{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":72,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":72,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"6b38d6abb64e","filters":{"venue":"Journal of Signal Processing Systems"}},"results":[{"id":"W2071727855","doi":"10.1007/s11265-012-0685-3","title":"Hardware Implementation of Successive-Cancellation Decoders for Polar Codes","year":2012,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":85,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Decoding methods; Computer science; Coding (social sciences); Polar; Logarithm; Arithmetic; Algorithm; Coding theory; Theoretical computer science; Computer engineering; Mathematics","authors":[{"name":"Camille Leroux","is_ca":false},{"name":"Alexandre J. Raymond","is_ca":true},{"name":"Gabi Sarkis","is_ca":true},{"name":"Ido Tal","is_ca":false},{"name":"Alexander Vardy","is_ca":false},{"name":"Warren J. Gross","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02961915339333666,"gpt":0.3307011821027505,"spread":0.3010820287094138,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004604762,0.0005763944,0.0003532921,0.0006738087,0.0004762332,0.0009592524,0.0008426491,0.0005573704,0.005804342],"category_scores_gemma":[0.001724186,0.0002945969,0.0002691094,0.0004236751,0.0002496442,0.0005527004,0.0005306815,0.000636113,0.0020292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000479806,"about_ca_system_score_gemma":0.00123902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001679147,"about_ca_topic_score_gemma":0.003837774,"domain_scores_codex":[0.999608,0.00009438516,0.00002587597,0.00003465362,0.0001729836,0.00006408799],"domain_scores_gemma":[0.9991672,0.000357895,0.00005022546,0.000104296,0.0002816108,0.0000388213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00188885,0.0003543061,0.001922975,0.0004305227,0.0001544213,0.0004570656,0.0003134271,0.06535044,0.3112888,0.05955629,0.007173326,0.5511096],"study_design_scores_gemma":[0.0002832341,0.0007002536,0.001004315,0.00007162039,0.00008414836,0.0007068066,0.00007817904,0.5764771,0.3928434,0.0112111,0.01646353,0.0000764038],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07801528,0.0005603195,0.9063286,0.0002941016,0.0002970462,0.0001313814,0.000217382,0.004012399,0.01014358],"genre_scores_gemma":[0.5315674,0.0003952413,0.4592222,0.000249386,0.00009933826,0.0001160868,0.0004154668,0.00009940119,0.007835457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005804342,"threshold_uncertainty_score":0.01941741,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2301698642","doi":"10.1007/s11265-016-1173-y","title":"Fast Low-Complexity Decoders for Low-Rate Polar Codes","year":2016,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure; McGill University","funders":"","keywords":"Decoding methods; Computer science; Application-specific integrated circuit; Clock rate; Polar code; Latency (audio); Throughput; Code rate; Polar; Algorithm; CMOS; Field-programmable gate array; Efficient energy use; Word error rate; Bit error rate; Computer hardware; Electronic engineering; Telecommunications; Wireless; Electrical engineering; Physics; Engineering; Chip; Speech recognition","authors":[{"name":"Pascal Giard","is_ca":true},{"name":"Alexios Balatsoukas‐Stimming","is_ca":false},{"name":"Gabi Sarkis","is_ca":true},{"name":"Claude Thibeault","is_ca":true},{"name":"Warren J. Gross","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03401375944202923,"gpt":0.285097868185592,"spread":0.2510841087435628,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001055456,0.001101734,0.0008722594,0.0009066685,0.0006010652,0.001870287,0.0007503701,0.001081233,0.006696536],"category_scores_gemma":[0.005590712,0.0005078747,0.0003383113,0.0008662513,0.0005562733,0.00161734,0.001467178,0.001663353,0.003952269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006440968,"about_ca_system_score_gemma":0.001738557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001363781,"about_ca_topic_score_gemma":0.003991804,"domain_scores_codex":[0.9990202,0.0002595473,0.00006093872,0.00008736789,0.0004563092,0.0001155443],"domain_scores_gemma":[0.9973317,0.001615818,0.0001832775,0.0002662698,0.0005269523,0.00007590446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001813178,0.0001815831,0.001408215,0.0006012474,0.0001397683,0.0004951347,0.0003984667,0.1342659,0.09913088,0.1661486,0.01524888,0.5801681],"study_design_scores_gemma":[0.0002204248,0.0002614883,0.000520192,0.0001377272,0.00006816439,0.000653453,0.00009247768,0.8388596,0.08571673,0.05704585,0.01632793,0.00009593332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01999358,0.0009202391,0.9718621,0.0003971547,0.0002073671,0.00009990962,0.0002766138,0.001346477,0.004896464],"genre_scores_gemma":[0.266853,0.001529989,0.7138855,0.0004426425,0.0003235685,0.0002986918,0.0008360933,0.0003237784,0.01550666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006696536,"threshold_uncertainty_score":0.02240211,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2105281355","doi":"10.1007/s11265-007-0141-y","title":"Interconnect Driver Design for Long Wires in Field-Programmable Gate Arrays","year":2007,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Western Canada Research Grid; CMC Microsystems","keywords":"Interconnection; Repeater (horology); Field-programmable gate array; Overhead (engineering); Computer science; Node (physics); Electronic engineering; Path (computing); Transistor; Critical path method; Electrical engineering; Engineering; Embedded system; Voltage; Telecommunications","authors":[{"name":"Edmund Lee","is_ca":true},{"name":"Guy Lemieux","is_ca":true},{"name":"Shahriar Mirabbasi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01834471730071356,"gpt":0.2463816501045032,"spread":0.2280369328037896,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000229629,0.0003710832,0.0001997665,0.0003349309,0.0003911332,0.0007528038,0.0009596723,0.0003086201,0.002186876],"category_scores_gemma":[0.0005727747,0.0002255327,0.0001514954,0.0002462119,0.0001430614,0.0005971387,0.0003144026,0.000267729,0.0004005044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007607891,"about_ca_system_score_gemma":0.0008221787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009846545,"about_ca_topic_score_gemma":0.004961522,"domain_scores_codex":[0.999863,0.0000300535,0.000008244605,0.00002421944,0.00004448295,0.00002998499],"domain_scores_gemma":[0.9996065,0.00008373205,0.00007791463,0.00002413641,0.0001807693,0.00002694327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007206269,0.0003819043,0.004794647,0.0007191419,0.0002361607,0.000609678,0.0008780636,0.1100487,0.5540248,0.0623951,0.01716153,0.2480297],"study_design_scores_gemma":[0.0001380744,0.002157511,0.002340168,0.00007287991,0.0002072209,0.0005387274,0.0004426255,0.6914895,0.2531127,0.01208946,0.03733145,0.00007980799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3588317,0.0008561155,0.6220757,0.0005664827,0.000240265,0.0002247674,0.0002183867,0.001670743,0.01531588],"genre_scores_gemma":[0.9332024,0.0002716295,0.05703459,0.0001936885,0.00005677203,0.0000980944,0.0001960207,0.0001800404,0.00876675],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002186876,"threshold_uncertainty_score":0.007315814,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2119245818","doi":"10.1007/s11265-008-0202-x","title":"Robust Multimodal Registration Using Local Phase-Coherence Representations","year":2008,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Artificial intelligence; Computer science; Robustness (evolution); Subpixel rendering; Residual; Image registration; Computer vision; Pattern recognition (psychology); Coherence (philosophical gambling strategy); Image (mathematics); Mathematics; Algorithm; Pixel; Statistics","authors":[{"name":"Alexander Wong","is_ca":true},{"name":"Jeff Orchard","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09840738497082493,"gpt":0.3438411514168963,"spread":0.2454337664460713,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001084842,0.0007657821,0.0006380025,0.001305584,0.0003815462,0.00131571,0.0007277681,0.001099444,0.002068472],"category_scores_gemma":[0.004450078,0.0006106674,0.0009142316,0.001230596,0.0006457369,0.001986274,0.001516899,0.001185956,0.001078765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000296563,"about_ca_system_score_gemma":0.0006422281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000641824,"about_ca_topic_score_gemma":0.001244973,"domain_scores_codex":[0.9994707,0.0001837098,0.00002962159,0.0001033605,0.0001629983,0.00004963419],"domain_scores_gemma":[0.9992055,0.0002990217,0.0001348692,0.0001897208,0.0001393768,0.0000315349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007468387,0.0001886552,0.001111557,0.000305344,0.0002607848,0.0002896022,0.0003020104,0.1215916,0.1763095,0.03429991,0.004801563,0.6597927],"study_design_scores_gemma":[0.00006233995,0.0001845432,0.002032116,0.00004289819,0.0001656563,0.0007100131,0.00009564513,0.901092,0.05763135,0.03222862,0.005677043,0.00007773491],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01182955,0.0002121312,0.9864926,0.0001269533,0.00002587636,0.00002852033,0.00004773524,0.000353563,0.0008831344],"genre_scores_gemma":[0.2833367,0.0007547813,0.7105502,0.0001667343,0.0001123696,0.0001820448,0.0004545922,0.0005946793,0.003847864],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002068472,"threshold_uncertainty_score":0.006919682,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2124989052","doi":"10.1007/s11265-007-0156-4","title":"On Bandwidth Selection in Local Polynomial Regression Analysis and Its Application to Multi-resolution Analysis of Non-uniform Data","year":2008,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of Saskatchewan; University of Missouri","keywords":"Bandwidth (computing); Algorithm; Computer science; Polynomial regression; Polynomial; Regression analysis; Signal processing; Mathematics; Digital signal processing; Machine learning; Telecommunications","authors":[{"name":"Z. G. Zhang","is_ca":false},{"name":"S. C. Chan","is_ca":false},{"name":"K.L. Ho","is_ca":false},{"name":"K. C. Ho","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03720577878590518,"gpt":0.3207950727128988,"spread":0.2835892939269936,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003876925,0.0007985047,0.00112969,0.001429458,0.0005402793,0.001035201,0.001046746,0.001510959,0.001386216],"category_scores_gemma":[0.0133333,0.000466838,0.0008836241,0.00165545,0.00130693,0.001475928,0.001291747,0.00154407,0.0005725559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003788227,"about_ca_system_score_gemma":0.00048188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001909813,"about_ca_topic_score_gemma":0.002147589,"domain_scores_codex":[0.9987057,0.0006959398,0.00006550107,0.0001658386,0.0002932692,0.00007371666],"domain_scores_gemma":[0.9941899,0.004559568,0.0002047409,0.000401121,0.000554363,0.00009027974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004702284,0.0001875705,0.001473102,0.0005957671,0.0001770684,0.0005412283,0.000406456,0.2517387,0.06870777,0.1040807,0.002935947,0.5686855],"study_design_scores_gemma":[0.0000113114,0.0000423097,0.00048837,0.00002973888,0.00003996541,0.0001250569,0.00002752751,0.9678049,0.008166312,0.02124091,0.001993884,0.00002969702],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004626862,0.0007259677,0.9940469,0.0001126817,0.00002971287,0.00001106263,0.000008088555,0.00009156959,0.0003471407],"genre_scores_gemma":[0.2612644,0.005664386,0.7265795,0.0002246751,0.0004303903,0.000125642,0.0001307722,0.0005131665,0.005067077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003876925,"threshold_uncertainty_score":0.0205034,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2163786726","doi":"10.1007/s11265-015-1012-6","title":"Speaker Adaptation of Hybrid NN/HMM Model for Speech Recognition Based on Singular Value Decomposition","year":2015,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Speech recognition; Singular value decomposition; TIMIT; Hidden Markov model; Adaptation (eye); Vocabulary; Speaker recognition; Pattern recognition (psychology); Artificial intelligence; Artificial neural network; Task (project management)","authors":[{"name":"Shaofei Xue","is_ca":false},{"name":"Hui Jiang","is_ca":true},{"name":"Li-Rong Dai","is_ca":false},{"name":"Qingfeng Liu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08558740047888537,"gpt":0.293905759405991,"spread":0.2083183589271057,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003796903,0.0003962899,0.0005957439,0.0002498154,0.0002349908,0.000325474,0.0004637911,0.0004565084,0.001754523],"category_scores_gemma":[0.0005862226,0.0002390027,0.0006575696,0.0002855563,0.0001204418,0.0004125532,0.0002842078,0.000624058,0.001327657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001573161,"about_ca_system_score_gemma":0.0003235019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003930071,"about_ca_topic_score_gemma":0.004849232,"domain_scores_codex":[0.9997438,0.00006089202,0.00001616358,0.00007953049,0.00007725869,0.00002241622],"domain_scores_gemma":[0.9997839,0.00006602416,0.000009268396,0.00002948874,0.000101074,0.0000102032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005783412,0.0001642369,0.002399316,0.0001856016,0.0002255799,0.0002040576,0.0001575715,0.1749005,0.1978183,0.002207711,0.003469903,0.6176889],"study_design_scores_gemma":[0.000005631265,0.00004652831,0.001515361,0.000007060078,0.00003705798,0.0001014968,0.00001056845,0.9800832,0.0165108,0.0003931045,0.001273886,0.00001526253],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02934953,0.0004709781,0.9677425,0.00005300778,0.0001213604,0.00002035156,0.00008702793,0.001013994,0.001141215],"genre_scores_gemma":[0.6631777,0.0007867978,0.3270794,0.00009677441,0.0001007879,0.0001127288,0.0007874441,0.000278391,0.007579882],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003930071,"threshold_uncertainty_score":0.007814348,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4385320790","doi":"10.1007/s11265-023-01880-w","title":"Low Power Blockchain in Industry 4.0 Case Study: Water Management in Tunisia","year":2023,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"","keywords":"Traceability; Blockchain; Computer security; Water security; Reliability (semiconductor); Business; Work (physics); Consumption (sociology); Service provider; Internet of Things; Environmental economics; Water industry; Computer science; Service (business); Water supply; Power (physics); Engineering; Water resources; Marketing","authors":[{"name":"Tarek Frikha","is_ca":false},{"name":"Jalel Ktari","is_ca":false},{"name":"Nader Ben Amor","is_ca":false},{"name":"Faten Chaabane","is_ca":false},{"name":"Monia Hamdi","is_ca":false},{"name":"Fehmi Denguir","is_ca":false},{"name":"Habib Hamam","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0173303216200356,"gpt":0.2698707386578749,"spread":0.2525404170378392,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001237468,0.0002549814,0.0002448122,0.0005755496,0.001725385,0.001328494,0.0008353637,0.001522024,0.006745162],"category_scores_gemma":[0.001883948,0.0001194038,0.0002146827,0.001031687,0.0008252572,0.001279296,0.001050113,0.0005843911,0.0005827625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001903723,"about_ca_system_score_gemma":0.001455095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03039485,"about_ca_topic_score_gemma":0.03795712,"domain_scores_codex":[0.999318,0.000287017,0.00002948107,0.00006221525,0.0001023834,0.0002010217],"domain_scores_gemma":[0.9984628,0.0006963526,0.0001369694,0.000165636,0.0002888552,0.0002493624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002996775,0.002845545,0.1376148,0.0009957044,0.0002444208,0.0552272,0.009513752,0.4554902,0.0341033,0.1122911,0.03412182,0.1545554],"study_design_scores_gemma":[0.0007635463,0.001865271,0.06044237,0.0003933362,0.0002035449,0.00564268,0.034741,0.6521402,0.04114151,0.03596582,0.1665354,0.0001652378],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9741666,0.0001572479,0.004404984,0.0008644731,0.00001769186,0.0001126859,0.0004253677,0.0001031481,0.01974788],"genre_scores_gemma":[0.9880001,0.00009018106,0.002780158,0.00003800233,0.000006270663,0.00003160473,0.0002065383,0.00001714404,0.008829965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03039485,"threshold_uncertainty_score":0.06043589,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2016433047","doi":"10.1007/s11265-009-0376-x","title":"Efficient FPGA Implementation of a Programmable Architecture for GF(p) Elliptic Curve Crypto Computations","year":2009,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Cryptography and Residue Arithmetic","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Jordan University of Science and Technology; Dalhousie University","keywords":"Elliptic curve cryptography; Elliptic curve point multiplication; Elliptic Curve Digital Signature Algorithm; Field-programmable gate array; Tripling-oriented Doche–Icart–Kohel curve; Computation; Computer science; Elliptic curve; Hessian form of an elliptic curve; Parallel computing; Multiplication (music); Cryptography; Prime (order theory); Arithmetic; Mathematics; Algorithm; Computer hardware; Public-key cryptography; Combinatorics; Encryption; Pure mathematics","authors":[{"name":"Lo’ai Tawalbeh","is_ca":false},{"name":"Abidalrahman Mohammad","is_ca":false},{"name":"Adnan Gutub","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.014614736333983,"gpt":0.2884955644651681,"spread":0.2738808281311851,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001127416,0.0004588521,0.0002505842,0.0005901676,0.0003011157,0.0006532372,0.000600873,0.0002425964,0.006759877],"category_scores_gemma":[0.0002968858,0.0001900861,0.0001841782,0.0003890857,0.0001240903,0.0003633178,0.0001819144,0.0002852641,0.001128503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003640777,"about_ca_system_score_gemma":0.0005788542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0015784,"about_ca_topic_score_gemma":0.003499216,"domain_scores_codex":[0.9998775,0.0000211075,0.000008050203,0.00001794645,0.00004066215,0.0000346789],"domain_scores_gemma":[0.9999055,0.00002554837,0.000009677722,0.00002068331,0.00002883552,0.00000976878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002411514,0.0003191712,0.002977214,0.0006038594,0.0001531703,0.001167998,0.000174804,0.03733817,0.2851296,0.02087694,0.01629896,0.6325486],"study_design_scores_gemma":[0.00138594,0.00298355,0.008006365,0.0002503401,0.0003074415,0.002646897,0.0002597969,0.4762054,0.4211413,0.0108517,0.07583758,0.0001236223],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5613201,0.002934552,0.3702429,0.0004907731,0.0006152281,0.000315786,0.0007056344,0.008264077,0.0551109],"genre_scores_gemma":[0.8890885,0.0004712571,0.1009944,0.0001061242,0.00005552344,0.00005869961,0.0004740454,0.00007339964,0.008678171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006759877,"threshold_uncertainty_score":0.02261406,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2094505522","doi":"10.1007/s11265-014-0911-2","title":"Iris Recognition using Robust Localization and Nonsubsampled Contourlet Based Features","year":2014,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Contourlet; Artificial intelligence; Pattern recognition (psychology); Iris recognition; Computer science; Computer vision; Support vector machine; Feature extraction; Feature selection; Feature vector; Biometrics; Wavelet transform","authors":[{"name":"Sirvan Khalighi","is_ca":false},{"name":"Fatemeh Pak","is_ca":false},{"name":"Parisa Tirdad","is_ca":true},{"name":"Urbano Nunes","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04843114347158269,"gpt":0.2589170760828741,"spread":0.2104859326112914,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003452724,0.0003309122,0.0005460755,0.0006953411,0.0001842685,0.0005667512,0.000382542,0.0005072629,0.001049098],"category_scores_gemma":[0.0009546258,0.00022654,0.0004200922,0.0006275336,0.0002251367,0.00089221,0.000404721,0.0003793846,0.0008458928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001398127,"about_ca_system_score_gemma":0.0002602951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004476688,"about_ca_topic_score_gemma":0.0006831198,"domain_scores_codex":[0.9996933,0.0000501212,0.00001781547,0.00007676573,0.0001326145,0.00002943213],"domain_scores_gemma":[0.9994196,0.000173035,0.00008387263,0.0001248028,0.0001735069,0.00002523537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007142496,0.0001798267,0.002706403,0.0001074113,0.00006461331,0.0001589849,0.00005576245,0.007519694,0.4321245,0.001181285,0.001289777,0.5538976],"study_design_scores_gemma":[0.00006082862,0.0005154622,0.01768523,0.0000252281,0.0001605979,0.001006446,0.00005674254,0.6472607,0.3290828,0.0009109592,0.003176352,0.00005871618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.176824,0.0007719232,0.8189004,0.0001636029,0.0001167345,0.00004191745,0.0001231197,0.001208217,0.001850093],"genre_scores_gemma":[0.6780674,0.000618032,0.3173908,0.00008871261,0.00009223622,0.00004623585,0.000355373,0.0001093114,0.003232021],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001049098,"threshold_uncertainty_score":0.003509581,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4367316159","doi":"10.1007/s11265-023-01870-y","title":"A Fast and Light Fingerprint-Matching Model Based on Deep Learning Approaches","year":2023,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Biometrics; Artificial intelligence; Preprocessor; Convolutional neural network; Identification (biology); Fingerprint (computing); Segmentation; Pattern recognition (psychology); Matching (statistics); Architecture; Deep learning; Computer vision; Machine learning","authors":[{"name":"Hamid Shafaghi","is_ca":false},{"name":"Meysam Kiani","is_ca":false},{"name":"Abdolah Amirany","is_ca":false},{"name":"Kian Jafari","is_ca":true},{"name":"Mohammad Hossein Moaiyeri","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04477417712601117,"gpt":0.2497754268995254,"spread":0.2050012497735142,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004556776,0.000503426,0.0009200786,0.0005401678,0.0003458396,0.0007426784,0.001540266,0.001141959,0.002759989],"category_scores_gemma":[0.0008648068,0.0004188388,0.0007693967,0.0007205829,0.000307342,0.001275672,0.00113373,0.001427586,0.001078134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005900493,"about_ca_system_score_gemma":0.0009120852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006735285,"about_ca_topic_score_gemma":0.006344634,"domain_scores_codex":[0.9997405,0.00003293881,0.00001146072,0.00007645957,0.00009119326,0.00004743921],"domain_scores_gemma":[0.9997296,0.00006197713,0.0000257944,0.00004882614,0.0001080405,0.00002578837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003199456,0.0002493712,0.001332964,0.0001039448,0.0001460304,0.0001105894,0.00003968089,0.4030983,0.03017236,0.01167269,0.004011337,0.5487428],"study_design_scores_gemma":[0.000003007054,0.00001776525,0.000102427,0.000002593949,0.000008624541,0.00001777106,0.000001391464,0.9968876,0.001620144,0.001056616,0.0002767925,0.000005233434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01504298,0.0002966982,0.9823142,0.00016376,0.00008899139,0.00002743409,0.00009571823,0.0008355221,0.0011348],"genre_scores_gemma":[0.6959891,0.0007251509,0.2873057,0.0004518784,0.0001416054,0.0001263148,0.0004920766,0.0001954578,0.01457271],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006735285,"threshold_uncertainty_score":0.01339221,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2524478612","doi":"10.1007/s11265-016-1159-9","title":"Discriminating Bipolar Disorder from Major Depression using Whole-Brain Functional Connectivity: a Feature Selection Analysis with SVM-FoBa Algorithm","year":2016,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":21,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Lawson Health Research Institute; Western University","funders":"National Institutes of Health; Chinese Academy of Sciences; National Natural Science Foundation of China; National High-tech Research and Development Program; Lawson Health Research Institute","keywords":"Feature selection; Support vector machine; Discriminative model; Feature (linguistics); Pattern recognition (psychology); Major depressive disorder; Artificial intelligence; Bipolar disorder; Neuroimaging; Mood; Computer science; Psychology; Machine learning; Psychiatry","authors":[{"name":"Nan-Feng Jie","is_ca":false},{"name":"Elizabeth Osuch","is_ca":true},{"name":"Mao-Hu Zhu","is_ca":false},{"name":"Michael Wammes","is_ca":true},{"name":"Xiao-Ying Ma","is_ca":false},{"name":"Tian-Zi Jiang","is_ca":false},{"name":"Jing Sui （Beijing Normal University）， my correct affiliation is beijing normal university, not Qingdao University of Science and Technology, please correct the current affiliation. Thank you","is_ca":false},{"name":"Vince D. Calhoun","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02645835649391739,"gpt":0.2559026675217106,"spread":0.2294443110277932,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009900404,0.0006273041,0.0009187983,0.0009296666,0.0004351632,0.0006002858,0.0004574467,0.0005063608,0.001330565],"category_scores_gemma":[0.001691177,0.0001346543,0.0009624542,0.0004975873,0.0001227742,0.0002579393,0.0003343554,0.0005192059,0.0003254932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001834734,"about_ca_system_score_gemma":0.0004682354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0027431,"about_ca_topic_score_gemma":0.003443935,"domain_scores_codex":[0.9997926,0.00005410579,0.00002313669,0.00005643437,0.00002962811,0.0000440442],"domain_scores_gemma":[0.9996418,0.0001839231,0.00002352465,0.00002150797,0.00009890173,0.00003037254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004718393,0.001141394,0.1194999,0.0003137993,0.001039833,0.0005562144,0.000197867,0.02525407,0.06340285,0.0008347195,0.0107389,0.7723021],"study_design_scores_gemma":[0.0003306236,0.0009764108,0.1918448,0.00006116697,0.0008530476,0.001160994,0.0002298959,0.7865637,0.01338141,0.002194493,0.002344432,0.00005908126],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8181724,0.001049384,0.1762034,0.0004679509,0.0001645396,0.0002772789,0.001271581,0.001013763,0.001379673],"genre_scores_gemma":[0.9510747,0.0001667581,0.04642274,0.00006649848,0.00005987652,0.0001294849,0.001415887,0.0000508759,0.0006132917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0027431,"threshold_uncertainty_score":0.005454302,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2766216077","doi":"10.1007/s11265-018-1430-3","title":"Fast and Flexible Software Polar List Decoders","year":2019,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Huawei Technologies (Canada); Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Huawei Technologies; Agence Nationale de la Recherche","keywords":"Computer science; Decoding methods; Puncturing; Software; Soft-decision decoder; Coding (social sciences); Redundancy (engineering); Computer engineering; Algorithm; Throughput; Computer hardware; Wireless; Telecommunications; Operating system; Mathematics","authors":[{"name":"Mathieu Léonardon","is_ca":true},{"name":"Adrien Cassagne","is_ca":false},{"name":"Camille Leroux","is_ca":false},{"name":"Christophe Jégo","is_ca":false},{"name":"Louis-Philippe Hamelin","is_ca":true},{"name":"Yvon Savaria","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01247361317575138,"gpt":0.2494648621683075,"spread":0.2369912489925561,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008273405,0.001055082,0.0007153302,0.001298037,0.0008155789,0.001687747,0.001454597,0.0009877665,0.01081186],"category_scores_gemma":[0.003285029,0.0005678351,0.0004238203,0.001342525,0.0005065654,0.001609144,0.00218034,0.00110222,0.007740741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006291547,"about_ca_system_score_gemma":0.001664954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001550648,"about_ca_topic_score_gemma":0.003716775,"domain_scores_codex":[0.9989961,0.0002410462,0.00006354432,0.0001009984,0.0004694421,0.0001288562],"domain_scores_gemma":[0.9975727,0.0009211641,0.0001502713,0.0005537191,0.000697495,0.0001045644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001756517,0.0001535801,0.001261307,0.0002955232,0.00009511665,0.0004317854,0.0002276106,0.04722781,0.09057248,0.07375551,0.01995915,0.7642636],"study_design_scores_gemma":[0.0003558684,0.0005003252,0.0008900643,0.0001540216,0.0001001743,0.001114407,0.0001239591,0.7050239,0.1999641,0.0471735,0.04443161,0.0001680899],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01756287,0.0004998356,0.9666747,0.0002659186,0.0001949943,0.00009566497,0.000312728,0.008197487,0.006195786],"genre_scores_gemma":[0.268122,0.0005771928,0.7074071,0.0004408032,0.0002520361,0.0002906781,0.001143321,0.001064288,0.02070265],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01081186,"threshold_uncertainty_score":0.03616929,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2069850539","doi":"10.1007/s11265-013-0797-4","title":"Music Genre Classification Using Spectral Analysis and Sparse Representation of the Signals","year":2013,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Music and Audio Processing","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Sparse approximation; Pattern recognition (psychology); Artificial intelligence; Computer science; Feature extraction; Classifier (UML); Dimensionality reduction; K-SVD; Audio signal; Speech recognition; Speech coding","authors":[{"name":"Mehdi Banitalebi-Dehkordi","is_ca":false},{"name":"Amin Banitalebi-Dehkordi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06478566272104326,"gpt":0.281435731470267,"spread":0.2166500687492237,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000465339,0.0005488555,0.0006579596,0.003165195,0.0003130223,0.0009106056,0.0004342057,0.0006273064,0.0018806],"category_scores_gemma":[0.001804276,0.0001542349,0.0008394168,0.001818571,0.0002663938,0.0008289997,0.0005696445,0.0006771052,0.001239664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000188117,"about_ca_system_score_gemma":0.0004510917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00148765,"about_ca_topic_score_gemma":0.001899186,"domain_scores_codex":[0.9996891,0.00006271646,0.00002057874,0.00006197284,0.0001100705,0.00005551704],"domain_scores_gemma":[0.9994791,0.0001692046,0.00005687955,0.00006135529,0.0001881446,0.00004538095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005540552,0.0003156473,0.004666209,0.0001753749,0.000100848,0.0001426864,0.00012468,0.01593016,0.1127792,0.003466061,0.004694022,0.857051],"study_design_scores_gemma":[0.00006252204,0.0002731924,0.0137141,0.0000462236,0.0001186867,0.0004478631,0.0003100216,0.9576486,0.01645318,0.007301897,0.003575716,0.00004801386],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1357924,0.0009731825,0.8570989,0.0004386057,0.000267065,0.0001160432,0.0006673204,0.001023996,0.003622509],"genre_scores_gemma":[0.6162719,0.001559701,0.3743081,0.0001857568,0.0005405769,0.0001416027,0.002533895,0.0001494197,0.004309087],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003165195,"threshold_uncertainty_score":0.006291211,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2057220308","doi":"10.1007/s11265-008-0274-7","title":"Monaural Speech Separation Based on Gain Adapted Minimum Mean Square Error Estimation","year":2008,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University; Queen's University","funders":"","keywords":"Monaural; Estimator; Mean squared error; Computer science; Speech recognition; SIGNAL (programming language); Minimum mean square error; Source separation; Separation (statistics); Mathematics; Statistics","authors":[{"name":"Mohammad Hadi Radfar","is_ca":true},{"name":"Richard M. Dansereau","is_ca":true},{"name":"W.-Y. Chan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03629040671234737,"gpt":0.2861034167571161,"spread":0.2498130100447688,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007292145,0.0007636292,0.001068353,0.000525411,0.0003970677,0.0008303619,0.000588279,0.001104259,0.001748032],"category_scores_gemma":[0.002057859,0.0003894689,0.0005705357,0.0004572645,0.0002302155,0.0009854509,0.0009432269,0.0009221811,0.001392559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002029258,"about_ca_system_score_gemma":0.0006820705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009286476,"about_ca_topic_score_gemma":0.002810558,"domain_scores_codex":[0.9994856,0.000137148,0.00003631507,0.00009862371,0.0001909749,0.00005125741],"domain_scores_gemma":[0.9991972,0.0003599271,0.00004564643,0.00009845684,0.0002609435,0.00003784322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001511496,0.0001890718,0.0009349377,0.0001787726,0.0001588861,0.0001515476,0.0001026464,0.03279208,0.2839356,0.00394647,0.001658054,0.6744404],"study_design_scores_gemma":[0.00008428917,0.0001902965,0.002775672,0.00002113916,0.000107301,0.0004422274,0.00003132049,0.8845453,0.1063172,0.002354181,0.003072489,0.00005860229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01728657,0.0003697022,0.9801009,0.00009313647,0.0001495482,0.00002559248,0.00003778787,0.0008334868,0.001103363],"genre_scores_gemma":[0.2786294,0.0003853293,0.7150351,0.0001865525,0.0001578816,0.00008219922,0.0002391681,0.0001788847,0.005105523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001748032,"threshold_uncertainty_score":0.005847752,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2899428255","doi":"10.1007/s11265-018-1413-4","title":"Operation Merging for Hardware Implementations of Fast Polar Decoders","year":2018,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Decoding methods; Soft-decision decoder; Throughput; Polar code; Block (permutation group theory); Node (physics); Application-specific integrated circuit; Coding (social sciences); Channel (broadcasting)","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.03184729412565777,"gpt":0.3307016108114475,"spread":0.2988543166857897,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007123601,0.0007507685,0.0004470771,0.0009298101,0.0007822247,0.001505414,0.001089814,0.0004714448,0.007545966],"category_scores_gemma":[0.001589483,0.0004474732,0.0003436953,0.0009507599,0.0004579633,0.001563233,0.001560695,0.0007436554,0.001994106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005489309,"about_ca_system_score_gemma":0.001274504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009744912,"about_ca_topic_score_gemma":0.002585887,"domain_scores_codex":[0.999239,0.0001714759,0.00007276053,0.00008249937,0.0002928552,0.0001414244],"domain_scores_gemma":[0.9989877,0.0003935957,0.00009142193,0.0002128504,0.000271127,0.00004315433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002304722,0.0001942122,0.001815902,0.0004240418,0.00009684794,0.0004003508,0.0005432473,0.03075173,0.1686925,0.1176604,0.00592484,0.6711912],"study_design_scores_gemma":[0.000231975,0.001144148,0.001466218,0.0001434784,0.0001650522,0.001003811,0.0003939988,0.3645918,0.5389886,0.05591353,0.03582793,0.0001294286],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08719523,0.0006749373,0.8989258,0.0001476948,0.0001287372,0.0001086916,0.0001466957,0.003209849,0.009462357],"genre_scores_gemma":[0.4767263,0.0003491435,0.5148762,0.0001316408,0.00008333976,0.0001166046,0.0004461901,0.000280732,0.006989792],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007545966,"threshold_uncertainty_score":0.02524382,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1979930092","doi":"10.1007/s11265-009-0434-4","title":"Study of Algorithmic and Architectural Characteristics of Gaussian Particle Filters","year":2009,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"","keywords":"Resampling; Computer science; Field-programmable gate array; Realization (probability); Gaussian; Particle filter; Throughput; Computer engineering; Algorithm; Parallel computing; Computer hardware; Artificial intelligence; Mathematics; Kalman filter; Wireless","authors":[{"name":"Miodrag Bolić","is_ca":true},{"name":"Akshay Athalye","is_ca":false},{"name":"Sangjin Hong","is_ca":false},{"name":"Petar M. Djurić","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01825937545305971,"gpt":0.2524535555139226,"spread":0.2341941800608628,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002221616,0.0005988089,0.0004998344,0.001416169,0.0008739425,0.002347729,0.001238844,0.001429696,0.002116684],"category_scores_gemma":[0.02986117,0.0007772393,0.0005060773,0.001259335,0.001521391,0.004023258,0.001050494,0.001077873,0.0002977656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001083476,"about_ca_system_score_gemma":0.001267668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001092506,"about_ca_topic_score_gemma":0.001184297,"domain_scores_codex":[0.9991342,0.0002556188,0.00005443861,0.0001320591,0.0003345564,0.00008915768],"domain_scores_gemma":[0.9797449,0.01404384,0.001353684,0.001505066,0.002926898,0.0004257404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001817089,0.0001480168,0.01031404,0.0001551089,0.00005630002,0.0002741036,0.0003788196,0.2807728,0.01291098,0.6396877,0.001157943,0.05396258],"study_design_scores_gemma":[0.00001673024,0.0001050539,0.003030636,0.00001775021,0.00002693955,0.0003633215,0.0001242703,0.8891678,0.002767376,0.1033016,0.001048738,0.0000298526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.214154,0.0007364727,0.7749575,0.00063005,0.00008123791,0.00006644827,0.0001098544,0.0002677733,0.00899658],"genre_scores_gemma":[0.9332476,0.000456724,0.06390173,0.00007479569,0.0001326414,0.00006520568,0.000191971,0.0001104636,0.001818903],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002347729,"threshold_uncertainty_score":0.01174915,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1982382171","doi":"10.1007/s11265-012-0656-8","title":"Differential Time Signaling Data-Link Architecture","year":2012,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Advancements in PLL and VCO Technologies","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Signal edge; Jitter; Computer science; Digital clock manager; SIGNAL (programming language); CMOS; Clock domain crossing; Field-programmable gate array; Bandwidth (computing); Electronic engineering; Computer hardware; Clock skew; Clock signal; Analog signal; Engineering; Telecommunications; Digital signal processing; Synchronous circuit","authors":[{"name":"Mostafa Rashdan","is_ca":true},{"name":"Abdel Yousif","is_ca":true},{"name":"J.W. Haslett","is_ca":true},{"name":"Brent Maundy","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02541652138477105,"gpt":0.2550465116825602,"spread":0.2296299902977891,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002082416,0.0002724334,0.0001897196,0.0005251637,0.000303069,0.0008314533,0.001114643,0.0005038915,0.004537945],"category_scores_gemma":[0.0002935441,0.0001664043,0.0001497548,0.0004691565,0.0002575225,0.0007528185,0.0003926499,0.000503408,0.001010804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006221537,"about_ca_system_score_gemma":0.000457085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004445706,"about_ca_topic_score_gemma":0.0006770703,"domain_scores_codex":[0.9996896,0.00003473758,0.00002655302,0.00005997584,0.0001398678,0.00004928945],"domain_scores_gemma":[0.9997608,0.00003197445,0.00003919587,0.00004343415,0.0001015022,0.00002301114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000590478,0.000172776,0.002029703,0.0004916126,0.00005413685,0.000497786,0.0002328594,0.01497347,0.7137934,0.05416752,0.005912934,0.2070833],"study_design_scores_gemma":[0.0001379665,0.001598125,0.002031365,0.00005650052,0.00009678023,0.001970423,0.00007645017,0.1679954,0.7284235,0.005810697,0.09170625,0.0000964557],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1981377,0.001414124,0.7608397,0.0006249111,0.0005804638,0.0002412341,0.0004916689,0.005975781,0.03169441],"genre_scores_gemma":[0.8697582,0.0005223189,0.1155962,0.0003705693,0.0001570207,0.0001139027,0.0004833181,0.00006952672,0.01292893],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004537945,"threshold_uncertainty_score":0.01518095,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4303645613","doi":"10.1007/s11265-022-01814-y","title":"PipeBERT: High-throughput BERT Inference for ARM Big.LITTLE Multi-core Processors","year":2022,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Huawei Technologies","keywords":"Computer science; Inference; Pipeline (software); Edge device; Throughput; Enhanced Data Rates for GSM Evolution; Parallel computing; Cluster analysis; Artificial intelligence; Computer engineering; Operating system","authors":[{"name":"Hung-Yang Chang","is_ca":true},{"name":"Seyyed Hasan Mozafari","is_ca":true},{"name":"Cheng Chen","is_ca":true},{"name":"James J. Clark","is_ca":true},{"name":"Brett H. Meyer","is_ca":true},{"name":"Warren J. Gross","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06144530065752316,"gpt":0.3143183680113405,"spread":0.2528730673538173,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007270032,0.00206016,0.000940843,0.0008418723,0.0008283636,0.001374242,0.003263957,0.001201574,0.03463892],"category_scores_gemma":[0.003539472,0.001469782,0.0008136429,0.0007579139,0.0004372498,0.001578076,0.001414453,0.002395628,0.01226121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009784694,"about_ca_system_score_gemma":0.002673604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01277894,"about_ca_topic_score_gemma":0.02570761,"domain_scores_codex":[0.9994307,0.00008453614,0.00002280847,0.000183084,0.0001989418,0.00007987343],"domain_scores_gemma":[0.9991845,0.0003048036,0.00004799043,0.0001769846,0.0002126665,0.00007300031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00281455,0.000495954,0.005602058,0.0007927481,0.0006214451,0.0004470937,0.000238252,0.153113,0.0248998,0.01306695,0.3066733,0.4912348],"study_design_scores_gemma":[0.0001879528,0.00009488232,0.0008947602,0.00002825916,0.0000479179,0.00006067004,0.00003054547,0.9480112,0.01661751,0.01160375,0.02236155,0.00006106115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01628911,0.000937521,0.698991,0.000653991,0.0005670507,0.0002422147,0.005967954,0.2627106,0.01364052],"genre_scores_gemma":[0.3310664,0.0004344191,0.608621,0.001074116,0.0001866667,0.0004909846,0.01194026,0.01322826,0.03295789],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03463892,"threshold_uncertainty_score":0.1158787,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2069839933","doi":"10.1007/s11265-009-0441-5","title":"Tracking Forecast Memories for Stochastic Decoding","year":2010,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Decoding methods; Computer science; Tracking (education); Encoding (memory); Channel (broadcasting); Enhanced Data Rates for GSM Evolution; Algorithm; Artificial intelligence; Theoretical computer science; Arithmetic; Mathematics; Computer network; Psychology","authors":[{"name":"Saeed Sharifi Tehrani","is_ca":true},{"name":"Ali Naderi","is_ca":true},{"name":"Guy-Armand Kamendje","is_ca":true},{"name":"Shie Mannor","is_ca":true},{"name":"Warren J. Gross","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03194897535052128,"gpt":0.2942733387485166,"spread":0.2623243633979954,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001308125,0.0007886742,0.0009172125,0.0007503998,0.0007433075,0.00154146,0.001142824,0.001449626,0.003725813],"category_scores_gemma":[0.01102292,0.0006735656,0.0004505275,0.0009777136,0.0009880258,0.002034553,0.001499787,0.001775479,0.0009467851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008799399,"about_ca_system_score_gemma":0.001595712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004010251,"about_ca_topic_score_gemma":0.00576473,"domain_scores_codex":[0.9995129,0.0001131621,0.00003997153,0.0001070254,0.0001496999,0.00007731388],"domain_scores_gemma":[0.9958361,0.002676205,0.0002574753,0.0005368047,0.0006020982,0.00009128513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005411648,0.00007746527,0.001354574,0.0001561185,0.0001153788,0.0001873837,0.0001646624,0.5428022,0.01189697,0.218818,0.005078257,0.2188078],"study_design_scores_gemma":[0.00001038984,0.00002414748,0.00009565507,0.00001620816,0.00001188276,0.00004809128,0.000007566092,0.9626614,0.004583378,0.03185711,0.0006702946,0.00001385756],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01962293,0.0003896318,0.9770494,0.0003251285,0.0001621389,0.00002289519,0.0001200217,0.0004915834,0.001816289],"genre_scores_gemma":[0.7107746,0.0009926837,0.2729804,0.0004567871,0.0003472259,0.0001304116,0.0005475962,0.0002533128,0.01351706],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004010251,"threshold_uncertainty_score":0.01246411,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1975528831","doi":"10.1007/s11265-013-0854-z","title":"Clockless Stochastic Decoding of Low-Density Parity-Check Codes: Architecture and Simulation Model","year":2013,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo; McGill University","funders":"","keywords":"Decoding methods; Computer science; Computation; Low-density parity-check code; Stochastic computing; Synchronization (alternating current); Algorithm; CMOS; Parallel computing; Theoretical computer science; Computer engineering; Electronic engineering; Channel (broadcasting); Telecommunications; Engineering","authors":[{"name":"Naoya Onizawa","is_ca":true},{"name":"Warren J. Gross","is_ca":true},{"name":"Takahiro Hanyu","is_ca":false},{"name":"Vincent Gaudet","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02056301322011973,"gpt":0.2714206369399246,"spread":0.2508576237198049,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001103321,0.0005437474,0.001247367,0.0009733207,0.0007773494,0.001396588,0.001547587,0.002230867,0.002772298],"category_scores_gemma":[0.006417689,0.0006128671,0.000842762,0.0009608096,0.001514213,0.001700561,0.0008114007,0.001193044,0.0003896915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001977642,"about_ca_system_score_gemma":0.001947865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01330688,"about_ca_topic_score_gemma":0.008025045,"domain_scores_codex":[0.9994357,0.0001904164,0.00002380973,0.00007023476,0.0001405887,0.0001392274],"domain_scores_gemma":[0.9967932,0.002061405,0.0002900757,0.0002124987,0.0005243371,0.0001184691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004683225,0.00003111025,0.000724717,0.00002368671,0.00001828617,0.00005853261,0.00003704132,0.964669,0.0008250191,0.03245887,0.0002249426,0.0008819456],"study_design_scores_gemma":[0.000007771395,0.00000535073,0.0000781156,0.000001974011,0.000004785708,0.000007295831,0.00000383181,0.9970114,0.0001520962,0.002681319,0.00004202775,0.000004038827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7143665,0.0009253153,0.2572404,0.001829379,0.0001708627,0.0001524877,0.0006868412,0.0005647674,0.0240635],"genre_scores_gemma":[0.9893453,0.0002471209,0.006226816,0.00008744372,0.00003131849,0.00006922132,0.0001523994,0.00004415023,0.003796258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01330688,"threshold_uncertainty_score":0.02645886,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3103043697","doi":"10.1007/s11265-016-1157-y","title":"Low-Latency Software Polar Decoders","year":2016,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure; McGill University","funders":"","keywords":"Decoding methods; Memory footprint; Software; Rendering (computer graphics); Exploit; Polar; Encoding (memory); Latency (audio); Efficient energy use","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.01574898870569315,"gpt":0.2521758610143998,"spread":0.2364268723087067,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003589949,0.0006658314,0.0004457048,0.0007371655,0.0005131919,0.001441207,0.0008157266,0.0005877494,0.01124342],"category_scores_gemma":[0.002151517,0.0003112407,0.0002034933,0.0007297707,0.0002881168,0.001270016,0.0008711806,0.0007394507,0.004377101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005151324,"about_ca_system_score_gemma":0.001427793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001237186,"about_ca_topic_score_gemma":0.004223606,"domain_scores_codex":[0.9995348,0.0000913788,0.00002799541,0.00005935436,0.0002147035,0.00007175661],"domain_scores_gemma":[0.9985972,0.0005228299,0.0001173992,0.0002306122,0.0004725798,0.00005932775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002192887,0.0001922313,0.003121037,0.0004833191,0.0001025904,0.0004487192,0.0002096504,0.02531139,0.2459766,0.06157006,0.012982,0.6474095],"study_design_scores_gemma":[0.0002679361,0.0007737182,0.001636308,0.0001823102,0.0001582731,0.001525093,0.0001937187,0.4893629,0.4303199,0.02432913,0.05114697,0.0001036878],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09354854,0.001831645,0.8743999,0.000634511,0.0004566726,0.0001358612,0.0003692538,0.007860132,0.02076352],"genre_scores_gemma":[0.6835148,0.001206586,0.2776716,0.0005808022,0.0003032741,0.00009829365,0.0006757444,0.0004700141,0.03547882],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01124342,"threshold_uncertainty_score":0.03761292,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2043724059","doi":"10.1007/s11265-008-0266-7","title":"A Test-oriented Embedded System Production Methodology","year":2008,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"BP (Canada); University of Alberta; University of Calgary","funders":"","keywords":"Agile software development; Computer science; Domain (mathematical analysis); Software engineering; Extreme programming; New product development; Embedded system; Human–computer interaction; Software development; Software; Operating system; Software development process","authors":[{"name":"Michael R. Smith","is_ca":true},{"name":"James Miller","is_ca":true},{"name":"Steve Daeninck","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07046605689061651,"gpt":0.2989667409933983,"spread":0.2285006841027817,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001503299,0.001154268,0.0005381138,0.0009352776,0.0004147305,0.001132379,0.001896902,0.0007266516,0.004631644],"category_scores_gemma":[0.003622594,0.0005949207,0.0009796461,0.0005073294,0.0006894361,0.00105082,0.00101033,0.001031573,0.001222849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003173233,"about_ca_system_score_gemma":0.00105075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006944825,"about_ca_topic_score_gemma":0.0007572132,"domain_scores_codex":[0.9986184,0.0004502247,0.0001082956,0.0001477583,0.000575525,0.00009977224],"domain_scores_gemma":[0.9974208,0.001104208,0.0002030326,0.0005368538,0.0006658161,0.00006924188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003282951,0.0004294839,0.002334906,0.0009421197,0.0002023324,0.001366328,0.0004311564,0.1779307,0.1248946,0.07134841,0.00556477,0.6142268],"study_design_scores_gemma":[0.0001391913,0.0008666245,0.0009653566,0.0001610994,0.0002442678,0.001108001,0.00009567718,0.8263353,0.09987254,0.05103165,0.01912962,0.00005069179],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003250645,0.00004380924,0.9938617,0.00003861457,0.00001356295,0.0001055367,0.00003174404,0.001103588,0.001550889],"genre_scores_gemma":[0.2049239,0.0002005031,0.7897821,0.0001450516,0.00004450729,0.0003844242,0.0003028754,0.0005469783,0.003669781],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004631644,"threshold_uncertainty_score":0.01549435,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1979231468","doi":"10.1007/s11265-012-0722-2","title":"Rotation Invariance in 2D-FRFT with Application to Digital Image Watermarking","year":2012,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Digital watermarking; Artificial intelligence; Computer vision; Rotation (mathematics); Image (mathematics); Computer science; Digital image; Mathematics; Pattern recognition (psychology); Image processing","authors":[{"name":"Lei Gao","is_ca":false},{"name":"Lin Qi","is_ca":false},{"name":"Yongjin Wang","is_ca":true},{"name":"Enqing Chen","is_ca":false},{"name":"Shouyi Yang","is_ca":false},{"name":"Ling Guan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01437300640706733,"gpt":0.2672975173131321,"spread":0.2529245109060647,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003683793,0.0004880876,0.000374671,0.0007165802,0.0001863944,0.0005886391,0.0003334024,0.0006343993,0.002534359],"category_scores_gemma":[0.001655649,0.0002210791,0.0005207798,0.001079379,0.0004847923,0.0006754146,0.0004073841,0.0004784999,0.0008509005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001357127,"about_ca_system_score_gemma":0.0001752698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005813742,"about_ca_topic_score_gemma":0.0006252942,"domain_scores_codex":[0.9997868,0.00005547261,0.00001489933,0.00004200903,0.0000775494,0.00002324774],"domain_scores_gemma":[0.9995452,0.0002114467,0.00006374706,0.00009454806,0.00006851478,0.00001653395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000392027,0.0001395544,0.001108407,0.0002492212,0.00004598722,0.0005294101,0.0002077246,0.07024516,0.2412719,0.05952891,0.001786243,0.6244953],"study_design_scores_gemma":[0.00002172271,0.0002087974,0.002700087,0.00002281665,0.00004256801,0.00102886,0.0000660177,0.8892928,0.08380067,0.01533521,0.007418023,0.00006252219],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03523623,0.0006608462,0.9609488,0.0001385087,0.00008679733,0.00002220519,0.00005952331,0.0003237719,0.002523282],"genre_scores_gemma":[0.4208496,0.002550532,0.5689458,0.00008812473,0.0003088726,0.00004862335,0.0002143939,0.0002304741,0.00676366],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002534359,"threshold_uncertainty_score":0.008478284,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2103372247","doi":"10.1007/s11265-008-0290-7","title":"A New Learning Algorithm for the Fusion of Adaptive Audio–Visual Features for the Retrieval and Classification of Movie Clips","year":2008,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Music and Audio Processing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Computer science; Artificial intelligence; Support vector machine; Pattern recognition (psychology); Search engine indexing; Feature (linguistics); CLIPS; Feature extraction; Process (computing)","authors":[{"name":"Paisarn Muneesawang","is_ca":false},{"name":"Ling Guan","is_ca":true},{"name":"Tahir Amin","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04558453011064346,"gpt":0.2844070727180484,"spread":0.238822542607405,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002173356,0.001041965,0.001765303,0.001680296,0.0006333243,0.00118815,0.00243746,0.001875654,0.002790266],"category_scores_gemma":[0.003207617,0.0005469942,0.001114427,0.001939093,0.000567664,0.001768339,0.001562187,0.001731537,0.001888711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006856658,"about_ca_system_score_gemma":0.001061524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004296965,"about_ca_topic_score_gemma":0.004671869,"domain_scores_codex":[0.998992,0.0001435884,0.000095851,0.0003088204,0.0003644144,0.00009529901],"domain_scores_gemma":[0.9987488,0.000375777,0.00007688104,0.0001042797,0.0006313832,0.00006286713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002566603,0.0001393325,0.0005074404,0.00007577839,0.0001197292,0.00003156947,0.00003726791,0.02122234,0.02255014,0.002076663,0.003548048,0.9494351],"study_design_scores_gemma":[0.00007407829,0.0001312593,0.0008677383,0.00001331071,0.00006348923,0.0001109721,0.00001882559,0.9804127,0.01229724,0.002402651,0.003578075,0.00002975519],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004169347,0.0003016218,0.9944061,0.00006972891,0.00009450794,0.00006628525,0.00004912067,0.0005814411,0.0002619019],"genre_scores_gemma":[0.0621076,0.0003122511,0.9337202,0.000198961,0.0001858948,0.000318928,0.0004219016,0.00009764393,0.00263661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004296965,"threshold_uncertainty_score":0.01149392,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2014624009","doi":"10.1007/s11265-013-0811-x","title":"Self-Adapting Resource Escalation for Resilient Signal Processing Architectures","year":2013,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Control reconfiguration; Computer science; Latency (audio); Redundancy (engineering); Real-time computing; Encoder; Benchmark (surveying); Throughput; Embedded system; Distributed computing; Telecommunications","authors":[{"name":"Naveed Imran","is_ca":false},{"name":"Ronald F. DeMara","is_ca":false},{"name":"Jooheung Lee","is_ca":false},{"name":"Jian Huang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01582267861742095,"gpt":0.2401296982736983,"spread":0.2243070196562774,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005749086,0.0005372188,0.0004537576,0.0005114183,0.0006955793,0.0008566708,0.001229671,0.000493629,0.003010423],"category_scores_gemma":[0.002392647,0.0002214343,0.0002604927,0.0003576067,0.0004939975,0.00112724,0.001081621,0.0008346344,0.0003766303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005053174,"about_ca_system_score_gemma":0.0005135936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007698445,"about_ca_topic_score_gemma":0.001448265,"domain_scores_codex":[0.9996384,0.00008043035,0.00002497544,0.00007393088,0.0000759567,0.0001062435],"domain_scores_gemma":[0.9990676,0.0002571369,0.0001161996,0.0002815384,0.0002039394,0.0000735893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007057528,0.0003222416,0.001838724,0.0001476267,0.0001072379,0.0004671737,0.0003657202,0.6464372,0.07936823,0.04955493,0.006159105,0.214526],"study_design_scores_gemma":[0.00001459283,0.00009248206,0.0002237888,0.000006659851,0.00001754446,0.00007835397,0.00004397666,0.9809194,0.00596429,0.01160909,0.001017701,0.00001211536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3471883,0.0006677318,0.6366911,0.0007790548,0.000269858,0.0001287017,0.00008334251,0.002540448,0.01165158],"genre_scores_gemma":[0.9785097,0.00006823159,0.01941682,0.00008419711,0.00002481597,0.00002911559,0.00003040505,0.00003997614,0.001796715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003010423,"threshold_uncertainty_score":0.01007086,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2041025829","doi":"10.1007/s11265-013-0791-x","title":"Design and Implementation of a Polynomial Basis Multiplier Architecture Over GF(2m)","year":2013,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Cryptography and Residue Arithmetic","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Huawei Technologies (Canada); Terry Fox Research Institute","funders":"","keywords":"Polynomial basis; Parameterized complexity; Finite field; Multiplier (economics); Multiplication (music); Mathematics; Primitive polynomial; Polynomial; Irreducible polynomial; Galois theory; Computer science; Architecture; Arithmetic; GF(2); Discrete mathematics; Algorithm; Combinatorics; Matrix polynomial","authors":[{"name":"H. Ho","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01056677226794983,"gpt":0.2482092481803203,"spread":0.2376424759123704,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001558704,0.0003868452,0.0002844981,0.0005807428,0.0005606415,0.0006775974,0.0009856194,0.0005061561,0.005124672],"category_scores_gemma":[0.0003712223,0.0002452203,0.000223381,0.0005164588,0.0001636245,0.0004474739,0.0002808588,0.0003541872,0.001421999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005079071,"about_ca_system_score_gemma":0.001185594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001510612,"about_ca_topic_score_gemma":0.003455633,"domain_scores_codex":[0.9998472,0.0000224688,0.00001056616,0.00003093201,0.00004746088,0.00004134032],"domain_scores_gemma":[0.9998459,0.00001970541,0.00002111414,0.00002608726,0.00007100902,0.0000162225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001100523,0.0003789284,0.003489166,0.0006903823,0.0002458324,0.001180299,0.0003509116,0.02169459,0.501408,0.02561739,0.01260393,0.43124],"study_design_scores_gemma":[0.0008667632,0.003853231,0.007141082,0.0001953231,0.0003555098,0.003646035,0.0002527454,0.3075939,0.595365,0.009881812,0.07068638,0.0001620615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.393401,0.001694837,0.5666308,0.0008719489,0.0006194134,0.00067654,0.0005085965,0.006583009,0.02901381],"genre_scores_gemma":[0.7607797,0.0003352689,0.2277165,0.0002331416,0.00008251649,0.0001739506,0.0004472522,0.00005304633,0.01017869],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005124672,"threshold_uncertainty_score":0.01714367,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2067412888","doi":"10.1007/s11265-014-0898-8","title":"Two Fast and Robust Modified Gaussian Mixture Models Incorporating Local Spatial Information for Image Segmentation","year":2014,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"","keywords":"Robustness (evolution); Mixture model; Artificial intelligence; Pattern recognition (psychology); Pixel; Image segmentation; Computer science; Mathematics; Segmentation; Gaussian; Spatial analysis; Gaussian noise; Algorithm; Statistics","authors":[{"name":"Hui Zhang","is_ca":true},{"name":"Wen Tian","is_ca":false},{"name":"Yuhui Zheng","is_ca":false},{"name":"Danhua Xu","is_ca":false},{"name":"Dingcheng Wang","is_ca":false},{"name":"Thanh Minh Nguyen","is_ca":true},{"name":"Q. M. Jonathan Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01903520241589814,"gpt":0.250775791999037,"spread":0.2317405895831389,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001967272,0.00132085,0.001659995,0.001527314,0.0004881549,0.001573375,0.002697166,0.00280068,0.001480883],"category_scores_gemma":[0.004131232,0.001247587,0.002087627,0.001469651,0.0005933153,0.002282773,0.001624726,0.001834493,0.001284173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007797264,"about_ca_system_score_gemma":0.001235608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008861408,"about_ca_topic_score_gemma":0.01129677,"domain_scores_codex":[0.9991411,0.0002388349,0.00005901057,0.0001843399,0.0002812277,0.00009554203],"domain_scores_gemma":[0.998682,0.0005740947,0.00008484558,0.0001913612,0.0004007157,0.00006701303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009407505,0.0001850367,0.001080792,0.0002402229,0.0003942291,0.0001120493,0.0001700166,0.3610002,0.03611103,0.0113283,0.003839973,0.5845974],"study_design_scores_gemma":[0.000006778101,0.00002001026,0.000182927,0.00000450845,0.00002813799,0.00003291252,0.000005684857,0.9943455,0.003111231,0.001583348,0.0006602164,0.00001871797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004268427,0.0003721849,0.9944596,0.00007549419,0.00004794069,0.00001851224,0.00003529175,0.0005184498,0.0002040629],"genre_scores_gemma":[0.1515215,0.0007354392,0.8424776,0.0001596849,0.0001061138,0.0001091029,0.0004598727,0.0005106404,0.00391991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008861408,"threshold_uncertainty_score":0.01761967,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2064553809","doi":"10.1007/s11265-011-0630-x","title":"A Filter Bank Based Approach for Rotation Invariant Fingerprint Recognition","year":2011,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Principal component analysis; Thresholding; Gabor filter; Computer science; Fingerprint (computing); Linear discriminant analysis; Dimensionality reduction; Filter bank; Filter (signal processing); Computer vision; Invariant (physics); Curse of dimensionality; Feature extraction; Mathematics; Image (mathematics)","authors":[{"name":"Muhammad Ibrahim","is_ca":true},{"name":"Yongjin Wang","is_ca":false},{"name":"Ling Guan","is_ca":true},{"name":"A.N. Venetsanopoulos","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1045631969782427,"gpt":0.2586738773583835,"spread":0.1541106803801408,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003335391,0.0005343665,0.0007491297,0.0009963984,0.0003951561,0.0008686408,0.000705733,0.0009420656,0.005860878],"category_scores_gemma":[0.0006314546,0.0003801209,0.0007539202,0.0007914052,0.0002416638,0.0007585822,0.0004296049,0.0006225414,0.004371295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002549007,"about_ca_system_score_gemma":0.0005221561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0021418,"about_ca_topic_score_gemma":0.003506876,"domain_scores_codex":[0.99965,0.00004228003,0.00002230048,0.00006885665,0.0001788738,0.00003770889],"domain_scores_gemma":[0.9997004,0.00006240103,0.00001723581,0.00006450329,0.0001402527,0.00001512976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002388046,0.0001713633,0.0004188633,0.0001161661,0.0001080686,0.000154258,0.00003229847,0.00955304,0.2979491,0.003524643,0.003367864,0.6843656],"study_design_scores_gemma":[0.00005561028,0.0006349104,0.005209208,0.000050881,0.0003210939,0.00162925,0.00005934737,0.7224721,0.2386418,0.002841206,0.02797678,0.000107745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006682633,0.000561376,0.9897838,0.00007013471,0.0001755879,0.00005284598,0.00008163764,0.00100388,0.001588022],"genre_scores_gemma":[0.1069791,0.00146106,0.8713279,0.0002492933,0.0002228362,0.0001356447,0.0005037712,0.0001294044,0.01899094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005860878,"threshold_uncertainty_score":0.01960653,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1991931032","doi":"10.1007/s11265-008-0230-6","title":"High Acceleration for Video Processing Applications Using Specialized Instruction Set Based on Parallelism and Data Reuse","year":2008,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Computer science; Parallel computing; Reuse; Acceleration; Cache; Leverage (statistics); Computation; Embedding; Block (permutation group theory); Frame rate; Set (abstract data type); Key (lock); Computer engineering; Matching (statistics); Algorithm; Artificial intelligence","authors":[{"name":"Nicolas Beucher","is_ca":true},{"name":"Normand Bélanger","is_ca":true},{"name":"Yvon Savaria","is_ca":true},{"name":"Guy Bois","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1299940746679136,"gpt":0.327400257089322,"spread":0.1974061824214084,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001824817,0.0005385443,0.0004056385,0.0007745543,0.0003882556,0.0004871782,0.0008863123,0.0003187131,0.005541633],"category_scores_gemma":[0.0005809637,0.0002649096,0.0002678186,0.001020023,0.0001880676,0.0007211455,0.0004493172,0.0006987297,0.0009229207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004079829,"about_ca_system_score_gemma":0.0005118169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009481451,"about_ca_topic_score_gemma":0.0022198,"domain_scores_codex":[0.9998266,0.00002032959,0.00001098714,0.00002398691,0.00007266452,0.0000454716],"domain_scores_gemma":[0.9995514,0.0001301591,0.00003397822,0.00009985784,0.000150232,0.00003443988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001599906,0.0004182279,0.004152272,0.0003362331,0.0001358634,0.0004679182,0.0002594635,0.02251837,0.5349567,0.02749129,0.01647505,0.3911887],"study_design_scores_gemma":[0.0002083094,0.001617108,0.00806738,0.00005925742,0.000189862,0.00081269,0.00008796711,0.5307078,0.4162183,0.01417052,0.02776923,0.00009166047],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4760287,0.003022363,0.4919864,0.0005131189,0.0002889191,0.000152831,0.0003180999,0.009588457,0.01810098],"genre_scores_gemma":[0.8577623,0.0004561361,0.130583,0.0001476361,0.00009785922,0.00008466296,0.000477742,0.0002712899,0.01011927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005541633,"threshold_uncertainty_score":0.01853859,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2025967251","doi":"10.1007/s11265-014-0886-z","title":"Algorithm and Architecture of Fully-Parallel Associative Memories Based on Sparse Clustered Networks","year":2014,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Network Packet Processing and Optimization","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Associative property; Field-programmable gate array; Content-addressable memory; Parallel computing; Artificial neural network; Architecture; Content-addressable storage; Computer architecture; Computer hardware; Artificial intelligence; Mathematics","authors":[{"name":"Hooman Jarollahi","is_ca":true},{"name":"Naoya Onizawa","is_ca":false},{"name":"Vincent Gripon","is_ca":false},{"name":"Warren J. Gross","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.00867406844215649,"gpt":0.2171119082575264,"spread":0.2084378398153699,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001529537,0.0002775672,0.0003046792,0.00033149,0.000444928,0.000441831,0.001259703,0.0004477467,0.003015976],"category_scores_gemma":[0.0004215313,0.0001775498,0.0002022623,0.0003912911,0.000200081,0.0005878438,0.0004254804,0.0003179516,0.0003931116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005193073,"about_ca_system_score_gemma":0.001003625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004038173,"about_ca_topic_score_gemma":0.007279957,"domain_scores_codex":[0.9999348,0.00001079933,0.000004492063,0.00001550339,0.00002246601,0.00001193027],"domain_scores_gemma":[0.9998595,0.0000269757,0.00001078705,0.00001864638,0.00007544138,0.000008640085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002557076,0.00008787913,0.001212788,0.0001735477,0.00007069534,0.00009591714,0.0000995986,0.7105182,0.01995068,0.03321225,0.005177896,0.2291448],"study_design_scores_gemma":[0.00001925968,0.00003532547,0.0001195175,0.00000476522,0.0000124836,0.00004055113,0.00001485545,0.9902845,0.003706704,0.004907191,0.0008494032,0.00000538102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06960386,0.0003015718,0.9204635,0.0002824319,0.00008089185,0.0001310015,0.0001359246,0.0009842989,0.00801647],"genre_scores_gemma":[0.5556983,0.0002429694,0.4365272,0.0001116693,0.00003498163,0.0002555983,0.0003056673,0.00006576732,0.006757789],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004038173,"threshold_uncertainty_score":0.0100894,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1983257031","doi":"10.1007/s11265-010-0525-2","title":"Interpolation-Free Fractional-Pixel Motion Estimation Algorithms with Efficient Hardware Implementation","year":2010,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary; IntelliView Technologies (Canada)","funders":"","keywords":"Algorithm; Computer science; Interpolation (computer graphics); Pixel; Block (permutation group theory); Hardware architecture; Motion estimation; Matching (statistics); Gate count; Software; Artificial intelligence; Computer hardware; Mathematics; Motion (physics)","authors":[{"name":"Mohammed S. Sayed","is_ca":false},{"name":"Wael Badawy","is_ca":true},{"name":"G.A. Jullien","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01224575015808283,"gpt":0.3032052656120817,"spread":0.2909595154539989,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000449906,0.0009969852,0.0007360767,0.001027414,0.0007251031,0.0009054884,0.001327232,0.0009273855,0.008925241],"category_scores_gemma":[0.002471461,0.0005288586,0.0004991676,0.001164387,0.0003067852,0.001240563,0.0009030917,0.0008729858,0.003155974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000501271,"about_ca_system_score_gemma":0.001099698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003229025,"about_ca_topic_score_gemma":0.006692981,"domain_scores_codex":[0.9996085,0.00006600206,0.00002914785,0.00005381241,0.0001926503,0.00004984729],"domain_scores_gemma":[0.9991292,0.0003369982,0.00006882655,0.0002096899,0.0002227275,0.00003254412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007071134,0.0001249104,0.0005901818,0.0001668308,0.0000667116,0.00009830661,0.0001345939,0.02381845,0.07071397,0.01288175,0.004560652,0.8861365],"study_design_scores_gemma":[0.0001739426,0.0002722811,0.00134977,0.00004726872,0.0000900821,0.00050401,0.00006498129,0.8480287,0.1206219,0.01017767,0.01859492,0.00007450128],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007703262,0.0002241462,0.9890347,0.0000842536,0.00005046418,0.00003405449,0.00005174769,0.001595817,0.001221523],"genre_scores_gemma":[0.06826215,0.000138663,0.9289937,0.00004638812,0.00003925249,0.00008174909,0.0001782692,0.00009907416,0.002160679],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008925241,"threshold_uncertainty_score":0.02985787,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2947592526","doi":"10.1007/s11265-019-01453-w","title":"POLYBiNN: Binary Inference Engine for Neural Networks using Decision Trees","year":2019,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; MNIST database; Convolutional neural network; Field-programmable gate array; Inference; Artificial intelligence; Machine learning; Artificial neural network; Inference engine; Deep learning; Computer engineering; Embedded system","authors":[{"name":"Ahmed M. Abdelsalam","is_ca":true},{"name":"Ahmed H. Elsheikh","is_ca":true},{"name":"Sivakumar Chidambaram","is_ca":true},{"name":"Jean‐Pierre David","is_ca":true},{"name":"J. M. Pierre Langlois","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02894082419403868,"gpt":0.300909515127282,"spread":0.2719686909332433,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002615624,0.001212097,0.001615572,0.001306869,0.0008622044,0.002076431,0.003339998,0.001754972,0.02236783],"category_scores_gemma":[0.008734837,0.001355717,0.001343681,0.001715132,0.0006103846,0.003368092,0.00185261,0.00361339,0.007960944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001149143,"about_ca_system_score_gemma":0.002102048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009297855,"about_ca_topic_score_gemma":0.01375732,"domain_scores_codex":[0.9989359,0.0002754231,0.0001271054,0.0002691427,0.000306551,0.0000860213],"domain_scores_gemma":[0.9978423,0.001161441,0.0001076892,0.0003237294,0.0004679346,0.00009691786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00153916,0.0003260227,0.001463209,0.0007960678,0.000391814,0.000172339,0.0001111193,0.1313852,0.00538275,0.03231944,0.05417184,0.771941],"study_design_scores_gemma":[0.00008724257,0.00004175153,0.0002051446,0.00004870487,0.00003996649,0.00003810896,0.0000104116,0.9592248,0.005432772,0.02799296,0.006856767,0.00002142263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002231232,0.0003380636,0.9817931,0.0001213308,0.0001599002,0.00007460907,0.0008708209,0.01338929,0.001021671],"genre_scores_gemma":[0.05714193,0.0003334348,0.9311979,0.0003352569,0.00009079486,0.0003765346,0.002995621,0.002144498,0.005383986],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02236783,"threshold_uncertainty_score":0.07482785,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2008272790","doi":"10.1007/s11265-014-0894-z","title":"Design and Implementation of a Power-aware FFT Core for OFDM-based DSA-enabled Cognitive Radios","year":2014,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Fast Fourier transform; Overhead (engineering); Computer science; Pruning; Node (physics); Cognitive radio; Orthogonal frequency-division multiplexing; Embedded system; Algorithm; Telecommunications; Engineering; Wireless; Channel (broadcasting)","authors":[{"name":"Roberto Airoldi","is_ca":false},{"name":"Fabio Campi","is_ca":true},{"name":"Manuele Cucchi","is_ca":false},{"name":"Deepak Revanna","is_ca":false},{"name":"Omer Anjum","is_ca":false},{"name":"Jari Nurmi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02402322601779646,"gpt":0.2834458679348129,"spread":0.2594226419170165,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002869993,0.0005406167,0.0004151341,0.0005380579,0.0004153025,0.0008407843,0.00148416,0.0003970832,0.00351997],"category_scores_gemma":[0.0007398651,0.0002763828,0.0002706035,0.0002538844,0.0002169735,0.0005789897,0.0004532239,0.0006071473,0.001041448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005212498,"about_ca_system_score_gemma":0.001049769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001746549,"about_ca_topic_score_gemma":0.00278515,"domain_scores_codex":[0.9997227,0.00002417696,0.00002343206,0.00006072929,0.0001077276,0.00006118797],"domain_scores_gemma":[0.9995503,0.00009496097,0.00004420519,0.00006232718,0.0002003921,0.00004782511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009590706,0.0005849557,0.003531573,0.0004209514,0.0002033941,0.0005860378,0.0003834631,0.04676039,0.5107832,0.01292061,0.009592017,0.4132744],"study_design_scores_gemma":[0.0001576308,0.0008187894,0.002023453,0.00004343391,0.0001275015,0.0006973679,0.00008054694,0.6820797,0.2880788,0.002329947,0.02351223,0.0000505794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07759475,0.0005126137,0.9088607,0.0002158005,0.0002471543,0.000202139,0.0001294106,0.004497839,0.007739639],"genre_scores_gemma":[0.7286377,0.0001395171,0.2659591,0.0002128198,0.00006230204,0.0001138177,0.0001759283,0.0001678293,0.004531071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00351997,"threshold_uncertainty_score":0.01177549,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2744617995","doi":"10.1007/s11265-017-1270-6","title":"Efficient Computation of the 8-point DCT via Summation by Parts","year":2017,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Virtual Materials Group (Canada); University of Calgary","funders":"","keywords":"Discrete cosine transform; Computation; Multiplicative function; SIGNAL (programming language); Matrix (chemical analysis); Transformation matrix; Transformation (genetics); Computational complexity theory; Harmonic","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.02877108645130621,"gpt":0.2812319284293984,"spread":0.2524608419780922,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003786635,0.00109401,0.0008524952,0.0008569775,0.000441702,0.001131013,0.0006101202,0.0004767097,0.01187086],"category_scores_gemma":[0.001748438,0.000377702,0.0005373404,0.0009366348,0.0002843419,0.0009710898,0.0007204957,0.0007460439,0.004765386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004244563,"about_ca_system_score_gemma":0.001212885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001776354,"about_ca_topic_score_gemma":0.004973477,"domain_scores_codex":[0.9995252,0.00006281721,0.00003234453,0.00004556779,0.0002816767,0.00005242876],"domain_scores_gemma":[0.9995,0.0002191899,0.00002805792,0.00009593779,0.0001337861,0.00002297598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005806697,0.0001036665,0.000677038,0.0002703265,0.00009965115,0.0004033678,0.000178336,0.03885077,0.1354135,0.02863412,0.009843728,0.7849448],"study_design_scores_gemma":[0.0001331015,0.0002659161,0.001279401,0.00006437484,0.00009833643,0.0008654717,0.00009410032,0.8066673,0.1465981,0.01890309,0.02497712,0.00005369847],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01471656,0.0003541094,0.9777803,0.0001145637,0.00009951063,0.00005630549,0.0001426281,0.001921317,0.004814753],"genre_scores_gemma":[0.1550256,0.0003935851,0.832839,0.0001093104,0.0001088174,0.0001379974,0.000704491,0.0003736455,0.01030755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01187086,"threshold_uncertainty_score":0.03971201,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4207078582","doi":"10.1007/s11265-021-01731-6","title":"Convolutional Fully-Connected Capsule Network (CFC-CapsNet): A Novel and Fast Capsule Network","year":2022,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Capsule; Convolutional neural network; Computer science; Artificial intelligence; Pattern recognition (psychology); Computer vision; Biology; Botany","authors":[{"name":"Pouya Shiri","is_ca":true},{"name":"Amirali Baniasadi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01686474437523127,"gpt":0.2339002047921497,"spread":0.2170354604169184,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006088214,0.001347234,0.0007621828,0.0006945616,0.0004397402,0.0008078215,0.002573258,0.001232831,0.00379029],"category_scores_gemma":[0.001978388,0.0004289796,0.0005277809,0.001006593,0.0006485386,0.001895476,0.001712707,0.001449142,0.001457631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007396653,"about_ca_system_score_gemma":0.001960793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01225511,"about_ca_topic_score_gemma":0.0191259,"domain_scores_codex":[0.9996496,0.00005042252,0.00001393573,0.0001051136,0.0001111356,0.00006966649],"domain_scores_gemma":[0.9993705,0.0001307935,0.00005769093,0.0001336492,0.0002108189,0.0000965084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001010758,0.0003259158,0.002790128,0.0002975199,0.0002319553,0.0004286502,0.00006623314,0.2148666,0.02630972,0.01628189,0.05528203,0.6821087],"study_design_scores_gemma":[0.00002275881,0.0001173633,0.0004023088,0.00001308123,0.0000318915,0.00008883928,0.00001159212,0.9845033,0.007311554,0.003077009,0.00440015,0.00002010585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05383971,0.001785986,0.926239,0.0006831132,0.0005179474,0.0001490864,0.001591656,0.007354536,0.007839098],"genre_scores_gemma":[0.6448466,0.001410446,0.3233528,0.00097774,0.0003151374,0.0002647818,0.008891776,0.0007066132,0.01923404],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01225511,"threshold_uncertainty_score":0.02436751,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1997564856","doi":"10.1007/s11265-011-0635-5","title":"An Efficient Block Entropy Based Compression Scheme for Systems-on-a-Chip Test Data","year":2011,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Positive Living North; University of Northern British Columbia","funders":"","keywords":"Computer science; Very-large-scale integration; Data compression; Test vector; Chip; Compression ratio; Entropy (arrow of time); Scheme (mathematics); Test data; Algorithm; Block (permutation group theory); Computer engineering; Embedded system; Mathematics; Artificial intelligence; Engineering; Test set","authors":[{"name":"Saif Zahir","is_ca":true},{"name":"Arber Borici","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09692173878471042,"gpt":0.2912436106994541,"spread":0.1943218719147437,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004391862,0.0005752229,0.0005057597,0.0008586089,0.000340846,0.0005306008,0.0005909731,0.0004726717,0.002389445],"category_scores_gemma":[0.001670124,0.0001681495,0.0002508924,0.0007414388,0.0002819884,0.0007792068,0.0008050002,0.0004925458,0.000577566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003242973,"about_ca_system_score_gemma":0.0005635367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006714032,"about_ca_topic_score_gemma":0.001531571,"domain_scores_codex":[0.999453,0.0001014345,0.00003618284,0.00004644147,0.0003108144,0.00005206459],"domain_scores_gemma":[0.9991154,0.0003630125,0.00007799996,0.0002276806,0.0001791514,0.00003677797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001081346,0.0001680836,0.0009043758,0.0001460901,0.00006585318,0.000251383,0.00008435331,0.04049152,0.2154745,0.01274351,0.004147782,0.7244411],"study_design_scores_gemma":[0.00008131261,0.0004527268,0.001691523,0.00003189113,0.00006523994,0.000655605,0.00002521581,0.807693,0.1794118,0.004569871,0.005284579,0.00003720967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06909032,0.0007941872,0.924997,0.0002600368,0.0001675563,0.0001696602,0.0002611362,0.001460073,0.002800071],"genre_scores_gemma":[0.6223474,0.0004049426,0.3711912,0.0002633347,0.0001932431,0.0001679514,0.0008030966,0.00009762076,0.004531245],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002389445,"threshold_uncertainty_score":0.00799346,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1967444872","doi":"10.1007/s11265-013-0795-6","title":"Area Efficient Sequential Decimal Fixed-point Multiplier","year":2013,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"University of Saskatchewan","keywords":"Adder; Decimal; Arithmetic; Multiplier (economics); Operand; Computer science; Computation; Mathematics; Parallel computing; Algorithm; Latency (audio); Computer hardware; Telecommunications","authors":[{"name":"Amir Kaivani","is_ca":true},{"name":"Seok‐Bum Ko","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02584134055562441,"gpt":0.2712819439382788,"spread":0.2454406033826544,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003169674,0.0009582671,0.0005580314,0.0008454436,0.0006030471,0.0009764554,0.0009613833,0.0003994771,0.01376994],"category_scores_gemma":[0.001196161,0.000221447,0.0003064566,0.001138228,0.00033551,0.001087946,0.0009271677,0.0005787408,0.003260967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005479152,"about_ca_system_score_gemma":0.00100422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008552219,"about_ca_topic_score_gemma":0.002164616,"domain_scores_codex":[0.9996449,0.00006405637,0.00002888145,0.00008207231,0.0001188177,0.00006130575],"domain_scores_gemma":[0.9996033,0.0001018975,0.00002934201,0.00009751446,0.0001487682,0.00001923124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001625707,0.0001333075,0.0005877741,0.0003871687,0.00008041294,0.0003028383,0.0001280079,0.02941644,0.07747202,0.07900013,0.02139749,0.7894687],"study_design_scores_gemma":[0.0005732414,0.00156082,0.001624169,0.0002304879,0.000268327,0.0021931,0.0002081736,0.4813417,0.2180917,0.1554356,0.1383461,0.0001265272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05134216,0.0018353,0.9103951,0.0005065024,0.0005454374,0.0001017431,0.00032697,0.002408567,0.03253818],"genre_scores_gemma":[0.4193214,0.0008586308,0.5463157,0.0003873409,0.0002482171,0.0001822649,0.000500833,0.0001911171,0.03199449],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01376994,"threshold_uncertainty_score":0.04606497,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3210268934","doi":"10.1007/s11265-021-01707-6","title":"Bilateral Filters with Adaptive Generalized Kernels Generated via Riemann-Lebesgue Theorem","year":2021,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Mathematics; Bilateral filter; Upsampling; Gaussian; Lebesgue integration; Adaptive filter; Filter (signal processing); Artificial intelligence; JPEG; Noise reduction; Pattern recognition (psychology); Algorithm; Computer vision; Computer science; Pixel; Image (mathematics); Pure mathematics; Data compression","authors":[{"name":"M. H. Annaby","is_ca":false},{"name":"Ebrahim A. Nehary","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02525561520820731,"gpt":0.2605640449131329,"spread":0.2353084297049256,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007906973,0.0006025847,0.0006775477,0.0005909954,0.0002799063,0.0008787471,0.000714669,0.001198794,0.001686124],"category_scores_gemma":[0.002217694,0.0002928662,0.0009670141,0.0006878734,0.0006859668,0.001347378,0.001022313,0.00116128,0.0005025795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004463326,"about_ca_system_score_gemma":0.0005431934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008281522,"about_ca_topic_score_gemma":0.000848415,"domain_scores_codex":[0.9996012,0.0001165945,0.0000184946,0.0000793428,0.0001452463,0.00003916783],"domain_scores_gemma":[0.9993512,0.0002245925,0.00008367172,0.0001029399,0.000196584,0.00004104365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000360338,0.00009914934,0.001152292,0.0002503959,0.0001718347,0.0002991446,0.0002356467,0.1578382,0.1135054,0.5089792,0.002354186,0.2147542],"study_design_scores_gemma":[0.00002789407,0.00004845642,0.000319565,0.000009467634,0.00002742965,0.000183121,0.0000159244,0.9328827,0.009764728,0.05474168,0.001952964,0.00002614237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007948047,0.00007653581,0.9911228,0.00004700845,0.0000195818,0.000007861753,0.00001187328,0.00005691679,0.000709378],"genre_scores_gemma":[0.3743837,0.0005844726,0.6174766,0.0001354081,0.0001007063,0.00009701936,0.0001324612,0.0001502174,0.006939469],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001686124,"threshold_uncertainty_score":0.005640626,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3198896842","doi":"10.1007/s11265-022-01752-9","title":"Online Dynamic Window (ODW) Assisted Two-Stage LSTM Frameworks For Indoor Localization","year":2022,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Inertial measurement unit; Context (archaeology); Artificial intelligence; Window (computing); Heading (navigation); Field (mathematics); Sliding window protocol; Real-time computing; Engineering","authors":[{"name":"Mohammadamin Atashi","is_ca":true},{"name":"Mohammad Salimibeni","is_ca":true},{"name":"Arash Mohammadi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01358725443114948,"gpt":0.2600478559222237,"spread":0.2464606014910743,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003711515,0.001064431,0.0007814725,0.0004070247,0.0002466057,0.0006422239,0.001479717,0.001000285,0.005437325],"category_scores_gemma":[0.001002964,0.0003876075,0.0005719158,0.0007300284,0.000214287,0.001546462,0.001190847,0.001385308,0.002134667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002868169,"about_ca_system_score_gemma":0.000820588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005880246,"about_ca_topic_score_gemma":0.01175288,"domain_scores_codex":[0.9997614,0.0000413817,0.00001392257,0.00007131472,0.00005776261,0.00005416606],"domain_scores_gemma":[0.9997694,0.00007483157,0.00001591676,0.00004004612,0.00008386846,0.00001585955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003821161,0.0001397806,0.0004117281,0.0001981064,0.00009066548,0.0001353253,0.0001033638,0.1267981,0.03396524,0.005160528,0.008666204,0.8239489],"study_design_scores_gemma":[0.000009711381,0.00004382085,0.0001545468,0.00001116424,0.00001831544,0.00003729558,0.00001985695,0.9895432,0.006086685,0.002365055,0.001699701,0.00001069219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008640015,0.0005334561,0.9863704,0.0001117661,0.0001398543,0.00001744827,0.0002198461,0.002677175,0.001289894],"genre_scores_gemma":[0.5092661,0.0009360197,0.4765105,0.000367746,0.0002037647,0.0001565043,0.0013677,0.0005825346,0.01060909],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005880246,"threshold_uncertainty_score":0.01818961,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1992374598","doi":"10.1007/s11265-008-0234-2","title":"Adaptive Duplicated Filters and Interference Canceller for DS-CDMA Systems","year":2008,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Payload (computing); Interference (communication); Block (permutation group theory); Multiuser detection; Code division multiple access; Context (archaeology); Telecommunications link; Reduction (mathematics); Throughput; Field-programmable gate array; Adaptive filter; Real-time computing; Electronic engineering; Computer hardware; Algorithm; Computer network; Telecommunications; Network packet; Engineering; Mathematics; Wireless","authors":[{"name":"François Nougarou","is_ca":true},{"name":"Daniel Massicotte","is_ca":true},{"name":"Messaoud Ahmed-Ouameur","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07510501831272712,"gpt":0.2903061565355309,"spread":0.2152011382228038,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003275047,0.0003112591,0.000217868,0.0003255249,0.0001918388,0.0004753293,0.0004794807,0.0004430395,0.001289206],"category_scores_gemma":[0.000720277,0.0001527271,0.0001752108,0.000287868,0.0002706579,0.0003044803,0.0002080523,0.0003304487,0.0002948758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000515833,"about_ca_system_score_gemma":0.0005736475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001075097,"about_ca_topic_score_gemma":0.00268641,"domain_scores_codex":[0.999718,0.00009044843,0.00001019795,0.00003108622,0.0001306884,0.0000194464],"domain_scores_gemma":[0.9998094,0.00009596594,0.0000240158,0.00002233618,0.00004105479,0.000007360957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005202979,0.00007004516,0.001406666,0.0003820461,0.0001103182,0.0004015477,0.0001399853,0.1590729,0.3085275,0.08106887,0.002002443,0.4462974],"study_design_scores_gemma":[0.00007312543,0.0004624513,0.0009610534,0.00002840121,0.0000878716,0.0004986358,0.00002482526,0.8597487,0.1136425,0.008715724,0.01571153,0.00004524045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02630943,0.00100507,0.9702027,0.0001008833,0.00003986718,0.00002776508,0.00002545696,0.0002464087,0.002042435],"genre_scores_gemma":[0.4566554,0.001073104,0.5350732,0.00008946801,0.00008766787,0.00007169429,0.00006538394,0.00002127209,0.006862809],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001289206,"threshold_uncertainty_score":0.004312873,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2068523583","doi":"10.1007/s11265-009-0374-z","title":"Feature Fusion Applied to Missing Data ASR with the Combination of Recognizers","year":2009,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Speech recognition; Computer science; Pattern recognition (psychology); Noise (video); Mel-frequency cepstrum; Artificial intelligence; Feature (linguistics); Cepstrum; Fusion; Process (computing); Hidden Markov model; Feature extraction","authors":[{"name":"Neil Joshi","is_ca":true},{"name":"Ling Guan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02352298276305343,"gpt":0.2572750499648186,"spread":0.2337520672017652,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001711537,0.0009669592,0.001440162,0.0009271645,0.0004123698,0.000983663,0.0007929099,0.0009329129,0.001858447],"category_scores_gemma":[0.003426327,0.0005002047,0.00102591,0.0008925144,0.0003822515,0.001429677,0.0009875022,0.001120823,0.001246049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002474572,"about_ca_system_score_gemma":0.0005315664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009176364,"about_ca_topic_score_gemma":0.001225503,"domain_scores_codex":[0.9985978,0.0003104373,0.0001114324,0.0003038778,0.0005418928,0.0001345948],"domain_scores_gemma":[0.9986797,0.0003770787,0.00009124701,0.0002994495,0.0005048164,0.00004781464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001347199,0.0001824305,0.001787421,0.0002474596,0.0002056807,0.0002655505,0.0001645437,0.03084158,0.2003834,0.002374995,0.002107751,0.760092],"study_design_scores_gemma":[0.00005996661,0.0006011821,0.004793031,0.00004410067,0.0002805353,0.0009630585,0.00006567535,0.8173244,0.1651947,0.004242208,0.006332269,0.00009893662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03333435,0.0005327995,0.9635723,0.000124527,0.0002101432,0.00004240213,0.0001280254,0.001269044,0.0007862921],"genre_scores_gemma":[0.521741,0.0004582867,0.474403,0.0001265099,0.0001533371,0.0001008971,0.0004643468,0.0001270537,0.002425612],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001858447,"threshold_uncertainty_score":0.009051561,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2997794147","doi":"10.1007/s11265-019-01506-0","title":"An Efficient Software List Sphere Decoder for Polar Codes","year":2020,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Soft-decision decoder; Computer science; Decoding methods; Algorithm; Software; Sorting; Theoretical computer science","authors":[{"name":"Huayi Zhou","is_ca":false},{"name":"Yuxiang Fu","is_ca":false},{"name":"Zaichen Zhang","is_ca":false},{"name":"Warren J. Gross","is_ca":true},{"name":"Xiaohu You","is_ca":false},{"name":"Chuan Zhang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02917613368098362,"gpt":0.2882462562259795,"spread":0.259070122544996,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004708011,0.0008933469,0.0008338077,0.000830669,0.0006371448,0.001437805,0.0007147882,0.0008364705,0.004542665],"category_scores_gemma":[0.001888012,0.0003592094,0.0003963335,0.001096065,0.000413569,0.0009214854,0.001778877,0.0008425657,0.004589254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000540609,"about_ca_system_score_gemma":0.00249623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002387485,"about_ca_topic_score_gemma":0.004360479,"domain_scores_codex":[0.9993148,0.0001635328,0.00004224808,0.00006345515,0.0003266863,0.00008928978],"domain_scores_gemma":[0.9989641,0.0003215491,0.00005772992,0.0001683974,0.0004301433,0.00005804464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001548541,0.0001786272,0.001563955,0.0004525591,0.00013033,0.0007108155,0.0002861616,0.1126843,0.1208702,0.1183876,0.02579593,0.617391],"study_design_scores_gemma":[0.0001344215,0.0003339529,0.0004154444,0.0000807973,0.00006293561,0.0007916735,0.00007315644,0.831873,0.1138555,0.02888364,0.02341787,0.0000776423],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01648255,0.0003964905,0.973056,0.0003190944,0.000180448,0.00006754999,0.0003289939,0.003147773,0.006021128],"genre_scores_gemma":[0.2632999,0.0007884119,0.7170093,0.0004447532,0.0002068594,0.000158818,0.001292551,0.0004880288,0.01631144],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004542665,"threshold_uncertainty_score":0.0151968,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2059340091","doi":"10.1007/s11265-010-0458-9","title":"Low Complexity Reconfigurable DSP Circuit Implementations Based on Common Sub-expression Elimination","year":2010,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University; Communications Research Centre Canada","funders":"","keywords":"Multiplier (economics); Operand; Computer science; Field-programmable gate array; Digital signal processing; Adder; Electronic circuit; Arithmetic; Booth's multiplication algorithm; Circuit design; Computer hardware; Parallel computing; Algorithm; Mathematics; Embedded system; Engineering","authors":[{"name":"H. Ho","is_ca":true},{"name":"V. Szwarc","is_ca":true},{"name":"T. Kwaśniewski","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04485017147096986,"gpt":0.2844201616064039,"spread":0.239569990135434,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001995511,0.0007703992,0.0004172316,0.0007130002,0.0004065588,0.0008871931,0.001328409,0.0003444602,0.005732913],"category_scores_gemma":[0.000586357,0.0002639063,0.0003802838,0.0006616946,0.0002375732,0.0006533135,0.0004241643,0.0005352502,0.001293772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003661606,"about_ca_system_score_gemma":0.0004990398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007751842,"about_ca_topic_score_gemma":0.002355028,"domain_scores_codex":[0.9996876,0.00005887253,0.0000249482,0.00005333354,0.0001111164,0.0000642364],"domain_scores_gemma":[0.9996328,0.0001260472,0.00005102518,0.0001042459,0.00006843595,0.00001743956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00112764,0.0002452941,0.0008546708,0.0002551377,0.000117353,0.000436738,0.0001577135,0.01710721,0.3718682,0.03383129,0.003264927,0.5707337],"study_design_scores_gemma":[0.000467633,0.001837927,0.002448904,0.0001067055,0.0004007468,0.00197478,0.0001309791,0.4120599,0.5336289,0.01683797,0.02999257,0.0001128993],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2430523,0.0008887031,0.7309692,0.0001969856,0.0001968834,0.0001450511,0.0001741896,0.004759878,0.01961686],"genre_scores_gemma":[0.7231498,0.0002131658,0.2669292,0.0001880106,0.00006625408,0.00007931134,0.0003039106,0.0002235898,0.008846815],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005732913,"threshold_uncertainty_score":0.01917857,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2126177875","doi":"10.1007/s11265-010-0562-x","title":"Rapid Synthesis and Simulation of Computational Circuits in an MPPA","year":2010,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Speedup; Computer science; Field-programmable gate array; Scalability; Electronic circuit; Routing (electronic design automation); Massively parallel; Parallel computing; Computer architecture; Range (aeronautics); Software; Design flow; Computer hardware; Computer engineering; Embedded system; Engineering","authors":[{"name":"David Grant","is_ca":true},{"name":"G. Smecher","is_ca":true},{"name":"Guy Lemieux","is_ca":true},{"name":"Rosemary Francis","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0305049917562528,"gpt":0.2891286780724233,"spread":0.2586236863161704,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002690671,0.0004176208,0.0003648235,0.0002459651,0.0003431923,0.0004663161,0.0007259789,0.0005654347,0.004503461],"category_scores_gemma":[0.001213152,0.0002836234,0.0003296853,0.0001873887,0.0004329433,0.0004764509,0.0003949561,0.0005651814,0.0003852717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003875611,"about_ca_system_score_gemma":0.0005823791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001832638,"about_ca_topic_score_gemma":0.002287834,"domain_scores_codex":[0.9998541,0.00004442083,0.000004745167,0.00001907821,0.00005879503,0.00001882161],"domain_scores_gemma":[0.999546,0.0002905153,0.00002487872,0.00006732421,0.00005851399,0.00001267389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001131106,0.00003894754,0.0003442792,0.00007504957,0.0000177723,0.00009404084,0.00007204244,0.9381173,0.01182622,0.03083584,0.0006712293,0.01779415],"study_design_scores_gemma":[0.00001470923,0.0000205272,0.00003808856,0.000003057195,0.000003345877,0.00001118691,0.000005885395,0.9921108,0.003332771,0.003618998,0.000838442,0.000002270468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1646563,0.0001835196,0.8129747,0.0002620173,0.0001045179,0.0001111157,0.0001769921,0.002203401,0.01932747],"genre_scores_gemma":[0.8178568,0.00009899228,0.1778926,0.00006921679,0.00001819959,0.0001605999,0.0001000638,0.000153563,0.003649904],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004503461,"threshold_uncertainty_score":0.01506555,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4409461316","doi":"10.1007/s11265-025-01949-8","title":"Generalized Restart Mechanism for Successive-Cancellation Flip Decoding of Polar Codes","year":2025,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Decoding methods; Mechanism (biology); Computer science; Polar; Algorithm; Speech recognition; Mathematics; Physics","authors":[{"name":"Ilshat Sagitov","is_ca":true},{"name":"Charles Pillet","is_ca":true},{"name":"Alexios Balatsoukas‐Stimming","is_ca":false},{"name":"Pascal Giard","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02538687802069558,"gpt":0.3018626466170238,"spread":0.2764757685963283,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001200753,0.0008066258,0.0008368599,0.0008860176,0.001068315,0.001877109,0.001429109,0.0016669,0.004841755],"category_scores_gemma":[0.003234413,0.0003310125,0.0006847545,0.0008821062,0.001270317,0.001411456,0.001738095,0.001242653,0.001319895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005079199,"about_ca_system_score_gemma":0.00120759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004568885,"about_ca_topic_score_gemma":0.0005062516,"domain_scores_codex":[0.9989937,0.0003304578,0.00005777685,0.0001398889,0.0003004351,0.0001777332],"domain_scores_gemma":[0.9981717,0.0006072064,0.0001655477,0.0006305774,0.0003624066,0.00006259744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000660895,0.00007939446,0.0004132873,0.0002149349,0.00006990991,0.0004998202,0.0002510949,0.04169386,0.04843435,0.841468,0.002740191,0.06347436],"study_design_scores_gemma":[0.0001320649,0.0002374722,0.0003321261,0.00009378534,0.00007082354,0.0008106756,0.00007842929,0.5317101,0.07605968,0.381848,0.008476493,0.0001502916],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07088744,0.0007492289,0.9092526,0.0004359682,0.0003603417,0.0001339417,0.0001545083,0.0007132547,0.01731268],"genre_scores_gemma":[0.8474107,0.0007610384,0.1351967,0.0004465182,0.0001831722,0.0001845808,0.0002242,0.0001931815,0.01539985],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004841755,"threshold_uncertainty_score":0.01619726,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2260407357","doi":"10.1007/s11265-015-1064-7","title":"On the Traffic Offloading in Wi-Fi Supported Heterogeneous Wireless Networks","year":2015,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"National Science Foundation","keywords":"Macrocell; Computer network; Computer science; Heterogeneous network; Small cell; Cellular network; Femtocell; Wireless network; Context (archaeology); Wireless; Telecommunications; Base station; Geography","authors":[{"name":"Ali Rıza Ekti","is_ca":false},{"name":"Muhammad Zeeshan Shakir","is_ca":true},{"name":"Erchin Serpedin","is_ca":false},{"name":"Khalid Qaraqe","is_ca":false},{"name":"Muhammad Ali Imran","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01955168446168878,"gpt":0.2273930385941686,"spread":0.2078413541324798,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008538804,0.001165937,0.0009436179,0.0007247111,0.0007087367,0.001586552,0.0007548281,0.000679875,0.00334889],"category_scores_gemma":[0.005373179,0.0003406092,0.0004191785,0.001070188,0.0008764334,0.001668349,0.001028656,0.000910445,0.0003760631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008307932,"about_ca_system_score_gemma":0.0006645521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003442894,"about_ca_topic_score_gemma":0.003717759,"domain_scores_codex":[0.9993215,0.0002613737,0.00001875149,0.00006421049,0.0001960723,0.0001382063],"domain_scores_gemma":[0.9982727,0.001198515,0.00006400458,0.0001188852,0.0002807877,0.00006520479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006237621,0.0001422702,0.001320612,0.00027019,0.0000922515,0.0004108987,0.0001390039,0.7910733,0.01245005,0.08441392,0.007238194,0.1018257],"study_design_scores_gemma":[0.000004619573,0.00003588727,0.0004096757,0.00001792331,0.00002080295,0.0000468651,0.00004037786,0.9837875,0.0007658988,0.0140755,0.0007859992,0.000009032153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2725831,0.01165991,0.6444687,0.002888977,0.001547862,0.0001856991,0.0003392898,0.0002540304,0.06607243],"genre_scores_gemma":[0.9801523,0.003560449,0.009587517,0.0001775913,0.0006720675,0.00003271737,0.00008751089,0.00006830581,0.005661484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003442894,"threshold_uncertainty_score":0.01120317,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1986429310","doi":"10.1007/s11265-010-0540-3","title":"Automatic Detection of Object of Interest and Tracking in Active Video","year":2010,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Artificial intelligence; Computer science; Computer vision; Initialization; Video tracking; AdaBoost; Pattern recognition (psychology); Classifier (UML); Outlier; Salient; Object detection; Tracking (education); Object (grammar)","authors":[{"name":"Jiawei Huang","is_ca":true},{"name":"Ze-Nian Li","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03947942196863002,"gpt":0.3100770123080309,"spread":0.2705975903394008,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009059013,0.0004857271,0.0006998616,0.00180421,0.0003611405,0.001040291,0.001030165,0.001112648,0.0006495271],"category_scores_gemma":[0.00247981,0.0004308747,0.0004002368,0.000823815,0.000397519,0.0009681051,0.0006880981,0.000670757,0.0004555134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002449331,"about_ca_system_score_gemma":0.0003467625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001190006,"about_ca_topic_score_gemma":0.001768058,"domain_scores_codex":[0.9995455,0.0000612341,0.00002094334,0.000139205,0.0001665868,0.00006641177],"domain_scores_gemma":[0.9986985,0.0005946624,0.0001259438,0.0001418757,0.000349459,0.00008955433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000945268,0.0003170205,0.005240474,0.0001595741,0.0000766429,0.0002647725,0.0002131501,0.01085951,0.3162754,0.003743075,0.001507541,0.6603977],"study_design_scores_gemma":[0.00005109947,0.0003166114,0.01665091,0.00002933769,0.0001206434,0.001016169,0.00009908809,0.8028151,0.1724837,0.003283833,0.003095243,0.0000382062],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1487653,0.0007213942,0.8479865,0.00009241747,0.0001323577,0.00005463698,0.0001013472,0.0005925273,0.001553427],"genre_scores_gemma":[0.6905215,0.0005733122,0.3046601,0.0001124401,0.000124022,0.00006543626,0.0003393244,0.0001072379,0.003496743],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00180421,"threshold_uncertainty_score":0.004790902,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1975649745","doi":"10.1007/s11265-013-0788-5","title":"Performance Characterization of AES Datapath Architectures in 90-nm Standard Cell CMOS Technology","year":2013,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Datapath; Advanced Encryption Standard; Computer science; Standard cell; Parameterized complexity; CMOS; Throughput; Computer architecture; Efficient energy use; Embedded system; Parallel computing; Computer hardware; Cryptography; Integrated circuit; Algorithm; Electronic engineering; Engineering; Electrical engineering","authors":[{"name":"Cheng Wang","is_ca":true},{"name":"Howard M. Heys","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.009626717723937602,"gpt":0.2343084231876711,"spread":0.2246817054637335,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002570376,0.0004119343,0.0002585708,0.0007958516,0.0003050332,0.000568451,0.0006059339,0.0003904412,0.003270325],"category_scores_gemma":[0.001333073,0.0001534929,0.0001895205,0.0008018853,0.0001992274,0.0009851411,0.0001837627,0.0002282804,0.0006604727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007903776,"about_ca_system_score_gemma":0.0005701714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001502498,"about_ca_topic_score_gemma":0.002137253,"domain_scores_codex":[0.9995514,0.00005254,0.00003437406,0.00009248746,0.0001516882,0.000117556],"domain_scores_gemma":[0.9987127,0.0004849171,0.0002487561,0.0001122543,0.0003827302,0.00005865341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003396387,0.0005360579,0.02251793,0.0006732128,0.000237044,0.0008923674,0.0004883078,0.06282034,0.8255039,0.007902907,0.004913754,0.07011788],"study_design_scores_gemma":[0.000186275,0.006692874,0.02273185,0.0000924475,0.0002323598,0.001674246,0.0004009445,0.3122439,0.6430156,0.002204972,0.01044317,0.00008139997],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886206,0.0006377388,0.005305858,0.0001499966,0.00004015907,0.00004274866,0.0004980593,0.0003311175,0.004373767],"genre_scores_gemma":[0.9970115,0.000155316,0.001396495,0.00002390143,0.000009332712,0.00001533806,0.0002147103,0.00002457921,0.001148719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003270325,"threshold_uncertainty_score":0.01094031,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2549866851","doi":"10.1007/s11265-017-1225-y","title":"Using OpenCL to Increase SCA Application Portability","year":2017,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Nordion (Canada)","funders":"","keywords":"Software portability; Computer science; Software; Software-defined radio; Embedded system; Component (thermodynamics); Operating system; Computer architecture; Telecommunications","authors":[{"name":"Steve Bernier","is_ca":true},{"name":"François Lévesque","is_ca":true},{"name":"Martin Phisel","is_ca":true},{"name":"Dmitry Zvernik","is_ca":true},{"name":"David Hagood","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04308871623232419,"gpt":0.3210319964322574,"spread":0.2779432801999332,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001798828,0.001074051,0.0004909828,0.001601024,0.000679161,0.002089899,0.002394924,0.001022055,0.009854978],"category_scores_gemma":[0.01624353,0.0007001591,0.0006758493,0.0006763064,0.0006907267,0.004562777,0.00292621,0.002155142,0.001408309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006565637,"about_ca_system_score_gemma":0.000824923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001803559,"about_ca_topic_score_gemma":0.003192095,"domain_scores_codex":[0.9980234,0.0004896054,0.0001904491,0.000381506,0.0006529078,0.0002621408],"domain_scores_gemma":[0.9843061,0.004672763,0.0007412679,0.007276755,0.002601711,0.0004013955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001953192,0.001489974,0.0155525,0.0004558362,0.0002184889,0.001033808,0.0009025535,0.1558128,0.1792477,0.02335515,0.01186917,0.6081087],"study_design_scores_gemma":[0.000220211,0.0003800351,0.001678761,0.00006062687,0.0001275442,0.0002921298,0.00007550274,0.8694078,0.09845328,0.01932623,0.009915656,0.00006230167],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1979155,0.0002268916,0.7260334,0.0004881496,0.0002517338,0.000147964,0.000131384,0.06019688,0.01460812],"genre_scores_gemma":[0.8906813,0.0000568351,0.09873686,0.0002254288,0.0000589438,0.00007623247,0.0002311957,0.003912723,0.006020469],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009854978,"threshold_uncertainty_score":0.03296816,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2148632366","doi":"10.1007/s11265-013-0798-3","title":"Efficient Uniform Quantization Likelihood Evaluation for Particle Filters in Embedded Implementations","year":2013,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"Concordia University; Polytechnique Montréal","keywords":"Speedup; Quantization (signal processing); Computer science; Software; Algorithm; Software implementation; Particle filter; Floating point; Parallel computing; Computer engineering; Computer hardware; Artificial intelligence; Programming language; Kalman filter","authors":[{"name":"Qifeng Gan","is_ca":true},{"name":"J. M. Pierre Langlois","is_ca":true},{"name":"Yvon Savaria","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03492705843829245,"gpt":0.3081439200539794,"spread":0.273216861615687,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002111088,0.0007571768,0.0009403716,0.0006597127,0.00046286,0.001865453,0.001239514,0.001075967,0.007105348],"category_scores_gemma":[0.01170191,0.0006445537,0.0004619707,0.000902398,0.0006700174,0.00249475,0.00180416,0.001332125,0.001592007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009246931,"about_ca_system_score_gemma":0.001830366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004521796,"about_ca_topic_score_gemma":0.006198025,"domain_scores_codex":[0.9987129,0.0003733955,0.0001117115,0.0001247902,0.0005778372,0.00009952252],"domain_scores_gemma":[0.997366,0.001413686,0.0001092127,0.0003802226,0.0006545967,0.00007618912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007081271,0.0001545539,0.001209205,0.0002975281,0.00009894055,0.0001600328,0.000191225,0.3478752,0.01639451,0.0750149,0.006161439,0.5517344],"study_design_scores_gemma":[0.00003169518,0.00003789937,0.0001524631,0.00001194477,0.000008530511,0.00003420372,0.00001479184,0.9846058,0.004948647,0.009313888,0.0008290739,0.00001117514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004859672,0.000162839,0.9936643,0.00008111829,0.00002843146,0.0000219242,0.00002969741,0.0005322131,0.000619747],"genre_scores_gemma":[0.2311247,0.0002463757,0.7644196,0.00009861653,0.00005703917,0.000108355,0.0002780464,0.0003602322,0.003307089],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007105348,"threshold_uncertainty_score":0.02376974,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}