006435497],"study_design_scores_gemma":[0.0008555517,0.00012336638,0.00091774814,0.000145615,0.000015205631,0.00007454459,0.0000079179445,0.9974008,0.000008211808,0.000059139315,0.00025338703,0.00013850923],"about_ca_topic_score_codex":0.000058459264,"about_ca_topic_score_gemma":0.00056085177,"teacher_disagreement_score":0.90888935,"about_ca_system_score_codex":0.00010515287,"about_ca_system_score_gemma":0.000047720518,"threshold_uncertainty_score":0.555938},"labels":[],"label_agreement":null},{"id":"W2276680976","doi":"10.1109/vtcfall.2015.7391070","title":"Performance Analysis of Low-Complexity Uniform Power Loading with Reduced-Overhead OFDM Systems over Rayleigh Fading Channels","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Orthogonal frequency-division multiplexing; Rayleigh fading; Fading; Transmitter; Overhead (engineering); Channel (broadcasting); Computer science; Channel capacity; Multiplexing; Power (physics); Electronic engineering; Control theory (sociology); Telecommunications; Engineering","score_opus":0.02136778226642598,"score_gpt":0.2268370264125552,"score_spread":0.20546924414612922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2276680976","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":[0.7788969,0.000109117405,0.20835459,0.0000038314847,0.0003283863,0.00019754101,0.000008471069,0.00027142942,0.011829687],"genre_scores_gemma":[0.99538636,0.000038746864,0.004152497,0.000007466856,0.00006223877,0.000014047711,0.000041221214,0.00005072494,0.00024667993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986415,0.000017787734,0.00039505438,0.00023580591,0.00034461173,0.00036524443],"domain_scores_gemma":[0.9991696,0.000037070844,0.00012495997,0.00035652003,0.0001681718,0.00014369127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019700505,0.00024272509,0.0004950928,0.00038558542,0.000051473424,0.000036159534,0.00016321635,0.00009116507,0.00006380263],"category_scores_gemma":[0.000011181313,0.00021100447,0.00006739855,0.0015936729,0.000055211225,0.0005911311,0.00003383745,0.00013230724,0.000008013917],"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":[0.000031129635,0.00001431881,0.0043577566,0.00009178667,0.00031662596,0.0000015005957,0.00039967804,0.9934975,0.00041679505,0.0006703151,0.00012404335,0.00007858226],"study_design_scores_gemma":[0.0004129645,0.000053151944,0.0018044566,0.00013819401,0.00014555198,0.0000032741086,0.00023909229,0.9944924,0.0023601507,0.000009291353,0.000055244604,0.00028623996],"about_ca_topic_score_codex":0.00004079875,"about_ca_topic_score_gemma":0.000018153774,"teacher_disagreement_score":0.21648943,"about_ca_system_score_codex":0.0002632723,"about_ca_system_score_gemma":0.00002319792,"threshold_uncertainty_score":0.8604513},"labels":[],"label_agreement":null},{"id":"W2277783967","doi":"10.1109/globalsip.2015.7418274","title":"Memory-less gain quantization in the EVS codec","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 de Sherbrooke","funders":"","keywords":"Codebook; Codec; Computer science; Adaptive Multi-Rate audio codec; Encoder; Intra-frame; Quantization (signal processing); Coding gain; Vector quantization; Coding (social sciences); Speech coding; Speech recognition; Decoding methods; Algorithm; Telecommunications; Mathematics; Voice activity detection; Speech processing","score_opus":0.03147633471055777,"score_gpt":0.2392477392614549,"score_spread":0.20777140455089713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2277783967","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":[0.028672555,0.00016530523,0.9426103,0.00011652311,0.00020799103,0.00017189614,7.012414e-7,0.00023543845,0.027819278],"genre_scores_gemma":[0.9933724,0.00004609368,0.0062245936,0.00010114134,0.00006429617,0.000016792988,0.000020103229,0.000019401243,0.0001352221],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995202,0.000032106414,0.0001263148,0.000072756106,0.00012338607,0.00012525225],"domain_scores_gemma":[0.9997439,0.000040927436,0.000013129806,0.00014784119,0.00002785436,0.000026382124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019312203,0.00007156219,0.00006929621,0.00004355241,0.000015137877,0.000019844032,0.00010734985,0.000040815346,0.000011225524],"category_scores_gemma":[0.000020036066,0.00005472577,0.000010210755,0.0003022691,0.000011022522,0.0001515955,0.00000891169,0.00007317564,0.00002720111],"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":[0.000002162758,0.0000058980104,0.00027587762,0.000004076954,0.0000019566196,0.0000014562557,0.0004723773,0.9925049,0.000021467798,0.0018973323,0.0018663942,0.002946117],"study_design_scores_gemma":[0.00024560964,0.0000064007513,0.0001643531,0.000008163893,0.0000023951275,0.0000019755064,0.00081802066,0.99708074,0.00040282964,0.00042767957,0.0007560104,0.000085831416],"about_ca_topic_score_codex":0.000012968691,"about_ca_topic_score_gemma":0.0001534479,"teacher_disagreement_score":0.9646998,"about_ca_system_score_codex":0.000048619986,"about_ca_system_score_gemma":0.000007996075,"threshold_uncertainty_score":0.22316521},"labels":[],"label_agreement":null},{"id":"W2285963488","doi":"","title":"Dual-Trigger Handover Algorithm for WiMAX Technology","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"WiMAX; Handover; Computer science; Computer network; Node (physics); Base station; Soft handover; Algorithm; Interoperability; Real-time computing; Wireless; Engineering; Telecommunications","score_opus":0.010980861688108445,"score_gpt":0.1960221571018246,"score_spread":0.18504129541371617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2285963488","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":[0.0002732122,0.00016515404,0.98848534,0.00002160353,0.00024577364,0.00019848745,0.0000040751734,0.00084008276,0.009766302],"genre_scores_gemma":[0.048448842,0.00014348081,0.9491114,0.000040304527,0.00011960134,0.00013636536,0.000014162479,0.00006782701,0.001918012],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995403,0.0000017725293,0.00011363876,0.00010919321,0.000038510483,0.00019653315],"domain_scores_gemma":[0.9997668,0.000015854635,0.0000137018105,0.00014044583,0.00003740144,0.000025751027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000025784071,0.00009345068,0.00010344386,0.000090118585,0.000027796685,0.0000046105483,0.000056704444,0.000103157814,0.00016506416],"category_scores_gemma":[0.0000063774073,0.00008951806,0.00002565049,0.00018377745,0.000022988947,0.00010985897,0.000014865733,0.0000572506,0.00003830351],"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":[0.0000134721895,0.000047169888,0.00012034913,0.00003188989,0.00009071606,0.000007613148,0.0001536377,0.14508885,0.00085946044,0.013217971,0.013674263,0.8266946],"study_design_scores_gemma":[0.0005157922,0.000029760267,0.000021984077,0.000006924197,0.000009856771,0.0000062214585,0.000022120528,0.9578613,0.022045672,0.0045266426,0.014772847,0.00018085448],"about_ca_topic_score_codex":0.0000011904903,"about_ca_topic_score_gemma":0.0000025130196,"teacher_disagreement_score":0.82651377,"about_ca_system_score_codex":0.00002364245,"about_ca_system_score_gemma":0.0000034408713,"threshold_uncertainty_score":0.36504403},"labels":[],"label_agreement":null},{"id":"W2289269826","doi":"10.1109/iwqos.2015.7404756","title":"Robust resource reservation in virtual wireless networks","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"","keywords":"Reservation; Computer science; Mathematical optimization; Convexity; Operator (biology); Dual (grammatical number); Constraint (computer-aided design); Wireless; Resource allocation; Wireless network; Operations research; Computer network; Mathematics; Telecommunications","score_opus":0.03036454012190288,"score_gpt":0.20825622442515265,"score_spread":0.17789168430324978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2289269826","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":[0.06075616,0.00012074591,0.9259605,0.00006082656,0.00019295128,0.00012749973,4.3706578e-7,0.00045477253,0.0123261465],"genre_scores_gemma":[0.99315876,0.000049964485,0.0059016356,0.00006844068,0.00019085029,0.000019475903,0.000048077338,0.000047846963,0.0005149459],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992459,0.00002837581,0.00021294084,0.00013905969,0.00013877738,0.00023498491],"domain_scores_gemma":[0.99963313,0.000043070144,0.000020689173,0.00018223081,0.000039277915,0.000081586506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001861295,0.00011221119,0.00012076195,0.00008538291,0.00001803788,0.000021295962,0.00010925827,0.000105243475,0.000014594401],"category_scores_gemma":[0.00002354669,0.0001205666,0.000014039763,0.00049357954,0.000016084516,0.0002823573,0.000029807576,0.00017113429,0.00001382955],"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":[0.00001245907,0.000007015557,0.0011675882,0.000002534919,0.0000028239879,0.0000027671829,0.00008885204,0.9859217,0.000010740692,0.0011678418,0.0063590254,0.0052566705],"study_design_scores_gemma":[0.0003770465,0.00001693767,0.00040462855,0.000021273776,0.0000014830623,0.0000011418549,0.00015955733,0.99627405,0.00004798451,0.00007856013,0.002473898,0.00014340949],"about_ca_topic_score_codex":0.000011985567,"about_ca_topic_score_gemma":0.00014265772,"teacher_disagreement_score":0.9324026,"about_ca_system_score_codex":0.00014606229,"about_ca_system_score_gemma":0.0000091936245,"threshold_uncertainty_score":0.49165633},"labels":[],"label_agreement":null},{"id":"W2291245833","doi":"","title":"Improving node behaviour in a QoS control environment by means of load-dependent resource redistributions in LANs: Research Articles","year":2005,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Reservation; Quality of service; Shared resource; Computer network; Bandwidth (computing); Resource (disambiguation); Control (management); Node (physics); Distributed computing; Operations research","score_opus":0.015745331435022537,"score_gpt":0.2784099662658823,"score_spread":0.2626646348308598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2291245833","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":[0.5592894,0.014757918,0.42189565,0.0019900056,0.00035268185,0.0006513937,0.0001613854,0.000046329682,0.00085525494],"genre_scores_gemma":[0.99746764,0.00086535484,0.0014737266,0.000008263582,0.00009430534,0.000027150536,0.000022728553,0.000016704986,0.00002409955],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99774456,0.00030339617,0.0009491236,0.0000803256,0.00076310575,0.00015949599],"domain_scores_gemma":[0.99875444,0.0002786117,0.00030406652,0.00027924293,0.00033663993,0.000047017395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016651083,0.00008605832,0.00019859214,0.00029787395,0.000028302376,0.000037922608,0.0006066563,0.0000709682,0.000010779527],"category_scores_gemma":[0.00011695721,0.000092357775,0.000040068982,0.00016395556,0.00005309491,0.00030425497,0.000059006525,0.00043039245,0.00000423104],"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":[0.00004778549,0.00012373774,0.006366919,0.000004685355,0.00002852495,0.000003267341,0.0005212051,0.98484176,0.00538268,0.00022406665,0.00036300413,0.002092342],"study_design_scores_gemma":[0.003189819,0.000049326965,0.0039017117,0.00065615727,0.000013766411,0.000042728407,0.0019263121,0.978604,0.0034739233,0.00006689634,0.007898589,0.00017677233],"about_ca_topic_score_codex":0.00014047578,"about_ca_topic_score_gemma":0.00013156932,"teacher_disagreement_score":0.4381783,"about_ca_system_score_codex":0.0011745986,"about_ca_system_score_gemma":0.00004079496,"threshold_uncertainty_score":0.37662408},"labels":[],"label_agreement":null},{"id":"W2291294793","doi":"10.1109/glocom.2015.7417108","title":"Time-Frequency Resource Conversion Based Scheduling for On-Demand Data Services","year":2015,"lang":"en","type":"article","venue":"2015 IEEE Global Communications Conference (GLOBECOM)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Provisioning; Quality of service; Scheduling (production processes); Computer network; Distributed computing; Time complexity; Job shop scheduling; Dynamic priority scheduling; Mathematical optimization; Real-time computing; Algorithm; Routing (electronic design automation)","score_opus":0.0803395251705915,"score_gpt":0.31372039062506635,"score_spread":0.23338086545447484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2291294793","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":[0.012972537,0.0036206453,0.93707573,0.0028522185,0.0008433366,0.0018871977,0.0019758332,0.0018084666,0.036964044],"genre_scores_gemma":[0.84264946,0.00030621214,0.15287732,0.00034270997,0.00010874225,0.000085806685,0.0035076858,0.000054606426,0.00006745041],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983603,0.00014358849,0.00042588302,0.00039494157,0.0002809884,0.00039430597],"domain_scores_gemma":[0.99519354,0.00023960746,0.00015089342,0.0037461733,0.00042012258,0.00024963488],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00047982438,0.00030443634,0.00031246178,0.00007546209,0.0002581857,0.00012372488,0.002925509,0.00018331433,0.000032555537],"category_scores_gemma":[0.00008930023,0.00033857455,0.000050355364,0.00040656165,0.00016360912,0.00059763645,0.0003630444,0.00024602536,0.00024424065],"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":[0.00006626053,0.00011685402,0.0004370982,0.00010397063,0.00006389154,9.3785115e-7,0.00011505191,0.96708834,0.0001431568,0.0030061693,0.025476288,0.0033819594],"study_design_scores_gemma":[0.0009775385,0.00005375578,0.00003333757,0.00017546107,0.00004390692,0.0000023551268,0.00020150452,0.96831346,0.000096305106,0.0009972608,0.028757099,0.000347998],"about_ca_topic_score_codex":0.000040357518,"about_ca_topic_score_gemma":0.000112867514,"teacher_disagreement_score":0.8296769,"about_ca_system_score_codex":0.00031155068,"about_ca_system_score_gemma":0.00018325575,"threshold_uncertainty_score":0.9999066},"labels":[],"label_agreement":null},{"id":"W2292921681","doi":"10.1109/wcnc.2015.7127600","title":"LTE multi-cell dynamic resource allocation for wireless network virtualization","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Computer network; Scheduling (production processes); Virtualization; Base station; Wireless network; Resource allocation; Heuristic; Wireless; Bandwidth allocation; Distributed computing; Bandwidth (computing); Mathematical optimization; Cloud computing; Telecommunications","score_opus":0.015851914053528402,"score_gpt":0.23621703744412176,"score_spread":0.22036512339059336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2292921681","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":[0.0037464951,0.00033282465,0.9926018,0.00003335769,0.00036384104,0.00047922667,0.0000036988883,0.0007606101,0.0016781077],"genre_scores_gemma":[0.8571145,0.000089180256,0.13981406,0.00008803219,0.0002416547,0.0001266108,0.0004747121,0.00012303957,0.0019282043],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909914,0.000024639861,0.0002575417,0.00019949439,0.00012971164,0.0002894989],"domain_scores_gemma":[0.9994424,0.000057575908,0.00005456734,0.00021872364,0.00012172331,0.000105026855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001630799,0.00016757062,0.00014833028,0.000053184773,0.0000636223,0.000031547894,0.00011767634,0.000115421055,0.0000062437393],"category_scores_gemma":[0.000020548743,0.0001840375,0.000034160585,0.00030105907,0.000016959566,0.00023018199,0.00002014065,0.00007130583,0.000022620152],"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":[0.000014902955,0.00002304173,0.00003597207,0.000025877498,0.000008286609,2.0244202e-7,0.00012485667,0.9876445,0.0002836272,0.00069713924,0.0056834226,0.0054581817],"study_design_scores_gemma":[0.00090197095,0.000033810655,0.000016515938,0.000019163423,0.000012749716,7.7381753e-7,0.00009618477,0.98942405,0.0005683685,0.00017071037,0.008530494,0.00022523815],"about_ca_topic_score_codex":0.0000021837056,"about_ca_topic_score_gemma":0.000039768664,"teacher_disagreement_score":0.853368,"about_ca_system_score_codex":0.00016489165,"about_ca_system_score_gemma":0.00001694215,"threshold_uncertainty_score":0.75048316},"labels":[],"label_agreement":null},{"id":"W2296708642","doi":"","title":"Innovative Opportunistic Scheduling Algorithms for Networks with Packet-Level Dynamics","year":2007,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","keywords":"Computer science; Network packet; Computer network; Distributed computing; Scheduling (production processes); Mathematical optimization; Mathematics","score_opus":0.017018546268858657,"score_gpt":0.22507698841615148,"score_spread":0.20805844214729283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2296708642","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":[0.08644263,0.000095642805,0.9116357,0.000025375095,0.00044479492,0.0005809817,0.00019053854,0.0002351356,0.0003492339],"genre_scores_gemma":[0.10325697,0.0008218595,0.73453456,0.00001915369,0.00030433628,0.0000073268516,0.029093364,0.0004254245,0.13153698],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880874,0.000012637182,0.00019822796,0.0003365894,0.00021730557,0.00042649393],"domain_scores_gemma":[0.9987233,0.00007788297,0.00026369723,0.00025169845,0.0005839821,0.00009941255],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012614355,0.00037372397,0.0004912999,0.00033934732,0.00017080417,0.000018426948,0.00025588062,0.00045229174,0.000020286145],"category_scores_gemma":[0.000010285196,0.00045462715,0.000079563964,0.00063874584,0.0000778124,0.00024181585,0.000022271619,0.00038343077,0.0000024744334],"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":[0.00025435354,0.000023579292,0.00006053731,0.0004112826,0.0002490436,0.000027848742,0.0056840875,0.965283,0.0000498063,0.0006533425,0.0001821595,0.027120972],"study_design_scores_gemma":[0.00076463306,0.000108532,0.00027047592,0.0004160296,0.00013839353,0.0000023619145,0.041878827,0.9556713,0.00010106946,0.000049435035,0.00006640899,0.00053252117],"about_ca_topic_score_codex":0.0004351355,"about_ca_topic_score_gemma":0.017290259,"teacher_disagreement_score":0.17710108,"about_ca_system_score_codex":0.00028319552,"about_ca_system_score_gemma":0.000070686045,"threshold_uncertainty_score":0.99979055},"labels":[],"label_agreement":null},{"id":"W2297871503","doi":"10.14288/1.0165801","title":"Uplink scheduling and resource allocation schemes for LTE-advanced systems that incorporate relays or carry heterogeneous traffic","year":2015,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Telecommunications link; Scheduling (production processes); Resource allocation; Computer network; LTE Advanced; Real-time computing; Distributed computing; Mathematical optimization; Mathematics","score_opus":0.01769319794489695,"score_gpt":0.18203452157210642,"score_spread":0.16434132362720946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2297871503","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":[0.80821663,0.0012876267,0.1894902,0.000012124578,0.00015359434,0.0005197507,0.000033548036,0.00024456103,0.000041990053],"genre_scores_gemma":[0.9805724,0.00030476827,0.01880498,0.000005928694,0.00004208094,0.000006023349,0.00007267644,0.00004448391,0.00014663089],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918103,0.000024246792,0.00014209142,0.00028940587,0.00014045238,0.00022277098],"domain_scores_gemma":[0.9993461,0.00004908537,0.00010292142,0.00019341568,0.00016589978,0.0001425857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001440826,0.00007013323,0.0002616191,0.000047911806,0.0001420026,0.00007797395,0.0001463631,0.00013838477,0.0000016715442],"category_scores_gemma":[0.000027499038,0.00021425498,0.000042686526,0.00021007989,0.00008911292,0.0003994287,0.000046132023,0.00010029115,0.0000015900218],"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":[0.000033803706,0.0000125549595,0.00021643376,0.00016533126,0.00003067992,0.000019729841,0.00012860716,0.85920966,0.00009351301,0.0000012286259,0.00017236141,0.1399161],"study_design_scores_gemma":[0.0016952775,0.00009712934,0.0028520063,0.00030933044,0.000043956028,0.000090836336,0.001575869,0.99210143,0.000010997445,0.00003173616,0.00088680844,0.00030463946],"about_ca_topic_score_codex":0.00047838772,"about_ca_topic_score_gemma":0.008163598,"teacher_disagreement_score":0.17235583,"about_ca_system_score_codex":0.00013454632,"about_ca_system_score_gemma":0.000039738967,"threshold_uncertainty_score":0.8737064},"labels":[],"label_agreement":null},{"id":"W2304090164","doi":"10.1109/iccnc.2016.7440662","title":"Resource allocation for relay-aided OFDMA networks with constraints on queue stability","year":2016,"lang":"en","type":"article","venue":"2016 International Conference on Computing, Networking and Communications (ICNC)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Queue; Computer network; Queueing theory; Relay; Mathematical optimization; Fork–join queue; Telecommunications link; Distributed computing; Queue management system; Mathematics","score_opus":0.04294577750078467,"score_gpt":0.26504491628411253,"score_spread":0.22209913878332788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2304090164","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":[0.010938002,0.00033480048,0.9686471,0.003263058,0.00053225644,0.000632661,0.000036586964,0.0004966739,0.015118822],"genre_scores_gemma":[0.9848463,0.0017864894,0.0123737315,0.00018398158,0.00034270456,0.00011987384,0.00012841767,0.00005426405,0.0001642719],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984855,0.0001293573,0.00043857435,0.00039087268,0.00022273244,0.00033296688],"domain_scores_gemma":[0.9975316,0.0009634278,0.00022837898,0.00084798475,0.0003273619,0.000101263984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038430636,0.00028372923,0.00024381756,0.000117812575,0.0002979303,0.000107021784,0.0006987815,0.00013508776,0.000051495797],"category_scores_gemma":[0.00004965234,0.00022647715,0.000052343552,0.0001668162,0.0003319126,0.000142004,0.00013822319,0.00029338742,0.000007734391],"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":[0.00019104902,0.00010877753,0.0009538915,0.00001693883,0.00015611462,5.9444164e-7,0.00021040828,0.53522766,0.00021695347,0.08697342,0.001846016,0.37409818],"study_design_scores_gemma":[0.00094817247,0.00012796704,0.00056427735,0.0011925142,0.000020083362,0.0000050750073,0.00007806541,0.983255,0.00008442905,0.00070932665,0.012675405,0.00033967895],"about_ca_topic_score_codex":0.0000060136604,"about_ca_topic_score_gemma":0.00003314173,"teacher_disagreement_score":0.97390825,"about_ca_system_score_codex":0.00018416086,"about_ca_system_score_gemma":0.00004778461,"threshold_uncertainty_score":0.923547},"labels":[],"label_agreement":null},{"id":"W2304277709","doi":"10.1109/jiot.2015.2471105","title":"Enhanced Control for Adaptive Resource Reservation of Guaranteed Services in LTE Networks","year":2015,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Computer network; Reservation; Bandwidth (computing); Cellular network; Throughput; Network packet; Quality of service; Core network; Mobile computing; LTE Advanced; Telecommunications; Wireless; Telecommunications link","score_opus":0.014039473375376534,"score_gpt":0.231967776684622,"score_spread":0.21792830330924548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2304277709","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":[0.20669393,0.0003573299,0.7920081,0.000020932679,0.0003857982,0.00017967336,0.000002480434,0.000029948553,0.00032181825],"genre_scores_gemma":[0.98863405,0.000035929144,0.010993581,0.00006345034,0.00017806375,0.0000103604625,0.0000041649782,0.000034453253,0.000045947465],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998799,0.000048972986,0.00062989205,0.00010557876,0.00020445783,0.00021205134],"domain_scores_gemma":[0.9990089,0.00013705084,0.00038748985,0.00010867938,0.00029650537,0.00006140606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057591737,0.00013446402,0.00031946003,0.0001626679,0.0000130490225,0.000019968353,0.00026655407,0.00010816923,0.000004527027],"category_scores_gemma":[0.00005002334,0.0001343725,0.00007243383,0.00017428504,0.000029449238,0.00047368123,0.000014216985,0.00028276598,6.0621596e-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":[0.0006954512,0.000017652756,0.00018702367,0.000046086276,0.000055334618,0.0000015871667,0.0023448782,0.99116266,0.0035387203,0.0000656152,0.0004596324,0.0014253734],"study_design_scores_gemma":[0.0019572529,0.00018297056,0.00007086694,0.00060988584,0.000017082873,0.000009104042,0.00032774356,0.9800694,0.015848475,0.000647921,0.00014900896,0.000110317196],"about_ca_topic_score_codex":0.000022608165,"about_ca_topic_score_gemma":0.000022622637,"teacher_disagreement_score":0.7819401,"about_ca_system_score_codex":0.00011144029,"about_ca_system_score_gemma":0.000015851725,"threshold_uncertainty_score":0.54795516},"labels":[],"label_agreement":null},{"id":"W2306757751","doi":"","title":"Constructive algorithms for the partial directed weighted improper coloring problem","year":2016,"lang":"en","type":"article","venue":"Espace ÉTS (ETS)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"Fractional coloring; Vertex (graph theory); Combinatorics; Constructive; Complete coloring; Graph coloring; Mathematics; Edge coloring; Greedy coloring; Bounded function; Algorithm; Discrete mathematics; Bipartite graph; Integer (computer science); Graph; Computer science; Graph power","score_opus":0.008748216244051485,"score_gpt":0.21916100250516074,"score_spread":0.21041278626110926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2306757751","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":[0.015842786,0.0003339681,0.97846997,0.00056724885,0.0018058865,0.001198261,0.00003912949,0.0010474965,0.0006952299],"genre_scores_gemma":[0.918396,0.00036371555,0.07690484,0.00003511723,0.0010416409,0.0008584916,0.000015100677,0.00016847697,0.0022166034],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990289,0.000025859927,0.00018704121,0.00023823539,0.00013168587,0.00038826762],"domain_scores_gemma":[0.9992058,0.00031282182,0.000058338715,0.00023425119,0.00012109258,0.000067650195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010470004,0.00019760757,0.00018036665,0.000044249507,0.00015179651,0.000032743515,0.00014687728,0.00009376665,0.00005451898],"category_scores_gemma":[0.00004562755,0.000118149575,0.000054200344,0.00022384891,0.00009120588,0.00023685365,0.000036684585,0.000105161394,0.000027918386],"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":[0.0005116398,0.000055128763,0.00088164775,0.00012142914,0.0006745321,0.00000896959,0.002262592,0.517752,0.04862339,0.007106758,0.010814519,0.41118738],"study_design_scores_gemma":[0.0019727417,0.00006592152,0.00033948553,0.00011919202,0.00006145764,0.000008758779,0.00013038253,0.89906543,0.046181455,0.00039814448,0.05118093,0.00047608206],"about_ca_topic_score_codex":0.0000037436719,"about_ca_topic_score_gemma":0.000016389105,"teacher_disagreement_score":0.9025532,"about_ca_system_score_codex":0.00012066421,"about_ca_system_score_gemma":0.000022462724,"threshold_uncertainty_score":0.4818},"labels":[],"label_agreement":null},{"id":"W2314648070","doi":"10.1109/glocomw.2013.6855679","title":"Statistical QoS guarantee for wireless multi-homing video transmission","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Computer network; Video quality; Real-time computing; Network packet; Quality of service; Wireless; Multihoming; Wireless network; Bandwidth (computing); Channel (broadcasting); Telecommunications; The Internet","score_opus":0.009743269705324006,"score_gpt":0.22869637850326857,"score_spread":0.21895310879794455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314648070","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":[0.009303305,0.000094773095,0.98893297,0.00004459514,0.00021858668,0.0005919279,0.00000827867,0.00046885884,0.0003367249],"genre_scores_gemma":[0.50339985,0.00009295671,0.49581552,0.00003861672,0.00009992206,0.00017112948,0.000037749367,0.00006215735,0.00028207875],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991881,0.000009868857,0.00023707312,0.00017463321,0.000090054644,0.00030022077],"domain_scores_gemma":[0.9995712,0.00016005323,0.000017056826,0.00012743789,0.000054371118,0.0000698888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000043895467,0.00015450949,0.00016922013,0.000044197415,0.00006465987,0.000033278546,0.00008699881,0.00008483369,0.00028881725],"category_scores_gemma":[0.000012683628,0.00014225578,0.000037402562,0.00008819472,0.000021466296,0.00025723362,0.000007848553,0.000088869754,0.000056252946],"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":[0.000011268932,0.00002489688,0.00004055932,0.00009192946,0.000017947925,0.0000010101851,0.00011362633,0.76108813,0.010875045,0.0018590759,0.004778618,0.2210979],"study_design_scores_gemma":[0.00067085994,0.000017953565,0.00019184586,0.000032905325,0.000008380674,0.0000014663915,0.000035806024,0.9913525,0.0048422767,0.0003188564,0.0023272608,0.000199915],"about_ca_topic_score_codex":0.000008876845,"about_ca_topic_score_gemma":0.00000509656,"teacher_disagreement_score":0.49409658,"about_ca_system_score_codex":0.000041596257,"about_ca_system_score_gemma":0.000006302493,"threshold_uncertainty_score":0.58010226},"labels":[],"label_agreement":null},{"id":"W2315852694","doi":"10.1109/lcomm.2016.2544830","title":"Power Allocation for SC-FDE-Based CR Systems Under Explicit Primary User Protection","year":2016,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Transmitter; Maximization; Mathematical optimization; Constraint (computer-aided design); Transmitter power output; Computer science; Power (physics); Max-min fairness; Convex optimization; Optimization problem; Regular polygon; Resource allocation; Mathematics; Telecommunications; Computer network","score_opus":0.024331128879375594,"score_gpt":0.23110350789876033,"score_spread":0.20677237901938472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315852694","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":[0.008933144,0.00022065963,0.9836095,0.0048711323,0.00044184944,0.0011450535,0.00001588245,0.0005702691,0.00019253531],"genre_scores_gemma":[0.96680355,0.000115095674,0.030189084,0.00067285326,0.000107393265,0.0018490414,0.000077897275,0.00009438821,0.00009070094],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990535,0.00007795165,0.00031597706,0.000184792,0.00013162351,0.00023619388],"domain_scores_gemma":[0.9980886,0.0003158645,0.00009741328,0.0013301475,0.00011901058,0.000048949445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015187841,0.00017320552,0.00015562892,0.00011365739,0.00019761165,0.000046401743,0.0004431527,0.00009709716,0.000006235345],"category_scores_gemma":[0.00002684524,0.00015940369,0.000060442984,0.00023782063,0.000063574946,0.00037927102,0.000027546828,0.000119008415,0.00002941073],"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":[0.000012860661,0.00002857955,0.000059791084,0.00003920493,0.0000315583,7.3952236e-8,0.000037747224,0.8394553,0.15405999,0.0010552101,0.003014817,0.0022048657],"study_design_scores_gemma":[0.0022846134,0.000066818124,0.0013353272,0.0005856963,0.00006061014,0.000005711356,0.000054342334,0.9243356,0.0182671,0.00022033634,0.051841296,0.0009425776],"about_ca_topic_score_codex":0.0000068504455,"about_ca_topic_score_gemma":0.0000070666247,"teacher_disagreement_score":0.9578704,"about_ca_system_score_codex":0.00044329057,"about_ca_system_score_gemma":0.000022664113,"threshold_uncertainty_score":0.65002936},"labels":[],"label_agreement":null},{"id":"W2324319665","doi":"10.5121/ijwmn.2013.5108","title":"Integration of 4G Wireless Technologies in a Test-Bed Environment","year":2013,"lang":"en","type":"article","venue":"International Journal of Wireless & Mobile Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Wireless; Test (biology); Computer science; Telecommunications; Geology","score_opus":0.004031587077199703,"score_gpt":0.20625689060973948,"score_spread":0.20222530353253979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2324319665","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":[0.6812586,0.0013006531,0.3158916,0.000097599324,0.0008334015,0.00035333328,0.000005442688,0.00010903518,0.00015030355],"genre_scores_gemma":[0.9911128,0.004629178,0.003841064,0.000014074613,0.00023099837,0.00009381036,0.000015965734,0.000046589936,0.00001552046],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980515,0.00003364719,0.0010254375,0.00016036328,0.00046812373,0.0002609269],"domain_scores_gemma":[0.99873406,0.000251038,0.00046816262,0.00019598147,0.00029869762,0.000052084386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019489197,0.00023449784,0.00040102072,0.00040503158,0.000023598472,0.000046299003,0.0005932066,0.00021212618,0.00007681086],"category_scores_gemma":[0.00003953203,0.00022115422,0.000116244046,0.00027063227,0.00011374221,0.00060490606,0.00007956983,0.0005154095,0.000008035959],"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":[0.000020872505,0.00010112839,0.0023822878,0.00000816591,0.00005713581,0.000014765394,0.00010952221,0.79582924,0.011001191,0.00012041851,0.00024312695,0.19011216],"study_design_scores_gemma":[0.000858699,0.00014124603,0.0021107171,0.00044824748,0.000015244655,0.000048756257,0.00061685755,0.98187274,0.012784894,0.0005890227,0.0002695113,0.00024406274],"about_ca_topic_score_codex":0.000017825278,"about_ca_topic_score_gemma":0.000014997804,"teacher_disagreement_score":0.31205052,"about_ca_system_score_codex":0.0003275769,"about_ca_system_score_gemma":0.000023168821,"threshold_uncertainty_score":0.9018407},"labels":[],"label_agreement":null},{"id":"W2333287722","doi":"10.1109/glocomw.2013.6855688","title":"Cross-layer carrier selection and power control for LTE-A uplink with Carrier Aggregation","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Telecommunications link; Computer science; Power control; Throughput; Offset (computer science); LTE Advanced; Physical layer; Computer network; Carrier frequency offset; Bandwidth (computing); Multi-user; Real-time computing; Power (physics); Orthogonal frequency-division multiplexing; Wireless; Telecommunications; Frequency offset; Channel (broadcasting)","score_opus":0.0045369544648132,"score_gpt":0.2145310627022431,"score_spread":0.2099941082374299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2333287722","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":[0.15376101,0.00010568053,0.84434783,0.00004314076,0.00011764217,0.00053754635,0.000009211167,0.0002692253,0.0008087255],"genre_scores_gemma":[0.9783294,0.000019958527,0.020273402,0.000076474134,0.00007758328,0.0001395625,0.000020676267,0.000056633635,0.0010062868],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993627,0.0000070738315,0.00015033325,0.00018301679,0.00007795773,0.00021893904],"domain_scores_gemma":[0.99949086,0.00005084479,0.00003131918,0.0001035776,0.00025034527,0.00007304178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000039365095,0.00014437044,0.00013198216,0.000040353436,0.00008868089,0.000086593434,0.000028778999,0.000099487246,0.00019080902],"category_scores_gemma":[0.000017226856,0.00012526878,0.000020446796,0.00013233037,0.000023743733,0.00048570964,0.0000052172727,0.000077768505,0.0000070714473],"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":[0.000027752243,0.0000044739395,0.005769281,0.000021419944,0.000043723856,2.597546e-7,0.00008200054,0.98689026,0.0020811278,0.00040367834,0.00049977656,0.0041762204],"study_design_scores_gemma":[0.0012476671,0.000055590932,0.002929406,0.000011777516,0.000018883466,0.000007727694,0.000022071783,0.98873407,0.0053345202,0.00028477068,0.0011457294,0.00020780688],"about_ca_topic_score_codex":0.000011657771,"about_ca_topic_score_gemma":0.00003799367,"teacher_disagreement_score":0.8245684,"about_ca_system_score_codex":0.0000547113,"about_ca_system_score_gemma":0.000013383635,"threshold_uncertainty_score":0.51083124},"labels":[],"label_agreement":null},{"id":"W2341485779","doi":"10.14288/1.0066831","title":"Optimal resource management in wireless access networks","year":2008,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Computer science; Wireless; Wireless network; Computer network; Resource management (computing); Telecommunications; Business","score_opus":0.007254964606553492,"score_gpt":0.16798939839681395,"score_spread":0.16073443379026045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2341485779","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":[0.8729795,0.0001579926,0.120777085,0.000006952352,0.00008230783,0.00020626409,0.0000092210785,0.00019519251,0.0055854726],"genre_scores_gemma":[0.99479586,0.0014800571,0.0032388072,0.000012053874,0.000027751717,0.0000011220341,0.000027984053,0.000029065388,0.00038727123],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9991704,0.00002280789,0.00012753256,0.0002451092,0.00015270847,0.00028139178],"domain_scores_gemma":[0.9996175,0.000020031472,0.000046181554,0.00021079491,0.000034384422,0.00007107897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060509166,0.00005093752,0.00020791373,0.000065737644,0.000095477684,0.000035055164,0.00035795948,0.00009697204,0.000029934454],"category_scores_gemma":[0.0000014682681,0.00021333371,0.000051309424,0.000534772,0.000119310775,0.00042408588,0.00014091108,0.00015744418,0.000004417328],"study_design_candidate":"simulation_or_modeling","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":[0.000006052007,0.000028595301,0.0047151777,0.0000366451,0.000022730756,0.00039293326,0.000054280663,0.8130899,0.0000029659857,0.0000012999014,0.003014713,0.17863469],"study_design_scores_gemma":[0.00071469217,0.000010387162,0.6186168,0.0001095416,0.0000101066125,0.000033714357,0.00021515613,0.37976092,3.124193e-7,0.00000990548,0.00032669827,0.0001917352],"about_ca_topic_score_codex":0.0026860088,"about_ca_topic_score_gemma":0.021954615,"teacher_disagreement_score":0.6139017,"about_ca_system_score_codex":0.000109457476,"about_ca_system_score_gemma":0.0000073671417,"threshold_uncertainty_score":0.99589217},"labels":[],"label_agreement":null},{"id":"W2345896629","doi":"10.1109/access.2016.2562024","title":"The Omitted Dimension: Exploiting Multiuser Diversity in Multi-Radio Access Technology Data Cellular Communication Systems","year":2016,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Wireless Network Optimization","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 Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Spectral efficiency; Computer network; Cellular network; Scalability; Distributed computing; Communications system; Transmission (telecommunications); Bandwidth (computing); Telecommunications","score_opus":0.09493724962596184,"score_gpt":0.3031636411067498,"score_spread":0.20822639148078798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345896629","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":[0.51639235,0.0017270655,0.47969455,0.0002451802,0.00078500423,0.0005051709,0.000018935983,0.0005823485,0.000049418282],"genre_scores_gemma":[0.9967607,0.0016159783,0.0013996941,0.000009626954,0.000054799348,0.00005258932,0.0000319055,0.000043003452,0.00003166305],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987895,0.00009138266,0.00033220337,0.0002994693,0.00015872471,0.00032872512],"domain_scores_gemma":[0.9978624,0.00032530332,0.00012244839,0.001562613,0.000084867504,0.000042359767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030100122,0.00017335538,0.0001982271,0.0001551929,0.00038663685,0.00013702064,0.0028046556,0.00015253997,0.000003571859],"category_scores_gemma":[0.000090101006,0.00012422341,0.000017408338,0.00058690936,0.000101001875,0.0018739289,0.0017622748,0.0002179811,0.00001284671],"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":[0.000022690609,0.000042514268,0.064738736,0.000043409345,0.000053827946,0.000014522313,0.00015044335,0.9152981,0.0051327664,0.00018161736,0.0008990377,0.013422323],"study_design_scores_gemma":[0.0011129292,0.0000044235708,0.0035128256,0.00028905825,0.000015523226,0.0000029684466,0.00012811764,0.9873157,0.0063524307,0.00009373695,0.00087121245,0.00030104376],"about_ca_topic_score_codex":0.000102522215,"about_ca_topic_score_gemma":0.00027175908,"teacher_disagreement_score":0.4803684,"about_ca_system_score_codex":0.00016325647,"about_ca_system_score_gemma":0.00000951962,"threshold_uncertainty_score":0.5211795},"labels":[],"label_agreement":null},{"id":"W2353462733","doi":"","title":"A feasible resource allocation scheme for multi-user OFDM systems with various services","year":2008,"lang":"en","type":"article","venue":"Journal of Circuits and Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"L'Alliance Boviteq","funders":"","keywords":"Computer science; Resource allocation; Orthogonal frequency-division multiplexing; Telecommunications link; Throughput; Fading; Quality of service; Resource management (computing); Transmission (telecommunications); Channel (broadcasting); Scheme (mathematics); Computer network; Distributed computing; Mathematical optimization; Algorithm; Wireless; Telecommunications; Mathematics","score_opus":0.02422511218098618,"score_gpt":0.22630608209173605,"score_spread":0.20208096991074986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2353462733","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":[0.15704574,0.009028766,0.8325131,0.000014137353,0.00049908983,0.0005427057,0.0000064410965,0.000076116885,0.00027389338],"genre_scores_gemma":[0.9966261,0.00033201298,0.0021381981,0.000010198087,0.00037635354,0.00002216689,0.0000054782813,0.00004782351,0.00044169242],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990081,0.00002903333,0.0004544965,0.00010480198,0.00022145339,0.00018210102],"domain_scores_gemma":[0.99916583,0.000049817543,0.0002891227,0.00011984885,0.00027651063,0.00009884261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022665407,0.00014271903,0.00032911805,0.0001130386,0.000108136344,0.00006940831,0.00010004867,0.00008684658,5.1731683e-7],"category_scores_gemma":[0.00000730017,0.000113249946,0.000035248522,0.00014586859,0.000018194582,0.00032339306,0.000005581475,0.00011580862,7.7939086e-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":[0.00001952783,0.000021470805,0.0020705096,0.0006867075,0.000098915574,0.0000143258485,0.00064761844,0.99462557,0.00091701257,0.00032772083,0.00031286333,0.00025776777],"study_design_scores_gemma":[0.0017406818,0.00016815998,0.001000749,0.0008187398,0.00004123267,0.0012500782,0.0006962595,0.9764889,0.00007894581,0.0000025189897,0.017492611,0.00022113681],"about_ca_topic_score_codex":0.00001174858,"about_ca_topic_score_gemma":0.00000580111,"teacher_disagreement_score":0.83958036,"about_ca_system_score_codex":0.00006812953,"about_ca_system_score_gemma":0.000026690303,"threshold_uncertainty_score":0.4618199},"labels":[],"label_agreement":null},{"id":"W2413417445","doi":"","title":"Optimal linear-time uplink scheduling algorithms for WiMAX","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Telecommunications link; WiMAX; Computer science; Scheduling (production processes); Network packet; Mathematical optimization; Wireless; Fair-share scheduling; Linear programming; Heuristic; Distributed computing; Algorithm; Computer network; Mathematics; Telecommunications; Quality of service; Artificial intelligence","score_opus":0.01729677776528334,"score_gpt":0.23607346735766802,"score_spread":0.21877668959238467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2413417445","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":[0.01520185,0.00018292337,0.9818358,0.00003187951,0.00019069137,0.00023871094,0.000003980628,0.0008722258,0.0014419369],"genre_scores_gemma":[0.04785634,0.00014899365,0.9501227,0.00003684964,0.00040706934,0.000046841014,0.00005765811,0.0000784937,0.0012450133],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992492,0.0000036296024,0.00020090073,0.00017021036,0.00008421846,0.00029181378],"domain_scores_gemma":[0.9996256,0.00006197419,0.000021075075,0.00015684025,0.0000635665,0.00007091531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000050263003,0.0001513412,0.0001648346,0.00005138763,0.000106502375,0.00000915281,0.00009698724,0.00009200389,0.000092720766],"category_scores_gemma":[0.000019079453,0.00015900351,0.00005904494,0.00016341076,0.000027106338,0.00019946657,0.000018674018,0.00010224205,0.00009984528],"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":[0.0000061187184,0.000008084529,0.000017725586,0.000011081098,0.000016224021,0.0000023988207,0.000037793783,0.9948291,0.0006581566,0.000072512084,0.00057307584,0.0037677279],"study_design_scores_gemma":[0.00037888478,0.000023222297,0.00001385529,0.000010021382,0.000006268221,0.000013097071,0.000006587454,0.9932226,0.0042641135,0.000025172983,0.0018330816,0.0002030872],"about_ca_topic_score_codex":7.870644e-7,"about_ca_topic_score_gemma":2.0278092e-7,"teacher_disagreement_score":0.03265449,"about_ca_system_score_codex":0.000044738874,"about_ca_system_score_gemma":0.000012539742,"threshold_uncertainty_score":0.6483975},"labels":[],"label_agreement":null},{"id":"W2415035074","doi":"","title":"Quality-of-service and performance optimization in broadband wireless access networks -- a cross-layer study","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"","keywords":"Computer science; Computer network; Wireless broadband; Quality of service; Wireless network; Link adaptation; Cross-layer optimization; Wireless; Media access control; Radio resource management; Network packet; Fading; Channel (broadcasting); Telecommunications","score_opus":0.023689895127724188,"score_gpt":0.30726548015164223,"score_spread":0.28357558502391805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2415035074","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":[0.68705344,0.00011704784,0.31119803,0.000011732281,0.000062434694,0.00029842902,5.5168044e-7,0.00012194316,0.0011363644],"genre_scores_gemma":[0.9955511,0.00038064705,0.0038566566,0.00008685067,0.00004146401,0.000017150978,0.000012191285,0.000025688667,0.000028223993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889165,0.000037028607,0.00047354633,0.00021650035,0.00014514348,0.00023614753],"domain_scores_gemma":[0.9995217,0.000054471377,0.000074395124,0.00021158489,0.00008896103,0.000048887763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021043241,0.0001760892,0.00027587113,0.000114312425,0.00003917237,0.000072187955,0.00016860927,0.00009407442,0.000019096417],"category_scores_gemma":[0.000007631979,0.00018130211,0.000014904786,0.0007131296,0.000018314971,0.00084080454,0.000039744686,0.00014894258,5.9507363e-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":[0.000045938767,0.000063363215,0.14244159,0.000035223886,0.0000071760687,6.221661e-7,0.00019521134,0.85002124,0.000021526183,0.00003589026,0.0000056591234,0.00712656],"study_design_scores_gemma":[0.00074656407,0.00004805427,0.24692492,0.000027426007,0.0000033496528,6.6860713e-7,0.000040998235,0.75197494,0.000064734646,0.000011097559,0.000001585334,0.00015564826],"about_ca_topic_score_codex":0.000027971137,"about_ca_topic_score_gemma":0.000118634096,"teacher_disagreement_score":0.30849767,"about_ca_system_score_codex":0.000039307994,"about_ca_system_score_gemma":0.0000066813905,"threshold_uncertainty_score":0.73932856},"labels":[],"label_agreement":null},{"id":"W2419144360","doi":"10.1109/wts.2016.7482052","title":"Resource management in OFDMA heterogeneous network","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Kensington Health","funders":"European Social Fund; National Technical University of Athens; European Commission","keywords":"Orthogonal frequency-division multiple access; Computer science; Channel state information; Resource allocation; Resource management (computing); Interference (communication); Frequency-division multiple access; Radio resource management; Heterogeneous network; Computer network; Orthogonal frequency-division multiplexing; Channel (broadcasting); Distributed computing; Telecommunications; Wireless network; Wireless","score_opus":0.004552831958689042,"score_gpt":0.18274617677164728,"score_spread":0.17819334481295823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2419144360","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":[0.024500854,0.00070640864,0.8982212,0.00019620937,0.00026282834,0.00029500877,0.0000012510651,0.0008399806,0.07497629],"genre_scores_gemma":[0.9834861,0.00083065644,0.013667569,0.000082838524,0.00012943344,0.000047529596,0.0000019272409,0.000042132342,0.0017118256],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947155,0.0000090370195,0.00012522745,0.00010789281,0.000060767474,0.00022555281],"domain_scores_gemma":[0.9997901,0.00002241292,0.000009435918,0.00014473962,0.0000042524566,0.000029057774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037357622,0.000080816455,0.00007310106,0.000038353774,0.000012727736,0.0000055705614,0.000073704716,0.000032510063,0.00012147308],"category_scores_gemma":[0.0000010020964,0.00006114693,0.000015564921,0.00015611055,0.000008228665,0.000055535766,0.00002061006,0.000027829397,0.00004097646],"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":[0.0000033761607,0.0000030470264,0.00034563438,0.000005339205,0.000010317672,0.000009186775,0.0000055640307,0.90404415,0.000040476523,0.00079252006,0.0019430082,0.0927974],"study_design_scores_gemma":[0.0016761321,0.000028741257,0.002316767,0.00033960684,0.000016865402,0.000008808736,0.000024597177,0.81383395,0.0025772844,0.0026212994,0.17580225,0.00075371517],"about_ca_topic_score_codex":5.1715904e-7,"about_ca_topic_score_gemma":0.000013520494,"teacher_disagreement_score":0.9589852,"about_ca_system_score_codex":0.00005793892,"about_ca_system_score_gemma":6.150983e-7,"threshold_uncertainty_score":0.24934995},"labels":[],"label_agreement":null},{"id":"W2421748616","doi":"10.1109/glocom.2016.7841867","title":"HARQ and AMC: Friends or Foes?","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"InterDigital (Canada); Institut National de la Recherche Scientifique","funders":"","keywords":"Hybrid automatic repeat request; Computer science; Fading; Automatic repeat request; Throughput; Decoding methods; Link adaptation; Computer network; Redundancy (engineering); Block Error Rate; Algorithm; Real-time computing; Wireless; Telecommunications; Telecommunications link","score_opus":0.010377802271304344,"score_gpt":0.2238662362030625,"score_spread":0.21348843393175818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2421748616","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":[0.0022150069,0.00046201903,0.96411395,0.00007112201,0.0007505947,0.00018144619,0.000019515735,0.0008532504,0.031333115],"genre_scores_gemma":[0.8758393,0.004105319,0.109067634,0.00008210165,0.0007948669,0.00013179527,0.000075616685,0.00021121318,0.009692159],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929917,0.000007642019,0.00017190301,0.00024315846,0.00008289863,0.00019522294],"domain_scores_gemma":[0.99953383,0.0000453174,0.00003246491,0.00029276934,0.000027540205,0.00006806412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003499639,0.00021215822,0.00020601547,0.000061793435,0.000024188423,0.00003663566,0.000108964756,0.00022171132,0.0003455402],"category_scores_gemma":[0.00001029872,0.00015127719,0.000027404209,0.000051714265,0.000025217163,0.00009154337,0.00021135049,0.00020175039,0.000026403728],"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":[0.00001683006,0.000006600955,0.00021800312,0.00025259558,0.000095489,0.0000103727925,0.00009242123,0.9385739,0.00012833565,0.002251072,0.006847699,0.0515067],"study_design_scores_gemma":[0.00060121,0.00002493877,0.00044126544,0.00047163913,0.00005149885,0.00001250244,0.000022958446,0.9622633,0.0015618457,0.008449469,0.025092762,0.0010066333],"about_ca_topic_score_codex":0.0000015912908,"about_ca_topic_score_gemma":0.00001088214,"teacher_disagreement_score":0.87362427,"about_ca_system_score_codex":0.00005572028,"about_ca_system_score_gemma":0.0000125756205,"threshold_uncertainty_score":0.6168905},"labels":[],"label_agreement":null},{"id":"W2468536001","doi":"10.1142/9789812839442_0003","title":"WIMAX/802.16 BROADBAND WIRELESS NETWORKS","year":2010,"lang":"en","type":"book-chapter","venue":"WORLD SCIENTIFIC eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"WiMAX; Wireless broadband; Computer network; Broadband; Computer science; Telecommunications; Broadband networks; Wireless; Wireless network","score_opus":0.008569080550097849,"score_gpt":0.19076372516762757,"score_spread":0.1821946446175297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2468536001","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001080813,0.0008743407,0.07281686,0.000009385374,0.008792889,0.0005902902,0.0000417385,0.0010969605,0.91566944],"genre_scores_gemma":[0.021450663,0.00002469565,0.0021988053,0.00005397734,0.0010954395,0.000041107593,0.0003143203,0.00038445526,0.9744365],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99701816,0.000014755454,0.00067192776,0.0009305642,0.00059050426,0.00077408593],"domain_scores_gemma":[0.9979353,0.00009190585,0.00022466033,0.0012803349,0.00017566555,0.0002921245],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00031939495,0.00076210767,0.00066391024,0.0006226594,0.00048727955,0.0004203181,0.00063529256,0.000615663,0.0007248701],"category_scores_gemma":[0.0000035352546,0.0008443448,0.00024088107,0.0001389722,0.00065297657,0.0001390782,0.00015077996,0.001684219,0.00026039124],"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":[0.000045918074,0.000026237361,0.000022546967,0.00031698865,0.0003283033,0.000104720115,0.00035222477,0.6264441,0.0025922845,0.114895195,0.10951657,0.14535493],"study_design_scores_gemma":[0.0002811381,0.000008910155,0.0000026448056,0.00039217647,0.00007248277,0.000010447817,0.0000024121307,0.07964804,0.000761738,0.0048539713,0.91294885,0.0010172122],"about_ca_topic_score_codex":0.0000010438893,"about_ca_topic_score_gemma":0.0016857312,"teacher_disagreement_score":0.8034323,"about_ca_system_score_codex":0.00025046594,"about_ca_system_score_gemma":0.000062923136,"threshold_uncertainty_score":0.99940073},"labels":[],"label_agreement":null},{"id":"W2471563798","doi":"10.4995/thesis/10251/63261","title":"3GPP Long Term Evolution: Performance Analysis and Evolution towards 4G with Coordinated Multi-Point Transmission.","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"","keywords":"LTE Advanced; Computer science; Scheduling (production processes); Telecommunications link; Radio resource management; Term (time); Transmission (telecommunications); Resource (disambiguation); Telecommunications; Computer network; Engineering; Wireless; Wireless network","score_opus":0.0041239113362897565,"score_gpt":0.20817062722038898,"score_spread":0.20404671588409923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2471563798","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":[0.07771539,0.0015484196,0.91728705,0.000012310752,0.00019518351,0.00040105946,0.000012583305,0.00059098325,0.002237004],"genre_scores_gemma":[0.98116106,0.0012799219,0.010993151,0.00000332986,0.00007920382,0.0000880195,0.0010490242,0.000113411974,0.0052329046],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984589,0.000028058028,0.0004399305,0.00043138477,0.00024563086,0.00039606326],"domain_scores_gemma":[0.9991378,0.00001865979,0.00014124285,0.0003134569,0.00023581042,0.00015299498],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008883683,0.00050711446,0.00054664636,0.0005772214,0.00018653098,0.000045517114,0.00014395356,0.00039998852,0.00015876515],"category_scores_gemma":[0.00000634276,0.0003891593,0.000110478504,0.0011008796,0.000045695702,0.0005409274,0.000010403186,0.00028754276,0.000010957869],"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":[0.0003064402,0.00006580252,0.02343043,0.0009546026,0.0015790908,0.000013324686,0.0005843867,0.8300159,0.001240903,0.00009509496,0.00007371567,0.14164032],"study_design_scores_gemma":[0.0012465483,0.000086568005,0.36219805,0.00076239987,0.0010916789,0.0000116410265,0.0001592491,0.63097113,0.0024971862,0.000017084523,0.000014530664,0.0009439288],"about_ca_topic_score_codex":0.000034302728,"about_ca_topic_score_gemma":0.00030501437,"teacher_disagreement_score":0.9062939,"about_ca_system_score_codex":0.00044775475,"about_ca_system_score_gemma":0.00006684249,"threshold_uncertainty_score":0.99985605},"labels":[],"label_agreement":null},{"id":"W2478294536","doi":"10.1142/9789812837318_0014","title":"Performance of Bridging Algorithms in IEEE 802.15.3 Multi-Piconet Networks","year":2010,"lang":"en","type":"book-chapter","venue":"WORLD SCIENTIFIC eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Bridging (networking); Piconet; Computer science; Algorithm; Computer network; Bluetooth; Wireless; Telecommunications","score_opus":0.014274331981112488,"score_gpt":0.20773246559261355,"score_spread":0.19345813361150105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2478294536","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01657034,0.0017630226,0.17377868,0.000010992581,0.022015573,0.0021277843,0.00010780667,0.0012167625,0.782409],"genre_scores_gemma":[0.22892962,0.000030441779,0.017630886,0.000016499684,0.00048402522,0.000036091176,0.00011899955,0.0002443144,0.7525091],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976536,0.000012451731,0.0007715977,0.00061353034,0.00038869696,0.00056013896],"domain_scores_gemma":[0.9986824,0.00005694448,0.00025049775,0.0007709688,0.00011688793,0.00012232782],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040774996,0.00048984005,0.00059572415,0.0008253708,0.00015179509,0.000086692504,0.0004417021,0.00036456875,0.00010506952],"category_scores_gemma":[0.0000035342373,0.00056987023,0.00012861898,0.00016095382,0.00041141477,0.00013385582,0.000082061655,0.0012257759,0.00003733386],"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":[0.000008809178,0.000009456911,0.00007583681,0.0001390334,0.000024722844,0.000011950039,0.00020630518,0.97351015,0.0013202566,0.00041713947,0.00076442864,0.023511915],"study_design_scores_gemma":[0.00037363003,0.000010265965,0.000045094002,0.0006039568,0.000024343983,0.0000042098604,0.0000027279373,0.9664556,0.0020222417,0.00007021476,0.029820714,0.00056703493],"about_ca_topic_score_codex":0.0000019827814,"about_ca_topic_score_gemma":0.0013329505,"teacher_disagreement_score":0.21235928,"about_ca_system_score_codex":0.00013225361,"about_ca_system_score_gemma":0.000045839948,"threshold_uncertainty_score":0.9996753},"labels":[],"label_agreement":null},{"id":"W2479930532","doi":"10.1109/icc.2016.7511481","title":"A performance study of proxy-based TCP rate control design for mobile video streaming services","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Petroleum Technology Research Centre","keywords":"Computer network; Computer science; Real-time computing; Backhaul (telecommunications); Proxy (statistics); Network packet; Base station; Queue; Bandwidth (computing)","score_opus":0.007246856868852926,"score_gpt":0.2110427360068348,"score_spread":0.20379587913798186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2479930532","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":[0.40964264,0.00001869409,0.5890173,0.000003008022,0.000038637034,0.0010902497,0.000003859337,0.00015004873,0.00003558119],"genre_scores_gemma":[0.98249084,0.000013257191,0.01663184,0.000012776585,0.00003095527,0.00072441215,0.0000023919054,0.000037509377,0.000056026412],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993334,0.00002681623,0.00023309665,0.00014150422,0.0000778449,0.00018737963],"domain_scores_gemma":[0.9993718,0.00027039423,0.000060478815,0.00017713787,0.00008873181,0.000031438543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014897576,0.0001275999,0.00018227965,0.000055295106,0.00003702859,0.000008060264,0.000099494835,0.000036105186,0.000019469915],"category_scores_gemma":[0.0000066733282,0.000089883215,0.00002281645,0.00011084631,0.000010239135,0.00021832604,0.0000067611277,0.000024753725,0.0000031761251],"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":[0.00008930271,0.000060479164,0.002370443,0.00012076508,0.000028162303,1.9493602e-7,0.00012836061,0.98181635,0.0063016987,0.00000446619,0.000012655668,0.009067096],"study_design_scores_gemma":[0.002877606,0.00042707036,0.00043703357,0.00008536088,0.000020396725,1.1215939e-7,0.00017547385,0.97484607,0.020960355,0.0000069618095,0.000037038735,0.00012653817],"about_ca_topic_score_codex":0.000002499998,"about_ca_topic_score_gemma":0.000009170371,"teacher_disagreement_score":0.5728482,"about_ca_system_score_codex":0.000037981536,"about_ca_system_score_gemma":0.000010626783,"threshold_uncertainty_score":0.36653313},"labels":[],"label_agreement":null},{"id":"W2480183620","doi":"10.1109/icc.2016.7511225","title":"Joint user association and rate allocation for HTTP adaptive streaming in heterogeneous cellular networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Scheduling (production processes); Cellular network; Greedy algorithm; Computer network; Wireless network; Distributed computing; Joint (building); Wireless; Mathematical optimization; Algorithm","score_opus":0.008671220193221243,"score_gpt":0.1887101422656559,"score_spread":0.18003892207243466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2480183620","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":[0.107893534,0.00015515364,0.89132464,0.00004409844,0.00011382878,0.0002712194,0.0000024983315,0.00011935088,0.00007568657],"genre_scores_gemma":[0.99009055,0.00023638041,0.009189984,0.00002009674,0.00008627476,0.00006354249,0.000014363939,0.000033272278,0.00026555604],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993822,0.000023400518,0.00018728992,0.00014730982,0.000052454387,0.00020731814],"domain_scores_gemma":[0.99964863,0.00014302823,0.00005116077,0.000078972174,0.000046434823,0.000031771648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015117352,0.00010661637,0.000119724995,0.000050201466,0.000027690501,0.000015572496,0.000027720074,0.00009684051,0.000007393416],"category_scores_gemma":[0.000031317686,0.0000901831,0.000019873152,0.00008350853,0.000006414867,0.0001969257,0.000011726006,0.000042898435,0.0000021524859],"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":[0.000009229731,0.0000048924476,0.00063532527,0.0000060789143,0.000015857237,5.2874714e-7,0.000030892155,0.97734845,0.004760192,0.00032203385,0.000058888527,0.016807642],"study_design_scores_gemma":[0.00048988324,0.000027959768,0.00080146175,0.0000430037,0.0000073104216,3.2101215e-7,0.000013194537,0.9893391,0.008794745,0.00020925075,0.00013797297,0.00013576634],"about_ca_topic_score_codex":0.000004434151,"about_ca_topic_score_gemma":0.00008038119,"teacher_disagreement_score":0.882197,"about_ca_system_score_codex":0.0002651468,"about_ca_system_score_gemma":0.0000040043165,"threshold_uncertainty_score":0.36775604},"labels":[],"label_agreement":null},{"id":"W2484513607","doi":"10.4018/978-1-60566-054-7.ch097","title":"Wireless Technologies for Mobile Computing and Commerce","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Cellular network; Handover; Telecommunications; Computer science; Computer network; Mobile commerce; Wireless network; Service (business); Mobile computing; Wireless; Business model; Mobility management; Business; World Wide Web; Marketing","score_opus":0.00908956048645529,"score_gpt":0.2311044574781472,"score_spread":0.2220148969916919,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2484513607","genre_codex":"other","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":[0.00041482606,0.003339821,0.1771074,0.000020169146,0.00035153874,0.0012699661,0.00013384149,0.0032329247,0.81412953],"genre_scores_gemma":[0.92370373,0.0005130916,0.058918398,0.0002279678,0.00052609784,0.00012616512,0.000073987765,0.0003697237,0.015540859],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990036,0.000002803779,0.00028297867,0.00029891555,0.0001079993,0.00030370403],"domain_scores_gemma":[0.99947566,0.000053287324,0.00009129309,0.00028013595,0.00005524277,0.000044393335],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000037408037,0.00038385155,0.00042649155,0.00005317135,0.00009039563,0.000042441578,0.0001836703,0.0004808396,0.0000010495816],"category_scores_gemma":[0.0000044501776,0.00043523387,0.000074306074,0.000016865113,0.00008515687,0.00003654477,0.00007665487,0.0002415747,0.000004448627],"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":[0.000008409476,0.0000020364516,0.0000033655929,0.00009742304,0.000044239256,0.0000048548522,0.000018702302,0.08573883,0.00001408702,0.44965565,0.0007444134,0.463668],"study_design_scores_gemma":[0.0014632469,0.0003542232,0.000017192424,0.0015520866,0.00020538976,0.00009286329,0.000113561684,0.4310143,0.00040405718,0.44251177,0.11979779,0.0024735178],"about_ca_topic_score_codex":0.0000010801419,"about_ca_topic_score_gemma":0.00000772901,"teacher_disagreement_score":0.9232889,"about_ca_system_score_codex":0.00016408168,"about_ca_system_score_gemma":0.000012593296,"threshold_uncertainty_score":0.9998099},"labels":[],"label_agreement":null},{"id":"W2485893990","doi":"10.1002/wcm.2717","title":"Wireless resource virtualization: opportunities, challenges, and solutions","year":2016,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Sheridan College; Western University","funders":"","keywords":"Computer science; Virtualization; Computer network; Cellular network; Wireless network; Network virtualization; Base station; Quality of service; Wireless; Telecommunications; Cloud computing; Operating system","score_opus":0.052869046961659436,"score_gpt":0.24374491438881113,"score_spread":0.19087586742715168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2485893990","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":[0.10547351,0.089278735,0.79378474,0.0015819509,0.00021278927,0.00077295053,0.000041394014,0.001588956,0.007265002],"genre_scores_gemma":[0.8797464,0.11636757,0.003548224,0.000037461108,0.000066186716,0.00006879679,0.000039007202,0.000053594635,0.00007279646],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988621,0.000112877344,0.00035541694,0.00024543286,0.000108513894,0.0003156544],"domain_scores_gemma":[0.99842906,0.0004115367,0.00008730662,0.0008566054,0.0000824903,0.00013298605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023792648,0.0002085022,0.00022622684,0.00011311593,0.000514003,0.000045833134,0.0003225242,0.00010655598,0.000005869417],"category_scores_gemma":[0.0000100080315,0.00019314143,0.000026972777,0.00014089141,0.00029698858,0.00024798393,0.0004637305,0.00014496519,0.0000025811908],"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":[0.0000023023415,0.00002704813,0.00006146658,0.000045885077,0.00002793632,9.606947e-7,0.0010444276,0.006835618,0.0005698267,0.04412957,0.00014438477,0.9471106],"study_design_scores_gemma":[0.0006567471,0.00005397262,0.00037282714,0.0005231039,0.000027978309,0.000043348296,0.0016160727,0.87068117,0.0000882513,0.00043878247,0.12497632,0.00052145007],"about_ca_topic_score_codex":0.000003392049,"about_ca_topic_score_gemma":0.000019384099,"teacher_disagreement_score":0.9465891,"about_ca_system_score_codex":0.00006292617,"about_ca_system_score_gemma":0.000018475075,"threshold_uncertainty_score":0.7876079},"labels":[],"label_agreement":null},{"id":"W2488604116","doi":"","title":"Courteous algorithm: performance optimization in WiMAX networks","year":2010,"lang":"en","type":"article","venue":"International Conference on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"WiMAX; Computer science; Quality of service; Scheduling (production processes); Network packet; Computer network; Algorithm; Mathematical optimization; Wireless; Mathematics; Telecommunications","score_opus":0.02133959105202333,"score_gpt":0.2676907548703346,"score_spread":0.2463511638183113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2488604116","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":[0.006243165,0.00007152564,0.88318086,0.0010550629,0.0014571758,0.00030809263,0.000023774186,0.00044623582,0.107214086],"genre_scores_gemma":[0.89617246,0.0024435367,0.10075416,0.00007106572,0.000090891896,0.00006712894,0.00027521065,0.000030202425,0.000095357296],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991758,0.000026678785,0.00029323186,0.00015277964,0.00017000809,0.00018153254],"domain_scores_gemma":[0.99891716,0.00008875406,0.00006165356,0.0007114542,0.00016958706,0.000051409323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011653744,0.00014773966,0.000117177064,0.00017891219,0.00009410008,0.00006946575,0.00091055466,0.00011155487,0.0002501057],"category_scores_gemma":[0.000024488982,0.000172432,0.000026294289,0.00024460268,0.00009076611,0.0003241638,0.0000957935,0.000647837,0.00003085829],"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":[0.000004219615,0.00004453773,0.00033852854,0.0000015975519,0.000010252411,6.26281e-7,0.000048809346,0.9519597,0.00009024752,0.011155349,0.000088890556,0.036257222],"study_design_scores_gemma":[0.00024546863,0.000014113036,0.00067265466,0.0000420912,0.0000029427329,0.000005400065,0.000024307863,0.997034,0.00005141426,0.00023053253,0.0015083052,0.0001687442],"about_ca_topic_score_codex":0.000008379866,"about_ca_topic_score_gemma":0.00013719201,"teacher_disagreement_score":0.8899293,"about_ca_system_score_codex":0.00008970805,"about_ca_system_score_gemma":0.000026814709,"threshold_uncertainty_score":0.7031573},"labels":[],"label_agreement":null},{"id":"W2492242152","doi":"10.1109/icc.2016.7511328","title":"Joint prioritized link scheduling and resource allocation for OFDMA-based wireless networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University; Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Scheduling (production processes); Mathematical optimization; Greedy algorithm; Resource allocation; Rounding; Job shop scheduling; Wireless network; Frequency-division multiple access; Wireless; Orthogonal frequency-division multiplexing; Computer network; Algorithm; Mathematics; Channel (broadcasting)","score_opus":0.010161249920494296,"score_gpt":0.20632081224475626,"score_spread":0.19615956232426196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2492242152","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":[0.023218906,0.00037677048,0.97449034,0.00071578275,0.00012460415,0.0003836624,0.0000029767054,0.00053859584,0.00014832983],"genre_scores_gemma":[0.8982016,0.00031665643,0.10068773,0.0001033001,0.00033643402,0.0001308691,0.000020420215,0.00007013068,0.00013286676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999208,0.000015539094,0.0002394713,0.0002034869,0.00007912677,0.00025438346],"domain_scores_gemma":[0.99946105,0.00018711753,0.000043832875,0.00016485335,0.000068937974,0.0000742051],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001374397,0.00014937652,0.00017181368,0.000059166174,0.000070639355,0.000027028136,0.000059126567,0.00012045648,0.000013243971],"category_scores_gemma":[0.000031722837,0.00012015053,0.000035610577,0.000116504074,0.00003137423,0.00013974126,0.000015045959,0.00006652183,0.0000016919887],"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":[0.000021808868,0.0000040509467,0.000069368725,0.000037355785,0.0000115991015,2.0349418e-7,0.000010879692,0.8740047,0.0062018842,0.00089553796,0.00011162025,0.11863095],"study_design_scores_gemma":[0.0011649781,0.000019453162,0.000112847774,0.00017771462,0.00001319088,5.722566e-7,0.000008662485,0.991263,0.0055970154,0.00012472937,0.0013216296,0.00019624378],"about_ca_topic_score_codex":9.456016e-7,"about_ca_topic_score_gemma":0.0000038786243,"teacher_disagreement_score":0.8749827,"about_ca_system_score_codex":0.00006087748,"about_ca_system_score_gemma":0.0000108160775,"threshold_uncertainty_score":0.48995966},"labels":[],"label_agreement":null},{"id":"W2493324792","doi":"10.1007/s12083-016-0498-4","title":"Optimizing broadcast duration for layered video streams in cellular networks","year":2016,"lang":"en","type":"article","venue":"Peer-to-Peer Networking and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Science Foundation of Heilongjiang Province; National Natural Science Foundation of China","keywords":"Computer science; Transmission (telecommunications); Optimization problem; Cellular network; Telecommunications link; Minification; Computer network; Base station; Real-time computing; Video quality; Signal-to-noise ratio (imaging); Layer (electronics); Mathematical optimization; Algorithm; Telecommunications; Mathematics; Engineering; Metric (unit)","score_opus":0.010317398202840401,"score_gpt":0.23297960006696555,"score_spread":0.22266220186412516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2493324792","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":[0.0036346049,0.00047537268,0.99221545,0.0013173012,0.0002521855,0.0012927165,0.000025436855,0.0003613332,0.00042559797],"genre_scores_gemma":[0.94247514,0.00021858932,0.053318508,0.00011299118,0.0012849249,0.0018350707,0.00012839376,0.00010021617,0.00052615744],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998345,0.000020785626,0.00044560072,0.00045297903,0.00020620601,0.00052938325],"domain_scores_gemma":[0.9989602,0.00024341184,0.00006733753,0.00034553217,0.00017785277,0.00020566398],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003167072,0.00025861463,0.00025321715,0.00016456204,0.00019106023,0.00008777964,0.00017646984,0.00013882796,0.0000065916693],"category_scores_gemma":[0.000033406355,0.0002478044,0.000046763937,0.0006591428,0.000025452173,0.00016324125,0.000053739757,0.00012944541,0.000014670788],"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":[0.000013527182,0.000013393446,0.00022158293,0.00001123026,0.000011502015,3.872988e-7,0.00012617983,0.80137926,0.0014906748,0.00053672213,0.0018084232,0.19438714],"study_design_scores_gemma":[0.00060633884,0.00003141808,0.00017366749,0.0001663913,0.000017669296,0.0000022356642,0.000050574123,0.82566994,0.0006586421,0.00049141963,0.17169996,0.0004317431],"about_ca_topic_score_codex":0.00000639162,"about_ca_topic_score_gemma":0.00004779998,"teacher_disagreement_score":0.93889695,"about_ca_system_score_codex":0.00013117545,"about_ca_system_score_gemma":0.000010729703,"threshold_uncertainty_score":0.99999744},"labels":[],"label_agreement":null},{"id":"W2502360706","doi":"10.4018/978-1-59904-820-8.ch017","title":"Cross-Layer Radio Resource Management Protocols for QoS Provisioning in Multimedia Wireless Networks","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Guelph","funders":"","keywords":"Computer network; Computer science; Quality of service; Provisioning; Scheduling (production processes); Wireless network; Network packet; Wireless; Radio resource management; Multimedia; Protocol stack; Distributed computing; Wireless sensor network; Telecommunications; Engineering","score_opus":0.013316151822071253,"score_gpt":0.2656554248961751,"score_spread":0.25233927307410386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2502360706","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000036124813,0.00033281528,0.20947824,0.0000074066747,0.0004171724,0.032974277,0.00006009485,0.00087281485,0.75582105],"genre_scores_gemma":[0.11511798,0.00025993903,0.35188702,0.0013282559,0.01213849,0.11255084,0.000951597,0.0034940992,0.40227178],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99728453,0.000015762525,0.0008333131,0.00071880623,0.00036937706,0.00077822374],"domain_scores_gemma":[0.9988272,0.000064608554,0.00022825568,0.000631146,0.00008310665,0.00016568486],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018398701,0.0007543933,0.0007210282,0.0001489511,0.00011171676,0.0001557551,0.00045227684,0.00073199597,0.000010557782],"category_scores_gemma":[0.00000769846,0.0008544017,0.00020205815,0.00006166496,0.00007167514,0.00011054448,0.000108640146,0.00053426303,0.000014434263],"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":[0.00012960561,0.000010542937,0.000025074476,0.00021637157,0.000068161986,0.000056444387,0.000030584055,0.7601869,0.0000025225984,0.082270294,0.00090879353,0.15609471],"study_design_scores_gemma":[0.0029445884,0.00013121756,0.00010975254,0.002970985,0.00006820051,0.000014069859,0.00000800247,0.8707342,0.000036392816,0.010883492,0.110662274,0.0014367821],"about_ca_topic_score_codex":0.0000026932,"about_ca_topic_score_gemma":0.000024983598,"teacher_disagreement_score":0.35354927,"about_ca_system_score_codex":0.00081116013,"about_ca_system_score_gemma":0.000031935575,"threshold_uncertainty_score":0.99939066},"labels":[],"label_agreement":null},{"id":"W2504567701","doi":"10.4018/978-1-59904-002-8.ch016","title":"Business and Technology Issues in Wireless Networking","year":2007,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"WiMAX; Computer science; Telecommunications; Wireless; Computer network; Metropolitan area; Quality of service; IEEE 802.11u; Wireless network; IEEE 802.11","score_opus":0.010695657851598688,"score_gpt":0.2302737641128788,"score_spread":0.21957810626128013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2504567701","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00072607957,0.0073533207,0.01741235,0.000033041644,0.0008476646,0.0003878764,0.000014814778,0.0009380561,0.9722868],"genre_scores_gemma":[0.9505642,0.0037536274,0.013947223,0.00020088295,0.0026907963,0.000067380504,0.000050881248,0.0006768234,0.028048182],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99866784,0.0000041078224,0.00038386058,0.00035838256,0.00015811049,0.00042768006],"domain_scores_gemma":[0.99945015,0.000022212655,0.00008576725,0.00029117466,0.00008701154,0.00006369814],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006568424,0.00043534802,0.0005015921,0.0002484677,0.000040654904,0.00003255994,0.00017393145,0.00082391204,0.0000048810607],"category_scores_gemma":[0.0000042567744,0.0005217285,0.000029549969,0.00013475005,0.000117870666,0.000052384734,0.00010280839,0.0004128245,0.000012715957],"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":[0.000016124355,0.0000032407759,0.0002897505,0.00012525564,0.00005120592,0.00017987216,0.000021961065,0.051484402,0.000017228562,0.81417876,0.00031672345,0.13331549],"study_design_scores_gemma":[0.0022685074,0.000094829054,0.00038855593,0.0062175514,0.00017316166,0.00036649063,0.000047412646,0.101782545,0.00020948524,0.69881684,0.18508342,0.0045512044],"about_ca_topic_score_codex":0.000013359967,"about_ca_topic_score_gemma":0.0003532453,"teacher_disagreement_score":0.9498381,"about_ca_system_score_codex":0.00026572662,"about_ca_system_score_gemma":0.000023102184,"threshold_uncertainty_score":0.99972343},"labels":[],"label_agreement":null},{"id":"W2505915706","doi":"10.4018/978-1-4666-0960-0.ch001","title":"Cross-Layer Adaptive Packet Scheduling over Fading Channel","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Fading; Cross-layer optimization; Physical layer; Network packet; Quality of service; Scheduling (production processes); Link adaptation; Computer network; Wireless; Channel (broadcasting); Transmission (telecommunications); Throughput; Wireless network; Engineering; Telecommunications","score_opus":0.022427901009562434,"score_gpt":0.25131684261676035,"score_spread":0.22888894160719792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2505915706","genre_codex":"other","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":[0.00042997644,0.0027316788,0.110963024,0.0000022996821,0.0014527407,0.00041138695,0.0001790504,0.0008813117,0.8829485],"genre_scores_gemma":[0.96777177,0.00011002511,0.00823908,0.00011915524,0.0021258006,0.00004142885,0.00004087904,0.0003907527,0.02116113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99797237,0.000009303787,0.00046967136,0.00045722685,0.0003623482,0.0007290648],"domain_scores_gemma":[0.99896395,0.00003925773,0.00017708403,0.0004649547,0.00011358863,0.00024118104],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008760469,0.00072585634,0.0005675886,0.00009246224,0.00012748914,0.00009485733,0.00026276644,0.0007597285,0.00012770119],"category_scores_gemma":[0.0000096630065,0.0008379243,0.00021521808,0.000034042052,0.000090330715,0.00023408471,0.0001322983,0.0005817021,0.00026081142],"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":[0.00002867722,0.000003596633,0.000025120118,0.0000574883,0.00018268869,0.000022310674,0.00008228943,0.5589718,0.00003001497,0.43501848,0.0002481085,0.0053293956],"study_design_scores_gemma":[0.003083029,0.00018631433,0.00026290756,0.0033087004,0.0006519694,0.00016080245,0.000057267967,0.61278707,0.0011489376,0.327045,0.04385895,0.007449054],"about_ca_topic_score_codex":0.000005901171,"about_ca_topic_score_gemma":0.000014232728,"teacher_disagreement_score":0.9673418,"about_ca_system_score_codex":0.00067384884,"about_ca_system_score_gemma":0.000037985767,"threshold_uncertainty_score":0.9994072},"labels":[],"label_agreement":null},{"id":"W2506127450","doi":"10.1109/icupc.1996.562657","title":"Non-uniform polling and reservation alternatives for bandwidth management in broadband wireless networks","year":2002,"lang":"en","type":"article","venue":"Proceedings of ICUPC - 5th International Conference on Universal Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Polling; Computer network; Computer science; Quality of service; Bandwidth (computing); Reservation; Wireless broadband; Base station; Bandwidth allocation; Broadband networks; Time division multiple access; Wireless; Channel (broadcasting); Polling system; Wireless network; Broadband; Telecommunications","score_opus":0.05129534470276267,"score_gpt":0.28174673385896704,"score_spread":0.23045138915620436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2506127450","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":[0.54546326,0.0007459055,0.19742115,0.0033449864,0.00046157837,0.0021875664,0.00014342312,0.00035682405,0.24987529],"genre_scores_gemma":[0.97916013,0.0063178507,0.0140328305,0.000033257016,0.00004094738,0.00005859014,0.00005906167,0.000025997697,0.0002713645],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990949,0.0000050904737,0.0002960882,0.000206471,0.00020655809,0.00019090569],"domain_scores_gemma":[0.9992583,0.00008135954,0.00013766455,0.0001272208,0.00034061787,0.00005485061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012596678,0.00017392352,0.00018006883,0.000324763,0.000116139534,0.00006445933,0.0005606353,0.00007306028,0.000033591303],"category_scores_gemma":[0.000014172644,0.00019925897,0.00004172604,0.0002583285,0.00012391312,0.0005941804,0.000119688935,0.00022499076,0.0000011503673],"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":[0.00030456117,0.0003362277,0.00594014,0.00025117924,0.00040669,0.0000017926425,0.0049318727,0.11339745,0.0021857356,0.83909506,0.0007157077,0.03243359],"study_design_scores_gemma":[0.00087052485,0.000056796765,0.0012918868,0.00026564277,0.000015675334,0.0000014838439,0.0014287912,0.9941706,0.00018182036,0.0010950412,0.00043917907,0.00018253247],"about_ca_topic_score_codex":0.00001117187,"about_ca_topic_score_gemma":0.000021479747,"teacher_disagreement_score":0.8807732,"about_ca_system_score_codex":0.00016318526,"about_ca_system_score_gemma":0.000005646171,"threshold_uncertainty_score":0.8125545},"labels":[],"label_agreement":null},{"id":"W2509323143","doi":"10.1109/lwc.2016.2601609","title":"Analytical Approximation of Packet Delay Jitter in Simple Queues","year":2016,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":22,"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":"","keywords":"Jitter; Computer science; Network packet; Queueing theory; Quality of service; Computer network; Processing delay; Scheduling (production processes); Real-time computing; Queue; Transmission delay; Packet analyzer; Mathematical optimization; Mathematics; Telecommunications","score_opus":0.017660280032283895,"score_gpt":0.24967348994576055,"score_spread":0.23201320991347665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509323143","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":[0.6227403,0.00008483568,0.37452188,0.001885372,0.00006822931,0.00019239286,0.000015080947,0.00016942217,0.00032246046],"genre_scores_gemma":[0.9906856,0.00045640583,0.008509701,0.00015455305,0.000030522675,0.000072127965,0.000039348648,0.000042770786,0.000008965855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989211,0.000102455655,0.00045131185,0.0001467973,0.00014121273,0.0002371326],"domain_scores_gemma":[0.998395,0.00030304358,0.00008479863,0.0011201161,0.000052420775,0.00004461119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014924542,0.00015182512,0.00023273786,0.00020932725,0.0000458421,0.000012851805,0.00052798854,0.0000806635,0.000016552154],"category_scores_gemma":[0.000020195115,0.00013448665,0.000052249816,0.00042730183,0.00018665213,0.00033091896,0.00005922065,0.00015085621,0.00002106597],"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":[0.000029035667,0.00016786868,0.01633974,0.00010119134,0.0001013028,0.0000038448034,0.00081010564,0.77503544,0.13293634,0.005471615,0.0056566503,0.06334684],"study_design_scores_gemma":[0.0007261079,0.000011203202,0.0023985372,0.00019318356,0.000019414783,0.000003790251,0.000053533928,0.98288244,0.011881724,0.00037825646,0.0011011686,0.00035064778],"about_ca_topic_score_codex":0.000013610056,"about_ca_topic_score_gemma":0.000079542086,"teacher_disagreement_score":0.36794525,"about_ca_system_score_codex":0.00015091979,"about_ca_system_score_gemma":0.000010346158,"threshold_uncertainty_score":0.5484206},"labels":[],"label_agreement":null},{"id":"W2513021552","doi":"10.1002/dac.3180","title":"An efficient network‐coding based back‐pressure scheduling algorithm for wireless multi‐hop networks","year":2016,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Memorial University of Newfoundland","funders":"National Natural Science Foundation of China","keywords":"Computer science; Linear network coding; Computer network; Hop (telecommunications); Wireless network; Coding (social sciences); Wireless; Scheduling (production processes); Maximum throughput scheduling; Distributed computing; Algorithm; Round-robin scheduling; Fair-share scheduling; Telecommunications; Quality of service; Mathematical optimization; Network packet","score_opus":0.01701329410286068,"score_gpt":0.2750245534377791,"score_spread":0.2580112593349184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2513021552","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":[0.0019451972,0.0031529134,0.99203485,0.00014464282,0.0022647409,0.00028829506,0.000023784445,0.00008887736,0.000056706624],"genre_scores_gemma":[0.84263307,0.0007017225,0.1555853,0.00003005542,0.00090198324,0.000029822368,0.000032990054,0.00005731766,0.000027731116],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981351,0.00018135278,0.0008895668,0.0001378076,0.00040207946,0.00025409818],"domain_scores_gemma":[0.99704504,0.0005468858,0.0006030847,0.00044361866,0.0012417287,0.00011963132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086927885,0.00019391112,0.0003050341,0.00018069192,0.00010830897,0.00013952787,0.0010459487,0.00013596003,0.000014547812],"category_scores_gemma":[0.000042025895,0.00016110223,0.00012645822,0.00015587501,0.000047226582,0.00045688648,0.00004547351,0.00020935088,0.000004779613],"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":[0.000035440156,0.000047011665,0.00017869215,0.000006445058,0.0001605702,0.0000012674925,0.000052137813,0.9664105,0.00041100007,0.0005671295,0.000186139,0.031943634],"study_design_scores_gemma":[0.0015888754,0.000032362615,0.00007569268,0.0008875496,0.000028611248,0.000019298186,0.00006249869,0.9927774,0.00019314348,0.000018190896,0.0041259616,0.00019042767],"about_ca_topic_score_codex":0.00000310651,"about_ca_topic_score_gemma":0.0000028243367,"teacher_disagreement_score":0.8406879,"about_ca_system_score_codex":0.00021123062,"about_ca_system_score_gemma":0.0000391989,"threshold_uncertainty_score":0.65695584},"labels":[],"label_agreement":null},{"id":"W2520674444","doi":"10.1109/twc.2016.2610430","title":"On Achieving Fair and Throughput-Optimal Scheduling for TCP Flows in Wireless Networks","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":22,"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":"Computer science; Maximum throughput scheduling; Computer network; Round-robin scheduling; Fair-share scheduling; Distributed computing; Dynamic priority scheduling; Transmission Control Protocol; Fair queuing; TCP Friendly Rate Control; Scheduling (production processes); Mathematical optimization; Network packet; Mathematics","score_opus":0.017525207582200983,"score_gpt":0.2522490271077955,"score_spread":0.2347238195255945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2520674444","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":[0.1138438,0.00021706437,0.88376653,0.00061735476,0.00030843954,0.00059981446,0.000045961155,0.00045217143,0.00014883472],"genre_scores_gemma":[0.96009755,0.004235547,0.034775984,0.000065634005,0.000049479717,0.00059012795,0.000018097038,0.00012302095,0.00004454617],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998398,0.000101246485,0.0005092894,0.00037205848,0.00014958098,0.0004698289],"domain_scores_gemma":[0.99716634,0.0013606064,0.00008121406,0.0011988635,0.00007714807,0.0001158119],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019818395,0.00034146427,0.0003695376,0.0002751124,0.00045790197,0.000053056552,0.00053429767,0.00022741404,0.000012257166],"category_scores_gemma":[0.000010525297,0.00032337313,0.00010615443,0.00047754456,0.00015368772,0.0004416428,0.0000099965555,0.00050610054,0.000010582103],"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":[0.000050489994,0.000112727415,0.000024744813,0.00002360068,0.000039796338,4.858596e-7,0.00013833218,0.8810469,0.0015793373,0.0022940654,0.000018821092,0.11467072],"study_design_scores_gemma":[0.0012039494,0.00007415737,0.000087194705,0.0005033978,0.000028429746,0.0000040937325,0.00006341687,0.9957278,0.0015463717,0.00016832979,0.00019179613,0.0004010869],"about_ca_topic_score_codex":0.000009174799,"about_ca_topic_score_gemma":0.00035473917,"teacher_disagreement_score":0.84899056,"about_ca_system_score_codex":0.0002442871,"about_ca_system_score_gemma":0.00002476601,"threshold_uncertainty_score":0.99992186},"labels":[],"label_agreement":null},{"id":"W2538129567","doi":"10.7939/r3-szjp-kd85","title":"Admission control of delay bounded traffic in cellular networks","year":2007,"lang":"en","type":"article","venue":"University of Alberta Library","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Scheduling (production processes); Cellular network; Preemption; Wireless network; Distributed computing; Wireless; Engineering; Telecommunications","score_opus":0.002667589580823208,"score_gpt":0.14860318189657118,"score_spread":0.14593559231574796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2538129567","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":[0.67905855,0.00035630798,0.316252,0.000026316806,0.00007284773,0.00011627816,9.627679e-7,0.00006296487,0.0040537985],"genre_scores_gemma":[0.99498767,0.00013211783,0.004498953,0.000009806666,0.00001946586,3.2066538e-8,0.000029841636,0.000018390629,0.00030374463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995177,0.000016732483,0.00015012354,0.000095868025,0.00005698504,0.00016260897],"domain_scores_gemma":[0.9995962,0.00015232291,0.00005363011,0.0001227954,0.000009381208,0.00006569062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042664364,0.000086314416,0.00017211329,0.00012981742,0.000021480862,0.0000025538327,0.00013722913,0.000108967455,0.00013081965],"category_scores_gemma":[0.0000043756036,0.00011042809,0.000045129575,0.00027923423,0.00004212772,0.0004010358,0.000022348753,0.000105007544,0.0000015603293],"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":[0.000118125325,0.000026261354,0.0023985321,0.000023821676,0.00001626331,0.000016250446,0.0004465203,0.9943515,0.00023049249,0.0003831881,0.0002563655,0.0017326478],"study_design_scores_gemma":[0.0011040448,0.000031105952,0.0012685208,0.000079245954,0.000013438556,8.800699e-7,0.0001848398,0.9937152,0.0013076587,0.000039725,0.0021219107,0.00013338756],"about_ca_topic_score_codex":0.000027808224,"about_ca_topic_score_gemma":0.000100641824,"teacher_disagreement_score":0.3159291,"about_ca_system_score_codex":0.000020474225,"about_ca_system_score_gemma":0.00001535916,"threshold_uncertainty_score":0.45031267},"labels":[],"label_agreement":null},{"id":"W2540444818","doi":"10.1109/itict.2007.4475652","title":"Minimizing average waiting time in video-on-demand broadcasting","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"Microsoft","keywords":"Upper and lower bounds; Computer science; Bandwidth (computing); Combinatorics; Video on demand; Broadcasting (networking); Discrete mathematics; Algorithm; Mathematics; Computer network; Mathematical analysis","score_opus":0.005881631395932403,"score_gpt":0.20428241866602084,"score_spread":0.19840078727008845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2540444818","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":[0.36579213,0.00012166099,0.5547575,0.000017414959,0.0001628625,0.0001556152,6.56296e-7,0.00061889976,0.0783733],"genre_scores_gemma":[0.9742005,0.00001956082,0.025159733,0.00006496997,0.00016077439,0.0000034806726,0.000006699411,0.000050883973,0.0003334316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900883,0.000010916217,0.00030551068,0.00016936741,0.000115694726,0.00038968876],"domain_scores_gemma":[0.99950546,0.00027114796,0.000030299996,0.00012082958,0.000015502937,0.00005674558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029660418,0.00014535766,0.00014836901,0.0001554118,0.000046272093,0.000021537115,0.00007233946,0.00007308623,0.000095505064],"category_scores_gemma":[0.00005702135,0.00015899581,0.000025419213,0.00030276872,0.00001021694,0.0001718483,0.00002155118,0.00017879887,0.00008407105],"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":[0.000006793646,0.0000061981273,0.0003433445,0.000013897622,0.0000042607994,0.000022564549,0.00014453944,0.9775725,0.003376281,0.00013451121,0.00011735281,0.018257758],"study_design_scores_gemma":[0.0003068645,0.000009853452,0.00037475192,0.000106232605,0.0000016651999,0.0000049835826,0.000044453576,0.9926821,0.005967337,0.000055753608,0.00025456375,0.00019145326],"about_ca_topic_score_codex":0.0000025228444,"about_ca_topic_score_gemma":0.000009798274,"teacher_disagreement_score":0.60840833,"about_ca_system_score_codex":0.00010379137,"about_ca_system_score_gemma":0.0000034410305,"threshold_uncertainty_score":0.6483661},"labels":[],"label_agreement":null},{"id":"W2546279284","doi":"10.1109/icics.2007.4449746","title":"Threshold-based power allocation algorithms for down-link switched-based parallel scheduling","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Scheduling (production processes); Bit error rate; Spectral efficiency; Algorithm; Power (physics); Signal-to-noise ratio (imaging); Real-time computing; Mathematical optimization; Computer network; Telecommunications; Mathematics; Decoding methods","score_opus":0.015972295297124857,"score_gpt":0.2579269887120958,"score_spread":0.24195469341497094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2546279284","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":[0.00522344,0.00020445761,0.9909635,0.00026065548,0.0003963269,0.00059690163,0.000004237699,0.00095296104,0.0013974952],"genre_scores_gemma":[0.5365251,0.0000073388637,0.46281466,0.00022401987,0.00015091801,0.000055849207,0.00011395832,0.000064686734,0.000043464926],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861956,0.000006107367,0.00039367503,0.0002843866,0.0002088419,0.0004874251],"domain_scores_gemma":[0.999175,0.00018053726,0.000060092498,0.00030569374,0.00016054556,0.00011809635],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035553737,0.0002493665,0.00020151782,0.00015464137,0.0000965311,0.00003844448,0.00015467944,0.00018468553,0.00006468869],"category_scores_gemma":[0.00003481183,0.0002589495,0.00009273812,0.0003253192,0.000026498943,0.00019721097,0.000009354899,0.00015348355,0.000022137363],"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":[0.00004353924,0.00002646039,0.000113766495,0.00003688018,0.000018244978,0.0000015388646,0.000021766822,0.9887028,0.002122274,0.00097641547,0.00013940077,0.0077969222],"study_design_scores_gemma":[0.001278282,0.000043752247,0.00014818029,0.00003425514,0.000014783236,5.301306e-7,0.00002670854,0.9776781,0.01916076,0.00027595618,0.0010062233,0.00033243865],"about_ca_topic_score_codex":0.0000026303026,"about_ca_topic_score_gemma":0.000018112603,"teacher_disagreement_score":0.5313017,"about_ca_system_score_codex":0.00015258652,"about_ca_system_score_gemma":0.000038031354,"threshold_uncertainty_score":0.9999863},"labels":[],"label_agreement":null},{"id":"W2546620535","doi":"10.1145/2983635","title":"Mobile Video Streaming over Dynamic Single-Frequency Networks","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Multimedia Computing Communications and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"Qatar National Research Fund","keywords":"Computer science; Computer network; Wireless network; Bandwidth (computing); Quality of service; Overhead (engineering); Multi-frequency network; Wireless; Cellular network; Network packet; Multimedia; Distributed computing; Real-time computing; Heterogeneous network; Telecommunications","score_opus":0.009426253141505187,"score_gpt":0.2443932312650757,"score_spread":0.2349669781235705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2546620535","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":[0.0035932562,0.0011246075,0.99315876,0.00017162912,0.00009754676,0.0006614428,0.00004437461,0.0007876182,0.00036078834],"genre_scores_gemma":[0.81261104,0.0042416034,0.1824108,0.000032780757,0.000048150447,0.0004937374,0.00005172593,0.0000619034,0.000048257414],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875456,0.00005499513,0.00043068794,0.0003221937,0.00011924607,0.0003183168],"domain_scores_gemma":[0.99667966,0.0010280036,0.00009329366,0.0019802204,0.00008541296,0.00013340259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010408395,0.00025304034,0.00020970448,0.00016959228,0.00060066243,0.000051294715,0.00071394094,0.00013175496,0.000029477831],"category_scores_gemma":[0.000012467139,0.0002357907,0.000068750844,0.0005027914,0.00022849563,0.0002197075,0.00004702649,0.00029712004,0.000025070229],"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":[0.0000018366594,0.00011658455,0.000079021906,0.000009024969,0.000036409216,1.2969147e-7,0.000110087974,0.20176727,0.003553004,0.00015671052,0.000014817751,0.7941551],"study_design_scores_gemma":[0.0005091689,0.000049585,0.00035533216,0.00012628055,0.0000437735,0.0000064751634,0.00007152459,0.9930774,0.00024511732,0.00069197064,0.004472816,0.0003505821],"about_ca_topic_score_codex":0.000008213644,"about_ca_topic_score_gemma":0.000043831606,"teacher_disagreement_score":0.8107479,"about_ca_system_score_codex":0.00016831337,"about_ca_system_score_gemma":0.000014114942,"threshold_uncertainty_score":0.96152663},"labels":[],"label_agreement":null},{"id":"W2546895355","doi":"10.1109/tvt.2016.2625326","title":"Head-of-Line Access Delay-Based Scheduling Algorithm for Flow-Level Dynamics","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":9,"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":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Scheduling (production processes); Round-robin scheduling; Dynamic priority scheduling; Fair-share scheduling; Queue; Algorithm; Rate-monotonic scheduling; Real-time computing; Distributed computing; Mathematical optimization; Computer network; Mathematics; Quality of service","score_opus":0.02045145612279852,"score_gpt":0.27381201895442375,"score_spread":0.2533605628316252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2546895355","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":[0.00958119,0.00009924663,0.98785245,0.0003885054,0.00048450846,0.0004063562,0.00024947093,0.00093116524,0.0000070953442],"genre_scores_gemma":[0.59841657,0.000101876845,0.40114513,0.00001945049,0.000023960069,0.00018880026,0.000015052449,0.00006942533,0.000019765906],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891055,0.000012059443,0.00034412285,0.00027671808,0.00012014132,0.00033640378],"domain_scores_gemma":[0.99922824,0.00011586421,0.000063836866,0.00039447378,0.00015023205,0.0000473558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007424371,0.00022621593,0.0002851802,0.0004964165,0.000095726326,0.000009453997,0.0002882807,0.00040210164,0.000015415102],"category_scores_gemma":[0.00000865591,0.00020479319,0.00011995872,0.00060684845,0.00011254092,0.0001692656,0.0000018913786,0.00022126087,0.0000072827747],"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":[0.000009127748,0.000036680714,0.0000029320117,0.000020840647,0.0000389096,0.0000018777287,0.0000019745646,0.6138359,0.0018861201,0.00007733358,0.0000024545634,0.3840859],"study_design_scores_gemma":[0.0009527244,0.000092027716,0.0000013495155,0.000112374066,0.000037395686,0.0000064915284,0.000006813963,0.8432565,0.15468213,0.0004921396,0.00015695737,0.00020312726],"about_ca_topic_score_codex":0.0000019998636,"about_ca_topic_score_gemma":0.00004857841,"teacher_disagreement_score":0.58883536,"about_ca_system_score_codex":0.00020137643,"about_ca_system_score_gemma":0.000033380224,"threshold_uncertainty_score":0.8351224},"labels":[],"label_agreement":null},{"id":"W2560712585","doi":"10.1109/cjece.2016.2538764","title":"Joint Best Price-CQI Product Scheduling and Congestion Control for LTE","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":4,"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; Maximum throughput scheduling; Scheduling (production processes); Network congestion; Computer network; Wireless network; Round-robin scheduling; Mathematical optimization; Fair-share scheduling; Proportionally fair; Dynamic priority scheduling; Wireless; Distributed computing; Quality of service; Network packet; Mathematics; Telecommunications","score_opus":0.005804388674438607,"score_gpt":0.16257319005346416,"score_spread":0.15676880137902555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2560712585","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":[0.07275022,0.002782652,0.9238949,0.00016993654,0.0002621651,0.00010914657,0.0000025196475,0.000023666717,0.0000048005154],"genre_scores_gemma":[0.97479343,0.00020052075,0.024445303,0.000020721543,0.0005061493,0.0000042764887,4.775821e-7,0.000023101711,0.000006039714],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937814,0.0000058820606,0.00021504957,0.00009445694,0.000047849215,0.0002585994],"domain_scores_gemma":[0.9994171,0.000103833365,0.00004019389,0.00004603599,0.00008772752,0.0003051068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009211013,0.00011245746,0.00018487909,0.00017617663,0.0000408621,0.00003696785,0.000046536225,0.0000424885,0.0000014437711],"category_scores_gemma":[0.00006336045,0.000090464324,0.000028150287,0.00010850375,0.000014149339,0.00016275985,0.0000032988798,0.00011216833,3.099635e-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":[0.0000069672674,0.000002699657,0.00043884752,0.000038185182,0.000047053218,0.00001105013,0.000025298004,0.9169799,0.0023330392,0.0007857561,0.000075392425,0.07925579],"study_design_scores_gemma":[0.00072757335,0.00014098744,0.0015005601,0.00016770902,0.000021227499,0.00014213427,8.420383e-7,0.99497896,0.00046864958,0.0000991316,0.0015932986,0.00015894765],"about_ca_topic_score_codex":0.000005236165,"about_ca_topic_score_gemma":0.000021880911,"teacher_disagreement_score":0.90204316,"about_ca_system_score_codex":0.00008783335,"about_ca_system_score_gemma":0.00004545542,"threshold_uncertainty_score":0.3689028},"labels":[],"label_agreement":null},{"id":"W2575067796","doi":"10.1109/indin.2016.7819347","title":"The role of queueing theory in the design and analysis of wireless sensor networks: An insight","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Queueing theory; Computer science; Wireless sensor network; Scheduling (production processes); Queue; Computer network; Stochastic geometry models of wireless networks; Layered queueing network; Reliability (semiconductor); Distributed computing; Network congestion; Routing (electronic design automation); Wireless network; Wireless; Power (physics); Routing protocol; Mathematical optimization; Network packet; Telecommunications","score_opus":0.005341670056860603,"score_gpt":0.19646755098971422,"score_spread":0.19112588093285363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2575067796","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":[0.11960277,0.0008435628,0.87893194,0.000014651823,0.000016886155,0.00012248248,8.417045e-7,0.00003092322,0.00043594005],"genre_scores_gemma":[0.99495345,0.0011046102,0.0038770877,0.0000092118225,0.00001618249,0.000009760406,0.0000014282241,0.000014196666,0.000014073702],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925226,0.00021076134,0.0002242768,0.00009265382,0.00008648477,0.00013357036],"domain_scores_gemma":[0.99858177,0.0010715656,0.00005353561,0.00024427095,0.000031072213,0.000017790027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050478685,0.00008548095,0.0001684978,0.000089624154,0.000036011737,0.000010046169,0.00013383247,0.00004524521,0.0000068077393],"category_scores_gemma":[0.000018253224,0.00003969004,0.000029921988,0.00057319156,0.00007265548,0.00013367378,0.000015010539,0.00005036026,1.4069917e-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":[0.00001909437,0.00000671923,0.0017417818,0.0000022806246,0.000090771,2.9281253e-7,0.0004338691,0.93301797,0.0018198988,0.009040162,0.0000021157625,0.05382503],"study_design_scores_gemma":[0.00010747168,0.000013877162,0.002268349,0.000018530349,0.00006499581,3.5577673e-7,0.000454975,0.993546,0.0025110967,0.0009105087,0.000039662256,0.000064151696],"about_ca_topic_score_codex":0.000007167372,"about_ca_topic_score_gemma":0.000069067355,"teacher_disagreement_score":0.87535065,"about_ca_system_score_codex":0.00001327738,"about_ca_system_score_gemma":0.0000039644415,"threshold_uncertainty_score":0.16185129},"labels":[],"label_agreement":null},{"id":"W2577045917","doi":"10.1109/tvt.2017.2655011","title":"Delay-Aware Load Balancing Over Multipath Wireless Networks","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Computer science; Computer network; End-to-end delay; Network packet; Transmission delay; Real-time computing; Traffic generation model; Processing delay; Network delay; Telecommunications link; Multipath propagation; Wireless network; Wireless; Channel (broadcasting); Telecommunications","score_opus":0.005849736114490459,"score_gpt":0.2181252117010734,"score_spread":0.21227547558658294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2577045917","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":[0.137677,0.00020513109,0.859209,0.000085579384,0.0009712771,0.00024130176,0.000010715472,0.0014711269,0.00012885273],"genre_scores_gemma":[0.9960917,0.0005495138,0.002946653,0.000036415433,0.000077700526,0.00012192673,0.000004841527,0.00010494164,0.00006630202],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99862146,0.000016368414,0.00028214612,0.00037679292,0.00019880182,0.0005044439],"domain_scores_gemma":[0.9986261,0.00003343528,0.0000962781,0.0010729026,0.0000925711,0.00007869178],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008173654,0.00031302648,0.00031646132,0.00021936136,0.0005918195,0.00006214169,0.0004795431,0.00059263443,0.000032429325],"category_scores_gemma":[0.0000060756784,0.0003483233,0.00010980839,0.00025480974,0.00016995097,0.00028778543,0.0000049578734,0.0007828015,0.00004054562],"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":[0.000012103404,0.00003472148,0.00015310809,0.000015140316,0.00006476555,0.000046769044,0.000017531669,0.9310736,0.0013067211,0.00009063125,0.000043935845,0.067140974],"study_design_scores_gemma":[0.00067503116,0.00004071626,0.00010353474,0.00009566934,0.000038585087,0.000034170174,0.0000278921,0.98302305,0.014889314,0.000080817576,0.0006293823,0.00036184263],"about_ca_topic_score_codex":0.000016979306,"about_ca_topic_score_gemma":0.000110872395,"teacher_disagreement_score":0.8584147,"about_ca_system_score_codex":0.0002747858,"about_ca_system_score_gemma":0.000022244585,"threshold_uncertainty_score":0.9998969},"labels":[],"label_agreement":null},{"id":"W2583199091","doi":"10.1109/glocom.2016.7841836","title":"Fair Robust Predictive Resource Allocation for Video Streaming under Rate Uncertainties","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Royal Military College of Canada; Queen's University","funders":"","keywords":"Computer science; Probabilistic logic; Quality of service; Resource allocation; Mathematical optimization; Benchmark (surveying); Convex optimization; Robustness (evolution); Constraint (computer-aided design); Video quality; Regular polygon; Metric (unit); Computer network; Artificial intelligence; Mathematics","score_opus":0.011411263328210202,"score_gpt":0.2066760079170959,"score_spread":0.19526474458888568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2583199091","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":[0.0040313876,0.000061344006,0.992707,0.00021097827,0.00012317488,0.00028238568,0.000010001381,0.0005857644,0.0019879777],"genre_scores_gemma":[0.97546303,0.000055496323,0.022507636,0.00006572824,0.0001566008,0.00010982182,0.000029823848,0.00005636662,0.0015554845],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937093,0.000015938773,0.00016154713,0.00016938885,0.000070563845,0.00021164147],"domain_scores_gemma":[0.9994552,0.00024514864,0.00003344531,0.00015443069,0.00007200737,0.000039764782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008548334,0.00012626313,0.0001032831,0.000054480828,0.00006165341,0.000017539858,0.00007483395,0.00005526154,0.00002992098],"category_scores_gemma":[0.00004246718,0.00009565154,0.000029988361,0.00010881486,0.000029847888,0.00029340954,0.000015312658,0.000036876303,0.000007434495],"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":[0.000020983143,0.000004049444,0.00004395868,0.000015066824,0.000026098516,1.2001102e-7,0.00005565638,0.98605376,0.0016863478,0.0026257636,0.0020443245,0.007423872],"study_design_scores_gemma":[0.000484113,0.000035318542,0.00026856558,0.00007788001,0.000014190669,5.89794e-7,0.0003305246,0.9868016,0.0067721787,0.0015120646,0.003517545,0.00018541666],"about_ca_topic_score_codex":0.0000029573616,"about_ca_topic_score_gemma":0.000022855102,"teacher_disagreement_score":0.9714317,"about_ca_system_score_codex":0.00015772734,"about_ca_system_score_gemma":0.000010160467,"threshold_uncertainty_score":0.39005566},"labels":[],"label_agreement":null},{"id":"W2586049136","doi":"10.1109/glocomw.2016.7848965","title":"Multi-Flow Carrier Aggregation in Heterogeneous Networks: Cross-Layer Performance Analysis","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Computer science; Queueing theory; Scheduling (production processes); Network packet; Quality of service; Computer network; Fair queuing; Queuing delay; End-to-end delay; Distributed computing; Real-time computing; Round-robin scheduling; Dynamic priority scheduling; Engineering","score_opus":0.009652938985308631,"score_gpt":0.23294851763369248,"score_spread":0.22329557864838384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586049136","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":[0.32656097,0.00023878198,0.6726553,0.0000063166685,0.00012696418,0.00006906816,0.000004264958,0.00019511378,0.00014325863],"genre_scores_gemma":[0.97005326,0.0009183914,0.028306387,0.00002368591,0.000068472444,0.000026616844,0.000020700822,0.00003663951,0.00054586015],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990842,0.000017928365,0.00027439903,0.00021960233,0.00010512424,0.00029877012],"domain_scores_gemma":[0.99954355,0.000040473595,0.000033568933,0.00026190447,0.000062136394,0.00005837731],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006936073,0.00015383065,0.00018336675,0.00015184606,0.0000381916,0.000026348802,0.00008632826,0.00010671398,0.00015808523],"category_scores_gemma":[0.000013659091,0.00012254738,0.00006559367,0.00076963607,0.000025758305,0.00035020703,0.000021578568,0.000070099326,0.000022406715],"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":[0.000006424194,0.0000068327945,0.066481896,0.0000052751907,0.00006202984,0.000003983948,0.000021181848,0.8903791,0.0002003881,0.000002481234,0.000013571067,0.04281685],"study_design_scores_gemma":[0.0004535679,0.0000057206444,0.015917175,0.000020198842,0.000027321274,0.0000021335545,0.0000023633784,0.98032373,0.0029034268,0.00000454457,0.00015208795,0.00018770086],"about_ca_topic_score_codex":0.000003419669,"about_ca_topic_score_gemma":0.00025371872,"teacher_disagreement_score":0.64434886,"about_ca_system_score_codex":0.00014465203,"about_ca_system_score_gemma":0.0000066396883,"threshold_uncertainty_score":0.49973372},"labels":[],"label_agreement":null},{"id":"W2594405368","doi":"10.1109/tmm.2017.2678198","title":"Cross-Layer Resource Allocation for Scalable Video Over OFDMA Wireless Networks: Tradeoff Between Quality Fairness and Efficiency","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":21,"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":"Computer science; Scalability; Video quality; Mathematical optimization; Resource allocation; Wireless; Fairness measure; Quality (philosophy); Spectral efficiency; Optimization problem; Computer network; Throughput; Channel (broadcasting); Algorithm; Metric (unit); Mathematics; Telecommunications","score_opus":0.026386789740327706,"score_gpt":0.3031946810506294,"score_spread":0.2768078913103017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594405368","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":[0.21020573,0.00009660843,0.7880615,0.00007335678,0.00056072,0.00053827604,0.00008857391,0.00029098828,0.00008424785],"genre_scores_gemma":[0.9940491,0.00019995467,0.004827634,0.000022272512,0.00030229246,0.0002528185,0.000034913213,0.00009548612,0.00021557008],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838287,0.000044765875,0.0004479875,0.00044114527,0.00023330904,0.00044990293],"domain_scores_gemma":[0.9985406,0.00047149058,0.00014886244,0.00058666576,0.000084684034,0.00016774333],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00031276324,0.00030421137,0.00035499767,0.00010308617,0.00076586544,0.00020201899,0.00029127553,0.00028063747,0.000031481886],"category_scores_gemma":[0.00002131908,0.00033083506,0.00010247538,0.00012927332,0.00020882396,0.00060452253,0.0000029345927,0.00031741787,0.00000608002],"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":[0.00005383185,0.000048312002,0.0010072677,0.00006954954,0.000047058216,3.8350063e-7,0.00017451815,0.8654316,0.0007847873,0.00000859878,0.00005151093,0.13232258],"study_design_scores_gemma":[0.001500426,0.000036073165,0.021181598,0.0000881301,0.0000615502,7.1746405e-7,0.00002244463,0.9639968,0.012373643,0.000023291712,0.00033541245,0.0003798657],"about_ca_topic_score_codex":0.0000483851,"about_ca_topic_score_gemma":0.00006481946,"teacher_disagreement_score":0.78384334,"about_ca_system_score_codex":0.00010823675,"about_ca_system_score_gemma":0.000016929243,"threshold_uncertainty_score":0.99991435},"labels":[],"label_agreement":null},{"id":"W2608144973","doi":"10.1109/tvt.2017.2696078","title":"User Behavior-Aware Scheduling Based on Time–Frequency Resource Conversion","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":17,"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; National Natural Science Foundation of China","keywords":"Computer science; Provisioning; Scheduling (production processes); Computer network; Quality of service; Dynamic priority scheduling; Distributed computing; Real-time computing; Mathematical optimization","score_opus":0.006844954386680242,"score_gpt":0.2171646616296529,"score_spread":0.21031970724297266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608144973","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":[0.10215574,0.000034609504,0.89485985,0.0003438033,0.000347976,0.0003336267,0.000018231061,0.0015292726,0.00037690293],"genre_scores_gemma":[0.989434,0.000039368533,0.01008393,0.0000595098,0.000030056664,0.00012392542,0.000013360064,0.00009019567,0.00012565046],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885947,0.000022066883,0.00022124113,0.00035677696,0.00019397543,0.0003464712],"domain_scores_gemma":[0.998664,0.000037562113,0.00007979781,0.0010902614,0.000060944112,0.00006738421],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007128015,0.0002646512,0.00023594433,0.00042351818,0.00057423493,0.000043362597,0.0004272673,0.00051544287,0.00011183606],"category_scores_gemma":[0.000009038079,0.00029787526,0.00010099061,0.00023435312,0.00016353354,0.00018284692,0.000002578449,0.00067183265,0.00021631812],"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":[0.000015332073,0.00006976097,0.00008845506,0.00001564312,0.000020716428,0.000039222396,0.0000058666137,0.9816975,0.0076872325,0.00003760506,0.00003869031,0.010283998],"study_design_scores_gemma":[0.0007421712,0.00012764896,0.000073511415,0.00012950972,0.000061138075,0.000011015536,0.000018117255,0.8733334,0.124169916,0.00004386889,0.0009485911,0.00034111468],"about_ca_topic_score_codex":0.0000041240373,"about_ca_topic_score_gemma":0.00000491223,"teacher_disagreement_score":0.88727826,"about_ca_system_score_codex":0.00018173302,"about_ca_system_score_gemma":0.000018052328,"threshold_uncertainty_score":0.9999473},"labels":[],"label_agreement":null},{"id":"W2610512993","doi":"10.1017/9781316212493.011","title":"Sub-Carrier/Sub-Channel Allocation in OFDMA Networks","year":2017,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 du Québec à Montréal; University of Manitoba","funders":"","keywords":"Orthogonal frequency-division multiplexing; Fading; Wireless broadband; Narrowband; Computer science; Channel (broadcasting); Electronic engineering; Transmission (telecommunications); Digital broadcasting; Computer network; Wireless; Digital television; Digital Video Broadcasting; Telecommunications; Broadband; Wireless network; Engineering","score_opus":0.012280578478633088,"score_gpt":0.17923977611043726,"score_spread":0.16695919763180417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610512993","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000284931,0.0009477177,0.09210982,0.000008563179,0.0008297615,0.00066469866,0.00014280631,0.00051763543,0.90449405],"genre_scores_gemma":[0.055147417,0.0062818956,0.00017772098,0.00003601153,0.0005668063,0.000008809059,0.00039904861,0.00029678506,0.9370855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986139,0.000022823158,0.00026621603,0.00048059874,0.00020292406,0.00041357227],"domain_scores_gemma":[0.99871784,0.000046196397,0.00022377264,0.00072897243,0.00012689218,0.00015629944],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008105363,0.0005024084,0.00049175246,0.00025962002,0.00017776822,0.000055472607,0.00053498213,0.00068875315,0.0000016569816],"category_scores_gemma":[0.000007408002,0.0007106585,0.00014034436,0.000011508646,0.00014245008,0.0002485404,0.00019554964,0.00072141486,0.0000055588744],"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":[0.00005959768,0.0000061538344,0.000004257983,0.00012885954,0.00013224763,0.00017925227,0.000044446213,0.8896107,0.000089173525,0.092409536,0.011469906,0.0058658705],"study_design_scores_gemma":[0.0013660194,0.000032985234,0.0000722232,0.0010024139,0.00023468884,0.000010733762,0.000014095728,0.6548638,0.001116387,0.00003431713,0.339643,0.0016093721],"about_ca_topic_score_codex":0.00002936741,"about_ca_topic_score_gemma":0.000028866507,"teacher_disagreement_score":0.3281731,"about_ca_system_score_codex":0.00044731976,"about_ca_system_score_gemma":0.000040852698,"threshold_uncertainty_score":0.9995344},"labels":[],"label_agreement":null},{"id":"W2612239633","doi":"10.1007/978-3-319-57693-0_3","title":"Joint Data Admission Control and Power Allocation Over Fading Channel Under Average Delay Constraint","year":2017,"lang":"en","type":"book-chapter","venue":"Springer briefs in electrical and computer engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Fading; Computer science; Queue; Constraint (computer-aided design); Channel (broadcasting); Power control; Transmission (telecommunications); Quality of service; Admission control; Computer network; Throughput; Network packet; Real-time computing; Power (physics); Wireless; Telecommunications; Mathematics","score_opus":0.011985304813736233,"score_gpt":0.20301113817579247,"score_spread":0.19102583336205625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612239633","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":[0.0006883275,0.0034723193,0.9929125,0.000041820927,0.0004351883,0.00034894457,0.00001737691,0.00028463593,0.0017989082],"genre_scores_gemma":[0.9888883,0.0023631414,0.0070496975,0.000108165885,0.0005165412,0.000015009057,0.00008898259,0.00019799716,0.0007721655],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983296,0.000008371116,0.00042731696,0.00060621777,0.00019754947,0.00043097895],"domain_scores_gemma":[0.99905884,0.00008964331,0.0000987482,0.00053637236,0.000033152122,0.00018323946],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001591411,0.0004878637,0.0005407445,0.0002623986,0.00008026399,0.00013277969,0.00026195953,0.00035878783,0.000012783772],"category_scores_gemma":[0.00001779557,0.00053689705,0.000045676694,0.00003947955,0.000044377295,0.0002940495,0.00023737148,0.0007370818,0.0000024858853],"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":[0.000011500849,0.00000891251,0.000012883938,0.00010496513,0.00011270015,0.00005323717,0.000048681806,0.96319765,0.000201227,0.0096371295,0.00010900487,0.026502114],"study_design_scores_gemma":[0.0006625801,0.000035165805,0.00060266623,0.0005104966,0.00002852503,0.000051921248,3.3627032e-7,0.9926863,0.0000241755,0.00064904353,0.004165679,0.000583145],"about_ca_topic_score_codex":0.000004341687,"about_ca_topic_score_gemma":0.0000033596884,"teacher_disagreement_score":0.98819995,"about_ca_system_score_codex":0.00015126663,"about_ca_system_score_gemma":0.000023006136,"threshold_uncertainty_score":0.99970824},"labels":[],"label_agreement":null},{"id":"W2612748665","doi":"","title":"Average probability of packet error with diversity reception over arbitrarily correlated fading channels: Research Articles","year":2004,"lang":"en","type":"article","venue":"Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":3,"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":"Fading; Nakagami distribution; Maximal-ratio combining; Diversity scheme; Rician fading; Diversity combining; Rayleigh fading; Mathematics; Time diversity; Fading distribution; Statistics; Diversity gain; Antenna diversity; Algorithm; Topology (electrical circuits); Telecommunications; Computer science; Wireless; Combinatorics","score_opus":0.05955792642731404,"score_gpt":0.2960684547149066,"score_spread":0.23651052828759256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612748665","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":[0.83458614,0.00055511977,0.16393478,0.000024389905,0.000037636226,0.00035409693,0.0000029840546,0.00013596292,0.00036890645],"genre_scores_gemma":[0.9752219,0.0004286682,0.024269093,0.000004464808,0.00001471734,0.000016978336,0.000023544442,0.000016327778,0.000004336289],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923,0.00008767425,0.00020726875,0.00014790586,0.00013028852,0.00019683059],"domain_scores_gemma":[0.9989846,0.00018270724,0.0000566471,0.00056197227,0.00016318494,0.00005092297],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039398597,0.00009465631,0.00013881223,0.0000925082,0.0005325172,0.000025211853,0.00024256909,0.00006060711,0.000005440232],"category_scores_gemma":[0.00002476309,0.00009606853,0.000019680509,0.0004871627,0.00022250458,0.00017496725,0.00046273627,0.0003164843,0.0000013745024],"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":[0.000010655664,0.000045786113,0.0028107378,0.00004262982,0.00001684969,3.3328314e-7,0.0033649062,0.9849018,0.00062003796,0.0007602656,0.000008543844,0.0074174427],"study_design_scores_gemma":[0.00066514994,0.00011003556,0.0035336846,0.0003057855,0.000011494971,0.0000046122314,0.0005266539,0.9911115,0.0007430403,0.0026980585,0.00012370518,0.00016624053],"about_ca_topic_score_codex":0.000047492755,"about_ca_topic_score_gemma":0.00003633929,"teacher_disagreement_score":0.14063574,"about_ca_system_score_codex":0.00011918844,"about_ca_system_score_gemma":0.000016596776,"threshold_uncertainty_score":0.40957457},"labels":[],"label_agreement":null},{"id":"W2612796108","doi":"10.1109/access.2017.2689718","title":"Optimization of Discrete Power and Resource Block Allocation for Achieving Maximum Energy Efficiency in OFDMA Networks","year":2017,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":24,"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":"Ontario Ministry of Economic Development and Innovation","keywords":"Computer science; Mathematical optimization; Orthogonal frequency-division multiple access; Resource allocation; Power control; Telecommunications link; Efficient energy use; Computational complexity theory; Optimization problem; Transmitter power output; Power budget; Heuristic; Relaxation (psychology); Power (physics); Orthogonal frequency-division multiplexing; Algorithm; Mathematics; Computer network; Engineering","score_opus":0.009614030290781858,"score_gpt":0.2530603222550739,"score_spread":0.24344629196429204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612796108","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":[0.061775938,0.00040047194,0.9369225,0.000051362156,0.00022697043,0.00019561687,0.0000038422604,0.000057685134,0.00036564126],"genre_scores_gemma":[0.9949152,0.0004505317,0.004405225,0.00001562167,0.00008267016,0.000054034335,0.000016749982,0.000040740983,0.000019266205],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992627,0.000015218112,0.0002539801,0.00018542325,0.00008479835,0.00019786702],"domain_scores_gemma":[0.9994027,0.000065035325,0.0001542206,0.0002918829,0.00005099717,0.000035160505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000109786306,0.00012683484,0.00017160294,0.000090055146,0.0001238567,0.00009937168,0.00029687848,0.000096905045,0.0000028333839],"category_scores_gemma":[0.00003868941,0.00013671875,0.000024507082,0.00011707825,0.000045636134,0.0005614553,0.000053611093,0.00006791721,5.496503e-8],"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":[0.000022197193,0.000009667557,0.0014605277,0.000033953784,0.000008068119,3.479825e-7,0.000053275802,0.9929352,0.0002082771,0.00009700546,0.000050513736,0.0051210145],"study_design_scores_gemma":[0.00039165435,0.000016627773,0.0019833676,0.000112487294,0.000010241796,6.321946e-7,0.000008820167,0.99600464,0.0011496507,0.00006830567,0.000109426095,0.00014416284],"about_ca_topic_score_codex":0.000020203319,"about_ca_topic_score_gemma":0.00003611483,"teacher_disagreement_score":0.9331392,"about_ca_system_score_codex":0.00003116322,"about_ca_system_score_gemma":0.000005899792,"threshold_uncertainty_score":0.5575229},"labels":[],"label_agreement":null},{"id":"W2613418868","doi":"10.1109/wcnc.2017.7925925","title":"Transmission Time Analysis for Adaptive Modulation System over Block Fading Channels","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Fading; Link adaptation; Transmission (telecommunications); Computer science; Fading distribution; Cumulative distribution function; Network packet; Channel (broadcasting); Channel state information; Modulation (music); Electronic engineering; Algorithm; Wireless; Mathematics; Computer network; Rayleigh fading; Telecommunications; Probability density function; Statistics; Physics; Engineering","score_opus":0.013242238370326427,"score_gpt":0.22847600954619468,"score_spread":0.21523377117586825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2613418868","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":[0.014823308,0.000031424417,0.98211616,0.0000111156005,0.00012192804,0.00028409302,0.000006371567,0.00034620892,0.0022593853],"genre_scores_gemma":[0.9769847,0.000009642542,0.022190366,0.000002441623,0.00012366526,0.000033616245,0.000030601346,0.0000326745,0.0005923224],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993955,0.0000074853447,0.0001656604,0.00016542281,0.00009484924,0.00017108413],"domain_scores_gemma":[0.99955,0.000031914165,0.00006497998,0.00025426244,0.000048100952,0.000050746625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000724587,0.0001230723,0.00020268219,0.0001123298,0.00023011914,0.000059852406,0.0001091046,0.000080568134,0.000026451256],"category_scores_gemma":[0.0000055592946,0.00011962136,0.00010361491,0.000120558834,0.000009032692,0.0003324251,0.000009882861,0.000040526575,0.000008425624],"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":[0.000011026696,0.000002901765,0.000061316576,0.000026620592,0.00015781043,3.486676e-7,0.00006484809,0.9945897,0.0010726464,0.00029277927,0.000059299622,0.0036607066],"study_design_scores_gemma":[0.00025851885,0.000011469974,0.00072200934,0.000039868588,0.00012606868,3.6257347e-7,0.000012070863,0.99705386,0.001473758,0.000040323423,0.00011300666,0.0001486953],"about_ca_topic_score_codex":0.0000058156966,"about_ca_topic_score_gemma":0.000002372143,"teacher_disagreement_score":0.96216136,"about_ca_system_score_codex":0.00009664294,"about_ca_system_score_gemma":0.000002787322,"threshold_uncertainty_score":0.48780176},"labels":[],"label_agreement":null},{"id":"W2713034347","doi":"10.1109/icassp.2017.7952851","title":"Traffic engineering for backhaul networks with wireless link scheduling","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Distributed computing; Scheduling (production processes); Backhaul (telecommunications); Computer network; Wireless; Wireless network; Cloud computing; Base station; Mathematical optimization","score_opus":0.00757741722075939,"score_gpt":0.20578747156871252,"score_spread":0.19821005434795314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2713034347","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":[0.05386077,0.00015434403,0.94394374,0.000058953756,0.00038218338,0.00030495212,0.0000016999564,0.0007419007,0.00055148045],"genre_scores_gemma":[0.81996137,0.000102554484,0.17911573,0.000012184914,0.000523494,0.00006848804,0.000016662214,0.00010717066,0.0000923254],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913245,0.0000026134578,0.0001773544,0.00020715712,0.000087509565,0.00039289263],"domain_scores_gemma":[0.9992967,0.000064159685,0.00005342881,0.00043879263,0.000057448786,0.00008942959],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007590888,0.00021634638,0.00021328992,0.000045969537,0.00022592813,0.00014485039,0.00025267687,0.000118917844,0.000011503114],"category_scores_gemma":[0.0000170386,0.00020345596,0.00004615732,0.000065415006,0.000026850827,0.00036668862,0.000024164214,0.00017149831,0.0000043383957],"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":[0.000012468525,0.0000037016705,0.000045664838,0.00004434094,0.0000333745,0.000001994328,0.000017406936,0.9730095,0.00010202929,0.0004497951,0.000053064363,0.026226657],"study_design_scores_gemma":[0.00055870577,0.00003273423,0.00014017118,0.00009609137,0.000015910915,0.000003858282,0.00000974221,0.99776393,0.0003551954,0.0000058828778,0.00071903894,0.0002987496],"about_ca_topic_score_codex":8.2737023e-7,"about_ca_topic_score_gemma":0.000012567332,"teacher_disagreement_score":0.76610065,"about_ca_system_score_codex":0.000046631234,"about_ca_system_score_gemma":0.0000084735775,"threshold_uncertainty_score":0.82966936},"labels":[],"label_agreement":null},{"id":"W2724402017","doi":"","title":"Joint Buffering and Rate Control for Video Streaming over Heterogeneous Wireless Networks","year":2011,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","keywords":"Computer science; Wireless network; Variable bitrate; Computer network; Handover; Distributed computing; Wireless; Real-time computing; Quality of service; Telecommunications","score_opus":0.009930789222417294,"score_gpt":0.24445577716575345,"score_spread":0.23452498794333615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2724402017","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":[0.31940213,0.004174133,0.67237526,0.0000037454236,0.0014146771,0.0011008596,0.000016277632,0.00057708257,0.00093580585],"genre_scores_gemma":[0.9943296,0.0010195078,0.002159943,0.000031799846,0.0003845991,0.0002580141,0.00038722597,0.0002955736,0.0011337666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99876726,0.000024247902,0.0003160474,0.0003627464,0.00009139275,0.0004382912],"domain_scores_gemma":[0.99930215,0.00010991178,0.00016301818,0.0002475181,0.00007250063,0.00010491906],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000944491,0.00043798416,0.0005111458,0.000099979035,0.00010234329,0.00005865919,0.00009940992,0.00030637364,0.000028315582],"category_scores_gemma":[0.000016861592,0.00049959327,0.000094458854,0.00009130902,0.000017179225,0.00011440399,0.000013242808,0.00027411798,0.00000216181],"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":[0.00011322171,0.000007463667,0.000026209584,0.00035968507,0.00013876474,0.0000076139836,0.00059948984,0.9855267,0.0019459084,0.00011294567,0.00012109545,0.011040909],"study_design_scores_gemma":[0.00086818123,0.000041722524,0.00029990255,0.00036194842,0.00012117062,0.0000047899703,0.00016856214,0.9941419,0.0029758357,0.000081013626,0.00037177568,0.0005632338],"about_ca_topic_score_codex":0.00003098527,"about_ca_topic_score_gemma":0.00021078585,"teacher_disagreement_score":0.6749274,"about_ca_system_score_codex":0.00010378106,"about_ca_system_score_gemma":0.000013821059,"threshold_uncertainty_score":0.99974555},"labels":[],"label_agreement":null},{"id":"W2735249221","doi":"10.5539/ibr.v10n8p129","title":"Wi-Fi Adoption and Security in Hong Kong","year":2017,"lang":"en","type":"article","venue":"International Business Research","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Flexibility (engineering); Computer science; Mobile device; The Internet; Internet access; Mobile phone; Phone; Computer security; Entertainment; Broadcasting (networking); Telecommunications; Internet privacy; World Wide Web","score_opus":0.038257375279985587,"score_gpt":0.34892378465102686,"score_spread":0.3106664093710413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735249221","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":[0.9635091,0.00026133368,0.019203724,0.0010202904,0.0007395039,0.00022071642,0.000011902059,0.00009913258,0.01493433],"genre_scores_gemma":[0.99769753,0.0009904389,0.00087640726,0.000004696472,0.00023654432,0.00002517552,0.000027067423,0.000021125868,0.00012103831],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9990894,0.000023611175,0.00013778833,0.00016869859,0.0003677257,0.00021277103],"domain_scores_gemma":[0.99929655,0.00007009905,0.000026551708,0.00021415517,0.00035353613,0.00003912232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031522044,0.00007892047,0.000084634914,0.00024215005,0.00014826325,0.0002185197,0.0003103602,0.000066605004,0.000045020686],"category_scores_gemma":[0.00027806868,0.000087374436,0.000010080085,0.00016616462,0.0001092598,0.0007197981,0.00015950436,0.00026597103,0.000019899862],"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":[0.00008936959,0.00007669667,0.22741987,0.00014516275,0.000040420717,0.00009534229,0.0003685915,0.7199803,0.0022365768,0.0040770015,0.0010719915,0.044398673],"study_design_scores_gemma":[0.00041861608,0.0000042290567,0.6266547,0.00013196655,8.3261165e-7,0.000006393177,0.00003158151,0.36789694,0.00027394562,0.0027474915,0.0017145417,0.000118794786],"about_ca_topic_score_codex":0.00007889286,"about_ca_topic_score_gemma":0.00018514546,"teacher_disagreement_score":0.39923477,"about_ca_system_score_codex":0.00014024347,"about_ca_system_score_gemma":0.000015442263,"threshold_uncertainty_score":0.3563026},"labels":[],"label_agreement":null},{"id":"W2736858543","doi":"","title":"Novel Resource Management Approach for End-to-End QoS Support in Wireless Mesh Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Quality of service; Computer network; End-to-end principle; Wireless mesh network; Wireless; Reuse; Resource allocation; Resource management (computing); Distributed computing; Resource (disambiguation); Wireless network; Telecommunications; Engineering","score_opus":0.009893091929468866,"score_gpt":0.21638425636636355,"score_spread":0.2064911644368947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736858543","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":[0.0005303892,0.000020409392,0.9537159,0.000063067666,0.00011754185,0.0009071871,0.0000043081222,0.00037628633,0.044264868],"genre_scores_gemma":[0.6850589,0.000056451463,0.31228247,0.00043330487,0.0002614019,0.00019278152,0.00020447739,0.00007058411,0.0014396587],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99865836,0.000008495468,0.0003302839,0.00033016197,0.00015916736,0.00051352987],"domain_scores_gemma":[0.99950784,0.000037392303,0.000029682324,0.00029895356,0.000021154214,0.00010497049],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017681035,0.00022671725,0.00023926602,0.00016802848,0.000043441356,0.000032588403,0.00020919775,0.000105632054,0.00003573802],"category_scores_gemma":[0.0000033622016,0.0002456119,0.000051105202,0.0004870084,0.000011477709,0.0001368144,0.000035852434,0.00014112104,0.0000041447806],"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":[0.000025052028,0.000054954737,0.000023614051,0.000028494993,0.000016712276,0.0000025998086,0.000057567642,0.9292775,0.00008682887,0.009115173,0.0055221836,0.055789344],"study_design_scores_gemma":[0.0007342618,0.00004335748,0.00044953168,0.000020674472,0.000010067759,0.0000029197665,0.00009397927,0.9920749,0.00016453833,0.000037951886,0.006062707,0.00030507555],"about_ca_topic_score_codex":0.0000020119548,"about_ca_topic_score_gemma":0.000009760217,"teacher_disagreement_score":0.68452847,"about_ca_system_score_codex":0.00012971483,"about_ca_system_score_gemma":0.0000041508333,"threshold_uncertainty_score":0.99999964},"labels":[],"label_agreement":null},{"id":"W2740309844","doi":"","title":"Dynamic Distributed Resource Allocation in Relay Assisted OFDMA Networks","year":2012,"lang":"en","type":"article","venue":"International Conference on Wireless and Mobile Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Relay; Computer science; Resource allocation; Computer network; Resource management (computing); Frequency-division multiple access; Orthogonal frequency-division multiplexing; Resource (disambiguation); Distributed computing","score_opus":0.023697666727383198,"score_gpt":0.28251008276549916,"score_spread":0.25881241603811594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2740309844","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":[0.50476795,0.005780509,0.46896604,0.0028084144,0.0010471306,0.0013059947,0.000248824,0.0008555613,0.014219574],"genre_scores_gemma":[0.9885919,0.00822246,0.0016094837,0.000047566748,0.00003371606,0.00046491358,0.00092907314,0.000029644916,0.000071231225],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909383,0.00007253558,0.00031545298,0.00014900895,0.00013824822,0.0002309403],"domain_scores_gemma":[0.99907047,0.00014294437,0.00008071964,0.000518564,0.00010222548,0.00008510534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014764883,0.00016049133,0.00015379334,0.00013152848,0.00010105326,0.000052598127,0.000459304,0.00011440473,0.000042555697],"category_scores_gemma":[0.000016901078,0.0001767551,0.000028370623,0.00023278406,0.000091601265,0.00028521428,0.00012811377,0.0003302281,0.000006903334],"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":[0.000021667287,0.00021668825,0.004180139,0.000011652456,0.000048668357,5.469704e-7,0.00036612654,0.8759359,0.00081192335,0.039184906,0.0001847886,0.07903696],"study_design_scores_gemma":[0.0002851866,0.000013527902,0.013168786,0.00013673547,0.000008125958,0.0000034816067,0.00018366778,0.9804791,0.00003407572,0.00007518853,0.005427823,0.00018429036],"about_ca_topic_score_codex":0.000013314888,"about_ca_topic_score_gemma":0.00009089484,"teacher_disagreement_score":0.48382396,"about_ca_system_score_codex":0.00018084071,"about_ca_system_score_gemma":0.00001289948,"threshold_uncertainty_score":0.7207864},"labels":[],"label_agreement":null},{"id":"W2742476617","doi":"10.1109/tvt.2017.2738024","title":"Energy-Efficiency Versus Delay Tradeoff in Wireless Networks Virtualization","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":41,"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":"Higher Education Discipline Innovation Project; Ministry of Science and Technology, Taiwan; National Natural Science Foundation of China","keywords":"Virtualization; Computer science; Physical layer; Wireless; Efficient energy use; Wireless network; Lyapunov optimization; Mathematical optimization; Computer network; Engineering; Mathematics; Telecommunications","score_opus":0.00890338431236119,"score_gpt":0.22325117649464002,"score_spread":0.21434779218227884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2742476617","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":[0.058955494,0.00015343266,0.93828326,0.00011423991,0.0012013238,0.00015967253,0.000004131496,0.00082097895,0.0003074509],"genre_scores_gemma":[0.99781406,0.00082738395,0.0010660767,0.000016641816,0.00004104126,0.0001226341,0.00000835251,0.000071165814,0.000032631786],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987769,0.000025381554,0.00030580594,0.0003341203,0.00014624202,0.00041156015],"domain_scores_gemma":[0.99906045,0.000041915824,0.00008026849,0.00072513527,0.000040851082,0.000051362724],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007328239,0.00025019818,0.00025361698,0.00047275613,0.00034545697,0.000044361026,0.00043186135,0.00052840647,0.000017486213],"category_scores_gemma":[0.000005570412,0.00029236637,0.00006852319,0.00052865065,0.0001684517,0.0002657071,0.0000028406998,0.0004719471,0.000010473297],"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":[0.000032640393,0.00006262952,0.000019159077,0.0000056329986,0.000025758345,0.000022533275,0.000016961483,0.92387104,0.000727116,0.0016788159,0.00001230721,0.0735254],"study_design_scores_gemma":[0.0010856395,0.000086848275,0.000028919008,0.000047668556,0.000021247366,0.000010448167,0.000025525624,0.98161274,0.016315278,0.0001479248,0.0003305339,0.00028725064],"about_ca_topic_score_codex":0.000013623904,"about_ca_topic_score_gemma":0.00026227822,"teacher_disagreement_score":0.93885857,"about_ca_system_score_codex":0.0001832366,"about_ca_system_score_gemma":0.000014879803,"threshold_uncertainty_score":0.99995285},"labels":[],"label_agreement":null},{"id":"W2743082635","doi":"10.1109/tcsvt.2017.2735444","title":"Energy-Efficient Traffic Rate Adaptation for Wireless Streaming Media Transmission","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems for Video Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"National Natural Science Foundation of China","keywords":"Computer science; Wireless; Computer network; Transmission (telecommunications); Wireless transmission; Energy (signal processing); Adaptation (eye); Telecommunications","score_opus":0.018927937740709524,"score_gpt":0.22998019712379808,"score_spread":0.21105225938308855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2743082635","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":[0.051985316,0.0005751337,0.94481254,0.00007203513,0.0011727792,0.0007144353,0.000087945766,0.00055591983,0.000023869758],"genre_scores_gemma":[0.9976851,0.000465564,0.00085034035,0.000006027977,0.00006978958,0.00078664394,0.000013925688,0.000075611395,0.0000470334],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988355,0.000017492743,0.0003605705,0.00034564734,0.000099415105,0.00034137283],"domain_scores_gemma":[0.9991308,0.00020544791,0.00012761848,0.00035426056,0.00010560658,0.00007629709],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016200492,0.00023696163,0.00033439745,0.00031455152,0.0006975377,0.00008325549,0.00018916858,0.000294226,0.0000015049709],"category_scores_gemma":[0.0000089777795,0.0002417251,0.000082079605,0.00012552671,0.00009201496,0.00015426445,7.618732e-7,0.00014140514,7.655453e-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":[0.00001388582,0.000021378915,4.1855102e-7,0.000104560175,0.00002906394,7.355865e-7,0.00010526781,0.6465276,0.0028585277,0.0007471972,0.000013648934,0.34957772],"study_design_scores_gemma":[0.0010525223,0.00010738764,0.0000045574934,0.00020047107,0.000053019365,0.000011208885,0.0002656923,0.9861312,0.010181104,0.00015509737,0.0015847608,0.000252984],"about_ca_topic_score_codex":0.000009633509,"about_ca_topic_score_gemma":0.000054240743,"teacher_disagreement_score":0.94569975,"about_ca_system_score_codex":0.0000836529,"about_ca_system_score_gemma":0.000020365516,"threshold_uncertainty_score":0.98572636},"labels":[],"label_agreement":null},{"id":"W2755417146","doi":"10.1007/s12083-017-0594-0","title":"Adaptive Flow Rate Control for Network Utility Maximization Subject to QoS Constraints in Wireless Multi-hop Networks","year":2017,"lang":"en","type":"article","venue":"Peer-to-Peer Networking and Applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Research and Development Corporation of Newfoundland and Labrador; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Quality of service; Hop (telecommunications); Computer network; Utility maximization; Wireless network; Maximization; Flow control (data); Wireless; Control (management); Distributed computing; Mathematical optimization; Telecommunications; Artificial intelligence; Mathematics; Mathematical economics","score_opus":0.021392336005416155,"score_gpt":0.26667026939771776,"score_spread":0.2452779333923016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2755417146","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":[0.0020103394,0.00014627815,0.9913711,0.0009544285,0.0007667983,0.0038498545,0.00011638309,0.00035284302,0.000432005],"genre_scores_gemma":[0.9212871,0.00007611089,0.07271859,0.0003730407,0.0019395618,0.0031125331,0.00018066181,0.00011866945,0.00019369394],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974068,0.00007283715,0.0005928489,0.0007590927,0.00024830183,0.00092014024],"domain_scores_gemma":[0.9977809,0.00037895617,0.00016305437,0.0008039783,0.0004542893,0.00041877583],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009731056,0.00043737428,0.00054637075,0.00014382933,0.00083567307,0.00028402708,0.00046703444,0.00022916023,0.000008041366],"category_scores_gemma":[0.00012633792,0.0005155578,0.000080826016,0.0005772968,0.00011230232,0.00020140794,0.00011808164,0.00032786204,0.000015750622],"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":[0.00009234926,0.000031292595,0.0025918114,0.000016230062,0.000037750942,0.0000010254621,0.00013540674,0.86316586,0.000028642382,0.0004942963,0.0026356766,0.13076968],"study_design_scores_gemma":[0.0012269248,0.000040581748,0.009434184,0.00015041175,0.000041369905,0.000002134892,0.00004159056,0.9727335,0.00001960795,0.00030589168,0.0154710915,0.00053268875],"about_ca_topic_score_codex":0.000024530415,"about_ca_topic_score_gemma":0.00040917858,"teacher_disagreement_score":0.9192768,"about_ca_system_score_codex":0.00015585349,"about_ca_system_score_gemma":0.00003154898,"threshold_uncertainty_score":0.9997296},"labels":[],"label_agreement":null},{"id":"W2756470574","doi":"10.1007/s11235-017-0384-2","title":"Pricing strategies and categories for LTE networks","year":2017,"lang":"en","type":"article","venue":"Telecommunication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Mount Allison University","funders":"","keywords":"Computer science; Quality of service; Operator (biology); Revenue; Dynamic pricing; Pricing strategies; The Internet; Computer network; Service (business); Service provider; Order (exchange); World Wide Web; Business; Marketing","score_opus":0.01994829504468875,"score_gpt":0.26146672756077216,"score_spread":0.2415184325160834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756470574","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":[0.010621048,0.00478493,0.97899294,0.000040658688,0.00037058067,0.00048152974,0.0000020618438,0.00034557984,0.0043606507],"genre_scores_gemma":[0.9914562,0.002420037,0.0056987084,0.000004421613,0.0001295231,0.00016254428,0.00003190201,0.000035754038,0.000060876264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945587,0.000023148976,0.00021129237,0.00009931509,0.000049227685,0.0001611719],"domain_scores_gemma":[0.9988461,0.00013681702,0.00012912147,0.00080202596,0.000053112577,0.00003281103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018667102,0.000108684166,0.0001568727,0.000032226777,0.0004994939,0.0004884291,0.000322022,0.00007278877,9.563965e-7],"category_scores_gemma":[0.000029556491,0.00011459511,0.000017114977,0.00003604788,0.000056285695,0.0007014695,0.000053017826,0.00009422286,0.0000014708334],"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":[0.0000032251535,0.000002671839,0.00023503638,0.00006849529,0.000018370707,7.499986e-8,0.00020326472,0.98062235,0.00008047614,0.009519376,0.00012254942,0.009124103],"study_design_scores_gemma":[0.00019746223,0.000010230297,0.0009741891,0.000046502402,0.000008413177,0.0000032178943,0.00054352573,0.9909731,0.000047975736,0.00027631526,0.006777823,0.00014120377],"about_ca_topic_score_codex":0.00003435398,"about_ca_topic_score_gemma":0.00003754115,"teacher_disagreement_score":0.9808352,"about_ca_system_score_codex":0.000037644124,"about_ca_system_score_gemma":0.0000092453,"threshold_uncertainty_score":0.4709933},"labels":[],"label_agreement":null},{"id":"W2759905166","doi":"10.1109/lcomm.2017.2752714","title":"User Association and Scheduling With Hard Deadlines in Heterogeneous Cellular Networks","year":2017,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Scheduling (production processes); Approximation algorithm; Benchmark (surveying); Mathematical optimization; Heuristic; Computational complexity theory; Distributed computing; Algorithm; Mathematics; Artificial intelligence","score_opus":0.014403599111896157,"score_gpt":0.22731443454175787,"score_spread":0.21291083542986172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2759905166","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":[0.6575858,0.0007031071,0.33973143,0.0014586712,0.00013358094,0.00016870961,0.0000018866191,0.00013323184,0.00008356479],"genre_scores_gemma":[0.95151365,0.0010147418,0.047127385,0.00016239674,0.00006328703,0.000044746444,0.000020478388,0.000037468566,0.00001582638],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993894,0.000041969175,0.00017271281,0.0001220128,0.0000796941,0.00019420391],"domain_scores_gemma":[0.9986086,0.000099941,0.000110872716,0.0011105487,0.000035176778,0.000034898996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001228956,0.00012009047,0.00013692044,0.00006223448,0.00030007566,0.00012631078,0.00044587927,0.00007319979,0.0000013309563],"category_scores_gemma":[0.000023901724,0.00013120414,0.00001757238,0.000078094905,0.00006643982,0.00030534665,0.00006648089,0.00024242523,0.0000030142292],"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":[0.0000029476266,0.0000072945945,0.02802493,0.0000060631232,0.00002229702,0.0000019471593,0.000058738387,0.96838504,0.002283869,0.000020167905,0.00007090797,0.0011158115],"study_design_scores_gemma":[0.00034544355,0.000005158368,0.0070786322,0.00007417861,0.000016012047,0.000002524588,0.000009410164,0.99087775,0.0007357994,0.000011262489,0.0006565002,0.0001873313],"about_ca_topic_score_codex":0.000018739036,"about_ca_topic_score_gemma":0.0002487036,"teacher_disagreement_score":0.29392785,"about_ca_system_score_codex":0.0001321626,"about_ca_system_score_gemma":0.0000044324834,"threshold_uncertainty_score":0.53503495},"labels":[],"label_agreement":null},{"id":"W2762457728","doi":"10.23919/itc.2017.8064334","title":"Scheduling Jobs with Estimation Errors for Multi-server Systems","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McMaster University","funders":"","keywords":"Computer science; Scheduling (production processes); Robustness (evolution); Server; Distributed computing; Rate-monotonic scheduling; Real-time computing; Dynamic priority scheduling; A priori and a posteriori; Job scheduler; Fair-share scheduling; Mathematical optimization; Computer network; Quality of service; Mathematics","score_opus":0.033441724437525855,"score_gpt":0.27644683064857006,"score_spread":0.2430051062110442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762457728","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":[0.034366578,0.00006720953,0.96418905,0.000014715997,0.00028585215,0.00034589285,0.0000018797452,0.00032141779,0.0004074284],"genre_scores_gemma":[0.60494584,0.0000069542157,0.39472768,0.0000028127422,0.000042493502,0.000052172454,0.000010623881,0.00002898675,0.0001824277],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995468,0.0000031999605,0.00011770718,0.00011129381,0.00006830106,0.00015269154],"domain_scores_gemma":[0.9995534,0.000017802535,0.00005640615,0.0002811397,0.00005530164,0.000035944886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057900852,0.00010110745,0.000107534535,0.000026868423,0.00018797314,0.00010012592,0.000111079156,0.000051208404,0.00000393123],"category_scores_gemma":[0.000030921565,0.00008746158,0.000017543207,0.000026766927,0.000016887918,0.00046138774,0.000011208066,0.000047299443,0.00000854468],"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":[0.0000054423253,0.000003846867,0.0008371162,0.00007086918,0.000014343209,3.9747098e-7,0.000025943293,0.99656504,0.000057686488,0.0010090513,0.000028600667,0.0013816394],"study_design_scores_gemma":[0.00050663186,0.000012636083,0.0011249763,0.00007461888,0.000009701704,0.0000014755851,0.000034312314,0.9976106,0.00038519473,0.000014749851,0.00009217783,0.00013288789],"about_ca_topic_score_codex":0.000012804077,"about_ca_topic_score_gemma":0.000045703568,"teacher_disagreement_score":0.5705793,"about_ca_system_score_codex":0.00004081984,"about_ca_system_score_gemma":0.0000054599127,"threshold_uncertainty_score":0.35665798},"labels":[],"label_agreement":null},{"id":"W2765984063","doi":"10.1109/twc.2017.2762680","title":"Low-Complexity Priority-Aware Interference-Avoidance Scheduling for Multi-user Coexisting Wireless Networks","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":16,"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 Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Guangxi Province; National Natural Science Foundation of China","keywords":"Computer science; Initialization; Scheduling (production processes); Greedy algorithm; Column generation; Mathematical optimization; Wireless network; Wireless; Linear programming; Maximization; Distributed computing; Algorithm; Mathematics","score_opus":0.07306982384635666,"score_gpt":0.31737090629473125,"score_spread":0.2443010824483746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765984063","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":[0.017401505,0.00015867839,0.9789981,0.00021753408,0.0010321663,0.0009336783,0.00014751322,0.00091410516,0.0001967161],"genre_scores_gemma":[0.8952184,0.0014433309,0.10210425,0.00004444137,0.00010931264,0.00066347525,0.00007029755,0.00015278177,0.00019375778],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99792784,0.00010608685,0.0006780718,0.00047166375,0.00019129732,0.00062501343],"domain_scores_gemma":[0.9953049,0.00045570076,0.00030617934,0.0034136719,0.00033374262,0.0001858171],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00026344982,0.0004681293,0.0004976659,0.00016244834,0.0032229228,0.00032166246,0.002146614,0.00028831532,0.000016306853],"category_scores_gemma":[0.000024383024,0.00056485855,0.00021364403,0.0002484181,0.00054537767,0.0007647922,0.000031011325,0.0010795373,0.000019901843],"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":[0.000037388276,0.00023820829,0.00007150796,0.000112586735,0.00008081526,7.548659e-7,0.0002573279,0.94081885,0.00067833206,0.0016281955,0.000026737021,0.0560493],"study_design_scores_gemma":[0.0010379188,0.000035386598,0.0002191427,0.00052836456,0.000058452966,0.000003703436,0.00013621814,0.9923464,0.0047272057,0.000098141994,0.00023888881,0.0005701902],"about_ca_topic_score_codex":0.00004695795,"about_ca_topic_score_gemma":0.0013033294,"teacher_disagreement_score":0.87781686,"about_ca_system_score_codex":0.00029002738,"about_ca_system_score_gemma":0.000055251792,"threshold_uncertainty_score":0.9996803},"labels":[],"label_agreement":null},{"id":"W2766446755","doi":"10.1049/iet-com.2016.0691","title":"Joint opportunistic user scheduling and power allocation: throughput optimisation and fair resource sharing","year":2017,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"National Natural Science Foundation of China","keywords":"Computer science; Scheduling (production processes); Joint (building); Throughput; Resource allocation; Computer network; Shared resource; Telecommunications; Wireless; Operations management; Economics","score_opus":0.05078964273548128,"score_gpt":0.2783183632623148,"score_spread":0.2275287205268335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766446755","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":[0.08538292,0.004084244,0.8645001,0.006665485,0.0002520862,0.00081812614,0.000025732526,0.0009792679,0.037292015],"genre_scores_gemma":[0.88239604,0.0021212013,0.1151341,0.000050984352,0.000031185296,0.000039977574,0.0000679127,0.000037171,0.00012139758],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993175,0.00002329714,0.00023617539,0.00018413251,0.00008551922,0.00015337333],"domain_scores_gemma":[0.9978903,0.00007594886,0.00010944011,0.0017794308,0.00006426763,0.00008059535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017357335,0.00013437522,0.0001383931,0.000050707855,0.0008481166,0.0002350696,0.00045474927,0.000078153054,0.0000118203725],"category_scores_gemma":[0.00010270546,0.00015826723,0.000018822439,0.000054531512,0.00019248757,0.00052657723,0.00043427496,0.00020669206,0.000005000921],"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":[0.000008772854,0.00005407878,0.004412394,0.000094392206,0.00010705582,0.000002234815,0.0025590658,0.89915115,0.0019426345,0.072828904,0.0005519954,0.018287342],"study_design_scores_gemma":[0.00028896195,0.000011553658,0.008146204,0.0001250072,0.000027905144,0.000011073874,0.00028889443,0.9801041,0.00008643687,0.0012247115,0.009436229,0.00024894977],"about_ca_topic_score_codex":0.000011163188,"about_ca_topic_score_gemma":0.000025805086,"teacher_disagreement_score":0.79701316,"about_ca_system_score_codex":0.000048467005,"about_ca_system_score_gemma":0.000011344872,"threshold_uncertainty_score":0.6523113},"labels":[],"label_agreement":null},{"id":"W2767873707","doi":"10.1109/tmc.2017.2771353","title":"QoS-Aware Energy and Jitter-Efficient Downlink Predictive Scheduler for Heterogeneous Traffic LTE Networks","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"","keywords":"Computer science; Jitter; Quality of service; Scheduling (production processes); Telecommunications link; Network packet; Computer network; Efficient energy use; Optimization problem; User equipment; Radio access network; Distributed computing; Real-time computing; Mathematical optimization; Base station; Algorithm","score_opus":0.008430268066044588,"score_gpt":0.22757831187119348,"score_spread":0.2191480438051489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767873707","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":[0.10942211,0.00022094551,0.88798046,0.000011702058,0.0014643832,0.00042302316,0.000023124732,0.0004279363,0.00002630344],"genre_scores_gemma":[0.99397874,0.00015805643,0.0052066436,0.000027312022,0.00035160556,0.00016143486,0.000011935604,0.00008591667,0.000018374338],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987998,0.000023471475,0.00028163582,0.0003774273,0.00011646948,0.00040120198],"domain_scores_gemma":[0.99917936,0.0001500868,0.00009869825,0.00039836124,0.00006176716,0.000111733796],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000082713486,0.0002720911,0.00025292882,0.000091631795,0.00083364826,0.0001263607,0.00018768874,0.0001551922,0.000004890001],"category_scores_gemma":[0.000002339452,0.0003020806,0.000105582796,0.00007942528,0.00008152315,0.00011580148,0.0000042337724,0.000210029,0.0000010852671],"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":[0.000026162437,0.000042201867,0.000002741143,0.00002498204,0.000055763772,0.0000023240593,0.000093958006,0.8828464,0.000056719502,0.000004955631,0.000016854627,0.116826914],"study_design_scores_gemma":[0.00061702455,0.00012984603,0.000020860422,0.0001114593,0.000040551928,0.000013395477,0.000029868723,0.996609,0.0019327559,0.0000035327314,0.00021429501,0.00027744134],"about_ca_topic_score_codex":0.0000020082548,"about_ca_topic_score_gemma":0.000012262344,"teacher_disagreement_score":0.8845566,"about_ca_system_score_codex":0.000097261385,"about_ca_system_score_gemma":0.000009670809,"threshold_uncertainty_score":0.99994314},"labels":[],"label_agreement":null},{"id":"W2772308048","doi":"10.17706/ijcce.2017.6.3.151-160","title":"Bandwidth Allocation with Fairness in Multipath Networks","year":2017,"lang":"en","type":"article","venue":"International Journal of Computer and Communication Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Ottawa","funders":"University of Ottawa","keywords":"Computer science; Multipath propagation; Bandwidth (computing); Computer network; Bandwidth allocation","score_opus":0.00436713570505597,"score_gpt":0.20816429279650295,"score_spread":0.20379715709144697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2772308048","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":[0.089145094,0.00047442262,0.9097666,0.00012684426,0.000323006,0.000043676097,4.2566094e-7,0.00002879611,0.000091128524],"genre_scores_gemma":[0.94873744,0.0011539696,0.049923986,0.0000125588995,0.00014493513,0.0000034645893,0.0000050717617,0.00001630432,0.0000022511736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946797,0.000011561222,0.00025123832,0.00005448659,0.00013273054,0.000082003506],"domain_scores_gemma":[0.99938536,0.000054158718,0.00013949387,0.00022370512,0.00016120676,0.000036072353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013535173,0.00009071243,0.00012276806,0.0001271372,0.000043902153,0.00012684973,0.00049176277,0.000036630616,0.0000016183355],"category_scores_gemma":[0.000010644542,0.000086669934,0.000019367038,0.00003691125,0.000022813432,0.0005758359,0.00006497572,0.00019426289,2.4343643e-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":[0.000014003944,0.000010669874,0.002818133,0.0000049556797,0.0000363232,0.000005646263,0.00012851198,0.96712387,0.000027626054,0.00065829785,0.000012010677,0.029159933],"study_design_scores_gemma":[0.0006118899,0.00001648026,0.03874048,0.00022149137,0.0000042829533,0.000048410042,0.0000083797495,0.9598581,0.00006349081,0.000052271072,0.0002849754,0.0000897067],"about_ca_topic_score_codex":0.0000040277764,"about_ca_topic_score_gemma":0.000010604713,"teacher_disagreement_score":0.8598426,"about_ca_system_score_codex":0.00005641963,"about_ca_system_score_gemma":0.000007052475,"threshold_uncertainty_score":0.35342973},"labels":[],"label_agreement":null},{"id":"W2784750874","doi":"10.1109/twc.2018.2799203","title":"Queue-Aware Joint Dynamic Interference Coordination and Heterogeneous QoS Provisioning in OFDMA Networks","year":2018,"lang":"en","type":"preprint","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"Ontario Centres of Excellence","keywords":"Computer science; Quality of service; Queue; Scheduling (production processes); Optimization problem; Mathematical optimization; Computer network; Backhaul (telecommunications); Convex optimization; Distributed computing; Algorithm; Regular polygon; Base station; Mathematics","score_opus":0.019269246200895523,"score_gpt":0.25679963546768764,"score_spread":0.23753038926679212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2784750874","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":[0.047764186,0.0012597388,0.9477621,0.00028513215,0.0010606615,0.00102681,0.000103764076,0.0006637906,0.00007385825],"genre_scores_gemma":[0.97870755,0.013604217,0.006109643,0.00003373296,0.000053560852,0.0011023598,0.00017890507,0.00015864111,0.000051359784],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99773026,0.00023130504,0.0008303819,0.0005844395,0.00019977424,0.00042386848],"domain_scores_gemma":[0.9972433,0.00024001255,0.00022504947,0.0019499065,0.00021455906,0.00012716283],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020270563,0.00055050233,0.0005640929,0.0005656802,0.00037888624,0.00015248096,0.00086773786,0.00056769064,0.000025450094],"category_scores_gemma":[0.000006433351,0.00066668907,0.00012586422,0.00050249475,0.0002821691,0.00025460767,0.00007326027,0.0018731192,0.000009646036],"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":[0.000015935362,0.00012326948,0.00002073646,0.00012505658,0.000073350064,0.0000016312549,0.00037255953,0.9428806,0.00023630737,0.000024294368,0.000027919259,0.056098353],"study_design_scores_gemma":[0.00035383215,0.000048688027,0.00011781154,0.0015657921,0.000060104332,0.000009600938,0.00006626872,0.9960793,0.0009296688,0.00016943461,0.000036206082,0.00056325604],"about_ca_topic_score_codex":0.0000793989,"about_ca_topic_score_gemma":0.001829378,"teacher_disagreement_score":0.9416524,"about_ca_system_score_codex":0.00058336067,"about_ca_system_score_gemma":0.00006735622,"threshold_uncertainty_score":0.9995784},"labels":[],"label_agreement":null},{"id":"W2785238551","doi":"10.1145/3151848.3151865","title":"Bandwidth and Resource Allocation Optimization Through a Probabilistic Algorithm for Mobile TV","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"INVIDI Technologies (Canada); University of Alberta","funders":"Mitacs","keywords":"Computer science; Probabilistic logic; Resource allocation; Bandwidth (computing); Bandwidth allocation; Broadcasting (networking); Revenue; Distributed computing; Algorithm; Computer network; Artificial intelligence","score_opus":0.010336440362943898,"score_gpt":0.24109699079545543,"score_spread":0.23076055043251154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785238551","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":[0.0003932501,0.00016492313,0.9956732,0.000059240512,0.000103922735,0.0007388304,0.0000071012096,0.00026709223,0.0025924586],"genre_scores_gemma":[0.08599157,0.0002947196,0.9123987,0.00004218726,0.0001704425,0.00045013987,0.000112043526,0.00006234184,0.00047787113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942636,0.0000072281478,0.00015093251,0.00018404867,0.00006931506,0.00016211356],"domain_scores_gemma":[0.99949753,0.000051126794,0.0000561395,0.00029836647,0.00006113987,0.0000356857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007022919,0.0001194407,0.00011932939,0.000021610227,0.00025331433,0.00010414693,0.00010332092,0.000072902,0.00001889076],"category_scores_gemma":[0.000045381952,0.000120410456,0.000019280125,0.00003881455,0.000047348476,0.0004376273,0.00002633081,0.000046986897,0.0000015290336],"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":[0.0000033667998,0.0000075029934,0.00000926856,0.000032131535,0.000008515986,1.4952947e-7,0.00008702399,0.93471164,0.000019380304,0.000588484,0.0004642573,0.06406827],"study_design_scores_gemma":[0.00040702798,0.00003484691,0.00003312636,0.000022190134,0.000014305539,0.0000019410784,0.000029368697,0.99436384,0.00027945903,0.0007460915,0.003918637,0.0001491705],"about_ca_topic_score_codex":0.0000052250357,"about_ca_topic_score_gemma":0.0000055648693,"teacher_disagreement_score":0.08559831,"about_ca_system_score_codex":0.000043149117,"about_ca_system_score_gemma":0.0000063266148,"threshold_uncertainty_score":0.49101958},"labels":[],"label_agreement":null},{"id":"W2785681569","doi":"10.1093/oso/9780198507345.003.0028","title":"A Mathematical Representation and Comparison of Detectors for Wireless Communication using Multiple Antennas","year":2002,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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","funders":"","keywords":"Transmitter; Multipath propagation; Computer science; Transmission (telecommunications); Electronic engineering; Data transmission; Wireless; Data stream; Rayleigh fading; Channel (broadcasting); Fading; Telecommunications; Computer network; Engineering","score_opus":0.058884336166262735,"score_gpt":0.2894093418337237,"score_spread":0.23052500566746095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785681569","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":[0.002863531,0.0007953538,0.980215,0.0000047061876,0.000059383634,0.00070124137,0.000017908302,0.00017610138,0.015166739],"genre_scores_gemma":[0.8003794,0.00086093694,0.19265483,0.0000038337525,0.000051642033,0.00003199253,0.00013509867,0.00017278234,0.0057094772],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990881,0.000008877346,0.0004933824,0.0001677825,0.00011964951,0.00012220745],"domain_scores_gemma":[0.9990171,0.0003249317,0.00018754417,0.00033426235,0.000097523814,0.000038639984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000534091,0.00021018772,0.00044643955,0.00010919585,0.00005256079,0.00001513786,0.00009488711,0.00022481468,0.000044881024],"category_scores_gemma":[0.00002402086,0.00022794885,0.000065482054,0.000034577854,0.00007359224,0.00010722007,0.000037462927,0.00014265646,0.0000019402864],"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":[0.000047091296,0.000044500677,0.000279683,0.0011855045,0.00021551653,7.0039926e-7,0.0008109368,0.9211271,0.002133534,0.035188146,0.00028734037,0.038679942],"study_design_scores_gemma":[0.00030285746,0.000017916127,0.0000052779114,0.00031868042,0.00006280901,0.0000032953435,0.000039114744,0.9946048,0.001139999,0.0031103296,0.00018714505,0.00020773604],"about_ca_topic_score_codex":0.0000028097047,"about_ca_topic_score_gemma":0.000013313901,"teacher_disagreement_score":0.79751587,"about_ca_system_score_codex":0.000059798615,"about_ca_system_score_gemma":0.00000352007,"threshold_uncertainty_score":0.92954844},"labels":[],"label_agreement":null},{"id":"W2787506056","doi":"10.1364/jocn.10.000138","title":"Delay-QoS-Aware Adaptive Modulation and Power Allocation for Dual-Channel Coherent OWC","year":2018,"lang":"en","type":"article","venue":"Journal of Optical Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":18,"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, Okanagan Campus","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Fading; Computer science; Link adaptation; Quality of service; Channel (broadcasting); Transmission (telecommunications); Transmitter power output; Wireless; Computer network; Electronic engineering; Real-time computing; Telecommunications; Engineering; Transmitter","score_opus":0.032270568380138885,"score_gpt":0.2701188253004668,"score_spread":0.23784825692032793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2787506056","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":[0.024662454,0.0033837995,0.9706732,0.00028279927,0.0003095147,0.00021374009,0.0000024103304,0.00003485127,0.00043721453],"genre_scores_gemma":[0.92838115,0.00312588,0.06802882,0.000029943985,0.00038277454,0.000012074343,0.000009388599,0.000024484993,0.000005511873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925643,0.000033938304,0.0003737041,0.000084966916,0.0000972172,0.0001537205],"domain_scores_gemma":[0.998948,0.0002693716,0.00014705308,0.0002353281,0.0003149723,0.000085270294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025421032,0.00011247035,0.00017543774,0.00007446493,0.00022493559,0.000048383878,0.00011324453,0.00008126954,0.0000025793092],"category_scores_gemma":[0.00001583212,0.000108282635,0.000035787372,0.00013735633,0.00012489165,0.00025496774,0.00007099695,0.00018409755,4.3348822e-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":[0.00032821696,0.00017509857,0.00051123084,0.000068034155,0.0003999567,0.0000032286553,0.0020695175,0.6826761,0.0017413814,0.015841948,0.0013213466,0.29486397],"study_design_scores_gemma":[0.00038003517,0.00022574961,0.00056508556,0.00013537936,0.000040056617,0.00003849202,0.00013612727,0.9940898,0.000038545484,0.0014375823,0.0027928618,0.00012030782],"about_ca_topic_score_codex":6.544224e-7,"about_ca_topic_score_gemma":0.000010055749,"teacher_disagreement_score":0.90371865,"about_ca_system_score_codex":0.000053400865,"about_ca_system_score_gemma":0.0000110066685,"threshold_uncertainty_score":0.44156376},"labels":[],"label_agreement":null},{"id":"W2789473569","doi":"10.1109/camsap.2017.8313219","title":"GenS: A new conflict-free link scheduler for next generation of wireless systems","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Computer science; Scheduling (production processes); Distributed computing; Scalability; Network topology; Computer network; Job shop scheduling; Reuse; Wireless; Computational complexity theory; Mathematical optimization; Algorithm; Routing (electronic design automation); Engineering; Mathematics","score_opus":0.09166898726158182,"score_gpt":0.27174607710463805,"score_spread":0.18007708984305623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789473569","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":[0.021655854,0.0007064978,0.9741956,0.00010059837,0.0008325436,0.000498708,0.00000994965,0.00018559683,0.0018146647],"genre_scores_gemma":[0.9177726,0.000384423,0.07874095,0.000021139662,0.0013934468,0.00007116604,0.000048932234,0.00007080067,0.0014965485],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992913,0.0000063277803,0.00027074025,0.00014702042,0.00010386114,0.00018073579],"domain_scores_gemma":[0.99894774,0.000030766005,0.000116143456,0.00072624197,0.000114103255,0.000065023196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007270172,0.000132018,0.00021084624,0.000041840303,0.00011257725,0.00011072168,0.00029956718,0.000118882424,0.000016197659],"category_scores_gemma":[0.000056036148,0.00013306548,0.000045999306,0.00003597053,0.00002557871,0.0004132397,0.000040114144,0.00005921881,0.0000065031577],"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":[0.0000068573268,0.000004416821,0.000046289566,0.00009318443,0.000036412002,2.7831297e-7,0.00006131225,0.95270056,0.021142842,0.010187421,0.005799805,0.00992062],"study_design_scores_gemma":[0.00068931474,0.000020149193,0.000042095588,0.00004587516,0.000015160466,0.0000012022759,0.000016896594,0.98242897,0.011492852,0.00007572469,0.0050206813,0.00015108004],"about_ca_topic_score_codex":0.000038423335,"about_ca_topic_score_gemma":0.00003426375,"teacher_disagreement_score":0.89611673,"about_ca_system_score_codex":0.000035275774,"about_ca_system_score_gemma":0.000021624113,"threshold_uncertainty_score":0.5426253},"labels":[],"label_agreement":null},{"id":"W2793309930","doi":"10.1590/0101-7438.2017.037.03.0525","title":"COST-EFFECTIVE BANDWIDTH PROVISIONING IN MICROWAVE WIRELESS NETWORKS UNDER UNRELIABLE CHANNEL CONDITIONS","year":2017,"lang":"en","type":"article","venue":"Pesquisa Operacional","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Dimensioning; Provisioning; Computer science; Computer network; Bandwidth (computing); Bandwidth allocation; Wireless network; Channel (broadcasting); Backhaul (telecommunications); Wireless; Telecommunications; Engineering; Base station","score_opus":0.01670374490501101,"score_gpt":0.2769415348887964,"score_spread":0.2602377899837854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793309930","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":[0.16019303,0.0005452058,0.82993126,0.00030811693,0.00181716,0.0023402632,0.000056332665,0.00035918428,0.004449421],"genre_scores_gemma":[0.9962904,0.00017566924,0.0019175757,0.00010518215,0.00033964423,0.0006919692,0.00021632614,0.00007814419,0.00018511622],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859655,0.00004175793,0.0002992654,0.00035693907,0.0001892769,0.00051623315],"domain_scores_gemma":[0.999109,0.00017153306,0.0000893297,0.0004076067,0.00010412259,0.00011837575],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018043097,0.00027931965,0.00029677167,0.00012673547,0.0005466108,0.00017862066,0.00030943172,0.00017499247,0.00010011127],"category_scores_gemma":[0.00004548459,0.0002995367,0.00006409197,0.00014951818,0.000118587166,0.00073119235,0.000110536515,0.00044096156,0.00004446005],"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":[0.000024443052,0.00004622262,0.0008428033,0.000018224946,0.000028456006,0.000013195403,0.00013765406,0.9907083,0.0005298277,0.0020590434,0.0005358269,0.005055999],"study_design_scores_gemma":[0.0010066013,0.000024408617,0.013700837,0.00024418463,0.000011799751,0.000015013324,0.000069459435,0.9824741,0.0007134515,0.0006995077,0.000655878,0.00038476594],"about_ca_topic_score_codex":0.000023284445,"about_ca_topic_score_gemma":0.00014679218,"teacher_disagreement_score":0.83609736,"about_ca_system_score_codex":0.0002672449,"about_ca_system_score_gemma":0.00003456686,"threshold_uncertainty_score":0.9999457},"labels":[],"label_agreement":null},{"id":"W2799080987","doi":"10.1109/acssc.2017.8335586","title":"Semi-distributed conflict-free multichannel TDMA link scheduling for 5G","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Time division multiple access; Computer science; Distributed computing; Scheduling (production processes); Computer network; Reuse; Link (geometry); Processor scheduling; Resource (disambiguation); Engineering","score_opus":0.022512693213692085,"score_gpt":0.25939309351667694,"score_spread":0.23688040030298485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799080987","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":[0.0051708044,0.00016766909,0.99031234,0.0002833035,0.0005400356,0.0003551751,0.000059820948,0.00063193555,0.002478891],"genre_scores_gemma":[0.86834717,0.00011939565,0.1302848,0.000042177297,0.00052283204,0.0000791951,0.00015255135,0.0000726611,0.00037919756],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991992,0.000004310242,0.00020461137,0.00018587893,0.00008590088,0.00032011175],"domain_scores_gemma":[0.99889916,0.000082935796,0.00006644327,0.0007574733,0.00010704037,0.0000869178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008001718,0.00016704017,0.00018098988,0.000033543427,0.00028108427,0.00010358617,0.0004187533,0.0001336419,0.00002638541],"category_scores_gemma":[0.00031722296,0.0001764532,0.000056763234,0.000041467403,0.00003560052,0.00028779104,0.000047322566,0.00011825012,0.000018790292],"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":[0.000009295192,0.000005131732,0.00006143753,0.000042651143,0.000026834208,0.0000010907264,0.00003792857,0.99337983,0.001003578,0.0006792572,0.0012101715,0.0035427723],"study_design_scores_gemma":[0.0010083659,0.000015630487,0.00019961334,0.000040320163,0.000012258384,0.0000012396198,0.000019536179,0.9836403,0.008613805,0.00034189687,0.00588077,0.00022626237],"about_ca_topic_score_codex":0.0000069591065,"about_ca_topic_score_gemma":0.000014019522,"teacher_disagreement_score":0.8631764,"about_ca_system_score_codex":0.00005016599,"about_ca_system_score_gemma":0.000008122762,"threshold_uncertainty_score":0.71955526},"labels":[],"label_agreement":null},{"id":"W2808116623","doi":"10.1109/wcnc.2018.8377370","title":"Efficient loss-aware uplink scheduling","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"University of Waterloo","funders":"","keywords":"Goodput; Telecommunications link; Computer science; Scheduling (production processes); Computer network; Benchmark (surveying); Real-time computing; Mathematical optimization; Telecommunications; Wireless; Throughput; Mathematics","score_opus":0.006460493086899767,"score_gpt":0.21842324570749702,"score_spread":0.21196275262059724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808116623","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":[0.081987716,0.00006045951,0.90921694,0.000020996282,0.00036772314,0.00006466564,4.6762216e-7,0.0006892254,0.007591781],"genre_scores_gemma":[0.9304898,0.0000131258,0.06898282,0.00003451813,0.00030336174,0.0000047771427,0.000004484252,0.000030417568,0.00013673434],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995194,0.0000030781548,0.00011209618,0.00010968052,0.00006900043,0.0001867275],"domain_scores_gemma":[0.99972725,0.000015605825,0.000010729501,0.00015021564,0.000050773222,0.000045439047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000035617246,0.000087225824,0.00007160253,0.000038079383,0.000053574477,0.000014131966,0.00006833138,0.000048361468,0.00023144414],"category_scores_gemma":[0.000006770962,0.00008561531,0.000018853885,0.00018275504,0.000033818338,0.000033149972,0.000019831203,0.00006628661,0.0003024997],"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":[0.0000014509143,0.0000039342176,0.00007447214,0.0000065787854,0.000004847485,9.2605353e-7,0.00003624288,0.99543154,0.00022796265,0.00058203173,0.00013547369,0.003494518],"study_design_scores_gemma":[0.00010596864,0.000009181158,0.000073319345,0.000014978349,0.0000024873846,0.0000018191158,0.000014009283,0.9962787,0.002824616,0.000051452957,0.0005117816,0.000111672234],"about_ca_topic_score_codex":6.8054743e-7,"about_ca_topic_score_gemma":0.0000020638377,"teacher_disagreement_score":0.84850204,"about_ca_system_score_codex":0.00003980211,"about_ca_system_score_gemma":0.000004373687,"threshold_uncertainty_score":0.3888123},"labels":[],"label_agreement":null},{"id":"W2883845218","doi":"10.1109/vtcspring.2018.8417547","title":"Low-Complexity Slot-Based Bit Loading for Multicarrier Wireless Systems","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"IBM (Canada)","funders":"","keywords":"Bit error rate; Computer science; Throughput; Fading; Signal-to-noise ratio (imaging); Bit (key); Computational complexity theory; Algorithm; Reduction (mathematics); Wireless; Orthogonal frequency-division multiplexing; Electronic engineering; Real-time computing; Computer network; Channel (broadcasting); Mathematics; Telecommunications; Decoding methods; Engineering","score_opus":0.021233291117264685,"score_gpt":0.24502017810489768,"score_spread":0.223786886987633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883845218","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":[0.04559968,0.00004335745,0.94976044,0.000015633272,0.0008860187,0.00049517635,0.000017932998,0.0008698129,0.0023119284],"genre_scores_gemma":[0.9538151,0.0000037898537,0.045261882,0.000045413097,0.0004828512,0.000099503646,0.000033774144,0.00007978784,0.000177903],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903226,0.0000137474535,0.00025218836,0.00021690493,0.000118644326,0.00036623003],"domain_scores_gemma":[0.99935573,0.00010701564,0.00003618057,0.00026365454,0.00013957004,0.00009783124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000095437084,0.0001822003,0.00020717262,0.000074924144,0.00012080053,0.000048926384,0.0001321447,0.00009642327,0.00005964029],"category_scores_gemma":[0.000021693137,0.0001822259,0.000051173207,0.00020577766,0.00008839433,0.00015149145,0.0000140869315,0.000071301445,0.000048932834],"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":[0.000022299304,0.000015514644,0.000083832696,0.00019672172,0.00002073892,6.842341e-7,0.000055461052,0.9849057,0.0064855167,0.0051657706,0.0010484519,0.001999288],"study_design_scores_gemma":[0.0005307532,0.000030368185,0.000031432373,0.000070377915,0.000010469038,7.7425386e-7,0.000035496592,0.96634763,0.03122007,0.000065482556,0.0014217921,0.00023533203],"about_ca_topic_score_codex":0.000009832255,"about_ca_topic_score_gemma":0.000023150149,"teacher_disagreement_score":0.9082154,"about_ca_system_score_codex":0.0001105921,"about_ca_system_score_gemma":0.000013187374,"threshold_uncertainty_score":0.7430956},"labels":[],"label_agreement":null},{"id":"W2884466981","doi":"10.1109/tac.2019.2926160","title":"Remote Estimation Over a Packet-Drop Channel With Markovian State","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Markov process; Drop (telecommunication); Network packet; Computer science; Channel (broadcasting); State (computer science); Control theory (sociology); Computer network; Telecommunications; Mathematics; Algorithm; Statistics; Control (management)","score_opus":0.003604022041491815,"score_gpt":0.1939724005330819,"score_spread":0.19036837849159008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884466981","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":[0.051762242,0.0000208967,0.94548124,0.00006466419,0.00041048907,0.00081250875,0.00002633124,0.0010106626,0.00041096957],"genre_scores_gemma":[0.9876898,0.00002484787,0.011724167,0.00008865507,0.000018639183,0.000051715415,0.0000063184966,0.00008889307,0.00030694436],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988681,0.00003801077,0.00029682016,0.00022553166,0.00025331564,0.00031823004],"domain_scores_gemma":[0.9993004,0.00012962168,0.000070536946,0.0003650915,0.00004291369,0.00009141431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008525221,0.00025870337,0.0002946306,0.000173619,0.00007451111,0.000045106037,0.00009531977,0.000077918725,0.00028841995],"category_scores_gemma":[0.000002387799,0.00024136546,0.00006537438,0.00031235974,0.000024539295,0.0003151553,3.5404548e-7,0.00017594176,0.00020696018],"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":[0.00004794377,0.000024701287,0.000004279332,0.00007435652,0.00008698171,0.0000033421086,0.00013810191,0.8893485,0.00043330042,0.00000415446,0.000026109838,0.109808244],"study_design_scores_gemma":[0.0022286808,0.00011584352,0.0002817203,0.00017638468,0.00005555694,0.0000107259675,0.000017533634,0.99595875,0.00076889846,0.000069134054,0.000036777823,0.00027998205],"about_ca_topic_score_codex":0.000008947865,"about_ca_topic_score_gemma":0.000044003096,"teacher_disagreement_score":0.93592757,"about_ca_system_score_codex":0.000118586875,"about_ca_system_score_gemma":0.000022091992,"threshold_uncertainty_score":0.9842598},"labels":[],"label_agreement":null},{"id":"W2888015138","doi":"10.1002/ett.3502","title":"Subcarriers assignment scheme for multiple secondary users in OFDMA‐based IEEE 802.22 WRAN: A game theoretic approach","year":2018,"lang":"en","type":"article","venue":"Transactions on Emerging Telecommunications Technologies","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Orthogonal frequency-division multiple access; Computer science; Channel (broadcasting); Benchmark (surveying); Mathematical optimization; Cournot competition; Orthogonal frequency-division multiplexing; Nash equilibrium; Cognitive radio; Computer network; Transmitter power output; Wireless; Telecommunications; Mathematics; Transmitter","score_opus":0.015789237378346265,"score_gpt":0.24893514446794313,"score_spread":0.23314590708959687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888015138","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":[0.016829127,0.00040129604,0.9771566,0.0007458474,0.0001692965,0.00092347566,0.000052280844,0.0031026495,0.0006194539],"genre_scores_gemma":[0.74180335,0.00079656264,0.2555327,0.000026020838,0.000010916337,0.0016957218,0.00003922142,0.000073269264,0.000022244209],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99853146,0.000054134995,0.0004532239,0.00034348652,0.00014617194,0.0004715419],"domain_scores_gemma":[0.99813944,0.0003214159,0.00008765048,0.0013151641,0.000097128366,0.00003917951],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020667374,0.00030765947,0.0002888443,0.0006946549,0.0003757897,0.00003625198,0.00081620464,0.0002674659,0.000049509505],"category_scores_gemma":[0.000053404732,0.00034534137,0.00011439201,0.0011721427,0.00044715157,0.00024582524,0.0000131061615,0.0006583904,0.000007797209],"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":[0.000039694864,0.00016129436,0.00010029959,0.00006112722,0.0000641671,1.7743422e-7,0.00027212032,0.95906985,0.0021976111,0.00064498576,0.0001264477,0.03726223],"study_design_scores_gemma":[0.0009894674,0.00009124618,0.000060124086,0.000091943555,0.00003124272,0.000001138854,0.0014171973,0.96340126,0.030885892,0.0008059198,0.00183327,0.0003913185],"about_ca_topic_score_codex":0.000010031244,"about_ca_topic_score_gemma":0.00007541988,"teacher_disagreement_score":0.7249742,"about_ca_system_score_codex":0.00034325453,"about_ca_system_score_gemma":0.000048994105,"threshold_uncertainty_score":0.99989986},"labels":[],"label_agreement":null},{"id":"W2889455910","doi":"10.1109/ccece.2018.8447698","title":"A Centralized Approach for Load Balancing in Heterogeneous Wireless Access Network","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","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":"Concordia University","funders":"","keywords":"Computer network; Computer science; Load balancing (electrical power); Call blocking; Blocking (statistics); Load management; Wireless network; Bandwidth (computing); Node (physics); Wireless; Distributed computing; Heterogeneous network; Telecommunications; Quality of service; Engineering; Grid","score_opus":0.013428391811931692,"score_gpt":0.24905277069333892,"score_spread":0.23562437888140722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889455910","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":[0.023467718,0.00017203257,0.96742165,0.000008484977,0.0002847119,0.0005485583,0.0000027235258,0.0004302173,0.0076638847],"genre_scores_gemma":[0.93042254,0.000063990956,0.06854861,0.00009344519,0.0005438654,0.00013101047,0.00004066106,0.00006875594,0.00008712411],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882525,0.0000169012,0.00026255668,0.00023895524,0.000113139446,0.0005431801],"domain_scores_gemma":[0.9995988,0.000046956557,0.00003225575,0.00020104571,0.000054578042,0.000066364366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011967907,0.00017633382,0.00022801032,0.000043058863,0.000045957837,0.000052871805,0.00021145094,0.00009927513,0.00002813358],"category_scores_gemma":[0.000009167642,0.00018126055,0.00004448885,0.0003625955,0.000029792369,0.0002214299,0.00003210325,0.00008128384,0.000004024238],"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":[0.0000364834,0.0000134898855,0.0007512385,0.000042342213,0.00001546483,0.0000010766704,0.000057773243,0.9919504,0.00011847463,0.00021222417,0.0018244005,0.0049766204],"study_design_scores_gemma":[0.0007140055,0.000018238989,0.000073203155,0.000028135106,0.0000057879806,0.0000037087175,0.000009767257,0.99548876,0.001790495,0.00017208382,0.0014711069,0.0002246987],"about_ca_topic_score_codex":0.000008903719,"about_ca_topic_score_gemma":0.00010016561,"teacher_disagreement_score":0.9069548,"about_ca_system_score_codex":0.0001768283,"about_ca_system_score_gemma":0.000015767815,"threshold_uncertainty_score":0.73915905},"labels":[],"label_agreement":null},{"id":"W2896435355","doi":"10.1002/cpe.5021","title":"Real‐time multiuser scheduling based on end‐user requirement using big data analytics","year":2018,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Université du Québec à Chicoutimi","funders":"National Natural Science Foundation of China","keywords":"Computer science; Maximum throughput scheduling; Scheduling (production processes); Quality of service; Computer network; Wireless network; Wireless; Throughput; Fading; Distributed computing; Channel (broadcasting); Round-robin scheduling; Fair-share scheduling; Telecommunications; Engineering","score_opus":0.08366151756304095,"score_gpt":0.3472004218482463,"score_spread":0.2635389042852053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896435355","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":[0.14952624,0.00022736317,0.8489337,0.00005621289,0.00042147277,0.000125044,0.000006636985,0.00011999542,0.00058334204],"genre_scores_gemma":[0.92780495,0.00038950486,0.07141007,0.00012742044,0.00019194104,0.000005443666,0.00004779835,0.000016991422,0.000005907186],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909097,0.00004460176,0.00022546948,0.00031091596,0.00016023983,0.00016779355],"domain_scores_gemma":[0.99922854,0.00024667333,0.00009591319,0.00023658789,0.00012076962,0.00007149754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016539212,0.00014048221,0.000120812794,0.000065892105,0.00019685092,0.0000903819,0.00010383783,0.00005044674,0.000013829901],"category_scores_gemma":[0.00016215771,0.00014844596,0.000008399787,0.00022172258,0.00011391101,0.0009630315,0.000060858223,0.00009818942,0.0000068784457],"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":[0.00003753983,0.000034120803,0.00017369288,0.000027674136,0.000015274369,0.0000040142595,0.0016614888,0.9159245,0.0016788737,0.00015534031,0.000057699526,0.08022981],"study_design_scores_gemma":[0.00032044607,0.000060012833,0.00008156231,0.00007823348,0.000025369474,0.000004679522,0.0004878833,0.9967578,0.00045428722,0.000022572429,0.001528453,0.00017871422],"about_ca_topic_score_codex":0.000010502021,"about_ca_topic_score_gemma":0.0000013967806,"teacher_disagreement_score":0.7782787,"about_ca_system_score_codex":0.000029967441,"about_ca_system_score_gemma":0.000028772381,"threshold_uncertainty_score":0.6053451},"labels":[],"label_agreement":null},{"id":"W2911511504","doi":"10.1109/access.2019.2899114","title":"Cross-Layer Performance Analysis of Downlink Multi-Flow Carrier Aggregation in Heterogeneous Networks","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":9,"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, Okanagan Campus; University of British Columbia","funders":"University of British Columbia; King Abdulaziz City for Science and Technology","keywords":"Computer science; Computer network; Queueing theory; Network packet; Scheduling (production processes); Quality of service; Telecommunications link; Channel (broadcasting); Real-time computing; Distributed computing","score_opus":0.014917252271623079,"score_gpt":0.27727862666156056,"score_spread":0.26236137438993745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911511504","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":[0.79498404,0.00030477814,0.20396881,0.0000011714878,0.00042600938,0.00013945896,0.000012355729,0.00007292055,0.00009048289],"genre_scores_gemma":[0.9968951,0.00049493473,0.0023427145,0.000019972815,0.000055760036,0.00001910861,0.00007336817,0.000035071695,0.000063988344],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990083,0.000019783198,0.00036376834,0.0002211733,0.00013966601,0.00024731143],"domain_scores_gemma":[0.9993746,0.000042335774,0.00009218894,0.00033894688,0.00011202153,0.00003986325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008017735,0.0001526382,0.00030360112,0.00024648607,0.000023199716,0.0000502814,0.00022373453,0.00013535129,0.0000875833],"category_scores_gemma":[0.0000074326085,0.000166514,0.000078644065,0.0013433201,0.000021832595,0.0006240936,0.000030632065,0.0001492791,0.0000071501127],"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":[0.000012039242,0.000010774788,0.21143362,0.000031750948,0.00010234403,0.0000020969508,0.00004896949,0.777445,0.00018795974,6.2459935e-7,0.0000037386678,0.010721031],"study_design_scores_gemma":[0.0003860346,0.0000069618663,0.052198872,0.00003136201,0.000058587153,8.4758096e-7,0.0000022678444,0.94004446,0.0070751416,0.000002166831,0.000028352608,0.00016497068],"about_ca_topic_score_codex":0.0000140519405,"about_ca_topic_score_gemma":0.00015486294,"teacher_disagreement_score":0.20191106,"about_ca_system_score_codex":0.00008628335,"about_ca_system_score_gemma":0.00001018212,"threshold_uncertainty_score":0.6790244},"labels":[],"label_agreement":null},{"id":"W2913690770","doi":"10.22215/etd/2012-09455","title":"Stability analysis and optimal control of multi-server wireless queueing systems","year":2012,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Queueing theory; Computer science; Queueing system; Computer network; Telecommunications","score_opus":0.009117366938805533,"score_gpt":0.2278291214535419,"score_spread":0.21871175451473637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913690770","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":[0.44009203,0.0027493702,0.5559586,4.4542145e-7,0.0003419706,0.0003468063,0.000030155034,0.00016895351,0.0003116524],"genre_scores_gemma":[0.99513495,0.0002248574,0.0036015667,0.0000010563253,0.000062561296,0.00005408307,0.00058786053,0.000071197865,0.000261865],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986391,0.000052851137,0.0005717617,0.0002608012,0.00020147066,0.00027403823],"domain_scores_gemma":[0.9991188,0.00010257607,0.00019943247,0.00031037466,0.00017511388,0.000093698734],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001925896,0.00031430234,0.00079312554,0.0002203568,0.00003780789,0.000027649798,0.00010488996,0.00033104798,0.00006518977],"category_scores_gemma":[0.000013754874,0.00031809526,0.00013423232,0.000463771,0.000023486058,0.00024795698,0.000009454862,0.00020588379,0.0000018221887],"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":[0.000029381123,0.000026838947,0.009392307,0.00084097206,0.00090082566,4.8176935e-7,0.00035752,0.985639,0.0014903573,0.00014428595,0.0000034074005,0.0011746371],"study_design_scores_gemma":[0.0003994053,0.0000076898295,0.017443467,0.00007453155,0.0008698507,3.182651e-7,0.0005377471,0.97872275,0.0016300563,7.870731e-7,0.000008268167,0.00030510285],"about_ca_topic_score_codex":0.00020501466,"about_ca_topic_score_gemma":0.00082500116,"teacher_disagreement_score":0.5550429,"about_ca_system_score_codex":0.000082481034,"about_ca_system_score_gemma":0.0000141418,"threshold_uncertainty_score":0.9999271},"labels":[],"label_agreement":null},{"id":"W2916704947","doi":"10.1109/nana.2018.8648771","title":"Joint User Scheduling for ODFMA-Based Multi-Cell Networks","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Scheduling (production processes); Computer science; Telecommunications link; Upper and lower bounds; Benchmark (surveying); Mathematical optimization; Integer programming; Job shop scheduling; Computation; Linear programming; Mathematics; Algorithm; Computer network; Routing (electronic design automation)","score_opus":0.01797150564021036,"score_gpt":0.2281037382219872,"score_spread":0.21013223258177685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916704947","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":[0.0031037498,0.00015621261,0.9943799,0.000026260746,0.000511504,0.00030723074,0.0000017752141,0.0006538572,0.0008595068],"genre_scores_gemma":[0.50866246,0.000011979712,0.49052286,0.00012588187,0.00032899325,0.000035974615,0.000018134811,0.00005600682,0.0002376866],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925387,0.0000070902784,0.00019595952,0.00016997721,0.00006147794,0.0003116535],"domain_scores_gemma":[0.9995658,0.000049089827,0.000028459765,0.00019788105,0.000092278395,0.00006652838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007618471,0.00014790463,0.00013436496,0.000050225146,0.00007965885,0.000026143263,0.00008033836,0.00009809026,0.00007049102],"category_scores_gemma":[0.000014676753,0.00014881138,0.00005316511,0.00015152,0.000028968143,0.00011515773,0.000013860258,0.000088215886,0.000031193264],"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":[0.000007389611,0.000016624599,0.000041501335,0.000021130178,0.0000066851317,2.5377716e-7,0.000011546927,0.99617904,0.00071361184,0.000097773795,0.0013433158,0.001561113],"study_design_scores_gemma":[0.00082974625,0.000030569696,0.000024029483,0.000022226048,0.000008115152,2.2590575e-7,0.000010854582,0.98129827,0.014137123,0.000011989933,0.0034319723,0.00019488027],"about_ca_topic_score_codex":0.0000016798249,"about_ca_topic_score_gemma":0.000015087149,"teacher_disagreement_score":0.5055587,"about_ca_system_score_codex":0.000049020906,"about_ca_system_score_gemma":0.000008777661,"threshold_uncertainty_score":0.6068352},"labels":[],"label_agreement":null},{"id":"W2917098087","doi":"10.1016/j.dam.2017.09.006","title":"On strong edge-coloring of graphs with maximum degree 4","year":2017,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":14,"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":"National Natural Science Foundation of China; National Sanitarium Association","keywords":"Mathematics; Degree (music); Edge coloring; Combinatorics; Brooks' theorem; Enhanced Data Rates for GSM Evolution; Graph coloring; Complete coloring; Discrete mathematics; Chordal graph; 1-planar graph; Graph; Artificial intelligence; Computer science; Line graph","score_opus":0.019134441784503974,"score_gpt":0.23147952676751912,"score_spread":0.21234508498301516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917098087","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":[0.14229353,0.0000236962,0.76049864,0.000007957181,0.0000952742,0.00040894432,0.000009715126,0.00022381393,0.09643841],"genre_scores_gemma":[0.8867959,0.00002477327,0.11300433,0.000003010398,0.000025104371,0.00004872423,0.000008342803,0.00006829755,0.000021562184],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99920297,0.000001946321,0.00022806264,0.00014288558,0.0001928562,0.00023126602],"domain_scores_gemma":[0.9990114,0.000059842983,0.00017049436,0.00068147655,0.000025584806,0.00005118404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006304039,0.00019438363,0.00026562274,0.000056596426,0.00012988146,0.000040634848,0.00028377798,0.00006357591,0.000013365359],"category_scores_gemma":[0.000014100039,0.00016612427,0.00003600297,0.00006438904,0.00008559403,0.00011008348,0.000045530418,0.00013098634,0.000011223816],"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":[0.000030429559,0.00003597847,0.000058017326,0.0003848326,0.000082783634,0.0000031843094,0.00042427605,0.71217686,0.0016707652,0.27925912,0.00007017522,0.00580359],"study_design_scores_gemma":[0.0029293522,0.00024516266,0.0012845835,0.0010655381,0.00021934228,0.000008954813,0.0010015584,0.7486559,0.057628926,0.1853663,0.00013246648,0.0014619183],"about_ca_topic_score_codex":7.7701486e-7,"about_ca_topic_score_gemma":0.0000054729244,"teacher_disagreement_score":0.7445023,"about_ca_system_score_codex":0.000028197053,"about_ca_system_score_gemma":0.0000062132417,"threshold_uncertainty_score":0.6774351},"labels":[],"label_agreement":null},{"id":"W2938542280","doi":"10.1109/cjece.2019.2890833","title":"A Novel Cost Optimization Method for Mobile Cloud Computing by Capacity Planning of Green Data Center With Dynamic Pricing","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":25,"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":"Lyapunov optimization; Data center; Computer science; Energy consumption; Cloud computing; Server; Real-time computing; Dynamic pricing; Renewable energy; Cost reduction; Reduction (mathematics); Mathematical optimization; Distributed computing; Computer network; Engineering","score_opus":0.00841724612974843,"score_gpt":0.21037743176918067,"score_spread":0.20196018563943224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2938542280","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":[0.03865329,0.00046673077,0.96041,0.0000072887574,0.00018621316,0.00022091136,0.00003028433,0.000020977672,0.000004322244],"genre_scores_gemma":[0.5227389,0.000011091814,0.47706303,0.000014820669,0.00010023916,0.0000016242947,0.000035057838,0.00003306801,0.0000022109427],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991933,0.000008560892,0.00029744965,0.00013872026,0.00008339219,0.00027855186],"domain_scores_gemma":[0.99934644,0.00015387227,0.00010386632,0.00012176198,0.00008829506,0.00018579405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014052168,0.00014088204,0.00027718823,0.0001788535,0.000034055465,0.000029690247,0.00018932135,0.00005727791,0.0000013808983],"category_scores_gemma":[0.000010279094,0.00013588394,0.00002536819,0.00025244884,0.000009079049,0.00020174366,0.000017001455,0.00020480632,5.8905112e-8],"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":[0.000007889859,0.000005390411,0.0004919346,0.00007383312,0.00005556032,0.00000193412,0.000109134184,0.9910856,0.0005251864,0.00002061707,0.000055919987,0.0075669955],"study_design_scores_gemma":[0.00061119726,0.00013804945,0.00013564012,0.00019016852,0.000019051859,0.000105537285,0.000006079297,0.99815077,0.00011341113,0.0000018330037,0.0003787009,0.00014955952],"about_ca_topic_score_codex":0.00006866636,"about_ca_topic_score_gemma":0.00003419586,"teacher_disagreement_score":0.48408556,"about_ca_system_score_codex":0.00010894472,"about_ca_system_score_gemma":0.000045600293,"threshold_uncertainty_score":0.55411863},"labels":[],"label_agreement":null},{"id":"W2942788336","doi":"10.1109/iwcmc.2019.8766750","title":"Dynamic QoS-aware Queuing for Heterogeneous Traffic in Smart Home","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Université du Québec","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Quality of service; Computer science; Computer network; Network packet; Queueing theory; Traffic classification; Scheduling (production processes); Queuing delay; Real-time computing; Distributed computing; Mathematical optimization","score_opus":0.00373209082206489,"score_gpt":0.19977607371082257,"score_spread":0.19604398288875768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942788336","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":[0.7427313,0.00016293854,0.25555152,0.000012590935,0.00048402243,0.00041043863,0.000004165624,0.0003940379,0.00024899552],"genre_scores_gemma":[0.990377,0.000053589178,0.009115788,0.000021047501,0.00002453958,0.00004566253,0.00003995253,0.000058888276,0.00026352203],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993767,0.0000058400365,0.00016652019,0.00015551312,0.000047538168,0.00024785442],"domain_scores_gemma":[0.99974334,0.000047054516,0.000014923612,0.00014876807,0.00001538969,0.00003054871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003915471,0.00011894698,0.00014844726,0.00008202995,0.000014223701,0.000013973815,0.0000771063,0.00007068468,0.00004434299],"category_scores_gemma":[0.0000028681732,0.00012871758,0.00003815957,0.0001422404,0.000005243748,0.00011613989,0.000010574782,0.000070554655,0.000046629473],"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":[0.0000059770196,0.0000057418442,0.00018326876,0.0000500887,0.0000061329324,0.0000012441482,0.00004378314,0.99430734,0.0002851214,0.000030631127,0.000032057284,0.005048588],"study_design_scores_gemma":[0.0003992501,0.000020952984,0.00015574155,0.000029966825,0.0000023099935,0.0000032680582,0.000027898917,0.9986868,0.00017803231,0.000032760756,0.0002919167,0.00017113418],"about_ca_topic_score_codex":0.0000015744725,"about_ca_topic_score_gemma":0.0001709974,"teacher_disagreement_score":0.24764572,"about_ca_system_score_codex":0.00011751017,"about_ca_system_score_gemma":0.0000049712444,"threshold_uncertainty_score":0.5248951},"labels":[],"label_agreement":null},{"id":"W2947239635","doi":"10.1109/twc.2019.2918145","title":"Computation Over Wide-Band Multi-Access Channels: Achievable Rates Through Sub-Function Allocation","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"Fundamental Research Funds for the Central Universities; Southeast University; National Natural Science Foundation of China","keywords":"Computation; Transmitter power output; Resource allocation; Channel (broadcasting); Wireless; Orthogonal frequency-division multiplexing; Power (physics); Function (biology)","score_opus":0.02952503215381607,"score_gpt":0.282835221275387,"score_spread":0.25331018912157094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947239635","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":[0.0925526,0.00033684904,0.9032784,0.00020716632,0.0012848628,0.00088036107,0.000031367177,0.0008834836,0.0005449209],"genre_scores_gemma":[0.98959744,0.0026240395,0.0066193608,0.00016733288,0.00004159802,0.00036431165,0.00025248306,0.00013268836,0.00020071873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982556,0.00015490572,0.00055046944,0.00038733776,0.00027474048,0.00037696544],"domain_scores_gemma":[0.9978443,0.00040888027,0.00015271266,0.0012967311,0.00020821043,0.0000891831],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014953784,0.00037147812,0.00033209447,0.00024953685,0.00052263075,0.00018627048,0.0006711794,0.00022281815,0.00007850484],"category_scores_gemma":[0.000004944448,0.00043626933,0.00012405106,0.00095858786,0.00011522285,0.0016969035,0.000008778491,0.0005819243,0.00021357399],"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":[0.00003868753,0.00024433344,0.0001529763,0.000057904264,0.00009884899,2.0840943e-7,0.0002964286,0.9823111,0.008277111,0.00028750492,0.00018395991,0.0080509195],"study_design_scores_gemma":[0.0011345017,0.00007254261,0.00063840835,0.00015006008,0.00007108947,0.000002831503,0.000104888524,0.95805585,0.038234662,0.000275828,0.00076605106,0.00049327506],"about_ca_topic_score_codex":0.00006445333,"about_ca_topic_score_gemma":0.00020466886,"teacher_disagreement_score":0.89704484,"about_ca_system_score_codex":0.00028272072,"about_ca_system_score_gemma":0.000045594614,"threshold_uncertainty_score":0.9998089},"labels":[],"label_agreement":null},{"id":"W2949259901","doi":"10.82308/27613","title":"Capacity and information rates for multiple antenna wireless systems with multi-dimensional modulation","year":2008,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transmitter; MIMO; Transmitter power output; Transmission (telecommunications); Computer science; Channel (broadcasting); Multi-user MIMO; Telecommunications; Precoding; Wireless; Electronic engineering; Engineering","score_opus":0.017665340828006797,"score_gpt":0.2021234478217765,"score_spread":0.1844581069937697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949259901","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":[0.98506916,0.000090878006,0.012500874,0.000004486924,0.00031531806,0.00095368375,0.00039305814,0.00051839795,0.00015414541],"genre_scores_gemma":[0.9761611,0.00011875457,0.023132613,0.0000361217,0.000027196387,0.00017796521,0.00023592105,0.00007898129,0.00003135328],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848413,0.000054637363,0.0004744523,0.00029603875,0.0002886787,0.0004020538],"domain_scores_gemma":[0.9988916,0.00019146397,0.00016015956,0.00024521,0.0003496326,0.00016196653],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020848711,0.00034513342,0.0003290727,0.00017837972,0.0007135213,0.000042262385,0.00010989616,0.0002010069,0.0000027769315],"category_scores_gemma":[0.00011096482,0.0003389762,0.000049968374,0.00031011415,0.000078243356,0.0031111606,0.000036382324,0.0002788338,0.000012327017],"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":[0.00009998302,0.000034715886,0.0008046904,0.00018394859,0.00006165816,0.0000034298596,0.000012324341,0.97399366,0.014133045,0.00329347,0.000001825112,0.0073772306],"study_design_scores_gemma":[0.0019594936,0.00006678365,0.003998941,0.00012617894,0.000020855417,0.00007891113,0.000027337182,0.9859197,0.0061649014,0.00011527889,0.001056242,0.00046533506],"about_ca_topic_score_codex":0.000044590157,"about_ca_topic_score_gemma":0.000054628923,"teacher_disagreement_score":0.011926063,"about_ca_system_score_codex":0.00025672367,"about_ca_system_score_gemma":0.000008859629,"threshold_uncertainty_score":0.99990624},"labels":[],"label_agreement":null},{"id":"W2949886190","doi":"10.22215/etd/2014-11043","title":"Utility-Based Packet Scheduling and Resource Allocation Algorithms with Heterogeneous Traffic for Wireless OFDMA Networks","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; University of Toronto","funders":"Ministero dello Sviluppo Economico","keywords":"Computer science; Network packet; Scheduling (production processes); Quality of service; Computer network; Algorithm; Wireless network; Distributed computing; Wireless; Real-time computing; Mathematical optimization","score_opus":0.006996731627806455,"score_gpt":0.21595015206171497,"score_spread":0.20895342043390852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949886190","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":[0.12409811,0.0010455423,0.87274873,0.000018398692,0.00026646824,0.00095928204,0.000015978861,0.00068035355,0.00016712844],"genre_scores_gemma":[0.94112706,0.00030088777,0.051225856,0.00005899488,0.00037604733,0.00043500602,0.0058363564,0.00033240044,0.00030738267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99832153,0.000039013015,0.0004323838,0.0005504354,0.00021531088,0.00044131483],"domain_scores_gemma":[0.99900323,0.0001875195,0.0001722399,0.0003318716,0.0001753216,0.00012980858],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014628078,0.00052796316,0.0005098346,0.00015245934,0.00015735033,0.00009056678,0.00015166191,0.0005159397,0.000013051139],"category_scores_gemma":[0.000011818681,0.00052164315,0.00007967201,0.00023725427,0.00003798742,0.00010503063,0.0000067016053,0.00031746927,8.9406313e-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":[0.0001557587,0.000016748572,0.000020277379,0.00049002643,0.0000742044,9.708582e-7,0.00006545928,0.8963655,0.000026050237,0.00002945166,0.00007841362,0.10267713],"study_design_scores_gemma":[0.00079524174,0.00008419377,0.00003793879,0.00041832036,0.00012378953,0.0000025545512,0.00009963465,0.99592334,0.0011322201,0.000009334801,0.00078236934,0.0005910795],"about_ca_topic_score_codex":0.0000030614992,"about_ca_topic_score_gemma":0.00030309358,"teacher_disagreement_score":0.8215229,"about_ca_system_score_codex":0.0000564694,"about_ca_system_score_gemma":0.00003766478,"threshold_uncertainty_score":0.9997235},"labels":[],"label_agreement":null},{"id":"W2950121851","doi":"10.48550/arxiv.1005.3238","title":"Power Control and Performance Analysis of Outage-Limited Cellular Network with MUD-SIC and Macro-Diversity","year":2010,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia","funders":"","keywords":"Goodput; Computer science; Network packet; Fading; Telecommunications link; Power control; Decoding methods; Single antenna interference cancellation; Computer network; Channel (broadcasting); Power (physics); Algorithm; Throughput; Telecommunications; Wireless; Physics","score_opus":0.011795663833337147,"score_gpt":0.13815546082721963,"score_spread":0.1263597969938825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950121851","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":[0.74184656,0.00019120313,0.25728735,0.0000023363841,0.00010594991,0.00019445962,0.000033687673,0.00011371378,0.00022471127],"genre_scores_gemma":[0.99759424,0.0011144972,0.0010737361,0.0000125086535,0.000030743515,4.0882136e-7,0.000056266366,0.000033414417,0.00008417885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988903,0.00003914033,0.0001743847,0.00052124035,0.000079004734,0.00029596285],"domain_scores_gemma":[0.9990094,0.000074623254,0.000183352,0.00047980572,0.00012254069,0.00013030869],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000115868555,0.00032701035,0.00058911403,0.00032243662,0.00015799492,0.000023484628,0.00024067277,0.00032932803,0.00003110129],"category_scores_gemma":[0.0000049174955,0.00036926506,0.00009383892,0.0008408666,0.00019948412,0.00019383775,0.00046289686,0.00058174,0.0000012136671],"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":[0.00011339284,0.000011827713,0.12603192,0.00007017617,0.0009554718,0.000029914567,0.00013621754,0.8721965,0.00003948331,0.00030444015,0.000009719619,0.000100941936],"study_design_scores_gemma":[0.0007538487,0.00005270139,0.034443904,0.00006212206,0.0015557953,9.267509e-7,0.000044829925,0.96253383,0.000044836834,0.00010816155,0.000024968698,0.00037406507],"about_ca_topic_score_codex":0.000021925305,"about_ca_topic_score_gemma":0.000074690244,"teacher_disagreement_score":0.2562136,"about_ca_system_score_codex":0.000068667905,"about_ca_system_score_gemma":0.000016242631,"threshold_uncertainty_score":0.9998759},"labels":[],"label_agreement":null},{"id":"W2950934110","doi":"10.48550/arxiv.cs/0703144","title":"On The Capacity Of Time-Varying Channels With Periodic Feedback","year":2007,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Codebook; Transmitter; Channel capacity; Channel state information; Channel (broadcasting); Additive white Gaussian noise; Fading; Multiplexing; Gaussian; Computer science; Control theory (sociology); Coding (social sciences); Mathematics; Telecommunications; Topology (electrical circuits); Algorithm; Physics; Statistics; Wireless","score_opus":0.026455160065654567,"score_gpt":0.21713062325581464,"score_spread":0.19067546319016007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950934110","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":[0.91370064,0.00018848605,0.08192382,0.000058640453,0.00040756204,0.00041518334,0.000013038229,0.0002687891,0.0030238652],"genre_scores_gemma":[0.9971665,0.00016526719,0.002034527,0.00006865372,0.00023179302,0.00004128305,0.000040500105,0.000104717845,0.00014672027],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998766,0.000034813864,0.0003088493,0.0003150666,0.0002441059,0.00033114353],"domain_scores_gemma":[0.99888825,0.00016476483,0.00015685814,0.0006402295,0.000089608555,0.00006026584],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001890434,0.00034701198,0.0003670056,0.000101803875,0.000087074804,0.000023734994,0.00031536454,0.0002485063,0.00012896578],"category_scores_gemma":[0.000036871705,0.00026556026,0.00008239191,0.00023105851,0.00011923239,0.00007194965,0.00012592439,0.0007850045,0.000094335344],"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":[0.000023405973,0.000016534052,0.002905962,0.00012061388,0.00007766352,0.0000038727067,0.00039574044,0.995394,0.000560859,0.00007078419,0.00016435604,0.0002661979],"study_design_scores_gemma":[0.0009278827,0.00018141863,0.0135747995,0.0026788197,0.00015734271,0.00001549594,0.000111134796,0.9407638,0.038536485,0.00085779215,0.00055878214,0.0016363019],"about_ca_topic_score_codex":0.000014171343,"about_ca_topic_score_gemma":0.0000047025933,"teacher_disagreement_score":0.08346593,"about_ca_system_score_codex":0.00012527892,"about_ca_system_score_gemma":0.000024954568,"threshold_uncertainty_score":0.9999797},"labels":[],"label_agreement":null},{"id":"W2951341175","doi":"10.48550/arxiv.cs/0606071","title":"Scheduling and Codeword Length Optimization in Time Varying Wireless Networks","year":2006,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Scheduling (production processes); Wireless; Wireless network; Computer network; Distributed computing; Mathematical optimization; Mathematics; Telecommunications","score_opus":0.012316915170005816,"score_gpt":0.21559659370541337,"score_spread":0.20327967853540754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951341175","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":[0.43949518,0.0013067882,0.55762494,0.000020207213,0.0003729195,0.0003312915,0.0000051761012,0.00046958125,0.0003739167],"genre_scores_gemma":[0.9482551,0.0023583558,0.048003383,0.000034415596,0.00047383373,0.000082383114,0.00051383075,0.0002068026,0.000071846815],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979871,0.00006303223,0.0006199535,0.0006074239,0.00019893282,0.00052355765],"domain_scores_gemma":[0.99912006,0.00011511438,0.00016937115,0.0004370078,0.00006578895,0.00009265156],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021150848,0.00050522375,0.00055734545,0.00024085608,0.000091868766,0.00009870307,0.00027931895,0.00064737536,0.000022622084],"category_scores_gemma":[0.00002302368,0.00063445437,0.000064270214,0.00038337804,0.000056085613,0.0002763934,0.00034730503,0.0011252618,0.000011517625],"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":[0.000011302773,0.000019866746,0.059413627,0.00011940832,0.00003135268,0.000011720965,0.000053708907,0.9379813,0.000040986906,0.000010183978,0.000038331425,0.0022681996],"study_design_scores_gemma":[0.00042739947,0.000007268315,0.005576932,0.00059885543,0.00003236403,0.0000032620844,0.000004713665,0.9926258,0.000070120805,0.000044735098,0.000023437724,0.0005851264],"about_ca_topic_score_codex":0.000032199543,"about_ca_topic_score_gemma":0.000020234145,"teacher_disagreement_score":0.50962156,"about_ca_system_score_codex":0.00024114057,"about_ca_system_score_gemma":0.000026492542,"threshold_uncertainty_score":0.99961066},"labels":[],"label_agreement":null},{"id":"W2951728081","doi":"10.48550/arxiv.1001.2274","title":"Network Capacity Region of Multi-Queue Multi-Server Queueing System with Time Varying Connectivities","year":2010,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Wireless Network Optimization","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":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Queue; Queueing theory; Bulk queue; Computer science; Queueing system; Computer network; Real-time computing; Layered queueing network; Upper and lower bounds; Mathematical optimization; Topology (electrical circuits); Mathematics; Combinatorics; Mathematical analysis","score_opus":0.04749684230216163,"score_gpt":0.1619647159572395,"score_spread":0.11446787365507785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951728081","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":[0.37534684,0.000079073194,0.6228224,0.000001617945,0.00037629655,0.00038757353,0.0000121696,0.00060902047,0.0003649713],"genre_scores_gemma":[0.98453426,0.00009538733,0.014768629,0.0000058839946,0.00016158135,0.000004083371,0.000041164876,0.0001261837,0.00026280672],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99832475,0.00012199289,0.0003179326,0.0006781921,0.00009283374,0.00046428083],"domain_scores_gemma":[0.99833834,0.00015259102,0.00036143418,0.0008098673,0.00021268374,0.00012508505],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016483892,0.0005092036,0.0006757224,0.00019418521,0.00015145737,0.000034184475,0.0004367201,0.000604116,0.000010026767],"category_scores_gemma":[0.000017289694,0.0005936951,0.00014293793,0.00044770696,0.00016615559,0.00037108327,0.00028459463,0.001052667,0.0000118639455],"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":[0.000057417004,0.000032279746,0.0024021547,0.00070133235,0.00016962018,0.00011810948,0.00018171027,0.99329764,0.00015728798,0.002822165,0.000021172858,0.000039120005],"study_design_scores_gemma":[0.0008490077,0.000022892782,0.00029939334,0.0011968595,0.00012893813,0.000015273563,0.00011421391,0.99620384,0.00042367255,0.00012450808,0.000011936415,0.000609454],"about_ca_topic_score_codex":0.00028979915,"about_ca_topic_score_gemma":0.0003369445,"teacher_disagreement_score":0.6091874,"about_ca_system_score_codex":0.00041306886,"about_ca_system_score_gemma":0.000055785873,"threshold_uncertainty_score":0.99965143},"labels":[],"label_agreement":null},{"id":"W2951927003","doi":"10.48550/arxiv.1403.8055","title":"Energy-Efficient Adaptive Video Transmission: Exploiting Rate Predictions in Wireless Networks","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Dynamic Adaptive Streaming over HTTP; Heuristic; Base station; Energy consumption; Transmission (telecommunications); Wireless network; Telecommunications link; Efficient energy use; Transmitter power output; Real-time computing; Video quality; Wireless; Energy (signal processing); Computer network; Quality of experience; Quality of service; Telecommunications; Transmitter","score_opus":0.02625487318813574,"score_gpt":0.15828516069450627,"score_spread":0.13203028750637053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951927003","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":[0.062265612,0.00019492647,0.93426484,0.000008978037,0.00065375224,0.00027015936,0.000012035017,0.0006844507,0.0016452521],"genre_scores_gemma":[0.9968157,0.001567222,0.00095250853,0.000021464688,0.00024972367,0.0000108752565,0.000097543714,0.00010746091,0.00017752686],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99801904,0.00018089445,0.00037642388,0.0008099474,0.00007658592,0.0005371114],"domain_scores_gemma":[0.9988353,0.00017744405,0.00015636813,0.00053670583,0.000096676566,0.00019750763],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020079612,0.00047701714,0.00047839092,0.0003465145,0.00014285564,0.000036964502,0.00041950055,0.0005066922,0.00003184176],"category_scores_gemma":[0.0000068822355,0.00061976863,0.00016805221,0.00076566736,0.00008348693,0.00016333058,0.00021961254,0.00091541,0.0000069409316],"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":[0.000048174305,0.00003908082,0.000106594285,0.000052386356,0.000056610537,0.00006888483,0.00010013773,0.9915776,0.000019440935,0.005982857,0.00008654921,0.0018616338],"study_design_scores_gemma":[0.0005441395,0.000020769772,0.000105726846,0.0005562426,0.00006318723,0.0000017095624,0.00009548439,0.9967182,0.0000820852,0.0010783635,0.0001773162,0.00055676524],"about_ca_topic_score_codex":0.00004067397,"about_ca_topic_score_gemma":0.000050537525,"teacher_disagreement_score":0.93455005,"about_ca_system_score_codex":0.00051180786,"about_ca_system_score_gemma":0.000049895207,"threshold_uncertainty_score":0.9996254},"labels":[],"label_agreement":null},{"id":"W2952154992","doi":"10.48550/arxiv.1112.1181","title":"On the Stability Region of Multi-Queue Multi-Server Queueing Systems with Stationary Channel Distribution","year":2011,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Polytope; Queue; Queueing theory; Stability (learning theory); Computer science; Channel (broadcasting); Stationary distribution; Layered queueing network; Bulk queue; Network packet; Applied mathematics; Mathematical optimization; Mathematics; Computer network; Combinatorics","score_opus":0.08948768818141309,"score_gpt":0.17222202502869643,"score_spread":0.08273433684728335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952154992","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":[0.33057284,0.00007218549,0.66819954,0.000004500483,0.00022367504,0.00057561864,0.00007439031,0.00018890254,0.00008833067],"genre_scores_gemma":[0.99888575,0.00025813878,0.0004008494,0.0000047208496,0.00003096591,0.000008586364,0.00027125364,0.000053144977,0.00008659342],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998706,0.00016166322,0.00026475795,0.00051713415,0.00009417578,0.0002563119],"domain_scores_gemma":[0.99846786,0.0001602521,0.00028219417,0.00076194515,0.00025502674,0.0000727436],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017601255,0.00033448997,0.00032377112,0.00008763288,0.00010973307,0.000018126535,0.00035220492,0.00026147856,0.000009595788],"category_scores_gemma":[0.000034098015,0.0002991092,0.0000935595,0.0003403036,0.0001318337,0.00022071856,0.000155967,0.0005073409,0.0000059125086],"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":[0.000099265206,0.00008873641,0.0010066149,0.0002934173,0.000094531264,0.00002857392,0.00021378197,0.9850679,0.000011399065,0.013046352,0.000030960055,0.000018478653],"study_design_scores_gemma":[0.0004897492,0.000039617586,0.0013409982,0.00043128378,0.00006267709,0.0000018500668,0.00035861487,0.9959282,0.00030022857,0.0007179726,0.000006806202,0.00032197757],"about_ca_topic_score_codex":0.0002652461,"about_ca_topic_score_gemma":0.00011634681,"teacher_disagreement_score":0.6683129,"about_ca_system_score_codex":0.00044382937,"about_ca_system_score_gemma":0.000049686667,"threshold_uncertainty_score":0.9999461},"labels":[],"label_agreement":null},{"id":"W2952685718","doi":"10.1109/glocom.2014.7416943","title":"Efficient Heuristic for Resource Allocation in Zero-Forcing OFDMA-SDMA Systems with Minimum Rate Constraints","year":2014,"lang":"en","type":"article","venue":"2015 IEEE Global Communications Conference (GLOBECOM)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Group for Research in Decision Analysis","funders":"","keywords":"Computer science; Subcarrier; Resource allocation; Heuristics; Space-division multiple access; Spectral efficiency; Mathematical optimization; Orthogonal frequency-division multiple access; Heuristic; Maximization; Distributed computing; Orthogonal frequency-division multiplexing; Real-time computing; Computer network; Telecommunications link; Channel (broadcasting); Mathematics","score_opus":0.023505019913239892,"score_gpt":0.2597932063062153,"score_spread":0.23628818639297539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952685718","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":[0.033228565,0.00064978725,0.95821756,0.00033731744,0.00030246066,0.0011601179,0.00011461258,0.0003686846,0.005620879],"genre_scores_gemma":[0.98626345,0.00018984622,0.012738594,0.000047128,0.000044521737,0.00043233112,0.00019644298,0.00004342942,0.000044242603],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99814606,0.0002510392,0.0006001698,0.00033143745,0.0001951544,0.00047612804],"domain_scores_gemma":[0.99753094,0.00039996917,0.00020506917,0.0013670716,0.000359406,0.00013756937],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005523976,0.00031565537,0.00039603421,0.000110234025,0.00021492912,0.00012691587,0.0008748588,0.00015211735,0.000007395527],"category_scores_gemma":[0.0001168877,0.00033111856,0.000046047768,0.00053754036,0.00027270988,0.00012938943,0.00009067251,0.00024248702,0.000024356044],"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":[0.000028994255,0.00005770603,0.0005047146,0.00008314207,0.000028066312,3.6386672e-7,0.00012638647,0.9785818,0.00015164807,0.014634292,0.00087619625,0.0049266936],"study_design_scores_gemma":[0.0009583955,0.000048331414,0.00055466953,0.00042236343,0.000036683163,0.000007656178,0.00026439774,0.9944507,0.000041768602,0.00033692567,0.0025098016,0.00036833814],"about_ca_topic_score_codex":0.00007275318,"about_ca_topic_score_gemma":0.0003290721,"teacher_disagreement_score":0.9530349,"about_ca_system_score_codex":0.00039230133,"about_ca_system_score_gemma":0.00010065305,"threshold_uncertainty_score":0.9999141},"labels":[],"label_agreement":null},{"id":"W2963184790","doi":"10.1109/glocom.2012.6503684","title":"Constrained Joint Bit and Power Allocation for Multicarrier Systems","year":2013,"lang":"en","type":"article","venue":"Ulster University Research Portal (Ulster University)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Communications Research Centre Canada; Memorial University of Newfoundland","funders":"","keywords":"Subcarrier; Computer science; Bit error rate; Computational complexity theory; Fading; Bit (key); Joint (building); Transmitter power output; Constraint (computer-aided design); Throughput; Orthogonal frequency-division multiplexing; Power (physics); Algorithm; Mathematical optimization; Wireless; Telecommunications; Mathematics; Computer network; Decoding methods; Engineering; Transmitter; Channel (broadcasting)","score_opus":0.024054736867674873,"score_gpt":0.22452859994522384,"score_spread":0.20047386307754897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963184790","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":[0.6395084,0.00017235056,0.27562857,0.0004674297,0.0006243067,0.00448331,0.00019137275,0.00080234197,0.07812187],"genre_scores_gemma":[0.9877657,0.0000985338,0.0023173185,0.000012629305,0.000044073775,0.0000022890943,0.00006366101,0.000037883452,0.009657905],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847674,0.00011198173,0.00016240776,0.0003880125,0.00029408373,0.00056679646],"domain_scores_gemma":[0.99869174,0.00015349819,0.000049102287,0.00030058442,0.00049751205,0.0003075406],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002045948,0.00020627188,0.0002419419,0.00071510073,0.0003049338,0.000102903534,0.0002567563,0.00018163439,0.00018794186],"category_scores_gemma":[0.000028183867,0.00025304838,0.00007148759,0.000595544,0.00030779338,0.0011054705,0.00016052494,0.0002865279,0.000040459527],"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":[0.0016651092,0.0009566841,0.02418083,0.0038384765,0.003634473,0.0025440254,0.016565561,0.5420374,0.086327136,0.19579032,0.09817718,0.024282759],"study_design_scores_gemma":[0.00831545,0.0006102804,0.0048562246,0.00044352477,0.00017389003,0.0000657256,0.0408994,0.7725759,0.0015684846,0.0002715554,0.1682738,0.0019457168],"about_ca_topic_score_codex":0.00007145151,"about_ca_topic_score_gemma":0.000039836774,"teacher_disagreement_score":0.34825727,"about_ca_system_score_codex":0.0002082651,"about_ca_system_score_gemma":0.0000537711,"threshold_uncertainty_score":0.9999922},"labels":[],"label_agreement":null},{"id":"W2963402703","doi":"","title":"QoS-Aware Power-Efficient Scheduler for LTE Uplink","year":2014,"lang":"en","type":"preprint","venue":"viXra","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"","keywords":"Computer science; Telecommunications link; Quality of service; Transmission (telecommunications); Computer network; Scheduling (production processes); Real-time computing; Power (physics); Distributed computing; Mathematical optimization; Telecommunications; Mathematics","score_opus":0.009399865310517253,"score_gpt":0.23302663523035969,"score_spread":0.22362676991984243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963402703","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":[0.008260299,0.00053981366,0.98420334,0.00006713882,0.0038283097,0.00080967986,0.00005353652,0.00090621243,0.0013316735],"genre_scores_gemma":[0.898136,0.00014619873,0.09907578,0.00008570909,0.0011349843,0.00044406223,0.00044444986,0.0002807694,0.0002520112],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985922,0.000015093298,0.00035735706,0.0004508838,0.00016489581,0.00041957048],"domain_scores_gemma":[0.9989233,0.000078676436,0.00010471658,0.0006632682,0.00012673368,0.00010331398],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013582049,0.00038202715,0.00039680107,0.00013121466,0.00006808076,0.000061231585,0.00030353313,0.0004371775,0.00006483159],"category_scores_gemma":[0.00003470398,0.00042156936,0.00016437347,0.00011541129,0.000028175311,0.000037227823,0.00020976519,0.00048164933,0.00008771916],"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":[0.000007813735,0.000014702335,0.00000875586,0.0002582461,0.00004294812,8.728207e-7,0.000062696054,0.99397475,0.0000786469,0.0004620441,0.0026767992,0.0024117301],"study_design_scores_gemma":[0.0002866304,0.000017773771,0.00004199896,0.00020743611,0.000028796907,9.670671e-7,0.0000089429195,0.9852624,0.00044477682,0.00036673553,0.012876164,0.0004573954],"about_ca_topic_score_codex":0.000001141091,"about_ca_topic_score_gemma":0.0000010742069,"teacher_disagreement_score":0.8898757,"about_ca_system_score_codex":0.00016620985,"about_ca_system_score_gemma":0.000028885848,"threshold_uncertainty_score":0.99982363},"labels":[],"label_agreement":null},{"id":"W2964149448","doi":"10.1109/glocom.2013.6831616","title":"A Novel Algorithm for Rate/Power Allocation in OFDM-based Cognitive Radio Systems with Statistical Interference Constraints","year":2014,"lang":"en","type":"article","venue":"Ulster University Research Portal (Ulster University)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Memorial University of Newfoundland","funders":"","keywords":"Subcarrier; Cognitive radio; Orthogonal frequency-division multiplexing; Computer science; Interference (communication); Transmitter power output; Transmitter; Bit error rate; Channel (broadcasting); Channel state information; Algorithm; Throughput; Power (physics); Computational complexity theory; Electronic engineering; Mathematical optimization; Telecommunications; Wireless; Mathematics; Engineering","score_opus":0.02127148381507422,"score_gpt":0.24421106605992718,"score_spread":0.22293958224485297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964149448","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":[0.013539,0.0000070399115,0.97751045,0.000030167583,0.00010548994,0.0009083506,0.00024364192,0.00012826506,0.0075275963],"genre_scores_gemma":[0.9853158,0.000011924211,0.013280986,0.00001170055,0.00003064712,0.00000273646,0.00025084894,0.00003963462,0.0010557161],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99813086,0.00024999573,0.0001836443,0.0004906128,0.00032609727,0.0006187866],"domain_scores_gemma":[0.99823827,0.0007066834,0.0000651459,0.00023748536,0.0005203707,0.00023203676],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00044214184,0.00024635947,0.00031162836,0.00090962456,0.00017331893,0.00006614113,0.0003429872,0.00016394469,0.00007825244],"category_scores_gemma":[0.000051564733,0.00029107524,0.000047195572,0.00092050195,0.00051158865,0.0006133279,0.000083344916,0.00043226182,0.000013035945],"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":[0.0056907763,0.0015490556,0.013460992,0.0014504701,0.0011637302,0.0028684791,0.004256511,0.8558249,0.0034478942,0.054477308,0.0022184176,0.053591497],"study_design_scores_gemma":[0.006577665,0.0005679999,0.0012471383,0.0005076142,0.000059682192,0.000016395048,0.0063405894,0.9814358,0.00030091565,0.000024569868,0.0023364257,0.0005852192],"about_ca_topic_score_codex":0.000049487982,"about_ca_topic_score_gemma":0.00021348527,"teacher_disagreement_score":0.9717768,"about_ca_system_score_codex":0.00036920456,"about_ca_system_score_gemma":0.00015367291,"threshold_uncertainty_score":0.99995416},"labels":[],"label_agreement":null},{"id":"W2966589507","doi":"10.22215/etd/2013-10385","title":"Towards Efficient and Fair Radio Resource Allocation Schemes for Interference-Limited Celluar Networks","year":2013,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Toronto Metropolitan University","funders":"","keywords":"Subgradient method; Mathematical optimization; Resource allocation; Computer science; Optimization problem; Maximization; Interference (communication); Convex optimization; Max-min fairness; Cellular network; Mathematics; Regular polygon; Computer network","score_opus":0.0073414992046564,"score_gpt":0.21560442386322964,"score_spread":0.20826292465857324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966589507","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":[0.032742884,0.0021412016,0.95803124,0.000018970635,0.0007242125,0.0011514685,0.000008395094,0.00063288875,0.0045487564],"genre_scores_gemma":[0.95701593,0.0010634579,0.028307978,0.00003223321,0.00041690358,0.00062046875,0.006606369,0.00024661407,0.00569007],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869186,0.000018826573,0.0004115458,0.0003885165,0.00014421086,0.00034502315],"domain_scores_gemma":[0.99926484,0.00008750181,0.00011895806,0.00026165467,0.00016974051,0.000097289114],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008658616,0.00039944227,0.00035730144,0.00017355515,0.00008902807,0.00009385597,0.00016648693,0.00044807332,0.000052603347],"category_scores_gemma":[0.000031606163,0.00040564995,0.000070993854,0.00022158092,0.000022445176,0.00010548446,0.000018038345,0.00027579942,0.0000067329847],"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":[0.000034971126,0.000012218348,0.0000059347794,0.00024279454,0.00005423557,2.0445064e-7,0.00028300897,0.94237566,0.0002289858,0.00070286606,0.0037878575,0.052271258],"study_design_scores_gemma":[0.00032346128,0.000037760943,0.00010282215,0.00021901811,0.000052460007,8.986099e-7,0.00039555057,0.990681,0.0026042035,0.00004211863,0.0051059164,0.00043477374],"about_ca_topic_score_codex":0.000008428892,"about_ca_topic_score_gemma":0.000027009048,"teacher_disagreement_score":0.92972326,"about_ca_system_score_codex":0.00012056243,"about_ca_system_score_gemma":0.00002095465,"threshold_uncertainty_score":0.99983954},"labels":[],"label_agreement":null},{"id":"W2972120183","doi":"10.1109/access.2019.2939120","title":"Matching-Based Resource Allocation for Critical MTC in Massive MIMO LTE Networks","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Quality of service; MIMO; Scheduling (production processes); Computational complexity theory; Latency (audio); Mathematical optimization; Distributed computing; Cellular network; Upper and lower bounds; Computer network; Algorithm; Channel (broadcasting); Mathematics; Telecommunications","score_opus":0.01137215927667498,"score_gpt":0.2767271194417814,"score_spread":0.26535496016510646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972120183","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":[0.06074614,0.00011593697,0.93724054,0.00016431749,0.00062326406,0.00046674645,0.000004695813,0.00020007274,0.0004382696],"genre_scores_gemma":[0.9922852,0.000013262683,0.0069814688,0.00021153406,0.00022081615,0.00012930413,0.00005589131,0.00006582959,0.00003667299],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990959,0.000025201314,0.00023589135,0.00022043452,0.000108839726,0.00031371217],"domain_scores_gemma":[0.9992748,0.00035477625,0.000034709083,0.00023163996,0.000053104606,0.000050958646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010958187,0.00014582006,0.00017274791,0.00009688251,0.0000348977,0.00007273968,0.00023945588,0.00012583875,0.000023770237],"category_scores_gemma":[0.000024178604,0.00016589691,0.00003819861,0.00026393947,0.000019301538,0.00039754162,0.00001691608,0.00016947143,0.00001252565],"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":[0.00003286617,0.000014278582,0.0005450767,0.00008446754,0.000005373346,0.0000015473765,0.000041409046,0.996483,0.00021190078,0.0005450404,0.000541015,0.0014940106],"study_design_scores_gemma":[0.00052080187,0.000016756969,0.00041475365,0.000106598454,0.0000071627774,3.8957117e-7,0.000017496805,0.9958848,0.0012579152,0.0009284864,0.00064641907,0.00019844317],"about_ca_topic_score_codex":0.000008236089,"about_ca_topic_score_gemma":0.00003487679,"teacher_disagreement_score":0.93153906,"about_ca_system_score_codex":0.00010350132,"about_ca_system_score_gemma":0.000012831573,"threshold_uncertainty_score":0.67650795},"labels":[],"label_agreement":null},{"id":"W2976839820","doi":"10.22215/etd/2013-10750","title":"Distributed Multiple Access for the Uplink of Multi-cell OFDMA Networks","year":2013,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"Ministero dello Sviluppo Economico; Ontario Ministry of Economic Development and Innovation","keywords":"Computer science; Computer network; Scheduling (production processes); Telecommunications link; Wireless network; Duplex (building); Quality of service; Cellular network; Overhead (engineering); Wireless; Distributed computing; Engineering; Telecommunications","score_opus":0.014668658740248213,"score_gpt":0.25547079635183456,"score_spread":0.24080213761158634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2976839820","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":[0.0022203112,0.0031011172,0.9913254,0.0000082096185,0.0012789882,0.0014866652,0.00009330737,0.00026924885,0.00021676524],"genre_scores_gemma":[0.9371824,0.0060301404,0.026713595,0.000026580912,0.0005216533,0.0023336755,0.018072525,0.0004006444,0.008718755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890524,0.000009543638,0.00045360439,0.00022277836,0.000111025096,0.0002978313],"domain_scores_gemma":[0.99870825,0.0004398192,0.00020794893,0.00033696424,0.00025913466,0.000047878457],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000566388,0.00031909073,0.00035185818,0.00005681963,0.00008506096,0.00005514574,0.00046334715,0.00037956904,0.00011897073],"category_scores_gemma":[0.000036466186,0.0002464007,0.00013948398,0.00024480923,0.000018191346,0.00019003225,0.000025763837,0.0002588779,0.0000039085244],"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":[0.000022680508,0.000028423254,0.00007949208,0.00028315687,0.00007215097,8.516943e-8,0.000039500756,0.9813234,0.00017231095,0.000018868233,0.0034356609,0.0145242205],"study_design_scores_gemma":[0.0006433815,0.000008605879,0.00060364563,0.00008291291,0.000083739375,7.5584516e-8,0.000090408306,0.9933482,0.0041095437,0.000008042292,0.0007500584,0.00027138676],"about_ca_topic_score_codex":0.00003659933,"about_ca_topic_score_gemma":0.00018459377,"teacher_disagreement_score":0.96461177,"about_ca_system_score_codex":0.00004519813,"about_ca_system_score_gemma":0.00001574612,"threshold_uncertainty_score":0.9999988},"labels":[],"label_agreement":null},{"id":"W2997803755","doi":"10.1109/tmc.2019.2962126","title":"Load Management, Power and Admission Control in Downlink Cellular OFDMA Networks","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; University of Manitoba","funders":"","keywords":"Telecommunications link; Computer science; Base station; Computer network; Load balancing (electrical power); Transmitter power output; Power control; Orthogonal frequency-division multiple access; Admission control; Cellular network; Resource management (computing); Orthogonal frequency-division multiplexing; Distributed computing; Power (physics); Transmitter; Mathematics; Quality of service","score_opus":0.0026288476344518328,"score_gpt":0.18963445289293476,"score_spread":0.18700560525848292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997803755","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":[0.15720136,0.0004512652,0.84048426,0.000008801742,0.00066494825,0.00052601856,0.0000024302306,0.00024134567,0.0004195674],"genre_scores_gemma":[0.9970897,0.0003419682,0.0023133617,0.0000482566,0.000034964694,0.00003424568,0.0000022951633,0.00004690963,0.00008831724],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901927,0.000031487227,0.000264047,0.00026628558,0.00012729815,0.00029164233],"domain_scores_gemma":[0.9995858,0.0000889122,0.000037684636,0.00019656266,0.000020385804,0.00007066671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011654482,0.00018816773,0.0002065102,0.00012670302,0.00007107793,0.000028292023,0.00008486686,0.000105619394,0.00007908519],"category_scores_gemma":[4.5274624e-7,0.00020817184,0.00004603215,0.00028438077,0.000014953179,0.000122069505,0.0000019694048,0.0003139066,0.00001889423],"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":[0.00002018567,0.00003231384,0.00016530063,0.00004066305,0.00002610117,0.0000054187767,0.00006802307,0.94939613,0.0007128293,0.000010651832,0.000014663826,0.049507737],"study_design_scores_gemma":[0.0011385838,0.000042955347,0.00016726092,0.0001977365,0.00001537988,0.0000018901269,0.00004035273,0.9972006,0.0006768216,0.000010109084,0.00030023165,0.00020808892],"about_ca_topic_score_codex":0.0000030834435,"about_ca_topic_score_gemma":0.0000031647621,"teacher_disagreement_score":0.83988833,"about_ca_system_score_codex":0.00011644877,"about_ca_system_score_gemma":0.000005504977,"threshold_uncertainty_score":0.84890014},"labels":[],"label_agreement":null},{"id":"W3002929358","doi":"10.1155/2020/4189789","title":"New Courteous Algorithm for Uplink Scheduling in LTE-Advanced and 5G Networks","year":2020,"lang":"en","type":"article","venue":"Journal of Computer Networks and Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; 3rd Generation Partnership Project 2; LTE Advanced; Quality of service; Scheduling (production processes); Computer network; Telecommunications link; Cellular network; Throughput; Wireless network; Wireless; Telecommunications; Mathematical optimization","score_opus":0.012211470832015108,"score_gpt":0.23109310112346396,"score_spread":0.21888163029144886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3002929358","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":[0.0008831814,0.016843917,0.9809831,0.00085245917,0.00019786267,0.00017164629,8.726134e-7,0.00004313888,0.00002382105],"genre_scores_gemma":[0.28223795,0.015160024,0.7017944,0.00021759681,0.00054493075,0.000005395369,0.000008611543,0.000028869863,0.0000022681465],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991511,0.000031254945,0.0004687863,0.00010006191,0.000062198116,0.00018656433],"domain_scores_gemma":[0.9990758,0.0002791526,0.00015889644,0.00022499183,0.00009000481,0.00017115833],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013320886,0.00014021726,0.00029502684,0.00005943403,0.00009946787,0.00006883385,0.0003044626,0.000087646404,0.000001211913],"category_scores_gemma":[0.0000068044897,0.00014661456,0.000047626065,0.00022614376,0.000034694356,0.00024233751,0.00009761472,0.00044011182,1.1879247e-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":[0.000007718244,0.0000062424124,0.000064952226,0.000004989265,0.00002008831,9.580117e-7,0.000080591875,0.63686836,0.0000020347863,0.00016656143,0.00023210185,0.36254543],"study_design_scores_gemma":[0.0009251112,0.000093041344,0.00021560816,0.00012346242,0.000022455824,0.000024534873,0.000025210646,0.99557394,0.0000015108203,0.0002991268,0.0025568472,0.00013915393],"about_ca_topic_score_codex":8.967167e-7,"about_ca_topic_score_gemma":0.000004856338,"teacher_disagreement_score":0.36240628,"about_ca_system_score_codex":0.00002610982,"about_ca_system_score_gemma":0.00001820821,"threshold_uncertainty_score":0.59787685},"labels":[],"label_agreement":null},{"id":"W3025507213","doi":"10.1109/tmc.2020.2994354","title":"Uplink Scheduling in Multi-Cell OFDMA Networks: A Comprehensive Study","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Computer science; Telecommunications link; Scheduling (production processes); Goodput; Benchmark (surveying); Cellular network; Computer network; Distributed computing; Mathematical optimization; Telecommunications; Wireless","score_opus":0.02506381545907331,"score_gpt":0.25246457490581387,"score_spread":0.22740075944674054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3025507213","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":[0.32125333,0.00033053444,0.6768759,0.000009181733,0.00039158124,0.00062713097,0.0000019293311,0.0004995044,0.000010893359],"genre_scores_gemma":[0.9752313,0.00013372472,0.0242477,0.00009043041,0.00010892063,0.000090928246,0.000003076085,0.000088531066,0.0000053727763],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985933,0.00006325825,0.00045319536,0.00038325912,0.00013459331,0.00037241256],"domain_scores_gemma":[0.99941826,0.00016358464,0.00005038338,0.00019003847,0.000057352812,0.000120362885],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000054116914,0.00027855893,0.0003302293,0.00012473906,0.00014539919,0.000038970822,0.00017297034,0.00009966668,0.000022645034],"category_scores_gemma":[0.0000019283048,0.00033693845,0.000078008154,0.0007596819,0.000021376112,0.00013518351,0.0000037960535,0.00066450646,0.000021087295],"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":[0.00001793076,0.00025273112,0.00015940156,0.000041552303,0.000028887185,0.000012878043,0.0012078406,0.96793807,0.0006544342,2.434252e-7,0.0000037524394,0.02968228],"study_design_scores_gemma":[0.0014938699,0.0001300356,0.00012513087,0.00008204076,0.000020764857,0.0000014069785,0.0009067518,0.9959014,0.0010282809,3.4936443e-7,0.000016342552,0.00029360515],"about_ca_topic_score_codex":0.000008684354,"about_ca_topic_score_gemma":0.000016005362,"teacher_disagreement_score":0.653978,"about_ca_system_score_codex":0.000098682154,"about_ca_system_score_gemma":0.000011433504,"threshold_uncertainty_score":0.99990827},"labels":[],"label_agreement":null},{"id":"W3036521752","doi":"10.1109/ants47819.2019.9118081","title":"An Evaluation of the Proportional Fair Scheduler in a Physically Deployed LTE-A Network","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Regina","funders":"","keywords":"Computer science; Computer network; Network scheduler; Proportionally fair; Quality of service; Dynamic priority scheduling; Round-robin scheduling","score_opus":0.007608259629789648,"score_gpt":0.23034689178543147,"score_spread":0.22273863215564182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036521752","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":[0.9431805,0.000034356177,0.05375145,0.000023253975,0.00019007425,0.0005297634,6.369222e-7,0.00010076807,0.0021891904],"genre_scores_gemma":[0.9927205,0.00000391168,0.0070903115,0.000018506344,0.000076321485,0.000032576256,0.000011600388,0.000021868487,0.000024434486],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992039,0.000051154053,0.00018670275,0.000110493645,0.00031582356,0.0001319305],"domain_scores_gemma":[0.9995968,0.00001861793,0.00004118175,0.00022114179,0.000104214596,0.000018046845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025007015,0.000076362216,0.000097009586,0.000023032255,0.000013715351,0.0000059715267,0.00010225366,0.000043579654,0.00011738717],"category_scores_gemma":[0.000011727847,0.000058003698,0.00002658228,0.00032251936,0.000014620054,0.00020500789,0.000011183202,0.000089087625,0.000010205722],"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":[0.0000051289853,0.0000241618,0.01579995,0.000008198152,0.000006678771,2.8948792e-8,0.000028844717,0.9774019,0.002032396,0.0018373387,0.000067015215,0.002788344],"study_design_scores_gemma":[0.0003163958,0.00001214731,0.060688708,0.000027160619,0.0000073669635,2.1945925e-7,0.000012557998,0.9363187,0.0011536569,0.0013769006,0.000015300371,0.000070903916],"about_ca_topic_score_codex":0.0000027363938,"about_ca_topic_score_gemma":0.000045178887,"teacher_disagreement_score":0.04953996,"about_ca_system_score_codex":0.00006514444,"about_ca_system_score_gemma":0.00003429379,"threshold_uncertainty_score":0.23653221},"labels":[],"label_agreement":null},{"id":"W3036979321","doi":"10.1109/tvt.2020.3003873","title":"Distributed Stable Global Broadcasting for SINR-Based Multi-Channel Wireless Multi-Hop Networks","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Network packet; Computer network; Broadcasting (networking); Scheduling (production processes); Queue; Wireless network; Wireless; Latency (audio); Channel (broadcasting); Throughput; Distributed computing; Mathematical optimization; Telecommunications; Mathematics","score_opus":0.01887875167935258,"score_gpt":0.23366002823072834,"score_spread":0.21478127655137577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036979321","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":[0.0076909414,0.00026178441,0.9871118,0.00046575654,0.00045693945,0.00076774874,0.00032414656,0.002918003,0.0000028860813],"genre_scores_gemma":[0.9428017,0.000060927083,0.056429997,0.000117771786,0.000055544173,0.00032382086,0.00010197709,0.000102297105,0.0000059613794],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982904,0.000026177628,0.00040546822,0.0004954237,0.00013494372,0.0006475749],"domain_scores_gemma":[0.99921674,0.00007211239,0.00008136204,0.0003350445,0.0001476632,0.00014709719],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006029203,0.00038272535,0.00040555964,0.00013123674,0.00026517827,0.000031484742,0.00028292474,0.0005800464,0.00000932911],"category_scores_gemma":[0.000019469788,0.0004508803,0.00015421183,0.0013024233,0.000108749846,0.00014129945,0.0000032146484,0.0005389479,0.000012065457],"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":[0.00005346393,0.0001195128,0.000015500016,0.000061896506,0.00008095966,0.000012269048,0.000012515072,0.98250276,0.0014818836,0.000023886776,0.000059984057,0.015575391],"study_design_scores_gemma":[0.0021213884,0.00014675687,0.0000061518867,0.00006298004,0.0000657565,0.0000067449755,0.00006265859,0.97466636,0.022012956,0.000017653616,0.00042177038,0.00040883906],"about_ca_topic_score_codex":0.0000051545367,"about_ca_topic_score_gemma":0.000038918028,"teacher_disagreement_score":0.93511075,"about_ca_system_score_codex":0.00025199255,"about_ca_system_score_gemma":0.000029763214,"threshold_uncertainty_score":0.9997943},"labels":[],"label_agreement":null},{"id":"W3038512991","doi":"10.1109/vtc2020-spring48590.2020.9129372","title":"Optimum Resource Allocation in MU-MIMO OFDMA Wireless Systems","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Ericsson (Canada)","funders":"","keywords":"Computer science; Scheduling (production processes); MIMO; Resource allocation; Orthogonal frequency-division multiplexing; Spatial multiplexing; Orthogonal frequency-division multiple access; Multi-user MIMO; Wireless; Frequency-division multiple access; Computer network; Transmitter power output; Max-min fairness; Distributed computing; Channel (broadcasting); Mathematical optimization; Telecommunications; Mathematics; Transmitter","score_opus":0.010605254996959378,"score_gpt":0.1977102275724466,"score_spread":0.18710497257548722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038512991","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":[0.07134308,0.00076642307,0.91382897,0.00066660583,0.00024690595,0.00046000353,0.0000037025336,0.0011730143,0.011511294],"genre_scores_gemma":[0.9965603,0.00012202302,0.0026655295,0.00012332282,0.00016943102,0.000054433323,0.00003761351,0.00005319691,0.00021416222],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992048,0.000024591096,0.0002588277,0.0001818818,0.00012398421,0.0002059026],"domain_scores_gemma":[0.9996932,0.000034300996,0.000028645163,0.0001365342,0.000024919082,0.00008236567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000055215824,0.00013263615,0.0001675689,0.00005428434,0.000021209207,0.000029134184,0.00012347153,0.00008514591,0.000036993362],"category_scores_gemma":[0.000010967147,0.0001438134,0.000020118616,0.00042778274,0.000011636267,0.0001793661,0.00002370058,0.0001365988,0.00004530656],"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":[0.000006332083,0.0000060175075,0.0003547695,0.000068714966,0.0000072965854,0.0000029410917,0.00021234063,0.9927886,0.0014505349,0.0008201686,0.0015984115,0.002683871],"study_design_scores_gemma":[0.00024880434,0.000010711359,0.00017369563,0.000048257967,0.000003558668,8.7611704e-7,0.00019423383,0.9944604,0.00084004644,0.000005297285,0.0038496198,0.00016449235],"about_ca_topic_score_codex":0.000010726354,"about_ca_topic_score_gemma":0.000009637543,"teacher_disagreement_score":0.9252172,"about_ca_system_score_codex":0.000072640745,"about_ca_system_score_gemma":0.000006924705,"threshold_uncertainty_score":0.58645403},"labels":[],"label_agreement":null},{"id":"W3049087923","doi":"","title":"Cross-layer communication over fading channels with adaptive decision feedback","year":2020,"lang":"en","type":"article","venue":"Modeling and Optimization in Mobile, Ad-Hoc and Wireless Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Fading; Network packet; Computer science; Channel (broadcasting); Queue; Transmitter; Markov decision process; Additive white Gaussian noise; Markov process; Control theory (sociology); Computer network; Mathematics; Statistics","score_opus":0.013300679618925466,"score_gpt":0.23321779459648373,"score_spread":0.21991711497755825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3049087923","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":[0.1892829,0.00834402,0.80156696,0.000022905904,0.00008867045,0.00039159218,0.0000035496312,0.00023760079,0.000061809966],"genre_scores_gemma":[0.90390074,0.03616869,0.059411608,0.00011460626,0.00010345139,0.00011382011,0.000073443676,0.000102372425,0.0000112633315],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843717,0.0000535713,0.00048360912,0.00046493814,0.00018846827,0.0003722686],"domain_scores_gemma":[0.99922955,0.00013377465,0.00009657395,0.00023761125,0.00012387005,0.00017863876],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016188277,0.0003451042,0.00038382766,0.00011489888,0.0002480398,0.00018647044,0.00014791482,0.00025579202,0.000017811522],"category_scores_gemma":[0.000009836387,0.000342538,0.000031509775,0.0005506541,0.00009040363,0.00063475105,0.00008933577,0.00041908392,9.471095e-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":[0.00021534113,0.00001435938,0.0005252831,0.00002996125,0.000020057412,0.0000024152716,0.00086963136,0.9720096,0.000006384668,0.00005061371,0.000025080817,0.026231255],"study_design_scores_gemma":[0.0013078371,0.00009473626,0.00006421885,0.00033557875,0.000016663698,0.0000038816993,0.0002097106,0.9974405,0.000008971652,0.000051259452,0.000058860398,0.00040775887],"about_ca_topic_score_codex":0.000004585474,"about_ca_topic_score_gemma":0.000013152958,"teacher_disagreement_score":0.7421553,"about_ca_system_score_codex":0.00006365461,"about_ca_system_score_gemma":0.0000122297815,"threshold_uncertainty_score":0.99990267},"labels":[],"label_agreement":null},{"id":"W3084868265","doi":"10.1109/tccn.2020.3022671","title":"Learning-Based Proactive Resource Allocation for Delay-Sensitive Packet Transmission","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Cognitive Communications and Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada); University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Provisioning; Resource allocation; Computer network; Network packet; Resource management (computing); Resource (disambiguation); Shared resource; Quality of service; Distributed computing","score_opus":0.03182727512979351,"score_gpt":0.25060741205266646,"score_spread":0.21878013692287296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084868265","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":[0.0009985518,0.0006400227,0.9958176,0.00065022625,0.0000637345,0.0008287242,0.000035272795,0.00041771244,0.00054812676],"genre_scores_gemma":[0.98476356,0.0027365673,0.011463065,0.00035951397,0.00008799869,0.00033888058,0.00015681787,0.00007768175,0.000015884732],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894005,0.00015592658,0.00026476537,0.00028045982,0.000112442314,0.00024635156],"domain_scores_gemma":[0.9984359,0.0009594792,0.00007267428,0.00021293914,0.00018309258,0.00013589728],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012435114,0.00023120482,0.00020985231,0.00009119646,0.00066662434,0.00004573874,0.00014155729,0.00012169779,0.000005762157],"category_scores_gemma":[0.000007676144,0.00026429945,0.00008337488,0.0004160666,0.00012337472,0.00016430106,0.0000028259476,0.00049624493,0.0000035919338],"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":[0.00017092183,0.000042329873,0.000003045274,0.000030772586,0.00007213642,4.2453482e-7,0.0008511806,0.6379489,0.00026056587,0.00001352579,0.000028297543,0.36057794],"study_design_scores_gemma":[0.00089684833,0.0002650348,0.000009954168,0.0002462577,0.00012031099,0.0000020988464,0.00056160276,0.98456794,0.005396442,0.000026974922,0.0076235496,0.00028296545],"about_ca_topic_score_codex":0.0000015618664,"about_ca_topic_score_gemma":0.000009027544,"teacher_disagreement_score":0.98435456,"about_ca_system_score_codex":0.000060000144,"about_ca_system_score_gemma":0.000023886489,"threshold_uncertainty_score":0.9999809},"labels":[],"label_agreement":null},{"id":"W3099417103","doi":"","title":"Delay Optimal Server Assignment to Symmetric Parallel Queues with Random Connectivities","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Queueing theory; Computer network; Scheduling (production processes); Queue; Fork–join queue; Bulk queue; Queue management system; Network packet; Layered queueing network; Bernoulli's principle; Server; Mathematical optimization; Mathematics; Engineering","score_opus":0.00877707335051095,"score_gpt":0.2111564945331458,"score_spread":0.20237942118263486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3099417103","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":[0.015680622,0.0005534748,0.9723608,0.00008698111,0.0006376847,0.0009592381,0.000023009758,0.00095214404,0.008746057],"genre_scores_gemma":[0.9088148,0.00046065007,0.0878866,0.00008186086,0.000396624,0.0006272968,0.000051452516,0.00018029222,0.0015004129],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99832505,0.000049852602,0.00034381865,0.0004912456,0.0003343886,0.00045567236],"domain_scores_gemma":[0.99884826,0.00022816501,0.000079393954,0.0005154852,0.00016506114,0.00016365832],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014162455,0.00050565694,0.00057567935,0.0002986433,0.000053871616,0.00008980232,0.00025992867,0.0002576327,0.00015118344],"category_scores_gemma":[0.00004034794,0.00037050524,0.00008954363,0.0002536131,0.000032514985,0.00018180095,0.0002506029,0.00031441305,0.000054304455],"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":[0.00014658523,0.000016002143,0.0000928182,0.000094024705,0.00020356271,0.000008740509,0.00008400226,0.9942585,0.000012645683,0.0012028633,0.0020801546,0.0018000595],"study_design_scores_gemma":[0.0040721567,0.00019253646,0.0002099823,0.00093467283,0.00013035409,0.000010456864,0.00012608098,0.9856412,0.0022469105,0.0011341017,0.0033808204,0.001920767],"about_ca_topic_score_codex":0.000016874605,"about_ca_topic_score_gemma":0.000038951675,"teacher_disagreement_score":0.8931342,"about_ca_system_score_codex":0.00037424936,"about_ca_system_score_gemma":0.00004294933,"threshold_uncertainty_score":0.9998747},"labels":[],"label_agreement":null},{"id":"W3102156549","doi":"","title":"On Optimal Zero-Delay Coding of Vector Markov Sources","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Bounded function; Markov process; Quantization (signal processing); Vector quantization; Markov chain; Encoder; Mathematical optimization; Markov decision process; Applied mathematics; Algorithm; Control theory (sociology); Computer science; Mathematical analysis; Statistics; Artificial intelligence","score_opus":0.01208695500442792,"score_gpt":0.21601690587299616,"score_spread":0.20392995086856824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102156549","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":[0.16241083,0.000107463944,0.8125971,0.000012532947,0.00023270154,0.000082167746,0.0000023095995,0.00031168378,0.024243211],"genre_scores_gemma":[0.96164715,0.000019184297,0.037907746,0.00002053942,0.00005007436,0.0000044843496,0.0000062658537,0.000029350473,0.00031521305],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995048,0.000008966714,0.00013905809,0.000086838256,0.000121459925,0.00013888777],"domain_scores_gemma":[0.99970025,0.000052205738,0.00002439611,0.00012399934,0.00003620443,0.000062959734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006260698,0.00009192038,0.000117515476,0.00005013054,0.000013747979,0.000008163191,0.00007300148,0.000045982524,0.000054487075],"category_scores_gemma":[0.0000249586,0.00008726067,0.000022520857,0.00012133549,0.000016333768,0.00009435927,0.00001611258,0.00006631314,0.00002122384],"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":[0.000014162233,0.000007220748,0.000058394864,0.000011480391,0.000010625927,0.0000015250345,0.00012750595,0.9932311,0.00035197547,0.002325895,0.003010662,0.0008494079],"study_design_scores_gemma":[0.00031327663,0.00005563691,0.000042329113,0.000032901968,0.0000055146866,0.0000023175373,0.00005427263,0.99086386,0.007653244,0.00020403112,0.0006370284,0.00013560681],"about_ca_topic_score_codex":0.0000022845988,"about_ca_topic_score_gemma":0.00000116115,"teacher_disagreement_score":0.7992363,"about_ca_system_score_codex":0.000043917113,"about_ca_system_score_gemma":0.000006227303,"threshold_uncertainty_score":0.35583866},"labels":[],"label_agreement":null},{"id":"W3106755046","doi":"10.1109/ccece47787.2020.9255724","title":"A Fairness Guaranteed Dynamic PF scheduler in LTE-A Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Regina","funders":"","keywords":"Computer science; Network scheduler; Proportionally fair; Scheduling (production processes); Base station; Fairness measure; Controller (irrigation); Computer network; Distributed computing; Throughput; Real-time computing; Dynamic priority scheduling; Quality of service; Operating system; Round-robin scheduling; Wireless; Mathematical optimization","score_opus":0.005345294934358038,"score_gpt":0.1857450116879573,"score_spread":0.18039971675359925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3106755046","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":[0.02996381,0.0003271274,0.9659775,0.00015833872,0.00015710469,0.0001642821,9.716971e-7,0.00063993817,0.0026109545],"genre_scores_gemma":[0.98772454,0.000118110576,0.011684948,0.00027870538,0.000068800444,0.000019084631,0.00001662907,0.000052210275,0.0000369798],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926,0.00001318359,0.00020966836,0.0001751229,0.00007985925,0.0002621509],"domain_scores_gemma":[0.9997541,0.000026802072,0.00001641049,0.00012187462,0.000014835914,0.000066016306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003485725,0.00014426326,0.00017076636,0.000046074438,0.000017536051,0.0000187832,0.00011907172,0.00009027589,0.00010711123],"category_scores_gemma":[0.000012340222,0.0001517915,0.000029272169,0.0005291954,0.000014910319,0.00015828143,0.000028284887,0.00020646899,0.00004267086],"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":[0.0000099212175,0.000005639486,0.00054526137,0.000018672843,0.000007580524,0.000006787245,0.00009642295,0.9945042,0.00012432136,0.00051322486,0.00014729699,0.0040206527],"study_design_scores_gemma":[0.0003804015,0.000009328491,0.0005088573,0.000023485225,0.0000030492643,0.000001192231,0.0000535743,0.9984269,0.000072425246,0.000062750325,0.00027669148,0.00018130582],"about_ca_topic_score_codex":0.0000031831637,"about_ca_topic_score_gemma":0.000046375644,"teacher_disagreement_score":0.95776075,"about_ca_system_score_codex":0.00005327375,"about_ca_system_score_gemma":0.0000053014464,"threshold_uncertainty_score":0.61898774},"labels":[],"label_agreement":null},{"id":"W3107755622","doi":"10.1007/978-3-030-60382-3_6","title":"Efficient and Fair Access Scheme for MTC: LTE/WiFi Coexistence Case","year":2020,"lang":"en","type":"book-chapter","venue":"Wireless networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"McGill University","funders":"","keywords":"Computer science; Computer network; Throughput; Scheduling (production processes); Time division multiple access; Wireless; Wireless network; Constraint (computer-aided design); Scheme (mathematics); Duty cycle; Mathematical optimization; Telecommunications","score_opus":0.021191832936445394,"score_gpt":0.23860604793116114,"score_spread":0.21741421499471575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107755622","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":[0.00054076227,0.0065289265,0.94512105,0.0000828201,0.0014592756,0.0018787237,0.0001691849,0.00125174,0.04296749],"genre_scores_gemma":[0.91934097,0.007001299,0.028159201,0.0006170534,0.0057319794,0.0007455396,0.0012774412,0.0019275016,0.035199046],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976347,0.000013935679,0.00064896327,0.000833337,0.0002558437,0.0006132186],"domain_scores_gemma":[0.99850523,0.00025741517,0.00024054895,0.00052185805,0.00015206111,0.00032288543],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011114387,0.0008138159,0.00085881253,0.00016377549,0.0002280723,0.0001820578,0.00039415728,0.0007579011,0.000034932244],"category_scores_gemma":[0.000014315074,0.00092515844,0.00018140799,0.0001686239,0.00017046316,0.0001363783,0.00024452634,0.00082547235,0.000012841611],"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":[0.000045723813,0.0000074538707,0.0000034260147,0.000357388,0.00011699009,0.00034535507,0.000060177226,0.9606846,0.0000072528833,0.02042785,0.002641605,0.015302195],"study_design_scores_gemma":[0.0005921057,0.00004599561,0.0000015588297,0.00048726902,0.000101224825,0.000224023,0.000012111092,0.9788958,0.00001174019,0.00040158315,0.018294822,0.0009318107],"about_ca_topic_score_codex":0.0000022774911,"about_ca_topic_score_gemma":0.000019383388,"teacher_disagreement_score":0.9188002,"about_ca_system_score_codex":0.0001715575,"about_ca_system_score_gemma":0.000031180756,"threshold_uncertainty_score":0.9993199},"labels":[],"label_agreement":null},{"id":"W3125707610","doi":"10.22215/etd/2013-10014","title":"Protection and Security Aware QoS Framework for 4G Multihop Wireless Networks","year":2013,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer network; Quality of service; Computer science; WiMAX; Bandwidth allocation; Scheduling (production processes); Call Admission Control; Bandwidth (computing); Relay; Network packet; Admission control; Wireless; Wireless network; Telecommunications; Engineering","score_opus":0.007271664442042565,"score_gpt":0.23339114644287762,"score_spread":0.22611948200083506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125707610","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":[0.017314801,0.00071841566,0.9758601,0.000009016703,0.0023015311,0.0025117553,0.000017191605,0.00086652744,0.00040065273],"genre_scores_gemma":[0.9371206,0.0034716274,0.045648765,0.000044021603,0.0025103104,0.0043858304,0.0037597488,0.0005716152,0.0024874918],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866825,0.000019574485,0.00036824006,0.00041461506,0.0001416997,0.0003876389],"domain_scores_gemma":[0.99916214,0.00014828889,0.00013542302,0.0002595931,0.00019150978,0.000103038925],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000062100626,0.0004459729,0.00040543138,0.00011320178,0.00015277824,0.00009642058,0.00011683972,0.0010516007,0.00006245524],"category_scores_gemma":[0.000044695364,0.0004761082,0.000073375224,0.00023728173,0.00001826917,0.0002654509,0.00001354506,0.00063525944,0.000006987291],"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":[0.000055164084,0.000019248697,0.000016321776,0.0011604221,0.000087339526,6.233894e-7,0.00033132985,0.9470075,0.000068034504,0.001741825,0.0015962381,0.04791599],"study_design_scores_gemma":[0.00027167134,0.00003239646,0.0000807405,0.00046761672,0.000043592216,0.0000013676331,0.00028163797,0.99519366,0.0006454082,0.0018430452,0.0005955985,0.0005432722],"about_ca_topic_score_codex":0.000023994708,"about_ca_topic_score_gemma":0.00024146287,"teacher_disagreement_score":0.93021137,"about_ca_system_score_codex":0.000099087345,"about_ca_system_score_gemma":0.000019419174,"threshold_uncertainty_score":0.99976903},"labels":[],"label_agreement":null},{"id":"W3127503959","doi":"10.1016/j.comnet.2021.107904","title":"Stochastic joint rate control and resource allocation for wireless video surveillance","year":2021,"lang":"en","type":"article","venue":"Computer Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Newfoundland and Labrador; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Base station; Telecommunications link; Resource allocation; Lyapunov optimization; Wireless; Real-time computing; Upload; Latency (audio); Quality of service; Optimization problem; Mathematical optimization; Computer network; Algorithm; Telecommunications; Artificial intelligence","score_opus":0.00652270278845727,"score_gpt":0.18868521973132946,"score_spread":0.1821625169428722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127503959","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":[0.0046633733,0.0016539589,0.99238116,0.00012603348,0.0005595291,0.00030293877,0.000005169249,0.0002774707,0.000030379644],"genre_scores_gemma":[0.98272556,0.00013868911,0.015742019,0.00026283538,0.0008659234,0.00006103569,0.000113923525,0.000060243678,0.000029754385],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990716,0.000059088805,0.00024623325,0.00027447855,0.00006381514,0.00028476177],"domain_scores_gemma":[0.99928576,0.00025117825,0.000051615978,0.00022348962,0.0001104604,0.00007748324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016765695,0.00017315302,0.0002584261,0.000031065647,0.00008416161,0.00006821407,0.000070164686,0.00009731382,0.0000025707973],"category_scores_gemma":[0.000012925492,0.00019901099,0.0000408507,0.00016549903,0.000028638293,0.00009270787,0.000036607915,0.00013311832,0.000001440315],"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":[0.000011766211,0.0000061652468,0.000030355895,0.000031052394,0.00003275543,0.0000026710698,0.000029963205,0.95878404,0.0001060914,0.00031349398,0.002200093,0.038451545],"study_design_scores_gemma":[0.00086192624,0.000019598247,0.0010481724,0.00006870525,0.000010992566,0.00000943626,0.0000041759113,0.9965634,0.00003388772,0.00011691124,0.0010516564,0.00021117167],"about_ca_topic_score_codex":4.060051e-7,"about_ca_topic_score_gemma":0.0000074231466,"teacher_disagreement_score":0.9780622,"about_ca_system_score_codex":0.000048907452,"about_ca_system_score_gemma":0.000010414588,"threshold_uncertainty_score":0.8115433},"labels":[],"label_agreement":null},{"id":"W3132575665","doi":"10.1109/ist50524.2020.9345825","title":"Queue based Resource Allocation for Tactile Services","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Upload; Resource allocation; Lyapunov optimization; Download; Queue; Telecommunications link; Computer network; Latency (audio); Real-time computing; Distributed computing; Mathematical optimization; Operating system; Telecommunications","score_opus":0.008166238100707383,"score_gpt":0.1951523227150401,"score_spread":0.18698608461433272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3132575665","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":[0.0017514288,0.0000451256,0.9933969,0.0006286191,0.000038739126,0.00019352481,0.000003847428,0.000618676,0.003323167],"genre_scores_gemma":[0.9274195,0.000006861019,0.07098155,0.0011376821,0.00016424635,0.000052511736,0.00013058812,0.000040265015,0.00006682383],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996619,0.000004464555,0.00009031176,0.000096347016,0.000048635487,0.00009834548],"domain_scores_gemma":[0.99979967,0.000039592047,0.000014494569,0.00007624368,0.000023820008,0.000046170702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001869203,0.00006698958,0.00006604956,0.000014643393,0.000025852485,0.000014364326,0.00006271934,0.00003639758,0.000046788617],"category_scores_gemma":[0.00000608396,0.00007115904,0.000018537645,0.000117286414,0.000003337122,0.000109900684,0.0000052640635,0.00003427575,0.0000139089225],"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":[0.000008933548,0.0000023238665,0.000015773714,0.000087785585,0.000004041442,1.3633208e-7,0.00006688027,0.99389607,0.0012211372,0.00022846748,0.0020968628,0.0023715766],"study_design_scores_gemma":[0.00017883551,0.000013126944,0.000014467529,0.000007641485,0.000004133674,9.042142e-8,0.00004690577,0.9391303,0.009010457,0.000019505434,0.05149533,0.000079201876],"about_ca_topic_score_codex":0.0000018340758,"about_ca_topic_score_gemma":0.000007582144,"teacher_disagreement_score":0.92566806,"about_ca_system_score_codex":0.000018696888,"about_ca_system_score_gemma":0.0000039901015,"threshold_uncertainty_score":0.29017815},"labels":[],"label_agreement":null},{"id":"W3138943246","doi":"10.1145/3258123","title":"Session details: QoS and scheduling in wireless networks (WLAN/WPAN symposium)","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Toronto Metropolitan University","funders":"","keywords":"Computer network; Computer science; Session (web analytics); Quality of service; Scheduling (production processes); Wireless; Personal area network; Wireless network; Wireless lan; Telecommunications; Engineering; World Wide Web","score_opus":0.0042208442818028585,"score_gpt":0.20289453556457773,"score_spread":0.19867369128277487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138943246","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":[0.595916,0.00010967703,0.401769,0.000030424982,0.00050289836,0.000129571,3.7430462e-7,0.00029985837,0.0012421904],"genre_scores_gemma":[0.97688234,0.00047211818,0.022226261,0.000030778087,0.00025598262,0.000019355715,0.00001213902,0.000051327523,0.00004970619],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991708,0.000014760196,0.00022368094,0.00020516216,0.00008620034,0.00029942452],"domain_scores_gemma":[0.99960726,0.000067043205,0.000026540418,0.00018615776,0.000022662949,0.00009034138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011187056,0.00016871435,0.0001727514,0.000091538095,0.000052942003,0.000044395987,0.00009094826,0.00018392844,0.000035437926],"category_scores_gemma":[0.000008871984,0.00016562473,0.000018539555,0.0002450545,0.00003080016,0.00028859067,0.000041284937,0.00043599567,0.0000056267445],"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":[0.000004761724,0.000008406806,0.008106444,0.000019325238,0.0000046861164,0.0000036883769,0.00005030329,0.96497077,0.018440418,0.0006353884,0.000024062032,0.007731728],"study_design_scores_gemma":[0.00031208352,0.000006710149,0.001274605,0.0000565741,0.0000043736454,0.0000068167237,0.00003717076,0.9964042,0.0015125964,0.000058828187,0.00011657134,0.00020950151],"about_ca_topic_score_codex":0.000008087058,"about_ca_topic_score_gemma":0.00021642465,"teacher_disagreement_score":0.38096637,"about_ca_system_score_codex":0.00002626173,"about_ca_system_score_gemma":0.000006564921,"threshold_uncertainty_score":0.67539805},"labels":[],"label_agreement":null},{"id":"W3139113958","doi":"10.82308/12565","title":"Dynamic resource allocation in multiuser multicarrier fading environments","year":2008,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Fading; Computer science; Resource allocation; Telecommunications; Computer network; Channel (broadcasting)","score_opus":0.009709709911325887,"score_gpt":0.20006012198678727,"score_spread":0.19035041207546138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3139113958","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":[0.99234134,0.0001575397,0.0005817398,0.0000073812066,0.00023170866,0.00046172988,0.00006172629,0.00045757994,0.0056992294],"genre_scores_gemma":[0.98693544,0.00042476263,0.011697084,0.00007771626,0.000015246033,0.00009057523,0.00009467499,0.00018441169,0.0004800726],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977505,0.00012059847,0.0005709418,0.0005437681,0.0003835703,0.000630623],"domain_scores_gemma":[0.99903804,0.00012928389,0.00009625817,0.0005146595,0.000025876974,0.00019590731],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002442012,0.0003998872,0.00032417313,0.00026830475,0.00039681492,0.00001555566,0.00029594605,0.00027911956,0.00005268912],"category_scores_gemma":[0.00015124021,0.0004900778,0.00008490037,0.000510587,0.000075704564,0.0008527604,0.00009876695,0.00066873175,0.00017343112],"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":[0.000021270485,0.000058305337,0.0003923506,0.000023256023,0.000030738876,0.0000441517,0.000018162034,0.92533016,0.044652242,0.0005491678,0.0000017705878,0.02887841],"study_design_scores_gemma":[0.0029908065,0.000059001624,0.011306615,0.00023263862,0.00004431763,0.000071831484,0.0001170549,0.8931406,0.04033253,0.0011204385,0.04897638,0.0016077762],"about_ca_topic_score_codex":0.000016893664,"about_ca_topic_score_gemma":0.00007965656,"teacher_disagreement_score":0.04897461,"about_ca_system_score_codex":0.0011069895,"about_ca_system_score_gemma":0.0000049729597,"threshold_uncertainty_score":0.9997551},"labels":[],"label_agreement":null},{"id":"W3151407988","doi":"10.1109/wcnc.2011.5779164","title":"Fair and efficient scheduling in wireless networks with successive interference cancellation","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary","funders":"","keywords":"Maximum throughput scheduling; Proportionally fair; Computer science; Round-robin scheduling; Fair-share scheduling; Scheduling (production processes); Dynamic priority scheduling; Rate-monotonic scheduling; Job shop scheduling; Greedy algorithm; Distributed computing; Computer network; Mathematical optimization; Algorithm; Mathematics; Quality of service","score_opus":0.00819358750271412,"score_gpt":0.18010028939339798,"score_spread":0.17190670189068386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3151407988","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":[0.3858416,0.00009495122,0.612186,0.0000021307717,0.0000499938,0.0000850177,1.7999372e-7,0.000096733755,0.0016433842],"genre_scores_gemma":[0.9844851,0.0000995833,0.015329766,0.000007695835,0.000022715509,0.000015656306,0.0000036902122,0.000022553726,0.0000132556515],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946934,0.000009552934,0.00013777337,0.00015176086,0.000052171472,0.0001793745],"domain_scores_gemma":[0.9997854,0.000028690863,0.000028154049,0.000089141686,0.000028465656,0.00004013084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003936653,0.00011385896,0.00011099489,0.00006370901,0.000024504185,0.00001373997,0.000053677915,0.0000517737,0.000020492465],"category_scores_gemma":[0.0000025762324,0.00010061479,0.0000061022165,0.00022520414,0.000031013722,0.000114834525,0.000018971841,0.00012158792,0.0000011556122],"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":[0.000019104164,0.0000062713307,0.0063041905,0.00001233145,0.000004497766,0.000002945621,0.00034220357,0.988074,0.000049132064,0.0006156025,0.0000012937959,0.004568395],"study_design_scores_gemma":[0.00023567589,0.000019324503,0.0030399587,0.00010694832,0.0000031043116,0.0000016294334,0.00012062193,0.995501,0.00081309024,0.000018919236,0.000001110011,0.00013865832],"about_ca_topic_score_codex":0.000039217466,"about_ca_topic_score_gemma":0.00038609776,"teacher_disagreement_score":0.5986435,"about_ca_system_score_codex":0.000052188654,"about_ca_system_score_gemma":0.0000061684523,"threshold_uncertainty_score":0.4102952},"labels":[],"label_agreement":null},{"id":"W3154193021","doi":"10.1109/cjece.2004.1425804","title":"Comparisons of link-adaptation-based scheduling algorithms for the WCDMA system with high-speed downlink packet access","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":9,"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; Proportionally fair; Maximum throughput scheduling; Scheduling (production processes); Fair queuing; Round-robin scheduling; Link adaptation; Computer network; Telecommunications link; Fairness measure; Code division multiple access; Generalized processor sharing; Fair-share scheduling; Distributed computing; Algorithm; Wireless; Fading; Channel (broadcasting); Throughput; Quality of service; Mathematical optimization; Telecommunications","score_opus":0.011983024697946602,"score_gpt":0.19678015948847077,"score_spread":0.18479713479052418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154193021","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":[0.019711485,0.0012058757,0.97849596,0.00014108622,0.00025478518,0.00014822048,0.0000061314313,0.000034136672,0.000002314838],"genre_scores_gemma":[0.8676176,0.000020741047,0.13199764,0.000016783319,0.0003136043,0.0000035300773,0.000004123788,0.000025575582,3.6258083e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992379,0.000006544694,0.00031051884,0.00008522585,0.000103966035,0.00025585914],"domain_scores_gemma":[0.999223,0.00022059734,0.00009136474,0.00008313716,0.00016260325,0.00021932353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008843431,0.00014071917,0.00025525628,0.00019846752,0.00007677351,0.000067697234,0.00018340345,0.000057972848,6.6222475e-7],"category_scores_gemma":[0.000013859893,0.00010749776,0.000049392413,0.00037082008,0.000021569567,0.00013171053,0.000004541022,0.00022585317,1.0740094e-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":[0.000009288215,0.000002975779,0.00008396583,0.000059333044,0.000067726134,0.000009509317,0.000048284313,0.99273074,0.000028051527,0.0010186476,0.000015516895,0.0059259594],"study_design_scores_gemma":[0.00077229546,0.00012810556,0.0006370683,0.00022197883,0.00003764035,0.00003889101,0.0000105204,0.9973996,0.00048648898,0.000016076097,0.00012203413,0.00012930117],"about_ca_topic_score_codex":0.00013378164,"about_ca_topic_score_gemma":0.00017503678,"teacher_disagreement_score":0.8479062,"about_ca_system_score_codex":0.00016165794,"about_ca_system_score_gemma":0.00018510188,"threshold_uncertainty_score":0.43836316},"labels":[],"label_agreement":null},{"id":"W3155509506","doi":"10.1109/jiot.2021.3072996","title":"Control-Aware Energy-Efficient Transmissions for Wireless Control Systems With Short Packets","year":2021,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":17,"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":"China Scholarship Council; Natural Science Basic Research Program of Shaanxi Province; National Research Foundation of Korea; China Postdoctoral Science Foundation; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Network packet; Aloha; Optimization problem; Mathematical optimization; Energy consumption; Transmission (telecommunications); Convex optimization; Wireless; Computer network; Throughput; Algorithm; Telecommunications; Engineering; Mathematics; Regular polygon","score_opus":0.0069671509044586764,"score_gpt":0.20763001977873502,"score_spread":0.20066286887427634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155509506","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":[0.042498678,0.0008351677,0.95498204,0.00006896692,0.001158134,0.0001749587,0.000024495577,0.000098657205,0.00015892694],"genre_scores_gemma":[0.9966139,0.00010270048,0.0026880607,0.00007205688,0.0002549959,0.000032131175,0.000009010516,0.000076320095,0.00015080518],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985426,0.00005436165,0.000552894,0.00018599513,0.00032135233,0.0003427903],"domain_scores_gemma":[0.9988853,0.00016826151,0.00014795444,0.00016128097,0.00046182703,0.00017541063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020409343,0.00023115343,0.00046375516,0.00009989953,0.00007112046,0.0000939466,0.00021320985,0.00011624696,0.000023036579],"category_scores_gemma":[0.000015525397,0.00019430232,0.00015532508,0.0001311984,0.000041551742,0.00020937303,0.00000607652,0.000297603,8.118243e-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":[0.0001493078,0.000048980655,0.00005553423,0.000086934044,0.00028269226,0.000054488894,0.00025747833,0.9882516,0.007375446,0.0002649878,0.00091160095,0.0022609443],"study_design_scores_gemma":[0.0018069787,0.000113733266,0.000009227309,0.000774023,0.00010290829,0.00043984703,0.00010909164,0.9792368,0.016318562,0.000035565172,0.0008325213,0.00022074183],"about_ca_topic_score_codex":0.00000509005,"about_ca_topic_score_gemma":0.000003904092,"teacher_disagreement_score":0.9541152,"about_ca_system_score_codex":0.0001229394,"about_ca_system_score_gemma":0.00006064815,"threshold_uncertainty_score":0.7923419},"labels":[],"label_agreement":null},{"id":"W3168573309","doi":"10.1109/twc.2021.3082080","title":"TSOR: Thompson Sampling-Based Opportunistic Routing","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Victoria","funders":"British Columbia Knowledge Development Fund; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Computer science; Regret; Routing (electronic design automation); Static routing; Destination-Sequenced Distance Vector routing; Link-state routing protocol; Upper and lower bounds; Network packet; Dynamic Source Routing; Routing protocol; Computer network; Mathematics; Machine learning","score_opus":0.046087478963180266,"score_gpt":0.2795717208126743,"score_spread":0.233484241849494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3168573309","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":[0.001852685,0.00018004265,0.9931674,0.0005645842,0.00047717124,0.00019683923,0.00009412265,0.0010184229,0.0024487437],"genre_scores_gemma":[0.94923925,0.0010843393,0.048871253,0.00015515005,0.000036148635,0.00015181233,0.00017137665,0.00010227307,0.00018838544],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986095,0.00012393028,0.00044234243,0.00027160323,0.00020830643,0.00034430844],"domain_scores_gemma":[0.99718136,0.0005138569,0.00007122669,0.0019155075,0.00017767533,0.00014040538],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011569142,0.00026146672,0.0002644441,0.00014808906,0.00059971126,0.00007665919,0.00053161086,0.00014677305,0.0001484048],"category_scores_gemma":[0.000010624283,0.0003299854,0.00013694061,0.00073487475,0.00011686088,0.00018800827,0.0000054243737,0.0005998106,0.00006114615],"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":[0.0000055029177,0.00016187993,0.000009265272,0.000025550144,0.000045373377,0.0000031195586,0.00009641554,0.9565137,0.003025763,0.0015364744,0.000046293186,0.038530678],"study_design_scores_gemma":[0.0003773519,0.000016697115,0.000032159944,0.00014272924,0.00005923126,0.0000098254695,0.00012015273,0.9855599,0.011328351,0.0000929375,0.0019108183,0.00034985438],"about_ca_topic_score_codex":0.0000057389657,"about_ca_topic_score_gemma":0.00014892108,"teacher_disagreement_score":0.94738656,"about_ca_system_score_codex":0.00021124505,"about_ca_system_score_gemma":0.00011476937,"threshold_uncertainty_score":0.99991524},"labels":[],"label_agreement":null},{"id":"W3183642464","doi":"10.18280/rces.080201","title":"Modelling and Development of a Radio Resource Control and Scheduling Algorithm for Long-Term Evolution (LTE) Uplink","year":2021,"lang":"en","type":"article","venue":"Review of Computer Engineering Studies","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Telecommunications link; Computer science; Base station; Scheduling (production processes); Orthogonal frequency-division multiple access; Computer network; Cellular network; Particle swarm optimization; Space-division multiple access; Real-time computing; Algorithm; Mathematical optimization; Orthogonal frequency-division multiplexing; Mathematics","score_opus":0.01382653164080798,"score_gpt":0.23925215579206677,"score_spread":0.22542562415125877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183642464","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":[0.0019457837,0.3478436,0.6499213,0.0000080922455,0.00006368647,0.00017190108,0.0000014766882,0.000043585795,5.6732415e-7],"genre_scores_gemma":[0.028984793,0.079435796,0.89141893,0.000007935901,0.000080541395,0.00003386996,0.000009089424,0.000027785441,0.0000012702792],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992074,0.000009355936,0.00041343734,0.00015128108,0.000078340316,0.00014022697],"domain_scores_gemma":[0.9995087,0.00014351086,0.00006870338,0.00009912236,0.00015071653,0.000029268935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016113374,0.00015533244,0.0005174439,0.0000501685,0.000034497112,0.0000056249796,0.000038714956,0.00003188031,1.7346426e-7],"category_scores_gemma":[0.00001724629,0.00016188211,0.00003804935,0.0001089117,0.000018364564,0.00006439467,0.000043496868,0.00006104552,6.083938e-8],"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":[8.999262e-7,0.000004677376,0.0000357994,0.011648288,0.00018958678,7.358782e-7,0.00012607693,0.9073332,0.000036906404,0.000045021257,0.000004977147,0.08057385],"study_design_scores_gemma":[0.00034867204,0.000011232283,0.000120440214,0.009364013,0.000056465688,0.0000074144164,0.00000617098,0.98953944,0.00021640175,0.0000055084297,0.00018514595,0.00013908563],"about_ca_topic_score_codex":5.9578124e-8,"about_ca_topic_score_gemma":7.9419806e-8,"teacher_disagreement_score":0.2684078,"about_ca_system_score_codex":0.00004461956,"about_ca_system_score_gemma":0.000012569479,"threshold_uncertainty_score":0.6601361},"labels":[],"label_agreement":null},{"id":"W3192352544","doi":"10.1109/icc42927.2021.9500923","title":"QoS-Aware Joint Component Carrier Selection and Resource Allocation for Carrier Aggregation in 5G","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":22,"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); University of Ottawa","funders":"","keywords":"Quality of service; Computer science; Throughput; Computer network; Resource allocation; Overhead (engineering); Selection (genetic algorithm); Resource management (computing); Distributed computing; Wireless; Telecommunications","score_opus":0.010520475847691882,"score_gpt":0.21374748562873172,"score_spread":0.20322700978103983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3192352544","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":[0.15331924,0.00060625456,0.8441916,0.0002547414,0.00024618194,0.00037857975,0.000016504333,0.00026441348,0.00072248204],"genre_scores_gemma":[0.9879472,0.00018873057,0.0109070735,0.00006052103,0.00013379322,0.00007898525,0.00028959365,0.000042298692,0.0003517762],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928975,0.000028661176,0.0002193992,0.0002063331,0.00009167044,0.00016421014],"domain_scores_gemma":[0.99964905,0.000040490988,0.000030447496,0.00010755147,0.00012533636,0.00004713648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007548405,0.00011231128,0.00013083388,0.0000655998,0.000057487836,0.000028427088,0.00002098124,0.00009063709,0.000021360835],"category_scores_gemma":[0.000036837017,0.000132808,0.000022834733,0.00027631942,0.000009308618,0.00016223612,0.000011226039,0.00008942765,0.0000010112727],"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":[0.000008967373,0.000008750876,0.00034060492,0.00006034972,0.000011521059,0.0000014688426,0.0001981081,0.97837096,0.008147313,0.00041979886,0.0005952331,0.011836923],"study_design_scores_gemma":[0.00048741043,0.000011452384,0.0018390936,0.000049439408,0.000010657587,0.0000108869945,0.00020631366,0.9299621,0.059392907,0.00019087656,0.0076764002,0.00016244613],"about_ca_topic_score_codex":0.00001273169,"about_ca_topic_score_gemma":0.00048328986,"teacher_disagreement_score":0.834628,"about_ca_system_score_codex":0.0001755062,"about_ca_system_score_gemma":0.000023470586,"threshold_uncertainty_score":0.5415753},"labels":[],"label_agreement":null},{"id":"W35404012","doi":"10.1007/978-0-387-48945-2_4","title":"Structural Results on Optimal Transmission Scheduling over Dynamical Fading Channels: A Constrained Markov Decision Process Approach","year":2007,"lang":"en","type":"book-chapter","venue":"The IMA volumes in mathematics and its applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Markov decision process; Fading; Computer science; Scheduling (production processes); Markov process; Process (computing); Mathematical optimization; Decision process; Markov chain; Mathematics; Computer network; Engineering; Channel (broadcasting); Statistics; Machine learning; Management science","score_opus":0.01707305443063959,"score_gpt":0.26046997323731685,"score_spread":0.24339691880667727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W35404012","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":[0.0020745138,0.0008059976,0.95468134,0.000018239585,0.000069527196,0.0016294803,0.00008211926,0.00019252895,0.040446274],"genre_scores_gemma":[0.6166238,0.0015922093,0.37414932,0.000038018887,0.0004344916,0.0004610187,0.0005178696,0.00039314822,0.0057900865],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99801934,0.0000075947146,0.0007946403,0.00047696749,0.00035871295,0.00034276483],"domain_scores_gemma":[0.99881035,0.0003870083,0.00021396515,0.00039181713,0.00008798636,0.00010888301],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003087302,0.00046668836,0.000456895,0.00023394555,0.00022062304,0.000085399355,0.00030921245,0.00042127402,0.000020482554],"category_scores_gemma":[0.000018808458,0.00039168348,0.00008451945,0.00017053413,0.00011476892,0.00010651227,0.000049171544,0.00069240324,0.0000068461],"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":[0.00004003694,0.000029352212,3.519031e-7,0.0004054834,0.000037104473,0.0000020618386,0.00056864007,0.9156056,0.000026327858,0.03767689,0.000025321733,0.04558282],"study_design_scores_gemma":[0.0004950924,0.000020650621,0.0000025061365,0.0006210963,0.00004125026,0.00002299826,0.000087720626,0.97650415,0.000010649567,0.02073224,0.001054418,0.00040725744],"about_ca_topic_score_codex":4.4678544e-7,"about_ca_topic_score_gemma":0.0000026849907,"teacher_disagreement_score":0.6145493,"about_ca_system_score_codex":0.00012954231,"about_ca_system_score_gemma":0.000024247782,"threshold_uncertainty_score":0.9998535},"labels":[],"label_agreement":null},{"id":"W363332807","doi":"10.1007/s11277-015-2726-2","title":"Navigation Data-Assisted Opportunistic Spectrum Scheduling for Network-Based UAV Systems: A Parallel Restless Bandits Formulation","year":2015,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Carleton University","funders":"","keywords":"Computer science; Scheduling (production processes); Real-time computing; Distributed computing; Mathematical optimization","score_opus":0.15744748804672287,"score_gpt":0.3244174627848363,"score_spread":0.16696997473811342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W363332807","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":[0.0070521627,0.0018048779,0.9874625,0.00055031484,0.00045849648,0.0010703048,0.00037187434,0.00068652164,0.0005429145],"genre_scores_gemma":[0.8988095,0.00016373709,0.08554579,0.00003635537,0.00031730963,0.00038573952,0.014589493,0.000104092105,0.000047987174],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808234,0.00014730665,0.0006109919,0.0003571957,0.00034373754,0.0004584258],"domain_scores_gemma":[0.9969323,0.00047137673,0.0002371052,0.0018303164,0.00030182532,0.00022703876],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00065352407,0.00029538962,0.00035738302,0.0001145803,0.0004882981,0.00014742698,0.0010642745,0.00018647237,0.0000041396734],"category_scores_gemma":[0.00008150853,0.00034227516,0.00007091706,0.0004964799,0.00009500937,0.00060707796,0.000177602,0.00032894532,0.000013542645],"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":[0.000050406026,0.00005343739,0.0002584785,0.000115319766,0.000061401755,0.0000011954011,0.00014376479,0.9856952,0.000060762748,0.010988166,0.0009861813,0.001585723],"study_design_scores_gemma":[0.0010423649,0.000037004713,0.00020824907,0.00028758438,0.00008896566,0.00000970192,0.00023510904,0.9929097,0.0000069996167,0.00046030994,0.004340231,0.00037374638],"about_ca_topic_score_codex":0.000035986544,"about_ca_topic_score_gemma":0.00014511231,"teacher_disagreement_score":0.90191674,"about_ca_system_score_codex":0.00037973945,"about_ca_system_score_gemma":0.00020836049,"threshold_uncertainty_score":0.9999029},"labels":[],"label_agreement":null},{"id":"W378615090","doi":"","title":"Token bank fair queuing: a new scheduling algorithm for wireless multimedia services: Research Articles","year":2004,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 British Columbia; Communications Research Centre Canada","funders":"","keywords":"Computer science; Computer network; Fair queuing; Quality of service; Scheduling (production processes); Proportionally fair; Token bucket; Wireless network; Wireless; Network packet; Algorithm; Distributed computing; Round-robin scheduling; Dynamic priority scheduling; Telecommunications","score_opus":0.035061693411313787,"score_gpt":0.3294789878201315,"score_spread":0.29441729440881775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W378615090","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":[0.03209643,0.00383774,0.9620469,0.00044021403,0.0009948708,0.00030853474,0.00001044829,0.00008882759,0.00017601578],"genre_scores_gemma":[0.8371157,0.0012059622,0.1608626,0.000021977592,0.00065946043,0.000025891219,0.000031379666,0.00004087376,0.000036157802],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812055,0.00010459046,0.00077031436,0.00010365132,0.0006835217,0.00021735516],"domain_scores_gemma":[0.9971953,0.00038246214,0.0003094134,0.00032184864,0.0016612062,0.0001297858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092656555,0.00013119617,0.00022744591,0.0003595592,0.00010247032,0.00020022907,0.0010723784,0.00009891167,0.000005759971],"category_scores_gemma":[0.000049407543,0.00013369082,0.00008722619,0.00026700372,0.000044774453,0.0007064877,0.00008253036,0.00036432888,0.000012812087],"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":[0.000024910789,0.00003566456,0.000054650256,0.000013490518,0.00013245596,0.0000030116605,0.0016520725,0.93583137,0.00094272837,0.0010818788,0.000099484634,0.060128313],"study_design_scores_gemma":[0.0016308952,0.000038560585,0.00005724498,0.00089567824,0.000011878485,0.000050569084,0.0017717641,0.9869596,0.0023897714,0.0013893067,0.004664976,0.00013980152],"about_ca_topic_score_codex":0.00009442367,"about_ca_topic_score_gemma":0.000030350348,"teacher_disagreement_score":0.80501926,"about_ca_system_score_codex":0.00046484167,"about_ca_system_score_gemma":0.00011432956,"threshold_uncertainty_score":0.5451753},"labels":[],"label_agreement":null},{"id":"W39533484","doi":"10.1016/b978-0-12-415844-3.00007-3","title":"Energy-Efficient Green Radio Communications for Delay Tolerant Applications","year":2012,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Energy (signal processing); Efficient energy use; Telecommunications; Electrical engineering; Engineering; Physics","score_opus":0.014827362648820761,"score_gpt":0.22454515784846693,"score_spread":0.20971779519964617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W39533484","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.6432527e-7,0.011680762,0.33934548,0.00002708869,0.00018789594,0.0010404356,0.00013779942,0.00039154908,0.6471885],"genre_scores_gemma":[0.0041744853,0.0027720993,0.05815931,0.00016699902,0.0012939965,0.003598556,0.0012964774,0.000610505,0.92792755],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986582,0.00001268722,0.00050640316,0.00028044262,0.00017182855,0.000370436],"domain_scores_gemma":[0.9979979,0.00013585121,0.0001592927,0.0014273779,0.00012958428,0.0001500277],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010467579,0.0004224938,0.00042551674,0.00014731567,0.00021784306,0.000024860548,0.0005733125,0.00032981735,0.00003570399],"category_scores_gemma":[0.0000016896244,0.00047350707,0.00020182756,0.00002757163,0.000112729664,0.000041991025,0.00011771299,0.00031020003,0.000049353057],"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":[0.0000029607165,0.000008806626,2.37465e-7,0.000069272384,0.00008998203,2.8903582e-7,0.00008911384,0.084250905,0.000011777555,0.04502661,0.00012068743,0.8703294],"study_design_scores_gemma":[0.00016424122,0.000008192042,4.0074806e-7,0.00010183005,0.00012591193,0.000006781518,0.0000021285216,0.15483014,0.00001762331,0.0023871972,0.8419382,0.00041737084],"about_ca_topic_score_codex":3.2857113e-7,"about_ca_topic_score_gemma":0.000019512001,"teacher_disagreement_score":0.86991197,"about_ca_system_score_codex":0.00022561364,"about_ca_system_score_gemma":0.000032672364,"threshold_uncertainty_score":0.99977165},"labels":[],"label_agreement":null},{"id":"W4210390153","doi":"10.1109/globecom46510.2021.9685672","title":"On Meeting a Maximum Delay Constraint","year":2021,"lang":"en","type":"article","venue":"2021 IEEE Global Communications Conference (GLOBECOM)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","funders":"","keywords":"Computer science; Probabilistic logic; Latency (audio); Scheduling (production processes); Constraint (computer-aided design); Network packet; Computational complexity theory; Mathematical optimization; Distributed computing; Real-time computing; Algorithm; Computer network; Mathematics; Artificial intelligence; Telecommunications","score_opus":0.026136278508383154,"score_gpt":0.2657200586599881,"score_spread":0.23958378015160495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210390153","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":[0.029521655,0.0033363241,0.555184,0.0019129992,0.001339761,0.0005637987,0.00034477003,0.0010365538,0.40676016],"genre_scores_gemma":[0.9468912,0.002556956,0.04984339,0.000216746,0.00005641043,0.000068430745,0.0002495339,0.00003395196,0.00008338937],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982834,0.00019279328,0.0004892379,0.0003402633,0.0002475186,0.00044678792],"domain_scores_gemma":[0.9970466,0.00024663957,0.00009798134,0.0020521905,0.00039602927,0.00016056215],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015603493,0.00030527473,0.00032392202,0.000051490246,0.00029595493,0.00015620913,0.00089657545,0.0001638032,0.00043389053],"category_scores_gemma":[0.00013904969,0.00036860685,0.00010777529,0.00077385147,0.00019285537,0.00021109269,0.00024105617,0.0004334306,0.00027156205],"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":[0.000013972057,0.00020435656,0.00046193023,0.000041731582,0.00017057921,0.000043086697,0.000166911,0.73907965,0.0010887487,0.16241232,0.00549263,0.09082407],"study_design_scores_gemma":[0.0010260013,0.000056334153,0.00039846607,0.00054886006,0.00008578131,0.00012883323,0.0008180634,0.94682544,0.0019324917,0.023735577,0.023350943,0.0010931862],"about_ca_topic_score_codex":0.000024384904,"about_ca_topic_score_gemma":0.000489134,"teacher_disagreement_score":0.91736954,"about_ca_system_score_codex":0.00036418386,"about_ca_system_score_gemma":0.00019313532,"threshold_uncertainty_score":0.99987656},"labels":[],"label_agreement":null},{"id":"W4210967211","doi":"10.32920/ryerson.14657934","title":"A Novel Control Theoretic Model for Resilient Packet Ring (RPR) Fairness","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Cisco Systems","keywords":"Fairness measure; Computer science; Network congestion; Computer network; Network packet; Bandwidth (computing); Queue; Max-min fairness; Bandwidth allocation; Throughput; Distributed computing; Packet loss; Telecommunications; Resource allocation","score_opus":0.01270974302198152,"score_gpt":0.23034465241978033,"score_spread":0.2176349093977988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210967211","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":[0.003423214,0.00051535794,0.9916125,0.000050172235,0.00064014655,0.00105032,0.000095656906,0.0007018474,0.001910819],"genre_scores_gemma":[0.814359,0.0002034763,0.18404476,0.000053783115,0.00015590726,0.0005650917,0.00021198195,0.00014880768,0.00025716375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984208,0.000016098182,0.0004298854,0.000512671,0.00019142097,0.00042914966],"domain_scores_gemma":[0.9988762,0.00014890646,0.00008501855,0.000618675,0.00017707606,0.00009411646],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015420766,0.00040733477,0.0005105665,0.000091641195,0.00005850548,0.000104157305,0.00026424092,0.00035102005,0.00003191924],"category_scores_gemma":[0.000058080474,0.00042916948,0.0001879247,0.00010040152,0.00003628122,0.00010219112,0.00018723347,0.00041273102,0.000002331461],"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":[0.000023339051,0.000025198055,0.000006170792,0.0004645799,0.00008853115,0.0000013776257,0.00022299794,0.98697984,0.00065539783,0.010376747,0.00012792133,0.0010278963],"study_design_scores_gemma":[0.0008767993,0.0000062983027,0.000009569143,0.00025714777,0.00006838536,0.0000023474536,0.000068369874,0.9934895,0.00054280827,0.0041882712,0.000018430195,0.0004720759],"about_ca_topic_score_codex":0.0000034446268,"about_ca_topic_score_gemma":0.000029570896,"teacher_disagreement_score":0.8109358,"about_ca_system_score_codex":0.00021068602,"about_ca_system_score_gemma":0.000063227475,"threshold_uncertainty_score":0.999816},"labels":[],"label_agreement":null},{"id":"W4211037983","doi":"10.32920/ryerson.14657925","title":"Power allocation in OFDM-based cognitive radio systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Subcarrier; Underlay; Orthogonal frequency-division multiplexing; Computer science; Transmitter power output; Cognitive radio; Mathematical optimization; Transmission (telecommunications); Algorithm; Interference (communication); Transmitter; Channel (broadcasting); Telecommunications; Wireless; Signal-to-noise ratio (imaging); Mathematics","score_opus":0.008500526822760798,"score_gpt":0.2205385520084981,"score_spread":0.21203802518573728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211037983","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":[0.028827393,0.0019481836,0.96041167,0.000019315195,0.0012770869,0.00061717554,0.000011205232,0.00047652717,0.0064114262],"genre_scores_gemma":[0.9927685,0.00020516393,0.005762146,0.000025985817,0.00007804661,0.00021832401,0.0007483687,0.00007909331,0.000114317685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887794,0.000057019748,0.00035619852,0.000327978,0.00016633705,0.00021453119],"domain_scores_gemma":[0.999388,0.00009461248,0.00006334317,0.00026624886,0.00014023612,0.000047555586],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010241293,0.00025440278,0.00032883923,0.00016780474,0.0000146121665,0.00007776475,0.0001075332,0.00031998908,0.00009116129],"category_scores_gemma":[0.000035275283,0.0003008791,0.000054299442,0.00023619147,0.00001596135,0.0000979037,0.00005950939,0.00043908381,0.000012664721],"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":[0.0000051706284,0.000019351095,0.0001907741,0.00022345598,0.00003123525,0.000012453067,0.00013431584,0.99875116,0.00005753254,0.00008211404,0.000100869,0.0003915382],"study_design_scores_gemma":[0.00033951507,0.0000056215,0.0004704303,0.0009119094,0.000012622359,0.0000013247393,0.00026693314,0.9969656,0.0006371178,0.000013214022,0.000053790776,0.00032194378],"about_ca_topic_score_codex":0.000033553435,"about_ca_topic_score_gemma":0.000047978305,"teacher_disagreement_score":0.96394116,"about_ca_system_score_codex":0.0003062264,"about_ca_system_score_gemma":0.00007498705,"threshold_uncertainty_score":0.9999443},"labels":[],"label_agreement":null},{"id":"W4211141123","doi":"10.32920/ryerson.14657934.v1","title":"A Novel Control Theoretic Model for Resilient Packet Ring (RPR) Fairness","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Cisco Systems","keywords":"Fairness measure; Computer science; Network congestion; Computer network; Max-min fairness; Network packet; Bandwidth (computing); Queue; Bandwidth allocation; Throughput; Distributed computing; Packet loss; Telecommunications; Resource allocation","score_opus":0.01270974302198152,"score_gpt":0.23034465241978033,"score_spread":0.2176349093977988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211141123","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":[0.003423214,0.00051535794,0.9916125,0.000050172235,0.00064014655,0.00105032,0.000095656906,0.0007018474,0.001910819],"genre_scores_gemma":[0.814359,0.0002034763,0.18404476,0.000053783115,0.00015590726,0.0005650917,0.00021198195,0.00014880768,0.00025716375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984208,0.000016098182,0.0004298854,0.000512671,0.00019142097,0.00042914966],"domain_scores_gemma":[0.9988762,0.00014890646,0.00008501855,0.000618675,0.00017707606,0.00009411646],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015420766,0.00040733477,0.0005105665,0.000091641195,0.00005850548,0.000104157305,0.00026424092,0.00035102005,0.00003191924],"category_scores_gemma":[0.000058080474,0.00042916948,0.0001879247,0.00010040152,0.00003628122,0.00010219112,0.00018723347,0.00041273102,0.000002331461],"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":[0.000023339051,0.000025198055,0.000006170792,0.0004645799,0.00008853115,0.0000013776257,0.00022299794,0.98697984,0.00065539783,0.010376747,0.00012792133,0.0010278963],"study_design_scores_gemma":[0.0008767993,0.0000062983027,0.000009569143,0.00025714777,0.00006838536,0.0000023474536,0.000068369874,0.9934895,0.00054280827,0.0041882712,0.000018430195,0.0004720759],"about_ca_topic_score_codex":0.0000034446268,"about_ca_topic_score_gemma":0.000029570896,"teacher_disagreement_score":0.8109358,"about_ca_system_score_codex":0.00021068602,"about_ca_system_score_gemma":0.000063227475,"threshold_uncertainty_score":0.999816},"labels":[],"label_agreement":null},{"id":"W4211185180","doi":"10.32920/ryerson.14657925.v1","title":"Power allocation in OFDM-based cognitive radio systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Subcarrier; Underlay; Orthogonal frequency-division multiplexing; Computer science; Cognitive radio; Transmitter power output; Transmission (telecommunications); Mathematical optimization; Algorithm; Transmitter; Interference (communication); Channel (broadcasting); Wireless; Telecommunications; Signal-to-noise ratio (imaging); Mathematics","score_opus":0.008500526822760798,"score_gpt":0.2205385520084981,"score_spread":0.21203802518573728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211185180","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":[0.028827393,0.0019481836,0.96041167,0.000019315195,0.0012770869,0.00061717554,0.000011205232,0.00047652717,0.0064114262],"genre_scores_gemma":[0.9927685,0.00020516393,0.005762146,0.000025985817,0.00007804661,0.00021832401,0.0007483687,0.00007909331,0.000114317685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887794,0.000057019748,0.00035619852,0.000327978,0.00016633705,0.00021453119],"domain_scores_gemma":[0.999388,0.00009461248,0.00006334317,0.00026624886,0.00014023612,0.000047555586],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010241293,0.00025440278,0.00032883923,0.00016780474,0.0000146121665,0.00007776475,0.0001075332,0.00031998908,0.00009116129],"category_scores_gemma":[0.000035275283,0.0003008791,0.000054299442,0.00023619147,0.00001596135,0.0000979037,0.00005950939,0.00043908381,0.000012664721],"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":[0.0000051706284,0.000019351095,0.0001907741,0.00022345598,0.00003123525,0.000012453067,0.00013431584,0.99875116,0.00005753254,0.00008211404,0.000100869,0.0003915382],"study_design_scores_gemma":[0.00033951507,0.0000056215,0.0004704303,0.0009119094,0.000012622359,0.0000013247393,0.00026693314,0.9969656,0.0006371178,0.000013214022,0.000053790776,0.00032194378],"about_ca_topic_score_codex":0.000033553435,"about_ca_topic_score_gemma":0.000047978305,"teacher_disagreement_score":0.96394116,"about_ca_system_score_codex":0.0003062264,"about_ca_system_score_gemma":0.00007498705,"threshold_uncertainty_score":0.9999443},"labels":[],"label_agreement":null},{"id":"W4232145095","doi":"10.32920/ryerson.14653935","title":"Optimal Resource Allocation For Video Streaming Over Cognitive Radio Network Via Geometric Programming","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Cognitive radio; Computer science; Computer network; Quality of service; Channel (broadcasting); Resource allocation; Queueing theory; Transmission (telecommunications); Network packet; Transmitter power output; Video quality; Wireless; Wireless network; Radio resource management; Real-time computing; Transmitter; Telecommunications","score_opus":0.010237174510221266,"score_gpt":0.23674710977563831,"score_spread":0.22650993526541705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232145095","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":[0.01528525,0.0031956816,0.97754306,0.000012383387,0.0007021569,0.0017432261,0.000017362046,0.0009839867,0.00051691884],"genre_scores_gemma":[0.528718,0.00027795107,0.4655296,0.00005257128,0.0013480565,0.0009601912,0.0026677412,0.00027019993,0.00017569723],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997564,0.000052138996,0.0006069738,0.00074805185,0.00030463177,0.00072415994],"domain_scores_gemma":[0.99842215,0.0005290054,0.00021906519,0.00041454087,0.0002794118,0.00013582055],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028415906,0.00054370996,0.0005761436,0.0003093354,0.00015031475,0.00024234952,0.00023527986,0.00044337517,0.00005796396],"category_scores_gemma":[0.0001585753,0.00065537915,0.00022029404,0.0010305163,0.000038535352,0.0002456876,0.00028404364,0.00064645853,0.0000033184065],"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":[0.00002510728,0.000026087142,0.00013100206,0.00031853636,0.00022691493,0.0000055519654,0.0001204047,0.8848559,0.000016953127,0.000025819869,0.0005218321,0.113725886],"study_design_scores_gemma":[0.00055860245,0.000036356752,0.00025143696,0.0006432611,0.0001766383,0.0000067861765,0.00019598888,0.99427605,0.0004854522,0.000038956103,0.002609077,0.0007213971],"about_ca_topic_score_codex":0.000016140979,"about_ca_topic_score_gemma":0.00002558792,"teacher_disagreement_score":0.51343274,"about_ca_system_score_codex":0.00037777846,"about_ca_system_score_gemma":0.00006045962,"threshold_uncertainty_score":0.99958974},"labels":[],"label_agreement":null},{"id":"W4232628124","doi":"10.1109/infcom.1998.665093","title":"Forwarding state reduction for sparse mode multicast communication","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":50,"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","funders":"","keywords":"Multicast; Reduction (mathematics); Computer science; Computer network; State (computer science); Mode (computer interface); Algorithm; Operating system; Mathematics","score_opus":0.022480437477718232,"score_gpt":0.23952198182583068,"score_spread":0.21704154434811246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232628124","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":[0.009506109,0.00019143747,0.9859243,0.00005993037,0.00012956701,0.00027473114,0.0000048557977,0.0004671905,0.003441888],"genre_scores_gemma":[0.81612664,0.000585909,0.18250908,0.0000069333432,0.00004040305,0.000060823528,0.000028246586,0.000033324817,0.0006086139],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954736,0.0000085118,0.00015319054,0.000088711524,0.00005019437,0.00015200934],"domain_scores_gemma":[0.99965674,0.000034850276,0.000022575101,0.00021300868,0.000041157768,0.000031700165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004197347,0.00008130041,0.000081932514,0.000042075688,0.000073318675,0.000019194253,0.0000666364,0.000033783836,0.000039568058],"category_scores_gemma":[0.000011406626,0.00008948166,0.000027382317,0.00010117502,0.000013698226,0.0002749847,0.000011305257,0.000058090136,0.0000193218],"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":[0.0000028731265,0.0000080403615,0.000005664113,0.000011807584,0.000008952911,4.6112437e-8,0.00017388449,0.9672432,0.0010071751,0.00034621605,0.0018463979,0.029345762],"study_design_scores_gemma":[0.00024392625,0.0000071280847,0.000008089111,0.000012648119,0.000006312755,0.0000019880179,0.00004095698,0.9941718,0.0030556957,0.00049266824,0.0018533372,0.000105426065],"about_ca_topic_score_codex":0.0000034068482,"about_ca_topic_score_gemma":0.0000069455614,"teacher_disagreement_score":0.80662054,"about_ca_system_score_codex":0.000067185596,"about_ca_system_score_gemma":7.88167e-7,"threshold_uncertainty_score":0.36489564},"labels":[],"label_agreement":null},{"id":"W4232791626","doi":"10.1017/cbo9780511760112.009","title":"WiMAX","year":2011,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 du Québec à Montréal","funders":"","keywords":"WiMAX; Interoperability; Computer network; Telecommunications; Metropolitan area; Metropolitan area network; Wireless; Computer science; Geography; Local area network; World Wide Web","score_opus":0.015410952505597823,"score_gpt":0.1605952935353814,"score_spread":0.1451843410297836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232791626","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000009400806,0.00024987283,0.04659789,6.903965e-7,0.00034734845,0.00022466091,0.000086683,0.00072492554,0.9517585],"genre_scores_gemma":[0.00088812463,0.00061337545,0.00089734426,0.000013003472,0.00014522516,5.956569e-7,0.000072315604,0.00013228766,0.99723774],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991873,0.0000075712132,0.00014089732,0.00028618492,0.0001295295,0.00024851688],"domain_scores_gemma":[0.99927413,0.000020287824,0.00007609358,0.0004354444,0.00007168627,0.00012237206],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00002275014,0.00035212608,0.0003003608,0.00013219091,0.000073203475,0.000013907052,0.00031186923,0.00036872047,0.000013405581],"category_scores_gemma":[0.0000014705481,0.00047867146,0.00012013992,0.000006494846,0.00010029668,0.00010049587,0.00012438072,0.00039855813,0.000040029925],"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":[0.000025154886,0.0000025313063,4.973379e-7,0.00009350846,0.00013968788,0.00015578784,0.000029419409,0.010398107,0.000019388532,0.94708675,0.037775323,0.0042738267],"study_design_scores_gemma":[0.00024986765,0.000014397343,0.0000024589199,0.00012189176,0.00010891508,0.0000075983385,0.0000030486885,0.0041501247,0.00023792638,0.00002132717,0.99455816,0.00052426296],"about_ca_topic_score_codex":0.000008627556,"about_ca_topic_score_gemma":7.5793685e-7,"teacher_disagreement_score":0.9567829,"about_ca_system_score_codex":0.00019775007,"about_ca_system_score_gemma":0.000019806612,"threshold_uncertainty_score":0.99976647},"labels":[],"label_agreement":null},{"id":"W4232862337","doi":"10.1109/cdc.2012.6426002","title":"On Games with Coupled Constraints","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Mathematical optimization; Minification; Computer science; Minimax; Maximization; Nash equilibrium; Dual (grammatical number); Game theory; Utility maximization problem; Constraint (computer-aided design); Set (abstract data type); Mathematical economics; Mathematics; Utility maximization","score_opus":0.005014232096269824,"score_gpt":0.19035386993108425,"score_spread":0.1853396378348144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232862337","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":[0.07725044,0.00006637372,0.87074953,0.00001057225,0.0001297879,0.00008515238,7.131074e-7,0.00045634384,0.051251065],"genre_scores_gemma":[0.98466796,0.000015658361,0.015027194,0.000047015794,0.00004991634,0.0000069517328,0.0000045600327,0.00001952869,0.0001611937],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969584,0.000002528944,0.00004846536,0.00004150446,0.0000562545,0.00015542626],"domain_scores_gemma":[0.99983084,0.000030444622,0.0000067500346,0.000076236094,0.000009156816,0.00004659463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000020261577,0.00006461422,0.00005532404,0.00001919698,0.000012863369,0.0000049110317,0.000023549284,0.000022363101,0.00034251623],"category_scores_gemma":[0.0000035329754,0.000050406143,0.0000066777748,0.00006355162,0.000024749692,0.00010072594,0.0000026354255,0.00004475316,0.000069270696],"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":[0.0000046787886,0.000009083648,0.0005542432,0.000004382285,0.000010154027,4.776096e-7,0.00003875036,0.98683363,0.00011513101,0.007914219,0.0005448138,0.003970412],"study_design_scores_gemma":[0.00058887806,0.000044466848,0.0018290125,0.000037074402,0.000009103797,0.000010561735,0.00006884977,0.9931117,0.0027583898,0.00012374455,0.0011271922,0.0002909945],"about_ca_topic_score_codex":2.860306e-7,"about_ca_topic_score_gemma":0.0000010733012,"teacher_disagreement_score":0.90741754,"about_ca_system_score_codex":0.000019618006,"about_ca_system_score_gemma":0.0000019436272,"threshold_uncertainty_score":0.37503123},"labels":[],"label_agreement":null},{"id":"W4234289156","doi":"10.22215/etd/2005-10161","title":"Evaluation of two wireless communication standards for public safety and security (PSS) network","year":2005,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Library and Archives Canada","funders":"","keywords":"Wireless; Telecommunications; Computer security; Computer science; Political science","score_opus":0.01672284282257976,"score_gpt":0.3045684648349541,"score_spread":0.28784562201237435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234289156","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":[0.101058416,0.04057674,0.69964355,0.00015711023,0.002114952,0.00813232,0.00084140303,0.0014125978,0.14606293],"genre_scores_gemma":[0.9734313,0.0072088693,0.012029369,0.000009345662,0.00027666282,0.00024229572,0.006508579,0.0001283323,0.00016523266],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978558,0.00014739778,0.00064720726,0.0002571432,0.00080728525,0.0002851981],"domain_scores_gemma":[0.99715936,0.00017912958,0.0002852085,0.0004460052,0.0018628351,0.000067473775],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0021815419,0.00030086644,0.00045363107,0.000120894925,0.00015884354,0.000046157005,0.00019402204,0.00030667576,0.00010294508],"category_scores_gemma":[0.0001029128,0.00034295494,0.00007404807,0.0002929033,0.000034785768,0.00035269995,0.000016753638,0.00024590915,6.128567e-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":[0.00006783534,0.000017577679,0.000027005817,0.00024664387,0.000117887364,2.1108344e-8,0.00034685506,0.8360936,0.000028543038,0.010284984,0.00092940975,0.15183964],"study_design_scores_gemma":[0.0013660438,0.000022615035,0.00020542089,0.0002465515,0.00028419,5.8511506e-7,0.00022786779,0.9883483,0.00033342186,0.005254683,0.0033625343,0.00034776525],"about_ca_topic_score_codex":0.00000836958,"about_ca_topic_score_gemma":0.0032357364,"teacher_disagreement_score":0.8723729,"about_ca_system_score_codex":0.00048723063,"about_ca_system_score_gemma":0.0002118883,"threshold_uncertainty_score":0.99990225},"labels":[],"label_agreement":null},{"id":"W4234496406","doi":"10.32920/ryerson.14644947","title":"Nonconvex and game theory optimization for resource allocation in wireless communications","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; University of Manitoba; University of Toronto","funders":"","keywords":"Mathematical optimization; Computer science; Stackelberg competition; Resource allocation; Optimization problem; Computational complexity theory; Wireless; Game theory; Algorithm; Mathematics; Computer network; Telecommunications","score_opus":0.014537189462751558,"score_gpt":0.24646698501917075,"score_spread":0.23192979555641918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234496406","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":[0.003971849,0.0015945896,0.9908767,0.00018238185,0.00014533682,0.000843988,0.000013894591,0.0003237589,0.0020475239],"genre_scores_gemma":[0.730359,0.0042631985,0.26195887,0.00007462255,0.00007026149,0.0005749148,0.002471983,0.000107414926,0.00011971813],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885875,0.00010540139,0.00041264854,0.0003295526,0.00009290686,0.00020075504],"domain_scores_gemma":[0.9985579,0.0003283076,0.000093236864,0.00085262425,0.00011724285,0.000050688057],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028580683,0.00024327515,0.00030665612,0.00016087005,0.000051083083,0.0000929709,0.00029916997,0.00033711616,0.000018969571],"category_scores_gemma":[0.00004909259,0.0002978897,0.000046798614,0.00020500836,0.000066203895,0.00016209323,0.00034075548,0.00038551766,5.8688744e-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":[0.000009445254,0.00002072064,0.000046366586,0.00021390225,0.00002622305,2.5968757e-7,0.00045844677,0.9813575,0.00003791845,0.003981201,0.00005590196,0.013792101],"study_design_scores_gemma":[0.00033113346,0.000006057349,0.000059497568,0.00024929913,0.000024587489,0.0000014022326,0.00033222107,0.99725443,0.00023886566,0.0009050565,0.00030330828,0.00029411627],"about_ca_topic_score_codex":0.000007611498,"about_ca_topic_score_gemma":0.000096229516,"teacher_disagreement_score":0.7289178,"about_ca_system_score_codex":0.00016764463,"about_ca_system_score_gemma":0.00004198562,"threshold_uncertainty_score":0.9999473},"labels":[],"label_agreement":null},{"id":"W4236605977","doi":"10.1007/978-3-030-62124-7_17","title":"Multimedia Over Wireless and Mobile Networks","year":2021,"lang":"en","type":"book-chapter","venue":"Texts in computer science","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Computer network; Computer science; Wireless network; Cordless; Wireless; Bluetooth; Wi-Fi array; Personal Communications Service; Multimedia; Telecommunications","score_opus":0.006472369058421839,"score_gpt":0.21263253964490933,"score_spread":0.2061601705864875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236605977","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":[0.0015019306,0.0035042602,0.9835964,0.0000040975674,0.0017824952,0.00032678197,0.0000043465084,0.00027253758,0.009007157],"genre_scores_gemma":[0.538714,0.01566789,0.41052943,0.00050746923,0.0038115208,0.00013828647,0.00013601029,0.00060280465,0.029892562],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851763,0.000006149476,0.00027830197,0.00054735335,0.000290353,0.0003601979],"domain_scores_gemma":[0.9992751,0.000093992705,0.00005922843,0.00039947545,0.00006024663,0.00011196748],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015778435,0.00029413786,0.00032039135,0.00020837283,0.000069048074,0.0001040544,0.00034583962,0.00019816749,0.00005557842],"category_scores_gemma":[0.0000026851963,0.00032972143,0.000031763433,0.00021070476,0.0003396755,0.00027999427,0.0003070417,0.00041614723,0.000007473644],"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":[6.369764e-7,0.000002980376,0.000015976442,0.000019426026,0.000003650786,0.000024300805,0.00007124796,0.75589746,0.000007280305,0.0008695557,0.00011853014,0.24296898],"study_design_scores_gemma":[0.00015206095,0.000014142567,0.00013140602,0.0003050309,0.000003923699,0.000011090857,5.455646e-7,0.9958949,0.000017564906,0.00030834725,0.0028154023,0.0003455739],"about_ca_topic_score_codex":0.0000013044056,"about_ca_topic_score_gemma":0.000011149813,"teacher_disagreement_score":0.57306695,"about_ca_system_score_codex":0.0001504732,"about_ca_system_score_gemma":0.0000446201,"threshold_uncertainty_score":0.9999155},"labels":[],"label_agreement":null},{"id":"W4236719087","doi":"10.4108/icst.wiopt2008.2988","title":"A Markovian Model for Mobile Cellular Networks with QoS Differentiation","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Nortel (Canada)","funders":"","keywords":"Computer science; Quality of service; General Packet Radio Service; Cellular network; Computer network; Markov process; Distributed computing; Mobile QoS; Mobile telephony; Enhanced Data Rates for GSM Evolution; Mobile radio; Service (business); Telecommunications; Wireless; Mathematics","score_opus":0.006863870767987023,"score_gpt":0.17119836582048242,"score_spread":0.1643344950524954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236719087","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":[0.035098188,0.00010997626,0.96328264,0.0000035409873,0.00009384466,0.00045148982,0.000002539551,0.00039759133,0.00056016754],"genre_scores_gemma":[0.91055787,0.00012532914,0.08813267,0.000017418371,0.00012775438,0.00025138663,0.0000908156,0.000056602534,0.00064016454],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994545,0.000004194076,0.00012486188,0.00013268535,0.00007519195,0.00020856371],"domain_scores_gemma":[0.99972665,0.000021755995,0.000021794505,0.00014517084,0.000037697704,0.000046951027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000018667324,0.00012632125,0.000115825635,0.00003575581,0.000077110475,0.000009222638,0.00005619157,0.00006424209,0.00002064062],"category_scores_gemma":[0.0000013205402,0.00011225735,0.000029329216,0.0001092802,0.000015050053,0.00014436993,0.0000075285798,0.00006182251,0.000001965011],"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":[0.000016208825,0.000011077261,0.00019616827,0.000013228821,0.000014050685,7.3637915e-7,0.000067284745,0.9975748,0.00016449548,0.000104324994,0.00081270456,0.0010248951],"study_design_scores_gemma":[0.0003819331,0.000027866769,0.00006614768,0.000008560697,0.000010028057,0.0000019991194,0.0000074215695,0.99861425,0.0005778453,0.00003301018,0.000110186906,0.00016073757],"about_ca_topic_score_codex":7.211635e-7,"about_ca_topic_score_gemma":0.000009472574,"teacher_disagreement_score":0.8754597,"about_ca_system_score_codex":0.000041123574,"about_ca_system_score_gemma":0.0000060352945,"threshold_uncertainty_score":0.4577722},"labels":[],"label_agreement":null},{"id":"W4237326313","doi":"10.32920/ryerson.14664714.v1","title":"Subcarrier availability in OFDM systems with imperfect carrier synchronization in deep fading noisy doppler channels","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Fading; Orthogonal frequency-division multiplexing; Additive white Gaussian noise; Subcarrier; Carrier frequency offset; Computer science; Electronic engineering; Channel (broadcasting); Frequency offset; Synchronization (alternating current); Telecommunications; Engineering","score_opus":0.007081407438342293,"score_gpt":0.20618127613579706,"score_spread":0.19909986869745477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237326313","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":[0.3815339,0.0019051874,0.6124396,0.000010604222,0.0013026512,0.0013035262,0.000016116053,0.00040182675,0.0010865998],"genre_scores_gemma":[0.99498343,0.00042053542,0.0031962092,0.000010707815,0.00021386545,0.0004596762,0.00044323716,0.00017705193,0.00009529151],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99724877,0.00016534886,0.0007975559,0.0008518346,0.0003333531,0.0006031557],"domain_scores_gemma":[0.9987111,0.00009980125,0.00012963268,0.0007548699,0.00018898076,0.0001156097],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000392648,0.0005823699,0.00082049746,0.00037902745,0.000041026204,0.0001890911,0.00024320227,0.0006060963,0.00014807566],"category_scores_gemma":[0.000063289626,0.00059315946,0.000071014256,0.0009352895,0.000046045654,0.000379902,0.000216998,0.0009547195,0.0000048388542],"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":[0.000014835763,0.00002076947,0.02122851,0.000838091,0.000044340402,0.00003787293,0.0009936915,0.9762355,0.00006527362,0.000034320637,0.000023282886,0.00046349913],"study_design_scores_gemma":[0.00052175595,0.000015898388,0.0012123173,0.0008477568,0.000020436637,0.000013393553,0.00045930297,0.99588466,0.00031423493,0.00001913078,0.00002668521,0.0006644446],"about_ca_topic_score_codex":0.0004494282,"about_ca_topic_score_gemma":0.0025645904,"teacher_disagreement_score":0.6134495,"about_ca_system_score_codex":0.0015397939,"about_ca_system_score_gemma":0.00013658487,"threshold_uncertainty_score":0.99965197},"labels":[],"label_agreement":null},{"id":"W4239684000","doi":"10.22215/etd/2010-06156","title":"Optimal packet scheduling in emerging wireless networks","year":2010,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Library and Archives Canada","funders":"","keywords":"Computer science; Scheduling (production processes); Network packet; Computer network; Telecommunications; Engineering; Operations management","score_opus":0.004379617590606648,"score_gpt":0.22808979565154,"score_spread":0.22371017806093335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239684000","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":[0.6145354,0.001102386,0.3667951,0.000008071776,0.0036263347,0.00042578936,0.0000033364718,0.0009886868,0.012514932],"genre_scores_gemma":[0.9338387,0.0016923675,0.05951821,0.000017299366,0.00070850237,0.00011752151,0.002219874,0.00036008164,0.0015274215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983282,0.000017598915,0.00052897556,0.00037661227,0.00020091012,0.0005477089],"domain_scores_gemma":[0.9993736,0.000055992994,0.00010108015,0.00031006412,0.00006793101,0.000091306676],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012313272,0.00045808672,0.00045343867,0.00030385636,0.000063582615,0.00006125529,0.00023872296,0.0008485978,0.00019231542],"category_scores_gemma":[0.000015511485,0.00053652923,0.00008498555,0.0005126185,0.000014364057,0.00025266167,0.000017982957,0.0015193543,0.000019985951],"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":[0.000016139049,0.000010217926,0.00010335621,0.00009388573,0.0000214513,0.0000097699485,0.00020086164,0.97976965,0.00039043464,0.0001646603,0.0000977932,0.019121788],"study_design_scores_gemma":[0.00024832843,0.0000060083867,0.0002673986,0.00026476654,0.000016325894,0.0000016930625,0.00035277798,0.99718755,0.000838704,0.00002453501,0.00022582812,0.0005660714],"about_ca_topic_score_codex":0.000012283678,"about_ca_topic_score_gemma":0.0012007786,"teacher_disagreement_score":0.31930333,"about_ca_system_score_codex":0.0001039299,"about_ca_system_score_gemma":0.000027357088,"threshold_uncertainty_score":0.99970865},"labels":[],"label_agreement":null},{"id":"W4241481467","doi":"10.4018/9781599048994.ch023","title":"End-to-End Security Comparisons Between IEEE 802.16e and 3G Technologies","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"","keywords":"Computer science; Computer network; WiMAX; Implementation; Cellular network; IEEE 802; Protocol (science); Authorization; Computer security; Telecommunications; Wireless; Quality of service","score_opus":0.01949258935346949,"score_gpt":0.22746788414300426,"score_spread":0.20797529478953478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241481467","genre_codex":"other","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":[0.00061871466,0.0013055628,0.06173643,0.000023588167,0.00052147754,0.0006241203,0.0005032283,0.0025919816,0.9320749],"genre_scores_gemma":[0.98753464,0.00013646335,0.008591418,0.000038125352,0.0002933778,0.0000392452,0.000029066345,0.00015442078,0.0031832259],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983538,0.000008640293,0.00042600025,0.0004988194,0.00023916281,0.000473576],"domain_scores_gemma":[0.9990478,0.00004704874,0.000121797166,0.00056523754,0.0000648087,0.00015329332],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005785223,0.0006036705,0.000707901,0.00013418782,0.00009440163,0.00005054907,0.000365077,0.0007881435,0.000021216212],"category_scores_gemma":[0.000010290099,0.0006781703,0.000097431126,0.000041420415,0.00018461983,0.00007167281,0.00020018869,0.0005914917,0.00009000441],"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":[0.000028155286,0.0000088631805,0.00053902,0.0002034612,0.00042941817,0.000051985753,0.00021474868,0.015536786,0.000026664226,0.9165748,0.009149229,0.057236895],"study_design_scores_gemma":[0.0010676665,0.00028307032,0.00045393244,0.0011044899,0.0006414924,0.00006791722,0.00008212164,0.005631967,0.0015496139,0.7613435,0.22393805,0.0038362236],"about_ca_topic_score_codex":0.000022707487,"about_ca_topic_score_gemma":0.00010248453,"teacher_disagreement_score":0.98691595,"about_ca_system_score_codex":0.0002389063,"about_ca_system_score_gemma":0.000028749348,"threshold_uncertainty_score":0.999567},"labels":[],"label_agreement":null},{"id":"W4242178347","doi":"10.1002/wcm.648","title":"An analytical model for reverse data channel scheduling techniques in cdma2000 1xEV‐DO","year":2008,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"CDMA2000; Computer science; Scheduling (production processes); Computer network; Markov chain; Markov model; Markov process; Wireless; Network packet; Real-time computing; Code division multiple access; Telecommunications; Mathematical optimization","score_opus":0.0629657462963575,"score_gpt":0.3204124867766084,"score_spread":0.2574467404802509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242178347","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":[0.1040995,0.0011532612,0.8936687,0.00003181041,0.000026888363,0.000475941,0.000029066377,0.00036081087,0.00015401411],"genre_scores_gemma":[0.74165237,0.0030030068,0.25493065,0.00002213982,0.000039303402,0.000074646014,0.00023184906,0.000039314724,0.0000067449487],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894357,0.000043869863,0.0003736332,0.00029336583,0.00007727598,0.00026828636],"domain_scores_gemma":[0.99794036,0.00016794799,0.000060643975,0.0016805662,0.00007289078,0.000077616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030133832,0.00016545312,0.00024534657,0.00013858444,0.0003303459,0.000035605353,0.0008227666,0.00010384492,8.88575e-7],"category_scores_gemma":[0.000016667595,0.00019584013,0.000024211971,0.00028790295,0.00012190293,0.00038552543,0.00038766942,0.0002567261,5.394865e-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":[0.000003972193,0.00005890201,0.00019441736,0.000027195929,0.00000840763,6.12255e-7,0.0006316486,0.94428605,0.00013733485,0.0005881022,0.000040575935,0.054022793],"study_design_scores_gemma":[0.00022194642,0.000020438285,0.000031685155,0.0001126586,0.000008980601,0.000008403656,0.0001839961,0.9985709,0.000051762174,0.00010967091,0.00046418936,0.0002153629],"about_ca_topic_score_codex":0.00001452119,"about_ca_topic_score_gemma":0.000030367666,"teacher_disagreement_score":0.6387381,"about_ca_system_score_codex":0.00005874563,"about_ca_system_score_gemma":0.000029092493,"threshold_uncertainty_score":0.79861283},"labels":[],"label_agreement":null},{"id":"W4242412790","doi":"10.1002/wcm.910","title":"Per‐user service model for opportunistic scheduling scheme over fading channels","year":2009,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rayleigh fading; Computer science; Scheduling (production processes); Fading; Markov process; Finite state; Queue; Markov chain; Computer network; Base station; Markov model; Algorithm; Real-time computing; Mathematical optimization; Channel (broadcasting); Mathematics; Statistics","score_opus":0.030149493212860975,"score_gpt":0.2808846657349409,"score_spread":0.25073517252207994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242412790","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":[0.14020354,0.0010060357,0.85750127,0.000120736695,0.00008082312,0.00045293153,0.00000946346,0.0004093432,0.0002158915],"genre_scores_gemma":[0.788481,0.0008441508,0.21020152,0.00016017053,0.000070201415,0.00006655843,0.00010284533,0.00004423351,0.000029306306],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989785,0.000022077322,0.0003545408,0.00022906483,0.00008294188,0.00033285152],"domain_scores_gemma":[0.9987981,0.00017351755,0.00008978891,0.00073075533,0.000105534324,0.00010231742],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014663624,0.00021446361,0.00024825713,0.00009276873,0.0004499785,0.00009138222,0.00042169212,0.00010085725,0.0000023885752],"category_scores_gemma":[0.000008248784,0.000254699,0.000047079495,0.00022966953,0.00003844521,0.00022529282,0.00016290101,0.00022717222,0.0000014371481],"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":[0.000003139731,0.000027742288,0.000029633202,0.000053828764,0.000015172695,1.560327e-7,0.00073874235,0.9490264,0.0033609741,0.0062399427,0.000015902106,0.04048839],"study_design_scores_gemma":[0.00035009265,0.000020659214,0.000023997021,0.00015943995,0.000016933272,0.000003748825,0.00015752488,0.99783206,0.000075923184,0.00037134212,0.00070787227,0.0002803824],"about_ca_topic_score_codex":0.0000013853688,"about_ca_topic_score_gemma":0.0000025447537,"teacher_disagreement_score":0.64827746,"about_ca_system_score_codex":0.000048855123,"about_ca_system_score_gemma":0.00001998211,"threshold_uncertainty_score":0.9999905},"labels":[],"label_agreement":null},{"id":"W4244459314","doi":"10.4018/978-1-60566-986-1.ch030","title":"Cross-Layer Radio Resource Management Protocols for QoS Provisioning in Multimedia Wireless Networks","year":2010,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Guelph","funders":"","keywords":"Computer science; Computer network; Quality of service; Provisioning; Wireless network; Scheduling (production processes); Network packet; Wireless; Multi-frequency network; Radio resource management; Multimedia; Distributed computing; Wi-Fi array; Telecommunications; Engineering","score_opus":0.012413274816522787,"score_gpt":0.2643013467720622,"score_spread":0.2518880719555394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244459314","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000102892875,0.00019632702,0.29088745,0.0000067633846,0.00095551333,0.037685543,0.000093278424,0.0009320111,0.6691402],"genre_scores_gemma":[0.12065129,0.00012875485,0.46710545,0.000708678,0.012641832,0.15138674,0.0008116761,0.003769455,0.24279612],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973517,0.000013309477,0.0007980917,0.0007187096,0.00035815465,0.00076005067],"domain_scores_gemma":[0.9986996,0.00008119779,0.00023596257,0.00071130355,0.00009448754,0.0001774199],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020498055,0.0007405647,0.00068646256,0.00014190437,0.00013146672,0.00016380344,0.0004964231,0.0010059276,0.000018673729],"category_scores_gemma":[0.000010558852,0.0008268732,0.00019524521,0.00005256322,0.00011059994,0.00010788288,0.00016334665,0.000864626,0.000018236735],"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":[0.00016536552,0.000013439414,0.00006693402,0.0004062179,0.00010688792,0.000062016494,0.000052506315,0.81177855,0.00002289837,0.119077556,0.0005752695,0.06767238],"study_design_scores_gemma":[0.0033969835,0.00009940787,0.000096096905,0.0025575347,0.00008058726,0.000018109482,0.000009614908,0.8180744,0.00015583217,0.010730686,0.1630522,0.001728568],"about_ca_topic_score_codex":0.0000040073173,"about_ca_topic_score_gemma":0.00006446676,"teacher_disagreement_score":0.4263441,"about_ca_system_score_codex":0.00052655255,"about_ca_system_score_gemma":0.00003570936,"threshold_uncertainty_score":0.9994182},"labels":[],"label_agreement":null},{"id":"W4248542086","doi":"10.1017/s0021900200004241","title":"Dynamic Distributed Scheduling in Random Access Networks","year":2008,"lang":"en","type":"article","venue":"Journal of Applied Probability","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Bell (Canada)","funders":"","keywords":"Random access; Queue; Scheduling (production processes); Aloha; Computer science; Network packet; Quality of service; Queueing theory; Computer network; Mathematics; Distributed computing; Mathematical optimization; Throughput","score_opus":0.011126060263418511,"score_gpt":0.2288776650458725,"score_spread":0.217751604782454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248542086","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":[0.47464082,0.00019415906,0.524544,0.000014625991,0.0001452347,0.00018842705,0.0000015248248,0.000046069494,0.00022513406],"genre_scores_gemma":[0.97009987,0.00038572322,0.029384637,0.000010939684,0.00007239336,0.000012049653,0.00001023633,0.000023418434,7.611349e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987387,0.000025486444,0.000680599,0.00012781164,0.00017794609,0.00024943418],"domain_scores_gemma":[0.9993537,0.00011986282,0.00018452245,0.00017356862,0.00008760153,0.00008071435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000418683,0.00015186938,0.0003724033,0.000086640524,0.00005060932,0.000021173808,0.0002448396,0.0001119694,0.000013735219],"category_scores_gemma":[0.000044290904,0.00014376812,0.00007203155,0.00048024213,0.000059200465,0.00030178222,0.000036337606,0.00049756054,0.0000010880353],"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":[0.00024507774,0.00004205816,0.0028312071,0.000030311705,0.000017839495,0.000010713373,0.000060817074,0.9947221,0.00007595846,0.000058777405,0.000024859452,0.0018802747],"study_design_scores_gemma":[0.0017955954,0.000013510926,0.007777688,0.000039359642,0.000009783177,0.00002674883,0.000010510726,0.9870243,0.00015022968,0.0029479025,0.000055665267,0.00014869141],"about_ca_topic_score_codex":6.4954196e-7,"about_ca_topic_score_gemma":0.000009638944,"teacher_disagreement_score":0.49545902,"about_ca_system_score_codex":0.00030538833,"about_ca_system_score_gemma":0.000044400887,"threshold_uncertainty_score":0.5862694},"labels":[],"label_agreement":null},{"id":"W4250310517","doi":"10.1109/tcomm.2009.5336832","title":"Policy allocation for transmission of embedded bit streams over noisy channels with feedback - [Transactions letters","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Network packet; Channel (broadcasting); Transmission (telecommunications); Rayleigh fading; Computer network; Automatic repeat request; Real-time computing; Fading; Bitstream; Algorithm; Hybrid automatic repeat request; Decoding methods; Telecommunications","score_opus":0.012811417657053988,"score_gpt":0.2546309348805072,"score_spread":0.2418195172234532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250310517","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":[0.0037783012,0.000094304785,0.9926859,0.0016553744,0.00012427529,0.00080352946,0.000098761426,0.00040115608,0.000358401],"genre_scores_gemma":[0.9260014,0.0011345611,0.07216879,0.00012924345,0.000038781884,0.00024451042,0.000079740465,0.00006827466,0.00013467752],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987783,0.000050955146,0.0004415296,0.00022861599,0.00019853708,0.00030209724],"domain_scores_gemma":[0.9983119,0.00019074023,0.00009991333,0.0011429058,0.000138966,0.00011559492],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007945156,0.00027785279,0.000273709,0.00039500013,0.00037022668,0.00003123315,0.000447446,0.00013140007,0.00003437482],"category_scores_gemma":[0.000001942489,0.0002897011,0.00014750063,0.00090811576,0.00012779026,0.0004085045,6.4201424e-7,0.0003047807,0.0000050881054],"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":[0.00006466369,0.00024979952,4.2397767e-7,0.000026208138,0.000071029914,1.0006588e-7,0.00045989218,0.8765113,0.01974135,0.00023072085,0.000061831845,0.102582686],"study_design_scores_gemma":[0.0014773877,0.0002685364,0.000053720207,0.0002159727,0.00015178898,0.0000064663045,0.00013240858,0.92729163,0.068816975,0.00030908154,0.00084040576,0.0004356176],"about_ca_topic_score_codex":0.000030386213,"about_ca_topic_score_gemma":0.00007302106,"teacher_disagreement_score":0.9222231,"about_ca_system_score_codex":0.00016206136,"about_ca_system_score_gemma":0.00005672939,"threshold_uncertainty_score":0.99995553},"labels":[],"label_agreement":null},{"id":"W4251959677","doi":"10.22215/etd/2008-08365","title":"Low bit-rate video transmission over wireless Zigbee networks","year":2008,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Computer science; Transmission (telecommunications); Bit (key); Wireless transmission; Wireless; Telecommunications; Computer network","score_opus":0.00408571780029702,"score_gpt":0.20525259060507772,"score_spread":0.2011668728047807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251959677","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":[0.040602252,0.0029585236,0.92630047,0.0000092061755,0.0027114707,0.00074132415,0.000010035252,0.0020304415,0.024636254],"genre_scores_gemma":[0.8734269,0.064370506,0.010967135,0.00019499558,0.0018319722,0.00031088677,0.0105673615,0.0013524893,0.03697772],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979585,0.00004159635,0.0006128845,0.0005084314,0.00030235702,0.0005762734],"domain_scores_gemma":[0.99909234,0.00008736011,0.00013144567,0.0004030105,0.00010217964,0.00018368493],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007099856,0.00067138835,0.0005968599,0.0002180482,0.0001534389,0.000052386404,0.00026786278,0.0008822726,0.000439811],"category_scores_gemma":[0.000005559457,0.0006896487,0.00019349647,0.0005416752,0.000024313524,0.00033399,0.000009471308,0.00071303424,0.000050352413],"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":[0.000052751984,0.000023004994,0.0000101294945,0.0002441239,0.000059692866,0.00002103318,0.00016305958,0.93651974,0.00095907284,0.00006601156,0.007975274,0.053906098],"study_design_scores_gemma":[0.00046514688,0.000021024902,0.00040812077,0.00054070994,0.00004474686,0.000004763302,0.000038507307,0.98748046,0.005426608,0.000047347778,0.0046673287,0.00085523963],"about_ca_topic_score_codex":0.000011099629,"about_ca_topic_score_gemma":0.00008092118,"teacher_disagreement_score":0.91533333,"about_ca_system_score_codex":0.00015106992,"about_ca_system_score_gemma":0.00004330388,"threshold_uncertainty_score":0.99955547},"labels":[],"label_agreement":null},{"id":"W4252112302","doi":"10.1002/wcm.467","title":"Optimized bandwidth allocation with fairness and service differentiation in multimedia wireless networks","year":2006,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; University of Guelph","funders":"","keywords":"Computer science; Markov decision process; Call Admission Control; Wireless; Computer network; Bandwidth (computing); Class (philosophy); Wireless network; Markov chain; Markov process; Decision process; Bandwidth allocation; Dynamic programming; Mathematical optimization; Telecommunications; Artificial intelligence; Algorithm; Machine learning; Management science","score_opus":0.005777932368574813,"score_gpt":0.20578918344858008,"score_spread":0.20001125108000525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252112302","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":[0.5077554,0.0013917738,0.49002755,0.000057977093,0.000044104767,0.0003997039,0.0000022338336,0.0002085923,0.00011264949],"genre_scores_gemma":[0.96449524,0.00198485,0.03295322,0.000026462525,0.000053902735,0.00013866097,0.00028493776,0.000056135646,0.000006580768],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988269,0.00009262226,0.0004120512,0.00026958506,0.00011081745,0.00028800635],"domain_scores_gemma":[0.99887586,0.00026911503,0.00012125854,0.0005580882,0.00011462453,0.00006105089],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016089821,0.00024551374,0.00030144185,0.00013769766,0.00025243562,0.000094238334,0.00024836877,0.000121559715,0.0000019848342],"category_scores_gemma":[0.000002581524,0.00025261112,0.00001719346,0.0005185062,0.00009933028,0.00025825045,0.00017736819,0.0002820726,6.3188037e-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":[0.000012430021,0.000053768756,0.0041193007,0.00005281309,0.000013544931,5.8022533e-7,0.00039304,0.9258852,0.00028619345,0.00050448993,0.0000056630465,0.06867298],"study_design_scores_gemma":[0.0011569439,0.000018728633,0.01173141,0.00021456889,0.00001903505,0.000007041506,0.00020519168,0.98616457,0.00008734476,0.000041727777,0.00006663166,0.00028680207],"about_ca_topic_score_codex":0.00016218804,"about_ca_topic_score_gemma":0.0005699776,"teacher_disagreement_score":0.45707434,"about_ca_system_score_codex":0.00007233541,"about_ca_system_score_gemma":0.000012556518,"threshold_uncertainty_score":0.9999926},"labels":[],"label_agreement":null},{"id":"W4252321683","doi":"10.1002/wcm.696","title":"Adaptive radio resource allocation in OFDMA systems: a survey of the state‐of‐the‐art approaches","year":2008,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"University of Manitoba","funders":"","keywords":"Computer science; Orthogonal frequency-division multiplexing; Orthogonal frequency-division multiple access; Resource allocation; Frequency-division multiple access; Computer network; Transmission (telecommunications); Wireless; Telecommunications; Channel (broadcasting)","score_opus":0.040055229469709075,"score_gpt":0.2218407593528702,"score_spread":0.18178552988316113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252321683","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":[0.9375384,0.0066388417,0.05474311,0.00003053217,0.000075494034,0.0006900399,0.000018757575,0.00005501424,0.00020983077],"genre_scores_gemma":[0.997298,0.0010426628,0.001519171,0.0000030095275,0.000007404551,0.000058655736,0.000019461044,0.0000228023,0.000028840066],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887466,0.0003413783,0.00042517902,0.00011449157,0.00011450701,0.00012976486],"domain_scores_gemma":[0.99847424,0.000356453,0.00020215774,0.00085565745,0.00009137349,0.000020133233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032835786,0.00011012669,0.00021704315,0.000055242217,0.00018724537,0.000007740841,0.0005384214,0.00004611693,2.7256334e-7],"category_scores_gemma":[0.000020524283,0.00008886179,0.000031916832,0.00062188524,0.00025179549,0.000064184256,0.00029194984,0.00020647277,1.9176788e-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":[0.00000352847,0.0000363603,0.013030067,0.000042310516,0.000015872301,4.0049144e-8,0.0016377614,0.9742297,0.000099465215,0.00019350857,0.0000282232,0.010683198],"study_design_scores_gemma":[0.00016376097,0.00000915284,0.047518473,0.00025602386,0.0000051626607,0.00000385688,0.00024893493,0.95134515,0.00019810982,0.0000070319797,0.00016003905,0.00008429497],"about_ca_topic_score_codex":0.00021136942,"about_ca_topic_score_gemma":0.00026583252,"teacher_disagreement_score":0.059759613,"about_ca_system_score_codex":0.000054865486,"about_ca_system_score_gemma":0.00003149888,"threshold_uncertainty_score":0.36236784},"labels":[],"label_agreement":null},{"id":"W4253550704","doi":"10.22215/etd/2007-07706","title":"Buffer management for WiMax/802.16 subscriber stations","year":2007,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"WiMAX; Buffer (optical fiber); Computer network; Computer science; Telecommunications; Wireless","score_opus":0.007516630249371928,"score_gpt":0.2689827641846857,"score_spread":0.26146613393531376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253550704","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":[0.0006610781,0.00036746985,0.8422253,0.000007774319,0.0012774741,0.000949307,0.000033285276,0.000591335,0.15388694],"genre_scores_gemma":[0.058931265,0.0028510783,0.5093329,0.00022878451,0.0008894948,0.0019360117,0.044021837,0.00092678727,0.38088185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988292,0.0000050523354,0.00035497258,0.00026531474,0.00018938053,0.0003560699],"domain_scores_gemma":[0.99944305,0.000059791135,0.00006091492,0.00024418702,0.00012822796,0.00006383197],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007166512,0.00030425985,0.0002288793,0.00024520396,0.00008065217,0.000037784754,0.00012806249,0.00022636153,0.00028311732],"category_scores_gemma":[0.000005892561,0.00033702754,0.00009287022,0.00025000062,0.000007931112,0.0001511712,0.0000067370065,0.00015113373,0.00005040629],"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":[0.000054084256,0.000031403644,0.0000083057275,0.00085016724,0.000240359,0.000003532222,0.00022060848,0.8739992,0.00005278596,0.01726368,0.04930845,0.057967465],"study_design_scores_gemma":[0.003473326,0.000115897914,0.0018817071,0.0007947498,0.00091862626,0.0000037062202,0.00425315,0.57929796,0.008180511,0.011574242,0.38562217,0.0038839837],"about_ca_topic_score_codex":0.000004140597,"about_ca_topic_score_gemma":0.00035912608,"teacher_disagreement_score":0.33631372,"about_ca_system_score_codex":0.00021482381,"about_ca_system_score_gemma":0.000009317685,"threshold_uncertainty_score":0.99990815},"labels":[],"label_agreement":null},{"id":"W4254290501","doi":"10.32920/ryerson.14644947.v1","title":"Nonconvex and game theory optimization for resource allocation in wireless communications","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; University of Manitoba; University of Toronto","funders":"","keywords":"Mathematical optimization; Computer science; Stackelberg competition; Resource allocation; Optimization problem; Computational complexity theory; Wireless; Game theory; Throughput; Algorithm; Mathematics; Computer network; Telecommunications","score_opus":0.014537189462751558,"score_gpt":0.24646698501917075,"score_spread":0.23192979555641918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254290501","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":[0.003971849,0.0015945896,0.9908767,0.00018238185,0.00014533682,0.000843988,0.000013894591,0.0003237589,0.0020475239],"genre_scores_gemma":[0.730359,0.0042631985,0.26195887,0.00007462255,0.00007026149,0.0005749148,0.002471983,0.000107414926,0.00011971813],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885875,0.00010540139,0.00041264854,0.0003295526,0.00009290686,0.00020075504],"domain_scores_gemma":[0.9985579,0.0003283076,0.000093236864,0.00085262425,0.00011724285,0.000050688057],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028580683,0.00024327515,0.00030665612,0.00016087005,0.000051083083,0.0000929709,0.00029916997,0.00033711616,0.000018969571],"category_scores_gemma":[0.00004909259,0.0002978897,0.000046798614,0.00020500836,0.000066203895,0.00016209323,0.00034075548,0.00038551766,5.8688744e-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":[0.000009445254,0.00002072064,0.000046366586,0.00021390225,0.00002622305,2.5968757e-7,0.00045844677,0.9813575,0.00003791845,0.003981201,0.00005590196,0.013792101],"study_design_scores_gemma":[0.00033113346,0.000006057349,0.000059497568,0.00024929913,0.000024587489,0.0000014022326,0.00033222107,0.99725443,0.00023886566,0.0009050565,0.00030330828,0.00029411627],"about_ca_topic_score_codex":0.000007611498,"about_ca_topic_score_gemma":0.000096229516,"teacher_disagreement_score":0.7289178,"about_ca_system_score_codex":0.00016764463,"about_ca_system_score_gemma":0.00004198562,"threshold_uncertainty_score":0.9999473},"labels":[],"label_agreement":null},{"id":"W4254474339","doi":"10.1002/dac.887","title":"Joint packet scheduling and dynamic base station assignment for CDMA data networks","year":2007,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Polytechnique Montréal","funders":"","keywords":"Computer science; Base station; Network packet; Computer network; Scheduling (production processes); Code division multiple access; Wireless; Queue; Real-time computing; Distributed computing; Telecommunications; Mathematical optimization","score_opus":0.03509135446373817,"score_gpt":0.30691584901180013,"score_spread":0.27182449454806196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254474339","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":[0.013900666,0.004863533,0.9796697,0.00019525243,0.0009977488,0.00021000873,0.000031155392,0.00003790212,0.00009403088],"genre_scores_gemma":[0.94607234,0.0026603485,0.050694678,0.000024457113,0.00021756832,0.0000068961463,0.0002846806,0.000027706867,0.000011310608],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864805,0.00005877586,0.0007649588,0.000094306095,0.00030712463,0.000126759],"domain_scores_gemma":[0.9981951,0.0003521603,0.0004665659,0.00039423455,0.0005234811,0.0000684735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015287207,0.000106735664,0.00017359962,0.00018018701,0.00005961548,0.000108742985,0.00057123334,0.00006437408,0.0000027636247],"category_scores_gemma":[0.00010124546,0.000108830594,0.000032123196,0.000084774336,0.000028135351,0.00061235967,0.000095921016,0.0001812686,7.831095e-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":[0.000040792987,0.000017298104,0.00016008965,0.000007877118,0.00010986993,0.0000018094564,0.00011461174,0.983582,0.00039411848,0.0007953979,0.0002657707,0.014510341],"study_design_scores_gemma":[0.0006268115,0.00002234892,0.0005278853,0.00025124167,0.000018569748,0.000043043416,0.00037748084,0.9950028,0.00008002014,0.00015965913,0.002789604,0.00010050586],"about_ca_topic_score_codex":0.000004119648,"about_ca_topic_score_gemma":0.000014799379,"teacher_disagreement_score":0.9321717,"about_ca_system_score_codex":0.00023173532,"about_ca_system_score_gemma":0.000020216508,"threshold_uncertainty_score":0.44379827},"labels":[],"label_agreement":null},{"id":"W4254557178","doi":"10.1002/wcm.695","title":"On the effect of reservation period on performance of IEEE 802.16 R‐MAC protocol","year":2008,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Reservation; Computer network; Network packet; Throughput; Access control; Bandwidth (computing); Telecommunications; Wireless","score_opus":0.016040311204582526,"score_gpt":0.2577058858287133,"score_spread":0.24166557462413077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254557178","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":[0.9832921,0.000059125203,0.0069978433,0.000022204604,0.000034162815,0.008531231,0.0000028399957,0.00008076586,0.000979722],"genre_scores_gemma":[0.9932332,0.0001939368,0.0009535793,0.000008619282,0.000019507532,0.005545095,0.000011865474,0.000025065568,0.000009149333],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917316,0.00012307531,0.00032882817,0.00011088908,0.00013377157,0.00013029287],"domain_scores_gemma":[0.9982742,0.0006342986,0.00015129322,0.000843855,0.0000734606,0.000022882043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024987888,0.00013525816,0.00020973486,0.00006893221,0.00031770632,0.000007703058,0.0003602559,0.00005291544,0.0000034370894],"category_scores_gemma":[0.000020027497,0.000104619954,0.000036805952,0.00027442377,0.0001705709,0.000071620416,0.00009285049,0.00022120216,0.0000013434467],"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":[0.00005066971,0.000042696287,0.0033093637,0.00018817018,0.000018575216,1.334663e-7,0.00047762642,0.9582118,0.00137381,0.0010274289,0.00007931186,0.035220426],"study_design_scores_gemma":[0.00041295777,0.00048646945,0.0011082708,0.00035860384,0.0000052106016,0.0000031081188,0.000034889596,0.9832404,0.0138299195,0.000008125369,0.00040934441,0.00010264973],"about_ca_topic_score_codex":0.000005794025,"about_ca_topic_score_gemma":0.000001988648,"teacher_disagreement_score":0.035117775,"about_ca_system_score_codex":0.00004149916,"about_ca_system_score_gemma":0.000012400063,"threshold_uncertainty_score":0.42662778},"labels":[],"label_agreement":null},{"id":"W4254995417","doi":"10.22215/etd/2008-08217","title":"Adaptive token bank fair queuing scheduling in the downlink of 4G wireless networks","year":2008,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Computer network; Computer science; Security token; Scheduling (production processes); Queueing theory; Queue; Telecommunications link; Telecommunications; Engineering; Operations management","score_opus":0.008357430739086642,"score_gpt":0.21687262640420232,"score_spread":0.20851519566511567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254995417","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":[0.27252612,0.0054397983,0.67365587,0.000018055614,0.0014163821,0.0014366027,0.000013782556,0.00062163774,0.044871785],"genre_scores_gemma":[0.9866768,0.0035123965,0.008304986,0.000024615247,0.00023877654,0.00008730997,0.0007928394,0.000119424396,0.00024281723],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99828076,0.000066403474,0.0006554626,0.00030057863,0.0003043072,0.0003924607],"domain_scores_gemma":[0.99908745,0.00021816627,0.00019572585,0.000344321,0.000114637034,0.0000397009],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016705578,0.0004058635,0.000512119,0.00021439657,0.00007505963,0.000022636501,0.00038314573,0.00049024966,0.000031289033],"category_scores_gemma":[0.000017725497,0.00035351634,0.00011869715,0.0006824184,0.00003179803,0.00022516669,0.000016865635,0.0008399189,0.00000480669],"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":[0.000035092824,0.000017112727,0.000056500892,0.00008688524,0.000042352764,0.000009157214,0.001366459,0.9880322,0.00006372546,0.00077761407,0.00011479939,0.009398069],"study_design_scores_gemma":[0.00026353684,0.000021126489,0.0006451384,0.00047937728,0.000026126661,0.000003712165,0.0025064112,0.9951724,0.00037732697,0.00006917882,0.0000561712,0.00037949823],"about_ca_topic_score_codex":0.00004759273,"about_ca_topic_score_gemma":0.0007399398,"teacher_disagreement_score":0.7141507,"about_ca_system_score_codex":0.00012405879,"about_ca_system_score_gemma":0.000041897558,"threshold_uncertainty_score":0.9998917},"labels":[],"label_agreement":null},{"id":"W4255014455","doi":"10.4018/978-1-60566-054-7.ch080","title":"Business and Technology Issues in Wireless Networking","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"WiMAX; Computer science; Telecommunications; Metropolitan area; Wireless; Quality of service; Computer network; IEEE 802.11u; Wireless network; Profitability index; IEEE 802.11; Business","score_opus":0.006844460826525675,"score_gpt":0.2118522127741145,"score_spread":0.20500775194758883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255014455","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000624623,0.008433474,0.005258862,0.00008558565,0.0006095752,0.00041793112,0.000014787245,0.0010700123,0.98348516],"genre_scores_gemma":[0.9506278,0.004419956,0.008966223,0.00022021821,0.002038026,0.00006053533,0.000045337605,0.00045551997,0.033166386],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987706,0.0000050383496,0.00034870306,0.00035892637,0.00014015411,0.00037658765],"domain_scores_gemma":[0.9994779,0.000014209159,0.0000819083,0.00029537544,0.000073608295,0.000056977584],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000039482402,0.00043711925,0.0005230199,0.00018875013,0.000040041698,0.000038198854,0.00017804473,0.0007185683,0.0000035790165],"category_scores_gemma":[0.000003637171,0.00052067864,0.000029879153,0.00011436302,0.00008710335,0.000056644032,0.00007312015,0.0003739012,0.000010428595],"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":[0.0000118317275,0.0000034723764,0.00011608128,0.00007979997,0.000037906822,0.00012420077,0.000017971091,0.07515179,0.000019527566,0.6530707,0.00043188405,0.27093485],"study_design_scores_gemma":[0.0012936799,0.00007869493,0.0002672243,0.0038136123,0.00010377826,0.00019069701,0.000016561993,0.06657343,0.0000865909,0.82106405,0.103907265,0.0026044091],"about_ca_topic_score_codex":0.000008047001,"about_ca_topic_score_gemma":0.00016071789,"teacher_disagreement_score":0.95031875,"about_ca_system_score_codex":0.0002313564,"about_ca_system_score_gemma":0.000023701752,"threshold_uncertainty_score":0.9997245},"labels":[],"label_agreement":null},{"id":"W4255565538","doi":"10.1007/978-3-319-78262-1_43","title":"Network Selection in Heterogeneous Wireless Networks","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 New Brunswick","funders":"","keywords":"Selection (genetic algorithm); Computer science; Wireless network; Computer network; Heterogeneous network; Wireless; Artificial intelligence; Telecommunications","score_opus":0.0084335957895355,"score_gpt":0.18169805296785382,"score_spread":0.17326445717831832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255565538","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":[0.000015223469,0.0019701393,0.65393776,0.000025495792,0.0007080903,0.00049299555,0.0000037528666,0.0013909976,0.34145552],"genre_scores_gemma":[0.6535811,0.019788757,0.033519443,0.0019499407,0.015353098,0.00029244184,0.0013187298,0.0034170838,0.27077946],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845576,0.000011787778,0.00049960654,0.00042405742,0.00017376494,0.0004350162],"domain_scores_gemma":[0.99953896,0.00004982875,0.000087565335,0.00017080728,0.000036301706,0.00011653574],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00004975526,0.0005139643,0.0005368417,0.000104192244,0.00004504861,0.000034697077,0.00016831866,0.0006312828,0.0002943311],"category_scores_gemma":[0.0000020837376,0.00061326294,0.000099603,0.00015845172,0.000026176056,0.000098691904,0.000052058345,0.0007994102,0.00008318468],"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":[0.00001349135,0.0000021859546,0.000014992406,0.000033110875,0.00004405456,0.000028945846,0.000007782895,0.97587955,0.0000033083095,0.01093207,0.0040338673,0.009006624],"study_design_scores_gemma":[0.00017629523,0.00002854164,0.0000043470495,0.00016199917,0.000022330007,0.000014764703,5.9210487e-7,0.97639966,0.000009900481,0.0029184548,0.01968344,0.00057967566],"about_ca_topic_score_codex":0.0000022489767,"about_ca_topic_score_gemma":0.00016197021,"teacher_disagreement_score":0.6535658,"about_ca_system_score_codex":0.00027653034,"about_ca_system_score_gemma":0.000016112675,"threshold_uncertainty_score":0.9996319},"labels":[],"label_agreement":null},{"id":"W4255743104","doi":"10.1002/wcm.485","title":"DSP implementation of a bit loading algorithm for adaptive wireless multicarrier transceivers","year":2007,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Transceiver; Subcarrier; Wireless; Robustness (evolution); Channel (broadcasting); Algorithm; Bit error rate; Digital signal processing; Computer hardware; Real-time computing; Orthogonal frequency-division multiplexing; Computer network; Telecommunications","score_opus":0.014474714348272792,"score_gpt":0.2867996885596497,"score_spread":0.2723249742113769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255743104","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":[0.21272485,0.00073568284,0.7855407,0.000007984184,0.00007815024,0.0006194484,0.000035758145,0.0001403642,0.00011707086],"genre_scores_gemma":[0.8364296,0.00059952174,0.16274935,0.000008561926,0.000037764043,0.00006002013,0.00007019265,0.00004155843,0.0000034413495],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888235,0.00003213873,0.0004881544,0.00018749201,0.00010410256,0.0003057808],"domain_scores_gemma":[0.998743,0.0004417089,0.00013797928,0.00043515261,0.00016350692,0.000078633595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032615117,0.00017691273,0.0002582359,0.00014305474,0.0002790214,0.000021256483,0.00027921138,0.00008138621,0.0000036100278],"category_scores_gemma":[0.0000028576783,0.00020976835,0.0000666677,0.0003006993,0.00013577915,0.00016155344,0.000063342515,0.00015326106,4.3001285e-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":[0.000006922504,0.000028760396,0.00024733672,0.0000489789,0.00006212608,2.9046e-7,0.0025985332,0.061090756,0.005571763,0.0010749194,0.000009166286,0.92926043],"study_design_scores_gemma":[0.00079559966,0.00006874967,0.00030876568,0.00009803805,0.0000368952,0.000002903094,0.0045191417,0.9842366,0.0091507435,0.000038853083,0.0005269602,0.00021674854],"about_ca_topic_score_codex":0.000032946915,"about_ca_topic_score_gemma":0.000059658225,"teacher_disagreement_score":0.9290437,"about_ca_system_score_codex":0.000083046376,"about_ca_system_score_gemma":0.000018382683,"threshold_uncertainty_score":0.85541046},"labels":[],"label_agreement":null},{"id":"W4256063023","doi":"10.1002/bltj.20335","title":"Performance assessment of next-generation wireless mobile systems","year":2009,"lang":"en","type":"article","venue":"Bell Labs Technical Journal","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Bell (Canada)","funders":"","keywords":"UMTS frequency bands; WiMAX; 3rd Generation Partnership Project 2; Telecommunications; Computer network; Mobile broadband; Engineering; Next-generation network; Wireless broadband; Orthogonal frequency-division multiplexing; Wireless; Computer science; Wireless network; The Internet; Telecommunications link","score_opus":0.017421103722550606,"score_gpt":0.2558220676393434,"score_spread":0.2384009639167928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256063023","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":[0.5982895,0.0008080859,0.39701626,0.000018179804,0.00046485706,0.00028702946,0.000002332011,0.00027269986,0.00284108],"genre_scores_gemma":[0.98279774,0.0017993639,0.014949136,0.00001250212,0.00035915792,0.000014703877,0.000009370235,0.000023222285,0.000034776454],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988677,0.000027713848,0.00049249316,0.000110244546,0.0002794561,0.0002223903],"domain_scores_gemma":[0.9994699,0.000021986792,0.00013071047,0.0001811828,0.000109272405,0.00008698345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024174244,0.0001381407,0.00022974645,0.000088297726,0.00009234172,0.000050807645,0.00017550089,0.000120556026,0.00002061599],"category_scores_gemma":[0.000005094867,0.00012957666,0.000053108157,0.00024307513,0.000023189039,0.00034043868,0.0000146129305,0.000366567,0.0000036659662],"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":[0.0000027589454,0.000031080228,0.00020065454,0.000018112329,0.0000073249516,0.0000028501236,0.0000070326273,0.87182754,0.105917275,0.0002698334,0.00045640688,0.02125912],"study_design_scores_gemma":[0.00022814627,0.0001973975,0.0016089528,0.00010451918,0.000013942408,0.0001004103,0.000009929997,0.99204576,0.0048183003,0.000020156656,0.0006973242,0.00015518435],"about_ca_topic_score_codex":3.2286272e-7,"about_ca_topic_score_gemma":4.50449e-7,"teacher_disagreement_score":0.38450828,"about_ca_system_score_codex":0.00016141435,"about_ca_system_score_gemma":0.000027246328,"threshold_uncertainty_score":0.5283982},"labels":[],"label_agreement":null},{"id":"W426264565","doi":"","title":"Resource management for cross layered star and mesh networks","year":2008,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Network packet; Cellular network; Wireless network; Scheduling (production processes); Wireless; Telecommunications; Engineering","score_opus":0.0143677558803131,"score_gpt":0.2547751339232195,"score_spread":0.24040737804290638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W426264565","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":[0.66674936,0.0027664362,0.028645627,0.000059376238,0.002271205,0.004168915,0.000060955696,0.0012939273,0.29398417],"genre_scores_gemma":[0.8914422,0.0070319083,0.0008448138,0.000004310731,0.0006898877,0.00004014122,0.00073203945,0.00024516802,0.09896954],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975928,0.00013604542,0.00028567648,0.0006684894,0.00045627257,0.0008607177],"domain_scores_gemma":[0.9987406,0.00021330426,0.00010047721,0.0005092525,0.00018088007,0.00025547412],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022101116,0.0003716942,0.00039949082,0.00079254276,0.0008352178,0.00014361004,0.00046980972,0.00043821806,0.0000087635535],"category_scores_gemma":[0.000013547026,0.00048610664,0.00013607346,0.0008133672,0.00017845037,0.0002819743,0.00010630945,0.0008348577,0.0000035531539],"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":[0.0028759073,0.00011070055,0.0038533476,0.0022835615,0.0013762346,0.0021482205,0.0009358545,0.947123,0.00058140536,0.009719531,0.02220943,0.006782795],"study_design_scores_gemma":[0.00579686,0.000761076,0.039425407,0.0010613168,0.00032222676,0.00007536811,0.00559019,0.4935313,0.007645893,0.00065476366,0.4420117,0.0031238883],"about_ca_topic_score_codex":0.00015808723,"about_ca_topic_score_gemma":0.0009814977,"teacher_disagreement_score":0.4535917,"about_ca_system_score_codex":0.00069235155,"about_ca_system_score_gemma":0.000081715676,"threshold_uncertainty_score":0.9997591},"labels":[],"label_agreement":null},{"id":"W4288640804","doi":"10.48550/arxiv.1901.02111","title":"Scheduling for VoLTE: Resource Allocation Optimization and\\n Low-Complexity Algorithms","year":2019,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Scheduling (production processes); Dynamic priority scheduling; Fair-share scheduling; Mathematical optimization; Proportionally fair; Maximization; Rate-monotonic scheduling; Round-robin scheduling; Quality of service; Optimization problem; Algorithm; Computer network; Mathematics","score_opus":0.052592156052445806,"score_gpt":0.18978131817062158,"score_spread":0.13718916211817578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288640804","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":[0.026332673,0.00035071356,0.9690861,0.000060820097,0.0009224283,0.0021761495,0.000089233974,0.0004645939,0.0005172513],"genre_scores_gemma":[0.8528021,0.0025206753,0.14217936,0.000042747793,0.00041629953,0.000010914596,0.0009695554,0.00021520015,0.00084315],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99638563,0.00015194897,0.0006565147,0.0018482215,0.0001504893,0.00080719945],"domain_scores_gemma":[0.9971366,0.0003344443,0.0005892276,0.0011325364,0.00051029306,0.00029690584],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00043448535,0.0008653899,0.00081404,0.00044806936,0.00045503298,0.0001640282,0.0006479597,0.0009229027,0.00006719964],"category_scores_gemma":[0.000112917405,0.0012668315,0.000269238,0.0008752888,0.0002502029,0.00081395556,0.00059294363,0.00085247756,0.000033824228],"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":[0.00017385097,0.0000726741,0.00020784835,0.0009953397,0.00016979728,0.000007619429,0.00021518953,0.9809271,0.00006751777,0.01572231,0.000038998543,0.0014017209],"study_design_scores_gemma":[0.0018406665,0.000077954785,0.00009137688,0.0005990153,0.0003257015,0.0000037485158,0.0002809556,0.9926394,0.00020157386,0.0024570948,0.00029815783,0.0011843082],"about_ca_topic_score_codex":0.000032579872,"about_ca_topic_score_gemma":0.000012200993,"teacher_disagreement_score":0.8269068,"about_ca_system_score_codex":0.0008586121,"about_ca_system_score_gemma":0.0001432864,"threshold_uncertainty_score":0.99897814},"labels":[],"label_agreement":null},{"id":"W4297785792","doi":"10.48550/arxiv.1103.1448","title":"Optimal Multi-Server Allocation to Parallel Queues With Independent\\n Random Queue-Server Connectivity","year":2011,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Natural Sciences and Engineering Research Council of Canada","keywords":"Queue; Computer science; Server; Scheduling (production processes); Network packet; Distributed computing; Computer network; Mathematical optimization; Mathematics","score_opus":0.04611190761999282,"score_gpt":0.1822160393684342,"score_spread":0.13610413174844138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297785792","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":[0.44932982,0.000053435288,0.54885733,0.000006664941,0.00023518928,0.000610645,0.000010655578,0.0004609847,0.00043526234],"genre_scores_gemma":[0.9856851,0.00031987045,0.012833724,0.00003221717,0.00008941577,0.000015935115,0.00010625441,0.0001255101,0.00079194095],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980371,0.00012095492,0.0002710697,0.0009591895,0.00013084144,0.00048082913],"domain_scores_gemma":[0.9983532,0.00007674986,0.00017230205,0.00090401474,0.00024337629,0.0002503513],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019669629,0.00057208544,0.0005587513,0.00026968785,0.00011455056,0.000060060178,0.00059374754,0.00047537143,0.000087841974],"category_scores_gemma":[0.000027697417,0.00065386714,0.00015000557,0.00045793797,0.000076107994,0.0005199345,0.00042383937,0.0007035601,0.00009706503],"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":[0.000493011,0.00009099482,0.0027544321,0.00011604916,0.00024378474,0.00007407372,0.00032063416,0.9933633,0.000030409636,0.00234141,0.000077930476,0.00009393699],"study_design_scores_gemma":[0.0031170682,0.000067957604,0.0041177906,0.00021994188,0.00017364576,0.0000037855925,0.000118507065,0.9900653,0.0004611625,0.0005690036,0.00009495027,0.0009908819],"about_ca_topic_score_codex":0.00033086757,"about_ca_topic_score_gemma":0.0016086773,"teacher_disagreement_score":0.5363553,"about_ca_system_score_codex":0.00045240106,"about_ca_system_score_gemma":0.00008022487,"threshold_uncertainty_score":0.99959123},"labels":[],"label_agreement":null},{"id":"W4298268516","doi":"","title":"Adaptive Incremental Redundancy for HARQ Transmission with Outdated CSI","year":2011,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Hybrid automatic repeat request; Computer science; Redundancy (engineering); Transmission (telecommunications); Computer network; Telecommunications; Operating system","score_opus":0.013941942763439887,"score_gpt":0.19210384926709945,"score_spread":0.17816190650365957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298268516","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":[0.015744062,0.00029396205,0.95965266,0.00017815582,0.000057909496,0.00043719535,0.000020136285,0.00043674983,0.023179172],"genre_scores_gemma":[0.6696228,0.00014593791,0.32908437,0.000014535168,0.000009089901,0.000069720765,0.0001728076,0.000053687763,0.00082706654],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986883,0.0003600215,0.00024806772,0.0002816491,0.00015700502,0.00026498598],"domain_scores_gemma":[0.9985484,0.00019979905,0.00009121536,0.00049083034,0.0005572635,0.00011247586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006457762,0.00018836638,0.00016694731,0.00008133485,0.00019136225,0.00004360774,0.0002952458,0.00008450576,0.00009834503],"category_scores_gemma":[0.00005451012,0.00018582697,0.000054017648,0.00030140928,0.00008468318,0.00027731893,0.000040089195,0.00014091293,0.000009275313],"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":[0.0008087173,0.0016971896,0.0032079965,0.0004942235,0.0006101537,0.000017803977,0.061944988,0.06791022,0.06042253,0.12740248,0.004524147,0.67095953],"study_design_scores_gemma":[0.001745924,0.0000034131822,0.0012861582,0.000919853,0.000052064406,0.0000090379235,0.00025790287,0.67539525,0.31112885,0.0010821171,0.007563432,0.00055601203],"about_ca_topic_score_codex":0.00006043711,"about_ca_topic_score_gemma":0.00017911606,"teacher_disagreement_score":0.67040354,"about_ca_system_score_codex":0.00007636734,"about_ca_system_score_gemma":0.000032102027,"threshold_uncertainty_score":0.7577804},"labels":[],"label_agreement":null},{"id":"W4300281352","doi":"10.48550/arxiv.1501.04199","title":"Distributed Resource Allocation in D2D-Enabled Multi-tier Cellular\\n Networks: An Auction Approach","year":2015,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Manitoba","funders":"","keywords":"Computer science; Resource allocation; Scalability; Computer network; Distributed computing; Resource management (computing); Scheme (mathematics); Heterogeneous network; Throughput; Interference (communication); Wireless network; Radio resource management; Wireless; Channel (broadcasting); Telecommunications","score_opus":0.05347831925146664,"score_gpt":0.17913379106258212,"score_spread":0.12565547181111547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300281352","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":[0.10149254,0.00036924687,0.89461696,0.00001133847,0.00077961356,0.0014650844,0.000049042934,0.00059695006,0.0006192494],"genre_scores_gemma":[0.9840812,0.0009437719,0.0081657795,0.000014451218,0.00047716688,0.000015829155,0.00520482,0.00023883751,0.0008581293],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99458593,0.0007364368,0.00093984953,0.002298424,0.00022912455,0.0012102048],"domain_scores_gemma":[0.99633574,0.000091691094,0.0006475223,0.001841971,0.0005131763,0.00056986907],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00093282585,0.0011254915,0.001021092,0.00071734725,0.00028815787,0.00016384006,0.0010975593,0.0015879066,0.000035980916],"category_scores_gemma":[0.00006605526,0.0016103535,0.00024407382,0.0029261892,0.00022297176,0.0013992867,0.00064662873,0.0020395785,0.00003840753],"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":[0.00033890488,0.0005606293,0.0014436572,0.00020034298,0.00014861864,0.00009546128,0.0004790176,0.9946658,0.0000731012,0.0011658757,0.0001549433,0.0006736365],"study_design_scores_gemma":[0.0028405848,0.00007395558,0.00061997556,0.00025832697,0.00024557367,0.0000054350407,0.0011151831,0.9921042,0.000078227524,0.0006263921,0.0005620816,0.0014700636],"about_ca_topic_score_codex":0.00021279263,"about_ca_topic_score_gemma":0.00014669649,"teacher_disagreement_score":0.8864511,"about_ca_system_score_codex":0.0031334863,"about_ca_system_score_gemma":0.00019123117,"threshold_uncertainty_score":0.99970824},"labels":[],"label_agreement":null},{"id":"W4300854307","doi":"10.48550/arxiv.1801.08620","title":"Queue-Aware Joint Dynamic Interference Coordination and Heterogeneous\\n QoS Provisioning in OFDMA Networks","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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; Quality of service; Queue; Scheduling (production processes); Optimization problem; Mathematical optimization; Computer network; Convex optimization; Distributed computing; Algorithm; Regular polygon; Mathematics","score_opus":0.026416904345998138,"score_gpt":0.1713612287812166,"score_spread":0.14494432443521846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300854307","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":[0.40164578,0.00021427908,0.59708726,0.000008332268,0.00043316986,0.00030226688,0.000007721339,0.00022764876,0.00007355099],"genre_scores_gemma":[0.9974951,0.0015273393,0.00061511964,0.000010651499,0.000089276386,0.000005535936,0.00007658383,0.00006551343,0.000114888855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986166,0.000068244386,0.00027011114,0.00066447275,0.00004746532,0.0003331582],"domain_scores_gemma":[0.999219,0.000045695222,0.00014657846,0.0003838568,0.00011084636,0.00009399924],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010936084,0.00035176481,0.00035098972,0.00030427217,0.00007528085,0.000058110072,0.00026465478,0.0003804206,0.000022740944],"category_scores_gemma":[0.000015766493,0.00045044863,0.00006347109,0.00036568946,0.00009254618,0.00024107272,0.0004984391,0.0005991955,0.0000058864757],"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":[0.000021345279,0.000015416692,0.0016498276,0.00012427212,0.000035114837,0.000043689677,0.00008891423,0.9960805,0.000040791845,0.00015947428,0.000034161185,0.0017064756],"study_design_scores_gemma":[0.0003212522,0.00003096183,0.00076339615,0.00069099176,0.000031819756,0.0000034123364,0.000040605093,0.9966698,0.00008807776,0.0009333618,0.000011122273,0.00041515534],"about_ca_topic_score_codex":0.000034345507,"about_ca_topic_score_gemma":0.0002869752,"teacher_disagreement_score":0.59647214,"about_ca_system_score_codex":0.00046126958,"about_ca_system_score_gemma":0.000028831031,"threshold_uncertainty_score":0.9997947},"labels":[],"label_agreement":null},{"id":"W4307874069","doi":"10.32604/cmc.2023.028597","title":"Analysis on D2D Heterogeneous Networks with State-Dependent Priority燭raffic","year":2022,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Windsor","funders":"Government of Jiangsu Province","keywords":"Priority inheritance; Computer science; Priority queue; Priority ceiling protocol; Queueing theory; Queue; Correctness; Network packet; Computer network; Scheduling (production processes); Priority inversion; Real-time computing; Deadline-monotonic scheduling; Dynamic priority scheduling; Mathematical optimization; Algorithm; Round-robin scheduling; Rate-monotonic scheduling; Quality of service; Mathematics","score_opus":0.004609764940400173,"score_gpt":0.18651933228623077,"score_spread":0.1819095673458306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307874069","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":[0.63893974,0.0002470608,0.3475683,0.000057095116,0.009001691,0.0017265668,0.00034663093,0.00201956,0.00009332149],"genre_scores_gemma":[0.98142755,0.00018441514,0.013917476,0.0005181763,0.0016580987,0.00039114323,0.0011389154,0.0005183954,0.00024585152],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9906315,0.0009923173,0.0026186057,0.0021569044,0.0013305537,0.0022701025],"domain_scores_gemma":[0.99541247,0.00049718475,0.0011514754,0.0020675738,0.00035801853,0.0005132818],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0018054611,0.0017874754,0.0029841473,0.0012024054,0.00070467783,0.0015015341,0.0019304273,0.00039434066,0.0013021324],"category_scores_gemma":[0.000023244902,0.0019175037,0.00042483702,0.0015009351,0.00022964035,0.0005961417,0.0015084082,0.00072583667,0.00015358823],"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":[0.0010234698,0.00024876636,0.00031330137,0.00015497529,0.0018569909,0.0005573472,0.00060117524,0.9554054,0.027435813,0.00010987356,0.0019031126,0.010389751],"study_design_scores_gemma":[0.017606534,0.003871641,0.009493972,0.0013979194,0.0034955177,0.0009333512,0.00039591518,0.6063874,0.30783588,0.0002420586,0.035331246,0.013008599],"about_ca_topic_score_codex":0.00012591887,"about_ca_topic_score_gemma":0.00009315067,"teacher_disagreement_score":0.34901804,"about_ca_system_score_codex":0.000906769,"about_ca_system_score_gemma":0.00008392674,"threshold_uncertainty_score":0.99961084},"labels":[],"label_agreement":null},{"id":"W4309227257","doi":"10.1109/icnp55882.2022.9940259","title":"Delay Laxity-Based Scheduling with Double-Deep Q-Learning for Time-Critical Applications","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Goodput; Computer science; Network packet; Queuing delay; Markov decision process; Queue; Mathematical optimization; Scheduling (production processes); Markov process; Q-learning; Computer network; Artificial intelligence; Reinforcement learning; Throughput; Mathematics; Wireless","score_opus":0.006776381870420725,"score_gpt":0.2284538729198936,"score_spread":0.22167749104947287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309227257","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":[0.0009710888,0.00009631029,0.9954772,0.000096913005,0.00003690061,0.00046074193,0.000003589287,0.00082523393,0.002032039],"genre_scores_gemma":[0.61344445,0.0000029783157,0.3845339,0.00006060578,0.000073736934,0.0014906784,0.0001426945,0.00007299698,0.00017796158],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928766,0.000014889123,0.00013928961,0.00018082367,0.00013511024,0.00024219717],"domain_scores_gemma":[0.9995271,0.00019357166,0.000018453162,0.00014458506,0.000056457757,0.000059842616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009591659,0.00011327938,0.00011294718,0.00006499731,0.00036226577,0.000025519792,0.000103802195,0.000030504743,0.00028095662],"category_scores_gemma":[0.000008485674,0.000120762044,0.000031323278,0.00030200157,0.000024701307,0.000094107185,0.00002510099,0.00022274273,0.000017404354],"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":[0.00004063007,0.000018804383,0.000058455214,0.000029164186,0.000011508916,6.750283e-7,0.000018963792,0.99278724,0.0002075463,0.0045948965,0.000035907517,0.0021962347],"study_design_scores_gemma":[0.00064796046,0.0000539801,0.0000035481803,0.000004903318,0.000016076574,0.0000038121668,0.000052084888,0.9866831,0.0003823796,0.00011303209,0.011865729,0.0001734068],"about_ca_topic_score_codex":8.952955e-7,"about_ca_topic_score_gemma":0.0000024597518,"teacher_disagreement_score":0.6124733,"about_ca_system_score_codex":0.0000944981,"about_ca_system_score_gemma":0.000016887805,"threshold_uncertainty_score":0.49245334},"labels":[],"label_agreement":null},{"id":"W4382119870","doi":"10.1109/lsp.2023.3289438","title":"Global Optimization of Long-Term Average Proportional Fair Throughput via Convex Reformulation","year":2023,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Ericsson (Canada); University of Toronto","funders":"","keywords":"Maximization; Term (time); Mathematics; Regular polygon; Mathematical optimization; Convex function; Convex optimization; Proportionally fair; Combinatorics; Throughput; Optimization problem; Discrete mathematics; Algorithm; Applied mathematics; Computer science","score_opus":0.010719856417022302,"score_gpt":0.23783938757357084,"score_spread":0.22711953115654854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382119870","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":[0.12575322,0.000052856845,0.87285143,0.00010687519,0.00023515048,0.00021134161,0.000009202403,0.00065763114,0.00012227635],"genre_scores_gemma":[0.9888201,0.000022506985,0.010466386,0.00011460296,0.00022168875,0.000023174187,0.0002654093,0.000052214516,0.00001395838],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986226,0.000021065825,0.00042986663,0.0002489244,0.0003716949,0.00030583414],"domain_scores_gemma":[0.9995131,0.000020459953,0.00017181455,0.00012831163,0.00011247844,0.000053865308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001140197,0.00020730584,0.00021505922,0.000118003634,0.00011040046,0.000040919072,0.00013111321,0.00010389,0.00003301858],"category_scores_gemma":[0.0000056373165,0.00021979427,0.000055849414,0.00087718986,0.000076708035,0.00068225333,0.000017659067,0.00011162017,0.000014338297],"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":[0.000019278914,0.000012256389,0.0028107623,0.00023297535,0.00002247537,0.000013069394,0.00008858959,0.9720532,0.0084840795,0.000008485444,0.00023350395,0.01602137],"study_design_scores_gemma":[0.00031813007,0.000016801125,0.0049348967,0.00013928895,0.000016445938,0.000010298887,0.0000047853036,0.99070054,0.0035286718,0.00009191506,0.000005727607,0.0002324714],"about_ca_topic_score_codex":0.000002102975,"about_ca_topic_score_gemma":0.0000016309839,"teacher_disagreement_score":0.86306685,"about_ca_system_score_codex":0.00020542047,"about_ca_system_score_gemma":0.00003302475,"threshold_uncertainty_score":0.896295},"labels":[],"label_agreement":null},{"id":"W4387883707","doi":"10.1109/icc45041.2023.10279566","title":"Augmenting Backpressure Scheduling and Routing for Wireless Computing Networks","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Waterloo; Memorial University of Newfoundland; Queen's University","funders":"","keywords":"Computer science; Distributed computing; Computer network; Provisioning; Wireless network; Utility maximization; Network packet; Scheduling (production processes); Wireless; Engineering","score_opus":0.009810154097804122,"score_gpt":0.2269079245727477,"score_spread":0.21709777047494358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387883707","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":[0.12732564,0.00019033892,0.87010354,0.000018836103,0.00031033528,0.00022428785,0.0000012133087,0.0013859099,0.00043986583],"genre_scores_gemma":[0.9362972,0.00008228937,0.06307945,0.000021579815,0.0003193011,0.0000140861775,0.00003459237,0.00006874914,0.00008277883],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990024,0.000010090301,0.00027517838,0.00020890763,0.000077367295,0.00042605423],"domain_scores_gemma":[0.9995221,0.00023570049,0.000043132524,0.00010628562,0.000036661222,0.000056131263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026861334,0.00015080736,0.00017560228,0.000066051005,0.00020668138,0.000068323694,0.00007381083,0.00008635604,0.000004458051],"category_scores_gemma":[0.000025235417,0.00016756145,0.00003248573,0.00034989926,0.00001592386,0.0001531546,0.00007130708,0.00013042666,0.0000034899851],"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":[0.0000020009911,0.0000013681015,0.0018243736,0.00006943799,0.000018951008,8.6625187e-7,0.000075135176,0.96181935,0.00024792622,0.000801647,0.00012667882,0.03501224],"study_design_scores_gemma":[0.00027602364,0.0000052761584,0.0003124267,0.00007998486,0.000011866308,0.0000015181737,0.00017760771,0.9985257,0.00022935195,0.000056278812,0.00013171077,0.0001922471],"about_ca_topic_score_codex":0.0000013759054,"about_ca_topic_score_gemma":0.0000031845877,"teacher_disagreement_score":0.8089715,"about_ca_system_score_codex":0.000022811622,"about_ca_system_score_gemma":0.0000028161137,"threshold_uncertainty_score":0.6832958},"labels":[],"label_agreement":null},{"id":"W4388683292","doi":"","title":"Cluster-based Resource Management in OFDMA Femtocell Networks with QoS Guarantees","year":2014,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Femtocell; Computer network; Computer science; Quality of service; Resource allocation; Cluster (spacecraft); Resource management (computing); Orthogonal frequency-division multiple access; Orthogonal frequency-division multiplexing; Distributed computing; Base station","score_opus":0.0056843542863732185,"score_gpt":0.1875262517690825,"score_spread":0.1818418974827093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388683292","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":[0.017984677,0.001046048,0.9519898,0.0009727839,0.00019322857,0.0009086153,0.000012582543,0.0006364552,0.026255803],"genre_scores_gemma":[0.85389394,0.0011288265,0.14204748,0.00012757568,0.00006612485,0.00039934152,0.00069067016,0.00018969408,0.0014563425],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962154,0.0016671763,0.0005664583,0.0007019746,0.00035864816,0.0004903112],"domain_scores_gemma":[0.9967077,0.00067516905,0.000284623,0.0018005195,0.00041261886,0.00011940607],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0018680574,0.0004750507,0.00045508237,0.00030427336,0.00013295558,0.00021147472,0.000945225,0.00032434516,0.0000401049],"category_scores_gemma":[0.00006275235,0.0005129908,0.00010762737,0.000531686,0.0001273295,0.00009193024,0.0005182107,0.0008126616,0.000010394601],"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":[0.00002479943,0.00011479636,0.00058913155,0.00030860674,0.00005550243,0.0000060820644,0.0005244587,0.97571623,0.000015686232,0.0014521249,0.0007202862,0.020472303],"study_design_scores_gemma":[0.0009222943,3.7973163e-7,0.0006768281,0.0033671062,0.000042917753,0.0000015665996,0.0000387145,0.98674506,0.0011299016,0.0001586491,0.006398743,0.0005178657],"about_ca_topic_score_codex":0.00007716232,"about_ca_topic_score_gemma":0.0008206711,"teacher_disagreement_score":0.83590925,"about_ca_system_score_codex":0.00020990212,"about_ca_system_score_gemma":0.000038619866,"threshold_uncertainty_score":0.9997322},"labels":[],"label_agreement":null},{"id":"W4391878022","doi":"10.1109/tcomm.2024.3366816","title":"Multi-Band Wireless Communication Networks: Fundamentals, Challenges, and Resource Allocation","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":49,"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 Manitoba; University of Victoria; University of Guelph; York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wireless; Computer science; Computer network; Resource allocation; Wireless network; Resource management (computing); Telecommunications; Radio resource management; Distributed computing","score_opus":0.03237932125287004,"score_gpt":0.2570997276444319,"score_spread":0.22472040639156185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391878022","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":[0.0007900851,0.056494594,0.93759936,0.0011835141,0.000247844,0.00042176017,0.000025630268,0.0012930327,0.0019441615],"genre_scores_gemma":[0.84506017,0.14285015,0.011406821,0.0000440365,0.00002701039,0.00026313603,0.00008624846,0.0000843131,0.00017813637],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988625,0.0001572121,0.00035070552,0.0002626918,0.00013391908,0.00023297315],"domain_scores_gemma":[0.99788445,0.00042661547,0.000036981142,0.0015040999,0.000049607326,0.00009825708],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021308722,0.00023798236,0.0001823378,0.00021128716,0.00043639148,0.000115912444,0.0004744399,0.00015584934,0.000016365808],"category_scores_gemma":[0.0000023589187,0.00027566974,0.00006203577,0.00038347958,0.000192938,0.00041301805,0.000007652998,0.00059442804,0.000030317377],"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":[0.000007311792,0.00010578819,0.0000010197745,0.000065577784,0.00009423827,5.3491385e-7,0.0009591376,0.78082275,0.0005834633,0.0014225086,0.00023114977,0.2157065],"study_design_scores_gemma":[0.0002619933,0.000024346808,0.000060209677,0.00030386692,0.000056936784,0.000012575983,0.0003373654,0.98234546,0.0007088145,0.00011894718,0.015498045,0.00027144188],"about_ca_topic_score_codex":0.000009955187,"about_ca_topic_score_gemma":0.00027791914,"teacher_disagreement_score":0.9261926,"about_ca_system_score_codex":0.00018600991,"about_ca_system_score_gemma":0.000016988595,"threshold_uncertainty_score":0.99996954},"labels":[],"label_agreement":null},{"id":"W4392940210","doi":"10.1109/tcomm.2024.3379368","title":"Distributed-Optimization With Centralized-Refining for Efficient Resource Allocation in Future Wireless Networks","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada Research Chairs","keywords":"Computer science; Resource allocation; Wireless; Distributed computing; Refining (metallurgy); Wireless network; Computer network; Resource management (computing); Telecommunications","score_opus":0.010284369780962782,"score_gpt":0.23265946193595569,"score_spread":0.2223750921549929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392940210","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":[0.00059237913,0.0009862084,0.9956946,0.00068652286,0.00037016653,0.00048634905,0.00010338293,0.0008253306,0.00025506687],"genre_scores_gemma":[0.9594601,0.001615217,0.0374568,0.000030851406,0.00007638197,0.0006459513,0.0005661585,0.00010225961,0.00004632539],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988708,0.000067172,0.0003537214,0.00025879213,0.0001382412,0.0003112552],"domain_scores_gemma":[0.99871683,0.00032249233,0.00003958751,0.00077832537,0.00007362314,0.0000691354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014373475,0.0002260073,0.00018218129,0.00023773867,0.00028313603,0.00009388331,0.0003266577,0.0001498414,0.000011510021],"category_scores_gemma":[0.0000021461433,0.00023390052,0.000067962166,0.0011454141,0.00006980201,0.00018886535,0.0000026614352,0.00045869328,0.000003974833],"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":[0.00003403104,0.000081013764,0.0000031195912,0.000050212755,0.000041264513,6.08734e-7,0.00023804679,0.9824323,0.0000341523,0.0009379664,0.00013505199,0.016012253],"study_design_scores_gemma":[0.00042521374,0.00003583299,0.000012957317,0.00027833515,0.000049866674,0.0000046486407,0.00017047788,0.99231946,0.00024918834,0.000009870752,0.0061971317,0.0002470253],"about_ca_topic_score_codex":0.0000063841785,"about_ca_topic_score_gemma":0.00015257724,"teacher_disagreement_score":0.95886767,"about_ca_system_score_codex":0.0003180236,"about_ca_system_score_gemma":0.000033692646,"threshold_uncertainty_score":0.9538186},"labels":[],"label_agreement":null},{"id":"W4400230865","doi":"10.1109/tbc.2024.3410706","title":"Packet Retransmission Schemes and Trials for Broadcast Services in Mobile Scenarios","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Broadcasting","topic":"Advanced Wireless Network Optimization","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":"Western University","funders":"National Natural Science Foundation of China","keywords":"Retransmission; Computer network; Computer science; Network packet; Broadcasting (networking); Mobile radio; Broadcast law; Packet switching; Mobile telephony; Telecommunications; Radio broadcasting; Packet radio; Commercial broadcasting","score_opus":0.02878536261445723,"score_gpt":0.2868984255987331,"score_spread":0.25811306298427583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400230865","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":[0.07561851,0.003560336,0.9185982,0.00002789545,0.00070346997,0.0007146422,0.00006484497,0.00061590155,0.00009621608],"genre_scores_gemma":[0.9826121,0.0014345044,0.015325895,0.000017115015,0.00013102152,0.00028230782,0.000014615415,0.000091590235,0.000090852525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986968,0.00004637474,0.00049228664,0.00033057516,0.00012789624,0.00030604668],"domain_scores_gemma":[0.999139,0.0005814583,0.0000340781,0.0001353046,0.00003082439,0.00007932374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040132762,0.00023599826,0.00033833584,0.00028596318,0.00012492001,0.00010991089,0.00007276198,0.00015077605,0.000037968977],"category_scores_gemma":[0.000009993997,0.00023470544,0.00009490487,0.0004497033,0.000023986133,0.00037442456,8.5913683e-7,0.0003035584,0.0000059010586],"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":[0.000031871372,0.000014178293,0.0000053743133,0.00046688513,0.000022371307,0.0000032832113,0.00038865814,0.6300153,0.0057733175,0.000004916539,0.000015578347,0.36325824],"study_design_scores_gemma":[0.00056385866,0.00006688542,0.000006642935,0.0011690519,0.000040938918,0.000012375698,0.00017628766,0.97376734,0.018203674,0.00006889074,0.005678239,0.0002457859],"about_ca_topic_score_codex":0.0000061205806,"about_ca_topic_score_gemma":0.00002204803,"teacher_disagreement_score":0.90699357,"about_ca_system_score_codex":0.00009309576,"about_ca_system_score_gemma":0.000017780614,"threshold_uncertainty_score":0.95710105},"labels":[],"label_agreement":null},{"id":"W4401111081","doi":"10.1109/mi-sta61267.2024.10599667","title":"On Demand User Association and Load Distribution with Guaranteed Rate in Multi UAV-Assisted Cellular Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"École de Technologie Supérieure","funders":"","keywords":"Association (psychology); Computer science; Computer network; Load distribution; Engineering; Psychology","score_opus":0.004994811912271606,"score_gpt":0.1947356652572719,"score_spread":0.1897408533450003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401111081","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":[0.19004296,0.0005582607,0.80851233,0.000030242521,0.00015227485,0.00018147493,0.0000066791486,0.00034258747,0.00017317597],"genre_scores_gemma":[0.99810916,0.00020483746,0.001121636,0.000021677099,0.00003729151,0.000020584393,0.00011820879,0.000033798646,0.0003328002],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927807,0.00003661888,0.00016967441,0.00019081315,0.0001128213,0.00021200835],"domain_scores_gemma":[0.9996977,0.00012969646,0.000023480416,0.00008497932,0.00003161616,0.00003254333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019577025,0.00014375568,0.00013464413,0.000045431574,0.000033157445,0.000072183706,0.00003037795,0.00011998601,0.000012360546],"category_scores_gemma":[0.000021061283,0.00012517875,0.000016326054,0.00036189024,0.000010086729,0.0001740537,0.000008811175,0.00018739814,0.0000073603796],"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":[0.00002888144,0.000012435303,0.001363614,0.000030382476,0.00002818818,0.000013513112,0.00005330149,0.9959798,0.0003004256,0.0004229657,0.00041936457,0.0013471458],"study_design_scores_gemma":[0.0005672938,0.000023407098,0.009967361,0.00015935168,0.000016278149,0.0000010851038,0.000015174593,0.9882051,0.00048402057,0.000031815925,0.000367014,0.000162118],"about_ca_topic_score_codex":0.000008400802,"about_ca_topic_score_gemma":0.00015877948,"teacher_disagreement_score":0.8080662,"about_ca_system_score_codex":0.00043679547,"about_ca_system_score_gemma":0.000009290868,"threshold_uncertainty_score":0.51046413},"labels":[],"label_agreement":null},{"id":"W4402508517","doi":"10.1109/tnse.2024.3460479","title":"Augmenting Backpressure Scheduling and Routing for Wireless Computing Networks","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Network Science and Engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Calgary; University of Waterloo; Queen's University","funders":"","keywords":"Computer science; Computer network; Scheduling (production processes); Wireless; Distributed computing; Wireless network; Dynamic Source Routing; Routing (electronic design automation); Wireless Routing Protocol; Routing protocol; Telecommunications; Mathematical optimization; Mathematics","score_opus":0.006654377918144828,"score_gpt":0.2111918904406165,"score_spread":0.20453751252247168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402508517","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":[0.0419091,0.0016781796,0.9536287,0.000018336254,0.0017131069,0.00023298549,0.000002556284,0.00076906953,0.00004796469],"genre_scores_gemma":[0.9639754,0.00039751094,0.035104968,0.000018760466,0.00040132873,0.000026579177,0.0000013258135,0.00006317572,0.000010929026],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851257,0.000005823304,0.00028031145,0.0003950133,0.00018821348,0.00061805797],"domain_scores_gemma":[0.99942005,0.00025043348,0.000020409752,0.00012460815,0.000053549305,0.00013097907],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006065841,0.00023261858,0.00019435315,0.0001723788,0.00050552894,0.0003268819,0.00011433032,0.00008925822,0.0000017760723],"category_scores_gemma":[0.0000071137815,0.00025467592,0.00003914395,0.00092682085,0.00008420369,0.00052212656,0.0000048621073,0.00034327168,7.1420703e-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":[0.0000026994967,0.0000024442138,0.000010989443,0.00013120285,0.000020544978,0.0000015781953,0.00010494726,0.9263025,0.0010274508,0.0003373132,0.0000140928205,0.07204422],"study_design_scores_gemma":[0.00012599416,0.000019070649,0.000025516725,0.0004990593,0.000031110936,0.000013875066,0.00003971036,0.99812895,0.0006226093,0.000013724507,0.00021099043,0.00026935936],"about_ca_topic_score_codex":0.0000013482494,"about_ca_topic_score_gemma":0.0000020052196,"teacher_disagreement_score":0.92206633,"about_ca_system_score_codex":0.00008466821,"about_ca_system_score_gemma":0.000021827507,"threshold_uncertainty_score":0.9999905},"labels":[],"label_agreement":null},{"id":"W4402834002","doi":"10.1109/vtc2024-spring62846.2024.10682823","title":"On the Resource Allocation and User Association in Future Multi-Band Wireless Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 du Québec à Montréal","funders":"","keywords":"Computer science; Resource allocation; Association (psychology); Wireless; Wireless network; Computer network; Resource management (computing); Resource (disambiguation); Telecommunications; Psychology","score_opus":0.004177215949410097,"score_gpt":0.19312126566839896,"score_spread":0.18894404971898887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402834002","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":[0.16196093,0.0021483938,0.8289093,0.0022078592,0.00071988977,0.000463659,0.0000024786082,0.00074691087,0.0028406258],"genre_scores_gemma":[0.99769706,0.0005939343,0.00058192026,0.00013764294,0.00023687481,0.000028521716,0.000017968172,0.000034060427,0.00067202735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994656,0.00003320676,0.00012480997,0.00013486312,0.000093864284,0.00014764196],"domain_scores_gemma":[0.9996175,0.00023528775,0.000014818977,0.00009860344,0.000013453447,0.000020318625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017962503,0.00009964534,0.000075014264,0.00005154656,0.000038996277,0.00007056652,0.000047137517,0.00011749972,0.000016321574],"category_scores_gemma":[0.000013525901,0.00007497819,0.000014227363,0.00028736354,0.000007333852,0.00012208009,0.00000805755,0.00023575137,0.000006576443],"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":[0.000003123172,0.000004748702,0.00042829744,0.00001215363,0.000011860891,0.0000010410328,0.00015136962,0.9804763,0.000054272718,0.0066686254,0.0050065843,0.007181614],"study_design_scores_gemma":[0.00011947124,0.000005249481,0.001674129,0.000060003844,0.0000046211203,4.8878206e-7,0.00007575335,0.9923342,0.00012672872,0.000060971357,0.005445653,0.00009274347],"about_ca_topic_score_codex":0.0000030906983,"about_ca_topic_score_gemma":0.000099343066,"teacher_disagreement_score":0.8357361,"about_ca_system_score_codex":0.00015611896,"about_ca_system_score_gemma":0.0000035432943,"threshold_uncertainty_score":0.3057522},"labels":[],"label_agreement":null},{"id":"W4402916039","doi":"10.1109/twc.2024.3465440","title":"Diverse and Differentiated QoS Provisioning for 6G Communications via Demand-Aware Prioritization and DEI-Based Resource Allocation","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Quality of service; Provisioning; Resource allocation; Computer network; Prioritization; Resource management (computing); Wireless; Telecommunications; Business; Process management","score_opus":0.018633987748085546,"score_gpt":0.25661248985931384,"score_spread":0.23797850211122829,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402916039","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":[0.008455936,0.0016833413,0.9866526,0.00078591873,0.0001985269,0.0010316509,0.00012401308,0.0010035207,0.00006449208],"genre_scores_gemma":[0.9713201,0.0035573163,0.02375511,0.000049854054,0.000030156398,0.0006995541,0.00043090613,0.000103571576,0.000053442356],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870497,0.00013870087,0.00042153616,0.00032925,0.00015379391,0.00025172616],"domain_scores_gemma":[0.9975072,0.0008243679,0.00006547089,0.0013421756,0.00014385031,0.00011692884],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017267768,0.0002772965,0.00023190693,0.0003329645,0.0009876771,0.00018712945,0.00045887035,0.00017697181,0.0000068542563],"category_scores_gemma":[0.000008208444,0.0003165875,0.00007164368,0.0005705389,0.00024566415,0.00042249224,0.00001812666,0.00041974842,0.0000048761503],"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":[0.000040108665,0.00020271781,0.00004162016,0.00042555164,0.00016331373,6.787181e-7,0.0008949222,0.7510621,0.0045821555,0.0017783825,0.0001668819,0.24064155],"study_design_scores_gemma":[0.00053034385,0.00004983539,0.00009389813,0.0003965351,0.00014902111,0.0000059864265,0.00019660188,0.99427754,0.002163138,0.00016100933,0.001663525,0.00031257913],"about_ca_topic_score_codex":0.000015027543,"about_ca_topic_score_gemma":0.00024175084,"teacher_disagreement_score":0.9628975,"about_ca_system_score_codex":0.00015223073,"about_ca_system_score_gemma":0.00004188177,"threshold_uncertainty_score":0.9999286},"labels":[],"label_agreement":null},{"id":"W4403052636","doi":"10.1109/mwc.019.2300540","title":"Resource Allocation for Ris-Empowered Wireless Communications: Low-Complexity and Robust Designs","year":2024,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Université Laval","funders":"National Natural Science Foundation of China","keywords":"Computer science; Wireless; Resource allocation; Computer network; Resource management (computing); Telecommunications; Distributed computing","score_opus":0.07607656483600968,"score_gpt":0.29635177583349626,"score_spread":0.2202752109974866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403052636","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":[0.014580425,0.012516367,0.96408004,0.0022638263,0.0003975549,0.0015945645,0.00019990013,0.0022187664,0.002148563],"genre_scores_gemma":[0.8918097,0.010789085,0.094999336,0.00008744391,0.00011816184,0.0009981784,0.000860697,0.00018399867,0.0001533936],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99801046,0.00022180499,0.00068536005,0.00042626786,0.00020583978,0.00045028058],"domain_scores_gemma":[0.99483615,0.0012405342,0.000109462235,0.003447919,0.00020529577,0.00016063501],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004410276,0.00038211513,0.0003802003,0.00026288262,0.00075794675,0.00026914888,0.001678771,0.00023644474,0.000009961881],"category_scores_gemma":[0.000040176892,0.00044996664,0.00011416549,0.00078356155,0.00063653046,0.0005881967,0.00029699714,0.00057335326,0.000028550456],"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":[0.00005845115,0.00036507408,0.00013178773,0.001213023,0.00038605722,0.0000024118467,0.003541234,0.67234933,0.014878754,0.15799522,0.0101147145,0.13896397],"study_design_scores_gemma":[0.00037151732,0.000025920714,0.00009789356,0.00048107895,0.0000778117,0.00001073805,0.00028311912,0.97667426,0.0010811607,0.0019410991,0.018471308,0.00048407854],"about_ca_topic_score_codex":0.0000244193,"about_ca_topic_score_gemma":0.00024335849,"teacher_disagreement_score":0.8772293,"about_ca_system_score_codex":0.0002680261,"about_ca_system_score_gemma":0.00007289695,"threshold_uncertainty_score":0.9997952},"labels":[],"label_agreement":null},{"id":"W4403937971","doi":"10.1109/iscc61673.2024.10733671","title":"A Context Augmented Multi-Play Multi-Armed Bandit Algorithm for Fast Channel Allocation in Opportunistic Spectrum Access","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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)","funders":"National Natural Science Foundation of China","keywords":"Computer science; Context (archaeology); Channel (broadcasting); Channel allocation schemes; Spectrum (functional analysis); Computer network; Algorithm; Telecommunications; Wireless; Physics","score_opus":0.03383483530014553,"score_gpt":0.2896750939574081,"score_spread":0.25584025865726256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403937971","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":[0.00032822648,0.00036019474,0.9963985,0.00011882266,0.00089845003,0.00094948296,0.00007462245,0.0007628351,0.0001088459],"genre_scores_gemma":[0.944129,0.0003223903,0.052539203,0.00007464617,0.00019332019,0.0005442137,0.0006816347,0.0001309209,0.0013846557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880874,0.000015839998,0.0003587836,0.0003291258,0.000109697256,0.0003777967],"domain_scores_gemma":[0.9995677,0.00010387298,0.00003091027,0.0001657305,0.000038745664,0.0000930584],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011465791,0.00023802792,0.00022523213,0.00024742458,0.00004675543,0.00011577408,0.00016583489,0.000108941254,0.0000833037],"category_scores_gemma":[0.00002155167,0.00024522695,0.000053070624,0.00039582732,0.000025310836,0.00045631945,0.000034055905,0.00015275972,0.000023659655],"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":[0.000009767544,0.00006999309,0.000016895456,0.00014955061,0.00006099289,0.000019909301,0.00034589643,0.90411514,0.00029039674,0.00026198465,0.00069214427,0.09396733],"study_design_scores_gemma":[0.0012208811,0.000023389102,0.00016073861,0.00014660326,0.00001770178,0.000004149686,0.0001446482,0.99601734,0.0012290918,0.00006461907,0.000690275,0.00028054294],"about_ca_topic_score_codex":0.000033216293,"about_ca_topic_score_gemma":0.0004921267,"teacher_disagreement_score":0.94385934,"about_ca_system_score_codex":0.0002552176,"about_ca_system_score_gemma":0.000030768453,"threshold_uncertainty_score":1},"labels":[],"label_agreement":null},{"id":"W4404057060","doi":"10.1109/tnsm.2024.3491432","title":"QoE-Oriented Dependent Task Scheduling Under Multi-Dimensional QoS Constraints Over Distributed Networks","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Network and Service Management","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Western University","funders":"Natural Science Foundation of Fujian Province; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Computer science; Scheduling (production processes); Quality of service; Distributed computing; Computer network; Processor scheduling; Task (project management); Resource (disambiguation)","score_opus":0.007862726144893627,"score_gpt":0.21581186756987972,"score_spread":0.20794914142498608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404057060","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":[0.0047601,0.0007880691,0.9898268,0.00013591076,0.0028561132,0.0004965742,0.000049398386,0.0008429278,0.00024413165],"genre_scores_gemma":[0.98249114,0.0016707698,0.014608009,0.00050877914,0.00027842599,0.00011286372,0.00012634427,0.000095605916,0.00010805869],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983428,0.00003974175,0.000361575,0.0004737146,0.00025989965,0.0005222757],"domain_scores_gemma":[0.9994161,0.00009214831,0.00003048415,0.0002609705,0.000045113225,0.00015519712],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001361646,0.00035843762,0.00023320963,0.00013224836,0.0002653915,0.000116044954,0.000112304275,0.00014891112,0.00012418628],"category_scores_gemma":[3.034835e-7,0.00037839988,0.0000776757,0.000775837,0.00004872477,0.00020990935,0.000008034087,0.00042994157,0.00003034434],"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":[0.00003122656,0.000055025863,0.0000054732404,0.00014773871,0.00037584596,0.00003858796,0.00003964439,0.97515047,0.000020892297,0.00052969065,0.00029996524,0.023305416],"study_design_scores_gemma":[0.00072552555,0.000021025757,0.0001450095,0.00034585927,0.00016637707,0.000010120681,0.00009472969,0.99635184,0.000030996176,0.000055187655,0.0016822155,0.00037113775],"about_ca_topic_score_codex":0.000007035719,"about_ca_topic_score_gemma":0.000103698694,"teacher_disagreement_score":0.97773105,"about_ca_system_score_codex":0.00015999436,"about_ca_system_score_gemma":0.000011076186,"threshold_uncertainty_score":0.9998668},"labels":[],"label_agreement":null},{"id":"W4404235631","doi":"10.1016/j.tre.2024.103826","title":"Mobile COVID-19 vaccination scheduling with capacity selection","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Ministry of Education, India; National Natural Science Foundation of China","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Vaccination; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Scheduling (production processes); Selection (genetic algorithm); Computer science; Operations research; Virology; Engineering; Medicine; Operations management; Outbreak; Infectious disease (medical specialty); Artificial intelligence","score_opus":0.07510274465677098,"score_gpt":0.36190406534316416,"score_spread":0.2868013206863932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404235631","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":[0.007900774,0.04400497,0.9450766,0.00022333529,0.00014981607,0.0014652843,0.00019505966,0.0007512481,0.00023295483],"genre_scores_gemma":[0.79288405,0.19558272,0.009096684,0.000116511204,0.00008642551,0.00063820416,0.001458994,0.00006831194,0.000068116846],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980976,0.00007956342,0.0005353924,0.0004139483,0.00052334194,0.00035014862],"domain_scores_gemma":[0.99904,0.00019931389,0.000048511753,0.00014101234,0.00031450263,0.00025666508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006812401,0.00023158193,0.00028456058,0.00022848306,0.00022924966,0.000083371524,0.00008202483,0.00011015868,0.00024996622],"category_scores_gemma":[0.000035044774,0.00021425734,0.000053540673,0.0012608018,0.00009585884,0.00037855454,7.19948e-7,0.00046434574,0.000015099975],"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":[0.000021513928,0.00002803013,0.0010692296,0.01330402,0.00006850415,0.000035274268,0.00049432105,0.9522501,0.00006673897,0.019272754,0.0009638535,0.012425616],"study_design_scores_gemma":[0.0014660608,0.00067823177,0.012715083,0.0072583663,0.0006413669,0.000019055247,0.00031546116,0.6045939,0.00045611657,0.0049987533,0.36541998,0.0014376278],"about_ca_topic_score_codex":0.000045003955,"about_ca_topic_score_gemma":0.0009255808,"teacher_disagreement_score":0.9359799,"about_ca_system_score_codex":0.00012839328,"about_ca_system_score_gemma":0.000119268916,"threshold_uncertainty_score":0.87371606},"labels":[],"label_agreement":null},{"id":"W4405490654","doi":"10.1109/iccspa61559.2024.10794260","title":"Scheduling Deadline-Constrained Traffic over Hybrid Channels","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Scheduling (production processes); Distributed computing; Computer network; Mathematical optimization; Mathematics","score_opus":0.007286762476042762,"score_gpt":0.21956210727561531,"score_spread":0.21227534479957255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405490654","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":[0.14246781,0.001330828,0.8492017,0.000051781462,0.0011053904,0.00011725689,0.000004433719,0.002555452,0.003165369],"genre_scores_gemma":[0.97165066,0.00014652008,0.027303115,0.00003388551,0.00039420553,0.000014526768,0.000026574511,0.00006581971,0.0003646869],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931574,0.0000055147198,0.00017063269,0.00017588017,0.00009203482,0.00024022217],"domain_scores_gemma":[0.999755,0.00004987746,0.000006568137,0.00011463476,0.000014588755,0.000059286842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000054267457,0.00014544684,0.000114106544,0.000098699675,0.000028991464,0.00007435112,0.00006752407,0.000045729183,0.0003040368],"category_scores_gemma":[0.000007850561,0.00014403983,0.00005016959,0.00024239063,0.000018884783,0.00024060103,0.000011414914,0.00014728661,0.00010689056],"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":[0.0000012155457,0.0000031803118,0.0000016508451,0.000054504842,0.000023164659,0.000019070883,0.000039620216,0.97354096,0.000459149,0.0012957269,0.0005446523,0.024017103],"study_design_scores_gemma":[0.00011163597,0.000006322696,0.0000026414966,0.00007535691,0.000008815921,0.00001576612,0.000013746017,0.9956576,0.0017768216,0.00015359893,0.002000113,0.00017756778],"about_ca_topic_score_codex":4.7071498e-7,"about_ca_topic_score_gemma":0.0000013534643,"teacher_disagreement_score":0.82918286,"about_ca_system_score_codex":0.000050354978,"about_ca_system_score_gemma":0.00001302146,"threshold_uncertainty_score":0.58737737},"labels":[],"label_agreement":null},{"id":"W4406755420","doi":"10.1007/978-3-031-76455-4_11","title":"Modeling and Performance Analysis of Cellular Systems","year":2024,"lang":"en","type":"book-chapter","venue":"Textbooks in telecommunication engineering","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto; InterDigital (Canada); Telus (Canada)","funders":"","keywords":"Computer science","score_opus":0.010392446390940285,"score_gpt":0.19401279194909046,"score_spread":0.18362034555815018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406755420","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":[0.018288758,0.098143466,0.7130342,0.0000092616965,0.0006565048,0.00097434584,0.00005849685,0.0016398422,0.16719513],"genre_scores_gemma":[0.98199695,0.009382316,0.0031769623,0.000001185367,0.000036066995,0.00003369994,0.00013423494,0.00016034485,0.0050782287],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988248,0.000005187185,0.00063846505,0.00021052135,0.00014141163,0.00017966083],"domain_scores_gemma":[0.9991156,0.000064761414,0.000066469795,0.0006659218,0.000046655063,0.00004058477],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017051135,0.000305557,0.00056344573,0.0011194178,0.000022714943,0.000026712041,0.0002597961,0.00025444542,0.000010894577],"category_scores_gemma":[0.0000048055795,0.00037789118,0.00008225321,0.00022987455,0.000023311863,0.00010813006,0.0000978729,0.0005521524,0.00000535841],"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":[0.0000014200783,0.0000016780025,0.000007183811,0.0005007562,0.00034177897,8.965637e-7,0.00011644214,0.9809559,0.00014476807,0.01624843,0.0000017718424,0.0016789543],"study_design_scores_gemma":[0.000057637077,0.00000766734,0.000009115298,0.0006750006,0.00031079227,0.0000012806297,0.00000731326,0.9977356,0.00004345956,0.00009516858,0.00075235433,0.00030457275],"about_ca_topic_score_codex":0.000006814235,"about_ca_topic_score_gemma":0.000009954346,"teacher_disagreement_score":0.9637082,"about_ca_system_score_codex":0.00017326139,"about_ca_system_score_gemma":0.000008648179,"threshold_uncertainty_score":0.9998673},"labels":[],"label_agreement":null},{"id":"W4411656313","doi":"10.51847/hgzhiqnrhp","title":"10.51847/hGZHiqnRHP","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Voice over IP; Computer network; Computer science; Network congestion; Telecommunications; World Wide Web; The Internet","score_opus":0.0029524199482351466,"score_gpt":0.15315353674220272,"score_spread":0.15020111679396758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411656313","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034733635,0.00008675495,0.00080519693,0.000024307781,0.0000045084125,0.00011351732,0.0000042388515,0.0006697286,0.9979444],"genre_scores_gemma":[0.0009969367,0.0000027544702,0.0024787292,0.000019746769,0.00012226457,0.000016772154,0.000019598401,0.00004828027,0.9962949],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99949557,0.0000070134824,0.00010944058,0.000109326706,0.00007975824,0.00019892058],"domain_scores_gemma":[0.99970454,0.000016943728,0.000006363201,0.00017771996,0.0000147382525,0.00007968898],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000027220804,0.00010384254,0.00009758951,0.000040241674,0.000029176623,0.000015418593,0.000095669144,0.000044076012,0.97067285],"category_scores_gemma":[0.0000048912398,0.00011824299,0.00002201512,0.00020532604,0.000008323655,0.0001012149,0.000009120015,0.000061126026,0.9454299],"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":[0.0000047603476,0.000002841457,3.283534e-8,0.0000020795521,0.0000037070267,9.822863e-7,0.000003507642,0.52654934,0.000025673233,6.330053e-7,0.008055579,0.46535087],"study_design_scores_gemma":[0.00008244914,0.000015160374,0.0000071112236,0.000009007133,0.0000036371714,0.0000019075026,1.3114004e-7,0.17249817,0.000041278454,0.0000019640868,0.8272167,0.00012252516],"about_ca_topic_score_codex":7.292555e-7,"about_ca_topic_score_gemma":4.0798867e-8,"teacher_disagreement_score":0.81916106,"about_ca_system_score_codex":0.000038558705,"about_ca_system_score_gemma":0.0000032177832,"threshold_uncertainty_score":0.48218092},"labels":[],"label_agreement":null},{"id":"W4412836976","doi":"10.1109/ojcoms.2025.3594950","title":"XR Streaming Performance With Wi-Fi 7 Multi-Link Operation","year":2025,"lang":"en","type":"article","venue":"IEEE Open Journal of the Communications Society","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Canadian Standards Association","funders":"Agencia Estatal de Investigación; HORIZON EUROPE Framework Programme; Ministerio de Ciencia e Innovación","keywords":"Link (geometry); Computer network; Computer science","score_opus":0.025412142412625856,"score_gpt":0.28291147483807333,"score_spread":0.2574993324254475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412836976","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":[0.09317864,0.002447447,0.8938312,0.0048398147,0.0007928851,0.00082671834,0.0000087444505,0.00008618002,0.003988369],"genre_scores_gemma":[0.8028496,0.0031177811,0.19351093,0.000119741315,0.000035430767,0.000013766197,0.0000040334567,0.000018086574,0.0003306543],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993253,0.0000687618,0.00032283372,0.00006068025,0.000108923625,0.000113543],"domain_scores_gemma":[0.99864775,0.00008488375,0.00016529896,0.0008691584,0.0002059174,0.000027006405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030302233,0.0001035852,0.00015338883,0.000024736775,0.00047522568,0.00011786942,0.0018472719,0.0000525312,0.0000046601126],"category_scores_gemma":[0.00001301592,0.00007486734,0.00007725643,0.00037535006,0.000093169154,0.00064844737,0.00023255804,0.0004323844,0.0000017594765],"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":[0.0000060754064,0.000027696806,0.0008552433,0.0000146019365,0.00009607602,6.6644965e-8,0.0005898828,0.9863517,0.00069540046,0.00011376092,0.0014271126,0.009822351],"study_design_scores_gemma":[0.00075391796,0.00002112892,0.0017917941,0.00040816335,0.00005801738,0.000011084873,0.00043159287,0.9893508,0.0023048273,0.000035245826,0.0047181277,0.00011532045],"about_ca_topic_score_codex":0.0000036626739,"about_ca_topic_score_gemma":0.000028063176,"teacher_disagreement_score":0.70967096,"about_ca_system_score_codex":0.0001821049,"about_ca_system_score_gemma":0.00009436868,"threshold_uncertainty_score":0.36551},"labels":[],"label_agreement":null},{"id":"W4413441427","doi":"10.1007/s12597-025-00987-x","title":"Quarantine-aware home healthcare routing and scheduling: a bi-objective approach","year":2025,"lang":"en","type":"article","venue":"OPSEARCH","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Qatar National Library; Hamad Bin Khalifa University","keywords":"Health care; Quarantine; Computer science; Routing (electronic design automation); Scheduling (production processes); Business; Medicine; Operations management; Computer network; Economics; Economic growth","score_opus":0.011596536950820982,"score_gpt":0.2668295413057821,"score_spread":0.25523300435496116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413441427","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":[0.13188535,0.0017013674,0.86025906,0.00027974005,0.00019343564,0.0004515837,0.000008488403,0.0005557538,0.004665253],"genre_scores_gemma":[0.9801967,0.00028134964,0.019155292,0.000030122514,0.00007044405,0.00004240911,0.00002449949,0.000034269564,0.00016491883],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990391,0.00004234224,0.00017165179,0.00025692605,0.00013698034,0.0003529838],"domain_scores_gemma":[0.99956757,0.000081366874,0.000017803402,0.00018060365,0.000087905966,0.00006475468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017757942,0.00013794082,0.00018400536,0.00016341833,0.00014763634,0.00004886524,0.00010126363,0.000097044634,0.0000036738163],"category_scores_gemma":[0.000029218409,0.0001494879,0.000025014755,0.0006602366,0.000041322837,0.00012432161,0.00006738858,0.0003336717,0.000004365736],"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":[0.000030455478,0.000026658454,0.012758864,0.0006113871,0.000060653398,0.0000048790766,0.00093920314,0.93899965,0.00033010365,0.010780568,0.000096031705,0.03536154],"study_design_scores_gemma":[0.00034966832,0.00001573478,0.0035477933,0.00012384409,0.00000561527,0.0000033407175,0.00059167796,0.99442554,0.00026939178,0.0004442595,0.00006702092,0.0001561093],"about_ca_topic_score_codex":0.000026219557,"about_ca_topic_score_gemma":0.00000800519,"teacher_disagreement_score":0.84831136,"about_ca_system_score_codex":0.00008761126,"about_ca_system_score_gemma":0.000042215048,"threshold_uncertainty_score":0.6095939},"labels":[],"label_agreement":null},{"id":"W4414538540","doi":"10.1109/icc52391.2025.11161043","title":"QoS-Aware Energy-Efficient Time-Slotted Channel Hopping Scheduling Algorithm","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Ontario Tech University","funders":"","keywords":"Quality of service; Network topology; Energy consumption; Duty cycle; Network packet; Packet loss; Wireless sensor network; Efficient energy use; Scheduling (production processes)","score_opus":0.00331333983714528,"score_gpt":0.1906463587210047,"score_spread":0.18733301888385942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414538540","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":[0.00082426786,0.00048033212,0.9892065,0.00006741435,0.00068578817,0.000105981,0.0000037392704,0.0012970759,0.007328927],"genre_scores_gemma":[0.74753726,0.00036541387,0.24532929,0.00053388305,0.0006453163,0.00010684751,0.00017836396,0.00016767024,0.0051359795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990508,0.00001468386,0.00024022005,0.0002331368,0.00012404044,0.0003371401],"domain_scores_gemma":[0.9995807,0.0000514037,0.000025030977,0.00022337164,0.00006037943,0.000059119528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006381763,0.00019540443,0.0001874362,0.00018991208,0.00010601268,0.000036563033,0.00013387106,0.000106837586,0.00006907978],"category_scores_gemma":[0.000011917098,0.00021131485,0.000050378734,0.00067585916,0.000018319124,0.00009357458,0.00005771098,0.0001271283,0.000036430807],"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":[0.0000015655206,0.000012426164,0.00000176904,0.000017526647,0.000030658048,0.000002306325,0.000023805436,0.97286636,0.00048279008,0.00045671052,0.0007619718,0.025342142],"study_design_scores_gemma":[0.00024120742,0.000004918518,0.000011326299,0.00010502521,0.000011164363,0.0000011562591,0.000048606347,0.9944318,0.003674144,0.00007358845,0.0011831585,0.0002139404],"about_ca_topic_score_codex":0.0000053458803,"about_ca_topic_score_gemma":0.0000019887739,"teacher_disagreement_score":0.746713,"about_ca_system_score_codex":0.00012735178,"about_ca_system_score_gemma":0.000016962267,"threshold_uncertainty_score":0.861717},"labels":[],"label_agreement":null},{"id":"W50682970","doi":"10.1007/978-1-4757-3569-7_19","title":"A Downlink SS-OFDM-F/TA Packet Data System Employing Multi-User Diversity","year":2002,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Orthogonal frequency-division multiplexing; Computer science; Telecommunications link; Hybrid automatic repeat request; Computer network; Link adaptation; Network packet; Automatic repeat request; Frequency-division multiplexing; Throughput; Time-division multiplexing; Multiplexing; Scheduling (production processes); Electronic engineering; Real-time computing; Telecommunications; Fading; Wireless; Engineering; Channel (broadcasting)","score_opus":0.0648101858910365,"score_gpt":0.22565956240607699,"score_spread":0.1608493765150405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W50682970","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00001591858,0.001453891,0.5021534,0.000015162687,0.0017652133,0.0007537141,0.0006838012,0.0033829762,0.4897759],"genre_scores_gemma":[0.012744133,0.0030142379,0.06005477,0.00006945685,0.0011194461,0.000016090124,0.0026722592,0.0006751673,0.91963446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99792445,0.000016784661,0.00045784644,0.00070626935,0.00046869804,0.00042598],"domain_scores_gemma":[0.99777436,0.00006645583,0.00013805972,0.0017434139,0.00011981987,0.00015790276],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016482874,0.0006099339,0.0005934951,0.0001771751,0.00022956669,0.000060915816,0.00093716313,0.00057854474,0.00059403403],"category_scores_gemma":[0.000012558635,0.0006513096,0.00010432835,0.00006537824,0.00004734969,0.00046834175,0.001433242,0.00058395916,0.0006690627],"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":[0.000011251354,0.000023768056,0.00018174665,0.0008291941,0.0006168987,0.0001328737,0.00018120868,0.9131855,0.0000059085323,0.025262147,0.05182907,0.007740478],"study_design_scores_gemma":[0.00067891314,0.00001014476,0.000016253523,0.0006601787,0.00025753345,0.000018238688,0.000029508941,0.8377556,0.0000054101224,0.00005518577,0.15947221,0.0010408143],"about_ca_topic_score_codex":0.00001473984,"about_ca_topic_score_gemma":0.00006341525,"teacher_disagreement_score":0.44209865,"about_ca_system_score_codex":0.00041769975,"about_ca_system_score_gemma":0.0000122190395,"threshold_uncertainty_score":0.9995938},"labels":[],"label_agreement":null},{"id":"W623403820","doi":"10.4018/978-1-61520-674-2.ch005","title":"Long Term Evolution (LTE)","year":2010,"lang":"en","type":"book-chapter","venue":"Advances in wireless technologies and telecommunication book series","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Blackberry (Canada)","funders":"","keywords":"Computer network; UMTS frequency bands; Next-generation network; Computer science; IPv6; IP Multimedia Subsystem; LTE Advanced; UMTS Terrestrial Radio Access Network; Core network; Provisioning; Scalability; Access network; Quality of service; Radio access network; The Internet; Base station; Telecommunications link","score_opus":0.005203129105336364,"score_gpt":0.2124392483107685,"score_spread":0.20723611920543214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W623403820","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038706325,0.6466132,0.0642281,0.0011385357,0.0013170181,0.0025930244,0.00007427864,0.020914175,0.25925106],"genre_scores_gemma":[0.21057414,0.7690549,0.011933889,0.000016998645,0.00005158004,0.00018814053,0.0001663772,0.0002512778,0.007762735],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99849015,0.000012450863,0.0005780345,0.00040291203,0.0001606991,0.00035572803],"domain_scores_gemma":[0.99831283,0.00011261524,0.00024739222,0.0012117526,0.000081010214,0.000034398116],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009140209,0.00052086427,0.00053882296,0.00037953586,0.0001646003,0.000052288546,0.0006910008,0.0009494303,0.00002101582],"category_scores_gemma":[0.000026750724,0.00057707756,0.000060451766,0.00012543552,0.000743963,0.0016966311,0.00035232608,0.0014369957,0.000007447877],"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":[0.00003260572,0.000021811056,0.0006719948,0.0004019938,0.000049374717,0.0000106059815,0.000073332136,0.010688009,0.0006037553,0.34494707,0.00004843539,0.642451],"study_design_scores_gemma":[0.0010430925,0.00021787726,0.0010524611,0.0024483888,0.00009937274,0.00013118645,0.00036754928,0.0070882537,0.008880505,0.17441852,0.80091757,0.0033352158],"about_ca_topic_score_codex":0.0000020326388,"about_ca_topic_score_gemma":0.00076158345,"teacher_disagreement_score":0.80086917,"about_ca_system_score_codex":0.00022286811,"about_ca_system_score_gemma":0.000021780534,"threshold_uncertainty_score":0.99966806},"labels":[],"label_agreement":null},{"id":"W6902059465","doi":"10.60692/thbg0-m9379","title":"Cross-layer distributed power control: a repeated game formulation to improve the sum energy efficiency","year":2015,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Queue; Nash equilibrium; Efficient energy use; Repeated game; Power (physics); Network packet; Energy (signal processing); Work (physics)","score_opus":0.013593013832236772,"score_gpt":0.2068391224669093,"score_spread":0.19324610863467254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6902059465","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":[0.1818313,0.0000050183535,0.8153204,0.000022040156,0.0006250162,0.0004275073,0.00013996272,0.0006576484,0.00097111496],"genre_scores_gemma":[0.9992967,9.756305e-8,0.00022721078,0.000088765206,0.000078667814,0.000097228425,0.00011781661,0.000026839461,0.00006662212],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985625,0.000036269445,0.0006001282,0.00013749536,0.00032633412,0.0003372786],"domain_scores_gemma":[0.9988227,0.000012387552,0.0001747654,0.00042995726,0.00041009721,0.00015013137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028486116,0.0002213601,0.0002099897,0.00013992598,0.00009913872,0.00024047085,0.00018482543,0.00012596216,0.0000066165453],"category_scores_gemma":[0.00004648493,0.0001634278,0.000055525317,0.00047777005,0.000016239244,0.0009309227,0.000035913876,0.00008784818,0.00017895437],"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":[0.00006300875,0.000001031766,0.0027712048,0.000026916681,0.000021036045,6.4577785e-7,0.008186406,0.98829603,0.0000067658334,0.00024208125,0.0001431474,0.00024173276],"study_design_scores_gemma":[0.0014740633,0.000044661876,0.0052942843,0.000042087126,0.000014816301,0.000010494884,0.0011762944,0.98973477,0.000644086,0.0000018454975,0.0013159073,0.00024668698],"about_ca_topic_score_codex":0.0000057388975,"about_ca_topic_score_gemma":3.0704783e-7,"teacher_disagreement_score":0.8174655,"about_ca_system_score_codex":0.00031831357,"about_ca_system_score_gemma":0.000021435673,"threshold_uncertainty_score":0.6664392},"labels":[],"label_agreement":null},{"id":"W69374","doi":"","title":"Comparison of WiMAX and ADSL Performance when Streaming Audio and Video Content","year":2011,"lang":"en","type":"article","venue":"Acta biologica et medica Germanica","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Simon Fraser University","funders":"","keywords":"Asymmetric digital subscriber line; WiMAX; Computer science; Computer network; Digital subscriber line; The Internet; File Transfer Protocol; File transfer; Last mile (transportation); Network packet; Internet access; Transfer (computing); Telecommunications; Wireless; Mile","score_opus":0.05983190693980697,"score_gpt":0.2596195649090461,"score_spread":0.1997876579692391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W69374","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":[0.99289846,0.0010447444,0.003764465,0.00006294825,0.000090949856,0.00016134726,0.0000062757535,0.00016696898,0.0018038121],"genre_scores_gemma":[0.98806655,0.0031081373,0.008654374,0.00006870189,0.00003097584,0.000015014413,0.000027830736,0.000017183389,0.000011236487],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99911594,0.000044632812,0.00031746077,0.00021091448,0.00009858144,0.00021245096],"domain_scores_gemma":[0.99944323,0.000102402846,0.00010599423,0.00020035048,0.000034824472,0.00011321203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018299054,0.00016020986,0.0003129121,0.00004179015,0.00004936917,0.0000072639027,0.00013923751,0.00013230926,0.00006689687],"category_scores_gemma":[0.000046218607,0.00012735768,0.000017476608,0.000058253674,0.00017195604,0.0002146917,0.0000839587,0.00018309725,0.0000016198456],"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":[0.0005296351,0.0007360673,0.31226283,0.00093323167,0.0006059494,0.00002620422,0.03159769,0.0065783197,0.1999864,0.0026737214,0.004120586,0.43994936],"study_design_scores_gemma":[0.0020893489,0.0019108888,0.5391339,0.00049899105,0.00014600034,0.00006404454,0.0015420043,0.4160195,0.028911736,0.00039292927,0.008111461,0.00117917],"about_ca_topic_score_codex":0.0000075143125,"about_ca_topic_score_gemma":0.000009694838,"teacher_disagreement_score":0.4387702,"about_ca_system_score_codex":0.00001564333,"about_ca_system_score_gemma":0.000008575423,"threshold_uncertainty_score":0.5193496},"labels":[],"label_agreement":null},{"id":"W6968258710","doi":"10.5281/zenodo.13139556","title":"CliMA/EnsembleKalmanProcesses.jl: v1.1.6","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Semtech (Canada)","funders":"","keywords":"Troubleshooting; Definiteness; Key (lock); Object (grammar); Broadcasting (networking); Covariance matrix; Matrix (chemical analysis)","score_opus":0.017867534676789622,"score_gpt":0.22703858956023412,"score_spread":0.2091710548834445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6968258710","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000005876129,0.0028537456,0.040070448,0.0000715395,0.0005193592,0.00043751753,0.0003276667,0.0098095285,0.9459043],"genre_scores_gemma":[0.010425695,0.010770347,0.005192045,0.00017109426,0.0031199125,4.9716016e-7,0.012634854,0.12397856,0.833707],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99829316,0.0000731473,0.00027849176,0.00053108484,0.0003452885,0.00047885286],"domain_scores_gemma":[0.9990236,0.000010310934,0.000081741666,0.00056147337,0.00016163937,0.00016124512],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00017333995,0.00034248456,0.00027415287,0.0005042835,0.00037094057,0.00056530384,0.000806489,0.00025286796,0.025757464],"category_scores_gemma":[0.00009115303,0.00038904825,0.00006904498,0.0007999987,0.00009650387,0.00014152797,0.0005437295,0.0005316652,0.05315273],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000060302996,0.000019561929,5.1157066e-8,0.0006464225,0.000084153144,0.000023993156,0.0001339499,0.008236022,0.00011510305,0.001016342,0.9585979,0.031120459],"study_design_scores_gemma":[0.00018120107,0.000040928466,0.000001056515,0.00031338463,0.000035110963,0.00005497035,0.00004352084,0.0072819246,0.000059012367,0.0001809307,0.9914184,0.00038953786],"about_ca_topic_score_codex":0.0000040240056,"about_ca_topic_score_gemma":7.657119e-7,"teacher_disagreement_score":0.11416904,"about_ca_system_score_codex":0.00019315902,"about_ca_system_score_gemma":0.0000023479083,"threshold_uncertainty_score":0.9998561},"labels":[],"label_agreement":null},{"id":"W7096853484","doi":"","title":"IEEE 802.16 Broadband Wireless Access Working Group","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Notice; Multipath propagation; Wireless broadband; PHY; Channel (broadcasting); Broadband networks; Broadband; Physical layer; License","score_opus":0.015501187714309412,"score_gpt":0.2473345164925205,"score_spread":0.23183332877821108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096853484","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":[0.08208198,0.0002023234,0.86584,0.0000074430977,0.0007979751,0.00013567688,4.9472453e-7,0.0008446169,0.05008947],"genre_scores_gemma":[0.99111325,0.00019780613,0.0075802077,0.0000855399,0.0004307427,0.0000088909055,0.000014082469,0.00007416334,0.0004953398],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892235,0.000008005804,0.00026502597,0.00020180158,0.00016445387,0.00043839132],"domain_scores_gemma":[0.999529,0.00008763337,0.000035111894,0.00022161174,0.000026239672,0.00010038074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015430055,0.00018527587,0.00016671534,0.00011119593,0.00005737052,0.000076976816,0.00023436753,0.00011361557,0.00009285686],"category_scores_gemma":[0.000004336308,0.00019031152,0.000040614137,0.00046362597,0.000025766158,0.00039881578,0.000034037075,0.00017431464,0.000028292214],"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":[0.000016065198,0.000016890945,0.0036717565,0.00002834885,0.00002627421,0.000011372446,0.000056386554,0.8473045,0.0015944291,0.0011336819,0.001937375,0.14420289],"study_design_scores_gemma":[0.0015264415,0.000040042516,0.0060054353,0.00024583453,0.0000366284,0.000025558344,0.00013551243,0.9253988,0.0391471,0.0010482735,0.024924334,0.0014659966],"about_ca_topic_score_codex":0.000008919219,"about_ca_topic_score_gemma":0.00015897218,"teacher_disagreement_score":0.9090313,"about_ca_system_score_codex":0.00014020021,"about_ca_system_score_gemma":0.000003724075,"threshold_uncertainty_score":0.77606785},"labels":[],"label_agreement":null},{"id":"W7097058803","doi":"","title":"Purpose Notice Release","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Notice; License; Discretion; Relevance (law); Subject (documents); Voting","score_opus":0.0022788118990436446,"score_gpt":0.15889728225190466,"score_spread":0.15661847035286103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097058803","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":[0.005431526,0.000035130874,0.93147385,0.00002684718,0.00016961986,0.000046438938,2.2607544e-7,0.0006123201,0.062204022],"genre_scores_gemma":[0.9565931,0.000031198557,0.04249582,0.000099909805,0.000118181924,0.000005683501,0.0000048574116,0.000024834066,0.0006264126],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969774,0.0000067480764,0.000071885304,0.000064372056,0.00004847097,0.00011079941],"domain_scores_gemma":[0.9997759,0.000031384727,0.000006340299,0.00013048564,0.000013723434,0.00004220717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000030792686,0.00005763713,0.00005370675,0.000020683598,0.000017817989,0.0000090063895,0.000047534635,0.000029804798,0.000091900976],"category_scores_gemma":[0.000020750835,0.000057274578,0.000012296568,0.00008968146,0.0000067903384,0.000095866475,0.000007782234,0.000051017378,0.00018121966],"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":[9.3678534e-7,0.0000024904207,0.00003035459,0.0000065088216,0.0000018793975,3.5477163e-7,0.000009574151,0.96854943,0.00020440377,0.0033231222,0.0014326392,0.026438281],"study_design_scores_gemma":[0.000099651596,0.0000056501426,0.00008810292,0.0000041603985,0.0000026551832,8.9750694e-7,0.0000032828602,0.9742917,0.0012847722,0.00025714104,0.02387755,0.00008443718],"about_ca_topic_score_codex":9.2375694e-7,"about_ca_topic_score_gemma":0.0000032337189,"teacher_disagreement_score":0.95116156,"about_ca_system_score_codex":0.000015048116,"about_ca_system_score_gemma":0.0000011925765,"threshold_uncertainty_score":0.23355894},"labels":[],"label_agreement":null},{"id":"W7104264533","doi":"10.23977/acss.2025.090318","title":"Multi-Objective Wireless Resource Management Optimization Framework Based on NSGA-II and Whale Optimization Algorithm","year":2025,"lang":"","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Flexibility (engineering); Resource management (computing); Optimization algorithm; Optimization problem; Wireless; Resource allocation; Resource (disambiguation); Whale; Control (management)","score_opus":0.006490071542611457,"score_gpt":0.23794446524392393,"score_spread":0.23145439370131246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7104264533","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":[0.00015836206,0.02199616,0.9729862,0.00006704564,0.0019047135,0.0022078417,0.000027296755,0.00019213914,0.00046019765],"genre_scores_gemma":[0.14615561,0.01747779,0.8351404,0.0002165578,0.00033971193,0.00035082674,0.000085559455,0.00010955473,0.00012398059],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99634874,0.00039622426,0.0010803706,0.0011694551,0.00038332547,0.0006218971],"domain_scores_gemma":[0.99816155,0.0006773534,0.00033436637,0.0005216361,0.00016013168,0.00014493018],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005242512,0.00070802897,0.00086553,0.0007043097,0.00045672964,0.00034707866,0.00026656035,0.00041007844,0.000009013891],"category_scores_gemma":[0.000018345376,0.00079481996,0.00007043569,0.0012781739,0.00013183213,0.000807739,0.0002460344,0.0004914788,9.939126e-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":[0.00006796986,0.00015270413,0.00015088357,0.00086181494,0.000083409235,0.000019953117,0.0004017011,0.8435719,0.0000013696673,0.00065031584,0.000026420626,0.15401158],"study_design_scores_gemma":[0.0020061985,0.00023422888,0.00005793891,0.006999073,0.0000655345,0.000004166549,0.0003025336,0.98877966,0.00001999174,0.000085145555,0.000764742,0.00068076054],"about_ca_topic_score_codex":0.000009344189,"about_ca_topic_score_gemma":0.0000034762909,"teacher_disagreement_score":0.15333082,"about_ca_system_score_codex":0.00028764768,"about_ca_system_score_gemma":0.000025410916,"threshold_uncertainty_score":0.99945027},"labels":[],"label_agreement":null},{"id":"W7132878068","doi":"","title":"Downlink resource allocation in cellular and multi-hop cellular CDMA systems","year":2004,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Toronto","keywords":"Telecommunications link; Cellular network; Resource allocation; Base station; Throughput; Resource management (computing); Code division multiple access; Cellular radio","score_opus":0.01052593528667396,"score_gpt":0.25396047586576087,"score_spread":0.24343454057908692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132878068","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":[0.2752553,0.07108479,0.64513206,0.00022426755,0.002312754,0.0036153004,0.000018062772,0.00051041035,0.0018470862],"genre_scores_gemma":[0.9730349,0.0041259825,0.01138559,0.000014114741,0.0005035845,0.0002380399,0.0029705286,0.00043458224,0.0072926315],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959863,0.00020796532,0.0012063454,0.0011603519,0.00052763714,0.0009114093],"domain_scores_gemma":[0.9979947,0.00017823107,0.00056166225,0.0007857151,0.0002021594,0.0002775352],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0004113876,0.0010607435,0.0010278255,0.00064615527,0.00022509185,0.00021014463,0.0003503081,0.0013153366,0.000054427437],"category_scores_gemma":[0.00011105443,0.0013739608,0.00012322671,0.0010499487,0.000081092934,0.00036709747,0.00006339013,0.0011839322,0.00008525422],"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":[0.00007832931,0.00009735824,0.00015084916,0.0020758566,0.0000700749,0.000047429447,0.011044549,0.9579609,0.026469367,0.00063109444,0.000028599094,0.0013456133],"study_design_scores_gemma":[0.0023381484,0.00006962603,0.00029233692,0.0031220654,0.00014539348,0.0000067805586,0.0075121084,0.974602,0.009421488,0.00004257338,0.0010519087,0.0013955641],"about_ca_topic_score_codex":0.00071155524,"about_ca_topic_score_gemma":0.00035842042,"teacher_disagreement_score":0.69777966,"about_ca_system_score_codex":0.0009863034,"about_ca_system_score_gemma":0.00013628988,"threshold_uncertainty_score":0.99998116},"labels":[],"label_agreement":null},{"id":"W7148310939","doi":"10.1007/978-3-032-07031-9_2","title":"Signal Quality-Based CSMA Networks","year":2025,"lang":"en","type":"book-chapter","venue":"Static & dynamic game theory: foundations & applications","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 du Québec à Trois-Rivières; Innovation and Economic Development Trois Rivières","funders":"","keywords":"Focus (optics); Doors; Duration (music); Wireless; SIGNAL (programming language); Wireless network","score_opus":0.008407971569849206,"score_gpt":0.26315773235552,"score_spread":0.2547497607856708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7148310939","genre_codex":"methods","genre_gemma":"other","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":[0.0000029538974,0.00049815245,0.8240267,0.0001437009,0.00020864002,0.0017067979,0.00046280478,0.0010647329,0.17188554],"genre_scores_gemma":[0.1360867,0.0027471627,0.18487145,0.0010857725,0.0008291368,0.009247769,0.042552885,0.0014617566,0.62111735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99715847,0.000098621225,0.0011237889,0.00071002485,0.00037284385,0.00053622917],"domain_scores_gemma":[0.996445,0.0013032188,0.0004034113,0.0013577375,0.00032454557,0.00016611358],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00042918106,0.00074966263,0.00071271777,0.0005097776,0.0003669221,0.00014466053,0.0006047315,0.0004586387,0.0009503012],"category_scores_gemma":[0.000032182783,0.00091615424,0.00025485575,0.00042322837,0.0003788552,0.0001732655,0.0000751604,0.0008366651,0.00033249764],"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":[0.000008412867,0.00001872835,5.499656e-7,0.00008437185,0.00014436033,5.0161003e-7,0.000027599861,0.50951934,0.0000053691006,0.45285642,0.00036088182,0.036973484],"study_design_scores_gemma":[0.00030885256,0.000016240789,0.000007642414,0.00016325626,0.0002864079,0.0000014799275,0.000022013679,0.6627002,0.000001793386,0.25883043,0.07702688,0.0006348503],"about_ca_topic_score_codex":0.0000043297514,"about_ca_topic_score_gemma":0.00007968596,"teacher_disagreement_score":0.6391552,"about_ca_system_score_codex":0.0007427602,"about_ca_system_score_gemma":0.0002920142,"threshold_uncertainty_score":0.999963},"labels":[],"label_agreement":null},{"id":"W74481606","doi":"10.1007/1-4020-4437-2_38","title":"Dynamic and Scalable Bandwidth Allocation for Beyond 3G CDMA Systems","year":2006,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","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 Victoria; University of British Columbia; Nortel (Canada)","funders":"","keywords":"Computer science; Scalability; Dynamic bandwidth allocation; Bandwidth (computing); Computer network; Code division multiple access; W-CDMA","score_opus":0.004323643471213483,"score_gpt":0.1823943904343744,"score_spread":0.17807074696316091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W74481606","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011827056,0.0029416617,0.6979601,0.000010833076,0.0004044566,0.00064670003,0.000039289145,0.00035264183,0.29763252],"genre_scores_gemma":[0.020479573,0.0017845134,0.0281917,0.0000240133,0.00030841594,0.00015402997,0.0016424251,0.00036232578,0.947053],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913746,0.0000025315576,0.00029404176,0.0002562286,0.000111608286,0.00019813937],"domain_scores_gemma":[0.9995472,0.000055897173,0.0000703509,0.0002039188,0.00007490257,0.000047748752],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005442931,0.0002881692,0.00030062653,0.00010790768,0.000054941258,0.000051532308,0.000066423905,0.00031560558,0.00002499865],"category_scores_gemma":[0.000002582768,0.00030722245,0.000042462485,0.000024031982,0.00002534817,0.00012951043,0.000015424106,0.00011689612,0.000013271299],"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":[0.0000036964564,0.0000019055561,0.000001562598,0.00030331273,0.000035805722,5.711371e-7,0.0000052040973,0.95944804,0.000032588498,0.030310774,0.0067289504,0.0031275966],"study_design_scores_gemma":[0.00023987597,0.0000185352,0.0000040621494,0.00014647025,0.000044103374,0.0000045686847,0.0000025017596,0.93915254,0.000012168049,0.0026030347,0.057432663,0.0003394854],"about_ca_topic_score_codex":0.000006730787,"about_ca_topic_score_gemma":0.00003404565,"teacher_disagreement_score":0.66976833,"about_ca_system_score_codex":0.00014990837,"about_ca_system_score_gemma":0.000010267331,"threshold_uncertainty_score":0.999938},"labels":[],"label_agreement":null},{"id":"W89354841","doi":"","title":"Dynamic Channel Adaptive MAC with Frame Length Prediction (DCAM/FLP).","year":2003,"lang":"en","type":"article","venue":"International Conference on Wireless Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Computer science; Computer network; Quality of service; Bandwidth (computing); Frame (networking); Wireless network; Wireless; Protocol (science); Channel (broadcasting); Interference (communication); Real-time computing; Telecommunications","score_opus":0.01242081328579036,"score_gpt":0.2211320544923911,"score_spread":0.20871124120660073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W89354841","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":[0.015524505,0.00016274652,0.9576227,0.00009351937,0.0016771053,0.0003540379,0.000056929093,0.0006182078,0.02389022],"genre_scores_gemma":[0.9953012,0.0012350281,0.002442095,0.00010290951,0.00018404404,0.00013440315,0.00019501873,0.00009995194,0.0003053448],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982104,0.0000619071,0.00035016696,0.00044327605,0.00044576536,0.00048849423],"domain_scores_gemma":[0.99907017,0.00008269529,0.00012130246,0.0002889369,0.00027455008,0.00016235227],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012584368,0.00038510995,0.00027241968,0.00016946532,0.0001267956,0.00009661818,0.00031126352,0.00023172986,0.00027979343],"category_scores_gemma":[0.000017802698,0.00037846362,0.000060330593,0.00028252992,0.00009229364,0.00037695165,0.000027790751,0.0005978346,0.000034282843],"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":[0.0000958758,0.000033046897,0.00018557499,0.0000071097115,0.00012305888,0.0000123224245,0.0000785601,0.94934446,0.000047679463,0.04510271,0.00020754916,0.0047620637],"study_design_scores_gemma":[0.0006443456,0.00014494329,0.00027604908,0.00026365338,0.000017552371,0.000020160565,0.00013902034,0.99633926,0.00012803647,0.0010775052,0.0005686381,0.00038083407],"about_ca_topic_score_codex":0.000004844718,"about_ca_topic_score_gemma":0.00006177119,"teacher_disagreement_score":0.9797767,"about_ca_system_score_codex":0.00030111315,"about_ca_system_score_gemma":0.000050393635,"threshold_uncertainty_score":0.9998667},"labels":[],"label_agreement":null}]}