{"meta":{"query_hash":"95fed808b220","filters":{"venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems"},"cohort_total":28,"direct_labels_cover":0,"predictions_cover":28,"exported":28,"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/95fed808b220","api":"https://metacan.xera.ac/api/v1/cohort?venue=IEEE+Journal+on+Emerging+and+Selected+Topics+in+Circuits+and+Systems"},"results":[{"id":"W1978360634","doi":"10.1109/jetcas.2012.2212774","title":"Algorithms to Approximately Solve NP Hard Row-Sparse MMV Recovery Problem: Application to Compressive Color Imaging","year":2012,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Sparse and Compressive Sensing Techniques","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":"","keywords":"Compressed sensing; Algorithm; Nondeterministic algorithm; Sparse approximation; Convex optimization; Mathematical optimization; Regular polygon; Computational complexity theory; Computer science; Optimization problem; Row; Mathematics","score_opus":0.023618238405197375,"score_gpt":0.2552226654830735,"score_spread":0.2316044270778761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978360634","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024157972,0.00014688206,0.99539715,0.00032385765,0.000022083961,0.00004998254,0.000043853994,0.00030973318,0.0012905815],"genre_scores_gemma":[0.13375492,0.0005518895,0.8615996,0.00027284917,0.00012630147,0.00047328425,0.00031033644,0.00022462377,0.0026861867],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922585,0.00027111976,0.000039369574,0.00014757292,0.0002231781,0.000092760456],"domain_scores_gemma":[0.9946556,0.0040819817,0.0003523778,0.00037193848,0.00043723683,0.00010084533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015438367,0.001257271,0.001115664,0.0006784254,0.0006452107,0.0012400771,0.0012655732,0.0016906962,0.0052987775],"category_scores_gemma":[0.008296932,0.000510051,0.000703265,0.001020352,0.000853277,0.0016956168,0.0015446248,0.003013896,0.001075429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014829884,0.00020158215,0.00053279067,0.0002630454,0.000045653363,0.00009760807,0.00011925491,0.7581346,0.003153566,0.04266739,0.007131873,0.18750429],"study_design_scores_gemma":[0.000021988393,0.000022714697,0.00005129113,0.000008998564,0.0000045375486,0.000030287778,0.00002234881,0.9822568,0.0007618582,0.015905647,0.0009064273,0.0000069939138],"about_ca_topic_score_codex":0.0041316603,"about_ca_topic_score_gemma":0.006863986,"teacher_disagreement_score":0.0052987775,"about_ca_system_score_codex":0.0010125615,"about_ca_system_score_gemma":0.0024557412,"threshold_uncertainty_score":0.017726123},"labels":[],"label_agreement":null},{"id":"W2009771843","doi":"10.1109/jetcas.2013.2284612","title":"Linearized Multi-Level $\\Delta\\Sigma$ Modulated Wireless Transmitters for SDR Applications Using Simple DLGA Algorithm","year":2013,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Radio Frequency Integrated Circuit Design","field":"Engineering","cited_by":10,"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":"CMC Microsystems","keywords":"Transmitter; Electronic engineering; Linearization; Linearity; Delta-sigma modulation; Amplifier; Software-defined radio; Control theory (sociology); Bandwidth (computing); Digital signal processing; Algorithm; Computer science; Engineering; Channel (broadcasting); Electrical engineering; Telecommunications; Physics; Nonlinear system; CMOS","score_opus":0.04719456566433031,"score_gpt":0.2669221270137215,"score_spread":0.21972756134939117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009771843","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01846576,0.0002948402,0.977436,0.00008802784,0.000027151265,0.000036422887,0.00001477889,0.00057615584,0.0030608512],"genre_scores_gemma":[0.551166,0.00032256878,0.44247535,0.00014384008,0.000045452132,0.00008619691,0.00007822635,0.0000653134,0.005617055],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999796,0.00003901774,0.000012677588,0.000041032476,0.00009411166,0.00001725634],"domain_scores_gemma":[0.9998617,0.000038915958,0.00003241265,0.000020121633,0.000040635998,0.0000062069635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021755046,0.0004511214,0.00020482403,0.00026850766,0.00022368855,0.00052742613,0.00046365603,0.00030834306,0.001762035],"category_scores_gemma":[0.00040342292,0.00016823484,0.00025138972,0.00023487279,0.00021647305,0.0004814012,0.00034175479,0.00050186337,0.00069531397],"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":[0.00024592064,0.00007334098,0.0019073987,0.00020056094,0.00006297961,0.00014661252,0.00029548415,0.09738034,0.28511646,0.022892278,0.0015714408,0.59010726],"study_design_scores_gemma":[0.00005884094,0.0005107913,0.0009302996,0.000048011203,0.00005338861,0.00049050135,0.000057410612,0.83457124,0.14019859,0.004173984,0.018862823,0.00004397746],"about_ca_topic_score_codex":0.0006270249,"about_ca_topic_score_gemma":0.0011910428,"teacher_disagreement_score":0.001762035,"about_ca_system_score_codex":0.0003445755,"about_ca_system_score_gemma":0.00031437233,"threshold_uncertainty_score":0.0058946013},"labels":[],"label_agreement":null},{"id":"W2016153077","doi":"10.1109/jetcas.2013.2256827","title":"Software Laboratory for Camera Networks Research","year":2013,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Pennsylvania","keywords":"Software; Computer science; Computer graphics (images); Operating system","score_opus":0.05937322974766214,"score_gpt":0.3387975889828744,"score_spread":0.27942435923521225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016153077","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067934613,0.0018204551,0.8033693,0.0016979214,0.0011432589,0.00055312127,0.0064302697,0.0825136,0.09567859],"genre_scores_gemma":[0.12298175,0.00351258,0.7036597,0.0008332915,0.00042800375,0.0019202358,0.027320728,0.012598459,0.12674527],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99757844,0.00047687523,0.00014418049,0.00058317947,0.0010220755,0.00019526717],"domain_scores_gemma":[0.9955623,0.00099362,0.0002068475,0.0013329356,0.0014413144,0.0004629297],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002180297,0.0017535198,0.0012550235,0.0017055252,0.00075964554,0.0023992702,0.0027445296,0.0012760649,0.094314426],"category_scores_gemma":[0.0066548362,0.00076982647,0.0008903001,0.0017561879,0.0007832018,0.003633621,0.002063535,0.0029444387,0.036793444],"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":[0.0006173767,0.00047736664,0.0030057807,0.00061363785,0.00014093716,0.0003535191,0.00035802653,0.030432453,0.02085468,0.1845468,0.29859808,0.4600014],"study_design_scores_gemma":[0.0004090094,0.00032054321,0.0014183822,0.00022118082,0.00007229186,0.0004708648,0.00009724437,0.22050694,0.01792089,0.049662545,0.70878285,0.00011728903],"about_ca_topic_score_codex":0.0044754,"about_ca_topic_score_gemma":0.0036065148,"teacher_disagreement_score":0.094314426,"about_ca_system_score_codex":0.0015818637,"about_ca_system_score_gemma":0.0026640655,"threshold_uncertainty_score":0.3155132},"labels":[],"label_agreement":null},{"id":"W2028847123","doi":"10.1109/jetcas.2013.2284616","title":"A Hybrid Amplitude/Time Encoding Scheme for Enhancing Coding Efficiency and Dynamic Range in Digitally Modulated Power Amplifiers","year":2013,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Advanced Power Amplifier Design","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":"Encoding (memory); Computer science; Dynamic range; Coding (social sciences); Amplifier; Time domain; Electronic engineering; Amplitude; ENCODE; Algorithm; Real-time computing; Telecommunications; Mathematics; Engineering; Bandwidth (computing); Physics; Artificial intelligence; Optics","score_opus":0.011210983056577814,"score_gpt":0.2322751950198326,"score_spread":0.2210642119632548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028847123","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24563622,0.0014581971,0.74619377,0.00025784908,0.00007397726,0.000075514654,0.000041759704,0.00044072876,0.0058221095],"genre_scores_gemma":[0.7888186,0.0004345665,0.20876998,0.00006691206,0.000040846902,0.000033056975,0.000029623914,0.000024278592,0.001782184],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998036,0.00005014265,0.000011057737,0.000024592511,0.00009260781,0.000018049253],"domain_scores_gemma":[0.99957806,0.00018011166,0.00008157359,0.00004285156,0.00009677049,0.000020566718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025400863,0.0002982583,0.00015211177,0.00028313274,0.00014770305,0.0003939119,0.0004194327,0.00032380363,0.00085942174],"category_scores_gemma":[0.00071939896,0.00010142526,0.0001329628,0.0003191479,0.0002588313,0.00082663674,0.00029546683,0.00032177503,0.00020363092],"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":[0.00019281417,0.000050277384,0.0005202191,0.00007986496,0.000017322636,0.00009208668,0.000074272,0.0128675,0.84162825,0.014026633,0.00022966115,0.13022111],"study_design_scores_gemma":[0.00004853771,0.0007644677,0.00067795167,0.000030245837,0.000046059886,0.00059073145,0.000027714908,0.34320897,0.64492905,0.003115223,0.006524484,0.000036540096],"about_ca_topic_score_codex":0.00018871088,"about_ca_topic_score_gemma":0.0003641012,"teacher_disagreement_score":0.00085942174,"about_ca_system_score_codex":0.00023271746,"about_ca_system_score_gemma":0.00013497038,"threshold_uncertainty_score":0.00287503},"labels":[],"label_agreement":null},{"id":"W2039827192","doi":"10.1109/jetcas.2013.2280804","title":"Effort-Reduced Calibration of Six-Port Based Receivers for CR/SDR Applications","year":2013,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Microwave and Dielectric Measurement Techniques","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 Calgary","funders":"","keywords":"Calibration; Electronic engineering; Port (circuit theory); Detector; Computer science; Nonlinear system; Software-defined radio; Radio frequency; Engineering; Telecommunications; Physics","score_opus":0.02488709059521679,"score_gpt":0.2435673474649582,"score_spread":0.2186802568697414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039827192","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03400512,0.00017812286,0.96246374,0.00007899422,0.00004519726,0.000052215673,0.00002714665,0.0010253851,0.0021239787],"genre_scores_gemma":[0.48464262,0.00022909514,0.5112277,0.00015786072,0.00006834056,0.00007455639,0.00012374912,0.00014773603,0.0033283674],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99844044,0.00038653304,0.00006111264,0.00023753366,0.0007989956,0.00007542159],"domain_scores_gemma":[0.99892527,0.00021213821,0.00019887152,0.0003797305,0.00025456244,0.000029346194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008777167,0.0009416537,0.0006055869,0.00066693366,0.00034629568,0.0007970109,0.0015326514,0.0009270453,0.0021314735],"category_scores_gemma":[0.002170626,0.0003681047,0.00057111506,0.000398125,0.00031270643,0.0012301374,0.0009438265,0.001075967,0.0012729876],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000506622,0.000223906,0.0036134736,0.00027199832,0.00014877609,0.00030288156,0.0002756984,0.062445763,0.47205913,0.008915977,0.0014387545,0.449797],"study_design_scores_gemma":[0.000051253646,0.0005459371,0.0032031501,0.000049820403,0.00011094198,0.0014418211,0.00006846916,0.54642135,0.43041393,0.0027720479,0.014835011,0.00008619152],"about_ca_topic_score_codex":0.0004156263,"about_ca_topic_score_gemma":0.0008181324,"teacher_disagreement_score":0.0021314735,"about_ca_system_score_codex":0.00040350598,"about_ca_system_score_gemma":0.00036331895,"threshold_uncertainty_score":0.007130444},"labels":[],"label_agreement":null},{"id":"W2063836047","doi":"10.1109/jetcas.2013.2256819","title":"Geometry-Based Object Association and Consistent Labeling in Multi-Camera Surveillance","year":2013,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer vision; Artificial intelligence; Object (grammar); Homography; Computer science; Camera resectioning; Field of view; Object detection; Ground plane; Camera auto-calibration; Association (psychology); Plane (geometry); Constraint (computer-aided design); Computer graphics (images); Geometry; Mathematics; Pattern recognition (psychology)","score_opus":0.036185649963141706,"score_gpt":0.28587336462916213,"score_spread":0.2496877146660204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063836047","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007990128,0.00013605187,0.99144334,0.000032584074,0.000009300818,0.000013023719,0.000014805568,0.00015857274,0.00020223278],"genre_scores_gemma":[0.33630332,0.00041459806,0.6619446,0.000085930355,0.00007079137,0.00007782923,0.00021147063,0.000111433576,0.0007800353],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99758434,0.00068842765,0.0000842968,0.0007857922,0.0006439122,0.00021313236],"domain_scores_gemma":[0.9981248,0.000526752,0.00039344106,0.00048514453,0.0003636199,0.00010623724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013445773,0.00095795677,0.0016380629,0.0014088496,0.00058257754,0.0012278125,0.0028764354,0.0012158672,0.0004888822],"category_scores_gemma":[0.0035353303,0.0010202393,0.0011472311,0.001549188,0.0011706834,0.0025504902,0.0022115358,0.0010725806,0.0003462125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004655596,0.00014680097,0.0043734387,0.00019258192,0.00019091382,0.00062296237,0.00061010045,0.47645313,0.051697105,0.041967716,0.0016262603,0.42165348],"study_design_scores_gemma":[0.000012337589,0.000081719045,0.0008731208,0.000008731407,0.000027127364,0.00026403822,0.00005326452,0.978204,0.009122407,0.010274097,0.0010511052,0.000027946686],"about_ca_topic_score_codex":0.0030828377,"about_ca_topic_score_gemma":0.002662681,"teacher_disagreement_score":0.0030828377,"about_ca_system_score_codex":0.00081502466,"about_ca_system_score_gemma":0.0007603941,"threshold_uncertainty_score":0.0071108937},"labels":[],"label_agreement":null},{"id":"W2065990337","doi":"10.1109/jetcas.2012.2183471","title":"Guest Editorial Special Issue on Brain–Machine Interface","year":2011,"lang":"en","type":"editorial","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","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":"Polytechnique Montréal","funders":"","keywords":"Biosignal; Brain–computer interface; Interface (matter); Computer science; Spike (software development); Electronics; Brain stimulation; Variety (cybernetics); Cover (algebra); Human–computer interaction; Electrical engineering; Artificial intelligence; Engineering; Telecommunications; Neuroscience; Stimulation; Software engineering; Electroencephalography; Wireless; Operating system; Mechanical engineering","score_opus":0.024667348276626692,"score_gpt":0.28880958603937745,"score_spread":0.26414223776275075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065990337","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000051058585,0.003466984,0.00016499544,0.012478216,0.98070234,0.0000206304,0.00004860883,0.000051976127,0.0030152362],"genre_scores_gemma":[0.0004911413,0.0037354599,0.00013054135,0.006822812,0.9649828,0.000022715836,0.0000554459,0.000047774112,0.023711262],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99778146,0.00023395292,0.0002467456,0.00031272165,0.0012034661,0.00022174693],"domain_scores_gemma":[0.99257225,0.0013867822,0.0004563487,0.00017397106,0.004029457,0.0013813004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031586632,0.0028606073,0.0029657404,0.0027014113,0.0017951934,0.0055049784,0.0018771027,0.0074253427,0.030558188],"category_scores_gemma":[0.007458469,0.00076143467,0.0018129454,0.0009809602,0.0010503558,0.002906369,0.0012240106,0.009805922,0.020921547],"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":[0.000060798644,0.000019071811,0.000028277984,0.0001649232,0.000012021307,0.00014740301,0.00000550753,0.000027795062,0.00014654422,0.00021265849,0.9889832,0.010191747],"study_design_scores_gemma":[0.000051394145,0.000041629697,0.00028644118,0.00018480951,0.00003314422,0.00034584553,0.000021529217,0.00017637355,0.00025159225,0.0005625259,0.99803156,0.000013155325],"about_ca_topic_score_codex":0.00064907374,"about_ca_topic_score_gemma":0.0020673326,"teacher_disagreement_score":0.030558188,"about_ca_system_score_codex":0.0015624968,"about_ca_system_score_gemma":0.001562197,"threshold_uncertainty_score":0.10222733},"labels":[],"label_agreement":null},{"id":"W2077060834","doi":"10.1109/jetcas.2014.2337211","title":"Hybrid Forward and Backward Threshold-Compensated RF-DC Power Converter for RF Energy Harvesting","year":2014,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":82,"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":"Voltage multiplier; Electrical engineering; Voltage; Electronic circuit; Materials science; Radio frequency; CMOS; Threshold voltage; Energy conversion efficiency; Transistor; Biasing; Optoelectronics; Electronic engineering; Voltage divider; Dropout voltage; Engineering","score_opus":0.014572745482966215,"score_gpt":0.21962913459727287,"score_spread":0.20505638911430665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077060834","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3749127,0.0020596534,0.5962711,0.00047055492,0.0003027994,0.00015766275,0.0003156735,0.0021350607,0.023374882],"genre_scores_gemma":[0.89371365,0.0005654784,0.09150347,0.0002467867,0.000050326693,0.000054318967,0.00013685276,0.00007518605,0.013653944],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998858,0.0000062433637,0.00000574235,0.000028805218,0.000059894097,0.000013636824],"domain_scores_gemma":[0.9999399,0.000013389728,0.000008534819,0.0000096034,0.000024104731,0.000004458714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008803144,0.00021635811,0.00021200863,0.00022380013,0.00019116864,0.0003385346,0.0007223977,0.0002962069,0.0017439182],"category_scores_gemma":[0.00012508714,0.00017609364,0.0001784235,0.00024454086,0.00013434724,0.00055020815,0.00022937612,0.000295597,0.00070678134],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054956843,0.00003275663,0.0001961911,0.00008810348,0.000012805265,0.000089202396,0.000028274198,0.00097077433,0.95416075,0.0020895281,0.00059476803,0.041681916],"study_design_scores_gemma":[0.000015936299,0.00018158053,0.0006378007,0.000014227492,0.0000246351,0.00064556726,0.000014415341,0.026081892,0.96176517,0.00065509346,0.009945268,0.000018434197],"about_ca_topic_score_codex":0.00017973591,"about_ca_topic_score_gemma":0.00059950043,"teacher_disagreement_score":0.0017439182,"about_ca_system_score_codex":0.0001730745,"about_ca_system_score_gemma":0.00015392361,"threshold_uncertainty_score":0.0058339834},"labels":[],"label_agreement":null},{"id":"W2552619944","doi":"10.1109/jetcas.2016.2619979","title":"Printed Organic and Inorganic Electronics: Devices To Systems","year":2016,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Organic Electronics and Photovoltaics","field":"Engineering","cited_by":39,"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; King Abdullah University of Science and Technology","keywords":"Electronics; Nanotechnology; Materials science; Printed electronics; Molecular electronics; Graphene; Nanowire; Organic electronics; Transistor; Electrical engineering; Engineering","score_opus":0.010177941950727649,"score_gpt":0.2171548867918125,"score_spread":0.20697694484108484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2552619944","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005785554,0.5417101,0.0621871,0.025303751,0.018705094,0.00021050377,0.0006572565,0.0012568706,0.3441838],"genre_scores_gemma":[0.095283195,0.55161273,0.059144575,0.012751331,0.010397125,0.00037541008,0.0008071615,0.0003549755,0.2692735],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996124,0.000068175825,0.000023943057,0.00009121802,0.00015477365,0.000049498314],"domain_scores_gemma":[0.9997303,0.0000789938,0.000016699885,0.000053843614,0.000086510845,0.000033596098],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041793004,0.00061682693,0.00064144144,0.0007415345,0.000653995,0.0036391874,0.0009092179,0.0014402878,0.02271906],"category_scores_gemma":[0.00073886814,0.00032033186,0.0003021781,0.00074350124,0.0021132315,0.0038649936,0.0018395948,0.0020963177,0.009523786],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029536168,0.00007511072,0.00013613251,0.0019579045,0.000023510498,0.00022182304,0.00037234274,0.0010320571,0.013331624,0.5915017,0.09326183,0.29805645],"study_design_scores_gemma":[0.0000039256483,0.000029582106,0.000062039726,0.00021738786,0.0000048665574,0.00018741578,0.00006426966,0.0005387487,0.0020927659,0.062691934,0.93409765,0.000009407895],"about_ca_topic_score_codex":0.00032837322,"about_ca_topic_score_gemma":0.00041694797,"teacher_disagreement_score":0.02271906,"about_ca_system_score_codex":0.0010880091,"about_ca_system_score_gemma":0.00074979395,"threshold_uncertainty_score":0.076002836},"labels":[],"label_agreement":null},{"id":"W2552869056","doi":"10.1109/jetcas.2016.2621348","title":"Device-Circuit Interactions and Impact on TFT Circuit-System Design","year":2016,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Thin-Film Transistor Technologies","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":"IGNIS Innovation (Canada)","funders":"","keywords":"Thin-film transistor; Compensation (psychology); Transistor; AMOLED; Electronic circuit; Electronic engineering; Circuit design; Computer science; Process (computing); Electrical engineering; Engineering; Materials science; Voltage; Active matrix","score_opus":0.03804462618207656,"score_gpt":0.25660275543447586,"score_spread":0.2185581292523993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2552869056","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.327499,0.072440736,0.50792044,0.001828027,0.00075769494,0.00038482025,0.0005629481,0.0016449346,0.0869615],"genre_scores_gemma":[0.9120317,0.013422205,0.0661625,0.0003041935,0.00026750145,0.0001329444,0.00018681806,0.00034832978,0.007143893],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945146,0.000109767825,0.00002206906,0.000107003994,0.00024377037,0.00006590942],"domain_scores_gemma":[0.9990778,0.00062204106,0.00008702582,0.000043383985,0.0001447482,0.000024982492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005872703,0.000546119,0.00057024613,0.00039787157,0.00049740856,0.0011042625,0.0007508751,0.00087220885,0.0024960795],"category_scores_gemma":[0.001659443,0.00032578353,0.0002948708,0.00035892442,0.0003726807,0.0011361971,0.00042226064,0.00072040403,0.0008873964],"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":[0.00023376424,0.00008487083,0.0036377693,0.0024403832,0.00017158134,0.0009737934,0.00040792287,0.090606675,0.7095134,0.04216815,0.0020477555,0.14771384],"study_design_scores_gemma":[0.000032545315,0.0015215981,0.007120086,0.00034322313,0.00034999524,0.0034739168,0.00019957978,0.20444925,0.6511552,0.013156228,0.1180909,0.00010758013],"about_ca_topic_score_codex":0.00051050994,"about_ca_topic_score_gemma":0.00084658386,"teacher_disagreement_score":0.0024960795,"about_ca_system_score_codex":0.0015674273,"about_ca_system_score_gemma":0.00033963483,"threshold_uncertainty_score":0.011372507},"labels":[],"label_agreement":null},{"id":"W2610709265","doi":"10.1109/jetcas.2017.2664899","title":"An Effective Method for Low-Frequency Oscillations Damping in MultiBus DC Microgrids","year":2017,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Microgrid Control and 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":"Polytechnique Montréal","funders":"","keywords":"Voltage droop; Control theory (sociology); Microgrid; Feed forward; MATLAB; Small-signal model; Low-frequency oscillation; Voltage; Oscillation (cell signaling); Computer science; Engineering; Power (physics); Electric power system; Electronic engineering; Control engineering; Voltage source; Physics; Control (management); Electrical engineering","score_opus":0.013641246396301028,"score_gpt":0.28346115477735273,"score_spread":0.2698199083810517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610709265","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052179457,0.0002884023,0.99145037,0.00003800274,0.00004690833,0.000044019675,0.0000097931415,0.00029037145,0.002614168],"genre_scores_gemma":[0.6452139,0.0008373893,0.34521568,0.00011478192,0.00016691133,0.0003194014,0.000057187965,0.00012141657,0.007953305],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981946,0.00003654298,0.000011168686,0.000036246052,0.000085917345,0.000010618511],"domain_scores_gemma":[0.9998621,0.000039968065,0.000022658845,0.0000216823,0.00004285597,0.0000106830885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021236553,0.00083962677,0.00042984908,0.0006735088,0.00040524895,0.00052219495,0.0007503994,0.0004221158,0.0033635213],"category_scores_gemma":[0.00042295983,0.00018474352,0.00026736068,0.00026783778,0.00037511752,0.00064359815,0.00061222044,0.0005117713,0.0005704372],"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":[0.0002211747,0.00012755593,0.0005323533,0.0009030621,0.000057559086,0.0002700171,0.0003928273,0.07817474,0.16377537,0.037079554,0.0026646291,0.71580124],"study_design_scores_gemma":[0.0001110086,0.00042645194,0.00066280225,0.00011717714,0.00005952775,0.00039314365,0.000115822135,0.9107977,0.045802865,0.008796754,0.03266829,0.00004850393],"about_ca_topic_score_codex":0.0003997855,"about_ca_topic_score_gemma":0.00055034953,"teacher_disagreement_score":0.0033635213,"about_ca_system_score_codex":0.00019341962,"about_ca_system_score_gemma":0.00018396796,"threshold_uncertainty_score":0.011252105},"labels":[],"label_agreement":null},{"id":"W2753878108","doi":"10.1109/jetcas.2017.2745704","title":"PolarBear: A 28-nm FD-SOI ASIC for Decoding of Polar Codes","year":2017,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","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":"McGill University; École de Technologie Supérieure","funders":"","keywords":"Decoding methods; Application-specific integrated circuit; Throughput; CMOS; Clock rate; Polar code; Energy (signal processing); Chip","score_opus":0.04165363227286917,"score_gpt":0.30996181697602526,"score_spread":0.2683081847031561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753878108","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42785853,0.005726288,0.3799646,0.0027396288,0.0013948481,0.0006554493,0.0034476332,0.008777063,0.1694359],"genre_scores_gemma":[0.8455862,0.001429066,0.1272825,0.00076128443,0.000113139824,0.00023107657,0.0011716087,0.00026913165,0.023156038],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996793,0.000043729844,0.000010958023,0.000053440577,0.0001632452,0.000049242662],"domain_scores_gemma":[0.99972874,0.000049479768,0.000055184617,0.000033455366,0.00011154011,0.000021634549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028785953,0.00055626646,0.00032551124,0.0004299968,0.00031055632,0.0007548206,0.0006796272,0.00059700524,0.0034971219],"category_scores_gemma":[0.0005363743,0.00017425747,0.00017316727,0.0003496229,0.0003894117,0.00065356446,0.00028057882,0.00054444,0.0019296086],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010935337,0.00025213283,0.0027810747,0.0010578701,0.000110711895,0.0009671638,0.0005775865,0.018500207,0.7437243,0.04736187,0.039757922,0.14381571],"study_design_scores_gemma":[0.00019674546,0.0013310021,0.00133553,0.00014883938,0.00009410082,0.0012847916,0.00014962525,0.08345667,0.74153006,0.0035594543,0.16682719,0.000085867345],"about_ca_topic_score_codex":0.0012484138,"about_ca_topic_score_gemma":0.0021884805,"teacher_disagreement_score":0.0034971219,"about_ca_system_score_codex":0.0008582502,"about_ca_system_score_gemma":0.0008761249,"threshold_uncertainty_score":0.011699021},"labels":[],"label_agreement":null},{"id":"W2766305411","doi":"10.1109/jetcas.2017.2764421","title":"Memory-Efficient Polar Decoders","year":2017,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","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":"McGill University","funders":"","keywords":"Computer science; Polar; Materials science; Electrical engineering; Electronic engineering; Physics; Engineering","score_opus":0.03062185756447545,"score_gpt":0.28877605967033304,"score_spread":0.2581542021058576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766305411","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05409971,0.0012454608,0.92381746,0.0002036217,0.00016000263,0.00010597285,0.00038357716,0.0028940162,0.017090203],"genre_scores_gemma":[0.49238294,0.0015820573,0.48573768,0.0002890838,0.00007313779,0.000116248244,0.0009510449,0.00023341402,0.018634325],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997869,0.000028740247,0.000018432776,0.000032109678,0.00010402742,0.000029742967],"domain_scores_gemma":[0.99956816,0.0001158036,0.000043950615,0.00006597706,0.00019291097,0.000013125891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020679046,0.000468617,0.00028068078,0.00060299743,0.0003018608,0.0006808891,0.0005511556,0.00038816914,0.00342219],"category_scores_gemma":[0.0009789291,0.00015176115,0.00021556267,0.00054562965,0.0002640268,0.0006549965,0.00040920006,0.0004368686,0.0016705943],"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":[0.0008413853,0.00009801006,0.0014263216,0.0006552059,0.0000619101,0.0005800707,0.00020478993,0.12892738,0.3000576,0.077092275,0.008589131,0.48146582],"study_design_scores_gemma":[0.00008508188,0.0003035576,0.00047354135,0.000060200182,0.000053879477,0.00086712115,0.00008646105,0.5037932,0.45123112,0.010253799,0.03275116,0.000040808914],"about_ca_topic_score_codex":0.0012818328,"about_ca_topic_score_gemma":0.0024349738,"teacher_disagreement_score":0.00342219,"about_ca_system_score_codex":0.00037971837,"about_ca_system_score_gemma":0.0008646144,"threshold_uncertainty_score":0.011448383},"labels":[],"label_agreement":null},{"id":"W2799283557","doi":"10.1109/jetcas.2018.2832204","title":"Low-Power Approximate Multipliers Using Encoded Partial Products and Approximate Compressors","year":2018,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":228,"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":"Gas compressor; Multiplier (economics); Computer science; Algorithm; Error detection and correction; Lookup table; Mathematics; Arithmetic","score_opus":0.022469510249336067,"score_gpt":0.24041299305975247,"score_spread":0.2179434828104164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799283557","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24266362,0.0015393976,0.7440008,0.00032075588,0.00015831558,0.00013454072,0.00020213911,0.0014246827,0.0095558],"genre_scores_gemma":[0.68267375,0.0005751299,0.31021988,0.00013579486,0.00007315837,0.0000887117,0.00022833786,0.000066952955,0.005938218],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996971,0.0000542666,0.000026328018,0.0000395483,0.00015581789,0.000027080396],"domain_scores_gemma":[0.9994168,0.00014565603,0.00016150632,0.00012977878,0.00013218808,0.000013989388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029109683,0.00057352067,0.00028962467,0.00043521423,0.00028192412,0.00071646896,0.0006704214,0.00037190554,0.0024498585],"category_scores_gemma":[0.0013289491,0.00021133978,0.00020686835,0.0007394426,0.00039258163,0.0013498128,0.00041427425,0.000454004,0.00044172088],"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":[0.0008927007,0.00011849891,0.0024841768,0.00053573586,0.00011844174,0.0005724353,0.00031696563,0.103078865,0.2966509,0.09374836,0.0036742804,0.49780864],"study_design_scores_gemma":[0.0001237748,0.0015596967,0.0013497123,0.00011555821,0.00010662587,0.0011353996,0.00009729956,0.52131945,0.41443425,0.020053573,0.039624035,0.000080720805],"about_ca_topic_score_codex":0.0004915384,"about_ca_topic_score_gemma":0.0011997627,"teacher_disagreement_score":0.0024498585,"about_ca_system_score_codex":0.00043198242,"about_ca_system_score_gemma":0.0005665079,"threshold_uncertainty_score":0.008195639},"labels":[],"label_agreement":null},{"id":"W2870050732","doi":"10.1109/jetcas.2018.2852705","title":"An Energy-Efficient Online-Learning Stochastic Computational Deep Belief Network","year":2018,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","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":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Deep belief network; Deep learning; Artificial intelligence; Computation; Artificial neural network; Floating point; Stochastic gradient descent; Computer engineering; Machine learning; Algorithm","score_opus":0.01826749025007503,"score_gpt":0.2743906919465532,"score_spread":0.2561232016964782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2870050732","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022356687,0.00038689925,0.97137445,0.00025963684,0.000080996964,0.000037713926,0.00009836609,0.0008827362,0.0045225928],"genre_scores_gemma":[0.7140237,0.0004502476,0.28018898,0.00029490926,0.00004525807,0.00010771352,0.00025716703,0.000059004127,0.004572977],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998324,0.00002410092,0.000008825974,0.00003704357,0.000074871976,0.000022754512],"domain_scores_gemma":[0.99986756,0.0000356129,0.000016507403,0.000016021464,0.00005246863,0.000011940642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023472524,0.0003453643,0.00033603839,0.00020572789,0.0001939132,0.00038215963,0.0010213028,0.00039087003,0.0013718806],"category_scores_gemma":[0.00052567956,0.00023313852,0.000271189,0.00027513926,0.00029244542,0.0006188541,0.00041635436,0.00066026277,0.0002902217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022567002,0.00014631779,0.0014873022,0.00023602821,0.00007833456,0.00019299754,0.00006396859,0.5907041,0.059673015,0.036251687,0.006936968,0.30400363],"study_design_scores_gemma":[0.0000079809815,0.000033241093,0.00009656634,0.0000052291057,0.000006583277,0.000026490812,0.0000023121117,0.99259746,0.004435484,0.0011801743,0.0016032899,0.000005241843],"about_ca_topic_score_codex":0.002306302,"about_ca_topic_score_gemma":0.004817007,"teacher_disagreement_score":0.002306302,"about_ca_system_score_codex":0.00048095692,"about_ca_system_score_gemma":0.0008391984,"threshold_uncertainty_score":0.0045894384},"labels":[],"label_agreement":null},{"id":"W2905544027","doi":"10.1109/jetcas.2018.2885981","title":"Emerging MPEG Standards for Point Cloud Compression","year":2018,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":756,"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); Simon Fraser University","funders":"","keywords":"Standardization; Computer science; Augmented reality; Popularity; Point cloud; Key (lock); Multimedia; Process (computing); Virtual reality; Point (geometry); Cloud computing; Human–computer interaction; Artificial intelligence; Computer security","score_opus":0.026958612565582945,"score_gpt":0.321774817776022,"score_spread":0.29481620521043905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905544027","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012674309,0.017452799,0.74964446,0.0038881912,0.0057071582,0.002198811,0.005157628,0.00802312,0.19525346],"genre_scores_gemma":[0.12847514,0.042733703,0.5846365,0.0046258476,0.003969021,0.0039686426,0.033448882,0.0028047403,0.19533761],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976035,0.00020128285,0.00018692114,0.0001348041,0.0016374568,0.00023600357],"domain_scores_gemma":[0.9976204,0.00024176844,0.00009439785,0.00035862628,0.0016001215,0.00008463997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017564554,0.0009988634,0.0005339704,0.0029729626,0.0009812625,0.002611562,0.0015200792,0.0017073879,0.015399242],"category_scores_gemma":[0.0043378985,0.00030960175,0.0004941419,0.0031551968,0.00072895427,0.002224989,0.001640041,0.0021619268,0.011428366],"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":[0.00041331165,0.00013266131,0.00076291605,0.000697685,0.000034190187,0.00059428543,0.0004658327,0.0040743877,0.04875977,0.1266837,0.10978672,0.7075946],"study_design_scores_gemma":[0.00006665783,0.0001340075,0.0013413542,0.00047126124,0.000037282905,0.00096331025,0.00023084019,0.016946593,0.03405135,0.030437173,0.9152221,0.00009801253],"about_ca_topic_score_codex":0.006022745,"about_ca_topic_score_gemma":0.003733144,"teacher_disagreement_score":0.015399242,"about_ca_system_score_codex":0.0013583855,"about_ca_system_score_gemma":0.0022129347,"threshold_uncertainty_score":0.05151564},"labels":[],"label_agreement":null},{"id":"W2937108468","doi":"10.1109/jetcas.2019.2911899","title":"Low-Power Computer Vision: Status, Challenges, and Opportunities","year":2019,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Qualcomm (Canada)","funders":"Xilinx; Electronics and Telecommunications Research Institute; Nvidia; MediaTek; Google; Facebook","keywords":"Power (physics); Computer science; Electrical engineering; Engineering physics; Engineering; Physics","score_opus":0.025434432783634955,"score_gpt":0.23361275169975754,"score_spread":0.2081783189161226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2937108468","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009387197,0.84677815,0.068853386,0.03223511,0.0019636012,0.000054345845,0.00013576262,0.0007689474,0.039823495],"genre_scores_gemma":[0.14229324,0.76011187,0.05847407,0.0060609477,0.005907248,0.00011687642,0.00054412975,0.00040944287,0.026082244],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99918336,0.00012837243,0.000044748667,0.00014180441,0.00039701024,0.000104651794],"domain_scores_gemma":[0.9972218,0.0012611535,0.0001276079,0.00014529623,0.0010311982,0.00021298605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002081336,0.0008084852,0.00082184974,0.0016330386,0.00078061066,0.004241051,0.0017942582,0.0024847407,0.007308055],"category_scores_gemma":[0.002916015,0.00060981215,0.00036330355,0.0023540882,0.0021577494,0.008815499,0.0016226092,0.0027540866,0.0035859463],"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":[0.00020559476,0.00019156339,0.00096903066,0.002428465,0.00004195943,0.00011356371,0.00019819675,0.002796611,0.006187264,0.07768406,0.05099773,0.85818595],"study_design_scores_gemma":[0.000045818655,0.00051929813,0.001778737,0.0018450705,0.00009358655,0.0009908999,0.0010995828,0.036485933,0.013659044,0.1478645,0.79547095,0.0001464714],"about_ca_topic_score_codex":0.0012211616,"about_ca_topic_score_gemma":0.0018231354,"teacher_disagreement_score":0.007308055,"about_ca_system_score_codex":0.0011134658,"about_ca_system_score_gemma":0.0012428038,"threshold_uncertainty_score":0.024447918},"labels":[],"label_agreement":null},{"id":"W2968287765","doi":"10.1109/jetcas.2019.2933774","title":"Input-Aware Flow-Based Computing on Memristor Crossbars With Applications to Edge Detection","year":2019,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Royal Bank of Canada; University of Central Florida; National Science Foundation","keywords":"Crossbar switch; Memristor; Computer science; Von Neumann architecture; Bottleneck; Computation; Parallel computing; Enhanced Data Rates for GSM Evolution; Edge computing; Neuromorphic engineering; In-Memory Processing; Computer engineering; Computer hardware; Algorithm; Artificial intelligence; Electronic engineering; Artificial neural network; Embedded system; Engineering; Telecommunications","score_opus":0.015932090203200588,"score_gpt":0.24768696130105652,"score_spread":0.23175487109785595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968287765","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43432567,0.0006164672,0.5516297,0.00039148435,0.00014564682,0.000064438296,0.00012199238,0.0015947904,0.011109774],"genre_scores_gemma":[0.8893808,0.00014326024,0.108439796,0.00007623762,0.00001606655,0.00003521514,0.000046726393,0.000045927798,0.0018158191],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999511,0.0000071835084,0.0000024896667,0.000012531882,0.000017683677,0.000008967832],"domain_scores_gemma":[0.9998572,0.00005331309,0.000025101917,0.000018177414,0.00003830152,0.000007873256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000117066156,0.00022386585,0.00014536828,0.00026106884,0.00017424402,0.0002975094,0.00062171154,0.00024167755,0.0015747022],"category_scores_gemma":[0.000387669,0.00012754263,0.00014380198,0.00020061375,0.00024710043,0.0004691585,0.00017664186,0.0002560743,0.000112851056],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017616147,0.00021802238,0.0014315539,0.00026956442,0.00003502896,0.00025012865,0.0001333793,0.47927532,0.35386994,0.037176628,0.0016006166,0.12556371],"study_design_scores_gemma":[0.000009785958,0.00008723635,0.00036531573,0.000012925759,0.000008963492,0.000041335217,0.000010001616,0.9174767,0.076165065,0.0041425014,0.0016709621,0.000009198082],"about_ca_topic_score_codex":0.0012056436,"about_ca_topic_score_gemma":0.0016193034,"teacher_disagreement_score":0.0015747022,"about_ca_system_score_codex":0.0005577838,"about_ca_system_score_gemma":0.00032348614,"threshold_uncertainty_score":0.0052678585},"labels":[],"label_agreement":null},{"id":"W4212926081","doi":"10.1109/jetcas.2022.3151645","title":"Incomplete Information Stochastic Game Theoretic Vulnerability Management for Wide-Area Damping Control Against Cyber Attacks","year":2022,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Smart Grid Security and Resilience","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":"McGill University; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vulnerability (computing); Game theory; Complete information; Control (management); Computer security; Computer science; Stochastic process; Mathematical economics; Economics; Mathematics; Statistics; Artificial intelligence","score_opus":0.013095371016429162,"score_gpt":0.2291144728826122,"score_spread":0.21601910186618303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212926081","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019562915,0.00027777167,0.97480917,0.0003293768,0.00006281128,0.000078661215,0.00008744358,0.00012763921,0.0046643387],"genre_scores_gemma":[0.9692012,0.00037281401,0.02645734,0.00013853193,0.000050480397,0.00019901076,0.00009318973,0.000033449876,0.0034539213],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984118,0.0005042653,0.00007001228,0.0003541437,0.00039706758,0.00026270293],"domain_scores_gemma":[0.99755317,0.0013451756,0.0004436692,0.00008890299,0.0003693635,0.00019967934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021694738,0.0017849598,0.0015952642,0.0007642381,0.0006165662,0.0019324991,0.0019683638,0.0012996248,0.0022235636],"category_scores_gemma":[0.004227603,0.0006609717,0.0010398795,0.0005504114,0.0016933767,0.0018144792,0.0019423558,0.0021780417,0.00023047288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004953517,0.000023293756,0.00032424286,0.000059721657,0.000043101187,0.00009747605,0.000063604726,0.96435857,0.0007790469,0.028531266,0.00040449368,0.0052655847],"study_design_scores_gemma":[0.000005812808,0.000017028331,0.00006964969,0.0000051433835,0.000008237725,0.0000075879348,0.000009001842,0.9920106,0.00007779728,0.0076092584,0.00017436229,0.000005600181],"about_ca_topic_score_codex":0.008374032,"about_ca_topic_score_gemma":0.0058721877,"teacher_disagreement_score":0.008374032,"about_ca_system_score_codex":0.0020901472,"about_ca_system_score_gemma":0.0024506534,"threshold_uncertainty_score":0.016650558},"labels":[],"label_agreement":null},{"id":"W4240819671","doi":"10.1109/jetcas.2019.2958462","title":"2019 Index IEEE Journal on Emerging and Selected Topics in Circuits and Systems Vol. 9","year":2019,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Analog and Mixed-Signal Circuit Design","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":"Ontario Ministry of Food and Agriculture","keywords":"Index (typography); Electronic circuit; Computer science; Engineering physics; Electrical engineering; Engineering; World Wide Web","score_opus":0.01578649579220067,"score_gpt":0.23012105500852884,"score_spread":0.21433455921632816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240819671","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003396223,0.027358625,0.025635164,0.0061617387,0.06412351,0.00052788324,0.006377074,0.0045052865,0.8619144],"genre_scores_gemma":[0.0052807247,0.015160793,0.006578794,0.0015826711,0.0068591773,0.00014085631,0.004630259,0.0006973312,0.95906943],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993394,0.00004760563,0.00007004832,0.0001154284,0.00038024498,0.000047267786],"domain_scores_gemma":[0.997846,0.00021179748,0.00010095522,0.00016236382,0.0012324731,0.00044632703],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007092526,0.0011029667,0.0015178366,0.0038711263,0.00090573693,0.005850601,0.0009512496,0.0012416868,0.45604423],"category_scores_gemma":[0.002235581,0.0003989445,0.0005645986,0.0038787962,0.00048955483,0.0021518695,0.0010321165,0.0015441241,0.47519296],"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":[0.00005679345,0.000055511224,0.00042520615,0.0005098329,0.000020103587,0.000093100534,0.00002860066,0.00025174857,0.003583085,0.003362673,0.79024565,0.20136768],"study_design_scores_gemma":[0.0000058529154,0.00003394009,0.00048050945,0.0001814465,0.0000150447895,0.00023073098,0.00003235301,0.00064367097,0.000500895,0.0013513813,0.9965138,0.000010436219],"about_ca_topic_score_codex":0.00091912487,"about_ca_topic_score_gemma":0.0017498336,"teacher_disagreement_score":0.5439558,"about_ca_system_score_codex":0.0010014394,"about_ca_system_score_gemma":0.001536215,"threshold_uncertainty_score":0.7758869},"labels":[],"label_agreement":null},{"id":"W4312744061","doi":"10.1109/jetcas.2022.3231642","title":"Efficient Approximate Posit Multipliers for Deep Learning Computation","year":2022,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Low-power high-performance VLSI design","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":"University of Saskatchewan","funders":"Ocean University of China; University of Saskatchewan","keywords":"Multiplier (economics); Adder; Computation; Logarithm; Fraction (chemistry); Computer science; Arithmetic; Artificial neural network; Deep learning; Mathematics; Algorithm; Mathematical optimization; Artificial intelligence","score_opus":0.013013070026984038,"score_gpt":0.22667485955304217,"score_spread":0.21366178952605813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312744061","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046993867,0.0012863899,0.9387152,0.00032108626,0.00020716817,0.00011316706,0.0002202095,0.00166776,0.010475106],"genre_scores_gemma":[0.54856795,0.00086581754,0.43929985,0.00031242432,0.000086329244,0.00015287426,0.00046715012,0.00011878289,0.010128781],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975866,0.00003923528,0.00002634529,0.000040871913,0.000108365144,0.000026525218],"domain_scores_gemma":[0.99969673,0.000079171245,0.000043226813,0.000059162543,0.000109457804,0.000012323214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037196954,0.00072753994,0.00028311656,0.0005596392,0.00033377417,0.00097648846,0.0009350146,0.00041978856,0.008688914],"category_scores_gemma":[0.0014200236,0.000249823,0.00029043926,0.00061799324,0.00040053774,0.0017153609,0.0005942995,0.0007073602,0.0016496675],"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":[0.00087355694,0.00014424024,0.0020287752,0.00056676473,0.00008417921,0.00037741082,0.0001659649,0.08914545,0.08976666,0.11655125,0.012166837,0.6881289],"study_design_scores_gemma":[0.000099472076,0.000691794,0.0006986241,0.00012964662,0.00007870225,0.0006015067,0.000117783144,0.7949447,0.11406513,0.04404382,0.044480473,0.000048331836],"about_ca_topic_score_codex":0.00074967754,"about_ca_topic_score_gemma":0.002369353,"teacher_disagreement_score":0.008688914,"about_ca_system_score_codex":0.00055663084,"about_ca_system_score_gemma":0.00091453566,"threshold_uncertainty_score":0.029067338},"labels":[],"label_agreement":null},{"id":"W4319303060","doi":"10.1109/jetcas.2023.3243135","title":"A Timing-Aware Configurable Adder Based on Timing Detection for Low-Voltage Computing","year":2023,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Low-power high-performance VLSI design","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 Alberta","funders":"Fundamental Research Funds for the Central Universities; Natural Sciences and Engineering Research Council of Canada","keywords":"Adder; Computer science; Propagation delay; Voltage; Propagation of uncertainty; Electronic engineering; Static timing analysis; Energy (signal processing); Transistor; Power (physics); Algorithm; Electrical engineering; Embedded system; Engineering; Telecommunications","score_opus":0.027429820220329373,"score_gpt":0.2506393047376006,"score_spread":0.22320948451727124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319303060","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22110552,0.002407218,0.75674146,0.0004068529,0.0005386074,0.00020880393,0.00060384744,0.00601509,0.011972582],"genre_scores_gemma":[0.7833812,0.00041419873,0.21255377,0.00019069621,0.00006960336,0.00007541055,0.0002995017,0.000090473426,0.0029251005],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99985135,0.000014320888,0.0000176049,0.000041093335,0.000052502663,0.000023097216],"domain_scores_gemma":[0.99969065,0.00004812604,0.000066124994,0.00009518739,0.00008082055,0.000019177094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013045421,0.0005651144,0.0002483063,0.0006177718,0.00039310555,0.0006440719,0.0013495081,0.00028652418,0.002239392],"category_scores_gemma":[0.00048631473,0.00021155026,0.00021948412,0.0006651756,0.00018941358,0.0010072495,0.00034049118,0.0003757014,0.00044839593],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005938037,0.000120914854,0.002179443,0.0003647091,0.00008054059,0.0005847378,0.00009840439,0.065617785,0.44396213,0.02888409,0.007533063,0.4499803],"study_design_scores_gemma":[0.00007100314,0.00085235346,0.002268501,0.00006651142,0.00017642428,0.0021689956,0.000053726737,0.57118785,0.37651038,0.010337362,0.036169466,0.00013742218],"about_ca_topic_score_codex":0.00079458347,"about_ca_topic_score_gemma":0.002630026,"teacher_disagreement_score":0.002239392,"about_ca_system_score_codex":0.00043009722,"about_ca_system_score_gemma":0.000705294,"threshold_uncertainty_score":0.0074915886},"labels":[],"label_agreement":null},{"id":"W4320713208","doi":"10.1109/jetcas.2023.3244775","title":"CTT-Based Scalable Neuromorphic Architecture","year":2023,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Neuromorphic engineering; MNIST database; Scalability; Computer science; Binary number; Emulation; Artificial neural network; Computer architecture; Artificial intelligence; Mathematics; Arithmetic","score_opus":0.03205538313289517,"score_gpt":0.2446920245691291,"score_spread":0.21263664143623395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320713208","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1636185,0.002316292,0.78305113,0.0009641658,0.000750211,0.00032379874,0.00093537447,0.0074253604,0.040615253],"genre_scores_gemma":[0.84683555,0.0005882711,0.1399851,0.00046419594,0.00006984237,0.00017652022,0.00047907908,0.000102555954,0.011298948],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987376,0.000009003376,0.000008634977,0.000034214823,0.000059393285,0.000015053078],"domain_scores_gemma":[0.9998603,0.000016723336,0.00001576042,0.00002420843,0.000063328574,0.00001969213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008894809,0.0002972772,0.00026780766,0.00030452677,0.00025532537,0.00054811285,0.001436902,0.00047983846,0.0039508073],"category_scores_gemma":[0.00037031423,0.00013276642,0.00026818633,0.00051984546,0.00020900083,0.0007475003,0.00048677548,0.00038835997,0.0009808214],"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":[0.00033144344,0.00017448796,0.0014889942,0.0005443856,0.00012537926,0.0009868493,0.00013016732,0.10883705,0.5137832,0.02881286,0.018452236,0.32633293],"study_design_scores_gemma":[0.00006959215,0.0006256077,0.0019663675,0.000071544375,0.000099812496,0.0019616045,0.000046872003,0.7918895,0.15047002,0.011963708,0.040762205,0.000073205956],"about_ca_topic_score_codex":0.0012302481,"about_ca_topic_score_gemma":0.0015234133,"teacher_disagreement_score":0.0039508073,"about_ca_system_score_codex":0.0005171401,"about_ca_system_score_gemma":0.000628796,"threshold_uncertainty_score":0.013216734},"labels":[],"label_agreement":null},{"id":"W4353048074","doi":"10.1109/jetcas.2023.3251059","title":"Guest Editorial Unconventional Computing Techniques for Emerging Technology Applications","year":2023,"lang":"en","type":"editorial","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Technical University of Athens; Chengdu University of Information Technology","keywords":"Computer science; Emerging technologies; Data science; Nanotechnology; Materials science; Artificial intelligence","score_opus":0.017035838363231734,"score_gpt":0.29321883935889,"score_spread":0.27618300099565823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4353048074","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000059620157,0.003499808,0.00020067744,0.00998507,0.9839909,0.00001609811,0.000035540135,0.00006108822,0.0021511721],"genre_scores_gemma":[0.0005521993,0.0038789038,0.00011303918,0.005469592,0.97738874,0.000016456603,0.000025008727,0.000041709107,0.012514327],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979684,0.00018415548,0.00018575814,0.00023996334,0.0012623847,0.0001594309],"domain_scores_gemma":[0.99122846,0.002182838,0.0005117852,0.00022233873,0.004154549,0.0017000812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002774172,0.0023349503,0.00206548,0.0023928997,0.0016357406,0.004522091,0.0017084269,0.0055318456,0.018671975],"category_scores_gemma":[0.008250857,0.0006559679,0.0013836847,0.0007949235,0.0011518515,0.0027000217,0.0010616032,0.010392599,0.013697303],"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":[0.000045317884,0.0000120430805,0.000018516694,0.00020246173,0.000009441316,0.000106037194,0.0000072444404,0.00003847297,0.00021967394,0.00048950367,0.989696,0.009155346],"study_design_scores_gemma":[0.000035952078,0.000038671682,0.00015090324,0.00018364126,0.000021522841,0.00029486057,0.000020991327,0.00020866454,0.0003218643,0.0011617575,0.9975477,0.000013440114],"about_ca_topic_score_codex":0.00035009466,"about_ca_topic_score_gemma":0.0011191395,"teacher_disagreement_score":0.018671975,"about_ca_system_score_codex":0.0011673889,"about_ca_system_score_gemma":0.0014104036,"threshold_uncertainty_score":0.06246394},"labels":[],"label_agreement":null},{"id":"W4380489767","doi":"10.1109/jetcas.2023.3278843","title":"Guest Editorial Circuits and Systems for Industry X.0 Applications","year":2023,"lang":"en","type":"editorial","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Digital Transformation in Industry","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":"Electronic circuit; Computer science; Engineering; Electrical engineering","score_opus":0.024220200479520507,"score_gpt":0.26839585917388986,"score_spread":0.24417565869436936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380489767","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000053186453,0.0020399198,0.00020917362,0.010843261,0.98297805,0.00001933279,0.000042429947,0.000084305124,0.0037303441],"genre_scores_gemma":[0.000525451,0.002596919,0.00012114924,0.0068074516,0.96153903,0.00001770563,0.000035874273,0.00005313972,0.028303305],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980781,0.00020162652,0.00017573636,0.00023636277,0.0011476238,0.00016051903],"domain_scores_gemma":[0.9922821,0.0017029914,0.00044170045,0.000202177,0.0037837126,0.0015872831],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025646177,0.002549657,0.002062391,0.0020819919,0.0015817079,0.0046086754,0.0014663676,0.0054876716,0.0319927],"category_scores_gemma":[0.007080799,0.00065407576,0.0013498449,0.00072092324,0.0010194766,0.0022143535,0.00097017747,0.009460705,0.026602844],"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":[0.00003962042,0.000010449751,0.000016954391,0.00013691961,0.000006512501,0.000102096936,0.0000049714126,0.00003138208,0.0001702548,0.00040907183,0.9903998,0.008671915],"study_design_scores_gemma":[0.00003656966,0.00004111571,0.00015810975,0.00012750768,0.000015195559,0.00023370225,0.000015605228,0.00015959285,0.00020795662,0.0008454808,0.9981487,0.000010511081],"about_ca_topic_score_codex":0.00041232698,"about_ca_topic_score_gemma":0.0012587976,"teacher_disagreement_score":0.0319927,"about_ca_system_score_codex":0.0011434021,"about_ca_system_score_gemma":0.001436843,"threshold_uncertainty_score":0.10702628},"labels":[],"label_agreement":null},{"id":"W4388052734","doi":"10.1109/jetcas.2023.3328926","title":"Spike Timing Dependent Gradient for Direct Training of Fast and Efficient Binarized Spiking Neural Networks","year":2023,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Advanced Memory and Neural Computing","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":"York University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"MNIST database; Computer science; Spiking neural network; Neuromorphic engineering; Speedup; Backpropagation; Spike (software development); Artificial neural network; Artificial intelligence; Efficient energy use; Pattern recognition (psychology); Parallel computing","score_opus":0.04430999213860597,"score_gpt":0.26743055858459547,"score_spread":0.2231205664459895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388052734","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.044112116,0.00026524795,0.95166355,0.00012076338,0.00004498178,0.000050883034,0.00009224699,0.0025586074,0.0010916078],"genre_scores_gemma":[0.60627675,0.00019752469,0.38984966,0.00016951184,0.000020861917,0.00015567511,0.000390575,0.0002910379,0.0026484055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984574,0.00002477247,0.000011427761,0.000039477833,0.000052248277,0.00002628063],"domain_scores_gemma":[0.99960417,0.00017339489,0.000040310613,0.000048342066,0.00010811822,0.000025762232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045291858,0.0006709795,0.0004988256,0.00045747464,0.00021321724,0.00039091453,0.0013105908,0.00067468575,0.0018721225],"category_scores_gemma":[0.00169405,0.0004054495,0.00035937602,0.0005301188,0.00033519414,0.0007573272,0.0006414876,0.0011777877,0.0005065263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016432694,0.000087665845,0.0010954445,0.000080731996,0.00003848143,0.00005490187,0.00007181932,0.73074543,0.019653162,0.0043094656,0.0017360464,0.24196257],"study_design_scores_gemma":[0.0000028813986,0.000007554705,0.00005695376,0.0000014649977,0.0000015046729,0.000005990678,0.0000018575519,0.99777263,0.0015282683,0.00047704767,0.00014218745,0.0000016383193],"about_ca_topic_score_codex":0.005198815,"about_ca_topic_score_gemma":0.008470364,"teacher_disagreement_score":0.005198815,"about_ca_system_score_codex":0.00061270176,"about_ca_system_score_gemma":0.0010500932,"threshold_uncertainty_score":0.010337114},"labels":[],"label_agreement":null},{"id":"W4395097710","doi":"10.1109/jetcas.2024.3392868","title":"Enhancing Image Quality by Reducing Compression Artifacts Using Dynamic Window Swin Transformer","year":2024,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Computer vision; Image compression; Compression artifact; Data compression; Pixel; Image quality; Transformer; Image processing; Engineering; Image (mathematics)","score_opus":0.02602552822990455,"score_gpt":0.33096843423982614,"score_spread":0.3049429060099216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395097710","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11517779,0.0009726794,0.87869036,0.0001715202,0.000078755445,0.000076193406,0.00009573003,0.0018899034,0.0028471274],"genre_scores_gemma":[0.7471823,0.0011565947,0.24594338,0.00027344422,0.00006997572,0.000058458372,0.00030888282,0.0003009588,0.004706064],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998592,0.000014286325,0.00000783413,0.000026407204,0.000074726464,0.000017497863],"domain_scores_gemma":[0.9997048,0.000072788345,0.00005510604,0.00004600455,0.00009821419,0.000023202047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027953723,0.0005721306,0.00038280356,0.0005559543,0.00013779923,0.0004640911,0.00051793654,0.0002905894,0.0015830224],"category_scores_gemma":[0.00093554,0.0001429816,0.0003502534,0.00031160202,0.00028928963,0.0008660932,0.0005967942,0.0005519129,0.00035505692],"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":[0.0004330034,0.0001738514,0.0015534698,0.00017588744,0.00007467984,0.00021869788,0.000094089046,0.047384497,0.33802435,0.0032139197,0.0025733938,0.60608023],"study_design_scores_gemma":[0.000028884173,0.00027916356,0.003041234,0.000029093671,0.00009956979,0.0005112016,0.00004782416,0.7110154,0.27799696,0.002148431,0.004773319,0.000028849814],"about_ca_topic_score_codex":0.001739188,"about_ca_topic_score_gemma":0.0028121728,"teacher_disagreement_score":0.001739188,"about_ca_system_score_codex":0.00033560282,"about_ca_system_score_gemma":0.00036319825,"threshold_uncertainty_score":0.005295694},"labels":[],"label_agreement":null},{"id":"W4414153861","doi":"10.1109/jetcas.2025.3608825","title":"Research on QC-LDPC Decoding Method With Low Quantization Word Length Based on Adaptive Information Mapping in Passive Optical Network","year":2025,"lang":"en","type":"article","venue":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","topic":"Optical Network Technologies","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":"Optech (Canada)","funders":"","keywords":"Decoding methods; Coding gain; List decoding; Quantization (signal processing); Adaptive coding; Sequential decoding; Linear network coding; Coding (social sciences)","score_opus":0.030498598112760202,"score_gpt":0.2979077763353293,"score_spread":0.2674091782225691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414153861","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09076548,0.003493957,0.89025337,0.00062495755,0.00024240729,0.00012381177,0.000061726285,0.0005703233,0.013863914],"genre_scores_gemma":[0.74350846,0.002902563,0.24486986,0.00017358403,0.00008996434,0.00009372492,0.00008789129,0.00006415998,0.008209842],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995628,0.000057362508,0.000019005549,0.000085562046,0.0002473948,0.000027897022],"domain_scores_gemma":[0.9995117,0.00016144155,0.000053784945,0.0000466978,0.0002097404,0.00001671521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031073403,0.00036195046,0.00030057106,0.00039290474,0.00044843124,0.00047664714,0.00063982623,0.00046579124,0.000992779],"category_scores_gemma":[0.0011210137,0.00019499731,0.0002542526,0.0005821513,0.00055105815,0.0013028354,0.00032706972,0.00054231007,0.00023701391],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028642738,0.00023345383,0.003302902,0.0008547534,0.00008238357,0.00050171127,0.00062697945,0.18992761,0.34282827,0.09801819,0.0034382103,0.359899],"study_design_scores_gemma":[0.000026210006,0.00014727467,0.0004747845,0.000025050556,0.000021027638,0.00028158963,0.000032112435,0.90273535,0.088267975,0.0032981953,0.004645589,0.000044884804],"about_ca_topic_score_codex":0.0041835667,"about_ca_topic_score_gemma":0.002763339,"teacher_disagreement_score":0.0041835667,"about_ca_system_score_codex":0.00083868037,"about_ca_system_score_gemma":0.001000522,"threshold_uncertainty_score":0.008318424},"labels":[],"label_agreement":null}]}