{"meta":{"query_hash":"3554c8011ca9","filters":{"venue":"EURASIP Journal on Advances in Signal Processing"},"cohort_total":192,"direct_labels_cover":0,"predictions_cover":192,"exported":192,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/3554c8011ca9","api":"https://metacan.xera.ac/api/v1/cohort?venue=EURASIP+Journal+on+Advances+in+Signal+Processing"},"results":[{"id":"W1498991127","doi":"10.1186/s13634-015-0238-6","title":"Speech recognition in reverberant and noisy environments employing multiple feature extractors and i-vector speaker adaptation","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Computer Research Institute of Montréal","funders":"","keywords":"Computer science; Speech recognition; Filter bank; Word error rate; Speaker recognition; Reverberation; Microphone; Channel (broadcasting); Word (group theory); Speech processing; Pattern recognition (psychology); Artificial intelligence; Mathematics","score_opus":0.03644563081396488,"score_gpt":0.27348327601168265,"score_spread":0.23703764519771778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1498991127","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43198216,0.0025864672,0.5394925,0.00038652442,0.00058803894,0.00046227046,0.0021292728,0.015889296,0.0064835567],"genre_scores_gemma":[0.59785986,0.001269991,0.37419838,0.00044263655,0.00019636334,0.00062712043,0.012141464,0.0010701672,0.012194012],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976544,0.0005225729,0.00014890614,0.0008060576,0.00067633664,0.00019172586],"domain_scores_gemma":[0.99840254,0.0005511906,0.00008324472,0.0004112603,0.00045406382,0.0000977511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021107371,0.0017709176,0.0018307039,0.0007970219,0.00060557364,0.0013136219,0.0011524146,0.0014416203,0.0030423095],"category_scores_gemma":[0.003857208,0.00040615338,0.0011359542,0.0006428552,0.00054416736,0.0019462189,0.0015959964,0.0013522189,0.0049487725],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019845718,0.0005914361,0.002233641,0.000709519,0.00041850365,0.0008065462,0.00045075177,0.02335169,0.35884252,0.00078788283,0.00802616,0.6017968],"study_design_scores_gemma":[0.00036109667,0.0030601996,0.024608715,0.00008588175,0.00035353054,0.0023921095,0.00063221954,0.37537733,0.57416415,0.0017845,0.016828636,0.0003515531],"about_ca_topic_score_codex":0.002999451,"about_ca_topic_score_gemma":0.00399123,"teacher_disagreement_score":0.0030423095,"about_ca_system_score_codex":0.000334277,"about_ca_system_score_gemma":0.0006359063,"threshold_uncertainty_score":0.011162758},"labels":[],"label_agreement":null},{"id":"W1585828867","doi":"10.1155/asp/2006/80941","title":"Joint Multiuser Detection and Optimal Spectrum Balancing for Digital Subscriber Lines","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Digital subscriber line; Asymmetric digital subscriber line; Computer science; Crosstalk; Electronic engineering; Frequency domain; Transmitter power output; Single antenna interference cancellation; Real-time computing; Algorithm; Telecommunications; Decoding methods; Engineering; Transmitter","score_opus":0.010636159706050531,"score_gpt":0.2460365345260804,"score_spread":0.23540037482002987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1585828867","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05716491,0.00030018698,0.94059193,0.00014081912,0.00001714002,0.000014910934,0.000017795744,0.000121820325,0.0016303778],"genre_scores_gemma":[0.8888691,0.00018499102,0.10926333,0.000060969247,0.000033894456,0.00003350552,0.000040169823,0.00003368805,0.0014804229],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998979,0.00049013866,0.00002867838,0.000113021575,0.00025103477,0.00013816851],"domain_scores_gemma":[0.9990853,0.0005615541,0.0001296494,0.00006341632,0.00010730196,0.000052744574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001025974,0.00067447685,0.0007004831,0.0004821814,0.00028483305,0.0007985777,0.00049225177,0.0005233081,0.0009694084],"category_scores_gemma":[0.0027892417,0.00048338695,0.00034041714,0.00049345917,0.0007227968,0.0008468077,0.00082745485,0.0004304098,0.00028822754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004528033,0.00012233113,0.000768446,0.00007025736,0.00005703212,0.00012727136,0.00008839872,0.86270654,0.025250547,0.024550661,0.0006926704,0.08511309],"study_design_scores_gemma":[0.000018705876,0.000028931006,0.00007787689,0.0000023301484,0.000004451267,0.000020128797,0.000007649186,0.99247086,0.0018182138,0.0054034316,0.00014191089,0.0000055352975],"about_ca_topic_score_codex":0.0012506477,"about_ca_topic_score_gemma":0.0013771082,"teacher_disagreement_score":0.0012506477,"about_ca_system_score_codex":0.0005410662,"about_ca_system_score_gemma":0.000617185,"threshold_uncertainty_score":0.00542593},"labels":[],"label_agreement":null},{"id":"W1919637680","doi":"10.1186/s13634-015-0270-6","title":"Bayesian STSA estimation using masking properties and generalized Gamma prior for speech enhancement","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Sherbrooke; Concordia University","funders":"","keywords":"Estimator; Computer science; Prior probability; Parametric statistics; Bayesian probability; Generalized gamma distribution; Masking (illustration); Noise (video); Speech enhancement; Speech recognition; Gamma distribution; Pattern recognition (psychology); Mathematics; Artificial intelligence; Noise reduction; Statistics","score_opus":0.06251715671442558,"score_gpt":0.32064099082905506,"score_spread":0.25812383411462947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1919637680","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007581073,0.00016919636,0.99171996,0.000038733404,0.000009026021,0.000011917145,0.000014033474,0.00007807606,0.00037800803],"genre_scores_gemma":[0.3864787,0.0012396941,0.60947746,0.00011489781,0.00007761374,0.00009967046,0.00019212774,0.00011447062,0.0022053577],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957305,0.00011836545,0.000030018171,0.00007017718,0.00017787665,0.000030412102],"domain_scores_gemma":[0.99907076,0.00055559364,0.00011272161,0.00009163721,0.0001423746,0.000027037813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012658084,0.00086787227,0.0006673517,0.0005959373,0.00020247277,0.0007833731,0.00060759624,0.0008019651,0.0009592277],"category_scores_gemma":[0.0038640515,0.0005295756,0.0008327108,0.0004214933,0.0005796675,0.0012666417,0.00112038,0.0007121881,0.00051045616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003951767,0.000096628,0.0016928858,0.0003679579,0.00015221637,0.00023817265,0.0002293985,0.5411643,0.13629743,0.035022408,0.0008081395,0.2835354],"study_design_scores_gemma":[0.00000908472,0.000042635806,0.00060760014,0.000014864501,0.000027456563,0.00010581809,0.00000956384,0.98073924,0.012349016,0.0053713783,0.00070041715,0.000022887692],"about_ca_topic_score_codex":0.0012213809,"about_ca_topic_score_gemma":0.0014741591,"teacher_disagreement_score":0.0012658084,"about_ca_system_score_codex":0.00032269236,"about_ca_system_score_gemma":0.00087535096,"threshold_uncertainty_score":0.006694317},"labels":[],"label_agreement":null},{"id":"W1919678181","doi":"10.1186/s13634-015-0276-0","title":"An efficient central DOA tracking algorithm for multiple incoherently distributed sources","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Tracking (education); Algorithm","score_opus":0.02646591219337527,"score_gpt":0.30525988129393056,"score_spread":0.2787939691005553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1919678181","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00084081886,0.000053913034,0.9987478,0.000011144549,0.000014760553,0.000005101811,0.000006843059,0.00013834458,0.00018126405],"genre_scores_gemma":[0.04084913,0.00020884335,0.9562405,0.000045490444,0.000051970153,0.00006768109,0.00017091933,0.000121692654,0.0022438443],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948835,0.00006484872,0.00003257507,0.00019659374,0.00018481014,0.000032821263],"domain_scores_gemma":[0.999265,0.00020231148,0.00010981289,0.000104556595,0.00029216404,0.000026049189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008340998,0.0008911174,0.0009740888,0.00090538396,0.0005333778,0.0008141315,0.0014161471,0.00072978006,0.0017865723],"category_scores_gemma":[0.0021631615,0.0005572713,0.0009803673,0.0012224661,0.00048390395,0.0015037905,0.00093958614,0.0013623092,0.0012235483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017073179,0.00006679337,0.0010533197,0.0001991915,0.00010755305,0.00009524357,0.00021426492,0.2107825,0.043569665,0.028275408,0.0027019375,0.7127635],"study_design_scores_gemma":[0.000018474953,0.000042547766,0.00035096388,0.000013853051,0.000024246592,0.00014907971,0.000017819895,0.98099226,0.008104535,0.00521079,0.0050473986,0.000027979822],"about_ca_topic_score_codex":0.002706775,"about_ca_topic_score_gemma":0.0033615462,"teacher_disagreement_score":0.002706775,"about_ca_system_score_codex":0.0005192638,"about_ca_system_score_gemma":0.0015103164,"threshold_uncertainty_score":0.0059766173},"labels":[],"label_agreement":null},{"id":"W1971260768","doi":"10.1155/2011/151436","title":"Trombone Synthesis by Model and Measurement","year":2011,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Reflection (computer programming); Focus (optics); Coupling (piping); Waveguide; Acoustics; Mouthpiece; Conical surface; Optics; Algorithm; Physics; Mathematics; Geometry; Mechanical engineering","score_opus":0.04841939339282471,"score_gpt":0.26148216841661404,"score_spread":0.21306277502378934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971260768","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033638983,0.00007306343,0.99365425,0.000031274794,0.000012843733,0.000021524513,0.00003580844,0.00035491222,0.0024524454],"genre_scores_gemma":[0.57010907,0.00074109295,0.41617626,0.00011586051,0.000052151005,0.00044483223,0.00045647245,0.0004089684,0.011495363],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996886,0.000052514548,0.000011602855,0.000072091425,0.000156984,0.000018283767],"domain_scores_gemma":[0.99974376,0.000107156724,0.000037460326,0.000055997694,0.00004855347,0.0000071382347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036296478,0.00058847247,0.00045558944,0.0002835012,0.0002212636,0.0009378185,0.0008945572,0.00095781713,0.0025959206],"category_scores_gemma":[0.0009353992,0.00046095467,0.0007537923,0.00028455458,0.00047564437,0.0010805395,0.00054621894,0.0008345955,0.0011620639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008618515,0.000036984755,0.00037069505,0.00023177612,0.000033042354,0.00010479279,0.00016597343,0.8339209,0.05058651,0.045960467,0.0010252545,0.06747747],"study_design_scores_gemma":[0.000007623988,0.000035113884,0.00012019574,0.000017118542,0.000007927829,0.000043600736,0.000010292811,0.98554975,0.0066193244,0.0032551747,0.004320701,0.000013155418],"about_ca_topic_score_codex":0.00238244,"about_ca_topic_score_gemma":0.0017610975,"teacher_disagreement_score":0.0025959206,"about_ca_system_score_codex":0.0004718647,"about_ca_system_score_gemma":0.0006331336,"threshold_uncertainty_score":0.008684278},"labels":[],"label_agreement":null},{"id":"W1971713955","doi":"10.1155/2008/485821","title":"Heterogeneous Stacking for Classification-Driven Watershed Segmentation","year":2008,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta; Syncrude","keywords":"Segmentation; Artificial intelligence; Computer science; Image segmentation; Maxima and minima; Watershed; Stacking; Pattern recognition (psychology); Scale-space segmentation; Segmentation-based object categorization; Pixel; Ground truth; Computer vision; Mathematics; Physics","score_opus":0.046906808485177635,"score_gpt":0.322696782570851,"score_spread":0.27578997408567335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971713955","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008343985,0.00006828892,0.9891885,0.00003524622,0.000017562012,0.00003544966,0.000034308956,0.0016963284,0.0005804013],"genre_scores_gemma":[0.20598136,0.00013011023,0.7918077,0.000071595954,0.00004270903,0.00009369076,0.00033710297,0.0003094376,0.0012263486],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99897015,0.00016824123,0.00006361022,0.00032507748,0.0003705051,0.00010249514],"domain_scores_gemma":[0.99879897,0.00033447638,0.00013982279,0.00034086884,0.00033862639,0.000047269405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012417962,0.0011691076,0.0011467133,0.00210337,0.0008682126,0.0014760816,0.0014705886,0.0012962939,0.0019849997],"category_scores_gemma":[0.002777629,0.0007495968,0.0011141225,0.0022148232,0.00084939983,0.0017158793,0.0014724847,0.0011756994,0.0011653817],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019463546,0.00009310637,0.001483776,0.00012093814,0.00009603862,0.00022823739,0.0002901656,0.15411745,0.11327976,0.012956179,0.0029944798,0.7141452],"study_design_scores_gemma":[0.0000071034387,0.00003362351,0.0006084957,0.000007485917,0.000026259715,0.0001006129,0.000028104347,0.9381645,0.049914695,0.007818931,0.003267956,0.000022234277],"about_ca_topic_score_codex":0.004170242,"about_ca_topic_score_gemma":0.006676457,"teacher_disagreement_score":0.004170242,"about_ca_system_score_codex":0.0011867185,"about_ca_system_score_gemma":0.0012641551,"threshold_uncertainty_score":0.008610249},"labels":[],"label_agreement":null},{"id":"W1973311809","doi":"10.1155/2007/12145","title":"Fast Burst Synchronization for Power Line Communication Systems","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Preamble; Computer science; Synchronization (alternating current); Burst mode (computing); Real-time computing; Power-line communication; Network packet; Multipath propagation; Asynchronous communication; Electronic engineering; Channel (broadcasting); Power (physics); Telecommunications; Computer network; Engineering","score_opus":0.014184186118891131,"score_gpt":0.29416825700333893,"score_spread":0.2799840708844478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973311809","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00816378,0.0010802908,0.9886545,0.00009285422,0.000026637452,0.000022052434,0.00001755511,0.000108714645,0.0018335374],"genre_scores_gemma":[0.53857124,0.0042446484,0.4507373,0.0001445462,0.00019867132,0.00019657737,0.0001389798,0.00016162706,0.00560637],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998184,0.00006532115,0.000008545616,0.000030113088,0.00006856862,0.000009060897],"domain_scores_gemma":[0.9998185,0.00010235926,0.000030570365,0.000017099688,0.000027141654,0.0000043723235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023906265,0.00039694057,0.0002782768,0.00016410359,0.00016156105,0.00043194043,0.00021551808,0.00036446427,0.001600917],"category_scores_gemma":[0.0006543691,0.0001262761,0.00016899982,0.0002779883,0.00024393655,0.0003814006,0.00031136003,0.00051957474,0.00046677308],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012596729,0.00005404075,0.00045772686,0.00051214016,0.000034934015,0.00021076229,0.0001578404,0.55155253,0.14613144,0.07942975,0.0028554194,0.21847743],"study_design_scores_gemma":[0.000009479512,0.0001325242,0.0002208165,0.00003072795,0.00000961623,0.00008957609,0.000017645894,0.97006375,0.009160139,0.012932282,0.0073205875,0.000012908955],"about_ca_topic_score_codex":0.0004240274,"about_ca_topic_score_gemma":0.0003503666,"teacher_disagreement_score":0.001600917,"about_ca_system_score_codex":0.00024400052,"about_ca_system_score_gemma":0.00026240488,"threshold_uncertainty_score":0.0053555965},"labels":[],"label_agreement":null},{"id":"W1975704496","doi":"10.1155/2008/194276","title":"Centimeter-Level Positioning Using an Efficient New Baseband Mixing and Despreading Method for Software GNSS Receivers","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"GNSS positioning and interference","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Baseband; GNSS applications; Computer science; Pseudorange; Carrier-to-noise ratio; Carrier recovery; Replica; Electronic engineering; Mixing (physics); Software; Real-time computing; Demodulation; Global Positioning System; Signal-to-noise ratio (imaging); Telecommunications; Bandwidth (computing); Engineering; Physics","score_opus":0.03742591777471226,"score_gpt":0.32797068775594646,"score_spread":0.2905447699812342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975704496","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0043804916,0.000057785415,0.99447423,0.0000241104,0.000028287312,0.000016131833,0.000008033042,0.0003674179,0.00064351026],"genre_scores_gemma":[0.0708159,0.000107718246,0.9268077,0.000030223511,0.000055472297,0.000043662207,0.000057966667,0.00007694137,0.0020043647],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944586,0.00005979647,0.000026609507,0.00007300262,0.00036955607,0.000025125855],"domain_scores_gemma":[0.99953043,0.0001297204,0.0000752666,0.00008647211,0.00015750497,0.000020574056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039575528,0.0005786965,0.00040903524,0.00083813426,0.0002280633,0.0005840487,0.00089205947,0.0005109994,0.0014977518],"category_scores_gemma":[0.0009958219,0.00038573085,0.0004114123,0.00043424848,0.00034535246,0.00082747923,0.0005719338,0.00076186465,0.00093628326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021759381,0.000074935684,0.0012004056,0.00020897714,0.00007061597,0.00019216051,0.00018754238,0.040460043,0.3896675,0.016266534,0.0014974421,0.54995626],"study_design_scores_gemma":[0.0001067752,0.00040010456,0.0016824715,0.000038193884,0.0000699364,0.0013907101,0.000041125957,0.6894782,0.2776362,0.0039476044,0.025106553,0.00010214227],"about_ca_topic_score_codex":0.00051902403,"about_ca_topic_score_gemma":0.0011519585,"teacher_disagreement_score":0.0014977518,"about_ca_system_score_codex":0.00034846252,"about_ca_system_score_gemma":0.000426582,"threshold_uncertainty_score":0.0050104856},"labels":[],"label_agreement":null},{"id":"W1977597938","doi":"10.1155/2008/247354","title":"Arabic Handwritten Word Recognition Using HMMs with Explicit State Duration","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Agence Universitaire de la Francophonie","keywords":"Hidden Markov model; Computer science; Speech recognition; Word recognition; Viterbi algorithm; Word (group theory); Duration (music); Artificial intelligence; Sliding window protocol; Pattern recognition (psychology); Handwriting; Intelligent word recognition; Spotting; Handwriting recognition; Cursive; Natural language processing; Intelligent character recognition; Window (computing); Character recognition; Feature extraction; Mathematics; Image (mathematics); Reading (process)","score_opus":0.026208253775838606,"score_gpt":0.29866400061739257,"score_spread":0.27245574684155394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977597938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033011984,0.00035617015,0.9578671,0.00006607142,0.00007451172,0.00007394822,0.00022823364,0.0067441682,0.00157783],"genre_scores_gemma":[0.40270206,0.00057880994,0.5869471,0.00013073278,0.00010116167,0.00022876247,0.0012921346,0.00029014362,0.007729199],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99964666,0.0000608943,0.000039212406,0.0001150946,0.00010002549,0.000038105736],"domain_scores_gemma":[0.9993167,0.0002921725,0.000065927496,0.00015459055,0.00013496363,0.000035705743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045790718,0.0005087924,0.0007147013,0.00038144478,0.00022517104,0.0005828553,0.00072209764,0.00048451946,0.0021864218],"category_scores_gemma":[0.0012276939,0.0004111224,0.00050744886,0.0003706319,0.00021680271,0.00095752557,0.00043357257,0.00068475807,0.001496186],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062599714,0.00023918964,0.0031425385,0.00027332446,0.0002074508,0.00047556113,0.00023110099,0.116431676,0.12026291,0.0033511177,0.003609769,0.7511494],"study_design_scores_gemma":[0.000042945532,0.00014865867,0.0021818457,0.000022312253,0.000074665346,0.00026451683,0.000023544602,0.94231164,0.04773589,0.0019160402,0.0052264337,0.00005149426],"about_ca_topic_score_codex":0.003096551,"about_ca_topic_score_gemma":0.0040932563,"teacher_disagreement_score":0.003096551,"about_ca_system_score_codex":0.00029696332,"about_ca_system_score_gemma":0.00041922648,"threshold_uncertainty_score":0.0073143244},"labels":[],"label_agreement":null},{"id":"W1979624743","doi":"10.1155/2007/43745","title":"A Supervised Classification Algorithm for Note Onset Detection","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Music and Audio Processing","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Hyperparameter; Computer science; Spectrogram; Classifier (UML); Artificial intelligence; Artificial neural network; Pattern recognition (psychology); Machine learning; Supervised learning; Algorithm; Speech recognition","score_opus":0.02042823757870681,"score_gpt":0.2939237268639054,"score_spread":0.27349548928519857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979624743","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0047005834,0.00012412925,0.9915031,0.000068392204,0.0000853298,0.000103640705,0.00015150396,0.002320572,0.0009427271],"genre_scores_gemma":[0.080271944,0.00013194032,0.91314876,0.00012627905,0.00019647619,0.00033907258,0.000986113,0.00020074226,0.004598701],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983368,0.00030783855,0.0001326311,0.00054996874,0.000580803,0.000092066555],"domain_scores_gemma":[0.99748296,0.00074026413,0.00025416238,0.00042022555,0.0010223811,0.00008011606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014083729,0.0010404384,0.0010593674,0.001979051,0.0007401857,0.0008167314,0.0019352895,0.0012579204,0.0039379895],"category_scores_gemma":[0.0041638827,0.00040764964,0.000866745,0.0013933238,0.00048217937,0.0012167599,0.0008116118,0.0016855756,0.0039881924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017455901,0.00020340281,0.0013534704,0.00009321043,0.00007366411,0.000059563263,0.000049498583,0.03177936,0.014832882,0.0035353191,0.009644143,0.938201],"study_design_scores_gemma":[0.00003637454,0.00008058662,0.00117302,0.000017083801,0.000024595984,0.00015413918,0.00002239056,0.97317713,0.011682523,0.0070811273,0.0065233284,0.000027681264],"about_ca_topic_score_codex":0.0020191176,"about_ca_topic_score_gemma":0.0032917373,"teacher_disagreement_score":0.0039379895,"about_ca_system_score_codex":0.0006048324,"about_ca_system_score_gemma":0.0010251987,"threshold_uncertainty_score":0.013173878},"labels":[],"label_agreement":null},{"id":"W1979671043","doi":"10.1155/2011/614571","title":"MMSE Beamforming for SC-FDMA Transmission over MIMO ISI Channels","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Beamforming; MIMO; Minimum mean square error; Computer science; Transmission (telecommunications); Precoding; Channel (broadcasting); Equalization (audio); Matched filter; Minification; Frequency-division multiple access; Transmitter power output; Telecommunications; Control theory (sociology); Algorithm; Orthogonal frequency-division multiplexing; Mathematics; Transmitter; Statistics","score_opus":0.01212432382322442,"score_gpt":0.3010388886468142,"score_spread":0.2889145648235898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979671043","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027301643,0.00038164246,0.96847266,0.00015356352,0.000026179883,0.000021268756,0.000058917212,0.00008516164,0.0034989403],"genre_scores_gemma":[0.8341399,0.0013427476,0.1599588,0.000081316575,0.00008429073,0.00010681779,0.00009897741,0.000022521546,0.004164562],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979633,0.000061768485,0.0000076313145,0.000020844407,0.00008935521,0.00002407593],"domain_scores_gemma":[0.99958557,0.00027033887,0.000041005376,0.000019672681,0.00007389342,0.000009520474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003684203,0.0004653958,0.00035816338,0.00018818244,0.00021938056,0.00047587833,0.00025549362,0.0004788607,0.0010444825],"category_scores_gemma":[0.0012999963,0.00020227114,0.00026825053,0.00040285548,0.0004361689,0.00035026524,0.00030870954,0.00033172456,0.00027881592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009830878,0.000021814158,0.0006651312,0.000110563684,0.000025866982,0.00015962234,0.00007781063,0.91540945,0.015918568,0.034732357,0.0008465162,0.031933926],"study_design_scores_gemma":[0.000008535269,0.000042605912,0.000204908,0.000007592786,0.000008996198,0.00004139565,0.000013288851,0.9908215,0.00274206,0.005654361,0.000448149,0.000006584622],"about_ca_topic_score_codex":0.0013534364,"about_ca_topic_score_gemma":0.0019575953,"teacher_disagreement_score":0.0013534364,"about_ca_system_score_codex":0.00039187958,"about_ca_system_score_gemma":0.00051826023,"threshold_uncertainty_score":0.0034941435},"labels":[],"label_agreement":null},{"id":"W1979999732","doi":"10.1155/2008/683105","title":"Bandwidth-Efficient Cooperative Relaying Schemes with Multiantenna Relay","year":2008,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Relay; Retransmission; Decoding methods; Bandwidth (computing); Computer network; Transmission (telecommunications); Spectral efficiency; Electronic engineering; Telecommunications; Power (physics); Channel (broadcasting); Engineering","score_opus":0.031121445228847525,"score_gpt":0.2924665802900789,"score_spread":0.26134513506123136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979999732","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07678519,0.001439644,0.9160606,0.0001861254,0.00005924579,0.00008023956,0.00005303167,0.0002813547,0.005054515],"genre_scores_gemma":[0.83746725,0.0007697584,0.15843146,0.00010032426,0.00003286381,0.00011220578,0.000068442605,0.00001448769,0.0030033167],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99952614,0.000121933765,0.000030862455,0.00007650516,0.00018484426,0.000059804413],"domain_scores_gemma":[0.99876416,0.00038755138,0.00020095146,0.000292847,0.0003143624,0.000040140996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000656932,0.00074600626,0.0005735103,0.00055324985,0.00046878387,0.00069380016,0.0013558704,0.00083238236,0.0006847007],"category_scores_gemma":[0.0015838434,0.00022406424,0.00031954917,0.0006824092,0.0005393377,0.0011807171,0.0010521209,0.0004746726,0.00039643192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004450579,0.00020046321,0.0013743528,0.00037208715,0.00017511446,0.0009250925,0.00076148415,0.42675698,0.19268605,0.13232839,0.0023638965,0.24161103],"study_design_scores_gemma":[0.000054061315,0.00035730697,0.00036747463,0.00003130178,0.00008874628,0.0009106576,0.00008705285,0.9320227,0.039370265,0.020395827,0.0062273145,0.00008728629],"about_ca_topic_score_codex":0.0007316345,"about_ca_topic_score_gemma":0.0012868728,"teacher_disagreement_score":0.0013558704,"about_ca_system_score_codex":0.0004307533,"about_ca_system_score_gemma":0.00037249617,"threshold_uncertainty_score":0.0034742355},"labels":[],"label_agreement":null},{"id":"W1980032382","doi":"10.1155/2007/80735","title":"Estimation of Time-Scaling Factor for Ultrasound Medical Images Using the Hilbert Transform","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Estimator; Cramér–Rao bound; Scaling; Mathematics; Upper and lower bounds; Minimum-variance unbiased estimator; Bandwidth (computing); Mean squared error; Statistics; Algorithm; Bias of an estimator; Estimation theory; Computer science; Mathematical analysis; Telecommunications; Geometry","score_opus":0.011119403586115947,"score_gpt":0.3094106229989634,"score_spread":0.2982912194128474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980032382","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012306701,0.00010619425,0.99847,0.000025899706,0.000009766541,0.0000057924135,0.0000067598994,0.000060364146,0.0000844242],"genre_scores_gemma":[0.078974634,0.00079236133,0.91896826,0.000050182898,0.000112874484,0.00007387208,0.000107675,0.00010281594,0.00081728364],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99932075,0.00024179467,0.0000484911,0.000083507824,0.00028128925,0.000024202523],"domain_scores_gemma":[0.9984633,0.0009789242,0.00016711833,0.00014538557,0.000213853,0.00003144597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013521964,0.00081603206,0.00060148013,0.0007023461,0.00017777903,0.0009833453,0.00060115085,0.00089347415,0.0012690985],"category_scores_gemma":[0.0066067837,0.00029654684,0.00057176757,0.0007166014,0.0006415833,0.0018048907,0.00067492016,0.0011567103,0.00068996387],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023854966,0.00007964766,0.0016473731,0.0005784274,0.00015483056,0.0003258296,0.00021648548,0.21830638,0.14204915,0.07289763,0.002155755,0.5613499],"study_design_scores_gemma":[0.000015368669,0.0000971051,0.00084300665,0.000024218001,0.00003140571,0.0004836146,0.0000204401,0.962397,0.018185345,0.014532534,0.003331896,0.000038133636],"about_ca_topic_score_codex":0.00048014687,"about_ca_topic_score_gemma":0.0004346587,"teacher_disagreement_score":0.0013521964,"about_ca_system_score_codex":0.00038665385,"about_ca_system_score_gemma":0.0005485825,"threshold_uncertainty_score":0.007151127},"labels":[],"label_agreement":null},{"id":"W1981301597","doi":"10.1155/2010/287929","title":"Image Processing and Analysis in Biomechanics","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Infrared Thermography in Medicine","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Biomechanics; Image processing; Computer science; Computer vision; Artificial intelligence; Image (mathematics); Computer graphics (images); Anatomy; Medicine","score_opus":0.009189409498030496,"score_gpt":0.31074388723334856,"score_spread":0.30155447773531807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981301597","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004328149,0.28083777,0.5942892,0.010508195,0.013510922,0.00038099792,0.0010442554,0.002707983,0.092392586],"genre_scores_gemma":[0.12827906,0.31842408,0.38872904,0.0069518522,0.020613734,0.001111121,0.0029276418,0.0011996812,0.13176376],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.997177,0.0006549922,0.00026353035,0.00051867444,0.0012592898,0.00012649271],"domain_scores_gemma":[0.9968202,0.0013361557,0.00022657863,0.0005170401,0.0009878546,0.000112139634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016533305,0.0014037177,0.0015829289,0.0036233687,0.00066685135,0.0053120716,0.0013790105,0.0024204762,0.017814556],"category_scores_gemma":[0.004876651,0.00047983116,0.0010416365,0.005113547,0.0031148484,0.003110716,0.0021241575,0.0036492348,0.010636256],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010976801,0.00007924054,0.00078857463,0.002956119,0.0001673799,0.0004504988,0.00038602098,0.0071943323,0.007885909,0.27166256,0.108762935,0.5995566],"study_design_scores_gemma":[0.000026763826,0.00013609251,0.0022759184,0.0010449598,0.00007178544,0.0013075589,0.00027996328,0.02308541,0.0036449763,0.23060338,0.7374363,0.00008689021],"about_ca_topic_score_codex":0.001474956,"about_ca_topic_score_gemma":0.00071872195,"teacher_disagreement_score":0.017814556,"about_ca_system_score_codex":0.0011442772,"about_ca_system_score_gemma":0.0016668116,"threshold_uncertainty_score":0.059595585},"labels":[],"label_agreement":null},{"id":"W1981446207","doi":"10.1155/s1110865703212014","title":"The Fusion of Distributed Microphone Arrays for Sound Localization","year":2003,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":138,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Microphone; Computer science; Noise-canceling microphone; Acoustic source localization; Microphone array; Acoustics; SIGNAL (programming language); Noise (video); Speech recognition; Sound (geography); Telecommunications; Artificial intelligence; Physics; Sound pressure","score_opus":0.013776794519437616,"score_gpt":0.2795702934340798,"score_spread":0.26579349891464216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981446207","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028794478,0.00032661698,0.9955445,0.000043399916,0.000053950345,0.000014167394,0.00002134224,0.00031915223,0.00079752266],"genre_scores_gemma":[0.17573145,0.00094924547,0.8197447,0.00013498377,0.00018927692,0.00009018514,0.00017893601,0.000116408344,0.0028649261],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893826,0.0002216651,0.000043495118,0.00020499146,0.00054532284,0.000046286314],"domain_scores_gemma":[0.9994043,0.00019409962,0.0000592551,0.00009997654,0.00021898738,0.000023440081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088930177,0.000997102,0.0010242488,0.000851252,0.00026710005,0.0006994525,0.0010007531,0.000995021,0.0018774299],"category_scores_gemma":[0.0027274548,0.0005228215,0.0007661128,0.0008599558,0.00041648655,0.001368271,0.0016835108,0.00083077577,0.0013644327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035213112,0.000062763356,0.00074070296,0.00043244436,0.00015611439,0.00039442835,0.00023314444,0.06379116,0.23422286,0.011854044,0.0021745083,0.68558574],"study_design_scores_gemma":[0.00006442488,0.00042609972,0.0014614007,0.0000693532,0.00013131426,0.0013726075,0.000086265776,0.8428192,0.12027112,0.013195198,0.019986995,0.00011603283],"about_ca_topic_score_codex":0.00032412919,"about_ca_topic_score_gemma":0.00052068895,"teacher_disagreement_score":0.0018774299,"about_ca_system_score_codex":0.00023140118,"about_ca_system_score_gemma":0.0003350881,"threshold_uncertainty_score":0.006280601},"labels":[],"label_agreement":null},{"id":"W1982050002","doi":"10.1155/2007/86874","title":"Music Information Retrieval Based on Signal Processing","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; McGill University","funders":"","keywords":"Computer science; Music information retrieval; Digital audio; MIDI; Search engine indexing; Signal processing; Audio signal processing; Statistical signal processing; Audio signal; Audio analyzer; Information retrieval; Speech recognition; Digital signal processing; Speech coding; Musical","score_opus":0.018037775206244087,"score_gpt":0.28180604908383805,"score_spread":0.26376827387759394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982050002","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009139869,0.27680948,0.5180396,0.011920207,0.06932022,0.00056021893,0.0012422452,0.0048291935,0.10813895],"genre_scores_gemma":[0.088104494,0.26432183,0.2997769,0.0067941807,0.11725719,0.0005123532,0.006886046,0.0019032413,0.21444383],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99859923,0.00020388911,0.00012849367,0.0002373287,0.0007552197,0.000075875425],"domain_scores_gemma":[0.99858046,0.0005499626,0.00007208394,0.00018075331,0.000549706,0.000066938264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007414147,0.0009717062,0.0016803665,0.004440841,0.00055120577,0.0040140185,0.0012497808,0.0014143856,0.022550048],"category_scores_gemma":[0.0035626919,0.00028416252,0.0009854067,0.004549598,0.00083448214,0.0041333125,0.0012692526,0.0015979649,0.01086129],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014115545,0.000075699165,0.0002930337,0.0013841767,0.00011437616,0.00016023804,0.00011721945,0.0027644713,0.009223463,0.037123635,0.20798333,0.74061924],"study_design_scores_gemma":[0.000051106912,0.00023137288,0.001379823,0.00045607754,0.000116263946,0.00093036005,0.00016685424,0.051750038,0.008589195,0.04506701,0.89116335,0.000098563214],"about_ca_topic_score_codex":0.0006383248,"about_ca_topic_score_gemma":0.00062526,"teacher_disagreement_score":0.022550048,"about_ca_system_score_codex":0.0007721518,"about_ca_system_score_gemma":0.0005532812,"threshold_uncertainty_score":0.07543743},"labels":[],"label_agreement":null},{"id":"W1984793157","doi":"10.1155/2011/490289","title":"Computationally Efficient DOA and Polarization Estimation of Coherent Sources with Linear Electromagnetic Vector-Sensor Array","year":2011,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Decorrelation; Algorithm; Computational complexity theory; Computer science; Polarization (electrochemistry); Preprocessor; Monte Carlo method; Direction of arrival; Stokes parameters; Mathematics; Physics; Optics; Telecommunications; Statistics; Artificial intelligence; Scattering","score_opus":0.012437371007973617,"score_gpt":0.2624894734558864,"score_spread":0.2500521024479128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984793157","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0096156355,0.00009106079,0.9897764,0.000040718267,0.000009781502,0.0000066302077,0.000013811096,0.00009570988,0.00035031379],"genre_scores_gemma":[0.26772502,0.000332053,0.73011696,0.00004848654,0.000064841515,0.00007116165,0.00023055806,0.00006381093,0.0013471047],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968004,0.00012695313,0.000017462455,0.00005286826,0.00010154186,0.00002106314],"domain_scores_gemma":[0.99938476,0.00040682426,0.00006907499,0.0000498717,0.00007410572,0.00001531405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005413061,0.0005899185,0.00054248504,0.0004218746,0.0001772545,0.0004726237,0.00040929543,0.0003853361,0.0007738235],"category_scores_gemma":[0.0020991275,0.00035988362,0.0004429952,0.00067132775,0.00027713776,0.0008415157,0.0006675069,0.00049755274,0.00034647735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034223698,0.00006228094,0.0016261775,0.00020464454,0.00010981561,0.00010489527,0.00010824369,0.5370833,0.03341919,0.016083846,0.001124203,0.4097311],"study_design_scores_gemma":[0.00001060741,0.000032033957,0.00034709135,0.0000040764376,0.000009567719,0.000047547186,0.00001215538,0.99001837,0.004679062,0.0042000078,0.00063049735,0.000008920451],"about_ca_topic_score_codex":0.0008091615,"about_ca_topic_score_gemma":0.0010806323,"teacher_disagreement_score":0.0008091615,"about_ca_system_score_codex":0.0001883465,"about_ca_system_score_gemma":0.0004646445,"threshold_uncertainty_score":0.0028626919},"labels":[],"label_agreement":null},{"id":"W1985186591","doi":"10.1155/2007/87425","title":"Emerging Signal Processing Techniques for Power Quality Applications","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Library science; Telecommunications; Management; Electrical engineering; Engineering physics; Engineering; Humanities; Computer science; Art","score_opus":0.02887531530486811,"score_gpt":0.36080582176843695,"score_spread":0.33193050646356886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985186591","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037426034,0.014275833,0.96184045,0.0013105057,0.0011758136,0.000080799495,0.00022521666,0.00075313513,0.016595637],"genre_scores_gemma":[0.1305672,0.053586885,0.7554607,0.0013495729,0.0039434005,0.00026587507,0.0013739733,0.00040356256,0.053048823],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99957746,0.000071634946,0.000026578111,0.000064832675,0.00023739337,0.000022141141],"domain_scores_gemma":[0.9992895,0.00019312277,0.00005545612,0.00010092873,0.0003327513,0.000028196493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006617259,0.00086499425,0.00049607875,0.0011461453,0.00034229673,0.0015661557,0.00062389026,0.0008965792,0.012107422],"category_scores_gemma":[0.0016444896,0.00021436079,0.000415216,0.0020715669,0.00042657656,0.0014237372,0.0006300023,0.0017101397,0.007152674],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001174433,0.000065464985,0.0004470137,0.00069357624,0.000053297666,0.00018862051,0.00011048781,0.0061282655,0.056684002,0.04011425,0.024056802,0.8713408],"study_design_scores_gemma":[0.00009086527,0.00059730466,0.0032847594,0.00070420414,0.00017665581,0.002204091,0.00031145837,0.28053606,0.058924362,0.124092,0.52898544,0.00009283893],"about_ca_topic_score_codex":0.00031395987,"about_ca_topic_score_gemma":0.0004870224,"teacher_disagreement_score":0.012107422,"about_ca_system_score_codex":0.00023194501,"about_ca_system_score_gemma":0.0003963316,"threshold_uncertainty_score":0.040503383},"labels":[],"label_agreement":null},{"id":"W1985818583","doi":"10.1155/asp/2006/45217","title":"An Automated Video Object Extraction System Based on Spatiotemporal Independent Component Analysis and Multiscale Segmentation","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Segmentation; Computer vision; Independent component analysis; Video tracking; Image segmentation; Object (grammar); Component (thermodynamics); Video processing; Image processing; Wavelet; Pattern recognition (psychology); Image (mathematics)","score_opus":0.01011532520667923,"score_gpt":0.3190834848886604,"score_spread":0.30896815968198116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985818583","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012064777,0.00017413993,0.9837857,0.0000608064,0.000043007924,0.00013096358,0.00010387199,0.0029197498,0.0007169984],"genre_scores_gemma":[0.07099054,0.00018227525,0.92658937,0.0000767105,0.000058718793,0.00021556462,0.00032364466,0.000090925154,0.0014723205],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968576,0.000031083797,0.000023208753,0.000082931714,0.00015389585,0.000023172859],"domain_scores_gemma":[0.99957746,0.00007616583,0.000051916173,0.000058172416,0.00021456277,0.000021663087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003924692,0.000480194,0.00082846865,0.0012964556,0.00032482058,0.0004357122,0.0006179284,0.0006324994,0.0010402928],"category_scores_gemma":[0.0008399448,0.00031871494,0.0004243386,0.0007492676,0.0002517531,0.00081524515,0.0004456698,0.00038912226,0.00090269826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001543836,0.00009547294,0.0009317318,0.000116034586,0.00006229469,0.00015409147,0.00006980421,0.0049760956,0.3885322,0.0027919598,0.0039471425,0.5981689],"study_design_scores_gemma":[0.00009322148,0.000484658,0.009911696,0.0000334817,0.00016248738,0.0011747222,0.000050028615,0.68549484,0.2787358,0.0030374,0.0206914,0.0001302941],"about_ca_topic_score_codex":0.0014519072,"about_ca_topic_score_gemma":0.002040712,"teacher_disagreement_score":0.0014519072,"about_ca_system_score_codex":0.0003021801,"about_ca_system_score_gemma":0.0005369459,"threshold_uncertainty_score":0.0034800768},"labels":[],"label_agreement":null},{"id":"W1985957650","doi":"10.1155/asp/2006/34653","title":"An FPGA-Based MIMO and Space-Time Processing Platform","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Nanyang Technological University; Government of the United Kingdom; University of Canterbury","keywords":"Field-programmable gate array; Computer science; Digital signal processing; MIMO; Signal processing; Baseband; Implementation; Computer hardware; Embedded system; Bandwidth (computing); Computer architecture; Telecommunications; Beamforming","score_opus":0.009998885929390888,"score_gpt":0.27266568220419557,"score_spread":0.26266679627480466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985957650","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10164637,0.00051655737,0.8417295,0.00040366422,0.0004634225,0.00044911908,0.00032576532,0.004812058,0.04965349],"genre_scores_gemma":[0.57768214,0.0004145751,0.40072814,0.00034551087,0.00013342423,0.00015468802,0.00044270564,0.00007355124,0.020025326],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997589,0.000050462535,0.000013387125,0.000038158345,0.00009802495,0.00004116625],"domain_scores_gemma":[0.9997521,0.000053730917,0.000024838915,0.000041242678,0.00009553055,0.000032514818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031823883,0.00033021442,0.00022129252,0.0003624679,0.00023582982,0.00055017014,0.00061452587,0.00036959632,0.004193814],"category_scores_gemma":[0.00045127646,0.00016354858,0.00017050724,0.00027388457,0.00017001323,0.0005153536,0.00030215792,0.0003942575,0.0016006465],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015219369,0.00030871187,0.0020381133,0.00047554926,0.00009638297,0.0016096632,0.0002542986,0.060028728,0.3149406,0.06498468,0.019673537,0.5340678],"study_design_scores_gemma":[0.0005775684,0.006189194,0.005404227,0.00014430222,0.00014315535,0.004317125,0.00017140979,0.49418572,0.31866467,0.010489498,0.15954748,0.00016560448],"about_ca_topic_score_codex":0.0005579407,"about_ca_topic_score_gemma":0.0007985994,"teacher_disagreement_score":0.004193814,"about_ca_system_score_codex":0.00021026567,"about_ca_system_score_gemma":0.00059767027,"threshold_uncertainty_score":0.014029682},"labels":[],"label_agreement":null},{"id":"W1988259170","doi":"10.1155/asp/2006/65716","title":"Fine-Granularity Loading Schemes Using Adaptive Reed-Solomon Coding for xDSL-DMT Systems","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"McGill University","keywords":"Granularity; Digital subscriber line; Computer science; Coding (social sciences); Algorithm; Link adaptation; Real-time computing; Mathematics; Decoding methods; Telecommunications; Statistics","score_opus":0.019299380121759448,"score_gpt":0.2697997941663114,"score_spread":0.2505004140445519,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988259170","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14925191,0.00023922916,0.84623164,0.00019653661,0.00004266212,0.00007210986,0.00004422603,0.0006577011,0.0032640037],"genre_scores_gemma":[0.8337549,0.0001325581,0.16507165,0.00006286025,0.00003050619,0.000050865212,0.00003461284,0.00003968745,0.0008223843],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996462,0.000118709315,0.000035479803,0.000042892752,0.00010161349,0.000055021104],"domain_scores_gemma":[0.9992607,0.00023839016,0.00016303513,0.00020269299,0.00009775557,0.0000373417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005533382,0.00054675236,0.0003473372,0.0004748946,0.0004095909,0.0005906071,0.0005159476,0.0003433869,0.0009724901],"category_scores_gemma":[0.0018847648,0.0001431539,0.00018750828,0.00057236623,0.0005567664,0.0007705593,0.00083225314,0.00041987118,0.00023993517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065524277,0.00016989076,0.0019080203,0.00015068709,0.000040662682,0.00027753416,0.00036766572,0.34177458,0.25842717,0.036679935,0.0017018436,0.3578467],"study_design_scores_gemma":[0.00006286596,0.00025330586,0.000559242,0.000028708502,0.000016834036,0.0002658864,0.000070499256,0.9029541,0.08044528,0.012367981,0.0029222053,0.000053067954],"about_ca_topic_score_codex":0.0004449575,"about_ca_topic_score_gemma":0.0006789778,"teacher_disagreement_score":0.0009724901,"about_ca_system_score_codex":0.00039034977,"about_ca_system_score_gemma":0.00032780078,"threshold_uncertainty_score":0.0032532811},"labels":[],"label_agreement":null},{"id":"W1989575623","doi":"10.1155/asp.2005.2026","title":"Cost-Effective Video Filtering Solution for Real-Time Vision Systems","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stratix; Computer science; Field-programmable gate array; Real-time computing; Filter (signal processing); Computer hardware; Video processing; Computer vision; Digital signal processing; Artificial intelligence; Computer engineering","score_opus":0.013198452650124447,"score_gpt":0.2992967850404984,"score_spread":0.28609833239037397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989575623","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02375442,0.00082678726,0.97015834,0.00031271277,0.00007865516,0.00003723008,0.00003705089,0.00073265645,0.0040621995],"genre_scores_gemma":[0.26622346,0.00078167894,0.7228988,0.000144855,0.0000934384,0.000066873516,0.00012962794,0.000063359694,0.009597964],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998437,0.000014718635,0.0000073151054,0.000023383614,0.000096072254,0.0000148236095],"domain_scores_gemma":[0.99988234,0.000027987442,0.000016470629,0.000016432035,0.000050343635,0.000006439451],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015349226,0.00035258144,0.00022519077,0.00041660925,0.00027139048,0.00047841514,0.0006098238,0.00045569456,0.0031174864],"category_scores_gemma":[0.0004582404,0.00013916897,0.00018155482,0.00032673872,0.00014918603,0.0008821074,0.00020328638,0.00037156127,0.0007797356],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023271491,0.00010231514,0.0003828176,0.0002255648,0.000034059136,0.00013162883,0.000063892076,0.03195129,0.30069077,0.03061973,0.0043661497,0.63119906],"study_design_scores_gemma":[0.00010042547,0.00037637376,0.0010205243,0.00004203575,0.00006133314,0.00045571255,0.000057074645,0.6963983,0.24750832,0.016512288,0.03742607,0.000041539046],"about_ca_topic_score_codex":0.00070499093,"about_ca_topic_score_gemma":0.0016043787,"teacher_disagreement_score":0.0031174864,"about_ca_system_score_codex":0.00052075024,"about_ca_system_score_gemma":0.00048183705,"threshold_uncertainty_score":0.010428965},"labels":[],"label_agreement":null},{"id":"W1989873462","doi":"10.1155/asp/2006/24012","title":"Analysis of Iterative Waterfilling Algorithm for Multiuser Power Control in Digital Subscriber Lines","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":203,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Digital subscriber line; Computer science; Iterated function; Mathematical optimization; Nash equilibrium; Iterative method; Power control; Rate of convergence; Power (physics); Telecommunications; Algorithm; Channel (broadcasting); Mathematics","score_opus":0.008920525516052089,"score_gpt":0.26651755323099835,"score_spread":0.25759702771494625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989873462","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009050759,0.00016697691,0.9876381,0.00014685171,0.000014737242,0.000034062785,0.000017087594,0.00006759506,0.002863856],"genre_scores_gemma":[0.7773607,0.0004804887,0.21497014,0.00017470306,0.00005438882,0.00032802954,0.000093807466,0.00014255504,0.006395266],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898916,0.0003948061,0.000030122079,0.000116157265,0.00031792282,0.00015171495],"domain_scores_gemma":[0.9974462,0.0018376965,0.00019678046,0.00008633755,0.00035966613,0.00007327374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024648646,0.0008453949,0.0010180426,0.0004857958,0.00045654603,0.0013585032,0.0010799314,0.0011090856,0.0032286749],"category_scores_gemma":[0.005897808,0.00044942295,0.0005149004,0.0006904115,0.0016392993,0.0012507656,0.0011433745,0.0011778241,0.00036422684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060996612,0.00003462593,0.00031695596,0.000077263,0.000021736592,0.000079146695,0.00012353223,0.90751934,0.0015806998,0.07301628,0.00076562446,0.016403817],"study_design_scores_gemma":[0.0000050393046,0.000012497986,0.000021767564,0.0000033636975,0.0000017540883,0.0000068690724,0.000006257088,0.99260485,0.0001997787,0.0069752736,0.00016006091,0.0000025463535],"about_ca_topic_score_codex":0.0038702511,"about_ca_topic_score_gemma":0.0024802466,"teacher_disagreement_score":0.0038702511,"about_ca_system_score_codex":0.0016507274,"about_ca_system_score_gemma":0.0021676146,"threshold_uncertainty_score":0.013035595},"labels":[],"label_agreement":null},{"id":"W1990286033","doi":"10.1155/2007/48612","title":"Advances in Subspace-Based Techniques for Signal Processing and Communications","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Telecommunications; Informatics; Library science; Engineering; Electrical engineering","score_opus":0.01715268628740064,"score_gpt":0.30664419245564184,"score_spread":0.2894915061682412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990286033","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011440751,0.02350582,0.96766895,0.0011354532,0.0008667466,0.000027477483,0.00008964609,0.00040076787,0.005161072],"genre_scores_gemma":[0.043102395,0.08576998,0.8539019,0.00062246056,0.004024417,0.00016578547,0.0006213005,0.00026124733,0.011530462],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99787664,0.0005984159,0.00014941662,0.00024535623,0.001058081,0.00007211643],"domain_scores_gemma":[0.99554056,0.0023807765,0.00016088373,0.0006466109,0.001170706,0.0001003693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021243,0.0015899129,0.0013412174,0.001986666,0.00049265596,0.0020345303,0.0012505024,0.0014997836,0.0055032787],"category_scores_gemma":[0.0064484444,0.000446885,0.00090998714,0.004903702,0.0011418158,0.0030455105,0.0015095953,0.0036692235,0.005086681],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079140096,0.000082978535,0.00034862946,0.0008027157,0.00013429856,0.000092533235,0.0001632375,0.020976448,0.012617476,0.10052819,0.02212023,0.8420541],"study_design_scores_gemma":[0.000052999854,0.00028434966,0.0013668139,0.00034521823,0.00010029331,0.0010665152,0.0001391193,0.39814797,0.014205762,0.2199725,0.3641607,0.00015784055],"about_ca_topic_score_codex":0.0012632428,"about_ca_topic_score_gemma":0.0013373704,"teacher_disagreement_score":0.0055032787,"about_ca_system_score_codex":0.00044980206,"about_ca_system_score_gemma":0.0009071939,"threshold_uncertainty_score":0.018410265},"labels":[],"label_agreement":null},{"id":"W1990330883","doi":"10.1155/2007/60839","title":"Improving a Power Line Communications Standard with LDPC Codes","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nortel (Canada); Queen's University","funders":"","keywords":"Computer science; Low-density parity-check code; Throughput; Algorithm; Decoding methods; Fading; Power-line communication; Channel (broadcasting); Multipath propagation; Telecommunications; Power (physics); Wireless","score_opus":0.013761550885820966,"score_gpt":0.2955230560256614,"score_spread":0.28176150513984044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990330883","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2741301,0.00050059153,0.71122867,0.00041900523,0.00004410571,0.000101996215,0.00006045243,0.000995941,0.012519086],"genre_scores_gemma":[0.8826956,0.00041661775,0.11474431,0.00009445262,0.00003666444,0.000051448293,0.00006359163,0.00003054548,0.0018667543],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927455,0.00024798265,0.00002163392,0.000070588634,0.0002922521,0.000093050454],"domain_scores_gemma":[0.9989104,0.00038206676,0.00018890925,0.00019376313,0.00029149855,0.000033414086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074717484,0.0006374926,0.00033587663,0.0004830171,0.0003521038,0.00060936535,0.0005329161,0.00058207475,0.0007125251],"category_scores_gemma":[0.003223143,0.00014489389,0.00018909524,0.0006763816,0.00052722206,0.0011797233,0.00074851996,0.0004896592,0.00027966866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049770396,0.0002860764,0.004616389,0.00026408696,0.000051668965,0.0004689722,0.00031293894,0.4767538,0.12380816,0.12555566,0.0028817495,0.26450273],"study_design_scores_gemma":[0.000031404226,0.0002673336,0.00037647356,0.000019451354,0.00002331606,0.0001828336,0.000029014898,0.9466649,0.038171727,0.009904753,0.004304561,0.000024275707],"about_ca_topic_score_codex":0.0013042382,"about_ca_topic_score_gemma":0.0012257816,"teacher_disagreement_score":0.0013042382,"about_ca_system_score_codex":0.0005439446,"about_ca_system_score_gemma":0.00061484776,"threshold_uncertainty_score":0.00395149},"labels":[],"label_agreement":null},{"id":"W1994107486","doi":"10.1155/2010/392782","title":"Advances in Modal Analysis Using a Robust and Multiscale Method","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Embedding; Modal; Rendering (computer graphics); Variety (cybernetics); Grid; Finite element method; Computer graphics (images); Algorithm; Computer vision; Artificial intelligence; Mathematics; Geometry; Engineering","score_opus":0.023256663453558937,"score_gpt":0.36523721717772056,"score_spread":0.34198055372416164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994107486","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014033281,0.0002046186,0.9969121,0.000058398105,0.00003884851,0.0000062467875,0.000013373064,0.00014830448,0.001214623],"genre_scores_gemma":[0.10381791,0.0009742102,0.89099514,0.000084556814,0.00027260752,0.00007094586,0.00008301217,0.00030502875,0.0033965064],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993723,0.00014221699,0.00003103916,0.00011439908,0.00031152458,0.000028462795],"domain_scores_gemma":[0.9994117,0.00022849109,0.000055907443,0.00017156627,0.00010843875,0.000023961846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008723888,0.00071456545,0.0006052191,0.001182035,0.00030323697,0.0008618749,0.0007459213,0.0007023454,0.0030462632],"category_scores_gemma":[0.0017664336,0.00042051947,0.0013468126,0.00049573695,0.0007989971,0.0011109604,0.0011632561,0.0012709396,0.0009641842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009319463,0.000052293406,0.00047952062,0.00034438833,0.00017308776,0.00014278937,0.00026519754,0.18036912,0.11174894,0.29285854,0.0030578726,0.41041502],"study_design_scores_gemma":[0.000015772714,0.00004817469,0.00032740986,0.00002564768,0.00003339443,0.00011789733,0.000020195821,0.9257056,0.008406099,0.046435986,0.018820472,0.000043356165],"about_ca_topic_score_codex":0.0007289491,"about_ca_topic_score_gemma":0.0006750903,"teacher_disagreement_score":0.0030462632,"about_ca_system_score_codex":0.00039890877,"about_ca_system_score_gemma":0.00031303664,"threshold_uncertainty_score":0.010190785},"labels":[],"label_agreement":null},{"id":"W1994373811","doi":"10.1155/2009/837601","title":"Network Anomaly Detection Based on Wavelet Analysis","year":2008,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":220,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Wavelet; Intrusion detection system; Anomaly detection; Data mining; Identification (biology); SIGNAL (programming language); Artificial intelligence; Pattern recognition (psychology); Machine learning","score_opus":0.014975564926058196,"score_gpt":0.25322590552097635,"score_spread":0.23825034059491815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994373811","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030108456,0.00013694279,0.96831334,0.00007440631,0.000031273794,0.00002812695,0.00009123645,0.00076065876,0.00045566986],"genre_scores_gemma":[0.52856624,0.0007533859,0.46824953,0.00006504774,0.00011510228,0.00009723507,0.0007398746,0.00015252575,0.0012609683],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904245,0.00017187455,0.00006110069,0.00017499442,0.00046990154,0.00007958135],"domain_scores_gemma":[0.9984837,0.0006572433,0.00022502204,0.00023187338,0.00035826155,0.000043971944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011072983,0.0008183339,0.0010315719,0.0029212865,0.00027083114,0.0008778174,0.0007939284,0.0006547378,0.000578517],"category_scores_gemma":[0.004145781,0.0002781479,0.0007405349,0.0024665724,0.00043476807,0.0019687864,0.0008295635,0.0011407129,0.0005403797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035329652,0.00022071821,0.012809881,0.00020019551,0.00021811576,0.00035425436,0.00018624181,0.14518905,0.08651406,0.012139127,0.0027688425,0.7390464],"study_design_scores_gemma":[0.0000076743145,0.000058700585,0.0023704641,0.000008090061,0.000022059246,0.00019327691,0.000023320637,0.9802265,0.011392018,0.0044715777,0.0012094355,0.000016862548],"about_ca_topic_score_codex":0.0009971999,"about_ca_topic_score_gemma":0.00071185554,"teacher_disagreement_score":0.0029212865,"about_ca_system_score_codex":0.0003373086,"about_ca_system_score_gemma":0.00034916785,"threshold_uncertainty_score":0.005856037},"labels":[],"label_agreement":null},{"id":"W1995804124","doi":"10.1186/1687-6180-2012-28","title":"Biologically inspired signal processing: analyses, algorithms and applications","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Signal processing; Algorithm; SIGNAL (programming language); Multidimensional signal processing; Digital signal processing; Computer hardware; Programming language","score_opus":0.042750614885376084,"score_gpt":0.3442295501907098,"score_spread":0.3014789353053337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995804124","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005179127,0.022220248,0.9610283,0.0022405079,0.00024348455,0.000053486565,0.000118654374,0.00046530267,0.0084508965],"genre_scores_gemma":[0.22132884,0.049316444,0.713233,0.000901291,0.0014860363,0.0003824471,0.00044686254,0.00031618835,0.012588931],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995777,0.00013956039,0.000030872172,0.000052642194,0.00018035463,0.000018880888],"domain_scores_gemma":[0.9992894,0.00040991878,0.0000732154,0.000076616256,0.00012989645,0.000020963627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087941514,0.0008301099,0.0007504034,0.0013139666,0.00033738386,0.0017664217,0.0007664067,0.0014577792,0.0028816345],"category_scores_gemma":[0.0032167044,0.00034492865,0.0005018832,0.0022917772,0.0010830815,0.0013116684,0.0008902522,0.001528296,0.0015227303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057361813,0.00010999523,0.0009803772,0.0007358582,0.00013130551,0.00018775812,0.00022320272,0.11868386,0.012867294,0.18345132,0.013787185,0.66878444],"study_design_scores_gemma":[0.0000142771805,0.000051830793,0.00088201126,0.00017879893,0.00003438834,0.0003945014,0.00006654533,0.7158854,0.0036211829,0.2416828,0.037147302,0.000040864437],"about_ca_topic_score_codex":0.0007650327,"about_ca_topic_score_gemma":0.00047605936,"teacher_disagreement_score":0.0028816345,"about_ca_system_score_codex":0.0004617991,"about_ca_system_score_gemma":0.00044756985,"threshold_uncertainty_score":0.009640038},"labels":[],"label_agreement":null},{"id":"W1998493629","doi":"10.1155/2010/641842","title":"Noiseless Codelength in Wavelet Denoising","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Thresholding; Orthonormal basis; Subspace topology; Wavelet; Linear subspace; Noise reduction; Pattern recognition (psychology); Noise (video); Algorithm; Computer science; Mathematics; Artificial intelligence; Image (mathematics)","score_opus":0.015550098373786713,"score_gpt":0.312607079714747,"score_spread":0.29705698134096026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998493629","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008684633,0.00053649204,0.98981094,0.00010808092,0.000032574477,0.000011415681,0.000022872999,0.000080100996,0.0007129285],"genre_scores_gemma":[0.30798376,0.001499147,0.6851057,0.00025336968,0.00018178757,0.00013243439,0.00020969346,0.00018015043,0.004453945],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924386,0.00021368917,0.000035864425,0.00011516733,0.00035034647,0.000041147672],"domain_scores_gemma":[0.99845815,0.00083041325,0.00016345199,0.00020556504,0.00028647837,0.000055974455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001254086,0.0004724534,0.0005532554,0.00074854854,0.0002807482,0.00078934827,0.001053047,0.00093799306,0.00069885614],"category_scores_gemma":[0.0047192136,0.00032445937,0.0003882787,0.00085615274,0.0010101228,0.0013825328,0.0010706108,0.0010326102,0.0003519536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002570132,0.00006795607,0.001204957,0.00031730026,0.00005619815,0.00022277051,0.00018689748,0.47088373,0.054673597,0.18960929,0.0023212978,0.28019905],"study_design_scores_gemma":[0.000008158272,0.00003547921,0.00013487204,0.000010443629,0.0000062347426,0.00006975217,0.0000067998185,0.9708562,0.008299719,0.018930595,0.0016267735,0.000014938053],"about_ca_topic_score_codex":0.00079165073,"about_ca_topic_score_gemma":0.0010055122,"teacher_disagreement_score":0.001254086,"about_ca_system_score_codex":0.0006484372,"about_ca_system_score_gemma":0.00061628927,"threshold_uncertainty_score":0.0066322684},"labels":[],"label_agreement":null},{"id":"W2001063070","doi":"10.1155/2008/471327","title":"Distributed Space-Time Block Coded Transmission with Imperfect Channel Estimation: Achievable Rate and Power Allocation","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transmitter; Upper and lower bounds; Computer science; Channel (broadcasting); Transmitter power output; Robustness (evolution); Block code; Transmission (telecommunications); Code rate; Channel capacity; Metric (unit); Topology (electrical circuits); Performance metric; Algorithm; Mathematics; Telecommunications; Decoding methods","score_opus":0.006439357467992123,"score_gpt":0.25638262977226295,"score_spread":0.24994327230427082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001063070","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035827935,0.0009951729,0.9537462,0.00043426617,0.000031078947,0.00005460006,0.000121287405,0.00022882625,0.008560608],"genre_scores_gemma":[0.8862034,0.0013127621,0.10973268,0.00013490478,0.00008272258,0.0003124981,0.00021023101,0.000101242724,0.001909535],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99482876,0.0021496976,0.000183059,0.0004332052,0.0017902842,0.00061489746],"domain_scores_gemma":[0.9786059,0.0163304,0.0015810293,0.001584167,0.0016820694,0.00021630654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048035095,0.0018987572,0.002158154,0.0010320246,0.0007714873,0.0020850622,0.0016644123,0.001829932,0.0013866482],"category_scores_gemma":[0.02969181,0.00062698935,0.000636452,0.0017567138,0.00228217,0.0028630472,0.0026500646,0.0014312951,0.00068191806],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024663782,0.00006421635,0.00090955815,0.0002727003,0.00007517955,0.0002917112,0.00020092804,0.8410363,0.0075203045,0.11949905,0.0009799649,0.028903496],"study_design_scores_gemma":[0.000024041534,0.00004720806,0.00016984038,0.000041153464,0.000017168753,0.00014813432,0.00003818868,0.9630272,0.0041316897,0.031824514,0.0005101599,0.000020680063],"about_ca_topic_score_codex":0.001677875,"about_ca_topic_score_gemma":0.0012290903,"teacher_disagreement_score":0.0048035095,"about_ca_system_score_codex":0.0020314597,"about_ca_system_score_gemma":0.0016972052,"threshold_uncertainty_score":0.025403678},"labels":[],"label_agreement":null},{"id":"W2001487393","doi":"10.1155/2009/984752","title":"Vector Field Driven Design for Lightweight Signal Processing and Control Schemes for Autonomous Robotic Navigation","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Neuromorphic engineering; Robotics; Artificial intelligence; Field (mathematics); Exploit; Signal processing; SIGNAL (programming language); Computer architecture; Control engineering; Robot; Human–computer interaction; Digital signal processing; Computer hardware; Artificial neural network","score_opus":0.019334171976119554,"score_gpt":0.29524634823391543,"score_spread":0.2759121762577959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001487393","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067992928,0.000083019484,0.99045724,0.00011525235,0.000028011475,0.0000340221,0.000007990255,0.00008497916,0.0023902226],"genre_scores_gemma":[0.5335156,0.00030921694,0.45969483,0.00014966636,0.00005279872,0.00030097863,0.000040089577,0.000071426235,0.0058653047],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982005,0.000048462796,0.000011633889,0.00002187917,0.00008336267,0.0000145925],"domain_scores_gemma":[0.9997768,0.000093708455,0.000038475886,0.000029932946,0.00004614848,0.00001499677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006003787,0.000327903,0.000239574,0.00027064708,0.000264055,0.0005633485,0.0005384283,0.00046618615,0.0025779475],"category_scores_gemma":[0.000920514,0.0001833124,0.00029183127,0.00020655595,0.0006225312,0.0007229401,0.00053181144,0.0005726148,0.0003504772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000063783285,0.00006180745,0.00023785449,0.00019100338,0.000019543473,0.00008913166,0.00017908642,0.31914726,0.03844903,0.5581592,0.0012499309,0.0821523],"study_design_scores_gemma":[0.000033736935,0.00011297876,0.000057713376,0.00001964052,0.000006635687,0.00004055442,0.000015448017,0.9086676,0.004967377,0.079166874,0.0068983254,0.000013097138],"about_ca_topic_score_codex":0.0003092731,"about_ca_topic_score_gemma":0.00043446833,"teacher_disagreement_score":0.0025779475,"about_ca_system_score_codex":0.00051286956,"about_ca_system_score_gemma":0.00042890946,"threshold_uncertainty_score":0.008624136},"labels":[],"label_agreement":null},{"id":"W2001929039","doi":"10.1155/2010/836753","title":"Optical Flow Active Contours with Primitive Shape Priors for Echocardiography","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vector flow; Active contour model; Computer science; Artificial intelligence; Optical flow; Computer vision; Prior probability; Sensitivity (control systems); Flow (mathematics); Pattern recognition (psychology); Image (mathematics); Image segmentation; Mathematics","score_opus":0.012296890739466038,"score_gpt":0.3106295995619595,"score_spread":0.29833270882249346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001929039","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032376733,0.00028184737,0.9957461,0.0000891787,0.000021476637,0.00002850975,0.0000237269,0.00022327686,0.00034821898],"genre_scores_gemma":[0.09836374,0.0006784853,0.8987405,0.00006989085,0.0000555047,0.00015435024,0.00012608396,0.00015770164,0.0016537483],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99956995,0.00017779789,0.000016564472,0.00005865636,0.00016070287,0.000016244612],"domain_scores_gemma":[0.99886584,0.00072060095,0.000093998104,0.00013949677,0.00015189628,0.000028205457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011823407,0.0006109934,0.00059581065,0.00094927225,0.00023975108,0.0006966949,0.0007806159,0.0011404167,0.0016014643],"category_scores_gemma":[0.0048672417,0.0005974083,0.00057257194,0.00082482904,0.00075625087,0.001022888,0.0007613008,0.0009901244,0.0005818603],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002959595,0.00006701771,0.00034552233,0.0002530194,0.00003978882,0.00015766415,0.00018409704,0.4664477,0.0569383,0.034554914,0.0023853176,0.4383307],"study_design_scores_gemma":[0.000016895305,0.00003509359,0.00022388803,0.000021988315,0.000009092421,0.00007301776,0.000007818045,0.9751923,0.0075097093,0.013250121,0.003640213,0.00001985742],"about_ca_topic_score_codex":0.0015949475,"about_ca_topic_score_gemma":0.0014024776,"teacher_disagreement_score":0.0016014643,"about_ca_system_score_codex":0.0005020969,"about_ca_system_score_gemma":0.00076718675,"threshold_uncertainty_score":0.0062529445},"labels":[],"label_agreement":null},{"id":"W2002422013","doi":"10.1155/2008/148658","title":"Analysis of Human Electrocardiogram for Biometric Recognition","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":339,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Ontario Centres of Excellence","keywords":"Fiducial marker; Biometrics; Computer science; Discrete cosine transform; Artificial intelligence; Pattern recognition (psychology); Heartbeat; Identification (biology); Autocorrelation; Computer vision; Speech recognition; Image (mathematics); Mathematics","score_opus":0.03485848196319918,"score_gpt":0.38416257758465494,"score_spread":0.34930409562145576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002422013","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026201762,0.006684575,0.95364916,0.0005698328,0.0003317989,0.00014361406,0.00044118657,0.0013159672,0.0106621245],"genre_scores_gemma":[0.4323766,0.009899921,0.5437446,0.00034951998,0.00058066135,0.0002089431,0.0013533283,0.00023756354,0.011248923],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99917454,0.00022982994,0.00006403412,0.00013410719,0.00036430833,0.000033066688],"domain_scores_gemma":[0.9990735,0.00032654704,0.00011742068,0.0001893019,0.00026892527,0.000024213616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055819016,0.00066356605,0.00047243744,0.0011169682,0.00024124705,0.00069146836,0.00037140277,0.00053352216,0.004399102],"category_scores_gemma":[0.0026756208,0.00014182064,0.00044572694,0.0013178042,0.00032823454,0.00051240536,0.00032737543,0.00047963747,0.002864119],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002089569,0.00007740842,0.0044934102,0.0007242024,0.00009177762,0.0006682773,0.00013282387,0.009333446,0.2800539,0.024732118,0.007185385,0.67229825],"study_design_scores_gemma":[0.00005463584,0.0009808015,0.053611755,0.00048966263,0.00027681128,0.007275524,0.0002984037,0.35255882,0.33771902,0.03514922,0.21139306,0.0001923345],"about_ca_topic_score_codex":0.0004885291,"about_ca_topic_score_gemma":0.0005545444,"teacher_disagreement_score":0.004399102,"about_ca_system_score_codex":0.0002695033,"about_ca_system_score_gemma":0.0004122126,"threshold_uncertainty_score":0.014716446},"labels":[],"label_agreement":null},{"id":"W2006705422","doi":"10.1155/2010/636458","title":"An Entropy-Based Propagation Speed Estimation Method for Near-Field Subsurface Radar Imaging","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; CancerCare Manitoba","funders":"","keywords":"Computer science; Radar; Entropy (arrow of time); Ranging; Metric (unit); Microwave; Microwave imaging; Sample entropy; Radar imaging; Computer vision; Algorithm; Acoustics; Artificial intelligence; Remote sensing; Pattern recognition (psychology); Geology; Telecommunications; Physics; Engineering","score_opus":0.007071147819892387,"score_gpt":0.29837751336086193,"score_spread":0.29130636554096956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006705422","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0047913925,0.0001393292,0.9946108,0.000025394771,0.000017823475,0.000013509408,0.00003079415,0.0001626145,0.00020826221],"genre_scores_gemma":[0.19888029,0.00046714375,0.7987294,0.000035199515,0.000111748675,0.000095181094,0.0003068454,0.00007510777,0.001299028],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995136,0.00011117451,0.000035337336,0.00007299289,0.0002463571,0.000020467369],"domain_scores_gemma":[0.99894375,0.00057236553,0.00013939635,0.00007727376,0.00023739766,0.000029768258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008040549,0.0006690807,0.0005684323,0.0018040712,0.0002988076,0.0005670087,0.00064194074,0.00058924925,0.00089600915],"category_scores_gemma":[0.0030263555,0.0003003929,0.0004327014,0.00089932984,0.00043999366,0.0012136336,0.00065372733,0.0006904993,0.00038634782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025980148,0.000092033646,0.0019801133,0.00019716383,0.00009752614,0.0001467828,0.00011542076,0.21459135,0.060141,0.016031003,0.0017267981,0.7046211],"study_design_scores_gemma":[0.000007952327,0.000046001875,0.0009617647,0.000008376541,0.000013214607,0.00013252436,0.00000834012,0.98167485,0.013139191,0.0029704045,0.0010089171,0.00002846396],"about_ca_topic_score_codex":0.0008400113,"about_ca_topic_score_gemma":0.00080739625,"teacher_disagreement_score":0.0018040712,"about_ca_system_score_codex":0.00041166577,"about_ca_system_score_gemma":0.0004839496,"threshold_uncertainty_score":0.004252255},"labels":[],"label_agreement":null},{"id":"W2007065460","doi":"10.1155/2008/356267","title":"A Reconfigurable GNSS Acquisition Scheme for Time-Frequency Applications","year":2008,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"GNSS positioning and interference","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Computer science; Block (permutation group theory); Satellite system; sort; Interference (communication); Key (lock); Scheme (mathematics); Real-time computing; GNSS augmentation; Electronic engineering; Telecommunications; Global Positioning System; Engineering","score_opus":0.014645919293877312,"score_gpt":0.26278293731594154,"score_spread":0.24813701802206423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007065460","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10601363,0.0005942338,0.87470937,0.0002596524,0.0002346207,0.00018290654,0.00016280524,0.0036896928,0.014153138],"genre_scores_gemma":[0.73613495,0.00019384417,0.25465968,0.000118865464,0.000079319776,0.00011773255,0.00016291015,0.000061844985,0.008470852],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99982136,0.000030240351,0.000011175036,0.000039770253,0.00007323699,0.00002422033],"domain_scores_gemma":[0.9998584,0.000015647305,0.000022664077,0.000061245264,0.000029467263,0.0000126081795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013465967,0.00041586428,0.00024296352,0.00041170715,0.00029109238,0.000325371,0.000644694,0.0003889832,0.0024291247],"category_scores_gemma":[0.00031515915,0.00013743862,0.0002044537,0.0003207646,0.00019412133,0.00042337936,0.0004011266,0.0003239466,0.00095162034],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063813105,0.0000879271,0.0018280514,0.00013635492,0.000050635696,0.0003972384,0.00013902015,0.033386882,0.5044542,0.015223029,0.0032571345,0.44040132],"study_design_scores_gemma":[0.0002494888,0.0009758288,0.0069896043,0.00006141286,0.00011189067,0.0022577008,0.00006675915,0.5193966,0.39288116,0.0055267015,0.07136394,0.0001189541],"about_ca_topic_score_codex":0.00059904036,"about_ca_topic_score_gemma":0.00075307436,"teacher_disagreement_score":0.0024291247,"about_ca_system_score_codex":0.00025932063,"about_ca_system_score_gemma":0.00018343024,"threshold_uncertainty_score":0.008126259},"labels":[],"label_agreement":null},{"id":"W2008467579","doi":"10.1155/asp/2006/79769","title":"RD Optimized, Adaptive, Error-Resilient Transmission of MJPEG2000-Coded Video over Multiple Time-Varying Channels","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Channel (broadcasting); Error detection and correction; Coding (social sciences); Transmission (telecommunications); Network packet; Algorithm; Code rate; Forward error correction; Bit error rate; Real-time computing; Frame (networking); Convolutional code; Decoding methods; Telecommunications; Mathematics; Computer network; Statistics","score_opus":0.018535940375257878,"score_gpt":0.27373648211462404,"score_spread":0.2552005417393662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008467579","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39599517,0.0003678994,0.6015424,0.00012347096,0.000050195446,0.000043735225,0.000051036994,0.0006220438,0.0012039684],"genre_scores_gemma":[0.8307534,0.000139093,0.16770291,0.00003283561,0.000013394781,0.000017783083,0.000057673587,0.00003596045,0.0012469138],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979633,0.000040943367,0.0000114168915,0.00003595242,0.00009598519,0.000019450054],"domain_scores_gemma":[0.9995012,0.00016321488,0.000111728266,0.00008871131,0.00011303968,0.000021959851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003671481,0.00035621697,0.00022026357,0.00023981556,0.00012515538,0.00021396852,0.0004728824,0.00033426296,0.00018766227],"category_scores_gemma":[0.0014860563,0.0001403457,0.00013575876,0.00016546223,0.00023884463,0.0003799208,0.00033674744,0.0003390908,0.00006449311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00097339624,0.00013407646,0.0023846172,0.00011773494,0.000067975554,0.00035151796,0.00019945238,0.41275313,0.4172521,0.0032445858,0.00083346054,0.161688],"study_design_scores_gemma":[0.00002325574,0.00009446056,0.0009057605,0.0000048751563,0.000014223923,0.00016113413,0.0000130380995,0.91733325,0.080635466,0.0003453122,0.00045558478,0.0000135548535],"about_ca_topic_score_codex":0.0018995517,"about_ca_topic_score_gemma":0.0030691847,"teacher_disagreement_score":0.0018995517,"about_ca_system_score_codex":0.00035767784,"about_ca_system_score_gemma":0.00032045983,"threshold_uncertainty_score":0.0037769675},"labels":[],"label_agreement":null},{"id":"W2009085230","doi":"10.1155/2008/587243","title":"Optimal Power Allocation with Channel Inversion Regularization-Based Precoding for MIMO Broadcast Channels","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Precoding; Dirty paper coding; MIMO; Zero-forcing precoding; Mathematics; Channel (broadcasting); Computer science; Mathematical optimization; Inversion (geology); Algorithm; Control theory (sociology); Telecommunications","score_opus":0.01091637055238604,"score_gpt":0.248603750214593,"score_spread":0.23768737966220696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009085230","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020059701,0.00013578386,0.97823113,0.00011629949,0.000014591515,0.000023003122,0.000017381692,0.00010653805,0.001295508],"genre_scores_gemma":[0.71875346,0.00025642643,0.27883598,0.00007727204,0.00003885312,0.00013853118,0.000068359426,0.000030755375,0.0018004761],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99964094,0.00014723546,0.000010099913,0.000045557295,0.000107662054,0.000048530514],"domain_scores_gemma":[0.99967456,0.00018839414,0.00003937024,0.000029041646,0.000056060926,0.000012697342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005972864,0.0005013167,0.0005926769,0.00022811485,0.00021807713,0.00034594495,0.000522902,0.0004882812,0.00057100295],"category_scores_gemma":[0.0015877594,0.00023443515,0.00027348322,0.0004067332,0.00077337417,0.0004624065,0.0004953152,0.00058723,0.0001944889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015927029,0.000074812684,0.00041218282,0.000085722466,0.0000332061,0.00007674833,0.00009899414,0.8683906,0.010396302,0.029640002,0.0017451432,0.08888702],"study_design_scores_gemma":[0.000023946079,0.000029005776,0.000056500194,0.0000030580877,0.000003914705,0.000017417937,0.000005652129,0.9950008,0.0012297526,0.0034383778,0.0001865756,0.0000048727834],"about_ca_topic_score_codex":0.0024165106,"about_ca_topic_score_gemma":0.0023303663,"teacher_disagreement_score":0.0024165106,"about_ca_system_score_codex":0.00045562652,"about_ca_system_score_gemma":0.0010381523,"threshold_uncertainty_score":0.0048048496},"labels":[],"label_agreement":null},{"id":"W2009853277","doi":"10.1155/asp/2006/98738","title":"Near-Capacity Coding for Discrete Multitone Systems with Impulse Noise","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Alberta","funders":"","keywords":"Low-density parity-check code; Computer science; Impulse noise; Erasure; Algorithm; Digital subscriber line; Gaussian noise; Coding (social sciences); Additive white Gaussian noise; Coding gain; Constant-weight code; Concatenated error correction code; Theoretical computer science; Decoding methods; Telecommunications; Channel (broadcasting); Mathematics; Block code; Artificial intelligence; Statistics","score_opus":0.012998119368416447,"score_gpt":0.27023813454531687,"score_spread":0.2572400151769004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009853277","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08712122,0.0005455006,0.9080033,0.00026263142,0.000041930718,0.000039467723,0.000040275492,0.00017243858,0.0037732807],"genre_scores_gemma":[0.8835122,0.0005493696,0.11316549,0.000079375954,0.00006479793,0.000098626726,0.00006869141,0.0000325544,0.0024289389],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994504,0.00016186792,0.000021125463,0.00006025947,0.00023118769,0.00007521064],"domain_scores_gemma":[0.99820054,0.001199312,0.00019438492,0.00014102868,0.00021419856,0.00005043565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007614891,0.000453087,0.00047814546,0.00043442837,0.00035650982,0.0007032278,0.00061826897,0.0006481505,0.00069716916],"category_scores_gemma":[0.0030914901,0.00023164842,0.0002853348,0.00043377333,0.0011970954,0.0008067929,0.00097596075,0.0006875228,0.00018926788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012365908,0.000044317665,0.0005455002,0.00015125978,0.00003687188,0.000293849,0.00023806945,0.83547544,0.020933477,0.105052635,0.0005818577,0.03652308],"study_design_scores_gemma":[0.000008028007,0.000035979618,0.0000687159,0.000010183331,0.0000060344023,0.00004868334,0.000011443358,0.9798752,0.006684178,0.012589286,0.0006516813,0.000010601003],"about_ca_topic_score_codex":0.0011739888,"about_ca_topic_score_gemma":0.0010271657,"teacher_disagreement_score":0.0011739888,"about_ca_system_score_codex":0.0007518328,"about_ca_system_score_gemma":0.0006689659,"threshold_uncertainty_score":0.005455017},"labels":[],"label_agreement":null},{"id":"W2009909707","doi":"10.1155/asp/2006/43154","title":"Iterative Refinement Methods for Time-Domain Equalizer Design","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"3v Geomatics (Canada)","funders":"","keywords":"Computer science; Rayleigh quotient; Iterative method; Algorithm; Rayleigh quotient iteration; Intersymbol interference; Time domain; Matrix (chemical analysis); Eigenvalues and eigenvectors; Mathematical optimization; Mathematics; Power iteration; Decoding methods","score_opus":0.027965169462473946,"score_gpt":0.3718589771743056,"score_spread":0.34389380771183164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009909707","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006018394,0.0000901316,0.99883324,0.000020393602,0.000007662595,0.000012126884,0.000005514189,0.000056206172,0.00037290843],"genre_scores_gemma":[0.048812382,0.0005092735,0.94801784,0.00004727229,0.000035158806,0.00019666774,0.00006963669,0.00007454542,0.002237294],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999188,0.00035868338,0.0000406142,0.000071793576,0.00030096958,0.0000399452],"domain_scores_gemma":[0.99851495,0.000912022,0.0000996002,0.000120058314,0.00033113052,0.000022244822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016831838,0.001070698,0.0006516982,0.00060897635,0.00029869968,0.0006578881,0.0008592019,0.0008724585,0.0028091085],"category_scores_gemma":[0.0047311997,0.0004812289,0.00068985444,0.0007343618,0.0005894944,0.00095276034,0.0009304654,0.0010585614,0.001178974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016699363,0.000047666315,0.0004526281,0.00021678078,0.00008697573,0.00008814703,0.00021527891,0.642699,0.016430127,0.07277415,0.0022674808,0.26455474],"study_design_scores_gemma":[0.000024556792,0.00003695352,0.000047599457,0.000013658402,0.000009147152,0.00003265858,0.000009633349,0.98488903,0.003317511,0.008609825,0.0029995132,0.000009919931],"about_ca_topic_score_codex":0.0017133991,"about_ca_topic_score_gemma":0.0023854214,"teacher_disagreement_score":0.0028091085,"about_ca_system_score_codex":0.0005362288,"about_ca_system_score_gemma":0.00083263783,"threshold_uncertainty_score":0.0093973875},"labels":[],"label_agreement":null},{"id":"W2012158430","doi":"10.1155/2008/672941","title":"A Window Width Optimized S-Transform","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":144,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Window function; Energy (signal processing); Window (computing); Fourier transform; Computer science; Frequency domain; Algorithm; S transform; Constant (computer programming); Short-time Fourier transform; SIGNAL (programming language); Fast Fourier transform; Time domain; Time–frequency analysis; Mathematics; Fourier analysis; Telecommunications; Spectral density; Statistics; Artificial intelligence; Mathematical analysis; Wavelet transform; Computer vision","score_opus":0.016487595365311598,"score_gpt":0.2910599605612794,"score_spread":0.27457236519596784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012158430","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00954897,0.00020341449,0.98896575,0.000052352436,0.000041276966,0.000023717343,0.000039842558,0.00026845414,0.00085618085],"genre_scores_gemma":[0.13870294,0.00048492168,0.8559998,0.00009233074,0.000077479875,0.00007891759,0.00023178098,0.0002193726,0.004112505],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996455,0.000071916926,0.00002879261,0.000081932136,0.00014444425,0.000027379441],"domain_scores_gemma":[0.99960774,0.00013570297,0.000046801808,0.000070283095,0.00012076384,0.000018747067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060727407,0.00072179764,0.0006219788,0.00050977105,0.00021225802,0.0008050063,0.0006112745,0.0006901803,0.0026595804],"category_scores_gemma":[0.0014824261,0.00028358822,0.00054639234,0.00073739415,0.00037812622,0.0012638994,0.0005376711,0.00075703353,0.00091184356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071944733,0.00012545876,0.00073933724,0.00026327133,0.000088989036,0.00015561745,0.000109618006,0.10328666,0.28404814,0.030643078,0.0032108377,0.5766095],"study_design_scores_gemma":[0.000035378158,0.00020497825,0.0006586936,0.000018892622,0.000053924214,0.00022710237,0.000026991602,0.89183956,0.09206812,0.0046197716,0.010215146,0.00003141118],"about_ca_topic_score_codex":0.0006014176,"about_ca_topic_score_gemma":0.0007581854,"teacher_disagreement_score":0.0026595804,"about_ca_system_score_codex":0.00031602266,"about_ca_system_score_gemma":0.0005806288,"threshold_uncertainty_score":0.008897185},"labels":[],"label_agreement":null},{"id":"W2012243263","doi":"10.1155/asp/2006/86712","title":"Time-Frequency Signal Synthesis and Its Application in Multimedia Watermark Detection","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Watermark; Chirp; Computer science; Digital watermarking; Transmitter; SIGNAL (programming language); Noise (video); Image (mathematics); Artificial intelligence; Computer vision; Speech recognition; Telecommunications","score_opus":0.007616264435737652,"score_gpt":0.2490174817947454,"score_spread":0.24140121735900774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012243263","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05732747,0.0021130305,0.93762183,0.0001325215,0.00007647435,0.000036544654,0.000026384005,0.0003769653,0.002288783],"genre_scores_gemma":[0.52941144,0.0025465759,0.4648348,0.0000827756,0.00014970725,0.00006316363,0.00007323071,0.000038021277,0.0028002025],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998491,0.0000310136,0.0000063743737,0.00003185737,0.00007411181,0.000007518501],"domain_scores_gemma":[0.99970835,0.00015405513,0.000041213116,0.000031797375,0.000053919975,0.000010663268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021165819,0.00033201915,0.00024152806,0.0005835126,0.00010542766,0.00026745631,0.00024285582,0.00048458343,0.00088080263],"category_scores_gemma":[0.0005847079,0.00014987384,0.00021388265,0.0005015117,0.00037173735,0.00041721534,0.0001885812,0.0002189411,0.00039707738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002766502,0.000041019248,0.0010458493,0.00022926863,0.000026856733,0.00022391416,0.0000758135,0.014078716,0.64956415,0.00852234,0.0002351374,0.32568032],"study_design_scores_gemma":[0.000043379616,0.00086671324,0.0024527046,0.000036054138,0.00006147702,0.0021893764,0.00005031437,0.41273737,0.5652468,0.0054317866,0.010836677,0.000047388923],"about_ca_topic_score_codex":0.0001528253,"about_ca_topic_score_gemma":0.00015712716,"teacher_disagreement_score":0.00088080263,"about_ca_system_score_codex":0.00013228117,"about_ca_system_score_gemma":0.00009750458,"threshold_uncertainty_score":0.0029466152},"labels":[],"label_agreement":null},{"id":"W2013415492","doi":"10.1155/2009/260148","title":"Sorted Index Numbers for Privacy Preserving Face Recognition","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biometrics; Computer science; Facial recognition system; Face (sociological concept); Index (typography); Set (abstract data type); Pattern recognition (psychology); Transformation (genetics); Artificial intelligence; Projection (relational algebra); Feature (linguistics); Matching (statistics); Random projection; Data mining; Algorithm; Mathematics","score_opus":0.03888488282297544,"score_gpt":0.3285459080691336,"score_spread":0.28966102524615817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013415492","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01545671,0.0008335165,0.9760576,0.00016787478,0.00015127135,0.00007069326,0.00012004417,0.00072800857,0.006414185],"genre_scores_gemma":[0.28604692,0.0012330747,0.7037434,0.0002509761,0.0002750871,0.0002047667,0.00045536095,0.00014616022,0.0076442864],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985043,0.00026169876,0.000118373166,0.00023475602,0.00079424365,0.000086651984],"domain_scores_gemma":[0.99861467,0.00040563516,0.00018249909,0.0005259306,0.00022405872,0.000047240806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008281553,0.0004579552,0.000531184,0.0010077462,0.0005507628,0.0012452049,0.00090115174,0.0005658398,0.003907404],"category_scores_gemma":[0.0036375711,0.00019425259,0.0003788612,0.0013441842,0.0009543202,0.0023192621,0.0009865373,0.0008465931,0.0018853928],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057774456,0.00007766792,0.0008052525,0.00024495518,0.000032785203,0.00025271403,0.00021351824,0.022762123,0.0650548,0.17639454,0.004476583,0.7291073],"study_design_scores_gemma":[0.00009027117,0.00061957823,0.0013460213,0.00010275702,0.00006784004,0.0025129344,0.00017079676,0.4482218,0.18671887,0.24838406,0.11161831,0.00014675097],"about_ca_topic_score_codex":0.0002984694,"about_ca_topic_score_gemma":0.00033599848,"teacher_disagreement_score":0.003907404,"about_ca_system_score_codex":0.00050151476,"about_ca_system_score_gemma":0.0006193943,"threshold_uncertainty_score":0.013071597},"labels":[],"label_agreement":null},{"id":"W2015553615","doi":"10.1186/1687-6180-2012-251","title":"Doubly selective channel estimation for amplify-and-forward relay networks","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Estimator; Channel (broadcasting); Relay; Computer science; Algorithm; Mean squared error; Bit error rate; Minimum mean square error; Sequence (biology); Basis (linear algebra); Exponential function; Computational complexity theory; Telecommunications; Mathematics; Statistics","score_opus":0.03399911896842289,"score_gpt":0.32874617059190525,"score_spread":0.29474705162348236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015553615","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0136303725,0.00035417583,0.9850795,0.000076031065,0.000011948681,0.0000108013655,0.000022803077,0.00006696204,0.0007473894],"genre_scores_gemma":[0.866796,0.001284298,0.12942378,0.00006816021,0.00005298738,0.00007232052,0.000096412616,0.00002192527,0.0021840795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996159,0.00015949897,0.000013988998,0.00005505187,0.000116811534,0.000038818882],"domain_scores_gemma":[0.999226,0.0005258304,0.000075797594,0.00005961178,0.000097879034,0.000014964286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061028334,0.00048355624,0.00045660156,0.0002978923,0.00025916714,0.00045781993,0.00044911803,0.0005141561,0.00047329953],"category_scores_gemma":[0.0023044094,0.000245152,0.00024259987,0.00034788367,0.00043270117,0.00062215194,0.00054939464,0.000478292,0.00018646778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009437232,0.000026498576,0.0005110945,0.00010409269,0.000037571597,0.00015446913,0.00009003833,0.88428146,0.011327039,0.03147364,0.0010301203,0.070869505],"study_design_scores_gemma":[0.0000025260993,0.00001657027,0.00007427505,0.000003123874,0.0000068395993,0.000032095482,0.0000075012636,0.9943463,0.00163479,0.0034969505,0.0003728325,0.0000061122487],"about_ca_topic_score_codex":0.001963225,"about_ca_topic_score_gemma":0.0021281485,"teacher_disagreement_score":0.001963225,"about_ca_system_score_codex":0.0004554103,"about_ca_system_score_gemma":0.00058185286,"threshold_uncertainty_score":0.0039035678},"labels":[],"label_agreement":null},{"id":"W2016209590","doi":"10.1155/asp.2005.382","title":"Principles and Limitations of Ultra-Wideband FM Communications Systems","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Ultra-Wideband Communications Technology","field":"Engineering","cited_by":124,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Demodulation; Subcarrier; Electronic engineering; Multipath propagation; Wideband; Frequency-shift keying; Bandwidth (computing); Frequency-hopping spread spectrum; Narrowband; Telecommunications; Orthogonal frequency-division multiplexing; Engineering; Channel (broadcasting)","score_opus":0.04374727212427549,"score_gpt":0.2826673075783133,"score_spread":0.23892003545403784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016209590","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022451188,0.034161463,0.8596705,0.00495804,0.00056707574,0.00009688254,0.00007306985,0.00063241,0.07738932],"genre_scores_gemma":[0.70150983,0.03845121,0.22798745,0.0023512943,0.0015432109,0.00043598062,0.000090424284,0.00012219456,0.027508473],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984471,0.0003134147,0.00006154586,0.00015395645,0.00094151153,0.000082498795],"domain_scores_gemma":[0.99826425,0.001043996,0.0001342531,0.00021801493,0.00030354605,0.000036002097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012647797,0.00055373815,0.0005066475,0.0006919087,0.00075597817,0.002026174,0.0014184457,0.0021158897,0.0021775733],"category_scores_gemma":[0.0023761243,0.0005312716,0.0002918914,0.00049522193,0.0022819028,0.0035985915,0.001548927,0.0019533054,0.00138426],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013751889,0.000052588708,0.0010077052,0.0010180388,0.00008473199,0.0005876197,0.00090143626,0.03329493,0.035385277,0.6087682,0.004230097,0.3145318],"study_design_scores_gemma":[0.00007709948,0.000452613,0.0014522863,0.00084377144,0.0000957999,0.0051032193,0.000492011,0.11264877,0.03319372,0.5074482,0.33796534,0.0002272202],"about_ca_topic_score_codex":0.00039203113,"about_ca_topic_score_gemma":0.00023436808,"teacher_disagreement_score":0.0021775733,"about_ca_system_score_codex":0.00077065884,"about_ca_system_score_gemma":0.00048384076,"threshold_uncertainty_score":0.007284701},"labels":[],"label_agreement":null},{"id":"W2016272839","doi":"10.1155/asp/2006/72705","title":"Wavelet Video Denoising with Regularized Multiresolution Motion Estimation","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Artificial intelligence; Motion compensation; Wavelet; Motion estimation; Computer vision; Smoothing; Quarter-pixel motion; Computer science; Wavelet transform; Noise reduction; Video denoising; Focus (optics); Mathematics; Pattern recognition (psychology); Video processing; Video tracking","score_opus":0.012028828946023128,"score_gpt":0.2818807796187281,"score_spread":0.26985195067270495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016272839","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008158475,0.00021254836,0.99115,0.00004270035,0.00002067175,0.000009370187,0.000012513085,0.00011508971,0.00027862325],"genre_scores_gemma":[0.18324073,0.00089133583,0.8128727,0.000078686964,0.00010853976,0.00005156885,0.00016373719,0.00011222831,0.0024804196],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999567,0.00010777931,0.000029736082,0.0000910576,0.00017863921,0.000025755206],"domain_scores_gemma":[0.9995691,0.00014795398,0.000064365166,0.000117518604,0.00008637424,0.0000146635175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009492238,0.0005118379,0.00080331817,0.00065518037,0.00015116368,0.00044660692,0.00060210214,0.00071092776,0.0005526161],"category_scores_gemma":[0.00258367,0.00030384873,0.0008458984,0.00054519996,0.00035593536,0.000852697,0.0006978602,0.0007736374,0.00030200873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031010894,0.000082785235,0.000809773,0.00028047367,0.00016042982,0.00028540756,0.00022390323,0.40512875,0.15766244,0.034821123,0.0016341179,0.39860064],"study_design_scores_gemma":[0.000009832913,0.000044365766,0.0002660971,0.00000927615,0.000021486747,0.00011224951,0.0000090307285,0.97842777,0.0154212,0.003940575,0.0017263612,0.000011735773],"about_ca_topic_score_codex":0.0008780546,"about_ca_topic_score_gemma":0.00096797734,"teacher_disagreement_score":0.0009492238,"about_ca_system_score_codex":0.00024183822,"about_ca_system_score_gemma":0.00028655096,"threshold_uncertainty_score":0.0050200224},"labels":[],"label_agreement":null},{"id":"W2017220535","doi":"10.1155/s1110865704403217","title":"Design of Farthest-Point Masks for Image Halftoning","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dither; Halftone; Computer science; Point (geometry); Measure (data warehouse); Image (mathematics); Flexibility (engineering); Algorithm; Simplicity; Sampling (signal processing); Artificial intelligence; Computer vision; Mathematics; Data mining","score_opus":0.020388060068881175,"score_gpt":0.3199889494377906,"score_spread":0.29960088936890944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017220535","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02271047,0.00014826565,0.97555643,0.00005682641,0.000036650268,0.00007689706,0.000034581637,0.0003118239,0.0010680514],"genre_scores_gemma":[0.11219936,0.0001712605,0.8857114,0.00005400918,0.000020580668,0.00011603747,0.00007174999,0.000084646796,0.0015709192],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969816,0.00004262893,0.000021041054,0.000056959554,0.00015154545,0.00002964993],"domain_scores_gemma":[0.9991652,0.00027754583,0.000104995175,0.00012269281,0.00026627711,0.00006328955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038457225,0.000584502,0.0004311064,0.00055556337,0.0003165905,0.00071522256,0.00087311224,0.000627206,0.0014002902],"category_scores_gemma":[0.0015549548,0.0003890933,0.00029557923,0.00035864327,0.0004162355,0.00092808815,0.0005870789,0.00054348336,0.0008053558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039830536,0.00010122704,0.001242403,0.00024440556,0.00003969877,0.00020595717,0.0003057276,0.025652628,0.6427729,0.03534728,0.0016583195,0.29203117],"study_design_scores_gemma":[0.0000421921,0.00018120924,0.0011129158,0.000020082045,0.000023999057,0.00049585913,0.000044093144,0.4710707,0.5098288,0.0048266803,0.012303092,0.00005042053],"about_ca_topic_score_codex":0.00061616296,"about_ca_topic_score_gemma":0.001086098,"teacher_disagreement_score":0.0014002902,"about_ca_system_score_codex":0.00070107315,"about_ca_system_score_gemma":0.00061309023,"threshold_uncertainty_score":0.0050866604},"labels":[],"label_agreement":null},{"id":"W2024180327","doi":"10.1155/2007/42505","title":"Representation of 3D and 4D Objects Based on an Associated Curved Space and a General Coordinate Transformation Invariant Description","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Invariant (physics); Coordinate system; Representation (politics); Graph; Transformation group; Mathematics; Coordinate space; Transformation (genetics); Algebra over a field; Pure mathematics; Computer science; Geometry; Discrete mathematics","score_opus":0.014299753751295288,"score_gpt":0.2565097592284183,"score_spread":0.242210005477123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024180327","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009298181,0.00023944567,0.985903,0.00014216185,0.000055832264,0.000027286327,0.00017686137,0.00017574176,0.003981566],"genre_scores_gemma":[0.3041175,0.0011867799,0.68035394,0.00026656748,0.00024452418,0.00017830923,0.0009953483,0.00031990922,0.012337224],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994862,0.00011973648,0.000041254756,0.000120072335,0.00018226459,0.00005045565],"domain_scores_gemma":[0.9995072,0.00005907488,0.00010796843,0.00013920321,0.00013457637,0.000052077794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059398013,0.00070313603,0.0005654214,0.0024022884,0.0004289156,0.0018556463,0.0009782084,0.0007217481,0.003088868],"category_scores_gemma":[0.00090780185,0.0002801012,0.0010783626,0.001400645,0.0015257413,0.0030740937,0.0014180811,0.00089896144,0.0011634994],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042860178,0.000012124183,0.00029131275,0.00006825823,0.000021219592,0.00016454024,0.00021279872,0.020528002,0.011133823,0.9280492,0.0015733627,0.037902486],"study_design_scores_gemma":[0.000015264597,0.00016234169,0.0012218388,0.00003691393,0.000041404848,0.0006441696,0.00020009326,0.40022802,0.004719232,0.55170715,0.040908523,0.000115038274],"about_ca_topic_score_codex":0.0012796664,"about_ca_topic_score_gemma":0.0008138081,"teacher_disagreement_score":0.003088868,"about_ca_system_score_codex":0.0008757226,"about_ca_system_score_gemma":0.0006505061,"threshold_uncertainty_score":0.0103333},"labels":[],"label_agreement":null},{"id":"W2024437575","doi":"10.1155/asp/2006/49073","title":"Information Mining from Multimedia Databases","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Multimedia; Database; Information retrieval; World Wide Web","score_opus":0.016361785347271725,"score_gpt":0.27678843063447334,"score_spread":0.2604266452872016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024437575","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006553784,0.19264546,0.56049794,0.08396974,0.07167372,0.0017462353,0.020472256,0.009197368,0.053243548],"genre_scores_gemma":[0.059823927,0.17160764,0.4747733,0.030178012,0.06787609,0.0021348319,0.08997519,0.0023028858,0.10132813],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99707365,0.000673811,0.00036128642,0.0004702712,0.0013028737,0.0001180642],"domain_scores_gemma":[0.99153006,0.004144377,0.00045716565,0.00097016216,0.0025334058,0.00036488537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033833361,0.0011153468,0.0016992262,0.008335983,0.00092303153,0.0048912764,0.0022895879,0.0020295205,0.018549694],"category_scores_gemma":[0.013763509,0.00059580134,0.0014406232,0.008645931,0.0006774944,0.0070607555,0.0025320323,0.0030835602,0.008617344],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000102946135,0.00008168866,0.0005934801,0.00093336933,0.00014729895,0.00023403554,0.00006397377,0.0013147556,0.0009946715,0.010682145,0.46111906,0.52373266],"study_design_scores_gemma":[0.000046591726,0.00009013025,0.0011150966,0.0006503008,0.00010411581,0.00059448933,0.00017990422,0.019543521,0.0027238338,0.0427522,0.9321444,0.0000554444],"about_ca_topic_score_codex":0.0008071235,"about_ca_topic_score_gemma":0.0010752502,"teacher_disagreement_score":0.018549694,"about_ca_system_score_codex":0.00077536586,"about_ca_system_score_gemma":0.0010086342,"threshold_uncertainty_score":0.062054873},"labels":[],"label_agreement":null},{"id":"W2026553896","doi":"10.1155/asp/2006/46357","title":"Advances in Multimicrophone Speech Processing","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Bar-Ilan University","keywords":"Speech recognition; Computer science; Speech processing; Signal processing; Digital signal processing; Computer hardware","score_opus":0.009334189827015083,"score_gpt":0.2757431463554137,"score_spread":0.26640895652839863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026553896","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022124724,0.092997804,0.8453375,0.0033497892,0.0029208146,0.00009804906,0.0006062607,0.0017491952,0.030815877],"genre_scores_gemma":[0.12835944,0.042226378,0.7743298,0.001412594,0.0034217245,0.00015873082,0.0021529752,0.000528091,0.047410276],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994356,0.00008614636,0.000054398195,0.00014897424,0.00023189397,0.000042980013],"domain_scores_gemma":[0.9985001,0.00047972903,0.000060113365,0.00019399004,0.0007119412,0.000054115677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011372664,0.00087864086,0.00063117093,0.0015190591,0.0002508467,0.0012829516,0.0009021014,0.00120179,0.011862691],"category_scores_gemma":[0.0016398669,0.00032469732,0.00041977732,0.0017864489,0.00034306166,0.0015622631,0.00076952536,0.00096904085,0.0063291946],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001287903,0.000064581465,0.00051261624,0.00032881545,0.000042896845,0.0001397707,0.000087746645,0.0034207052,0.040975444,0.008924665,0.009982009,0.93539196],"study_design_scores_gemma":[0.00008498019,0.0004981909,0.006786985,0.00047916445,0.00017911829,0.0018997228,0.000259737,0.24764839,0.12500694,0.026175935,0.59082735,0.00015344853],"about_ca_topic_score_codex":0.0014586089,"about_ca_topic_score_gemma":0.0019282372,"teacher_disagreement_score":0.011862691,"about_ca_system_score_codex":0.0004310955,"about_ca_system_score_gemma":0.00068453985,"threshold_uncertainty_score":0.039684653},"labels":[],"label_agreement":null},{"id":"W2027901383","doi":"10.1155/asp/2006/36093","title":"Adaptive Local Polynomial Fourier Transform in ISAR","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Department of National Defence","funders":"","keywords":"Chirp; Fourier transform; Computer science; Polynomial; Radar; Inverse synthetic aperture radar; Algorithm; Simple (philosophy); Fast Fourier transform; Computer vision; Artificial intelligence; Radar imaging; Mathematics; Optics; Telecommunications; Physics; Mathematical analysis","score_opus":0.007712217372547663,"score_gpt":0.25444806992099056,"score_spread":0.2467358525484429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027901383","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077585266,0.0007132264,0.98761916,0.0001243638,0.000053874413,0.000017569067,0.000033965596,0.00041285186,0.0032665066],"genre_scores_gemma":[0.2017832,0.0015358948,0.79003185,0.00010638503,0.00016207369,0.000048185557,0.000170717,0.00015141544,0.0060102907],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996877,0.00008603827,0.00000783718,0.000045185447,0.00015295662,0.000020398184],"domain_scores_gemma":[0.9997907,0.00007459781,0.000025535817,0.000048114067,0.000053215423,0.000007887448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042369164,0.00039865216,0.00034687988,0.00040089875,0.00016005807,0.00040356425,0.00049052853,0.000598123,0.0015835741],"category_scores_gemma":[0.0010255162,0.00018234731,0.00029747168,0.0008779821,0.00044108115,0.0007400432,0.0003885653,0.0008421635,0.0012076803],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018350601,0.000058935642,0.0008128839,0.00028053278,0.00003148082,0.00048304762,0.00020238514,0.22145824,0.12059986,0.102920465,0.0062671965,0.54670143],"study_design_scores_gemma":[0.000015974878,0.00007390006,0.0008193713,0.000017785658,0.000012163876,0.000470686,0.000025876625,0.9370165,0.026379397,0.019101625,0.016034627,0.000032159656],"about_ca_topic_score_codex":0.0009163473,"about_ca_topic_score_gemma":0.0008703202,"teacher_disagreement_score":0.0015835741,"about_ca_system_score_codex":0.00026892347,"about_ca_system_score_gemma":0.00027894884,"threshold_uncertainty_score":0.005297601},"labels":[],"label_agreement":null},{"id":"W2029459011","doi":"10.1155/2008/258184","title":"On the Use of Complementary Spectral Features for Speaker Recognition","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Additive white Gaussian noise; Mel-frequency cepstrum; Speech recognition; Computer science; Cepstrum; Vocal tract; Pattern recognition (psychology); Crest factor; Linear prediction; Speaker recognition; Noise (video); White noise; Artificial intelligence; Mathematics; Bandwidth (computing); Feature extraction; Telecommunications","score_opus":0.08896500203753117,"score_gpt":0.3259021926772365,"score_spread":0.23693719063970536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029459011","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034114327,0.0034621248,0.9529112,0.00023061845,0.00027697315,0.00014006364,0.00029471578,0.0019858999,0.006584106],"genre_scores_gemma":[0.4519403,0.0036949976,0.5365376,0.00029605886,0.00036172048,0.00021008315,0.0012924501,0.00018464867,0.005482111],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99896705,0.00024664446,0.000052216554,0.00020522095,0.00047031196,0.00005866438],"domain_scores_gemma":[0.9988201,0.0004747096,0.000079466416,0.00013976204,0.00046308388,0.000022872015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011555215,0.0008551413,0.0006931964,0.0015928418,0.00030767708,0.0008632799,0.0005252308,0.00078366505,0.001772239],"category_scores_gemma":[0.0030516651,0.0002196384,0.0006413773,0.0011283482,0.00041900974,0.0011847973,0.0007592229,0.00064583815,0.0018815276],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022947174,0.00008550749,0.0011072791,0.00023576076,0.000095346295,0.00020310748,0.000106571686,0.015498372,0.08414946,0.0050192703,0.0023789145,0.89089096],"study_design_scores_gemma":[0.0000359091,0.0006632887,0.010541743,0.00018633349,0.0002716517,0.0017833337,0.00016038198,0.79437274,0.15056689,0.011040658,0.03015,0.0002270289],"about_ca_topic_score_codex":0.0014524028,"about_ca_topic_score_gemma":0.0012919251,"teacher_disagreement_score":0.001772239,"about_ca_system_score_codex":0.00023224842,"about_ca_system_score_gemma":0.00036696947,"threshold_uncertainty_score":0.0061110854},"labels":[],"label_agreement":null},{"id":"W2031433076","doi":"10.1155/2011/963642","title":"Recent Advances in Theory and Methods for Nonstationary Signal Analysis","year":2011,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Türkiye Bilimler Akademisi","keywords":"Computer science; Signal processing; SIGNAL (programming language); Mathematical economics; Speech recognition; Telecommunications; Mathematics; Programming language","score_opus":0.027932711325622524,"score_gpt":0.37379221682320424,"score_spread":0.3458595054975817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031433076","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004988325,0.019423546,0.97711825,0.00043049527,0.00047962056,0.000018572217,0.000054518478,0.00023107404,0.0017451387],"genre_scores_gemma":[0.03448786,0.07401611,0.87732005,0.00084232865,0.005125719,0.00024201504,0.00050742313,0.00053568074,0.0069227335],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99804,0.00058395305,0.00017627853,0.00033718845,0.00079058326,0.00007190394],"domain_scores_gemma":[0.9938082,0.0038302657,0.00021439513,0.0008808679,0.0011549486,0.00011120636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024618767,0.0014169018,0.001973053,0.002415373,0.00053998816,0.0021836534,0.0022023753,0.001649216,0.0061525516],"category_scores_gemma":[0.008913482,0.00080289727,0.0012611318,0.004134777,0.0015261024,0.0029395043,0.0019161865,0.003782233,0.0048452737],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011171437,0.00011012577,0.00051124353,0.001573507,0.00018305324,0.00013096468,0.00016779256,0.034787096,0.008608186,0.15758663,0.014144065,0.78208566],"study_design_scores_gemma":[0.0000430304,0.000093803465,0.0009909619,0.0002853381,0.00014631069,0.00044385134,0.000075647135,0.5311641,0.0055790404,0.33408788,0.12696968,0.00012031355],"about_ca_topic_score_codex":0.0016911961,"about_ca_topic_score_gemma":0.0013740367,"teacher_disagreement_score":0.0061525516,"about_ca_system_score_codex":0.0006169175,"about_ca_system_score_gemma":0.0011497813,"threshold_uncertainty_score":0.020582318},"labels":[],"label_agreement":null},{"id":"W2031719061","doi":"10.1155/2010/345743","title":"Facial Recognition in Uncontrolled Conditions for Information Security","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Face recognition and analysis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina; Defence Research and Development Canada","funders":"Engineering and Physical Sciences Research Council","keywords":"Computer science; Facial recognition system; Lock (firearm); Preprocessor; Authentication (law); Face (sociological concept); Identity (music); Biometrics; Face detection; Computer security; Audit; Artificial intelligence; Computer vision; Pattern recognition (psychology)","score_opus":0.012015115222769377,"score_gpt":0.2922976603013759,"score_spread":0.2802825450786065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031719061","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5729212,0.0009762242,0.41705617,0.00045723387,0.0003249618,0.0001937147,0.00047168392,0.0009355446,0.0066631935],"genre_scores_gemma":[0.911265,0.0007212236,0.08442938,0.00010195477,0.00007507163,0.000094048024,0.00047858778,0.00006280167,0.0027719757],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995503,0.00011585953,0.000018351388,0.00010066003,0.00017089696,0.00004397444],"domain_scores_gemma":[0.99960166,0.00014344598,0.000043130472,0.00009610873,0.000099570156,0.000016051978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046040615,0.00034892562,0.0004216706,0.00030735956,0.00028344497,0.00042204192,0.00028134574,0.0004201845,0.0021728994],"category_scores_gemma":[0.0014348987,0.0001601315,0.0003300772,0.00027828608,0.00036494946,0.0005766167,0.0004173673,0.00040579133,0.00072435034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001356047,0.00027851106,0.005509859,0.0001974813,0.00005324838,0.00054156885,0.00021772597,0.025622219,0.66216004,0.0025598179,0.0032822054,0.29822132],"study_design_scores_gemma":[0.00010476288,0.0009443973,0.04371893,0.000058554517,0.00014451984,0.0017263943,0.0003431009,0.6141509,0.3240696,0.0046883435,0.009953119,0.00009741433],"about_ca_topic_score_codex":0.0019346958,"about_ca_topic_score_gemma":0.0020777558,"teacher_disagreement_score":0.0021728994,"about_ca_system_score_codex":0.00028027885,"about_ca_system_score_gemma":0.0003299158,"threshold_uncertainty_score":0.007269025},"labels":[],"label_agreement":null},{"id":"W2034367898","doi":"10.1155/s1110865703210076","title":"Retrieval by Local Motion","year":2003,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science; Motion (physics); Video retrieval; Ranking (information retrieval); Invariant (physics); Quarter-pixel motion; Minimum bounding box; Bounding overwatch; Mathematics; Image (mathematics)","score_opus":0.009932568818001657,"score_gpt":0.266163763396072,"score_spread":0.25623119457807036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034367898","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.119789,0.012837062,0.85002744,0.0006431152,0.00037870125,0.0004235525,0.001900496,0.0031016814,0.010898965],"genre_scores_gemma":[0.7636029,0.005705017,0.20795742,0.00048324437,0.0008067337,0.0003164335,0.0058996803,0.00030927933,0.014919438],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999119,0.00014056252,0.00007099036,0.00021697376,0.0003423844,0.00011004906],"domain_scores_gemma":[0.99910116,0.00023053677,0.00012830069,0.00025962302,0.0002362533,0.00004414237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000644428,0.0006668647,0.0016525066,0.0030499888,0.00041452036,0.0013423682,0.00080052787,0.0007388562,0.0038076434],"category_scores_gemma":[0.003525706,0.00021249393,0.0006094899,0.0035725185,0.000460212,0.0027171217,0.00092667964,0.0005088014,0.0025476785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005702979,0.00016115641,0.0029221298,0.0004939376,0.00013897811,0.00020152371,0.00013038902,0.018236041,0.093610786,0.0142403245,0.01453212,0.8547624],"study_design_scores_gemma":[0.00027862296,0.0015977215,0.024086926,0.00020265032,0.00045802514,0.0026010533,0.0005273371,0.7198169,0.13470648,0.04984642,0.06558871,0.00028918733],"about_ca_topic_score_codex":0.0025416913,"about_ca_topic_score_gemma":0.0026557497,"teacher_disagreement_score":0.0038076434,"about_ca_system_score_codex":0.0007220746,"about_ca_system_score_gemma":0.00054652937,"threshold_uncertainty_score":0.012737811},"labels":[],"label_agreement":null},{"id":"W2034826133","doi":"10.1155/2007/45364","title":"Carrier Frequency Offset Estimation and I/Q Imbalance Compensation for OFDM Systems","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Preamble; Orthogonal frequency-division multiplexing; Carrier frequency offset; Frequency offset; Estimator; Computer science; Algorithm; Offset (computer science); Telecommunications; Mathematics; Statistics","score_opus":0.014021758783889815,"score_gpt":0.2873850939578256,"score_spread":0.27336333517393574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034826133","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023441212,0.00041191338,0.97527814,0.000064590546,0.000027783703,0.000012734095,0.0000124320895,0.00014190345,0.00060930056],"genre_scores_gemma":[0.62040454,0.00066867453,0.37647474,0.00006334461,0.00012389883,0.00004971758,0.00008494557,0.000033442913,0.0020968046],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997396,0.00006232502,0.00001805421,0.000044887645,0.00011348968,0.000021797148],"domain_scores_gemma":[0.9997067,0.00014169667,0.000059650014,0.000026715963,0.00005807943,0.0000071884815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035585245,0.00041795973,0.00033745158,0.00029472326,0.00029214582,0.00032278436,0.00027327499,0.00044912274,0.00071481266],"category_scores_gemma":[0.0015785723,0.00019388419,0.00014727624,0.00038693516,0.00024181863,0.0006518799,0.000231098,0.00034633136,0.00025672503],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041670562,0.000078840945,0.0025281787,0.00020020426,0.00005053781,0.00025787068,0.00013782099,0.2450239,0.112064384,0.010914995,0.001329141,0.62699735],"study_design_scores_gemma":[0.000025511463,0.00014979612,0.0017424905,0.000014559316,0.000027817527,0.00029882425,0.000021423639,0.94391865,0.047591668,0.0031373447,0.003046884,0.00002499485],"about_ca_topic_score_codex":0.0011800639,"about_ca_topic_score_gemma":0.0011831084,"teacher_disagreement_score":0.0011800639,"about_ca_system_score_codex":0.0002343127,"about_ca_system_score_gemma":0.00036964778,"threshold_uncertainty_score":0.0023912787},"labels":[],"label_agreement":null},{"id":"W2035729910","doi":"10.1155/s1110865703306079","title":"Nonlinear System Identification Using Neural Networks Trained with Natural Gradient Descent","year":2003,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency","keywords":"Gradient descent; Nonlinear system; Artificial neural network; Convergence (economics); Computer science; Mean squared error; Filter (signal processing); Kalman filter; Extended Kalman filter; Control theory (sociology); Levenberg–Marquardt algorithm; Adaptive filter; Stochastic gradient descent; Kernel adaptive filter; Algorithm; Nonlinear conjugate gradient method; Gradient method; Artificial intelligence; Mathematics; Filter design; Computer vision; Statistics","score_opus":0.016125871334562798,"score_gpt":0.27179829719716897,"score_spread":0.2556724258626062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035729910","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025047645,0.00039520202,0.9719561,0.00010889667,0.000047356516,0.000041544812,0.000026394144,0.0005158621,0.0018610349],"genre_scores_gemma":[0.6568129,0.00037297382,0.33874986,0.000110764515,0.000042893807,0.0002104059,0.00012641987,0.000053568656,0.0035200974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997801,0.000072086754,0.00001702126,0.000050576004,0.000060616127,0.000019477098],"domain_scores_gemma":[0.999474,0.00025953073,0.0000867205,0.000057702182,0.00010919135,0.00001286621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083319977,0.0005530648,0.0006088565,0.00037153982,0.00030145844,0.00046642392,0.0005161854,0.00069732236,0.00080140174],"category_scores_gemma":[0.0023014138,0.00032140684,0.00037885274,0.0004325628,0.00047557178,0.0008849233,0.0006210393,0.00063335325,0.00035697423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056656107,0.000034040524,0.00074050843,0.000072581985,0.000044488377,0.00007620757,0.000056455465,0.9008921,0.0030497452,0.0052275825,0.00057270454,0.089176975],"study_design_scores_gemma":[0.000002451199,0.000010052522,0.00007394688,0.0000022377114,0.0000019519957,0.000006671913,0.0000012412953,0.99848926,0.000375705,0.00086645683,0.00016758998,0.0000024513251],"about_ca_topic_score_codex":0.0045903344,"about_ca_topic_score_gemma":0.004787302,"teacher_disagreement_score":0.0045903344,"about_ca_system_score_codex":0.0003888032,"about_ca_system_score_gemma":0.0005443922,"threshold_uncertainty_score":0.0091272},"labels":[],"label_agreement":null},{"id":"W2036633357","doi":"10.1155/2010/623540","title":"Advanced Equalization Techniques for Wireless Communications","year":2011,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University","funders":"","keywords":"Atlanta; Telecommunications; Computer science; Wireless; Electrical engineering; Engineering","score_opus":0.04527208174357795,"score_gpt":0.3291665287974841,"score_spread":0.28389444705390615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036633357","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067675374,0.021835672,0.9499881,0.0011345572,0.0016361012,0.00004601721,0.00011747309,0.0005075629,0.017967073],"genre_scores_gemma":[0.16654089,0.041932765,0.71742314,0.0013368931,0.0032082726,0.00018847325,0.0007767271,0.00021399469,0.06837877],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998436,0.000029067618,0.000010332649,0.000034286073,0.00006505918,0.000017560194],"domain_scores_gemma":[0.99978477,0.00006836605,0.000021092566,0.000037304533,0.00008174748,0.0000066903694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024808673,0.0005185454,0.0003314909,0.00052841316,0.00021010115,0.0005311425,0.0003375431,0.00055969413,0.005340109],"category_scores_gemma":[0.00078443496,0.00013372225,0.00027842834,0.0008687211,0.0002969299,0.0006872693,0.00049311144,0.0010520001,0.0031751522],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011389616,0.00006318477,0.0006488535,0.0005063527,0.00006554794,0.00020126994,0.000084346335,0.011398587,0.073359475,0.10002773,0.026284447,0.7872463],"study_design_scores_gemma":[0.00009013271,0.0003812263,0.004063239,0.000496999,0.00017831272,0.0030880421,0.00008878112,0.2516961,0.08214443,0.17645925,0.48117706,0.00013639321],"about_ca_topic_score_codex":0.00028193888,"about_ca_topic_score_gemma":0.00056579395,"teacher_disagreement_score":0.005340109,"about_ca_system_score_codex":0.00019563234,"about_ca_system_score_gemma":0.00029065367,"threshold_uncertainty_score":0.017864406},"labels":[],"label_agreement":null},{"id":"W2036727854","doi":"10.1155/2009/727196","title":"Downlink Resource Allocation for Autonomous Infrastructure-based Multihop Cellular Networks","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Base station; Relay; Telecommunications link; Knapsack problem; Transmitter power output; Mathematical optimization; Resource allocation; Throughput; Computer network; Cellular network; Power (physics); Wireless; Algorithm; Telecommunications; Mathematics","score_opus":0.017818442050379385,"score_gpt":0.29138216015064183,"score_spread":0.2735637181002625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036727854","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033345394,0.0005124514,0.9622731,0.00015029924,0.000024950452,0.000034636567,0.000056788347,0.00009252438,0.0035098607],"genre_scores_gemma":[0.9370438,0.0005808044,0.05960447,0.00006619689,0.00003915981,0.0001112909,0.00007580042,0.000029050689,0.0024494356],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999686,0.00011280802,0.00000866775,0.000049741742,0.00007719398,0.0000655518],"domain_scores_gemma":[0.99976367,0.00012595023,0.000032981843,0.00002325392,0.00003590879,0.000018208488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040169197,0.00047686644,0.0005029991,0.00029567,0.00038968597,0.0007938115,0.00071793876,0.00050129514,0.0008007849],"category_scores_gemma":[0.0010419352,0.00031892344,0.0002504648,0.0005321357,0.00040833693,0.0007037423,0.0005992431,0.00050392846,0.00018357755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026456486,0.000024272023,0.00023483079,0.000036886348,0.000011419014,0.00005483877,0.000038675,0.96384954,0.0020722917,0.013060721,0.00054666377,0.020043517],"study_design_scores_gemma":[0.0000021859576,0.000009383543,0.00004522324,0.0000015447545,0.0000021263622,0.000008702799,0.000008234861,0.9968657,0.00025172505,0.0025658233,0.00023697386,0.0000022441538],"about_ca_topic_score_codex":0.0037178244,"about_ca_topic_score_gemma":0.0036025364,"teacher_disagreement_score":0.0037178244,"about_ca_system_score_codex":0.0010119524,"about_ca_system_score_gemma":0.0006884148,"threshold_uncertainty_score":0.007392347},"labels":[],"label_agreement":null},{"id":"W2037086293","doi":"10.1155/asp.2005.346","title":"A New Time-Hopping Multiple Access Communication System Simulator: Application to Ultra-Wideband","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Ultra-Wideband Communications Technology","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universidad Politécnica de Madrid; Polytechnique Montréal","keywords":"Time-hopping; Ultra-wideband; Computer science; Wideband; Wireless; Multipath propagation; Electronic engineering; Transmission (telecommunications); Frequency-hopping spread spectrum; Communications system; Random access; Real-time computing; Telecommunications; Computer network; Channel (broadcasting); Engineering","score_opus":0.009411432151636557,"score_gpt":0.2739107364398597,"score_spread":0.26449930428822316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037086293","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017082792,0.000085154126,0.9793839,0.00007329874,0.00005738166,0.00007511287,0.000103810875,0.0010447626,0.0020938579],"genre_scores_gemma":[0.4398624,0.00036255424,0.5525113,0.00010483759,0.000048161663,0.00038988574,0.0004054936,0.00028186574,0.0060335714],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984527,0.00004664252,0.000010822225,0.000016371378,0.000068320325,0.000012508897],"domain_scores_gemma":[0.99942565,0.00027490637,0.000046451718,0.00007389351,0.00015241918,0.000026730697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042952958,0.00030868777,0.000370958,0.0001978802,0.00023667408,0.00036082472,0.00082370045,0.0007246707,0.0026289932],"category_scores_gemma":[0.0012920888,0.00015526504,0.0002710427,0.00022765335,0.00019908042,0.0004874692,0.00039730433,0.0007271448,0.00047030812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000104688865,0.00007086008,0.0009515929,0.00013401764,0.000061233244,0.00015506695,0.00013439624,0.90847784,0.021870205,0.015350714,0.0016037297,0.051085625],"study_design_scores_gemma":[0.000009342935,0.000016708353,0.000043942047,0.0000024689423,0.0000040030013,0.000024923049,0.0000030816018,0.99511456,0.0023227958,0.0006202838,0.0018343364,0.0000035068301],"about_ca_topic_score_codex":0.0011004499,"about_ca_topic_score_gemma":0.0011628683,"teacher_disagreement_score":0.0026289932,"about_ca_system_score_codex":0.0002447055,"about_ca_system_score_gemma":0.0004629066,"threshold_uncertainty_score":0.008794844},"labels":[],"label_agreement":null},{"id":"W2037551279","doi":"10.1155/2010/323125","title":"Time-Frequency Analysis and Hermite Projection Method Applied to Swallowing Accelerometry Signals","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Dysphagia Assessment and Management","field":"Health Professions","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; Toronto Rehabilitation Institute; University of Toronto","funders":"Canada Research Chairs; Toronto Rehabilitation Institute; Ontario Centres of Excellence","keywords":"Hermite polynomials; Projection (relational algebra); Computer science; Hermite interpolation; Time–frequency analysis; Swallowing; Signal processing; Noise (video); Frequency analysis; Accelerometer; Instantaneous phase; SIGNAL (programming language); Artificial intelligence; Computer vision; Mathematics; Algorithm; Image (mathematics); Telecommunications; Filter (signal processing); Mathematical analysis; Medicine","score_opus":0.02721616424103676,"score_gpt":0.4330739784276451,"score_spread":0.4058578141866084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037551279","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008364733,0.00007623036,0.9908825,0.000028871375,0.000021191312,0.000012178364,0.00001548182,0.00008534814,0.0005135005],"genre_scores_gemma":[0.1945141,0.00075305114,0.8008705,0.000039160903,0.00008357936,0.00008960858,0.00009408665,0.00009948037,0.0034564883],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996031,0.00014840714,0.000019496989,0.000059362595,0.00015160751,0.000018034347],"domain_scores_gemma":[0.9994973,0.00025949962,0.000050702743,0.000053555377,0.00011889521,0.000019914249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006915705,0.0005809485,0.00036496058,0.0006881377,0.00028970835,0.0007296945,0.00026328524,0.000490178,0.0016410712],"category_scores_gemma":[0.0018096529,0.0002246827,0.0005804869,0.00087545445,0.00059087854,0.0007516977,0.00041623233,0.00070164195,0.0004931359],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003323795,0.000106354375,0.0015050822,0.00033658673,0.000100263576,0.00041331226,0.00043434795,0.17241749,0.17693572,0.096424825,0.0014640397,0.5495297],"study_design_scores_gemma":[0.000008167146,0.00009483444,0.0012311899,0.000010841298,0.000018408742,0.00031514495,0.000049558388,0.9636776,0.020024365,0.011295858,0.0032371448,0.00003696336],"about_ca_topic_score_codex":0.0006560129,"about_ca_topic_score_gemma":0.0006785441,"teacher_disagreement_score":0.0016410712,"about_ca_system_score_codex":0.00018289094,"about_ca_system_score_gemma":0.00042360098,"threshold_uncertainty_score":0.005489886},"labels":[],"label_agreement":null},{"id":"W2038172264","doi":"10.1155/2008/261317","title":"A Full-Body Layered Deformable Model for Automatic Model-Based Gait Recognition","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"University of Toronto; Ontario Centres of Excellence; University of South Florida","keywords":"Gait; Silhouette; Computer science; Artificial intelligence; Computer vision; Dynamic time warping; Matching (statistics); Background subtraction; Gait analysis; Pattern recognition (psychology); Mathematics; Pixel; Physical medicine and rehabilitation","score_opus":0.0232364673225952,"score_gpt":0.2843414633018644,"score_spread":0.26110499597926917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038172264","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002805475,0.00013465226,0.99599993,0.000035948433,0.00003391787,0.000023914754,0.00011108743,0.00050482684,0.00035027825],"genre_scores_gemma":[0.26500246,0.0007073267,0.7279423,0.00018597377,0.0000530868,0.00028273257,0.0015940871,0.0002587831,0.003973315],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997377,0.000039527997,0.000020283178,0.00007476257,0.00010587778,0.000021950284],"domain_scores_gemma":[0.9997888,0.00005556357,0.000035537087,0.000054150703,0.000049202285,0.00001677058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003687072,0.0007750335,0.00067134725,0.0008686288,0.00017601105,0.00056708377,0.0012060174,0.0009703855,0.0014627345],"category_scores_gemma":[0.0011638281,0.0005434958,0.0013360127,0.0006815049,0.00030797848,0.00068403734,0.0006405813,0.00094976585,0.001189195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000090502144,0.00006313123,0.0013207621,0.00012735977,0.000105285515,0.00020440869,0.00006908982,0.6142727,0.03374256,0.006474111,0.0029352282,0.34059477],"study_design_scores_gemma":[0.0000018206389,0.0000127017165,0.00022914681,0.000006762707,0.0000060195066,0.000053660493,0.0000028319612,0.9963948,0.001428777,0.00079657306,0.0010582191,0.000008709404],"about_ca_topic_score_codex":0.0046692537,"about_ca_topic_score_gemma":0.004975525,"teacher_disagreement_score":0.0046692537,"about_ca_system_score_codex":0.0004366612,"about_ca_system_score_gemma":0.0005111758,"threshold_uncertainty_score":0.009284139},"labels":[],"label_agreement":null},{"id":"W2039494011","doi":"10.1155/s1110865704309170","title":"Comparative Genomics via Wavelet Analysis for Closely Related Bacteria","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Comparative genomics; Wavelet; Genome; Genomics; Biology; Computational biology; Computer science; Genetics; Artificial intelligence; Gene","score_opus":0.01865660204895807,"score_gpt":0.2976089521469759,"score_spread":0.27895235009801783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039494011","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.119728915,0.0033035527,0.87228656,0.00034990188,0.000132014,0.00010444701,0.0002527614,0.0006264182,0.0032154107],"genre_scores_gemma":[0.2562757,0.002221119,0.7391596,0.000086995315,0.00007818345,0.00028606938,0.0006091437,0.00014844566,0.0011347947],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993463,0.00030473174,0.000044709126,0.00011048037,0.00014543049,0.000048332593],"domain_scores_gemma":[0.9995735,0.00020445097,0.00006397952,0.000061264145,0.00005830604,0.000038536473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013503534,0.0004409462,0.00061477686,0.0026247068,0.00037951514,0.00091597374,0.00045091694,0.0004552571,0.0018214786],"category_scores_gemma":[0.0026428944,0.00022981722,0.0007311128,0.0023109084,0.0005601731,0.00089391734,0.0010996342,0.0010696271,0.0004931911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059628964,0.00012229955,0.0032128189,0.00085721177,0.00023660524,0.0012388015,0.00081988313,0.018986441,0.5537829,0.09041556,0.0017072789,0.32802397],"study_design_scores_gemma":[0.00018884867,0.001319553,0.037654918,0.00027252402,0.0002916937,0.003941498,0.0010688741,0.47666538,0.14021304,0.26078779,0.0773344,0.0002615603],"about_ca_topic_score_codex":0.00032726277,"about_ca_topic_score_gemma":0.00020772636,"teacher_disagreement_score":0.0026247068,"about_ca_system_score_codex":0.00040353023,"about_ca_system_score_gemma":0.00023652722,"threshold_uncertainty_score":0.007141471},"labels":[],"label_agreement":null},{"id":"W2040965106","doi":"10.1155/asp/2006/45742","title":"Performance Evaluation in Image Processing","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Image processing; Image (mathematics); Computer vision; Artificial intelligence","score_opus":0.012222669528326527,"score_gpt":0.2990612803208765,"score_spread":0.28683861079254996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040965106","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21974991,0.061089206,0.65228385,0.0038494926,0.0030627663,0.0010850513,0.004065946,0.012528619,0.04228511],"genre_scores_gemma":[0.79012674,0.0068560573,0.18106301,0.0006893299,0.0007763953,0.00032429173,0.006677868,0.0009955921,0.01249066],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98750055,0.0046661766,0.0008810556,0.0014169498,0.0047613517,0.0007738693],"domain_scores_gemma":[0.98117894,0.010853634,0.00079965364,0.001919056,0.004694656,0.00055407296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009181683,0.001555687,0.0018121791,0.0031685007,0.00088876055,0.0031496272,0.0014828983,0.0019482948,0.006899302],"category_scores_gemma":[0.032235935,0.00028950183,0.0007653576,0.003991594,0.00077612104,0.00212087,0.0012430323,0.0009844998,0.002903764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004502675,0.00071410986,0.00874758,0.0013862823,0.00056169444,0.0002569814,0.0001238977,0.09634653,0.014477975,0.007959694,0.033724774,0.83119774],"study_design_scores_gemma":[0.00025886708,0.0023489713,0.013892001,0.0001644819,0.00028089038,0.0010147677,0.00021888412,0.9094599,0.03842991,0.012448357,0.021383574,0.00009943913],"about_ca_topic_score_codex":0.0053704414,"about_ca_topic_score_gemma":0.0034652753,"teacher_disagreement_score":0.009181683,"about_ca_system_score_codex":0.0016964177,"about_ca_system_score_gemma":0.0014148968,"threshold_uncertainty_score":0.048557937},"labels":[],"label_agreement":null},{"id":"W2041100838","doi":"10.1155/2008/547923","title":"Hierarchical Fuzzy Feature Similarity Combination for Presentation Slide Retrieval","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Information retrieval; Feature (linguistics); Relevance (law); Disk formatting; Presentation (obstetrics); Relevance feedback; XML; Fuzzy logic; Scheme (mathematics); Data mining; Similarity (geometry); Artificial intelligence; Image retrieval; World Wide Web","score_opus":0.01656152424879052,"score_gpt":0.314791954584857,"score_spread":0.29823043033606644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041100838","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05309245,0.001221304,0.9416357,0.00010736763,0.000078834695,0.00018020195,0.00019504389,0.0016413272,0.0018476847],"genre_scores_gemma":[0.5359628,0.0005177707,0.4592127,0.000100740675,0.00018694114,0.00019400983,0.0006960978,0.000084984305,0.0030438926],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986185,0.00019524159,0.00011798905,0.00023579218,0.0007340328,0.00009847003],"domain_scores_gemma":[0.99934286,0.00015697356,0.000083033585,0.000104418956,0.0002780016,0.0000346513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090374297,0.0005345881,0.0009722132,0.0027890734,0.0004146743,0.00082702015,0.0010794587,0.0006329275,0.0023802766],"category_scores_gemma":[0.0025230462,0.00024679457,0.0009632068,0.0020654732,0.00031009773,0.0014067334,0.0007642112,0.0005080974,0.0010766068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005193523,0.00014340313,0.0013758267,0.00022708254,0.00013623711,0.00016757243,0.00013744777,0.020426719,0.08061429,0.0031288534,0.0034580594,0.8896651],"study_design_scores_gemma":[0.00012116218,0.0006987086,0.009549231,0.00003951698,0.00031937024,0.0009396101,0.00018568503,0.86957157,0.10143308,0.007209444,0.009803061,0.00012953313],"about_ca_topic_score_codex":0.0026536589,"about_ca_topic_score_gemma":0.002572151,"teacher_disagreement_score":0.0027890734,"about_ca_system_score_codex":0.00064267387,"about_ca_system_score_gemma":0.00052644697,"threshold_uncertainty_score":0.007962823},"labels":[],"label_agreement":null},{"id":"W2041773471","doi":"10.1155/asp/2006/95360","title":"A Systematic Approach to Modified BCJR MAP Algorithms for Convolutional Codes","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Communications Research Centre Canada; Defence Research and Development Canada; Department of National Defence","funders":"","keywords":"BCJR algorithm; Algorithm; Computer science; Convolutional code; Turbo code; Mathematics; Concatenated error correction code; Block code; Decoding methods","score_opus":0.022294441801497464,"score_gpt":0.29219158106603016,"score_spread":0.2698971392645327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041773471","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00080708065,0.00043232532,0.99640167,0.00008879182,0.00008217338,0.000046605895,0.000023093737,0.00012655646,0.0019917996],"genre_scores_gemma":[0.04148964,0.001953542,0.9516466,0.00021331414,0.00032752164,0.000266145,0.0001341682,0.00015610208,0.0038128223],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99802244,0.00053030095,0.0001858818,0.0002445879,0.00093218125,0.00008474856],"domain_scores_gemma":[0.9970036,0.0012738614,0.0002122104,0.0006109798,0.0008622752,0.000037173915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014598366,0.0014616158,0.00070070045,0.0016339957,0.0006847118,0.0013465662,0.0018725992,0.0011704704,0.0023888324],"category_scores_gemma":[0.009386136,0.0006874727,0.0011846811,0.0022472634,0.0015506432,0.002174604,0.0014407735,0.0028448175,0.0018096925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009947609,0.00008321628,0.00030726517,0.00047990296,0.00011989957,0.00016308282,0.0002405785,0.15920766,0.019613942,0.47552833,0.006639574,0.3375171],"study_design_scores_gemma":[0.000039705665,0.00015283603,0.00027861595,0.000098518874,0.000056950965,0.00068557466,0.000031988304,0.7009888,0.024366803,0.24027741,0.032924563,0.000098205295],"about_ca_topic_score_codex":0.0016184741,"about_ca_topic_score_gemma":0.0021159158,"teacher_disagreement_score":0.0023888324,"about_ca_system_score_codex":0.001025146,"about_ca_system_score_gemma":0.0015958081,"threshold_uncertainty_score":0.007991433},"labels":[],"label_agreement":null},{"id":"W2041884833","doi":"10.1155/asp/2006/52919","title":"FPGA Implementation of an MUD Based on Cascade Filters for a WCDMA System","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Field-programmable gate array; Computer science; Virtex; UMTS frequency bands; Embedded system; Computer architecture; MPSoC; Computer hardware; System on a chip; Computer network","score_opus":0.024615820206167545,"score_gpt":0.3572430310083744,"score_spread":0.33262721080220686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041884833","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20872232,0.0009131227,0.7668757,0.00019493657,0.00025082013,0.00018587586,0.00019778385,0.005378997,0.017280476],"genre_scores_gemma":[0.78797895,0.00024837442,0.20520656,0.0000895995,0.00004351972,0.0000638121,0.00011400412,0.000029942032,0.006225317],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99993503,0.000012513647,0.00000392909,0.000012870132,0.0000226124,0.000012967241],"domain_scores_gemma":[0.9999349,0.000020034295,0.000008340743,0.00000928992,0.00002091606,0.000006521388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009777067,0.0002792679,0.00016160434,0.0002992538,0.00020191485,0.00029519567,0.0003938747,0.00028902525,0.0028487702],"category_scores_gemma":[0.00021319772,0.00013276035,0.00013776441,0.0001439367,0.000101704485,0.00016198818,0.0000879249,0.00022862914,0.00047117076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010638686,0.0001623315,0.00245672,0.00041212508,0.00016412178,0.00088150345,0.0001698274,0.08020006,0.5109698,0.017309848,0.005486892,0.38072294],"study_design_scores_gemma":[0.00021286609,0.0018218491,0.005479038,0.00007976108,0.00016789576,0.0015788487,0.000050955994,0.6157239,0.34103975,0.0018242901,0.031961966,0.00005883834],"about_ca_topic_score_codex":0.0014181904,"about_ca_topic_score_gemma":0.0024452389,"teacher_disagreement_score":0.0028487702,"about_ca_system_score_codex":0.0002788462,"about_ca_system_score_gemma":0.0002865769,"threshold_uncertainty_score":0.009530127},"labels":[],"label_agreement":null},{"id":"W2042519643","doi":"10.1155/s1110865702204138","title":"A DSP Based POD Implementation for High Speed Multimedia Communications","year":2002,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge; University of Regina","funders":"","keywords":"Computer science; Elliptic Curve Digital Signature Algorithm; Encryption; Elliptic curve cryptography; Cryptography; Key (lock); Digital signal processing; Embedded system; Public-key cryptography; Computer hardware; Computer security","score_opus":0.04039586108695611,"score_gpt":0.34437499469247324,"score_spread":0.30397913360551715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042519643","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08523204,0.0003039102,0.8836815,0.00018085698,0.00037620656,0.0002838252,0.00015609294,0.007561444,0.022224164],"genre_scores_gemma":[0.7459348,0.0002130343,0.23409764,0.00018145937,0.000061734085,0.00015796829,0.00029362616,0.000117623356,0.018942054],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978036,0.000037416816,0.00001863539,0.000040250103,0.000092930604,0.000030486104],"domain_scores_gemma":[0.9997087,0.00005320208,0.000024046054,0.00007962758,0.000110259876,0.000024126912],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022720815,0.00028880793,0.0002507666,0.00037770183,0.000276908,0.00071761623,0.00072007766,0.00043155046,0.0067470986],"category_scores_gemma":[0.00069336686,0.00013795082,0.0001953358,0.00024295796,0.00017181368,0.00057530217,0.00026389543,0.00056861195,0.0018597152],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011739462,0.0004922323,0.002494368,0.00053730566,0.000077446944,0.0006613563,0.00021570441,0.011532318,0.46074075,0.036592614,0.01059766,0.47488436],"study_design_scores_gemma":[0.00046742952,0.002112586,0.0031855016,0.000088590816,0.00013888239,0.0030860235,0.000121967794,0.3092217,0.55930847,0.005434907,0.11676058,0.00007329518],"about_ca_topic_score_codex":0.00032753244,"about_ca_topic_score_gemma":0.0004935516,"teacher_disagreement_score":0.0067470986,"about_ca_system_score_codex":0.00027440052,"about_ca_system_score_gemma":0.00042240138,"threshold_uncertainty_score":0.022571266},"labels":[],"label_agreement":null},{"id":"W2043919758","doi":"10.1155/2010/390910","title":"Estimation of Time-Varying Coherence and Its Application in Understanding Brain Functional Connectivity","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"Coherence (philosophical gambling strategy); Magnetoencephalography; Computer science; Kernel (algebra); Artificial intelligence; Time–frequency analysis; Class (philosophy); Representation (politics); Pattern recognition (psychology); Mathematics; Statistical physics; Electroencephalography; Statistics; Pure mathematics; Radar; Physics","score_opus":0.036019654691439626,"score_gpt":0.30021757585182773,"score_spread":0.2641979211603881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043919758","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07791637,0.00077842036,0.91959286,0.00017041613,0.000023220719,0.000019959292,0.000097807635,0.00014360115,0.0012573688],"genre_scores_gemma":[0.8262109,0.0012300382,0.17127255,0.000041738716,0.00008179116,0.000050944833,0.00021214347,0.00006773887,0.0008322133],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997944,0.000064971915,0.000013755387,0.00006980074,0.00004123247,0.000015817383],"domain_scores_gemma":[0.9985461,0.0010083456,0.00023443876,0.000093389644,0.00008936203,0.00002835918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078313274,0.00037568348,0.00030643702,0.0013318342,0.00020294379,0.00047797733,0.00039238596,0.0005782992,0.0008593206],"category_scores_gemma":[0.004495387,0.0001553881,0.0003566878,0.001344311,0.0006737457,0.001509929,0.0004153894,0.00047789642,0.00014713305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019174909,0.00011057399,0.01332735,0.00039171652,0.00024584163,0.00053033116,0.00053162745,0.1595073,0.14927317,0.11923218,0.001387365,0.55527085],"study_design_scores_gemma":[0.000018342655,0.00015945383,0.025850952,0.00004330758,0.000080301856,0.0007334431,0.00016487119,0.8196819,0.022717815,0.12693076,0.0035191695,0.00009962286],"about_ca_topic_score_codex":0.00079631817,"about_ca_topic_score_gemma":0.00089659967,"teacher_disagreement_score":0.0013318342,"about_ca_system_score_codex":0.0002450492,"about_ca_system_score_gemma":0.00023636602,"threshold_uncertainty_score":0.0041416287},"labels":[],"label_agreement":null},{"id":"W2044303468","doi":"10.1155/2010/657323","title":"Wavefront Reconstruction of Elevation Circular Synthetic Aperture Radar Imagery Using a Cylindrical Green's Function","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; CancerCare Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; University of Manitoba","keywords":"Synthetic aperture radar; Radar; Elevation (ballistics); Computer science; Wavefront; Function (biology); Radar imaging; Computer vision; Artificial intelligence; Algorithm; Geology; Geometry; Mathematics; Optics; Physics; Telecommunications","score_opus":0.01152746879038628,"score_gpt":0.25777010586215354,"score_spread":0.24624263707176727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044303468","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10582272,0.000093040275,0.89182836,0.00009960473,0.000017488235,0.000034046305,0.00012307614,0.000558655,0.001422936],"genre_scores_gemma":[0.32672614,0.00025170745,0.6709179,0.000035469337,0.0000131396855,0.000029505592,0.000363767,0.000075480304,0.0015869329],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998847,0.000019504996,0.000006770872,0.000015885737,0.000057265963,0.000015805239],"domain_scores_gemma":[0.99973506,0.00008418925,0.000043440024,0.000051143183,0.000074135234,0.000012143113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031179577,0.0004774891,0.0002939249,0.00038182808,0.00013815853,0.00042453254,0.00026444174,0.00032090623,0.0007500748],"category_scores_gemma":[0.00072330807,0.00020872861,0.00032424074,0.00047509428,0.00025552968,0.0004919148,0.00039628684,0.000383736,0.00041327946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000477336,0.000095238545,0.0019204224,0.00019316259,0.00004082762,0.0004837156,0.0003050378,0.19098061,0.46555302,0.011446591,0.0018274633,0.32667655],"study_design_scores_gemma":[0.000026593552,0.00009846388,0.0019126954,0.000009631923,0.000009563449,0.00034156354,0.000077337536,0.89377344,0.10005337,0.0017368732,0.0019306184,0.00002981548],"about_ca_topic_score_codex":0.0010106758,"about_ca_topic_score_gemma":0.0012006623,"teacher_disagreement_score":0.0010106758,"about_ca_system_score_codex":0.0001759129,"about_ca_system_score_gemma":0.0005560409,"threshold_uncertainty_score":0.0025092363},"labels":[],"label_agreement":null},{"id":"W2044315089","doi":"10.1155/2010/108130","title":"Investigating the Bag-of-Words Method for 3D Shape Retrieval","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Benchmark (surveying); Discriminative model; Computer science; Task (project management); Artificial intelligence; Field (mathematics); Information retrieval; Image retrieval; Pattern recognition (psychology); Image (mathematics); Mathematics; Cartography","score_opus":0.028542796878046395,"score_gpt":0.35158813770176256,"score_spread":0.32304534082371616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044315089","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03740909,0.0035159595,0.95384264,0.00041248792,0.00022459647,0.00016025764,0.00027985833,0.0017458568,0.002409287],"genre_scores_gemma":[0.39957848,0.0027294934,0.5849893,0.00049488345,0.0005475776,0.00027489473,0.0021413635,0.0005012798,0.008742667],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99761957,0.00076968287,0.00013622374,0.00034627013,0.0009765764,0.0001516923],"domain_scores_gemma":[0.99693394,0.0016163825,0.00019755993,0.00045231666,0.0006978804,0.00010200188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028796692,0.0010231243,0.001478494,0.002703393,0.00051517214,0.0018122446,0.001676169,0.0017099532,0.004163503],"category_scores_gemma":[0.007603955,0.00043592614,0.00097167515,0.002885055,0.0008992686,0.0044905134,0.0016589509,0.00097248284,0.0035032204],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005716612,0.00019562988,0.0015006439,0.00041340583,0.00014332558,0.000107991764,0.0001800097,0.037310187,0.02444275,0.011090066,0.005888682,0.91815555],"study_design_scores_gemma":[0.00006634233,0.00041147595,0.0014141932,0.00003863769,0.00007235591,0.000521994,0.00020568765,0.9565604,0.019919807,0.011961592,0.008754798,0.000072785006],"about_ca_topic_score_codex":0.0035914946,"about_ca_topic_score_gemma":0.0026036594,"teacher_disagreement_score":0.004163503,"about_ca_system_score_codex":0.0004990813,"about_ca_system_score_gemma":0.0008701626,"threshold_uncertainty_score":0.015229285},"labels":[],"label_agreement":null},{"id":"W2044993457","doi":"10.1155/2007/76256","title":"Real-Time Cardiac Arrhythmia Detection Using WOLA Filterbank Analysis of EGM Signals","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Magnum Semiconductor (Canada)","funders":"","keywords":"Beat (acoustics); Computer science; Fibrillation; Noise (video); Filter bank; Electrocardiography; Atrial fibrillation; Speech recognition; Mathematics; Cardiology; Acoustics; Medicine; Artificial intelligence; Telecommunications; Physics; Channel (broadcasting)","score_opus":0.0172937320311474,"score_gpt":0.3357411566858372,"score_spread":0.3184474246546898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044993457","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04343357,0.00031000815,0.9546991,0.00008576019,0.00004068579,0.000024894742,0.0001044136,0.0009005935,0.00040108856],"genre_scores_gemma":[0.24060583,0.00034151203,0.7569255,0.00006158515,0.00004601039,0.00006684227,0.00030146036,0.00007466828,0.0015765536],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997632,0.00006379235,0.000018500636,0.000053484528,0.00008000705,0.000021134434],"domain_scores_gemma":[0.99966633,0.00016382574,0.000043952954,0.000047188834,0.00006611638,0.000012578619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081462314,0.0006182283,0.0005160846,0.0007608232,0.00015463283,0.0005402108,0.00034642065,0.0005341399,0.0008735133],"category_scores_gemma":[0.0013392594,0.00020201517,0.00030868573,0.00040020057,0.0002210816,0.00062561344,0.0003688721,0.0003985319,0.00053222093],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006200585,0.0001268094,0.0033456539,0.0001713625,0.00011681627,0.00024756527,0.0001385168,0.030642522,0.20237938,0.003659624,0.002100211,0.7564515],"study_design_scores_gemma":[0.000048132657,0.00021845454,0.01124356,0.000026810329,0.00007129315,0.00057353335,0.00003442912,0.8977594,0.0832764,0.0019372071,0.0047601513,0.000050660306],"about_ca_topic_score_codex":0.0004507059,"about_ca_topic_score_gemma":0.00091233506,"teacher_disagreement_score":0.0008735133,"about_ca_system_score_codex":0.00016785732,"about_ca_system_score_gemma":0.00023950684,"threshold_uncertainty_score":0.004308164},"labels":[],"label_agreement":null},{"id":"W2045033846","doi":"10.1186/1687-6180-2012-93","title":"An improved method for the removal of ring artifacts in high resolution CT imaging","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Research Foundation","keywords":"Artificial intelligence; Artifact (error); Computer science; Computer vision; Multislice; Detector; Ring (chemistry); Resolution (logic); Image processing; Image (mathematics); Nuclear medicine","score_opus":0.030753340259658812,"score_gpt":0.3983689172414482,"score_spread":0.36761557698178937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045033846","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013724865,0.00037080748,0.98474485,0.000053896194,0.00006727195,0.00004245043,0.000031585707,0.0007079979,0.0002562739],"genre_scores_gemma":[0.065346256,0.00032426775,0.9328503,0.000054051354,0.000055470355,0.00003823374,0.000095097865,0.00007611638,0.0011602485],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991866,0.00012779277,0.000066836605,0.00015831053,0.00041555753,0.00004488053],"domain_scores_gemma":[0.9987764,0.00032226718,0.00015810237,0.00023262626,0.00046036643,0.0000501307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008886851,0.00077953807,0.0007508129,0.0014873304,0.00032863533,0.0008143543,0.00091327267,0.0009447901,0.0011362621],"category_scores_gemma":[0.0019583642,0.0003678595,0.00079078024,0.0011231663,0.00046863934,0.0009390738,0.0006073033,0.00089538185,0.0009436305],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029658974,0.00009561861,0.0012942246,0.00028022635,0.0000941678,0.00023855065,0.00011157732,0.013668978,0.29829082,0.0022082822,0.0015392039,0.6818817],"study_design_scores_gemma":[0.00007080418,0.0003516386,0.005766111,0.000039452683,0.0001434346,0.0023937149,0.000039943407,0.68883204,0.2905079,0.0012892359,0.0104564745,0.00010916989],"about_ca_topic_score_codex":0.0011060543,"about_ca_topic_score_gemma":0.0016696643,"teacher_disagreement_score":0.0014873304,"about_ca_system_score_codex":0.00028608416,"about_ca_system_score_gemma":0.00087383925,"threshold_uncertainty_score":0.004699886},"labels":[],"label_agreement":null},{"id":"W2045116509","doi":"10.1155/asp.2005.1603","title":"Analysis of Optical CDMA Signal Transmission: Capacity Limits and Simulation Results","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"graph theory and CDMA systems","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Code division multiple access; Computer science; Bit error rate; Transmission (telecommunications); Additive white Gaussian noise; Turbo code; Electronic engineering; Channel (broadcasting); Throughput; Binary number; Decoding methods; Computer network; Telecommunications; Algorithm; Mathematics; Engineering; Wireless; Arithmetic","score_opus":0.018063042931133245,"score_gpt":0.2725134626304974,"score_spread":0.25445041969936416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045116509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7944272,0.0030625688,0.14963317,0.0012517326,0.000069529524,0.0001536607,0.0009810178,0.00065446424,0.04976663],"genre_scores_gemma":[0.98996395,0.000431944,0.0077860854,0.000054171924,0.000013772475,0.00008642114,0.00016091486,0.000040702023,0.0014620102],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992931,0.00029126223,0.000021659156,0.000039167742,0.0002035449,0.00015118155],"domain_scores_gemma":[0.9899198,0.008442992,0.00052141846,0.00027919371,0.00072866306,0.00010782368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013507934,0.00063194684,0.0006647701,0.0012225453,0.00053163985,0.0007447053,0.0008105912,0.0012145032,0.0021679932],"category_scores_gemma":[0.00820211,0.000248343,0.00039177967,0.0012124348,0.00078636245,0.00088948227,0.0006790807,0.0007383191,0.0001814918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040803618,0.000022643071,0.00057949015,0.000038873197,0.000009403492,0.000056701396,0.000053777574,0.98960996,0.00054710184,0.0072124465,0.00028666126,0.0015422095],"study_design_scores_gemma":[0.0000034826999,0.000008097644,0.00010030598,0.000008288598,0.000002431224,0.000013673567,0.000011710746,0.9982741,0.00036408834,0.0010990521,0.00011075015,0.0000041424873],"about_ca_topic_score_codex":0.010308144,"about_ca_topic_score_gemma":0.0036704508,"teacher_disagreement_score":0.010308144,"about_ca_system_score_codex":0.0016022818,"about_ca_system_score_gemma":0.0006306869,"threshold_uncertainty_score":0.020496309},"labels":[],"label_agreement":null},{"id":"W2045153903","doi":"10.1186/1687-6180-2014-85","title":"MMSE precoding for multiuser MISO downlink transmission with non-homogeneous user SNR conditions","year":2014,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Precoding; Telecommunications link; Base station; Channel state information; Computer science; Quantization (signal processing); Algorithm; Zero-forcing precoding; Minimum mean square error; Control theory (sociology); Transmission (telecommunications); Channel (broadcasting); Mathematics; MIMO; Estimator; Mathematical optimization; Wireless; Statistics; Telecommunications","score_opus":0.007836762995809295,"score_gpt":0.26023548799189405,"score_spread":0.25239872499608473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045153903","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021485431,0.000241625,0.97609335,0.00007241958,0.000022467084,0.00002247902,0.000058322938,0.00011994444,0.0018839125],"genre_scores_gemma":[0.83255833,0.000649647,0.1619693,0.00013903131,0.00007044917,0.000091801936,0.00018105729,0.000028126626,0.0043123052],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995964,0.000120874014,0.000021979373,0.00008038985,0.00012840872,0.000051896957],"domain_scores_gemma":[0.99960333,0.00017715052,0.0000642305,0.00005908721,0.000082974795,0.00001333441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045713506,0.00059468084,0.0005411913,0.00020301987,0.00021307316,0.00056975824,0.00042349863,0.0004034706,0.0010417234],"category_scores_gemma":[0.0017980584,0.00022923005,0.00034593852,0.00035435797,0.0004159953,0.0004718209,0.00048645918,0.00042853,0.00038545666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001954819,0.000052061656,0.0010921108,0.00020136294,0.000085930085,0.00021839445,0.00021636926,0.82504386,0.026869481,0.032953724,0.0013879131,0.11168334],"study_design_scores_gemma":[0.000010842138,0.000114174865,0.0003425158,0.000013278049,0.000017815264,0.00007010449,0.000030856376,0.9868526,0.0067907316,0.004614842,0.0011313806,0.000010943329],"about_ca_topic_score_codex":0.0018270576,"about_ca_topic_score_gemma":0.003125731,"teacher_disagreement_score":0.0018270576,"about_ca_system_score_codex":0.00034687857,"about_ca_system_score_gemma":0.0006846775,"threshold_uncertainty_score":0.0036328435},"labels":[],"label_agreement":null},{"id":"W2045527432","doi":"10.1155/2008/142013","title":"Advanced Signal Processing and Pattern Recognition Methods for Biometrics","year":2008,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Scientific Research and Discoveries","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"West virginia; Biometrics; Library science; Division (mathematics); Engineering; Telecommunications; Computer science; History; Archaeology; Artificial intelligence","score_opus":0.061323067193563535,"score_gpt":0.39893751168458463,"score_spread":0.33761444449102107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045527432","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037548502,0.018356932,0.96828395,0.0009031566,0.00075130095,0.00006357952,0.0003724072,0.00058783166,0.006925941],"genre_scores_gemma":[0.10581283,0.031797856,0.8310136,0.00082410587,0.0018352539,0.00028649298,0.0013493022,0.0001990591,0.026881553],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987752,0.00029694525,0.0000847946,0.00025364506,0.0005357656,0.000053653843],"domain_scores_gemma":[0.9989184,0.0003695372,0.000108330874,0.0002272956,0.0003453812,0.00003109289],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011059017,0.0008706984,0.0008977426,0.0020175828,0.00030563117,0.0013856653,0.00075442507,0.0013403452,0.0094192475],"category_scores_gemma":[0.0032060607,0.00029209824,0.00082245294,0.0026326415,0.0007936777,0.0015338361,0.0010567125,0.0014045855,0.008681898],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001053815,0.0000668107,0.0010045561,0.0006618583,0.00009869444,0.00021637505,0.00009306636,0.011888333,0.04507096,0.047080077,0.014955559,0.87875825],"study_design_scores_gemma":[0.000057057412,0.0004049387,0.008434584,0.00051580195,0.00014970849,0.004138641,0.00018159216,0.39968005,0.058844578,0.15605338,0.37131643,0.00022322398],"about_ca_topic_score_codex":0.0005179879,"about_ca_topic_score_gemma":0.000557941,"teacher_disagreement_score":0.0094192475,"about_ca_system_score_codex":0.00034918633,"about_ca_system_score_gemma":0.00041723443,"threshold_uncertainty_score":0.031510472},"labels":[],"label_agreement":null},{"id":"W2047530045","doi":"10.1155/2007/45194","title":"Recursive and Fast Recursive Capon Spectral Estimators","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Capon; Algorithm; Signal processing; Estimator; Recursive least squares filter; Statistical signal processing; Computer science; Spectral density estimation; Computational complexity theory; Adaptive filter; Mathematics; Digital signal processing; Beamforming; Statistics; Telecommunications; Fourier transform","score_opus":0.010060365212122056,"score_gpt":0.30398275454411977,"score_spread":0.2939223893319977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047530045","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029571669,0.0002123786,0.9952173,0.000055288943,0.00003161688,0.000018694298,0.000021467895,0.00028915267,0.0011968933],"genre_scores_gemma":[0.1233668,0.0005511329,0.86961406,0.00018346385,0.00012523442,0.00021139348,0.000288622,0.00025388662,0.0054054316],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988813,0.00035828934,0.000045659635,0.00017480641,0.00043368485,0.000106291816],"domain_scores_gemma":[0.996912,0.0017698935,0.00017784268,0.0003775504,0.000712044,0.000050613526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014487642,0.0012416496,0.00092339213,0.0011017795,0.0005488304,0.0013938926,0.0014433695,0.0015779313,0.0032068198],"category_scores_gemma":[0.010005533,0.00064448087,0.0006806296,0.0010235406,0.0008565669,0.002242374,0.0014327645,0.0012911932,0.0013399969],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023493833,0.00007074143,0.0010882181,0.0002080063,0.000078917314,0.00017649899,0.00026762794,0.36558864,0.017226528,0.1090096,0.0054018963,0.5006484],"study_design_scores_gemma":[0.000013366712,0.000022816892,0.0002907118,0.000018826317,0.0000109137445,0.00010178371,0.000018239418,0.9798402,0.0045682713,0.0114121195,0.00367788,0.000024889281],"about_ca_topic_score_codex":0.0023191012,"about_ca_topic_score_gemma":0.0033529403,"teacher_disagreement_score":0.0032068198,"about_ca_system_score_codex":0.00069444306,"about_ca_system_score_gemma":0.0011281021,"threshold_uncertainty_score":0.010727882},"labels":[],"label_agreement":null},{"id":"W2047534701","doi":"10.1155/2007/21515","title":"Visual Sensor Networks","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Infrared Target Detection Methodologies","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Session (web analytics); Digital watermarking; Multimedia; Focus (optics); Signal processing; Telecommunications; Digital signal processing; Computer security; World Wide Web; Image (mathematics); Artificial intelligence; Computer hardware","score_opus":0.01975251845048002,"score_gpt":0.3197547385019086,"score_spread":0.30000222005142857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047534701","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018159986,0.03226746,0.6116967,0.0043696356,0.0058843913,0.00064359134,0.0049651037,0.008164348,0.3138488],"genre_scores_gemma":[0.53503066,0.028564382,0.16662249,0.0025562078,0.0015959518,0.0005529247,0.011291724,0.00055158406,0.25323406],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99938715,0.0001086545,0.00003472674,0.00014477219,0.00026032716,0.00006439249],"domain_scores_gemma":[0.9996253,0.00006852498,0.000028639413,0.000077346696,0.0001724373,0.000027722608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031651053,0.00078531494,0.0005342211,0.0008656605,0.00036225942,0.0012032791,0.000942066,0.0008379211,0.019629762],"category_scores_gemma":[0.0011539854,0.00018217387,0.0002409776,0.0010190833,0.00021811601,0.0013397487,0.0009457186,0.0006939936,0.008411291],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024823868,0.00007603608,0.000902903,0.0005141913,0.00007381592,0.00028029006,0.00005487543,0.014832995,0.016030207,0.029834978,0.1359512,0.8012002],"study_design_scores_gemma":[0.00005710422,0.0002026566,0.0018579541,0.00019483888,0.000038472008,0.0012747593,0.00015613963,0.25021365,0.019617012,0.04409065,0.6822356,0.000061172694],"about_ca_topic_score_codex":0.0013569082,"about_ca_topic_score_gemma":0.0018505228,"teacher_disagreement_score":0.019629762,"about_ca_system_score_codex":0.00044505467,"about_ca_system_score_gemma":0.00040340115,"threshold_uncertainty_score":0.06566805},"labels":[],"label_agreement":null},{"id":"W2048114889","doi":"10.1155/2008/529879","title":"Biometric Methods for Secure Communications in Body Sensor Networks: Resource-Efficient Key Management and Signal-Level Data Scrambling","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Encryption; Secure communication; Cryptography; Key (lock); Biometrics; Scrambling; Key management; Context (archaeology); Computer security; Computer network; Distributed computing; Algorithm","score_opus":0.11870241365886368,"score_gpt":0.4260407637518721,"score_spread":0.3073383500930084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048114889","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009229011,0.0025864216,0.98500407,0.00036362294,0.0000776245,0.00008641811,0.000018045372,0.00024109305,0.0023935596],"genre_scores_gemma":[0.4498296,0.0048582563,0.53969234,0.00026655753,0.00023807297,0.00033666525,0.000068354726,0.00007419389,0.004636013],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989208,0.00036562962,0.00006752515,0.00011199869,0.00048290894,0.0000512009],"domain_scores_gemma":[0.9989459,0.0003591963,0.00023983352,0.0002784841,0.0001486144,0.000028051078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011742696,0.0005173521,0.0005142792,0.0006598847,0.00042671422,0.0008810385,0.0007601503,0.00076988986,0.0016066356],"category_scores_gemma":[0.0023519078,0.00023194656,0.0003127142,0.0006481237,0.0009634514,0.0019568242,0.0010396701,0.0008104271,0.00083922036],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006004014,0.0001680303,0.0007354101,0.001001984,0.000080189646,0.00030411064,0.0004250767,0.043899503,0.22095619,0.20589766,0.003201982,0.52272946],"study_design_scores_gemma":[0.00018459621,0.0010153257,0.0016243112,0.00029759223,0.000090329166,0.0022970445,0.00024474482,0.62043697,0.23166275,0.08974309,0.052235797,0.00016745854],"about_ca_topic_score_codex":0.00017090653,"about_ca_topic_score_gemma":0.00017331031,"teacher_disagreement_score":0.0016066356,"about_ca_system_score_codex":0.00047492355,"about_ca_system_score_gemma":0.00047882413,"threshold_uncertainty_score":0.006210208},"labels":[],"label_agreement":null},{"id":"W2050328357","doi":"10.1186/1687-6180-2014-133","title":"Joint mean angle of arrival, angular and Doppler spreads estimation in macrocell environments","year":2014,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Macrocell; Non-line-of-sight propagation; Estimator; Angle of arrival; Computer science; Doppler effect; Algorithm; Joint (building); Orthogonality; Channel (broadcasting); Direction of arrival; Cramér–Rao bound; Minimum mean square error; Time of arrival; Wireless; Telecommunications; Estimation theory; Mathematics; Statistics; Physics; Base station; Antenna (radio); Geometry; Engineering","score_opus":0.011800634351273653,"score_gpt":0.26937291122214674,"score_spread":0.2575722768708731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050328357","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0151475165,0.0002457781,0.9840416,0.000035195124,0.000014679346,0.000006510157,0.000033644363,0.00018515025,0.00028995384],"genre_scores_gemma":[0.546746,0.00073733064,0.4504111,0.00007320896,0.00011674974,0.00005489779,0.00028573658,0.00008178063,0.0014931074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953973,0.000110498484,0.000024065068,0.00008345621,0.00018741778,0.000054845306],"domain_scores_gemma":[0.998958,0.0004745461,0.000178267,0.00011905827,0.00022448917,0.000045676425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006086012,0.0008509025,0.0008930308,0.00058499555,0.0002382394,0.0007885799,0.00061945274,0.0004183847,0.00042949684],"category_scores_gemma":[0.0026369083,0.0003834577,0.00041490662,0.0007076518,0.00034999687,0.0010880838,0.00093412877,0.0007028265,0.00038299337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028734276,0.000063661224,0.0061253393,0.00013186283,0.00015619009,0.00019041073,0.00012318145,0.62996715,0.03232116,0.011927753,0.001165602,0.31754035],"study_design_scores_gemma":[0.000011070239,0.00005237598,0.0012782383,0.0000076050105,0.000027413533,0.00015284661,0.000023524011,0.98764765,0.006796753,0.0030545716,0.0009253718,0.000022692742],"about_ca_topic_score_codex":0.0011898521,"about_ca_topic_score_gemma":0.0020723497,"teacher_disagreement_score":0.0011898521,"about_ca_system_score_codex":0.00021989005,"about_ca_system_score_gemma":0.00082039204,"threshold_uncertainty_score":0.0032186508},"labels":[],"label_agreement":null},{"id":"W2051172238","doi":"10.1155/2010/380349","title":"Parametric Time-Frequency Analysis and Its Applications in Music Classification","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Linear discriminant analysis; Matching pursuit; Pattern recognition (psychology); Discriminant; Artificial intelligence; Computer science; Feature (linguistics); SIGNAL (programming language); Time–frequency analysis; Parametric statistics; Spectrogram; Speech recognition; Range (aeronautics); Feature extraction; Signal processing; Mathematics; Statistics; Computer vision","score_opus":0.01733537147191682,"score_gpt":0.2911786061219365,"score_spread":0.2738432346500197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051172238","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022971883,0.010538633,0.9597293,0.0006146573,0.00018146471,0.000052330764,0.00016252097,0.0006174153,0.005131752],"genre_scores_gemma":[0.39705348,0.011985682,0.5859658,0.00015682795,0.0006847188,0.0000964369,0.00037108466,0.00015250452,0.0035335105],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939036,0.00015259386,0.00004805271,0.0001380132,0.00024026263,0.000030656836],"domain_scores_gemma":[0.99775237,0.001530398,0.00019135031,0.0002187276,0.00025311628,0.00005397252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011328835,0.0007022828,0.00073158665,0.002560838,0.00041847545,0.0008565403,0.0005470362,0.0011413314,0.0029716145],"category_scores_gemma":[0.0044587874,0.0002517776,0.0007318879,0.004065237,0.00092879764,0.001053776,0.0006486554,0.0009427076,0.0013811081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000143395,0.00010473629,0.0032655047,0.00029820405,0.00009024872,0.00030280737,0.00017697566,0.04654973,0.022903234,0.016322836,0.0023197804,0.9075226],"study_design_scores_gemma":[0.00003345329,0.00027873478,0.011929402,0.00010582756,0.00013437969,0.0015013944,0.00024187329,0.8662854,0.019922646,0.06887969,0.030566772,0.00012040193],"about_ca_topic_score_codex":0.0008513972,"about_ca_topic_score_gemma":0.00063947175,"teacher_disagreement_score":0.0029716145,"about_ca_system_score_codex":0.00021177386,"about_ca_system_score_gemma":0.00029380724,"threshold_uncertainty_score":0.0099410415},"labels":[],"label_agreement":null},{"id":"W2052110378","doi":"10.1155/2007/29749","title":"Eigenstructures of MIMO Fading Channel Correlation Matrices and Optimum Linear Precoding Designs for Maximum Ergodic Capacity","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Precoding; MIMO; Spatial correlation; Fading; Channel capacity; Ergodic theory; Transmitter; Mathematics; Eigenvalues and eigenvectors; Channel (broadcasting); Transformation (genetics); Topology (electrical circuits); Algebraic number; Computer science; Control theory (sociology); Telecommunications; Mathematical analysis; Physics","score_opus":0.02452754592069542,"score_gpt":0.27909681771464684,"score_spread":0.2545692717939514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052110378","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023288751,0.00023148017,0.97132933,0.00019817948,0.00001647683,0.00002350036,0.00006519964,0.00009233498,0.0047547384],"genre_scores_gemma":[0.8229677,0.0010596131,0.17166051,0.0001491945,0.000102377184,0.00023816737,0.00018173296,0.00008916936,0.0035514177],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993703,0.00029817558,0.00002157496,0.000075208554,0.0001648698,0.00006986741],"domain_scores_gemma":[0.9981553,0.0011865747,0.00018963056,0.00016245194,0.00025396483,0.000052015537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010378126,0.0007628047,0.00051731785,0.00058132986,0.00035317874,0.00080529705,0.00032412793,0.00058375933,0.0021194427],"category_scores_gemma":[0.004887087,0.0005476442,0.00046347178,0.00062908704,0.001307875,0.0010678642,0.0005819846,0.0007896346,0.00063186913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008087819,0.00004423631,0.00039724764,0.00007737105,0.000030730967,0.00012837436,0.00015586423,0.5961339,0.011600277,0.36163843,0.0018620824,0.027850552],"study_design_scores_gemma":[0.000012772887,0.00004711139,0.000269228,0.000019802043,0.0000073741016,0.00008036694,0.00003083553,0.8253513,0.0023782651,0.1710346,0.00074241834,0.000025994415],"about_ca_topic_score_codex":0.0005996479,"about_ca_topic_score_gemma":0.00078139734,"teacher_disagreement_score":0.0021194427,"about_ca_system_score_codex":0.0006389238,"about_ca_system_score_gemma":0.00091822504,"threshold_uncertainty_score":0.0070902705},"labels":[],"label_agreement":null},{"id":"W2053702202","doi":"10.1155/asp/2006/42737","title":"A New Position Location System Using DTV Transmitter Identification Watermark Signals","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Communications Research Centre Canada","funders":"","keywords":"Transmitter; Global Positioning System; Computer science; SIGNAL (programming language); Synchronization (alternating current); Digital television; Position (finance); Digital watermarking; Positioning system; Watermark; Electronic engineering; Telecommunications; Acoustics; Computer vision; Engineering; Physics","score_opus":0.00791523779757921,"score_gpt":0.2410611767967255,"score_spread":0.2331459389991463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053702202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0246045,0.00069506525,0.9688401,0.00024414447,0.00045277653,0.00008190366,0.00008401788,0.0022415563,0.0027559388],"genre_scores_gemma":[0.4234839,0.0010844024,0.5542774,0.00039270858,0.00056395977,0.00018248089,0.00037134232,0.00008693924,0.01955686],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995055,0.000061241226,0.00004090258,0.00012353172,0.00023011226,0.000038765396],"domain_scores_gemma":[0.99942577,0.0000729644,0.0001327007,0.000117103824,0.00020252974,0.000048972393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036077833,0.00047448638,0.00067550415,0.0006274505,0.0003271371,0.0008495171,0.0013184701,0.0010819755,0.0019300415],"category_scores_gemma":[0.0008283554,0.00030343275,0.00025929319,0.0006395442,0.00031773894,0.0018090844,0.0010662718,0.0008039672,0.0016112614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055870996,0.00011492713,0.0016988895,0.00050244346,0.00007974363,0.00060108776,0.0003122959,0.008491629,0.44153398,0.017084531,0.005227616,0.5237942],"study_design_scores_gemma":[0.0004566667,0.0025296288,0.0027506116,0.000109059394,0.0003188011,0.0045651714,0.00011325402,0.42971364,0.43440494,0.0038064232,0.12101088,0.0002208814],"about_ca_topic_score_codex":0.0002712676,"about_ca_topic_score_gemma":0.00035812412,"teacher_disagreement_score":0.0019300415,"about_ca_system_score_codex":0.00026442963,"about_ca_system_score_gemma":0.00038016244,"threshold_uncertainty_score":0.0064566135},"labels":[],"label_agreement":null},{"id":"W2054898736","doi":"10.1155/asp/2006/35352","title":"Spectrally Efficient Communication over Time-Varying Frequency-Selective Mobile Channels: Variable-Size Burst Construction and Adaptive Modulation","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Link adaptation; Spectral efficiency; Channel (broadcasting); Quality of service; Modulation (music); Key (lock); Fading; Variable (mathematics); Burst mode (computing); Real-time computing; Adaptation (eye); Electronic engineering; Telecommunications; Mathematics; Engineering","score_opus":0.011324883805544481,"score_gpt":0.2727373087615287,"score_spread":0.2614124249559842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054898736","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043707658,0.0013882659,0.9526811,0.00014459228,0.000037266414,0.00003199742,0.000012872494,0.00012146408,0.001874806],"genre_scores_gemma":[0.8171984,0.0012449365,0.17982937,0.000067954075,0.0001061745,0.000107267784,0.000031722877,0.000033942335,0.0013801779],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996518,0.00015351258,0.000014182049,0.00003531668,0.000101080645,0.00004416425],"domain_scores_gemma":[0.99916387,0.00052870275,0.00011012792,0.000098901306,0.00007489573,0.000023444993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006688212,0.00043875477,0.00043429068,0.0003953141,0.00032025584,0.00053313584,0.0005387153,0.0004047073,0.0003976795],"category_scores_gemma":[0.0016884643,0.00019096059,0.00022161091,0.0005637452,0.0007915281,0.00065659184,0.00071642076,0.000560719,0.00011094308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005838417,0.0001400194,0.0013758731,0.00024170193,0.0000756762,0.00022642178,0.0004127785,0.54189295,0.0755935,0.1071092,0.0014570806,0.27089098],"study_design_scores_gemma":[0.000029397746,0.00014695707,0.00025385633,0.000014908486,0.000017051636,0.0001444033,0.000024469822,0.9805038,0.0073529533,0.009667912,0.0018252486,0.000019036012],"about_ca_topic_score_codex":0.0005498213,"about_ca_topic_score_gemma":0.00058810745,"teacher_disagreement_score":0.0006688212,"about_ca_system_score_codex":0.00032275973,"about_ca_system_score_gemma":0.00031691967,"threshold_uncertainty_score":0.0035371184},"labels":[],"label_agreement":null},{"id":"W2059936181","doi":"10.1155/asp.2005.892","title":"Performance Evaluation of Linear Turbo Receivers Using Analytical Extrinsic Information Transfer Functions","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Comisión Nacional de Investigación Científica y Tecnológica; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Turbo; Turbo equalizer; Algorithm; Turbo code; EXIT chart; Channel (broadcasting); Transmission (telecommunications); Interference (communication); Information transfer; Decoding methods; Transceiver; Telecommunications; Wireless; Block code; Concatenated error correction code","score_opus":0.035795987266845776,"score_gpt":0.31700398544162006,"score_spread":0.28120799817477427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059936181","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44920027,0.0016217157,0.53653663,0.00032370657,0.00003378106,0.00011133804,0.00015060374,0.0009685139,0.011053446],"genre_scores_gemma":[0.97606796,0.00035162928,0.022319395,0.00003970002,0.000015185901,0.00003681041,0.00006458838,0.000049500573,0.0010552602],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975274,0.0013483209,0.000094443625,0.0001297081,0.00070415734,0.0001959713],"domain_scores_gemma":[0.9910744,0.006675237,0.00057863235,0.00042960234,0.001145368,0.000096675234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032459681,0.0011408156,0.0009891872,0.0008838354,0.0004649395,0.0011404026,0.0008204666,0.0014562807,0.0011876838],"category_scores_gemma":[0.014042353,0.0003593541,0.00045949247,0.00085092767,0.0013036248,0.0012313811,0.0010485401,0.0004866087,0.00045307187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041391418,0.000044014003,0.0011257178,0.00013003922,0.000047416157,0.0001450886,0.000084399,0.97470903,0.007097579,0.005265662,0.00014479253,0.010792307],"study_design_scores_gemma":[0.000013152536,0.00017530944,0.0002352953,0.00001734652,0.000016434791,0.00009913357,0.000020436151,0.9883642,0.009734957,0.0012174023,0.00008835793,0.000017891865],"about_ca_topic_score_codex":0.0015185146,"about_ca_topic_score_gemma":0.0007394236,"teacher_disagreement_score":0.0032459681,"about_ca_system_score_codex":0.0013569794,"about_ca_system_score_gemma":0.0007267285,"threshold_uncertainty_score":0.017166495},"labels":[],"label_agreement":null},{"id":"W2061106957","doi":"10.1155/2007/45812","title":"Advanced Signal Processing and Computational Intelligence Techniques for Power Line Communications","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Signal processing; Line (geometry); Power (physics); SIGNAL (programming language); Digital signal processing; Power-line communication; Telecommunications; Computer hardware; Mathematics","score_opus":0.02607536784492221,"score_gpt":0.3436217252496064,"score_spread":0.3175463574046842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061106957","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023351929,0.0036268393,0.9907974,0.0005495069,0.00023656005,0.000012529885,0.000040296807,0.00012877982,0.002272823],"genre_scores_gemma":[0.15793715,0.012622128,0.8168387,0.00041535564,0.0013775005,0.00012687327,0.0002317398,0.00008746615,0.0103630535],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972945,0.00008356867,0.000020404268,0.000041538893,0.00010984443,0.000015136467],"domain_scores_gemma":[0.9994342,0.00030901362,0.000042728243,0.000078144956,0.00012279059,0.000012994607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040163798,0.00062615064,0.00063559215,0.0005750147,0.00019909388,0.0008551739,0.00043025738,0.00062970276,0.0033068827],"category_scores_gemma":[0.0018255955,0.00018129325,0.00039086255,0.0012734291,0.00043310376,0.0010495896,0.0005615277,0.0015598402,0.0011437322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009772611,0.000083691986,0.0003455086,0.00035392915,0.00007480026,0.00011789029,0.00008556497,0.13522771,0.012757805,0.1348997,0.010403505,0.70555216],"study_design_scores_gemma":[0.000016772026,0.000058969224,0.00032154494,0.000032271968,0.000020751771,0.00011317582,0.00002003516,0.88217044,0.0028562439,0.10222248,0.012153904,0.0000134478405],"about_ca_topic_score_codex":0.000645001,"about_ca_topic_score_gemma":0.00070175435,"teacher_disagreement_score":0.0033068827,"about_ca_system_score_codex":0.00019232191,"about_ca_system_score_gemma":0.00032366352,"threshold_uncertainty_score":0.011062682},"labels":[],"label_agreement":null},{"id":"W2062309565","doi":"10.1155/2010/864032","title":"Vehicular Ad Hoc Networks","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Wireless ad hoc network; Vehicular ad hoc network; Mobile ad hoc network; Computer network; Telecommunications; Wireless","score_opus":0.0054809330506329435,"score_gpt":0.23572899648807905,"score_spread":0.2302480634374461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062309565","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006965956,0.07060783,0.45972553,0.0101246,0.023407381,0.0024415625,0.015629308,0.011190939,0.39990687],"genre_scores_gemma":[0.3076406,0.14268108,0.13322732,0.009007241,0.011363752,0.0037914023,0.053710826,0.0009848227,0.33759293],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99735594,0.00063956383,0.00033773558,0.00039601894,0.0009936176,0.00027718017],"domain_scores_gemma":[0.9979221,0.00047147894,0.00022437019,0.00036546984,0.0008372895,0.00017939192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094091834,0.001740591,0.0015963255,0.0019993484,0.0011109816,0.0047197687,0.0026083977,0.0025044864,0.02944116],"category_scores_gemma":[0.0036646833,0.0003978782,0.0006748983,0.0034572654,0.0005857071,0.0030995894,0.00284896,0.002257696,0.031723626],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016602819,0.00010074499,0.0014703582,0.0017477829,0.00014743593,0.0008862047,0.00013660663,0.018495312,0.0031388046,0.09243688,0.3796579,0.501616],"study_design_scores_gemma":[0.00003904789,0.00010593354,0.00044574897,0.000365099,0.00003803786,0.0008339867,0.00014081896,0.026894655,0.0009669636,0.03728595,0.93282366,0.000060133254],"about_ca_topic_score_codex":0.002138537,"about_ca_topic_score_gemma":0.0014951342,"teacher_disagreement_score":0.02944116,"about_ca_system_score_codex":0.0009121908,"about_ca_system_score_gemma":0.0015615618,"threshold_uncertainty_score":0.09849048},"labels":[],"label_agreement":null},{"id":"W2064513814","doi":"10.1155/2007/12172","title":"Blind Identification of FIR Channels in the Presence of Unknown Noise","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Upsampling; Subspace topology; Computer science; Noise (video); Channel (broadcasting); Algorithm; Identification (biology); Finite impulse response; Linear subspace; Distortion (music); Mathematics; Artificial intelligence; Telecommunications; Bandwidth (computing); Image (mathematics)","score_opus":0.025010819035043735,"score_gpt":0.340229834089079,"score_spread":0.31521901505403527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064513814","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054950345,0.00013125583,0.94404006,0.0000678551,0.000028289533,0.000014863473,0.000034560187,0.0002598452,0.00047291952],"genre_scores_gemma":[0.59173506,0.00021528473,0.4066489,0.00004612587,0.00005683131,0.00004160438,0.00012218067,0.000020874717,0.0011130512],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99935836,0.00024278581,0.00002951028,0.00013286828,0.0001755399,0.000060928254],"domain_scores_gemma":[0.99846363,0.0009845152,0.00017697166,0.00013938238,0.00019620461,0.00003934866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008587186,0.0004917821,0.00077475363,0.0005510411,0.0002734126,0.00051631854,0.00040158324,0.00072384457,0.00053014635],"category_scores_gemma":[0.0041722865,0.00021625396,0.00026631152,0.0005008538,0.0006822681,0.00061705307,0.0006120145,0.0004994044,0.00021106952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010575334,0.00013788567,0.0031772116,0.00019870055,0.00007694052,0.00030375042,0.00012159459,0.58509225,0.079240635,0.022599425,0.0014043256,0.30658978],"study_design_scores_gemma":[0.000016072594,0.000038967803,0.00041333912,0.000004791122,0.00000634594,0.00007054448,0.000010349376,0.9813731,0.014596665,0.0031311137,0.0003288299,0.000009994864],"about_ca_topic_score_codex":0.0012849009,"about_ca_topic_score_gemma":0.0011590288,"teacher_disagreement_score":0.0012849009,"about_ca_system_score_codex":0.00026468415,"about_ca_system_score_gemma":0.00089988444,"threshold_uncertainty_score":0.004541397},"labels":[],"label_agreement":null},{"id":"W2065133500","doi":"10.1186/1687-6180-2011-94","title":"Advances in angle-of-arrival and multidimensional signal processing for localization and communications","year":2011,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Angle of arrival; SIGNAL (programming language); Computer science; Signal processing; Direction of arrival; Antenna array; Antenna (radio); Telecommunications","score_opus":0.025390338989777723,"score_gpt":0.28260221887654136,"score_spread":0.25721187988676364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065133500","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034077468,0.022520734,0.9608675,0.0013793698,0.00087557785,0.00003992463,0.0001487074,0.00060193316,0.010158524],"genre_scores_gemma":[0.096937016,0.06408265,0.823947,0.0009486387,0.0023943454,0.00017601065,0.0006086526,0.00022420984,0.010681433],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99855393,0.0003760823,0.000108902175,0.00024338637,0.00065385626,0.00006382996],"domain_scores_gemma":[0.995968,0.0018831841,0.00030363558,0.0004480479,0.0013153127,0.000081881706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014870479,0.0011806784,0.00087007723,0.0017857067,0.00031141672,0.0016863438,0.0009004445,0.0013315533,0.0051843785],"category_scores_gemma":[0.004754112,0.0004039006,0.00062896445,0.0034717415,0.0008084036,0.0029443074,0.0015414738,0.0023231767,0.004042101],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016034153,0.00011673108,0.0014405617,0.0008918722,0.00007832814,0.0001240228,0.00016200509,0.022417331,0.04903068,0.060926847,0.010509289,0.8541419],"study_design_scores_gemma":[0.00009669746,0.0007524872,0.0048595215,0.0005349579,0.00017666495,0.0022055043,0.0003913511,0.33969623,0.06860847,0.09631224,0.48598814,0.0003777924],"about_ca_topic_score_codex":0.00083926076,"about_ca_topic_score_gemma":0.00087488483,"teacher_disagreement_score":0.0051843785,"about_ca_system_score_codex":0.00041147918,"about_ca_system_score_gemma":0.0005644907,"threshold_uncertainty_score":0.017343462},"labels":[],"label_agreement":null},{"id":"W2065641815","doi":"10.1155/2007/76146","title":"LDPC Code Design for Nonuniform Power-Line Channels","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Low-density parity-check code; Computer science; Channel (broadcasting); Decoding methods; Algorithm; Coding (social sciences); Code rate; Code (set theory); Electronic engineering; Theoretical computer science; Computer engineering; Telecommunications; Mathematics","score_opus":0.04221261234473051,"score_gpt":0.3508074368376701,"score_spread":0.30859482449293957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065641815","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058293544,0.00016402519,0.93885404,0.00012661958,0.000009343088,0.000035555167,0.000052714877,0.00010797952,0.0023562459],"genre_scores_gemma":[0.811021,0.00028314156,0.18648376,0.00005818901,0.000018652463,0.000102163256,0.00008033184,0.00004121782,0.0019115009],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960345,0.0001393084,0.000017797578,0.00006600751,0.00013753765,0.000035955218],"domain_scores_gemma":[0.99863976,0.0007808441,0.00021059622,0.00012567852,0.00021221151,0.000030903444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004655021,0.00031658084,0.00037242193,0.0003162689,0.00024471298,0.00041279258,0.00036555377,0.0004216949,0.00074314175],"category_scores_gemma":[0.0033821883,0.00013893601,0.00012819545,0.0005093725,0.0005757981,0.00062665803,0.00042530603,0.00031385513,0.0001637961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006351169,0.000020528207,0.00087480753,0.0000940913,0.000014937138,0.00008212434,0.000072898016,0.913006,0.011140049,0.033732355,0.00048670548,0.0404119],"study_design_scores_gemma":[0.0000066331554,0.000019273886,0.00006866292,0.0000036251429,0.0000031039085,0.000023980128,0.00000624921,0.99110925,0.0034987945,0.0048318533,0.00042502146,0.0000035280605],"about_ca_topic_score_codex":0.001402469,"about_ca_topic_score_gemma":0.0012193919,"teacher_disagreement_score":0.001402469,"about_ca_system_score_codex":0.00070194795,"about_ca_system_score_gemma":0.0006587885,"threshold_uncertainty_score":0.005093038},"labels":[],"label_agreement":null},{"id":"W2066348733","doi":"10.1155/2007/83858","title":"Design of Optimal Quincunx Filter Banks for Image Coding","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Filter bank; Mathematics; Filter design; Finite impulse response; Algorithm; Filter (signal processing); Digital filter; JPEG; Separable space; Coding (social sciences); Coding gain; Control theory (sociology); Computer science; Artificial intelligence; Data compression; Computer vision; Decoding methods; Statistics","score_opus":0.032264472913966454,"score_gpt":0.31589564793695135,"score_spread":0.2836311750229849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066348733","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013308512,0.00024029681,0.9850531,0.00006859322,0.000028600618,0.000026178359,0.000017141536,0.00011890768,0.0011386174],"genre_scores_gemma":[0.24940053,0.00044288218,0.74815047,0.00010103455,0.00002909029,0.00018796195,0.00006821139,0.000038206967,0.0015815702],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996772,0.00011357874,0.000019922429,0.00006194403,0.00009669428,0.00003073364],"domain_scores_gemma":[0.9996244,0.00014265538,0.000059898597,0.000041501822,0.00011579079,0.000015686086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059904665,0.00049443543,0.00045755424,0.00037478778,0.0002118385,0.0005207602,0.00048609692,0.0005989159,0.0014725934],"category_scores_gemma":[0.0013345833,0.0003639806,0.0002322318,0.0002667458,0.00041943617,0.0005840896,0.00033794093,0.00041980157,0.0004108601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054336694,0.00012309189,0.0010767729,0.00033705682,0.00009172292,0.00019449404,0.00021953676,0.37065423,0.19439259,0.08323449,0.0038019903,0.3453307],"study_design_scores_gemma":[0.00004468624,0.00014937377,0.00027990068,0.000026399928,0.000015874322,0.00012588156,0.00002347615,0.9609832,0.027894305,0.0053169713,0.005108144,0.000031694635],"about_ca_topic_score_codex":0.00052249595,"about_ca_topic_score_gemma":0.00081987155,"teacher_disagreement_score":0.0014725934,"about_ca_system_score_codex":0.00040212108,"about_ca_system_score_gemma":0.00052909635,"threshold_uncertainty_score":0.004926324},"labels":[],"label_agreement":null},{"id":"W2067093455","doi":"10.1155/2010/782438","title":"On Converting Secret Sharing Scheme to Visual Secret Sharing Scheme","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China; University of Alberta","keywords":"Secret sharing; Grayscale; Shamir's Secret Sharing; Secure multi-party computation; Homomorphic secret sharing; Image sharing; Computer science; Visual cryptography; Concatenation (mathematics); Pixel; Image (mathematics); Computation; Theoretical computer science; Computer vision; Artificial intelligence; Mathematics; Algorithm; Cryptography; Arithmetic","score_opus":0.014823863687954908,"score_gpt":0.3132409333807357,"score_spread":0.2984170696927808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067093455","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03667788,0.00048653493,0.94347906,0.00028827504,0.00015969892,0.00019127005,0.00006585125,0.00044028857,0.018211197],"genre_scores_gemma":[0.745003,0.0011975107,0.2414868,0.0003422819,0.00015034438,0.00024342217,0.0001879158,0.00007524466,0.011313431],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994141,0.00010221859,0.000031600255,0.00009031639,0.00028236108,0.00007940577],"domain_scores_gemma":[0.9996271,0.000114646486,0.00004179275,0.00012789776,0.000069022586,0.00001954316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031846343,0.00031622278,0.00036083505,0.0004388692,0.00042698765,0.00066396117,0.00042303704,0.00048067162,0.0024010625],"category_scores_gemma":[0.0011506507,0.00014439666,0.0005132728,0.00073646044,0.0008130144,0.001450731,0.0011840775,0.0009053141,0.000503492],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030390662,0.00009789631,0.00063443976,0.00030075238,0.000044877124,0.0006456722,0.0006419398,0.053813253,0.09746926,0.58075327,0.0033146348,0.26198015],"study_design_scores_gemma":[0.00013193533,0.000576104,0.0012288482,0.00012815178,0.00009369296,0.0025947941,0.00024155978,0.48791936,0.11939476,0.33279824,0.0547553,0.00013731606],"about_ca_topic_score_codex":0.00032594474,"about_ca_topic_score_gemma":0.0001958481,"teacher_disagreement_score":0.0024010625,"about_ca_system_score_codex":0.00041580363,"about_ca_system_score_gemma":0.00036168398,"threshold_uncertainty_score":0.008032322},"labels":[],"label_agreement":null},{"id":"W2067865896","doi":"10.1155/2008/360490","title":"On the Duality between MIMO Systems with Distributed Antennas and MIMO Systems with Colocated Antennas","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"MIMO; 3G MIMO; Antenna (radio); Computer science; Transmission (telecommunications); Transmitter; Multi-user MIMO; Telecommunications; Electronic engineering; Topology (electrical circuits); Electrical engineering; Engineering; Beamforming; Channel (broadcasting)","score_opus":0.014377861949124136,"score_gpt":0.2552219440544217,"score_spread":0.2408440821052976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067865896","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018352892,0.009721864,0.9129913,0.0012206532,0.0005544465,0.00005233026,0.00022094818,0.0000673611,0.05681816],"genre_scores_gemma":[0.80490655,0.026271148,0.14176963,0.002521599,0.0037940352,0.0003171618,0.0005256932,0.00014130818,0.019752843],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985606,0.00055769744,0.00005264814,0.0002587274,0.00039739028,0.00017301162],"domain_scores_gemma":[0.99683136,0.0019734593,0.00046460054,0.00021426899,0.00038039155,0.00013585933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012731514,0.0013590455,0.00096607156,0.00096810784,0.0006564091,0.0022006428,0.00088260294,0.001197307,0.0028939066],"category_scores_gemma":[0.0037623509,0.00056636345,0.00089563825,0.0014671953,0.0031328218,0.0028289251,0.002205283,0.003854492,0.0007959886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006153443,0.00004297967,0.0004295576,0.00020324177,0.000030436282,0.00021373825,0.00027447884,0.040204436,0.0028501072,0.9359342,0.0020768011,0.017678525],"study_design_scores_gemma":[0.000028776229,0.00027447855,0.00109925,0.00021083409,0.000037378366,0.0006289852,0.00017476945,0.22647975,0.0015241039,0.7503749,0.019091655,0.000075066244],"about_ca_topic_score_codex":0.0008466178,"about_ca_topic_score_gemma":0.00052080414,"teacher_disagreement_score":0.0028939066,"about_ca_system_score_codex":0.0010114436,"about_ca_system_score_gemma":0.0006110851,"threshold_uncertainty_score":0.009681046},"labels":[],"label_agreement":null},{"id":"W2067933400","doi":"10.1155/asp/2006/32476","title":"Advanced Signal Processing for Digital Subscriber Lines","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Digital subscriber line; Computer science; Telecommunications; Cable modem; Broadband; Telephone line; Signal processing; Computer network; Electronic engineering; Telephony; Engineering","score_opus":0.013528887966440343,"score_gpt":0.27630818638475335,"score_spread":0.262779298418313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067933400","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0053076297,0.03513127,0.91000074,0.0019572705,0.0040880865,0.00013844194,0.00044337008,0.0016213937,0.041311793],"genre_scores_gemma":[0.14279209,0.068697125,0.6316751,0.0021099707,0.0068244007,0.00051818416,0.0030742458,0.0005754942,0.14373334],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996598,0.00005415621,0.000017790657,0.000055152606,0.00019058025,0.00002262291],"domain_scores_gemma":[0.99965394,0.00008356259,0.000021952108,0.00004401147,0.00018099163,0.000015491469],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035061903,0.0007827131,0.00040014333,0.00083011866,0.00030863305,0.00092977245,0.00045088408,0.0009166822,0.016051462],"category_scores_gemma":[0.0013048757,0.00016732136,0.0003095079,0.0011395286,0.00023430599,0.00088884693,0.00049977674,0.0012703199,0.012749431],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016632491,0.00006100497,0.0003790647,0.0005347306,0.000034996876,0.00031326315,0.00014069577,0.012205992,0.048740882,0.08333539,0.058846124,0.7952415],"study_design_scores_gemma":[0.000048659967,0.00028838645,0.001130627,0.0003180598,0.000041813717,0.0014038163,0.00008707034,0.15143228,0.02367788,0.0702222,0.75127375,0.00007548141],"about_ca_topic_score_codex":0.00051242736,"about_ca_topic_score_gemma":0.000591597,"teacher_disagreement_score":0.016051462,"about_ca_system_score_codex":0.0002917061,"about_ca_system_score_gemma":0.00029794767,"threshold_uncertainty_score":0.053697526},"labels":[],"label_agreement":null},{"id":"W2070005935","doi":"10.1155/2011/184685","title":"Virtual Cooperation for Throughput Maximization in Distributed Large-Scale Wireless Networks","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo; Johns Hopkins University","keywords":"Throughput; Computer science; Bandwidth (computing); Maximum throughput scheduling; Wireless network; Code rate; Fading; Computer network; Wireless; Maximization; Power (physics); Mathematical optimization; Algorithm; Mathematics; Quality of service; Telecommunications; Channel (broadcasting); Decoding methods","score_opus":0.017113999900364437,"score_gpt":0.30002420439909433,"score_spread":0.2829102044987299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070005935","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051257275,0.0011071207,0.942106,0.00040769365,0.000060435465,0.000036061345,0.0000270477,0.00017956593,0.004818818],"genre_scores_gemma":[0.97754556,0.0005088982,0.020222044,0.000054611333,0.000055557313,0.000080290534,0.000023167158,0.00003166176,0.0014782703],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986259,0.0008193319,0.00003101515,0.00014015593,0.00023266442,0.00015098309],"domain_scores_gemma":[0.99713576,0.0021324924,0.00022535736,0.00014914799,0.00022310582,0.00013415789],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002221158,0.0011178193,0.0012246694,0.0004645335,0.0006328748,0.0013848565,0.0012032647,0.0008970244,0.0010080457],"category_scores_gemma":[0.0048810584,0.00039086703,0.00040317283,0.0009047558,0.0018221412,0.001240832,0.0013915118,0.0008660718,0.00020543818],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009596497,0.000031621214,0.00021893902,0.00010512456,0.000035777168,0.00019065358,0.00012258174,0.92742836,0.003196826,0.058867697,0.0009291275,0.008777382],"study_design_scores_gemma":[0.000010334894,0.000024810262,0.00004390485,0.0000042374254,0.000006147633,0.00002131625,0.000016489399,0.9809667,0.0003021255,0.018364554,0.00023471133,0.0000046206137],"about_ca_topic_score_codex":0.0009602431,"about_ca_topic_score_gemma":0.0009838064,"teacher_disagreement_score":0.002221158,"about_ca_system_score_codex":0.0012767098,"about_ca_system_score_gemma":0.0008524672,"threshold_uncertainty_score":0.011746705},"labels":[],"label_agreement":null},{"id":"W2071879168","doi":"10.1155/2008/580368","title":"Performance of Multiple-Relay Cooperative Diversity Systems with Best Relay Selection over Rayleigh Fading Channels","year":2008,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":200,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Relay; Rayleigh fading; Cooperative diversity; Relay channel; Node (physics); Computer science; Fading; Computer network; Signal-to-noise ratio (imaging); Interference (communication); Diversity gain; Diversity combining; Telecommunications; Topology (electrical circuits); Channel (broadcasting); Mathematics; Power (physics); Engineering; Physics","score_opus":0.035809271223522204,"score_gpt":0.274050797603345,"score_spread":0.2382415263798228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071879168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85730714,0.0019172198,0.13048796,0.00046807574,0.00006722967,0.00004721198,0.00025769798,0.00036861887,0.009078771],"genre_scores_gemma":[0.9982734,0.00016371156,0.0012149956,0.000016524269,0.0000100176985,0.000007778567,0.00002621444,0.0000063002794,0.0002811247],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987332,0.00050435844,0.00004759055,0.00016066269,0.00022923906,0.00032497093],"domain_scores_gemma":[0.9949805,0.0031952236,0.00049717375,0.00024591078,0.0008859152,0.00019525891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017721326,0.0014747889,0.0014145734,0.00061550445,0.00077188696,0.0014936535,0.0007980357,0.0012985051,0.00095844106],"category_scores_gemma":[0.0047211894,0.00039739528,0.0005108441,0.00067289965,0.0015810393,0.0012094686,0.0013701872,0.00056399807,0.00021920659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033375283,0.00003024936,0.0018207286,0.00006404119,0.00007259531,0.00020508745,0.000100665755,0.9865632,0.0040979586,0.0028905063,0.00019920568,0.0036219337],"study_design_scores_gemma":[0.000027153996,0.00019675186,0.0007862029,0.000009235026,0.000037927606,0.00007940727,0.000054475095,0.9955309,0.0013012425,0.001873189,0.00007847144,0.000025078254],"about_ca_topic_score_codex":0.007421467,"about_ca_topic_score_gemma":0.0030605623,"teacher_disagreement_score":0.007421467,"about_ca_system_score_codex":0.0012982591,"about_ca_system_score_gemma":0.0010677741,"threshold_uncertainty_score":0.01475656},"labels":[],"label_agreement":null},{"id":"W2071935478","doi":"10.1155/2008/371621","title":"Multimodality Inferring of Human Cognitive States Based on Integration of Neuro-Fuzzy Network and Information Fusion Techniques","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multimodality; Computer science; Feature (linguistics); Artificial intelligence; Cognition; Artificial neural network; Operator (biology); State (computer science); Fuzzy logic; Sensor fusion; Task (project management); Machine learning; Pattern recognition (psychology); Engineering; Algorithm; Psychology","score_opus":0.013608993984670805,"score_gpt":0.293550235090245,"score_spread":0.2799412411055742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071935478","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027844025,0.0002920291,0.9705221,0.000085641885,0.000022757293,0.000035738252,0.000026565607,0.00015738168,0.0010136901],"genre_scores_gemma":[0.8103322,0.0003502102,0.18814614,0.000059418737,0.000048118025,0.00008588067,0.000070988885,0.000017975748,0.000889121],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995902,0.00008292553,0.00003427176,0.00012508228,0.00012848522,0.000039006478],"domain_scores_gemma":[0.99962175,0.0001436575,0.000062837775,0.00002559242,0.00012941544,0.00001677755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009798309,0.0007395743,0.0006444357,0.0011565881,0.00047234804,0.0006759069,0.00061161973,0.0006281123,0.0006048961],"category_scores_gemma":[0.0017871974,0.0003327178,0.0008328474,0.00068378705,0.00037779275,0.0011773608,0.0006979067,0.0006301843,0.00010233692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026778356,0.0001429156,0.004246282,0.00019674053,0.00026390795,0.00033654616,0.0005425408,0.6283321,0.024798017,0.009388558,0.00077832915,0.3307064],"study_design_scores_gemma":[0.000003500111,0.000022270848,0.0007523745,0.0000074730933,0.000021544698,0.000026128273,0.000023437298,0.99451303,0.0016654313,0.0027724502,0.00017914348,0.000013141868],"about_ca_topic_score_codex":0.0055080676,"about_ca_topic_score_gemma":0.0044979826,"teacher_disagreement_score":0.0055080676,"about_ca_system_score_codex":0.00066186365,"about_ca_system_score_gemma":0.00048720624,"threshold_uncertainty_score":0.010951996},"labels":[],"label_agreement":null},{"id":"W2072085450","doi":"10.1155/asp/2006/76462","title":"Fast Registration of Remotely Sensed Images for Earthquake Damage Estimation","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Iran Telecommunication Research Center","keywords":"Multispectral image; Computer science; Remote sensing; Event (particle physics); Computer vision; Artificial intelligence; Real-time computing; Geology","score_opus":0.012731527402270303,"score_gpt":0.2678622281681992,"score_spread":0.2551307007659289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072085450","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10572606,0.001074494,0.889477,0.00014811338,0.00009777082,0.00008799579,0.00017995415,0.0019476388,0.0012609727],"genre_scores_gemma":[0.5366826,0.0007331772,0.45978162,0.00006812473,0.00012410607,0.00009260501,0.0006477082,0.00016712723,0.0017030176],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999335,0.0002007025,0.000027324046,0.00009554162,0.00028650227,0.00005498981],"domain_scores_gemma":[0.9990013,0.00032786393,0.00016992318,0.00024067628,0.00022296565,0.00003723679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009856748,0.0006352866,0.00061128783,0.0017148384,0.000212591,0.00054037484,0.0005547442,0.0007361591,0.0014042698],"category_scores_gemma":[0.0025474618,0.0003652481,0.0003769482,0.0014109933,0.00025118823,0.00087221124,0.00044212467,0.00059739116,0.0014114918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008278308,0.00024887134,0.0033279234,0.00021457937,0.0001128499,0.00017981774,0.00007974343,0.06011308,0.25757656,0.002417747,0.0029319273,0.67196906],"study_design_scores_gemma":[0.000054851767,0.00031863514,0.011133563,0.000016785527,0.000059253438,0.00034245805,0.00004266587,0.8500837,0.13123445,0.001718498,0.004936365,0.000058830352],"about_ca_topic_score_codex":0.00055453647,"about_ca_topic_score_gemma":0.000984128,"teacher_disagreement_score":0.0017148384,"about_ca_system_score_codex":0.0001722505,"about_ca_system_score_gemma":0.00029175394,"threshold_uncertainty_score":0.0052128434},"labels":[],"label_agreement":null},{"id":"W2074557689","doi":"10.1155/2011/283020","title":"Improvement on EVESPA for Beamforming and Direction of Arrival Estimation","year":2011,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Beamforming; Direction of arrival; Computer science; Computational complexity theory; Algorithm; Signal subspace; Matrix (chemical analysis); Reduction (mathematics); Subspace topology; Covariance matrix; Adaptive beamformer; Estimation; SIGNAL (programming language); Mathematical optimization; Mathematics; Telecommunications; Artificial intelligence; Noise (video); Engineering","score_opus":0.02383832453633264,"score_gpt":0.30426548861623987,"score_spread":0.2804271640799072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074557689","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013477147,0.00007169984,0.9975579,0.000043877742,0.000024260169,0.000016004378,0.000034316992,0.00024778384,0.0006564398],"genre_scores_gemma":[0.06241126,0.0004201359,0.9330503,0.00016035576,0.00010542496,0.0001583522,0.00040225987,0.0001371933,0.003154754],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998574,0.000500674,0.00008209251,0.00019009187,0.0005819971,0.00007111321],"domain_scores_gemma":[0.99826777,0.00075918925,0.00009359753,0.0003921417,0.0004408551,0.0000463726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014751751,0.0015366443,0.0009293323,0.000612163,0.00035767816,0.0007262463,0.0011984725,0.0009410555,0.004938688],"category_scores_gemma":[0.0045601334,0.0005870577,0.0010713913,0.0007941191,0.0005903595,0.0018577396,0.0024201884,0.0019789492,0.004176076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053599576,0.0001229756,0.0009623737,0.00031985203,0.00016711015,0.00045171927,0.0001601616,0.099983156,0.10214958,0.05799405,0.0038699165,0.73328316],"study_design_scores_gemma":[0.00006325816,0.00028875028,0.0008791588,0.00006546023,0.00007283782,0.0012579306,0.000049466526,0.9102541,0.047799483,0.018579919,0.020613773,0.00007579722],"about_ca_topic_score_codex":0.0004663953,"about_ca_topic_score_gemma":0.00088880496,"teacher_disagreement_score":0.004938688,"about_ca_system_score_codex":0.00016169266,"about_ca_system_score_gemma":0.0007774408,"threshold_uncertainty_score":0.016521573},"labels":[],"label_agreement":null},{"id":"W2075758563","doi":"10.1155/2010/281769","title":"Channel Equalization for Single Carrier MIMO Underwater Acoustic Communications","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Equalization (audio); Adaptive equalizer; MIMO; Phase distortion; Electronic engineering; Channel (broadcasting); Underwater acoustic communication; Interference (communication); Compensation (psychology); Single antenna interference cancellation; Intersymbol interference; Underwater; Telecommunications; Engineering; Transmission (telecommunications)","score_opus":0.03568848899222314,"score_gpt":0.2968806377312947,"score_spread":0.26119214873907154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075758563","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031324204,0.001253344,0.9617993,0.00016122349,0.0001688345,0.00004011257,0.000064042266,0.00050472084,0.004684219],"genre_scores_gemma":[0.7155469,0.0013440246,0.2740664,0.00012539925,0.00012345819,0.000069873924,0.00018132768,0.000057670208,0.008485019],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998161,0.000041878382,0.0000066140888,0.000030301077,0.00007956144,0.00002550913],"domain_scores_gemma":[0.99978524,0.00008995272,0.000021649805,0.000030482417,0.000066060646,0.000006603057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019052665,0.0002536178,0.00028074151,0.00025666264,0.00026220107,0.0003088756,0.00024033584,0.0003182789,0.0019908356],"category_scores_gemma":[0.0006080846,0.00011472752,0.00015842082,0.00031378094,0.00023441146,0.00041418758,0.00028413735,0.0003521993,0.0006434203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032998866,0.00007424558,0.0013566546,0.00031701458,0.00008985395,0.00020524197,0.00010018342,0.16107811,0.2720329,0.01981951,0.004774149,0.5398222],"study_design_scores_gemma":[0.000035784862,0.00017874046,0.0017576782,0.000032772994,0.000041238665,0.00022674628,0.000059772545,0.8442282,0.13258144,0.0050890287,0.015719749,0.000048839578],"about_ca_topic_score_codex":0.0008948581,"about_ca_topic_score_gemma":0.0024805546,"teacher_disagreement_score":0.0019908356,"about_ca_system_score_codex":0.0002425136,"about_ca_system_score_gemma":0.00046826107,"threshold_uncertainty_score":0.0066599846},"labels":[],"label_agreement":null},{"id":"W2077936074","doi":"10.1155/2008/593216","title":"Adaptive S-Method for SAR/ISAR Imaging","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Inverse synthetic aperture radar; Computer science; Artificial intelligence; Computer vision; Radar imaging; Synthetic aperture radar; Fourier transform; Radar; Telecommunications; Mathematics","score_opus":0.015126493532876154,"score_gpt":0.3395792242860114,"score_spread":0.32445273075313524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077936074","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018557211,0.00026219836,0.9964845,0.00005685203,0.00004424344,0.000012790348,0.000013221324,0.00017034517,0.0011000353],"genre_scores_gemma":[0.07333326,0.000641344,0.92005473,0.000121480334,0.00013229644,0.00007598268,0.000102814854,0.00011302044,0.0054251836],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981254,0.000051966825,0.0000063527427,0.00002512707,0.00009440987,0.000009695935],"domain_scores_gemma":[0.99987483,0.000037313872,0.000015430553,0.000016982125,0.000044534754,0.000010895262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023656353,0.00041574318,0.0003086863,0.00044237636,0.0001827872,0.00023653374,0.0006134903,0.0005645143,0.002360844],"category_scores_gemma":[0.00037279865,0.0001459477,0.00042597472,0.00041642544,0.00039632936,0.00034720823,0.00047302438,0.00050802453,0.0012478669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001779391,0.00006525414,0.0008234996,0.00031325466,0.00007680638,0.00024638578,0.000104870094,0.09833563,0.1925096,0.07282652,0.009403486,0.62511677],"study_design_scores_gemma":[0.000026542066,0.00009518477,0.00043488652,0.000015579619,0.000013523498,0.00034894893,0.000013648814,0.93867403,0.020006755,0.014020113,0.026321134,0.000029681258],"about_ca_topic_score_codex":0.00061127014,"about_ca_topic_score_gemma":0.0008130977,"teacher_disagreement_score":0.002360844,"about_ca_system_score_codex":0.00015540188,"about_ca_system_score_gemma":0.00032345435,"threshold_uncertainty_score":0.007897854},"labels":[],"label_agreement":null},{"id":"W2079287883","doi":"10.1155/2008/476125","title":"Power and Resource Allocation for Orthogonal Multiple Access Relay Systems","year":2008,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Canada Research Chairs; Government of Ontario","keywords":"Quasiconvex function; Resource allocation; Computer science; Relay; Channel (broadcasting); Mathematical optimization; Power (physics); Joint (building); Signal-to-noise ratio (imaging); Convex optimization; Computer network; Regular polygon; Telecommunications; Mathematics; Convex combination; Engineering","score_opus":0.04928030065112178,"score_gpt":0.32747803208547355,"score_spread":0.2781977314343518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079287883","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028517481,0.0016366614,0.96058375,0.00060917164,0.000059583388,0.000058303074,0.00009735059,0.00012793395,0.008309782],"genre_scores_gemma":[0.91365886,0.0018879604,0.07926198,0.0001342931,0.000114079325,0.00020298202,0.00008061749,0.00006655044,0.004592649],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986393,0.00074734044,0.000039170496,0.00014826673,0.00024637784,0.00017950371],"domain_scores_gemma":[0.9981317,0.0014118757,0.00018211933,0.0000687716,0.00015701314,0.000048442365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016898416,0.0013207117,0.0012926944,0.00057998,0.00045244975,0.0015159154,0.0010539729,0.0010631001,0.0022157854],"category_scores_gemma":[0.00450559,0.00050149875,0.0004069818,0.0011888376,0.0011051149,0.0016756194,0.0011680145,0.00087557413,0.0005355117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007957149,0.00003415301,0.00019536345,0.000108682536,0.00003699695,0.00019940616,0.000060977523,0.9423945,0.0014617861,0.03836922,0.0010311138,0.016028099],"study_design_scores_gemma":[0.000021165548,0.000034405308,0.000058307567,0.0000060169777,0.000008447657,0.00004396688,0.00001651205,0.9838124,0.00037089825,0.014995374,0.0006256262,0.0000070086585],"about_ca_topic_score_codex":0.0017630467,"about_ca_topic_score_gemma":0.0012919736,"teacher_disagreement_score":0.0022157854,"about_ca_system_score_codex":0.0011119817,"about_ca_system_score_gemma":0.0008092302,"threshold_uncertainty_score":0.008936822},"labels":[],"label_agreement":null},{"id":"W2080927857","doi":"10.1155/s1110865704404028","title":"Gaussian Channel Model for Mobile Multipath Environment","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Angle of arrival; Multipath propagation; Gaussian; Computer science; Channel (broadcasting); Probability density function; Base station; Gaussian process; Algorithm; Statistical physics; Physics; Optics; Telecommunications; Mathematics; Statistics","score_opus":0.020933222228818348,"score_gpt":0.3046314250766167,"score_spread":0.2836982028477984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080927857","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0072932583,0.0023717915,0.9794112,0.00042582335,0.0003714705,0.00009032072,0.0014333768,0.0011946949,0.0074080364],"genre_scores_gemma":[0.6827395,0.019067148,0.22331367,0.001089206,0.0014768007,0.0013195152,0.0053308355,0.00047629583,0.06518707],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993364,0.00013885926,0.000022739256,0.00013458701,0.00023463082,0.00013267492],"domain_scores_gemma":[0.99944836,0.00017565803,0.00008557494,0.00007174507,0.00019616824,0.000022531407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047140327,0.0014686602,0.0011433428,0.0007931152,0.0005269573,0.0010733937,0.0021494278,0.0017950946,0.0043824804],"category_scores_gemma":[0.0012265483,0.00034423586,0.00069019734,0.0020800182,0.00064984127,0.0012438039,0.00066842197,0.0016245532,0.0039319545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013835281,0.000056288667,0.0009425225,0.00037432468,0.00006143486,0.000947321,0.00023043381,0.7189167,0.009227745,0.21265584,0.018027458,0.038421556],"study_design_scores_gemma":[0.000021355783,0.00006525635,0.00047844497,0.0000292952,0.000036410518,0.0005062334,0.00004361369,0.93943167,0.0009549118,0.040251102,0.018120592,0.000061139996],"about_ca_topic_score_codex":0.010291525,"about_ca_topic_score_gemma":0.006738345,"teacher_disagreement_score":0.010291525,"about_ca_system_score_codex":0.0008453703,"about_ca_system_score_gemma":0.0011209288,"threshold_uncertainty_score":0.020463228},"labels":[],"label_agreement":null},{"id":"W2081507356","doi":"10.1155/asp.2005.1071","title":"Perception SoC Based on an Ultrasonic Array of Sensors: Efficient DSP Core Implementation and Subsequent Experimental Results","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Digital signal processing; Computer science; Field-programmable gate array; Beamforming; Computer hardware; Software portability; Ultrasonic sensor; Embedded system; Signal processing; Acoustics; Telecommunications","score_opus":0.020141415366955486,"score_gpt":0.3462090395084309,"score_spread":0.32606762414147544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081507356","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75882345,0.00054898515,0.22448082,0.00026071395,0.00022314928,0.0006525313,0.00040783864,0.005351121,0.009251367],"genre_scores_gemma":[0.9472801,0.00013470254,0.048378624,0.000088878616,0.000016394672,0.00020304706,0.00023969509,0.00010101895,0.003557485],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99923,0.00014666705,0.000053499098,0.000088496636,0.0003352438,0.00014608631],"domain_scores_gemma":[0.9989454,0.0002745668,0.00011915525,0.0001029068,0.0004919766,0.00006594771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000713074,0.0005421508,0.00047256696,0.00038900427,0.00014910767,0.00050751824,0.00086270226,0.00035926985,0.0050313487],"category_scores_gemma":[0.0015210131,0.00014890364,0.00019920782,0.00022729223,0.00022379225,0.00051729416,0.00024480445,0.00032938216,0.0005820381],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023354436,0.0007841079,0.0035388968,0.0015615685,0.00017088874,0.0007542482,0.00050277624,0.053164717,0.72322434,0.005396793,0.004809931,0.20375627],"study_design_scores_gemma":[0.0005255857,0.008114926,0.006700208,0.00008391617,0.00015890403,0.00076989,0.00018384017,0.25363642,0.7123709,0.00065848505,0.016715221,0.0000817861],"about_ca_topic_score_codex":0.0013000056,"about_ca_topic_score_gemma":0.0009371641,"teacher_disagreement_score":0.0050313487,"about_ca_system_score_codex":0.00039756446,"about_ca_system_score_gemma":0.0006409654,"threshold_uncertainty_score":0.016831517},"labels":[],"label_agreement":null},{"id":"W2082488947","doi":"10.1155/2009/540409","title":"Alternative Speech Communication System for Persons with Severe Speech Disorders","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation; Université de Moncton","keywords":"Intelligibility (philosophy); Computer science; Dysarthria; Speech recognition; PESQ; Speech synthesis; PSQM; Voice activity detection; Perception; Speech processing; Speech communication; Speech technology; Speech enhancement; Artificial intelligence; Audiology; Psychology; Linguistics; Medicine","score_opus":0.019855821837908207,"score_gpt":0.2904018645717373,"score_spread":0.2705460427338291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082488947","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6885898,0.0024786014,0.28890544,0.00069638574,0.0005148502,0.0004835454,0.0012340095,0.0070430697,0.010054345],"genre_scores_gemma":[0.8794567,0.00067148654,0.105373606,0.00037371772,0.00012471876,0.0004668022,0.0014259865,0.00008181808,0.012025074],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998381,0.00004882105,0.000015898804,0.00003917453,0.000040686304,0.00001738333],"domain_scores_gemma":[0.9997942,0.00005922352,0.000014835532,0.000023193854,0.000081729624,0.000026894773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002786421,0.00038448925,0.000439731,0.00030637012,0.00027718954,0.00031257677,0.00036094963,0.00055345555,0.0069683343],"category_scores_gemma":[0.00048874755,0.0000889134,0.0002217428,0.00012242718,0.000127844,0.00027029536,0.0004157519,0.00024249718,0.0024573165],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027194417,0.00028684404,0.0058576623,0.0007514214,0.00010328463,0.002726886,0.00093888986,0.0013702905,0.38461438,0.0018721767,0.011211546,0.5875471],"study_design_scores_gemma":[0.0018491339,0.0110151,0.099142835,0.00037444447,0.0013168213,0.05428798,0.002757604,0.14753662,0.51842844,0.0031757208,0.15973544,0.0003798385],"about_ca_topic_score_codex":0.00050309504,"about_ca_topic_score_gemma":0.0008050078,"teacher_disagreement_score":0.0069683343,"about_ca_system_score_codex":0.00014594758,"about_ca_system_score_gemma":0.00019272888,"threshold_uncertainty_score":0.023311436},"labels":[],"label_agreement":null},{"id":"W2082832612","doi":"10.1155/2008/127689","title":"Censored Distributed Space-Time Coding for Wireless Sensor Networks","year":2007,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Coding (social sciences); Fusion center; Wireless sensor network; Censoring (clinical trials); Block code; Algorithm; Likelihood-ratio test; Real-time computing; Wireless; Decoding methods; Mathematics; Telecommunications; Statistics; Computer network","score_opus":0.01046260093278066,"score_gpt":0.2709164507378465,"score_spread":0.2604538498050658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082832612","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007389571,0.00064704975,0.99088633,0.0001850709,0.000033738805,0.000013608459,0.000022950624,0.00006388393,0.00075773185],"genre_scores_gemma":[0.71967703,0.0021489486,0.27495778,0.00018031592,0.00015105898,0.00015945881,0.00015641084,0.000044586268,0.0025244057],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992112,0.0003495677,0.000027486505,0.000075997115,0.00028772352,0.000047877373],"domain_scores_gemma":[0.99728525,0.0018105343,0.00026185633,0.000284446,0.00030845037,0.000049412618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010673337,0.00059995713,0.00043591013,0.00044358577,0.00026151948,0.00061149674,0.00087325444,0.00077094714,0.00083754514],"category_scores_gemma":[0.0061808317,0.00019255275,0.00033444914,0.00087937113,0.0009389539,0.0008718685,0.00078891893,0.0011504513,0.00028526626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011247145,0.000029202973,0.00051328755,0.00014324315,0.00002875944,0.00013182631,0.00011180487,0.7859303,0.006816276,0.1328769,0.0009882769,0.07231771],"study_design_scores_gemma":[0.000008514397,0.000031117295,0.000073850206,0.000009907128,0.0000047861477,0.000034922108,0.0000072607527,0.96491134,0.0012823943,0.033095423,0.00053061056,0.000009943882],"about_ca_topic_score_codex":0.0017859107,"about_ca_topic_score_gemma":0.0017256711,"teacher_disagreement_score":0.0017859107,"about_ca_system_score_codex":0.00077002455,"about_ca_system_score_gemma":0.00077609735,"threshold_uncertainty_score":0.005644679},"labels":[],"label_agreement":null},{"id":"W2082906988","doi":"10.1155/s1110865704407197","title":"A Nonlinear Entropic Variational Model for Image Filtering","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Air Force Office of Scientific Research; U.S. Air Force; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Negentropy; Gaussian; Mathematics; Nonlinear system; Maximum a posteriori estimation; Noise reduction; Variational method; Noise (video); Filter (signal processing); Gaussian noise; Applied mathematics; Computer science; Image (mathematics); Mathematical optimization; Algorithm; Artificial intelligence; Mathematical analysis; Computer vision; Maximum likelihood; Statistics","score_opus":0.0253695634984427,"score_gpt":0.32834158715803063,"score_spread":0.3029720236595879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082906988","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0070719277,0.00026927248,0.9896673,0.0004334451,0.00004958012,0.000013145457,0.0000447981,0.000049240658,0.0024013377],"genre_scores_gemma":[0.6607422,0.0016424726,0.30377838,0.0006442891,0.00038226324,0.00020775443,0.00028564988,0.00020007599,0.032116946],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996823,0.000094733245,0.000013458371,0.000063038104,0.000110656205,0.00003575262],"domain_scores_gemma":[0.99964285,0.00015726362,0.000051662875,0.00004065059,0.00006686228,0.00004060673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094491115,0.0005874506,0.00076223287,0.00058740133,0.00038194313,0.0010318953,0.0015957018,0.0016875844,0.001924493],"category_scores_gemma":[0.0018241215,0.0003936666,0.0008953575,0.0005148742,0.001418568,0.0016477989,0.0014205675,0.0012060795,0.00044558826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028952669,0.000023420127,0.00026601614,0.000075898584,0.000050231247,0.000117911746,0.00009604055,0.39709696,0.0069648824,0.57826024,0.0013632091,0.015656183],"study_design_scores_gemma":[0.0000032752005,0.000012477064,0.000050313844,0.000004068682,0.0000059532094,0.00002988993,0.0000050871377,0.93351334,0.00034469768,0.065037236,0.0009838229,0.000009888561],"about_ca_topic_score_codex":0.003072164,"about_ca_topic_score_gemma":0.0030684364,"teacher_disagreement_score":0.003072164,"about_ca_system_score_codex":0.0010144511,"about_ca_system_score_gemma":0.0009394295,"threshold_uncertainty_score":0.0073604584},"labels":[],"label_agreement":null},{"id":"W2082989160","doi":"10.1155/2010/739017","title":"Time-Frequency Analysis and Its Applications to Multimedia Signals","year":2011,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Multimedia; Telecommunications; Speech recognition","score_opus":0.024604664503675617,"score_gpt":0.2988907761723891,"score_spread":0.27428611166871353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082989160","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013581885,0.013870629,0.963156,0.00047282214,0.00040570545,0.000030667918,0.00017276643,0.0006522298,0.007657324],"genre_scores_gemma":[0.31573313,0.03291086,0.6266534,0.00036347526,0.0021791367,0.000109210356,0.00041187226,0.00027581592,0.021363089],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984694,0.000027489466,0.000015566753,0.000033537144,0.000066706554,0.0000096154545],"domain_scores_gemma":[0.9993624,0.00037499287,0.000057718855,0.000055513083,0.00012610925,0.00002322655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003129707,0.00063952105,0.00043352213,0.00187544,0.00025202858,0.0008370892,0.00034287252,0.0007313448,0.0036954978],"category_scores_gemma":[0.0013756952,0.00019835168,0.0004991593,0.0026998662,0.00045203546,0.0006304877,0.00034385078,0.00051568775,0.0015917919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001350986,0.00006326861,0.0008148953,0.00035935052,0.000075873984,0.00039950098,0.0001569226,0.026892882,0.07790274,0.035941657,0.0039443173,0.85331357],"study_design_scores_gemma":[0.000028265737,0.00018419942,0.0056855013,0.00013189937,0.00020991666,0.0022570684,0.00024116552,0.8009058,0.044728853,0.07438382,0.07113541,0.00010813562],"about_ca_topic_score_codex":0.0009809008,"about_ca_topic_score_gemma":0.00088720076,"teacher_disagreement_score":0.0036954978,"about_ca_system_score_codex":0.00018175418,"about_ca_system_score_gemma":0.00018638975,"threshold_uncertainty_score":0.012362659},"labels":[],"label_agreement":null},{"id":"W2084886252","doi":"10.1186/s13634-015-0194-1","title":"Object detection oriented video reconstruction using compressed sensing","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Government of Jiangsu Province; National Natural Science Foundation of China","keywords":"Computer vision; Artificial intelligence; Computer science; Object detection; Object (grammar); Video tracking; Video denoising; Background subtraction; Sequence (biology); Compressed sensing; Key (lock); Multiview Video Coding; Pattern recognition (psychology); Pixel","score_opus":0.02829355811478894,"score_gpt":0.2793816119028577,"score_spread":0.25108805378806875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084886252","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016901825,0.00033366325,0.9814709,0.0001421436,0.000042719403,0.000031035044,0.00005134695,0.00029492387,0.00073147356],"genre_scores_gemma":[0.36824197,0.00090374035,0.62810683,0.0002284617,0.00015776439,0.00007987892,0.00048181423,0.00006112783,0.0017383782],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958664,0.000074455515,0.00001823767,0.00008401498,0.0002066864,0.000029868717],"domain_scores_gemma":[0.99940765,0.00024868196,0.000086511805,0.00008610913,0.00014199257,0.000029067887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043416466,0.00070025347,0.0005965809,0.00081220095,0.00018190448,0.00047110746,0.0006206103,0.00070018246,0.0007656989],"category_scores_gemma":[0.0022150371,0.00024236683,0.0004337338,0.0008373229,0.00038941076,0.00084448105,0.00065701845,0.00082003366,0.00030349728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005950044,0.00016981618,0.0018191473,0.00034073295,0.00012230981,0.0005700014,0.00022051446,0.21109235,0.1635651,0.02318757,0.0035398286,0.59477764],"study_design_scores_gemma":[0.00001522878,0.00006185369,0.00040273808,0.000010471091,0.000011624847,0.00021639395,0.000016463255,0.9776775,0.017608097,0.002899016,0.0010688527,0.000011804623],"about_ca_topic_score_codex":0.0017786454,"about_ca_topic_score_gemma":0.00130323,"teacher_disagreement_score":0.0017786454,"about_ca_system_score_codex":0.00026471214,"about_ca_system_score_gemma":0.000426204,"threshold_uncertainty_score":0.0035366416},"labels":[],"label_agreement":null},{"id":"W2085409801","doi":"10.1155/2009/360834","title":"Incremental Local Linear Fuzzy Classifier in Fisher Space","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Ottawa","funders":"Iran Telecommunication Research Center","keywords":"Classifier (UML); Computer science; Artificial intelligence; Linear discriminant analysis; Quadratic classifier; Machine learning; Linear classifier; Pattern recognition (psychology); Random subspace method; Margin classifier; Data mining; Mathematics","score_opus":0.015471452206042086,"score_gpt":0.2739704490181178,"score_spread":0.2584989968120757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085409801","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03095931,0.0002636442,0.96701896,0.00007907404,0.00001965075,0.00004485105,0.00003653988,0.00063831214,0.0009397155],"genre_scores_gemma":[0.57814425,0.00022804219,0.4173687,0.00010665426,0.000047925398,0.0001481266,0.00025577194,0.00006708169,0.0036334866],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996294,0.00007070487,0.00002275026,0.000100216246,0.00012915181,0.000047775287],"domain_scores_gemma":[0.9993154,0.00027548042,0.00005544539,0.0000769786,0.0002521726,0.000024582869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008706403,0.00043847776,0.000965003,0.0006317466,0.00039576527,0.0004999633,0.0010441362,0.00072938553,0.0013692016],"category_scores_gemma":[0.002234523,0.00023720654,0.0005278433,0.00049690506,0.00030589674,0.0009181524,0.0005393357,0.0007614205,0.00063215947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024798943,0.00009535385,0.0017538008,0.00010426641,0.00005774746,0.00012516456,0.00014998307,0.3020508,0.018612297,0.0082940925,0.002772059,0.6657364],"study_design_scores_gemma":[0.000005239794,0.00003020851,0.00025448104,0.000003903432,0.0000083169325,0.000026831774,0.00000747311,0.9949137,0.0029103763,0.0014636316,0.0003698906,0.0000058386763],"about_ca_topic_score_codex":0.0048944457,"about_ca_topic_score_gemma":0.005137751,"teacher_disagreement_score":0.0048944457,"about_ca_system_score_codex":0.0005749171,"about_ca_system_score_gemma":0.00066516356,"threshold_uncertainty_score":0.009731889},"labels":[],"label_agreement":null},{"id":"W2088208328","doi":"10.1155/2008/765462","title":"Blind Channel Equalization Using Constrained Generalized Pattern Search Optimization and Reinitialization Strategy","year":2008,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Concordia University","keywords":"Blind equalization; Intersymbol interference; Algorithm; Channel (broadcasting); Convergence (economics); Computer science; Constant (computer programming); Interference (communication); Mathematical optimization; Equalization (audio); Mathematics; Telecommunications","score_opus":0.08240214386754008,"score_gpt":0.35432108742260576,"score_spread":0.2719189435550657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088208328","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0046725394,0.000066030276,0.99468464,0.00002583562,0.000015756816,0.000012196459,0.000007065207,0.00014771381,0.00036826008],"genre_scores_gemma":[0.15243338,0.00014883623,0.84404314,0.00007232948,0.00003451652,0.00009173173,0.000055579454,0.00007627024,0.0030442078],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997002,0.00008212163,0.000018861567,0.000060924223,0.000107317835,0.000030612253],"domain_scores_gemma":[0.9997186,0.00009424934,0.000035324967,0.00006648753,0.000071221744,0.0000140609],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039413257,0.00066270726,0.0009199375,0.00039507376,0.00021805549,0.0004949864,0.0007640604,0.0007631945,0.0014004143],"category_scores_gemma":[0.0010119404,0.00023492383,0.0004998856,0.00053757016,0.0005442301,0.0008754231,0.0006968623,0.0006107055,0.00050903106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002485327,0.00007382481,0.00043689038,0.00018247786,0.000118147465,0.00011431048,0.00008321771,0.45992136,0.071003586,0.026183898,0.0022517252,0.439382],"study_design_scores_gemma":[0.000030976636,0.00007281971,0.00012914086,0.000004894835,0.000012738843,0.0001039546,0.000006858923,0.98259914,0.012423774,0.003108655,0.0014877736,0.00001933063],"about_ca_topic_score_codex":0.0009773606,"about_ca_topic_score_gemma":0.0011575752,"teacher_disagreement_score":0.0014004143,"about_ca_system_score_codex":0.0002064453,"about_ca_system_score_gemma":0.0005936558,"threshold_uncertainty_score":0.0046848655},"labels":[],"label_agreement":null},{"id":"W2091019510","doi":"10.1155/s1110865704312126","title":"Generalized Selection Weighted Vector Filters","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonlinear filter; Filter (signal processing); Filter design; Adaptive filter; Kernel adaptive filter; Computer science; Prototype filter; Median filter; Root-raised-cosine filter; Noise (video); Algorithm; Signal processing; SIGNAL (programming language); Artificial intelligence; Mathematics; Computer vision; Image processing; Image (mathematics); Telecommunications","score_opus":0.018965577115514776,"score_gpt":0.31038103046009036,"score_spread":0.2914154533445756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091019510","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007426834,0.00044775187,0.989783,0.000069300906,0.000072025054,0.00002934259,0.000040439514,0.00021855372,0.0019127415],"genre_scores_gemma":[0.37074143,0.002305036,0.6038265,0.0004001453,0.00045066694,0.0002897065,0.00066572597,0.00022785542,0.021092897],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993204,0.0001619894,0.000032899254,0.0001478406,0.00027121807,0.00006568174],"domain_scores_gemma":[0.9995732,0.00013141608,0.000058521273,0.00006519175,0.00015025558,0.00002140812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007639964,0.0008628573,0.00084296154,0.0007482108,0.00025717655,0.0007806505,0.00079345616,0.0007318081,0.0022184711],"category_scores_gemma":[0.0012920771,0.00022812007,0.00070031855,0.00092395005,0.00047468726,0.000980019,0.0006343503,0.00066681986,0.00069160643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037854232,0.00006387987,0.00083205046,0.00024395608,0.00015227529,0.00013830606,0.0001115555,0.16554746,0.060553834,0.111831985,0.0053543965,0.65479183],"study_design_scores_gemma":[0.000036603877,0.00019556812,0.00090991,0.000020772175,0.000047361074,0.00019438718,0.000027103863,0.931911,0.013603286,0.031096056,0.021919494,0.00003842739],"about_ca_topic_score_codex":0.0012575508,"about_ca_topic_score_gemma":0.0015827866,"teacher_disagreement_score":0.0022184711,"about_ca_system_score_codex":0.00041863546,"about_ca_system_score_gemma":0.00044533963,"threshold_uncertainty_score":0.007421553},"labels":[],"label_agreement":null},{"id":"W2091582232","doi":"10.1155/asp/2006/20858","title":"A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":280,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"City University of Hong Kong","keywords":"Multilateration; RSS; Cramér–Rao bound; Angle of arrival; Estimator; Algorithm; Computer science; Least-squares function approximation; Time of arrival; Non-line-of-sight propagation; Upper and lower bounds; Position (finance); Wireless; Statistics; Mathematics; Estimation theory; Telecommunications; Antenna (radio)","score_opus":0.0077095608325364814,"score_gpt":0.24738996313926417,"score_spread":0.23968040230672769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091582232","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007105427,0.00035744318,0.99837613,0.00008127001,0.00001427289,0.000007412139,0.000012991811,0.000037853042,0.00040204576],"genre_scores_gemma":[0.13763028,0.0027518005,0.85461915,0.00021188322,0.0003038012,0.00029190388,0.00022239758,0.00012649593,0.0038423212],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99901533,0.0004325129,0.00004271156,0.00018075996,0.0002851254,0.000043518718],"domain_scores_gemma":[0.9981652,0.0013419436,0.00012662784,0.000085784995,0.00025829516,0.00002217606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011799453,0.0010803173,0.0010476192,0.0007469737,0.00033103584,0.0008818716,0.0011224673,0.0014317369,0.0010926999],"category_scores_gemma":[0.00662636,0.00063867995,0.00052029034,0.0017506442,0.0010804165,0.0012489514,0.0012194384,0.0014357911,0.0007546854],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003573173,0.000027682132,0.00033772245,0.00018516519,0.000056946326,0.000055907443,0.00007945959,0.7932378,0.0018591961,0.069585726,0.0020258583,0.1325128],"study_design_scores_gemma":[0.000009980731,0.000029595547,0.00011846452,0.000018957558,0.0000074385134,0.000044699278,0.00001057111,0.966695,0.00056735834,0.029969461,0.0025137556,0.000014718049],"about_ca_topic_score_codex":0.003693627,"about_ca_topic_score_gemma":0.0019483474,"teacher_disagreement_score":0.003693627,"about_ca_system_score_codex":0.0005864358,"about_ca_system_score_gemma":0.0009679016,"threshold_uncertainty_score":0.0073443055},"labels":[],"label_agreement":null},{"id":"W2092005902","doi":"10.1155/2010/857685","title":"Approximating the Time-Frequency Representation of Biosignals with Chirplets","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Wigner distribution function; Chirp; Matching pursuit; Time–frequency analysis; Computer science; Kernel (algebra); Quadratic equation; SIGNAL (programming language); Interference (communication); Representation (politics); Instantaneous phase; Matching (statistics); Algorithm; Distribution (mathematics); Pattern recognition (psychology); Speech recognition; Time–frequency representation; Mathematics; Artificial intelligence; Radar; Telecommunications; Physics; Statistics; Mathematical analysis","score_opus":0.007782094884663988,"score_gpt":0.2945327127656943,"score_spread":0.28675061788103035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092005902","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01801829,0.00010825561,0.9814185,0.00004091121,0.000022102717,0.00000823126,0.000015030239,0.00007615064,0.0002926014],"genre_scores_gemma":[0.5855956,0.001095355,0.40928108,0.00008180679,0.000104881954,0.00009426156,0.00019797069,0.00015524795,0.0033937902],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984825,0.00004032922,0.000007260496,0.00003347526,0.000053584397,0.000017003356],"domain_scores_gemma":[0.99928063,0.00041562063,0.00008353012,0.00006927829,0.00012665044,0.000024304847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006394242,0.0005230154,0.00042158173,0.0006574064,0.00017081674,0.00055091217,0.0006015073,0.0006007897,0.00081498147],"category_scores_gemma":[0.002373246,0.00019603493,0.00036331822,0.00068622635,0.000497927,0.00092993275,0.0004313154,0.0006908808,0.0003054654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041727762,0.000091539594,0.0025319995,0.00028813345,0.00008336587,0.00043579194,0.00019281817,0.4944379,0.10294812,0.11297489,0.0015939877,0.28400406],"study_design_scores_gemma":[0.0000056502395,0.000023334873,0.0002601683,0.0000043833643,0.0000052701594,0.00009924327,0.000010125004,0.98959666,0.0042371727,0.0049689123,0.0007791028,0.000009897649],"about_ca_topic_score_codex":0.0010275807,"about_ca_topic_score_gemma":0.0011729248,"teacher_disagreement_score":0.0010275807,"about_ca_system_score_codex":0.00033030036,"about_ca_system_score_gemma":0.00038773642,"threshold_uncertainty_score":0.00338161},"labels":[],"label_agreement":null},{"id":"W2095847469","doi":"10.1186/1687-6180-2014-3","title":"An analysis of maximum likelihood estimation method for bit synchronization and decoding of GPS L1 C/A signals","year":2014,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"GNSS positioning and interference","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; General Motors of Canada; University of Calgary","keywords":"Decoding methods; Computer science; Bit error rate; Synchronization (alternating current); Algorithm; GNSS applications; Real-time computing; Global Positioning System; Electronic engineering; Telecommunications; Channel (broadcasting)","score_opus":0.009918869389957325,"score_gpt":0.3080234916711007,"score_spread":0.29810462228114337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095847469","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058477656,0.00082984567,0.99197805,0.00007579532,0.00001966565,0.000022189688,0.000016962747,0.0002040763,0.0010056662],"genre_scores_gemma":[0.50647175,0.003577091,0.48385724,0.00018128913,0.00018532421,0.0003324043,0.00031686493,0.00041485485,0.0046632136],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961104,0.0015499308,0.00016023222,0.0004214543,0.0015575099,0.0002005332],"domain_scores_gemma":[0.9927516,0.005661781,0.00044474934,0.0002535911,0.0008292704,0.000059024347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003848683,0.0012879738,0.0008689844,0.0011225599,0.0005584371,0.0012663956,0.0009911215,0.0010996294,0.0019484523],"category_scores_gemma":[0.015981415,0.00073609524,0.0008214873,0.0009704817,0.00091248855,0.0017737825,0.0008857808,0.001373189,0.0008377886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005024773,0.0000680784,0.0038036178,0.00047203756,0.00019383637,0.0003304776,0.00036591242,0.7203891,0.023641251,0.051644783,0.0015113587,0.19707714],"study_design_scores_gemma":[0.000004863936,0.00004049186,0.0004225369,0.000018996172,0.00001564394,0.000088996894,0.00001150732,0.9931732,0.003756498,0.0018693622,0.0005769026,0.00002102881],"about_ca_topic_score_codex":0.0036689236,"about_ca_topic_score_gemma":0.0018642029,"teacher_disagreement_score":0.003848683,"about_ca_system_score_codex":0.00121526,"about_ca_system_score_gemma":0.0013048317,"threshold_uncertainty_score":0.020354033},"labels":[],"label_agreement":null},{"id":"W2096141515","doi":"10.1186/1687-6180-2012-78","title":"Distributed transform coding via source-splitting","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Distributed source coding; Algorithm; Rate distortion; Computer science; Entropy (arrow of time); Gaussian; Source code; Mathematics; Quantization (signal processing); Theoretical computer science; Coding (social sciences); Decoding methods; Variable-length code; Statistics","score_opus":0.014785664047219454,"score_gpt":0.27992446582408137,"score_spread":0.2651388017768619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096141515","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0060345717,0.00011460699,0.9919574,0.000064151325,0.00001983097,0.00002560107,0.000038877697,0.00015796063,0.0015869038],"genre_scores_gemma":[0.44196677,0.00045611945,0.55240834,0.00015497369,0.000083202285,0.00018207154,0.0003172552,0.000084299296,0.004347023],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993881,0.0001220875,0.000026684791,0.00010055006,0.00032006012,0.00004241371],"domain_scores_gemma":[0.9992029,0.00032119043,0.00007190367,0.00018113285,0.00019993576,0.000022897762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005645356,0.0005153332,0.00042677746,0.000431454,0.0002571285,0.0005727794,0.0007130077,0.00061527244,0.00170132],"category_scores_gemma":[0.0020906057,0.00016422037,0.0003683671,0.0008655257,0.00075907423,0.0009952916,0.0010330619,0.0009357116,0.000545626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030955268,0.000073275965,0.00042870414,0.00017003428,0.0000456499,0.00019415062,0.00018443867,0.20413259,0.107847154,0.28121242,0.0032499991,0.40215197],"study_design_scores_gemma":[0.00004128863,0.00011960428,0.00014203292,0.000023976881,0.000015561605,0.00024495024,0.000021163822,0.9006493,0.039926533,0.052878615,0.0059139514,0.000022895205],"about_ca_topic_score_codex":0.0007867399,"about_ca_topic_score_gemma":0.0010020884,"teacher_disagreement_score":0.00170132,"about_ca_system_score_codex":0.00053279067,"about_ca_system_score_gemma":0.00081928814,"threshold_uncertainty_score":0.0056915283},"labels":[],"label_agreement":null},{"id":"W2096180483","doi":"10.1155/asp.2005.3015","title":"A Low-Power Two-Digit Multi-dimensional Logarithmic Number System Filterbank Architecture for a Digital Hearing Aid","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Filter bank; Computer science; Logarithm; Multiplication (music); Reduction (mathematics); Numerical digit; Arithmetic; Dynamic range; Computer hardware; Mathematics; Telecommunications","score_opus":0.01895903974653008,"score_gpt":0.3188527664335761,"score_spread":0.299893726687046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096180483","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03608779,0.0004004278,0.95485854,0.00056431553,0.00027757252,0.000101128404,0.00009634677,0.0017453245,0.005868608],"genre_scores_gemma":[0.30683577,0.00046517272,0.67932177,0.00060637883,0.00021423875,0.0001610802,0.00020352914,0.000071071954,0.012121084],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986684,0.00003275803,0.000011575058,0.000029476509,0.00004756126,0.000011734386],"domain_scores_gemma":[0.99985623,0.00004244564,0.000012280174,0.000029286444,0.000043938257,0.00001571818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003169381,0.00032769114,0.00026768513,0.00027787144,0.00026501645,0.0005507649,0.00067662913,0.0006292022,0.0062768017],"category_scores_gemma":[0.00052248844,0.00016916411,0.00021516104,0.00024148848,0.00021436652,0.00066362333,0.00031162758,0.00038335047,0.0025049462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085976627,0.0001260453,0.00084165065,0.00032243493,0.000054408225,0.0006304207,0.00017757717,0.008907763,0.49491003,0.01929917,0.00644214,0.4674286],"study_design_scores_gemma":[0.00048050503,0.0022933912,0.0036468003,0.00017919358,0.00022151713,0.0047894474,0.0001210324,0.5099396,0.3376569,0.008745959,0.13179344,0.00013221856],"about_ca_topic_score_codex":0.0003679035,"about_ca_topic_score_gemma":0.0010799046,"teacher_disagreement_score":0.0062768017,"about_ca_system_score_codex":0.0003301631,"about_ca_system_score_gemma":0.00039308288,"threshold_uncertainty_score":0.02099806},"labels":[],"label_agreement":null},{"id":"W2096275885","doi":"10.1155/s1110865704403023","title":"Downlink Channel Estimation in Cellular Systems with Antenna Arrays at Base Stations Using Channel Probing with Feedback","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University; Alexander von Humboldt-Stiftung","keywords":"Base station; Channel (broadcasting); Telecommunications link; Beamforming; Computer science; Antenna array; Antenna (radio); Electronic engineering; Telecommunications; Engineering","score_opus":0.01804801751183085,"score_gpt":0.2592908965294491,"score_spread":0.24124287901761823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096275885","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1652423,0.0011005335,0.83183,0.00022924974,0.000028288201,0.000026349155,0.000035071094,0.00035356646,0.0011546683],"genre_scores_gemma":[0.93694454,0.00044154262,0.061962243,0.000053144344,0.000026905363,0.000028116132,0.000033151748,0.000012468988,0.0004979243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919087,0.00038246787,0.000024267276,0.000079650265,0.00021018219,0.000112430986],"domain_scores_gemma":[0.9978523,0.0016853367,0.00013798293,0.00011372486,0.00017945364,0.00003111957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084534334,0.0006368066,0.00062671927,0.0003004662,0.0003133872,0.0004908492,0.00030535678,0.00061970815,0.00026740835],"category_scores_gemma":[0.0046789083,0.0003338948,0.00020534241,0.0005135498,0.00067008316,0.00080480386,0.0007518618,0.00042951157,0.00009567166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005935474,0.00007623499,0.003594008,0.000117046075,0.00007055103,0.00016133944,0.00021505597,0.80320495,0.024960587,0.0044361795,0.00054813473,0.1620225],"study_design_scores_gemma":[0.000011238658,0.00008537246,0.0004692021,0.0000037257907,0.000015305883,0.00004627891,0.000026259964,0.9927664,0.005376769,0.0010229943,0.00016704327,0.000009410043],"about_ca_topic_score_codex":0.0029491377,"about_ca_topic_score_gemma":0.0031513716,"teacher_disagreement_score":0.0029491377,"about_ca_system_score_codex":0.00044211457,"about_ca_system_score_gemma":0.00041027574,"threshold_uncertainty_score":0.0058639646},"labels":[],"label_agreement":null},{"id":"W2097098226","doi":"10.1186/1687-6180-2013-155","title":"Deterministic construction of Fourier-based compressed sensing matrices using an almost difference set","year":2013,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Compressed sensing; Block matrix; DFT matrix; Matrix (chemical analysis); Algorithm; Concatenation (mathematics); Fast Fourier transform; Discrete Fourier transform (general); Fourier transform; Mathematics; Sparse matrix; Single-entry matrix; Integer matrix; Row; Computer science; Combinatorics; Symmetric matrix; Short-time Fourier transform; Fourier analysis; Square matrix; Mathematical analysis; Nonnegative matrix; Physics","score_opus":0.029727312320954977,"score_gpt":0.2877581266520866,"score_spread":0.2580308143311316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097098226","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0061064223,0.00008558924,0.99213636,0.00007446399,0.000034345365,0.00002467374,0.000038498085,0.000072687784,0.0014269991],"genre_scores_gemma":[0.27906042,0.00043393398,0.7167882,0.00022288767,0.00012549275,0.00019622795,0.0003260953,0.00007561763,0.0027712085],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879277,0.00031707677,0.00006364333,0.00022214638,0.0005379099,0.00006637333],"domain_scores_gemma":[0.99852955,0.0007231981,0.00015628917,0.00027905244,0.00025787196,0.000054022807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009577027,0.0005917256,0.0005243991,0.00077900704,0.00040200684,0.00071914843,0.00084649393,0.0005855165,0.0019049774],"category_scores_gemma":[0.0035600048,0.00034618512,0.0006433017,0.00066509447,0.001016584,0.0012120706,0.0012121795,0.0011333951,0.00050896604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018538658,0.00009177327,0.0006393587,0.00020152888,0.000055231132,0.00022126421,0.0002323152,0.19194175,0.04050424,0.6089562,0.0023605747,0.15461043],"study_design_scores_gemma":[0.000022151893,0.00017490657,0.00021552606,0.000022955574,0.000012202664,0.00033379925,0.00003071233,0.92051244,0.014171075,0.058416873,0.006046071,0.000041335446],"about_ca_topic_score_codex":0.0005263554,"about_ca_topic_score_gemma":0.00052062667,"teacher_disagreement_score":0.0019049774,"about_ca_system_score_codex":0.0005304546,"about_ca_system_score_gemma":0.00067382754,"threshold_uncertainty_score":0.00637275},"labels":[],"label_agreement":null},{"id":"W2097467897","doi":"10.1186/1687-6180-2012-41","title":"Cooperative MIMO multicell networks","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; MIMO; Telecommunications; Computer network; Beamforming","score_opus":0.033806729268514794,"score_gpt":0.3225495827629747,"score_spread":0.2887428534944599,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097467897","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06556247,0.00523699,0.86865443,0.000886029,0.00072351587,0.00015226264,0.0004322499,0.0011327065,0.05721939],"genre_scores_gemma":[0.9237878,0.002842869,0.050843935,0.00042180528,0.00030780295,0.00015442715,0.00027001215,0.00004448155,0.021326808],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994289,0.00013305292,0.000015477217,0.000120304656,0.00018039951,0.00012176991],"domain_scores_gemma":[0.9991394,0.0003027143,0.00009665407,0.00013989727,0.00024785977,0.00007351231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038001096,0.00064806495,0.0006060546,0.000561008,0.0005469303,0.00105292,0.0011168342,0.00080357544,0.003613892],"category_scores_gemma":[0.00101626,0.00023897013,0.00037773422,0.00083445356,0.00046773427,0.000906178,0.0012109055,0.00061637675,0.0010608288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002984559,0.00013275792,0.0010385423,0.0003142594,0.00014101191,0.0008023693,0.00038945966,0.5949875,0.021752981,0.21279307,0.013047759,0.1543018],"study_design_scores_gemma":[0.000026922147,0.0001091276,0.00023740943,0.000017796216,0.000025469062,0.00022088637,0.000061821374,0.9475188,0.002621229,0.037191622,0.011938415,0.000030486372],"about_ca_topic_score_codex":0.003065331,"about_ca_topic_score_gemma":0.0032991231,"teacher_disagreement_score":0.003613892,"about_ca_system_score_codex":0.0009188994,"about_ca_system_score_gemma":0.0004702597,"threshold_uncertainty_score":0.01208967},"labels":[],"label_agreement":null},{"id":"W2097612980","doi":"10.1155/s111086570431111x","title":"High Capacity Downlink Transmission with MIMO Interference Subspace Rejection in Multicellular CDMA Networks","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Telecommunications link; Computer science; MIMO; Multiuser detection; Single antenna interference cancellation; Subspace topology; Interference (communication); Code division multiple access; Erlang (programming language); Detector; Electronic engineering; Algorithm; Computer network; Telecommunications; Theoretical computer science; Engineering; Artificial intelligence; Beamforming","score_opus":0.021920617904599628,"score_gpt":0.28240870257699,"score_spread":0.2604880846723904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097612980","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2696815,0.0010964888,0.72407144,0.00021449574,0.000025146965,0.00004006309,0.00004842131,0.000635787,0.0041866307],"genre_scores_gemma":[0.94841397,0.00019992243,0.05073442,0.00003956047,0.000017923947,0.00002719828,0.00002652403,0.000014638213,0.0005257112],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985629,0.00068853004,0.000032784836,0.0000925197,0.00043425895,0.00018906483],"domain_scores_gemma":[0.99667287,0.0021127055,0.00029916482,0.00036881343,0.00044430533,0.00010207519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018797365,0.00046322093,0.0007879182,0.00060613954,0.00054000417,0.00097449677,0.00058485445,0.0005123656,0.00047110903],"category_scores_gemma":[0.0051592314,0.00028663047,0.00021061237,0.0008202493,0.0008804712,0.0008421407,0.0010887079,0.0005932757,0.00016543322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006303109,0.00011678665,0.0030120711,0.00015031312,0.00007156223,0.00039447672,0.0002358422,0.84451145,0.04576727,0.021664543,0.00065098406,0.082794525],"study_design_scores_gemma":[0.0000176667,0.00008954035,0.0002913248,0.0000067899,0.000010693203,0.00008766983,0.000025831456,0.9781286,0.018168524,0.002653484,0.00050478464,0.000014967133],"about_ca_topic_score_codex":0.0016729063,"about_ca_topic_score_gemma":0.0014944595,"teacher_disagreement_score":0.0018797365,"about_ca_system_score_codex":0.00065989187,"about_ca_system_score_gemma":0.00051039486,"threshold_uncertainty_score":0.009941101},"labels":[],"label_agreement":null},{"id":"W2097907657","doi":"10.1155/asp.2005.649","title":"A MUSIC-Based Algorithm for Blind User Identification in Multiuser DS-CDMA","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Code division multiple access; Subspace topology; Computer science; Linear subspace; SIGNAL (programming language); Ambiguity; Algorithm; Multiuser detection; Signal subspace; Identification (biology); Interference (communication); Code (set theory); Scheme (mathematics); Transformation (genetics); Process (computing); Speech recognition; Theoretical computer science; Mathematics; Artificial intelligence; Telecommunications","score_opus":0.028616822579504528,"score_gpt":0.3375854192288836,"score_spread":0.30896859664937903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097907657","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022786492,0.00015133414,0.99677163,0.000038843475,0.000028597551,0.00002497603,0.0000142552535,0.00027656902,0.00041510267],"genre_scores_gemma":[0.057871666,0.00020803038,0.93997926,0.00005370129,0.000044798177,0.00012451869,0.00006572797,0.000039898736,0.0016123715],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99925953,0.00022136538,0.000050979965,0.00010008396,0.0003221913,0.00004575597],"domain_scores_gemma":[0.9995283,0.0001617935,0.000045380326,0.000067959896,0.0001724505,0.000024214061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007977077,0.00069459435,0.0006690297,0.00085176644,0.0006959368,0.00069596793,0.00072299485,0.0007916541,0.0015536058],"category_scores_gemma":[0.0020645494,0.00028786558,0.00045601002,0.0007891362,0.00065578165,0.0009992631,0.00082539,0.0008693616,0.0012074278],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004148403,0.00007973962,0.00054515013,0.0001326372,0.00005353077,0.00009733828,0.0001322815,0.09258246,0.035330515,0.04368217,0.002906016,0.82404333],"study_design_scores_gemma":[0.00004805263,0.0001231227,0.0003593226,0.000015243309,0.000015007114,0.00020666479,0.000019686542,0.96123475,0.018507931,0.013908183,0.0055213803,0.000040712835],"about_ca_topic_score_codex":0.0010229977,"about_ca_topic_score_gemma":0.0013240366,"teacher_disagreement_score":0.0015536058,"about_ca_system_score_codex":0.00044066092,"about_ca_system_score_gemma":0.00093601877,"threshold_uncertainty_score":0.0051972866},"labels":[],"label_agreement":null},{"id":"W2098279136","doi":"10.1155/asp.2005.775","title":"Parallel and Serial Concatenated Single Parity Check Product Codes","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Concatenation (mathematics); Computer science; Concatenated error correction code; Decoding methods; Serial concatenated convolutional codes; Algorithm; Arithmetic; Mathematics; Block code","score_opus":0.0195759247878482,"score_gpt":0.2851109752731551,"score_spread":0.2655350504853069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098279136","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16110088,0.0010462594,0.8206236,0.00031993774,0.0001457729,0.00008692526,0.0003289049,0.00069684006,0.015650924],"genre_scores_gemma":[0.84115195,0.00065664056,0.15065333,0.00013733252,0.0001297935,0.00012285345,0.00036765428,0.0000879427,0.0066926028],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987594,0.00023006133,0.000070734066,0.00017299804,0.0006613075,0.00010555701],"domain_scores_gemma":[0.9965759,0.0012364009,0.00056407927,0.00068786676,0.00083411706,0.00010164931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000762981,0.00058361184,0.0004863291,0.0006239521,0.00042512445,0.00087750127,0.0007091492,0.00052233884,0.0013774565],"category_scores_gemma":[0.005633165,0.0003386895,0.00033751834,0.00093973114,0.000759865,0.0010205859,0.0010641848,0.0007258187,0.0006940501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006432628,0.00008567494,0.005534727,0.00026286213,0.00011337557,0.0012973675,0.00019128801,0.5812469,0.05252843,0.16278416,0.0035951396,0.19171678],"study_design_scores_gemma":[0.000020163945,0.00018554961,0.0013640024,0.000025956286,0.000033295142,0.0012669583,0.000022657121,0.91666466,0.027480608,0.047685534,0.005211456,0.000039272516],"about_ca_topic_score_codex":0.00062986935,"about_ca_topic_score_gemma":0.00073310675,"teacher_disagreement_score":0.0013774565,"about_ca_system_score_codex":0.00047206137,"about_ca_system_score_gemma":0.0009251125,"threshold_uncertainty_score":0.0046080947},"labels":[],"label_agreement":null},{"id":"W2100014484","doi":"10.1155/s1110865704401024","title":"Estimating Intrinsic Camera Parameters from the Fundamental Matrix Using an Evolutionary Approach","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Carleton University","funders":"","keywords":"Epipolar geometry; Fundamental matrix (linear differential equation); Computer science; Camera auto-calibration; Computer vision; Artificial intelligence; Camera resectioning; Process (computing); Set (abstract data type); Calibration; Sequence (biology); Algorithm; Function (biology); Minification; Focal length; Image (mathematics); Mathematics; Optics","score_opus":0.03243355179095918,"score_gpt":0.33278497278961505,"score_spread":0.30035142099865586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100014484","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024205882,0.000087171065,0.97495055,0.00004992055,0.000008148683,0.000018101402,0.000016135025,0.00015033425,0.00051370275],"genre_scores_gemma":[0.19751534,0.00016593619,0.8006898,0.000037530503,0.000020371072,0.0000947589,0.00018970307,0.00010141125,0.0011851683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994597,0.00009735623,0.000024682953,0.00015691124,0.00021521845,0.00004618332],"domain_scores_gemma":[0.99858725,0.000587579,0.00020295662,0.0001567215,0.0004199488,0.000045509536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010808047,0.000814161,0.0009793829,0.0012943945,0.00051762315,0.00088251976,0.0010190197,0.0011658375,0.0009235888],"category_scores_gemma":[0.004359651,0.0007455983,0.0008444593,0.0010768044,0.0005770744,0.001183091,0.0008095098,0.0009802767,0.0003202302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000451174,0.00006581851,0.0021298758,0.00006335116,0.000074380354,0.00008878541,0.0001230588,0.6821439,0.02382214,0.009546065,0.00066873117,0.28122875],"study_design_scores_gemma":[0.00000529663,0.000016232236,0.00047086924,0.000004940789,0.000009326128,0.000042888365,0.0000102134545,0.9939413,0.002538477,0.0025024235,0.00044780146,0.000010209054],"about_ca_topic_score_codex":0.004169355,"about_ca_topic_score_gemma":0.0047224867,"teacher_disagreement_score":0.004169355,"about_ca_system_score_codex":0.00073646114,"about_ca_system_score_gemma":0.0011155306,"threshold_uncertainty_score":0.008290172},"labels":[],"label_agreement":null},{"id":"W2100396823","doi":"10.1155/s1110865704408142","title":"Autonomous Mobile Robot That Can Read","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Pentium; Mobile robot; Robot; Zoom; Computer vision; Artificial intelligence; Process (computing); Social robot; Character (mathematics); Robot control; Engineering","score_opus":0.021960648483362537,"score_gpt":0.3178272352320062,"score_spread":0.29586658674864363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100396823","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23256111,0.001099816,0.6845395,0.00089830393,0.00049611187,0.00052327476,0.0004218715,0.019194689,0.060265258],"genre_scores_gemma":[0.592967,0.00037734478,0.3424618,0.0003472403,0.00012082919,0.0005016223,0.0007119997,0.00024695715,0.06226531],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985397,0.000013251918,0.0000051045304,0.00004985573,0.000054829386,0.000022985627],"domain_scores_gemma":[0.99967337,0.00006862952,0.00003451992,0.00008762108,0.00008063507,0.00005520172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015639266,0.0004754399,0.0006013732,0.00023193884,0.0004261382,0.0005468357,0.00078669493,0.0011024462,0.007840799],"category_scores_gemma":[0.00055647275,0.00025225576,0.00026128994,0.00016557555,0.00046488902,0.0012020647,0.0007528422,0.00054954673,0.0040634843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062691234,0.00030828218,0.0018439954,0.0004467975,0.00005829119,0.0014954235,0.0005588922,0.023657382,0.63988864,0.01559072,0.019420657,0.29610404],"study_design_scores_gemma":[0.0005709294,0.002727359,0.007526926,0.00010501943,0.000121906734,0.0032581165,0.000593862,0.5370646,0.20789434,0.01732127,0.22259896,0.00021668008],"about_ca_topic_score_codex":0.00092817255,"about_ca_topic_score_gemma":0.0013253518,"teacher_disagreement_score":0.007840799,"about_ca_system_score_codex":0.00021030015,"about_ca_system_score_gemma":0.00040176112,"threshold_uncertainty_score":0.026230156},"labels":[],"label_agreement":null},{"id":"W2100666253","doi":"10.1186/1687-6180-2012-88","title":"Efficient blind decoders for additive spread spectrum embedding based data hiding","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Decoding methods; Embedding; Algorithm; Watermark; Computer science; Digital watermarking; Discrete cosine transform; Information hiding; Discrete Fourier transform (general); Mathematics; Fourier transform; Image (mathematics); Artificial intelligence; Fourier analysis; Fractional Fourier transform","score_opus":0.04376237567971395,"score_gpt":0.349406259138135,"score_spread":0.30564388345842103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100666253","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0074858284,0.00034981963,0.9908297,0.00005650693,0.000023659857,0.00002120941,0.000023481085,0.00013129163,0.0010785135],"genre_scores_gemma":[0.44775406,0.0014954676,0.5444022,0.00015520172,0.000094338335,0.00010080616,0.00014066012,0.00007955646,0.005777775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903774,0.00023412956,0.00006218625,0.00011666862,0.0004788297,0.00007047619],"domain_scores_gemma":[0.9991303,0.00045288366,0.00010116231,0.000098945726,0.00019177454,0.00002504731],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007961118,0.0008335706,0.0007449715,0.0007203024,0.00036412355,0.0007991997,0.00059941015,0.00091448036,0.0015198071],"category_scores_gemma":[0.0028848809,0.00033485625,0.0004618233,0.0005957332,0.0007209112,0.0015204925,0.0009547749,0.00093040423,0.00082722463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044404797,0.00014578758,0.00083379616,0.00052951864,0.0001326787,0.00025227218,0.00034309505,0.38943022,0.13935502,0.15184727,0.0018720317,0.31481433],"study_design_scores_gemma":[0.00002035415,0.00008889115,0.000108725326,0.000024504749,0.000031005664,0.00022033631,0.000025224981,0.9386585,0.04649219,0.011682622,0.0026192022,0.00002847183],"about_ca_topic_score_codex":0.00051775586,"about_ca_topic_score_gemma":0.00093293545,"teacher_disagreement_score":0.0015198071,"about_ca_system_score_codex":0.0004771684,"about_ca_system_score_gemma":0.0008547926,"threshold_uncertainty_score":0.0050842166},"labels":[],"label_agreement":null},{"id":"W2102377326","doi":"10.1155/s1110865703305128","title":"An Efficient Feature Extraction Method with Pseudo-Zernike Moment in RBF Neural Network-Based Human Face Recognition System","year":2003,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":87,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Zernike polynomials; Artificial intelligence; Computer science; Pattern recognition (psychology); Facial recognition system; Feature extraction; Artificial neural network; Radial basis function; Face (sociological concept); Computer vision; Moment (physics)","score_opus":0.020168874623293784,"score_gpt":0.31761110340111665,"score_spread":0.29744222877782284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102377326","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011227932,0.0002742682,0.9868838,0.000058448448,0.000051391882,0.000045716293,0.000031868585,0.0007597021,0.0006669172],"genre_scores_gemma":[0.2258223,0.00040986715,0.7699364,0.00007938101,0.00007265429,0.00015883964,0.00018483502,0.00006777927,0.0032679206],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948573,0.00007892944,0.000026733784,0.0000943047,0.00028284438,0.00003146623],"domain_scores_gemma":[0.9997234,0.000056573528,0.00003149533,0.000035443416,0.00014207211,0.00001101642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061398634,0.00044893462,0.0007121429,0.00056177104,0.00023484477,0.00037440687,0.0007454349,0.00061286904,0.0013907983],"category_scores_gemma":[0.000952537,0.00022715531,0.00044967816,0.0004389309,0.00019433856,0.00075802754,0.00034892713,0.00047556523,0.0008758331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030984843,0.00010574888,0.0007088836,0.00022765622,0.000064299915,0.00012355801,0.00006464466,0.02347985,0.19382511,0.0034748153,0.0025058382,0.7751097],"study_design_scores_gemma":[0.000056323333,0.00035245388,0.0033332258,0.000020481984,0.00007490262,0.0007367308,0.000021583026,0.8444966,0.14052138,0.0013049758,0.009014472,0.000066814595],"about_ca_topic_score_codex":0.0012151698,"about_ca_topic_score_gemma":0.001158541,"teacher_disagreement_score":0.0013907983,"about_ca_system_score_codex":0.00028388336,"about_ca_system_score_gemma":0.00029098167,"threshold_uncertainty_score":0.0046526194},"labels":[],"label_agreement":null},{"id":"W2103856048","doi":"10.1155/asp.2005.575","title":"Simplifying Physical Realization of Gaussian Particle Filters with Block-Level Pipeline Control","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Society of Interventional Radiology Foundation","keywords":"Computer science; Realization (probability); Pipeline (software); Block (permutation group theory); Controller (irrigation); Control reconfiguration; Verilog; Parallel computing; Field-programmable gate array; Embedded system","score_opus":0.01929345983658817,"score_gpt":0.28584903284677016,"score_spread":0.266555573010182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103856048","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0098814545,0.000070949674,0.98732424,0.00005196039,0.000024536299,0.000041424693,0.000023438704,0.0006947942,0.0018872753],"genre_scores_gemma":[0.48425493,0.00017781804,0.513104,0.000058647332,0.00001825276,0.00015697775,0.000110155415,0.00008171579,0.0020375792],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997613,0.000034318353,0.000019444162,0.000037709273,0.000117570795,0.000029754061],"domain_scores_gemma":[0.9997671,0.000082818246,0.000032787895,0.000056345918,0.0000526809,0.000008270668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034758396,0.00035576255,0.0002089064,0.00020605633,0.0002137585,0.00055099354,0.0006371958,0.0003279527,0.001980105],"category_scores_gemma":[0.00081987976,0.00021974796,0.00025786328,0.0002024672,0.0003911923,0.0006548052,0.0002938882,0.00052138424,0.00041218862],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027116018,0.00013237739,0.0010580792,0.00036447935,0.000047806552,0.000400899,0.00028583975,0.37446904,0.22794229,0.15854865,0.0025732508,0.23390615],"study_design_scores_gemma":[0.00005250306,0.00017931276,0.00029933167,0.000013036033,0.00001856411,0.00009948889,0.000013719734,0.92141193,0.054822903,0.010626909,0.012448755,0.000013575681],"about_ca_topic_score_codex":0.0019174333,"about_ca_topic_score_gemma":0.0023687626,"teacher_disagreement_score":0.001980105,"about_ca_system_score_codex":0.00045363238,"about_ca_system_score_gemma":0.0010462726,"threshold_uncertainty_score":0.0066241026},"labels":[],"label_agreement":null},{"id":"W2103882108","doi":"10.1186/1687-6180-2012-16","title":"SSIM-inspired image restoration using sparse representation","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sparse approximation; Metric (unit); Image quality; Mean squared error; Computer science; Norm (philosophy); Gradient descent; Representation (politics); Artificial intelligence; Pattern recognition (psychology); Image restoration; Algorithm; Peak signal-to-noise ratio; Image (mathematics); Mathematics; Image processing; Statistics; Artificial neural network","score_opus":0.04963724024173807,"score_gpt":0.36971601822226563,"score_spread":0.32007877798052753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103882108","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006085368,0.00015698164,0.99240875,0.00008420229,0.000023900991,0.000016130125,0.000014446917,0.0001758629,0.0010343107],"genre_scores_gemma":[0.16943601,0.0005463863,0.8263031,0.00014948836,0.0000634689,0.00008168835,0.00015465281,0.00011072414,0.0031544778],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973065,0.000062312756,0.00001414845,0.000030707368,0.0001460277,0.00001615229],"domain_scores_gemma":[0.9995871,0.0001379743,0.000061396815,0.00006279365,0.00013099685,0.000019854424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005949019,0.0005511188,0.0006697579,0.00067865435,0.00017817375,0.0005556592,0.0006739345,0.0007272928,0.0012271953],"category_scores_gemma":[0.0014633643,0.00023290457,0.0006147645,0.00074836344,0.0005574174,0.00093818933,0.0008042786,0.000714026,0.00051502313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020652964,0.00011220194,0.00058504875,0.0004078553,0.000103424136,0.00020383889,0.00022071262,0.3760531,0.14202154,0.059176546,0.004154597,0.41675463],"study_design_scores_gemma":[0.000007895169,0.000045932873,0.00012023051,0.000009343112,0.000008931148,0.00013593442,0.000011460375,0.9760384,0.015511945,0.0059588365,0.0021408289,0.000010147618],"about_ca_topic_score_codex":0.00048825907,"about_ca_topic_score_gemma":0.00071596046,"teacher_disagreement_score":0.0012271953,"about_ca_system_score_codex":0.00033212928,"about_ca_system_score_gemma":0.0003993465,"threshold_uncertainty_score":0.004105389},"labels":[],"label_agreement":null},{"id":"W2104033031","doi":"10.1155/s1110865702209038","title":"Multiuser Delay-Tracking CDMA Receiver","year":2003,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Government of Canada","keywords":"Computer science; Code division multiple access; Single antenna interference cancellation; Multiuser detection; Algorithm; SIGNAL (programming language); Fading; Spread spectrum; Chip; Demodulation; Group delay and phase delay; Delay spread; Propagation of uncertainty; Detector; Control theory (sociology); Telecommunications; Channel (broadcasting); Bandwidth (computing); Artificial intelligence; Decoding methods","score_opus":0.03538073528887042,"score_gpt":0.3386004977682455,"score_spread":0.3032197624793751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104033031","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018035568,0.0011751698,0.9740007,0.00023598196,0.0003352058,0.00006784682,0.000076855955,0.0014622498,0.0046104193],"genre_scores_gemma":[0.3069746,0.0006769523,0.6767036,0.00056099106,0.0003009951,0.00009477565,0.00014632386,0.000042442356,0.014499247],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932134,0.00010628814,0.00002626061,0.0001769994,0.00028989185,0.00007937765],"domain_scores_gemma":[0.9995054,0.000111417714,0.000049865594,0.00012125738,0.00017775827,0.000034163324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006434249,0.0005428259,0.0007488899,0.0005044932,0.00037073635,0.0007986139,0.0013327376,0.0010083065,0.00225262],"category_scores_gemma":[0.0010196773,0.0003160814,0.00045573298,0.0004745364,0.00023654388,0.0009627064,0.0007166516,0.00074412464,0.0019639146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075500755,0.00032261922,0.0030259995,0.00028689337,0.00017963316,0.00041034725,0.00011640396,0.1074233,0.2587485,0.03691571,0.0051075113,0.58670807],"study_design_scores_gemma":[0.00009331193,0.00042598572,0.0006304343,0.000021097258,0.000098209326,0.0006523968,0.000010033125,0.8906411,0.08587828,0.0043853708,0.01711596,0.00004796608],"about_ca_topic_score_codex":0.0005784999,"about_ca_topic_score_gemma":0.0010096692,"teacher_disagreement_score":0.00225262,"about_ca_system_score_codex":0.00049273437,"about_ca_system_score_gemma":0.00072782015,"threshold_uncertainty_score":0.0075357556},"labels":[],"label_agreement":null},{"id":"W2105720907","doi":"10.1186/1687-6180-2011-139","title":"Performance evaluation of space-time-frequency spreading for MIMO OFDM-CDMA systems","year":2011,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"MIMO-OFDM; Orthogonal frequency-division multiplexing; Computer science; MIMO; Code division multiple access; Multiplexing; Throughput; Diversity gain; Electronic engineering; Transmit diversity; Telecommunications; Real-time computing; Fading; Beamforming; Engineering; Wireless; Channel (broadcasting)","score_opus":0.08229697516428548,"score_gpt":0.3464442065610594,"score_spread":0.26414723139677393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105720907","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.832821,0.0031690241,0.14603454,0.00027245883,0.000085200496,0.00007532165,0.00016266732,0.00041898293,0.016960815],"genre_scores_gemma":[0.9958923,0.00019381802,0.0035175025,0.000010364071,0.000009311653,0.000006426612,0.00004087546,0.000008781842,0.00032063283],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984535,0.00055799726,0.0000670917,0.00010239857,0.0006363589,0.00018261031],"domain_scores_gemma":[0.9951839,0.0030949072,0.00030228865,0.000267195,0.0010651565,0.00008660863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001565991,0.0006744778,0.0004370812,0.0006926202,0.0003867493,0.00066989835,0.0002929058,0.0005361609,0.0011888031],"category_scores_gemma":[0.0060723973,0.000100137506,0.00023860973,0.0007604669,0.00037851103,0.00062478817,0.00045631328,0.00024774467,0.00023414698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078366586,0.00008422124,0.007935669,0.00022314524,0.00009835537,0.0002532228,0.000103275976,0.9076984,0.024253469,0.005288867,0.00043052962,0.052847255],"study_design_scores_gemma":[0.00001588145,0.00049381383,0.0033769615,0.000014270564,0.000033517746,0.0002338438,0.000056839654,0.9813533,0.013099086,0.000924681,0.00037678928,0.000021040141],"about_ca_topic_score_codex":0.002334935,"about_ca_topic_score_gemma":0.0017185147,"teacher_disagreement_score":0.002334935,"about_ca_system_score_codex":0.0008094249,"about_ca_system_score_gemma":0.0004678689,"threshold_uncertainty_score":0.008281887},"labels":[],"label_agreement":null},{"id":"W2106830952","doi":"10.1155/s1110865704403114","title":"Design of Ultraspherical Window Functions with Prescribed Spectral Characteristics","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Ripple; Main lobe; Computer science; Side lobe; Window (computing); Window function; Algorithm; Telecommunications; Spectral density; Power (physics); Physics","score_opus":0.017653811309207897,"score_gpt":0.2774860106362932,"score_spread":0.2598321993270853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106830952","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014398897,0.00013962398,0.9842917,0.000026952257,0.00001722789,0.00003912449,0.00002031675,0.00016977021,0.0008964311],"genre_scores_gemma":[0.21525995,0.00039082288,0.78226,0.000043907716,0.000028860128,0.00025253196,0.00007378588,0.00013247973,0.0015575993],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99972683,0.00007516969,0.000022556607,0.000038312162,0.000102344224,0.000034791396],"domain_scores_gemma":[0.99917954,0.00032599634,0.00014724123,0.00007611424,0.00022101143,0.000050024544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064921234,0.00077115727,0.00043649852,0.00043524784,0.00023427785,0.0006248903,0.00068976765,0.0004351655,0.0011693737],"category_scores_gemma":[0.0014705083,0.00031188887,0.0002965166,0.0004012178,0.00037315334,0.00062480423,0.00039962414,0.00050959055,0.00047276047],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063546654,0.00015497975,0.0010536084,0.00042179957,0.000074977965,0.000271061,0.00031851523,0.12556805,0.4474195,0.074005574,0.002152644,0.3479239],"study_design_scores_gemma":[0.0000862521,0.00036980407,0.0005794896,0.000033713633,0.000036637462,0.00031314755,0.000058527854,0.79310334,0.18533206,0.00843549,0.011600917,0.000050582028],"about_ca_topic_score_codex":0.00025226272,"about_ca_topic_score_gemma":0.0003404373,"teacher_disagreement_score":0.0011693737,"about_ca_system_score_codex":0.00034418906,"about_ca_system_score_gemma":0.00046108323,"threshold_uncertainty_score":0.003911972},"labels":[],"label_agreement":null},{"id":"W2106841063","doi":"10.1155/s1110865704312151","title":"Group-Oriented Fingerprinting for Multimedia Forensics","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":81,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Air Force Research Laboratory; National Science Foundation","keywords":"Collusion; Computer science; Computer security; Identification (biology); Scheme (mathematics); Adversary","score_opus":0.01433442165376406,"score_gpt":0.28925192611389183,"score_spread":0.27491750446012775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106841063","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03928967,0.0015779191,0.9543937,0.0003350645,0.00007929816,0.00009749795,0.00008544674,0.0008306414,0.003310744],"genre_scores_gemma":[0.5113233,0.001444329,0.48488253,0.00010390266,0.000105363906,0.00007942249,0.00012132586,0.00004202301,0.0018977851],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999371,0.00025397676,0.00002650004,0.00007266397,0.00021321433,0.00006274842],"domain_scores_gemma":[0.9981481,0.00066867564,0.0001938806,0.0007524639,0.00018293875,0.00005407999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093652675,0.00043215932,0.0005366502,0.0012662032,0.00056041294,0.00064910774,0.00068289397,0.001318928,0.0020763257],"category_scores_gemma":[0.0030540326,0.00022210632,0.00036289197,0.0012201704,0.00070482737,0.0015303872,0.00093275454,0.00070659345,0.0006618791],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004806275,0.00016847037,0.0021041504,0.00025836003,0.00006742816,0.00037965638,0.00021901088,0.09428007,0.114712216,0.06466344,0.0037430043,0.71892357],"study_design_scores_gemma":[0.000058255257,0.00032667347,0.0018168399,0.00009364941,0.00007518945,0.0013452355,0.00018948884,0.8057963,0.111366645,0.06010059,0.018755507,0.00007555863],"about_ca_topic_score_codex":0.00038514644,"about_ca_topic_score_gemma":0.0004494512,"teacher_disagreement_score":0.0020763257,"about_ca_system_score_codex":0.00045331233,"about_ca_system_score_gemma":0.00040468687,"threshold_uncertainty_score":0.0069460273},"labels":[],"label_agreement":null},{"id":"W2107461080","doi":"10.1155/asp.2005.25","title":"Performance of GCC- and AMDF-Based Time-Delay Estimation in Practical Reverberant Environments","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Estimator; Reverberation; Computer science; Noise (video); Function (biology); Speech recognition; Weighting; Algorithm; Artificial intelligence; Statistics; Mathematics; Acoustics","score_opus":0.010590949599210343,"score_gpt":0.28350737558428585,"score_spread":0.2729164259850755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107461080","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4892827,0.0027407361,0.50129694,0.0002207739,0.00023191914,0.00004964678,0.0002676166,0.0033454502,0.0025642528],"genre_scores_gemma":[0.7934006,0.00048016917,0.20392464,0.00011031884,0.00005926889,0.000030151643,0.0005535335,0.00012120177,0.0013201277],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991942,0.00017522274,0.000060519622,0.00018127367,0.00029803324,0.00009083089],"domain_scores_gemma":[0.99701667,0.0013311503,0.00028517353,0.00028902444,0.0009660895,0.00011199692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001484063,0.000975403,0.0006783782,0.0011514752,0.00027331302,0.0005564661,0.00074854493,0.0010459397,0.00093516486],"category_scores_gemma":[0.0075282026,0.00024133884,0.00038798933,0.00069499365,0.00034825466,0.0008220737,0.00067471113,0.0005364504,0.00043741593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022409768,0.0002033388,0.025202,0.00033625186,0.00031931527,0.00045328267,0.00035227736,0.23414987,0.115305185,0.002212597,0.001965308,0.61725956],"study_design_scores_gemma":[0.000062422616,0.0002586149,0.013643979,0.00003672426,0.000082333514,0.00058666937,0.0000668234,0.9143439,0.0685879,0.0004398959,0.0017857306,0.00010501023],"about_ca_topic_score_codex":0.007233962,"about_ca_topic_score_gemma":0.0051993397,"teacher_disagreement_score":0.007233962,"about_ca_system_score_codex":0.00037022174,"about_ca_system_score_gemma":0.00087434775,"threshold_uncertainty_score":0.014383674},"labels":[],"label_agreement":null},{"id":"W2108331676","doi":"10.1155/2010/740130","title":"Moving Target Indication via RADARSAT-2 Multichannel Synthetic Aperture Radar Processing","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Moving target indication; Synthetic aperture radar; Computer science; Inverse synthetic aperture radar; Remote sensing; Radar; Stationary target indication; Radar imaging; Computer vision; Artificial intelligence; Bistatic radar; Geology; Continuous-wave radar; Telecommunications","score_opus":0.007155603609034557,"score_gpt":0.26213102341418915,"score_spread":0.2549754198051546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108331676","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18278547,0.00027865721,0.8106405,0.00018249656,0.000055197313,0.000055595552,0.0004119564,0.0016313428,0.003958702],"genre_scores_gemma":[0.52973914,0.00018184548,0.46668997,0.00007302037,0.00005398463,0.00003986382,0.0007875712,0.00009230798,0.002342272],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999759,0.000066001856,0.000009802025,0.00005560406,0.000089479625,0.000020073358],"domain_scores_gemma":[0.99972624,0.00009993076,0.000051662602,0.000034660425,0.000076995704,0.000010580919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006130239,0.00045641788,0.0002711355,0.00046896556,0.00011756094,0.00041585098,0.00033720763,0.00029334094,0.0008181768],"category_scores_gemma":[0.0013099031,0.00015448869,0.00020224608,0.0005497547,0.00018493438,0.00063463877,0.0003316863,0.0003574048,0.00036488372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007483251,0.00010644094,0.005819667,0.00020449537,0.000062356085,0.00017210386,0.00017565336,0.25643146,0.19936973,0.010177858,0.003782824,0.5229491],"study_design_scores_gemma":[0.000038165737,0.0001602707,0.004937344,0.000014591109,0.000024117751,0.00019661176,0.00003022737,0.94980365,0.039076567,0.0020638392,0.0036169626,0.000037589514],"about_ca_topic_score_codex":0.0012550175,"about_ca_topic_score_gemma":0.0027516559,"teacher_disagreement_score":0.0012550175,"about_ca_system_score_codex":0.00021828533,"about_ca_system_score_gemma":0.00035173993,"threshold_uncertainty_score":0.0032420158},"labels":[],"label_agreement":null},{"id":"W2108487450","doi":"10.1186/1687-6180-2013-146","title":"Special Issue on “advanced distributed wireless communication techniques - theory and practice”","year":2013,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Universität Bremen; Aristotle University of Thessaloniki; Killam Trusts; University of Toronto; Universität Stuttgart; Technische Universität Dresden; Deutsche Forschungsgemeinschaft; Deutscher Akademischer Austauschdienst; Vodafone Foundation; University of British Columbia; Alexander von Humboldt-Stiftung","keywords":"Computer science; Wireless; Communication theory; Telecommunications; Distributed computing; Sociology; Communication","score_opus":0.0096169475687896,"score_gpt":0.2893318987346032,"score_spread":0.2797149511658136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108487450","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007555349,0.04194722,0.00756452,0.01730226,0.83045197,0.00023440942,0.00050075824,0.00044245226,0.10080098],"genre_scores_gemma":[0.004519723,0.033901658,0.0019515958,0.0056222016,0.7775194,0.00020379563,0.0009947179,0.0004528451,0.17483398],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.997232,0.00038456812,0.00025912494,0.00041786936,0.0014817992,0.0002245165],"domain_scores_gemma":[0.9934574,0.0015536216,0.0005079137,0.00054871687,0.0029169593,0.001015426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002273331,0.0025452308,0.0034449953,0.00479934,0.0015471389,0.0050865943,0.002261381,0.0042855474,0.09995005],"category_scores_gemma":[0.0058089285,0.0006556222,0.0015130551,0.0029181172,0.0011545775,0.0033625527,0.0026715535,0.0036737411,0.04867125],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000066802786,0.000056335728,0.00015043047,0.00049609825,0.00002733991,0.00009496827,0.000013713757,0.00021708083,0.0006860329,0.003673945,0.94080997,0.05370741],"study_design_scores_gemma":[0.000017900193,0.0000853101,0.00060193206,0.00021850677,0.000029104576,0.00025222322,0.000014981924,0.0006841879,0.00034171718,0.0034193823,0.99431926,0.000015680658],"about_ca_topic_score_codex":0.00064087164,"about_ca_topic_score_gemma":0.0011768433,"teacher_disagreement_score":0.09995005,"about_ca_system_score_codex":0.0016257524,"about_ca_system_score_gemma":0.0017896045,"threshold_uncertainty_score":0.3343662},"labels":[],"label_agreement":null},{"id":"W2108611115","doi":"10.1186/1687-6180-2012-50","title":"Novel methodologies for spectral classification of exon and intron sequences","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Fractal and DNA sequence analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; University of Ottawa; University of Windsor","funders":"","keywords":"Sequence (biology); Algorithm; Representation (politics); Intron; Threshold limit value; Computer science; Exon; Mathematics; Biology; Genetics","score_opus":0.06180294203904813,"score_gpt":0.36821578548264083,"score_spread":0.3064128434435927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108611115","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011412344,0.00013818494,0.98687893,0.000042161588,0.000039164006,0.000030439473,0.000049987404,0.00034266917,0.0010661641],"genre_scores_gemma":[0.09642007,0.0003089184,0.9010718,0.00004007376,0.00004899387,0.0000879824,0.00022890298,0.000091506416,0.0017017887],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939764,0.00011209513,0.000063614076,0.00014654454,0.00023824621,0.000041837226],"domain_scores_gemma":[0.9989343,0.00029031924,0.00017627417,0.00018404951,0.00036520747,0.000049860257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057135546,0.0005129906,0.00034269603,0.0019624224,0.00041796512,0.001066483,0.00073248905,0.0005549026,0.001984145],"category_scores_gemma":[0.0023409284,0.00018336205,0.00044697404,0.0014950259,0.00068898645,0.0015029166,0.00055675925,0.000743457,0.0010401505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014555597,0.000089865694,0.0013579755,0.0002900355,0.000025289373,0.00013761985,0.00031316472,0.020810727,0.16728346,0.059233043,0.0016815625,0.7486317],"study_design_scores_gemma":[0.000023625895,0.00021476929,0.0024559898,0.000080514605,0.00003711611,0.00095711474,0.00027682044,0.79368925,0.13252456,0.053116005,0.016542647,0.00008156225],"about_ca_topic_score_codex":0.0005205976,"about_ca_topic_score_gemma":0.0006125602,"teacher_disagreement_score":0.001984145,"about_ca_system_score_codex":0.00046682404,"about_ca_system_score_gemma":0.00065187586,"threshold_uncertainty_score":0.006637633},"labels":[],"label_agreement":null},{"id":"W2109573991","doi":"10.1155/2010/451695","title":"Audio Signal Processing Using Time-Frequency Approaches: Coding, Classification, Fingerprinting, and Watermarking","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Music and Audio Processing","field":"Computer Science","cited_by":97,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Digital watermarking; Audio signal; Digital audio; Speech coding; Audio signal processing; Speech recognition; Coding (social sciences); Psychoacoustics; Signal processing; Artificial intelligence; Digital signal processing; Perception; Computer hardware","score_opus":0.04103532990992343,"score_gpt":0.2835590867445217,"score_spread":0.24252375683459826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109573991","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009767645,0.020816352,0.961947,0.0005199982,0.0003858852,0.00006969971,0.000051482035,0.00038090392,0.0060610007],"genre_scores_gemma":[0.2271005,0.044171575,0.70888054,0.0006119869,0.0020326748,0.00017195765,0.0002725953,0.00010659401,0.016651511],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99953806,0.00007967171,0.000026292044,0.00008185586,0.00024841854,0.00002562515],"domain_scores_gemma":[0.9995209,0.00018242569,0.00007170136,0.000064157124,0.00014296557,0.000017860462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005889306,0.0007059641,0.0004531339,0.0015476288,0.00029912143,0.0010622755,0.0005723256,0.0015604404,0.0015437617],"category_scores_gemma":[0.0014530206,0.0002045075,0.0004341897,0.0025473828,0.0010436584,0.0015954509,0.0005134485,0.0007548037,0.0010140153],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014033476,0.00007255629,0.00054207037,0.00056767056,0.00004187679,0.00017795284,0.00014969848,0.014108174,0.0908326,0.03297355,0.003010368,0.8573832],"study_design_scores_gemma":[0.00006112108,0.0010441546,0.005554676,0.00052508403,0.00022320784,0.004786387,0.00036967927,0.5747241,0.18466473,0.11539971,0.11237011,0.00027703305],"about_ca_topic_score_codex":0.001029313,"about_ca_topic_score_gemma":0.0007787009,"teacher_disagreement_score":0.0015604404,"about_ca_system_score_codex":0.0002997269,"about_ca_system_score_gemma":0.0002780612,"threshold_uncertainty_score":0.005164385},"labels":[],"label_agreement":null},{"id":"W2110405445","doi":"10.1155/s1110865702000550","title":"Compressive Data Hiding: An Unconventional Approach for Improved Color Image Coding","year":2002,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Chrominance; Computer science; Artificial intelligence; JPEG; Computer vision; Set partitioning in hierarchical trees; Luminance; Lossy compression; Color image; Image compression; Grayscale; Data compression; Information hiding; Color Cell Compression; Color space; JPEG 2000; Redundancy (engineering); Image processing; Image (mathematics)","score_opus":0.06403384618954394,"score_gpt":0.32855494307723565,"score_spread":0.2645210968876917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110405445","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040788308,0.0010262706,0.9512163,0.0010382441,0.00017384092,0.00007240032,0.000047470156,0.00031769736,0.005319413],"genre_scores_gemma":[0.45996577,0.001856177,0.5321319,0.00045733876,0.00031192016,0.00007958042,0.000087346,0.000049033497,0.0050609293],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997894,0.000026434638,0.0000073443175,0.000022837012,0.00013926762,0.000014658387],"domain_scores_gemma":[0.9997389,0.000078312194,0.000032414817,0.00007131298,0.00006726769,0.000011848657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026522018,0.00039508883,0.00023370514,0.00037521642,0.00017323514,0.00034026743,0.0005258945,0.00051374634,0.0010512918],"category_scores_gemma":[0.0009784348,0.00011932996,0.00022209891,0.00041614624,0.0006242177,0.00094258005,0.00058254035,0.00067845907,0.00027782508],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027084033,0.00011847596,0.0005925931,0.0002944711,0.000054614677,0.00028486902,0.00018711067,0.0347172,0.5784072,0.07127122,0.0022654303,0.3115359],"study_design_scores_gemma":[0.00007753772,0.00050382654,0.00080003875,0.000064645705,0.000057326255,0.0014024549,0.000053393906,0.5525467,0.40810442,0.018698905,0.017634606,0.00005607792],"about_ca_topic_score_codex":0.000477394,"about_ca_topic_score_gemma":0.00086372136,"teacher_disagreement_score":0.0010512918,"about_ca_system_score_codex":0.00024268476,"about_ca_system_score_gemma":0.00033315964,"threshold_uncertainty_score":0.0035168529},"labels":[],"label_agreement":null},{"id":"W2113888395","doi":"10.1186/1687-6180-2014-37","title":"Single-channel noise reduction using unified joint diagonalization and optimal filtering","year":2014,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Danmarks Frie Forskningsfond; Villum Fonden","keywords":"Distortion (music); Wiener filter; Filter (signal processing); Mathematics; SIGNAL (programming language); Noise (video); Algorithm; Noise reduction; Signal-to-noise ratio (imaging); Rank (graph theory); Covariance matrix; Control theory (sociology); Computer science; Statistics; Telecommunications; Artificial intelligence; Bandwidth (computing); Combinatorics","score_opus":0.032832105436107664,"score_gpt":0.27274243022626,"score_spread":0.23991032479015234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113888395","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022478455,0.00017437713,0.99643683,0.000046021425,0.000020327025,0.000011912433,0.000009033682,0.000075299315,0.0009783057],"genre_scores_gemma":[0.3217721,0.0011675891,0.6705835,0.00023352883,0.00018294908,0.00024763754,0.00018702913,0.00015380738,0.0054718973],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989492,0.00022400216,0.00006239542,0.00024176609,0.00039131218,0.00013131024],"domain_scores_gemma":[0.99949336,0.00021254607,0.00006913377,0.00007346391,0.00013114631,0.00002037775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011398401,0.001239933,0.0015753943,0.00063376594,0.00055210834,0.0013705636,0.000960994,0.0012190418,0.0015031813],"category_scores_gemma":[0.0016274762,0.00058916217,0.0011455308,0.0008809646,0.0011656915,0.0014553699,0.001311338,0.0011167119,0.0005819871],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020059367,0.00014164712,0.00042395273,0.00029187847,0.00014810314,0.0001809981,0.00026163482,0.66735977,0.031252217,0.10198394,0.002299229,0.19545607],"study_design_scores_gemma":[0.000010790249,0.0000452134,0.00006754745,0.000013011504,0.000014160809,0.000038070815,0.000014227461,0.9849952,0.0029994347,0.010734962,0.0010491044,0.00001831638],"about_ca_topic_score_codex":0.0032634807,"about_ca_topic_score_gemma":0.0036133942,"teacher_disagreement_score":0.0032634807,"about_ca_system_score_codex":0.00066356454,"about_ca_system_score_gemma":0.0014770222,"threshold_uncertainty_score":0.006488979},"labels":[],"label_agreement":null},{"id":"W2114495165","doi":"10.1155/s1110865704311194","title":"Channel Estimation and Data Detection for MIMO Systems under Spatially and Temporally Colored Interference","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"MIMO; Interference (communication); Computer science; Spatial correlation; Channel (broadcasting); Rayleigh fading; Algorithm; Fading; Telecommunications","score_opus":0.035487472751737324,"score_gpt":0.31797771791925333,"score_spread":0.28249024516751603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114495165","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06529266,0.00026030466,0.9327334,0.00024219713,0.0000194792,0.000014954832,0.000037466372,0.00019279076,0.0012066661],"genre_scores_gemma":[0.8041394,0.0003813757,0.19425118,0.000105954816,0.00004526813,0.000047241898,0.00009521327,0.00002086036,0.00091366906],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898964,0.00036907327,0.000032888118,0.00010036534,0.00037572393,0.0001323345],"domain_scores_gemma":[0.9958229,0.0030095815,0.0002949884,0.00030499182,0.0004946754,0.000072844974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017362441,0.00049210095,0.00058941916,0.00042503854,0.00031263637,0.00079134636,0.00042950417,0.0008490907,0.00056493096],"category_scores_gemma":[0.009825889,0.0003061406,0.00030543335,0.0005879743,0.00091163686,0.0012309232,0.0008330148,0.0005486029,0.00021016544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003665747,0.00007621446,0.0037383307,0.00014245528,0.00009484772,0.0003497123,0.00017196468,0.82580423,0.025004948,0.026145345,0.0006020132,0.11750332],"study_design_scores_gemma":[0.000015053923,0.000054145177,0.0006855874,0.000006596635,0.000013267088,0.00011053434,0.00003200164,0.98299396,0.009682431,0.0061505614,0.00024250105,0.000013279316],"about_ca_topic_score_codex":0.0015630428,"about_ca_topic_score_gemma":0.0026926026,"teacher_disagreement_score":0.0017362441,"about_ca_system_score_codex":0.0005942607,"about_ca_system_score_gemma":0.0014183734,"threshold_uncertainty_score":0.009182215},"labels":[],"label_agreement":null},{"id":"W2114545952","doi":"10.1186/1687-6180-2012-85","title":"Advances in single carrier block modulation with frequency domain processing","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Telecommunications link; Orthogonal frequency-division multiple access; Computer science; Frequency-division multiple access; Orthogonal frequency-division multiplexing; Modulation (music); Base station; Electronic engineering; Equalization (audio); Block (permutation group theory); Frequency domain; Telecommunications; Computer network; Channel (broadcasting); Engineering; Mathematics; Physics","score_opus":0.011470857294522943,"score_gpt":0.2617386367942173,"score_spread":0.25026777949969436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114545952","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018032404,0.04768226,0.86285454,0.003451475,0.0020324143,0.000095717354,0.000113497976,0.0005125103,0.06522522],"genre_scores_gemma":[0.21650323,0.08148443,0.6184697,0.0012863893,0.005632841,0.00014812902,0.00045202335,0.00021628974,0.07580698],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99969864,0.00006093052,0.000016412838,0.000049176266,0.00015754334,0.000017243703],"domain_scores_gemma":[0.99919564,0.0003566911,0.000038974908,0.00009294945,0.00028900328,0.000026831753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068209553,0.00046465197,0.00044506625,0.00073109707,0.00019012776,0.00084700104,0.00039457672,0.0007919695,0.006798939],"category_scores_gemma":[0.0016475024,0.00020806515,0.00022157075,0.0010912872,0.00043345915,0.0012142187,0.00050511025,0.0011454162,0.0028211488],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000089408066,0.00010426119,0.00052500045,0.0004735129,0.000028755047,0.000116182615,0.000116347044,0.0104095135,0.045836996,0.06471526,0.007281781,0.87030303],"study_design_scores_gemma":[0.000051096496,0.0006967358,0.0040749297,0.0004696439,0.00008749641,0.0017919188,0.00012743771,0.33292946,0.080631964,0.08714963,0.49188167,0.000107963824],"about_ca_topic_score_codex":0.00027293988,"about_ca_topic_score_gemma":0.0003649484,"teacher_disagreement_score":0.006798939,"about_ca_system_score_codex":0.00026123913,"about_ca_system_score_gemma":0.00041251213,"threshold_uncertainty_score":0.022744775},"labels":[],"label_agreement":null},{"id":"W2116635162","doi":"10.1155/asp/2006/26503","title":"Time Delay Estimation in Room Acoustic Environments: An Overview","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":368,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Reverberation; Computer science; Sonar; Noise (video); Identification (biology); Ranging; Channel (broadcasting); Radar; Estimation; Acoustics; Telecommunications; Speech recognition; Real-time computing; Artificial intelligence; Engineering; Systems engineering","score_opus":0.015113347188334283,"score_gpt":0.2898631340188438,"score_spread":0.2747497868305095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116635162","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004257919,0.20536144,0.78463817,0.00033772681,0.0004635631,0.000047204496,0.00007479068,0.00042615403,0.0043930756],"genre_scores_gemma":[0.09079365,0.4795448,0.41587847,0.00039412634,0.0043768752,0.00016710082,0.000496493,0.00019676411,0.008151685],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995702,0.00007707536,0.00004777838,0.00010617387,0.00017548521,0.000023291408],"domain_scores_gemma":[0.9993303,0.00037718244,0.00004043415,0.00003531866,0.00019299348,0.000023816938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069511286,0.0009266337,0.0009312957,0.0016482373,0.00023902231,0.0014998342,0.000705003,0.0016137994,0.0015743797],"category_scores_gemma":[0.001262734,0.0006036337,0.0005550496,0.002670253,0.000517578,0.0021336358,0.0005955299,0.0011231472,0.0018714053],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018664479,0.00011775536,0.0013935163,0.0032114945,0.0001338775,0.00035775237,0.00019664777,0.04549277,0.018393872,0.027118715,0.008183896,0.8952131],"study_design_scores_gemma":[0.00007250719,0.0010433365,0.0055420357,0.0008970266,0.0003382105,0.0043894364,0.0003678768,0.5742239,0.03069821,0.050892796,0.33119065,0.00034401187],"about_ca_topic_score_codex":0.0017443557,"about_ca_topic_score_gemma":0.0008706934,"teacher_disagreement_score":0.0017443557,"about_ca_system_score_codex":0.00030277445,"about_ca_system_score_gemma":0.00042387607,"threshold_uncertainty_score":0.0052667856},"labels":[],"label_agreement":null},{"id":"W2117155258","doi":"10.1186/1687-6180-2012-185","title":"Remotely-sensed TOA interpretation of synthetic UWB based on neural networks","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Ultra-Wideband Communications Technology","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Program for New Century Excellent Talents in University","keywords":"Computer science; Time of arrival; Robustness (evolution); Algorithm; Ultra-wideband; Artificial neural network; Metric (unit); Ranging; Channel (broadcasting); Energy (signal processing); Real-time computing; Artificial intelligence; Telecommunications; Mathematics","score_opus":0.009132804830651226,"score_gpt":0.2566937253094969,"score_spread":0.24756092047884568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117155258","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52461076,0.00052251335,0.46620867,0.00033121,0.00020713631,0.000046616246,0.00035588726,0.001268868,0.0064482754],"genre_scores_gemma":[0.94791204,0.00016552574,0.05065091,0.00005151869,0.00003429065,0.000024562552,0.00022575694,0.00004718122,0.0008883154],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998646,0.000041066687,0.000008044804,0.00003446533,0.000034613622,0.000017323415],"domain_scores_gemma":[0.999706,0.000119591845,0.00004095513,0.00002365649,0.0000974975,0.00001223201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029065507,0.00056732196,0.00031082053,0.0006982237,0.00015101746,0.000568938,0.00040659594,0.00045713724,0.0009351796],"category_scores_gemma":[0.0012878231,0.00018818658,0.00036220555,0.000517751,0.00025690647,0.00055203936,0.00031886448,0.0003558891,0.00028720274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000576206,0.00013404277,0.004165658,0.00016065402,0.00009115373,0.00043503853,0.00013237316,0.72018385,0.072087914,0.0020223428,0.0013718841,0.19863887],"study_design_scores_gemma":[0.000005132406,0.000015908015,0.0013588237,0.000008004675,0.000010546249,0.000046281035,0.000020696994,0.9935696,0.004232162,0.0005359785,0.00018679809,0.000010098815],"about_ca_topic_score_codex":0.0013580007,"about_ca_topic_score_gemma":0.001388118,"teacher_disagreement_score":0.0013580007,"about_ca_system_score_codex":0.00029369662,"about_ca_system_score_gemma":0.0001961473,"threshold_uncertainty_score":0.003128469},"labels":[],"label_agreement":null},{"id":"W2118481608","doi":"10.1155/s1110865703301027","title":"Rapid Prototyping of Field Programmable Gate Array-Based Discrete Cosine Transform Approximations","year":2003,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Discrete cosine transform; Field-programmable gate array; Datapath; Quantization (signal processing); Computer science; Gate array; Algorithm; Mean squared error; Computer hardware; Mathematics; Embedded system; Artificial intelligence","score_opus":0.024910604612713712,"score_gpt":0.3049897489856568,"score_spread":0.28007914437294307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118481608","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040245067,0.0005041336,0.94785,0.00016856338,0.00025660227,0.00024263031,0.000103453676,0.0020644064,0.008565152],"genre_scores_gemma":[0.27486417,0.00044604196,0.7182618,0.000097572134,0.000039532035,0.00025778371,0.00020220327,0.00021466943,0.0056162146],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993824,0.00008976945,0.00003345851,0.000052491454,0.00039717907,0.000044629458],"domain_scores_gemma":[0.999005,0.00040338296,0.00009217775,0.00015472918,0.00029479977,0.00005001657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005892748,0.0005074805,0.00034281204,0.00038141478,0.00018427976,0.00063056214,0.0008257382,0.00039789983,0.0026734394],"category_scores_gemma":[0.0027067324,0.00028398164,0.00030147337,0.00021675434,0.00027289876,0.0006016644,0.0003110968,0.00064918667,0.0009385457],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048288307,0.00013064391,0.00079075614,0.0004312281,0.000058857135,0.0008653394,0.00026499457,0.09096905,0.5656076,0.032249466,0.00544313,0.30270603],"study_design_scores_gemma":[0.00020676517,0.0012671471,0.0008542132,0.00008642572,0.00004561575,0.0011332784,0.000060167044,0.44203138,0.48285088,0.004104582,0.06728883,0.000070759015],"about_ca_topic_score_codex":0.0005311741,"about_ca_topic_score_gemma":0.0006938421,"teacher_disagreement_score":0.0026734394,"about_ca_system_score_codex":0.00036643303,"about_ca_system_score_gemma":0.0003690182,"threshold_uncertainty_score":0.008943558},"labels":[],"label_agreement":null},{"id":"W2118738916","doi":"10.1155/s111086570220414x","title":"Low-Complexity Versatile Finite Field Multiplier in Normal Basis","year":2002,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Coding theory and cryptography","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina; University of Lethbridge","funders":"","keywords":"Multiplier (economics); Very-large-scale integration; Computer science; Pipeline (software); Finite field; Basis (linear algebra); Arithmetic; Computational science; Computer hardware; Computer architecture; Mathematics; Embedded system; Discrete mathematics","score_opus":0.027146521306878724,"score_gpt":0.268918607304453,"score_spread":0.24177208599757427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118738916","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08828315,0.0007165964,0.8917197,0.00025204316,0.00018544662,0.00010299221,0.00016153147,0.0014000068,0.017178517],"genre_scores_gemma":[0.5793024,0.00050246704,0.40593752,0.00013716877,0.00011521087,0.00011004806,0.00029681847,0.000076060096,0.013522324],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99986005,0.00003187854,0.000009108547,0.000030130574,0.000045427438,0.000023451306],"domain_scores_gemma":[0.9998528,0.000031699656,0.00002062083,0.000028266679,0.000050869738,0.000015741287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021759691,0.00038334882,0.0003737803,0.00042687717,0.000391276,0.00046287506,0.0006360763,0.00032579375,0.0052122525],"category_scores_gemma":[0.00040737833,0.00019860035,0.00026669112,0.00061424036,0.00024202162,0.0009225458,0.00040990242,0.0005008641,0.0013416857],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083085743,0.00010724326,0.00078944094,0.00044962353,0.000068615394,0.0006688053,0.0002070987,0.021636574,0.42976812,0.15827139,0.00855108,0.3786512],"study_design_scores_gemma":[0.00029072163,0.002923846,0.0015188566,0.00014162413,0.00018230513,0.0047885245,0.00014075307,0.32989433,0.44065836,0.098078914,0.12118168,0.00020011954],"about_ca_topic_score_codex":0.00022839037,"about_ca_topic_score_gemma":0.00046054224,"teacher_disagreement_score":0.0052122525,"about_ca_system_score_codex":0.000323201,"about_ca_system_score_gemma":0.00040797621,"threshold_uncertainty_score":0.017436683},"labels":[],"label_agreement":null},{"id":"W2120857402","doi":"10.1155/asp.2005.1736","title":"Design Verification and Performance Evaluation of an Enhanced Wideband CDMA Receiver Using Channel Measurements","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multipath propagation; Wideband; Channel (broadcasting); Computer science; Delay spread; Electronic engineering; Power delay profile; Code division multiple access; Doppler effect; Power (physics); Telecommunications; Physics; Engineering","score_opus":0.14345330888917276,"score_gpt":0.3787856059851118,"score_spread":0.23533229709593903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120857402","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39115375,0.00022702171,0.60195637,0.00018950546,0.000076482036,0.00018614324,0.00017383101,0.00218991,0.0038470477],"genre_scores_gemma":[0.8939657,0.000085164844,0.10419689,0.000057926038,0.000024647765,0.000054749253,0.00013080715,0.000056651035,0.0014275186],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976386,0.00083399186,0.00017262551,0.00034333122,0.00087097054,0.00014041184],"domain_scores_gemma":[0.9964011,0.0011917506,0.00035166068,0.0005864931,0.001397141,0.000071881084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029610519,0.0005528426,0.0006132681,0.00032648185,0.00026031496,0.00065968884,0.0007336473,0.00076170533,0.0010401456],"category_scores_gemma":[0.004862348,0.00029081307,0.00038842898,0.00019512302,0.0003751082,0.00073448993,0.00043604148,0.00045793448,0.0005756425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003762375,0.00052768947,0.0108344415,0.0006863092,0.0003081313,0.0004425427,0.0004031934,0.31712413,0.48582938,0.0079977205,0.0010176589,0.17106643],"study_design_scores_gemma":[0.00019877213,0.0025279867,0.002639449,0.000017870241,0.00010618767,0.00039628247,0.00003855267,0.67682964,0.3145646,0.00034948354,0.0022975954,0.000033617194],"about_ca_topic_score_codex":0.00071140047,"about_ca_topic_score_gemma":0.0006064946,"teacher_disagreement_score":0.0029610519,"about_ca_system_score_codex":0.00042940985,"about_ca_system_score_gemma":0.00066675374,"threshold_uncertainty_score":0.01565975},"labels":[],"label_agreement":null},{"id":"W2121711322","doi":"10.1186/1687-6180-2014-77","title":"An orthogonal wavelet division multiple-access processor architecture for LTE-advanced wireless/radio-over-fiber systems over heterogeneous networks","year":2014,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Orthogonal frequency-division multiple access; Radio over fiber; Wireless; Field-programmable gate array; Clock rate; Wireless network; Throughput; Orthogonal frequency-division multiplexing; Computer network; Electronic engineering; Embedded system; Channel (broadcasting); Chip; Telecommunications; Engineering","score_opus":0.010730956873979573,"score_gpt":0.28242416313123697,"score_spread":0.2716932062572574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121711322","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17865905,0.0011721372,0.79737884,0.00028265067,0.00019275497,0.00021047115,0.00014282101,0.0021265813,0.019834608],"genre_scores_gemma":[0.83017427,0.0003904856,0.16240858,0.00013043308,0.000043556938,0.000096894415,0.00018833751,0.000034623936,0.006532856],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999187,0.000017522318,0.000005979832,0.000016148657,0.000027288297,0.00001442254],"domain_scores_gemma":[0.9999479,0.000010055203,0.00000840227,0.0000081960725,0.000021521959,0.000003924347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010709508,0.00019277705,0.00011622571,0.00017992487,0.0001831541,0.00032762554,0.0003394634,0.00015177,0.0019934694],"category_scores_gemma":[0.00018327952,0.00007728115,0.00014531186,0.00015301078,0.00006969721,0.0002462251,0.00011339149,0.00024199877,0.00036943462],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004341827,0.00017411346,0.002042878,0.0003047376,0.00009404988,0.00067277235,0.00014555705,0.059954114,0.4141095,0.025746204,0.007889568,0.48843238],"study_design_scores_gemma":[0.00015403988,0.001765836,0.0031999429,0.0000740261,0.00013852706,0.0009883202,0.00006064093,0.7603424,0.17275165,0.0040271636,0.05645531,0.000042097825],"about_ca_topic_score_codex":0.0008709166,"about_ca_topic_score_gemma":0.0015455384,"teacher_disagreement_score":0.0019934694,"about_ca_system_score_codex":0.00027531246,"about_ca_system_score_gemma":0.0003647846,"threshold_uncertainty_score":0.0066688657},"labels":[],"label_agreement":null},{"id":"W2127666915","doi":"10.1155/s1110865704402212","title":"Generic Multimedia Multimodal Agents Paradigms and Their Dynamic Reconfiguration at the Architectural Level","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control reconfiguration; Computer science; Adaptation (eye); Architecture; Dialog box; Distributed computing; Intelligent agent; Human–computer interaction; Computer architecture; Multimedia; Artificial intelligence; Embedded system; World Wide Web","score_opus":0.028347314156366304,"score_gpt":0.28154152841324137,"score_spread":0.25319421425687505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127666915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049966183,0.0007359794,0.9341487,0.00030474688,0.000047963378,0.00013192717,0.000055695506,0.0007445654,0.013864205],"genre_scores_gemma":[0.5034579,0.0009413,0.48636457,0.00018110011,0.000043370943,0.0003806625,0.00019265995,0.00009971726,0.008338676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995542,0.00015117391,0.00004071092,0.00009128894,0.000107349864,0.000055183667],"domain_scores_gemma":[0.9996165,0.00006304766,0.000058231693,0.0001415406,0.000080590515,0.000040046874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007430543,0.00050862995,0.00025536455,0.00040555716,0.0004983855,0.0012879935,0.0010145038,0.0010210065,0.001331781],"category_scores_gemma":[0.00094791665,0.00025966528,0.00058936526,0.00031772742,0.0011341689,0.0018953445,0.0011601262,0.0008721444,0.00041529894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016834018,0.00008515565,0.0016882234,0.00031429727,0.00009874309,0.00073119596,0.0014915444,0.12522423,0.06847262,0.67139643,0.0028801945,0.12744905],"study_design_scores_gemma":[0.00004353069,0.00018699735,0.0014406712,0.000086129636,0.00011797971,0.000766568,0.00048481175,0.64835626,0.034807444,0.24031234,0.07332885,0.00006838314],"about_ca_topic_score_codex":0.0009830527,"about_ca_topic_score_gemma":0.0014752025,"teacher_disagreement_score":0.001331781,"about_ca_system_score_codex":0.0007071037,"about_ca_system_score_gemma":0.000476078,"threshold_uncertainty_score":0.00513041},"labels":[],"label_agreement":null},{"id":"W2128714178","doi":"10.1155/asp.2005.1047","title":"An FPGA-Based People Detection System","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; JPEG; MicroBlaze; Field-programmable gate array; Discrete cosine transform; Frame rate; Computer hardware; Artificial intelligence; Process (computing); Background subtraction; Computer vision; Embedded system; Real-time computing; Data compression; Pixel; Image (mathematics)","score_opus":0.011486478433701954,"score_gpt":0.3024103474440572,"score_spread":0.2909238690103553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128714178","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1955375,0.0021606847,0.69790214,0.00069399574,0.001332808,0.0008437897,0.0013065931,0.051536698,0.048685722],"genre_scores_gemma":[0.78955424,0.0007730045,0.17968778,0.00074165344,0.00022348744,0.00037595312,0.0010552038,0.00023088316,0.02735787],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996947,0.000029320161,0.000018276069,0.00007973346,0.00013400272,0.00004411862],"domain_scores_gemma":[0.99979585,0.000039107257,0.000019965995,0.000024279932,0.00008690468,0.000033884622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018987087,0.0005248394,0.0005726855,0.0009781081,0.00032725435,0.0005050229,0.00086638826,0.00048375866,0.009021124],"category_scores_gemma":[0.0003756389,0.00021535272,0.0001862176,0.0003700014,0.00014486238,0.00049928634,0.00043250344,0.00029841159,0.0032668312],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015573656,0.00038015572,0.006912206,0.0006368767,0.00014227224,0.0012551536,0.00025016413,0.010215344,0.1923434,0.0037587837,0.038857676,0.74369055],"study_design_scores_gemma":[0.0007704541,0.0027563896,0.022612913,0.00033537787,0.0004890411,0.0064531676,0.00027291494,0.40129068,0.40315554,0.0028424347,0.15872262,0.0002984324],"about_ca_topic_score_codex":0.001552513,"about_ca_topic_score_gemma":0.0017824831,"teacher_disagreement_score":0.009021124,"about_ca_system_score_codex":0.0003329158,"about_ca_system_score_gemma":0.00034823176,"threshold_uncertainty_score":0.030178726},"labels":[],"label_agreement":null},{"id":"W2128899090","doi":"10.1186/1687-6180-2012-118","title":"Multispectral texture characterization: application to computer aided diagnosis on prostatic tissue images","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen's University","keywords":"Multispectral image; Artificial intelligence; Computer science; Pattern recognition (psychology); Spectral bands; Texture (cosmology); Computer vision; Image texture; Image processing; Image (mathematics); Remote sensing; Geography","score_opus":0.009789660375040416,"score_gpt":0.2767334285487104,"score_spread":0.26694376817367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128899090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52589244,0.001147894,0.46964362,0.00022113335,0.000038467,0.000108968154,0.00020991445,0.0012770023,0.0014605245],"genre_scores_gemma":[0.85891396,0.00031843598,0.1400822,0.00003743024,0.000021677013,0.000027341697,0.00008493598,0.000032758606,0.0004812222],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998375,0.0000468989,0.000009416275,0.00002483578,0.00006448408,0.000016855078],"domain_scores_gemma":[0.9995876,0.0002020686,0.0000492319,0.00003491847,0.00010426131,0.000021976959],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037963022,0.00026790265,0.0002481733,0.0024000462,0.00012786679,0.0003484167,0.00017732938,0.00038701558,0.0010807202],"category_scores_gemma":[0.00097145257,0.00012181617,0.00026134675,0.0009354148,0.00020136325,0.00018137867,0.00022825778,0.00016619623,0.00020172377],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006399512,0.00015434138,0.0096307285,0.0004940582,0.00007035829,0.00058378954,0.00020964218,0.049061004,0.4552125,0.00095647806,0.00065955677,0.4823275],"study_design_scores_gemma":[0.000026961296,0.00019821733,0.030459892,0.000027510529,0.000072398376,0.0012517051,0.00014989752,0.83358335,0.13194351,0.00083410053,0.00141643,0.000035958627],"about_ca_topic_score_codex":0.0010282412,"about_ca_topic_score_gemma":0.0008985213,"teacher_disagreement_score":0.0024000462,"about_ca_system_score_codex":0.0001524184,"about_ca_system_score_gemma":0.0001417475,"threshold_uncertainty_score":0.0036153793},"labels":[],"label_agreement":null},{"id":"W2129961876","doi":"10.1186/1687-6180-2014-162","title":"A brief overview of speech enhancement with linear filtering","year":2014,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Danmarks Frie Forskningsfond; Villum Fonden","keywords":"Speech enhancement; Computer science; Speech recognition; Artificial intelligence; Noise reduction","score_opus":0.02417315718196709,"score_gpt":0.3041992503486555,"score_spread":0.2800260931666884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129961876","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023688588,0.19899099,0.7677139,0.00080341735,0.00095784006,0.000101764046,0.00014060002,0.00076412695,0.028158566],"genre_scores_gemma":[0.078775756,0.36235455,0.50562423,0.0019078862,0.0063462886,0.00033397842,0.0006058163,0.0002942043,0.04375727],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99972075,0.000055508735,0.000030227564,0.00007494591,0.000101062265,0.000017453644],"domain_scores_gemma":[0.9997794,0.0001259891,0.000016444277,0.00001808193,0.0000524611,0.000007669663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044632048,0.00083985634,0.0006893398,0.0011423723,0.00025857132,0.0011851698,0.0006705,0.0013049068,0.004853238],"category_scores_gemma":[0.00045319003,0.00048231933,0.0006352645,0.001205383,0.0005133927,0.0014267069,0.00057121087,0.0013176692,0.0029122573],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013751694,0.00013161763,0.00042380544,0.004049501,0.00011430122,0.00047806898,0.00023135066,0.017944865,0.043220825,0.10595288,0.013077771,0.81423753],"study_design_scores_gemma":[0.000031365013,0.000650232,0.001796859,0.0012471074,0.00015685409,0.0026372424,0.00011519945,0.11301462,0.036291994,0.07584689,0.76801264,0.00019899006],"about_ca_topic_score_codex":0.00062134484,"about_ca_topic_score_gemma":0.0004118893,"teacher_disagreement_score":0.004853238,"about_ca_system_score_codex":0.0004070615,"about_ca_system_score_gemma":0.00029665543,"threshold_uncertainty_score":0.01623571},"labels":[],"label_agreement":null},{"id":"W2130614494","doi":"10.1186/1687-6180-2012-151","title":"Detection method of flexion relaxation phenomenon based on wavelets for patients with low back pain","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Musculoskeletal pain and rehabilitation","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wavelet; Computer science; Repeatability; Low back pain; Wavelet transform; Wavelet packet decomposition; Pattern recognition (psychology); Artificial intelligence; Mathematics; Medicine; Statistics; Pathology","score_opus":0.010559241433143941,"score_gpt":0.3068098891776058,"score_spread":0.29625064774446186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130614494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65968883,0.00047663206,0.33805043,0.000112347036,0.00006990891,0.00010911273,0.00024524776,0.000393464,0.00085400726],"genre_scores_gemma":[0.9315752,0.00034693888,0.06721328,0.000035808025,0.00005255288,0.000087955144,0.00018074817,0.000027051803,0.00048050858],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99961394,0.00013430457,0.000033039858,0.00007464261,0.00011817099,0.000025931951],"domain_scores_gemma":[0.99914825,0.00033652768,0.0001631935,0.00007496523,0.00024125428,0.000035783305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005558923,0.00034307656,0.00033501972,0.0008010108,0.00009813121,0.0002873098,0.00026675343,0.0005508644,0.000660614],"category_scores_gemma":[0.002713909,0.00011557608,0.00023583298,0.00045036367,0.00012835176,0.0003086881,0.00023058848,0.00024967085,0.00040164316],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002244695,0.00039335914,0.058075685,0.0007856554,0.00012391378,0.0011919235,0.00048126793,0.009519323,0.34588963,0.0006262896,0.001467925,0.5792003],"study_design_scores_gemma":[0.00020594303,0.0022661632,0.27254274,0.000104549246,0.00029016432,0.0050427094,0.00052288687,0.5442702,0.17040516,0.0015110133,0.0027157285,0.00012270393],"about_ca_topic_score_codex":0.00026733518,"about_ca_topic_score_gemma":0.00027175713,"teacher_disagreement_score":0.0008010108,"about_ca_system_score_codex":0.00007314769,"about_ca_system_score_gemma":0.00014883593,"threshold_uncertainty_score":0.00293988},"labels":[],"label_agreement":null},{"id":"W2131391877","doi":"10.1155/s1110865703301015","title":"A Methodology for Rapid Prototyping Peak-Constrained Least-Squares Bit-Serial Finite Impulse Response Filters in FPGAs","year":2003,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Field-programmable gate array; Finite impulse response; Bitstream; Computer hardware; Virtex; Embedded system; Algorithm; Decoding methods","score_opus":0.0739556401258799,"score_gpt":0.3611863760328273,"score_spread":0.2872307359069474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131391877","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00204027,0.000028553315,0.99539584,0.000016467888,0.000019032746,0.00005125519,0.0000161345,0.0015082657,0.0009241354],"genre_scores_gemma":[0.035737023,0.00006975701,0.96192366,0.000022897308,0.000008548896,0.00014460688,0.00006362572,0.00022146838,0.0018084904],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99941206,0.00009079309,0.000049581788,0.000070002396,0.00033827953,0.000039412378],"domain_scores_gemma":[0.9993086,0.00020322473,0.00006890058,0.0001628394,0.00023021307,0.000026166403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058901845,0.00063872134,0.0003028657,0.0004846744,0.00030196755,0.0006194814,0.00090988696,0.00033662113,0.0050384365],"category_scores_gemma":[0.0014616534,0.00045372624,0.0003921515,0.00027623874,0.0003743398,0.00050743215,0.0003588601,0.0006185633,0.0013491182],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016805837,0.00007484584,0.0007359624,0.00054481666,0.00007872786,0.0005696701,0.00028591917,0.060855106,0.29532862,0.037337735,0.0055567874,0.5984637],"study_design_scores_gemma":[0.00018787694,0.00061052816,0.0010543459,0.00012079498,0.00006935363,0.0019999347,0.0000926829,0.41561136,0.4549954,0.012817135,0.11235438,0.000086255284],"about_ca_topic_score_codex":0.0007311354,"about_ca_topic_score_gemma":0.0012196358,"teacher_disagreement_score":0.0050384365,"about_ca_system_score_codex":0.0002950432,"about_ca_system_score_gemma":0.0004909421,"threshold_uncertainty_score":0.01685524},"labels":[],"label_agreement":null},{"id":"W2134264161","doi":"10.1155/s1110865704402042","title":"Optimal STBC Precoding with Channel Covariance Feedback for Minimum Error Probability","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Precoding; Beamforming; Space–time block code; Computer science; Transmitter; Decoding methods; MIMO; Algorithm; Covariance; Block code; Covariance matrix; Channel (broadcasting); Transformation (genetics); Control theory (sociology); Mathematics; Mathematical optimization; Telecommunications; Statistics; Artificial intelligence","score_opus":0.02721339231101231,"score_gpt":0.2938873628640294,"score_spread":0.26667397055301706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134264161","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016862238,0.00021554925,0.97909373,0.00028702003,0.000024097646,0.000028904933,0.000075153876,0.0001324442,0.003280818],"genre_scores_gemma":[0.7358042,0.0007217351,0.25758195,0.00020841011,0.00011430099,0.00018873248,0.0002083642,0.00011693435,0.005055335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869955,0.00040299282,0.00005301898,0.00013252691,0.00056335295,0.00014861474],"domain_scores_gemma":[0.9981487,0.0012149493,0.00019428736,0.00014243515,0.0002551926,0.00004444422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009609249,0.0008935525,0.0010336308,0.00034967103,0.00039060498,0.0008621143,0.00063403754,0.0009651795,0.0013442758],"category_scores_gemma":[0.0052478174,0.0003743575,0.00038927383,0.00088756764,0.0013166268,0.0012169906,0.00078391854,0.0007946592,0.00048960315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000099776524,0.000028150429,0.00021498396,0.00009208963,0.000029231922,0.00009286289,0.00010661394,0.84754956,0.0061027575,0.11472843,0.0012189002,0.02973658],"study_design_scores_gemma":[0.00002737879,0.00003729525,0.00008175823,0.000013660644,0.0000071794843,0.00004710013,0.000013352495,0.9458886,0.0028052155,0.050440274,0.00062788976,0.000010335037],"about_ca_topic_score_codex":0.0021792194,"about_ca_topic_score_gemma":0.002233761,"teacher_disagreement_score":0.0021792194,"about_ca_system_score_codex":0.0009792416,"about_ca_system_score_gemma":0.0022078855,"threshold_uncertainty_score":0.0071049333},"labels":[],"label_agreement":null},{"id":"W2136254992","doi":"10.1155/asp.2005.183","title":"Cross-Layer Resource Allocation for Variable Bit Rate Multiclass Services in a Multirate Multicarrier DS-CDMA Network","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Quality of service; Computer network; Network packet; Code division multiple access; Resource allocation; Link layer; Physical layer; Bit error rate; Channel (broadcasting); Telecommunications; Wireless","score_opus":0.027146047681877304,"score_gpt":0.3482001863142992,"score_spread":0.32105413863242194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136254992","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.092755295,0.00070831494,0.900629,0.0002553258,0.000044520453,0.000055057277,0.00003287231,0.00014843309,0.0053711785],"genre_scores_gemma":[0.9416394,0.00040481772,0.055205435,0.00008239586,0.000030655563,0.0000683695,0.000024602903,0.000038855662,0.0025053106],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953115,0.00017882182,0.000012915532,0.00005136692,0.00011801391,0.00010784115],"domain_scores_gemma":[0.9995121,0.0002853172,0.00006270463,0.000030302814,0.00007933786,0.000030224655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010073761,0.0005930829,0.0005599102,0.00038887025,0.0005008345,0.0011040616,0.0007116731,0.0005923276,0.0017826045],"category_scores_gemma":[0.0019255528,0.00037657647,0.00032568973,0.0004440867,0.00058276945,0.0009648794,0.0007450762,0.0005265483,0.0002340885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044484244,0.000023884912,0.00021911036,0.000032268734,0.000015459336,0.000068800444,0.000044745957,0.9713651,0.0029967364,0.013792279,0.00036254944,0.011034533],"study_design_scores_gemma":[0.0000028274937,0.000008999246,0.0000341008,0.0000015459427,0.0000034147515,0.0000116898655,0.000008177684,0.9983215,0.00027710342,0.0012120481,0.00011661666,0.0000020546906],"about_ca_topic_score_codex":0.0045176474,"about_ca_topic_score_gemma":0.0047618235,"teacher_disagreement_score":0.0045176474,"about_ca_system_score_codex":0.0016095449,"about_ca_system_score_gemma":0.0011184089,"threshold_uncertainty_score":0.011678159},"labels":[],"label_agreement":null},{"id":"W2137827918","doi":"10.1186/1687-6180-2012-192","title":"EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer’s disease","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Electroencephalography; Metric (unit); Computer science; Pattern recognition (psychology); Maximization; Artificial intelligence; Support vector machine; Classifier (UML); Speech recognition; Mathematics; Psychology; Neuroscience","score_opus":0.05055506876944835,"score_gpt":0.35726742520700056,"score_spread":0.30671235643755224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137827918","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29703146,0.0043630023,0.6852639,0.00040767816,0.00015567664,0.00037182833,0.0027333659,0.005784144,0.0038890168],"genre_scores_gemma":[0.75782156,0.00082500675,0.23857152,0.00007624216,0.00011184909,0.00027003244,0.0015645362,0.00008896729,0.0006703149],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992987,0.00030359003,0.00006623303,0.00009997064,0.00020350801,0.000028047127],"domain_scores_gemma":[0.9982315,0.0009708227,0.00025380915,0.00015885652,0.00031695268,0.00006804841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010885757,0.00074769335,0.00073411694,0.0026457715,0.00018664084,0.00070478366,0.0005453816,0.00047383463,0.0016395857],"category_scores_gemma":[0.0044480837,0.00020158071,0.00028256213,0.0011482161,0.00019314687,0.0005291851,0.00047522402,0.00043113434,0.0009561007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011388698,0.00026029765,0.020460613,0.00043846315,0.00016628587,0.00026090178,0.000116627205,0.014991112,0.08872108,0.0010831719,0.005220306,0.8671423],"study_design_scores_gemma":[0.00018167862,0.0005882325,0.1100347,0.00010565303,0.00014696698,0.0015108443,0.00016724336,0.8406863,0.03605487,0.00479483,0.0056251045,0.0001035852],"about_ca_topic_score_codex":0.000997532,"about_ca_topic_score_gemma":0.0016099595,"teacher_disagreement_score":0.0026457715,"about_ca_system_score_codex":0.00019971616,"about_ca_system_score_gemma":0.00036790755,"threshold_uncertainty_score":0.005756974},"labels":[],"label_agreement":null},{"id":"W2139181200","doi":"10.1155/s1110865704309285","title":"A Digital Signal Processing Method for Gene Prediction with Improved Noise Suppression","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Fractal and DNA sequence analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Coding (social sciences); Computer science; Digital signal processing; Algorithm; Coding region; Gene; Gene prediction; Speech recognition; Pattern recognition (psychology); Artificial intelligence; Mathematics; Biology; Genetics; Genome; Statistics","score_opus":0.008302830274343368,"score_gpt":0.28577085164880683,"score_spread":0.27746802137446347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139181200","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005665396,0.00027710898,0.9925932,0.00008408794,0.00008505138,0.00002203064,0.000059921018,0.0007090723,0.00050416804],"genre_scores_gemma":[0.048224024,0.00030051154,0.94861853,0.000097366246,0.00006902866,0.000076714125,0.00021652158,0.000056174948,0.002341058],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969256,0.000043381173,0.000020614281,0.000073538984,0.00015261729,0.000017282355],"domain_scores_gemma":[0.999574,0.00015494626,0.00004247431,0.000057074052,0.00015045861,0.000021099706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046656939,0.00057608273,0.000484801,0.0008753856,0.0002811489,0.0003862147,0.0005276534,0.00062102184,0.0021226874],"category_scores_gemma":[0.0011886118,0.00020866115,0.00047928834,0.0007994724,0.00031718114,0.00051129225,0.00034677208,0.00069475255,0.0009581494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002786814,0.00007816376,0.0005008947,0.00020483992,0.000047195834,0.00020879002,0.00006878942,0.020713696,0.2856094,0.010416593,0.0025477298,0.67932534],"study_design_scores_gemma":[0.000055837107,0.00027420788,0.0017540092,0.000030064892,0.000062332925,0.0010134566,0.000018640923,0.79070675,0.1734209,0.004676379,0.02792679,0.00006050301],"about_ca_topic_score_codex":0.00058695977,"about_ca_topic_score_gemma":0.00084301224,"teacher_disagreement_score":0.0021226874,"about_ca_system_score_codex":0.00026187752,"about_ca_system_score_gemma":0.00036892327,"threshold_uncertainty_score":0.0071011186},"labels":[],"label_agreement":null},{"id":"W2144463651","doi":"10.1155/asp.2005.1628","title":"DS-CDMA Receiver Based on a Five-Port Technology","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Rake receiver; Computer science; Pseudorandom noise; Spread spectrum; Code division multiple access; Electronic engineering; Radio receiver design; Symbol rate; Rake; Digital audio broadcasting; Robustness (evolution); Channel (broadcasting); Bit error rate; Fading; Telecommunications; Engineering; Transmitter","score_opus":0.01901435071864167,"score_gpt":0.3247171442835292,"score_spread":0.30570279356488755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144463651","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.067811556,0.0020095957,0.9053261,0.000287321,0.00029650348,0.00019620515,0.00014868322,0.0013667075,0.022557175],"genre_scores_gemma":[0.5440009,0.0016513581,0.43254828,0.00031020053,0.00013668655,0.000116480165,0.00017172626,0.000040910345,0.021023372],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99962294,0.000093460934,0.0000326368,0.00007947775,0.00014078293,0.00003072852],"domain_scores_gemma":[0.9997261,0.00005753933,0.000056380428,0.00005143636,0.00008892349,0.000019591751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033668694,0.000511073,0.00035664663,0.00048255225,0.00021756702,0.00090640766,0.0007455571,0.0007129072,0.0027717352],"category_scores_gemma":[0.000446971,0.0002328224,0.0003147907,0.0003369541,0.00029807095,0.0010816602,0.00037919474,0.0007463198,0.002066933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003795338,0.00015711098,0.0014242764,0.0006206361,0.000080639744,0.0005520092,0.00019382639,0.007089703,0.77060604,0.066053465,0.0020636579,0.15077904],"study_design_scores_gemma":[0.00009416392,0.0017259305,0.001967964,0.00015383711,0.00016963673,0.0034132858,0.00007320323,0.16379483,0.71733296,0.0061575263,0.10499475,0.000121914716],"about_ca_topic_score_codex":0.00019589573,"about_ca_topic_score_gemma":0.0002531407,"teacher_disagreement_score":0.0027717352,"about_ca_system_score_codex":0.00030824813,"about_ca_system_score_gemma":0.0003299608,"threshold_uncertainty_score":0.009272397},"labels":[],"label_agreement":null},{"id":"W2146737350","doi":"10.1155/2010/621064","title":"Drift-Compensated Adaptive Filtering for Improving Speech Intelligibility in Cases with Asynchronous Inputs","year":2010,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute for Microstructural Sciences","funders":"","keywords":"Computer science; Asynchronous communication; Intelligibility (philosophy); Speech recognition; Adaptive filter; Single antenna interference cancellation; Interference (communication); Compensation (psychology); Algorithm; Telecommunications; Decoding methods","score_opus":0.01623680714063486,"score_gpt":0.2815462268140014,"score_spread":0.2653094196733665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146737350","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06277712,0.0007204408,0.9344451,0.000083889405,0.00007818987,0.00003012922,0.000024564171,0.00031941195,0.0015212069],"genre_scores_gemma":[0.659902,0.001225065,0.33535293,0.00011034637,0.0001544222,0.00006149559,0.00010861188,0.000061897874,0.0030233464],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972135,0.00006534714,0.000028715927,0.00004928241,0.000109670735,0.000025653571],"domain_scores_gemma":[0.99951255,0.00025998862,0.000050359777,0.00004630502,0.00011139726,0.000019365936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053240254,0.00053047005,0.0003549067,0.0004231651,0.0002927425,0.00038333418,0.00040046882,0.00059118046,0.000990575],"category_scores_gemma":[0.0019912014,0.00015170749,0.00024057474,0.00035622326,0.00026955237,0.00060388376,0.00030045502,0.00041735717,0.00040759955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073605706,0.000120826386,0.001445258,0.0002614309,0.000046931375,0.00048758925,0.00021398238,0.06295512,0.40488395,0.010237251,0.0010841776,0.5175274],"study_design_scores_gemma":[0.00006500579,0.00038667445,0.0029897944,0.00004326637,0.00007759752,0.0006777846,0.0000581894,0.82350296,0.16069603,0.0052907104,0.0061614546,0.000050490446],"about_ca_topic_score_codex":0.0005658603,"about_ca_topic_score_gemma":0.0008609187,"teacher_disagreement_score":0.000990575,"about_ca_system_score_codex":0.00018052185,"about_ca_system_score_gemma":0.0003227585,"threshold_uncertainty_score":0.0033137798},"labels":[],"label_agreement":null},{"id":"W2147393459","doi":"10.1155/asp.2005.1834","title":"Optimized Multichannel Filter Bank with Flat Frequency Response for Texture Segmentation","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Filter bank; Artificial intelligence; Gabor filter; Computer science; Filter (signal processing); Segmentation; Pattern recognition (psychology); Computer vision; Feature (linguistics); Frequency domain; Image texture; Feature extraction; Scale-space segmentation; Image segmentation","score_opus":0.018198482464285015,"score_gpt":0.3050850072436164,"score_spread":0.2868865247793314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147393459","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031917755,0.0003683675,0.9655848,0.000061431274,0.00004631181,0.00003325338,0.000050505063,0.0006368484,0.0013007366],"genre_scores_gemma":[0.20750372,0.00025978385,0.789604,0.00008289384,0.000030102492,0.000079382145,0.00012923095,0.00010258646,0.002208266],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996555,0.000056780747,0.000020854315,0.000093794886,0.00012202948,0.000051034414],"domain_scores_gemma":[0.99958664,0.00016187316,0.000040987125,0.00006224866,0.0001278966,0.000020440304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000673764,0.00057037553,0.0006901339,0.00069868704,0.00030153748,0.00058204506,0.00061417394,0.0008273551,0.0016598176],"category_scores_gemma":[0.0009584858,0.00031926905,0.0005505935,0.00059797225,0.00036918098,0.0007073312,0.00021947866,0.0004618457,0.0005525469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007732141,0.00019854723,0.0013490027,0.00023247747,0.00015275003,0.00016301441,0.00011628924,0.12339326,0.36147252,0.006070943,0.0026565413,0.50342137],"study_design_scores_gemma":[0.00002366334,0.00011760102,0.0020001803,0.000010705953,0.00006022573,0.00017396438,0.0000196654,0.8752312,0.117676616,0.0012757384,0.0033800588,0.000030436477],"about_ca_topic_score_codex":0.002585755,"about_ca_topic_score_gemma":0.005945836,"teacher_disagreement_score":0.002585755,"about_ca_system_score_codex":0.00084238383,"about_ca_system_score_gemma":0.0005357113,"threshold_uncertainty_score":0.00611192},"labels":[],"label_agreement":null},{"id":"W2147720374","doi":"10.1186/1687-6180-2012-82","title":"Using learned under-sampling pattern for increasing speed of cardiac cine MRI based on compressive sensing principles","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institutes of Health","keywords":"Compressed sensing; k-space; Computer science; Thresholding; Cardiac cycle; Artificial intelligence; Sampling (signal processing); Algorithm; Fuzzy logic; Markov chain; Pattern recognition (psychology); Fourier transform; Computer vision; Mathematics; Image (mathematics)","score_opus":0.0856835156420304,"score_gpt":0.33958764019480486,"score_spread":0.25390412455277445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147720374","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03732206,0.00027573228,0.96054316,0.00018878216,0.00005297635,0.0000397066,0.000046866637,0.00038813276,0.0011426649],"genre_scores_gemma":[0.48916423,0.00053409865,0.5080806,0.00018903558,0.000104494815,0.000111865964,0.00025041102,0.000115002855,0.0014502461],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948275,0.00012736444,0.000031635715,0.00009700388,0.00021698902,0.000044229993],"domain_scores_gemma":[0.99849,0.0007460701,0.00016459895,0.00023461167,0.00029813522,0.00006648947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007456995,0.0005122425,0.0005329037,0.00055297837,0.0002750889,0.0004674038,0.0005805032,0.0005927427,0.0013892971],"category_scores_gemma":[0.0045673517,0.00027756163,0.00027774615,0.00048668665,0.00044842265,0.0010224564,0.00073429046,0.00075739506,0.00038056218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000824481,0.00027743535,0.0038931167,0.0003084551,0.000075420605,0.00039692182,0.00043831076,0.25900635,0.16305618,0.022690939,0.0036261547,0.5454063],"study_design_scores_gemma":[0.000017225899,0.00010924357,0.00059551955,0.00001621141,0.00001195749,0.0001565639,0.00002155927,0.9787127,0.01591552,0.0031046518,0.0013238469,0.000015007868],"about_ca_topic_score_codex":0.0011724862,"about_ca_topic_score_gemma":0.0016568706,"teacher_disagreement_score":0.0013892971,"about_ca_system_score_codex":0.00023236581,"about_ca_system_score_gemma":0.0005481983,"threshold_uncertainty_score":0.004647672},"labels":[],"label_agreement":null},{"id":"W2148681587","doi":"10.1155/2009/928974","title":"A Joint Time-Frequency and Matrix Decomposition Feature Extraction Methodology for Pathological Voice Classification","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Non-negative matrix factorization; Speech recognition; Matrix decomposition; SIGNAL (programming language); Feature extraction; Pattern recognition (psychology); Artificial intelligence; Joint (building); Feature (linguistics); Abnormality","score_opus":0.054922779208024054,"score_gpt":0.38576813271843713,"score_spread":0.33084535351041305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148681587","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005055031,0.00014849578,0.9941415,0.000047341084,0.000034419634,0.00003763093,0.00006024231,0.00028314942,0.0001922329],"genre_scores_gemma":[0.09078131,0.00026792847,0.9072065,0.000043492877,0.000058326368,0.00013612313,0.0003252799,0.00004155914,0.0011394776],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993623,0.00012123135,0.00006354622,0.00014511154,0.00026367602,0.000044199827],"domain_scores_gemma":[0.9992925,0.0001891952,0.00009445944,0.000078470664,0.00031644525,0.000028990737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086997973,0.000624201,0.0006128171,0.0017563376,0.0003487831,0.00051128253,0.00044028298,0.00057773315,0.001205589],"category_scores_gemma":[0.0019114601,0.00017504267,0.0008536547,0.0011721741,0.0003386393,0.0006937565,0.0004056577,0.0005830681,0.0007245875],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013339071,0.000109223496,0.0018815296,0.00013777943,0.000062094645,0.00012471716,0.00008402231,0.008103514,0.10867607,0.00280608,0.002531351,0.8753503],"study_design_scores_gemma":[0.000050011407,0.000553641,0.015481565,0.00004631673,0.00012743073,0.0017318741,0.00011859243,0.894483,0.06539653,0.006205493,0.015685478,0.00012013508],"about_ca_topic_score_codex":0.0014608365,"about_ca_topic_score_gemma":0.0017540992,"teacher_disagreement_score":0.0017563376,"about_ca_system_score_codex":0.00024778533,"about_ca_system_score_gemma":0.00052544987,"threshold_uncertainty_score":0.004600942},"labels":[],"label_agreement":null},{"id":"W2148913652","doi":"10.1155/asp.2005.1910","title":"Design of Nonrecursive Digital Filters Using the Ultraspherical Window Function","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Chebyshev filter; Passband; Computer science; Window function; Prototype filter; Computation; Ripple; Elliptic filter; Low-pass filter; Algorithm; Window (computing); Digital filter; Mathematics; Stopband; Filter (signal processing); Band-pass filter; Electronic engineering; Mathematical analysis; Physics","score_opus":0.036145773634130865,"score_gpt":0.304048980228436,"score_spread":0.26790320659430517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148913652","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004817559,0.0000722486,0.99451715,0.000013799424,0.000011751931,0.0000186606,0.000007896076,0.00013215741,0.00040868606],"genre_scores_gemma":[0.099205025,0.00031208587,0.89805514,0.00004099536,0.00002732328,0.0001347739,0.000054311684,0.000068456204,0.002101976],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99978846,0.000037381167,0.000019177945,0.000041265976,0.00009421153,0.000019529358],"domain_scores_gemma":[0.9997136,0.00010313808,0.00004964066,0.000035675672,0.00008535668,0.000012529717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046141975,0.0006161994,0.00040086245,0.0003527921,0.00023331775,0.0006543619,0.00076425413,0.0004441013,0.0016926102],"category_scores_gemma":[0.00083075406,0.00030274183,0.00038579688,0.0003131689,0.00028838968,0.0006623318,0.0002677589,0.00048402415,0.00066248776],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034053306,0.0001129934,0.0005847308,0.00029026374,0.00011083043,0.00026414302,0.0001921597,0.06832048,0.38995913,0.07396463,0.0015895155,0.4642706],"study_design_scores_gemma":[0.00008171351,0.00036376092,0.00064118527,0.000029101579,0.00006276195,0.00042164623,0.00003767648,0.7781069,0.19253045,0.010635855,0.017050274,0.000038749873],"about_ca_topic_score_codex":0.00046143166,"about_ca_topic_score_gemma":0.00085924694,"teacher_disagreement_score":0.0016926102,"about_ca_system_score_codex":0.00037829767,"about_ca_system_score_gemma":0.0005060083,"threshold_uncertainty_score":0.0056623816},"labels":[],"label_agreement":null},{"id":"W2153853271","doi":"10.1186/1687-6180-2012-40","title":"Nonlinear filtering based on 3D wavelet transform for MRI denoising","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Noise reduction; Artificial intelligence; Computer science; Pattern recognition (psychology); Thresholding; Noise (video); Wavelet; Wavelet transform; Peak signal-to-noise ratio; Rician fading; Mathematics; Image (mathematics); Algorithm","score_opus":0.02654141483167622,"score_gpt":0.3282085510992462,"score_spread":0.30166713626756997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153853271","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007732841,0.00037849334,0.99101514,0.000062049374,0.00003259007,0.000014700567,0.000016491542,0.00010518519,0.0006424454],"genre_scores_gemma":[0.13419685,0.0019872824,0.860949,0.00009834369,0.000071070186,0.000089581044,0.0001532695,0.00008764204,0.0023670022],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965024,0.000068867164,0.00002242961,0.000042514508,0.00020071796,0.000015306669],"domain_scores_gemma":[0.9997483,0.00009822398,0.000029453064,0.00003344954,0.00008279505,0.000007760178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006898587,0.0004631496,0.00047391962,0.0005907425,0.00017727155,0.00042564675,0.00034041508,0.0006927975,0.00089214236],"category_scores_gemma":[0.0011981843,0.0002061886,0.000933779,0.0008448891,0.0003115988,0.0005569864,0.000389845,0.0006279342,0.00049027335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018846257,0.00009253493,0.0011041177,0.0002985457,0.00011744459,0.00027141083,0.0001899552,0.19885089,0.27327967,0.02668023,0.0018027511,0.49712396],"study_design_scores_gemma":[0.000008305983,0.000057941852,0.00068025413,0.000015082507,0.000024924806,0.0001779259,0.000012401894,0.9619333,0.02861423,0.0037934454,0.0046579856,0.000024135314],"about_ca_topic_score_codex":0.001302235,"about_ca_topic_score_gemma":0.0015746984,"teacher_disagreement_score":0.001302235,"about_ca_system_score_codex":0.00029836353,"about_ca_system_score_gemma":0.00039708932,"threshold_uncertainty_score":0.0036484003},"labels":[],"label_agreement":null},{"id":"W2154561622","doi":"10.1186/1687-6180-2014-107","title":"GPS-R L1 interference signal processing for soil moisture estimation: an experimental study","year":2014,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; Australian Research Council; Alzheimer Society Research Program","keywords":"Global Positioning System; GPS signals; Remote sensing; Interference (communication); Multipath propagation; Computer science; Water content; Environmental science; SIGNAL (programming language); Multipath interference; Reflectometry; Assisted GPS; Geology; Telecommunications","score_opus":0.0176297200080127,"score_gpt":0.3086061812877076,"score_spread":0.2909764612796949,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154561622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881714,0.000064914406,0.010764209,0.0000320848,0.000022738752,0.00007944087,0.0001814316,0.000078773206,0.0006049352],"genre_scores_gemma":[0.9846807,0.00015872117,0.013832717,0.000030170198,0.000018267328,0.00009741316,0.00023927247,0.000022875814,0.0009198417],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994968,0.00013928396,0.000039805942,0.00010090395,0.00015276839,0.00007049278],"domain_scores_gemma":[0.99867946,0.00056696776,0.00013588282,0.00020488755,0.0003364728,0.00007640843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086340297,0.0004105179,0.00036213183,0.00045040314,0.000310625,0.00030413418,0.0004662857,0.00065019564,0.0016061463],"category_scores_gemma":[0.0014599278,0.00017174947,0.00024124821,0.0005046687,0.00046859242,0.00053881924,0.00038654215,0.0003575275,0.00040187812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027226284,0.0035577035,0.010415002,0.00041095936,0.000072023504,0.00035896132,0.00046626455,0.009456046,0.91478735,0.000506531,0.0005077016,0.056738865],"study_design_scores_gemma":[0.0004580621,0.035281226,0.05230762,0.00004647941,0.00015971319,0.0005729857,0.0008751381,0.08554038,0.821012,0.00037867457,0.003271062,0.000096713375],"about_ca_topic_score_codex":0.0012350843,"about_ca_topic_score_gemma":0.0011701297,"teacher_disagreement_score":0.0016061463,"about_ca_system_score_codex":0.00017448426,"about_ca_system_score_gemma":0.0002023923,"threshold_uncertainty_score":0.0053730607},"labels":[],"label_agreement":null},{"id":"W2154781685","doi":"10.1155/s1110865704402029","title":"Fast Watermarking of MPEG-1/2 Streams Using Compressed-Domain Perceptual Embedding and a Generalized Correlator Detector","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Digital watermarking; Computer science; Watermark; Detector; Preprocessor; MPEG-2; Computer vision; Artificial intelligence; Embedding; Real-time computing; Image (mathematics); Telecommunications","score_opus":0.015739782811673843,"score_gpt":0.28981028603289655,"score_spread":0.2740705032212227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154781685","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07233174,0.0012546175,0.9236258,0.00015260126,0.00015604663,0.00014674553,0.000049459337,0.0007349529,0.0015479949],"genre_scores_gemma":[0.313571,0.0010626825,0.68171406,0.00013381647,0.00013472897,0.0001051482,0.00014092139,0.00004830407,0.0030893784],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99976665,0.00004214562,0.000010625841,0.000038192647,0.00012349083,0.000018930781],"domain_scores_gemma":[0.9995952,0.00012755906,0.000088273024,0.000056818495,0.00011159352,0.000020520189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040251767,0.0005300152,0.00041769847,0.00064118294,0.0001771065,0.00032441513,0.000439696,0.00061940134,0.00055562315],"category_scores_gemma":[0.0007357916,0.00020197936,0.0002605295,0.0005756038,0.0004153518,0.00068503094,0.0003626433,0.00053668086,0.00031638413],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003022362,0.00011544785,0.0006462961,0.00019301764,0.000046523863,0.00032267164,0.00005707424,0.00639108,0.7347893,0.0070779826,0.00082755997,0.24923083],"study_design_scores_gemma":[0.00010265179,0.0012463764,0.0026963665,0.000047673457,0.00011713123,0.002683643,0.000027509255,0.32193172,0.6586805,0.0017632758,0.0106231645,0.00007994385],"about_ca_topic_score_codex":0.00027630277,"about_ca_topic_score_gemma":0.00075820205,"teacher_disagreement_score":0.00064118294,"about_ca_system_score_codex":0.00024720907,"about_ca_system_score_gemma":0.0004958639,"threshold_uncertainty_score":0.00212878},"labels":[],"label_agreement":null},{"id":"W2160354731","doi":"10.1155/s1110865704405010","title":"A Neural Network MLSE Receiver Based on Natural Gradient Descent: Application to Satellite Communications","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Viterbi algorithm; Channel (broadcasting); Multipath propagation; Maximum likelihood sequence estimation; Gradient descent; Estimator; Algorithm; Electronic engineering; Telecommunications; Artificial neural network; Estimation theory; Artificial intelligence; Engineering; Mathematics; Statistics; Decoding methods","score_opus":0.01725542566618462,"score_gpt":0.30892354478653156,"score_spread":0.29166811912034696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160354731","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012925793,0.00032064584,0.9848546,0.00017894467,0.000030745312,0.000016214715,0.000011796233,0.00043712175,0.0012242337],"genre_scores_gemma":[0.35988435,0.0005414319,0.63339394,0.00016587632,0.00010723383,0.00005615755,0.000059445745,0.000074552925,0.0057169404],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997563,0.00008945019,0.000009741591,0.000037208607,0.00009010449,0.000017133],"domain_scores_gemma":[0.9996686,0.00016555155,0.000028027664,0.000028664204,0.000095242496,0.000013948013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005766384,0.00034563753,0.0005068842,0.00019096732,0.00020785574,0.00035453268,0.00043099176,0.001060166,0.0008224377],"category_scores_gemma":[0.001241523,0.00020621592,0.00021065075,0.00032754056,0.00034361435,0.00057149376,0.0004481934,0.0006060792,0.00038892514],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028986923,0.00009377161,0.002151098,0.00020446445,0.00011737369,0.0004342229,0.00020920223,0.49926805,0.077160195,0.020647509,0.0023530887,0.39707118],"study_design_scores_gemma":[0.000014543812,0.000063329506,0.0002106975,0.000006564656,0.000010540542,0.00013938636,0.0000060229986,0.9878906,0.008863833,0.0014216223,0.001360654,0.000012156469],"about_ca_topic_score_codex":0.0012753827,"about_ca_topic_score_gemma":0.0016594614,"teacher_disagreement_score":0.0012753827,"about_ca_system_score_codex":0.00023545978,"about_ca_system_score_gemma":0.000325371,"threshold_uncertainty_score":0.003049612},"labels":[],"label_agreement":null},{"id":"W2163473895","doi":"10.1155/asp.2005.306","title":"Performance and Capacity of PAM and PPM UWB Time-Hopping Multiple Access Communications with Receive Diversity","year":2005,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Ultra-Wideband Communications Technology","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Pulse-position modulation; Additive white Gaussian noise; Computer science; Time-hopping; Diversity combining; Telecommunications; Pulse-amplitude modulation; Diversity gain; Probability of error; Time diversity; Modulation (music); Electronic engineering; Channel capacity; Fading; SIGNAL (programming language); Channel (broadcasting); Algorithm; Pulse (music); Physics; Engineering; Acoustics","score_opus":0.021005134282054628,"score_gpt":0.25316477546269756,"score_spread":0.23215964118064292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163473895","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7886449,0.0028236853,0.19227819,0.00075808837,0.0000780417,0.00004694617,0.0003682769,0.00042615156,0.014575574],"genre_scores_gemma":[0.9956079,0.00029777063,0.003239244,0.000030194007,0.000027812654,0.000031948395,0.00006855533,0.000018716906,0.00067794096],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973013,0.0009380941,0.000092545684,0.0002205173,0.0009043209,0.0005432625],"domain_scores_gemma":[0.9718441,0.022849193,0.001488185,0.0011331296,0.0024106898,0.00027484613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030138332,0.00084216596,0.0010085726,0.000855057,0.0006816062,0.0011108048,0.0009131713,0.0015635875,0.0014048102],"category_scores_gemma":[0.017567622,0.000335755,0.00039373018,0.00091734756,0.0017769227,0.0016044887,0.001785422,0.0007355325,0.0002460029],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081035355,0.00006791273,0.0033614913,0.00022210104,0.000089803194,0.0004578775,0.0002806006,0.92508984,0.015292831,0.030648058,0.0005600426,0.02311904],"study_design_scores_gemma":[0.000028206689,0.00022363466,0.0019316139,0.000038238697,0.000045530778,0.000432959,0.00009896311,0.97097707,0.014158552,0.011596097,0.0004028481,0.000066287845],"about_ca_topic_score_codex":0.0017307592,"about_ca_topic_score_gemma":0.00084419665,"teacher_disagreement_score":0.0030138332,"about_ca_system_score_codex":0.0011432165,"about_ca_system_score_gemma":0.0008968013,"threshold_uncertainty_score":0.015938878},"labels":[],"label_agreement":null},{"id":"W2163954795","doi":"10.1186/1687-6180-2014-155","title":"Approximate computing for complexity reduction in timing synchronization","year":2014,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advancements in PLL and VCO Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Aalto-Yliopisto; Academy of Finland","keywords":"Computer science; Reduction (mathematics); Computational complexity theory; Synchronization (alternating current); Code division multiple access; Code (set theory); Power consumption; Algorithm; Computer engineering; Power (physics); Real-time computing; Mathematics; Telecommunications; Channel (broadcasting)","score_opus":0.030866830148597934,"score_gpt":0.30367175381785233,"score_spread":0.2728049236692544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163954795","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067415102,0.0002052248,0.99153495,0.000048064645,0.000025634401,0.0000174147,0.000010172864,0.00031953942,0.0010974389],"genre_scores_gemma":[0.3614143,0.0003897123,0.6362347,0.000080299746,0.000101289654,0.00009155603,0.00008233228,0.00014306244,0.0014627632],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861526,0.00029161177,0.000071563125,0.00015280682,0.00077366794,0.00009510186],"domain_scores_gemma":[0.99827933,0.00093024917,0.00015953535,0.0003102132,0.00027977413,0.00004089645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075723993,0.0006618261,0.00069841905,0.00074351864,0.00045733096,0.0011579087,0.00091066235,0.00047495682,0.002129976],"category_scores_gemma":[0.0050412845,0.00027630618,0.00042156805,0.0008556687,0.0005571603,0.0014263021,0.00074082566,0.0009803304,0.0005941636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006056502,0.000094191695,0.0008581934,0.00024832896,0.00007531463,0.0001405779,0.00021257439,0.3794212,0.06521442,0.10428556,0.0019980976,0.44684583],"study_design_scores_gemma":[0.000022269833,0.00014321275,0.00017103176,0.000014555121,0.000018942243,0.00010523463,0.000012721429,0.9701552,0.01740098,0.008211126,0.0037304417,0.000014260945],"about_ca_topic_score_codex":0.0012252675,"about_ca_topic_score_gemma":0.0014390855,"teacher_disagreement_score":0.002129976,"about_ca_system_score_codex":0.00071984367,"about_ca_system_score_gemma":0.0009272423,"threshold_uncertainty_score":0.0071254373},"labels":[],"label_agreement":null},{"id":"W2164315346","doi":"10.1186/1687-6180-2012-142","title":"Real-time target detection in hyperspectral images based on spatial-spectral information extraction","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Hyperspectral imaging; Computer science; Digital signal processing; Software; Image processing; Artificial intelligence; Covariance matrix; Pixel; Computer vision; Pattern recognition (psychology); Computer hardware; Algorithm; Image (mathematics)","score_opus":0.008420047041147433,"score_gpt":0.2565784559468113,"score_spread":0.24815840890566385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164315346","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04927032,0.00011518825,0.94899243,0.00006361524,0.000015738924,0.000026776133,0.000033399607,0.0005098053,0.0009727559],"genre_scores_gemma":[0.32308257,0.00018814087,0.6750013,0.00005972929,0.000017401851,0.000049687947,0.00013502335,0.00005848326,0.0014076184],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997383,0.000042607797,0.00001684566,0.000049908427,0.00013096731,0.000021435972],"domain_scores_gemma":[0.9997414,0.000096597454,0.000033518383,0.000029988114,0.00008865413,0.000009822907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034816333,0.00037849462,0.00033999167,0.0005965249,0.00017428823,0.0003472349,0.00039015748,0.0002567718,0.0009122256],"category_scores_gemma":[0.00081819395,0.00019937636,0.00029633375,0.0005988893,0.00025915157,0.0007900734,0.0004621148,0.00028441107,0.00035243796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024975347,0.00013818685,0.0018675289,0.00015581757,0.000043758606,0.00011243784,0.000114211645,0.039255336,0.41392797,0.0047282786,0.0009277698,0.5384789],"study_design_scores_gemma":[0.00001686206,0.00008996851,0.0031474307,0.000008057164,0.00002338751,0.00022579869,0.000032418237,0.7815908,0.21077065,0.0019686944,0.0021009224,0.0000249111],"about_ca_topic_score_codex":0.00041465572,"about_ca_topic_score_gemma":0.00065525185,"teacher_disagreement_score":0.0009122256,"about_ca_system_score_codex":0.00016021152,"about_ca_system_score_gemma":0.00023283597,"threshold_uncertainty_score":0.0030516982},"labels":[],"label_agreement":null},{"id":"W2164497124","doi":"10.1186/1687-6180-2012-188","title":"Direct path detection using multipath interference cancelation for communication-based positioning system","year":2012,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Electronics and Telecommunications Research Institute","keywords":"Multipath propagation; Computer science; Multipath interference; Preamble; Delay spread; Interference (communication); Estimator; Algorithm; SIGNAL (programming language); Real-time computing; Electronic engineering; Channel (broadcasting); Telecommunications; Mathematics; Statistics; Engineering","score_opus":0.017499838336846298,"score_gpt":0.27455283485963233,"score_spread":0.257052996522786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164497124","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0266967,0.0007775938,0.96977824,0.00009740993,0.00007483101,0.000038917195,0.000040370498,0.0006765834,0.0018193409],"genre_scores_gemma":[0.6043084,0.00073682127,0.3914434,0.00010342278,0.000091512935,0.00008292164,0.00013803894,0.000028070455,0.0030674373],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930155,0.00015120042,0.000026318103,0.00010263705,0.00037242172,0.000045919904],"domain_scores_gemma":[0.9995499,0.00012559073,0.000063994,0.00005089382,0.00019673433,0.000012803194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032994003,0.0006323342,0.00049939053,0.00047062672,0.00025751613,0.00045140076,0.00063311425,0.00050071016,0.0010166091],"category_scores_gemma":[0.0011532612,0.00018685647,0.00030062124,0.0005736806,0.00024941415,0.00041458695,0.0006400799,0.00038676994,0.0004686871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004357582,0.00010239205,0.0034519276,0.00039160627,0.00018120688,0.00044070563,0.00017976812,0.13205418,0.21221049,0.009175022,0.0029050813,0.6384719],"study_design_scores_gemma":[0.000044312885,0.0004378266,0.0018554407,0.000034256456,0.00009370344,0.00071903015,0.000028426153,0.9071802,0.08237231,0.0016102825,0.0055631856,0.00006116561],"about_ca_topic_score_codex":0.0011981786,"about_ca_topic_score_gemma":0.0018155791,"teacher_disagreement_score":0.0011981786,"about_ca_system_score_codex":0.00037619687,"about_ca_system_score_gemma":0.00066704396,"threshold_uncertainty_score":0.0034009218},"labels":[],"label_agreement":null},{"id":"W2164811834","doi":"10.1155/s1110865704312229","title":"Signal Reception for Space-Time Differentially Encoded Transmissions over FIR Rich Multipath Channels","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Multipath propagation; Computer science; Intersymbol interference; Fading; MIMO; Electronic engineering; Antenna diversity; Algorithm; Channel (broadcasting); Telecommunications; Antenna (radio); Engineering","score_opus":0.014643292333704552,"score_gpt":0.2883595733958502,"score_spread":0.2737162810621457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164811834","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026478747,0.00011497006,0.97206974,0.00005084227,0.000022870492,0.000009200599,0.000014521198,0.00012734828,0.001111788],"genre_scores_gemma":[0.5998338,0.0002238314,0.39681467,0.000070446185,0.00003466992,0.000027143786,0.00006282116,0.000023534265,0.0029091595],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997168,0.00008104936,0.000013902734,0.00003559813,0.0001284928,0.000024155239],"domain_scores_gemma":[0.99940586,0.00030473422,0.00008553246,0.00009336875,0.000090325295,0.000020213738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051450543,0.00032680042,0.0003022046,0.00017388602,0.0001903966,0.00043715167,0.00038662966,0.00047106275,0.0009358538],"category_scores_gemma":[0.0013618883,0.00012020329,0.00024254693,0.00017212686,0.00034098673,0.00043788174,0.00045706227,0.00039227412,0.00042341143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055937626,0.00009031061,0.0035562357,0.00033985495,0.00009058413,0.00037869165,0.00033170753,0.3652838,0.1903492,0.101607405,0.0012643525,0.3361485],"study_design_scores_gemma":[0.000023616274,0.00019199998,0.00047488557,0.000016027081,0.00001899763,0.000401059,0.00002794882,0.940692,0.048374057,0.00723253,0.0025272183,0.000019652003],"about_ca_topic_score_codex":0.00018489665,"about_ca_topic_score_gemma":0.00046794498,"teacher_disagreement_score":0.0009358538,"about_ca_system_score_codex":0.00029403734,"about_ca_system_score_gemma":0.00030762397,"threshold_uncertainty_score":0.003130734},"labels":[],"label_agreement":null},{"id":"W2168330445","doi":"10.1155/s1110865704311157","title":"Adaptive Zero-Padding OFDM over Frequency-Selective Multipath Channels","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Orthogonal frequency-division multiplexing; Guard interval; Cyclic prefix; Computer science; Padding; Delay spread; Channel (broadcasting); Frequency-division multiplexing; Electronic engineering; Multipath propagation; Algorithm; Telecommunications; Engineering","score_opus":0.016744554445891662,"score_gpt":0.2878865999519468,"score_spread":0.27114204550605514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168330445","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12406242,0.0007055215,0.8731397,0.00010968827,0.000051013336,0.000020982065,0.000032064017,0.00021199785,0.0016667235],"genre_scores_gemma":[0.8167688,0.00050623453,0.1816288,0.000047004454,0.00006225832,0.000022575687,0.000030036754,0.00001188325,0.0009224401],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998683,0.00003478281,0.000006405074,0.000023126175,0.000043765063,0.000023676264],"domain_scores_gemma":[0.99972075,0.00013761308,0.00004674197,0.00003993297,0.000042337208,0.000012629862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021241978,0.0003488586,0.00027745633,0.00020221868,0.00025306104,0.00026672494,0.00050843606,0.00029096752,0.00034504212],"category_scores_gemma":[0.00054026436,0.00014328187,0.00018831347,0.00030881466,0.00036256103,0.0005138117,0.00036438977,0.0003733576,0.00012050603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005051838,0.000091636066,0.002099002,0.00032437837,0.00007506543,0.00075847376,0.00017005378,0.22850306,0.3637274,0.048817813,0.0012270713,0.35370085],"study_design_scores_gemma":[0.000042365828,0.00035731666,0.00064190774,0.000013420752,0.000052313517,0.0007542524,0.000022475615,0.92375904,0.06438162,0.0067791957,0.003162871,0.000033110286],"about_ca_topic_score_codex":0.00027640947,"about_ca_topic_score_gemma":0.00043804644,"teacher_disagreement_score":0.00050843606,"about_ca_system_score_codex":0.00014991457,"about_ca_system_score_gemma":0.00024350572,"threshold_uncertainty_score":0.0011543036},"labels":[],"label_agreement":null},{"id":"W2171894261","doi":"10.1155/s1110865703305037","title":"A Multidelay Double-Talk Detector Combined with the MDF Adaptive Filter","year":2003,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Institut National de la Recherche Scientifique","funders":"","keywords":"Algorithm; Block (permutation group theory); Adaptive filter; Computational complexity theory; Computer science; Detector; Filter (signal processing); Frequency domain; Least mean squares filter; Mathematics; Computer vision; Telecommunications","score_opus":0.018229692649088684,"score_gpt":0.25987017704060245,"score_spread":0.24164048439151375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171894261","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00859343,0.00021509301,0.9896163,0.00014051204,0.00009511573,0.000034986886,0.000043859785,0.00043862822,0.00082202215],"genre_scores_gemma":[0.10767457,0.0001605963,0.8882414,0.00019987753,0.000075793796,0.00007892146,0.000097769735,0.000033592645,0.0034374767],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994056,0.00009360652,0.00002903223,0.00012042938,0.00029978604,0.00005151548],"domain_scores_gemma":[0.9992594,0.00030124668,0.000059260805,0.00008133634,0.00024671244,0.00005211292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080683484,0.0005182677,0.0007400672,0.0009631076,0.0003432133,0.0005381146,0.0009087697,0.0013324845,0.001814374],"category_scores_gemma":[0.0018912372,0.00038824056,0.00043817505,0.0005954243,0.00032559998,0.0009624266,0.00050021714,0.0006660199,0.0007343787],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087567477,0.00014645247,0.0019468154,0.00016258885,0.00014851538,0.00024690968,0.00008466632,0.03528261,0.30701792,0.014567872,0.0033784462,0.63614154],"study_design_scores_gemma":[0.000104277475,0.00031854512,0.0015415951,0.00002017865,0.00008195104,0.0012763733,0.000016875094,0.773991,0.20212722,0.0028310625,0.017600024,0.000090951384],"about_ca_topic_score_codex":0.0013661041,"about_ca_topic_score_gemma":0.0028760293,"teacher_disagreement_score":0.001814374,"about_ca_system_score_codex":0.0006078323,"about_ca_system_score_gemma":0.00095132354,"threshold_uncertainty_score":0.00606966},"labels":[],"label_agreement":null},{"id":"W2172288663","doi":"10.1155/2007/36871","title":"Mobile Agent-Based Directed Diffusion in Wireless Sensor Networks","year":2006,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":149,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Korea Science and Engineering Foundation","keywords":"Computer science; Computer network; Wireless sensor network; Mobile agent; Network packet; Latency (audio); Energy consumption; Redundancy (engineering); Wireless; Distributed computing; Real-time computing; Telecommunications; Operating system","score_opus":0.007401170963270073,"score_gpt":0.24608428007335528,"score_spread":0.23868310911008522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172288663","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01678996,0.004064232,0.97463757,0.0006013217,0.00017098324,0.000078210935,0.000054063392,0.00030740697,0.003296326],"genre_scores_gemma":[0.8230778,0.007260144,0.16160287,0.00024692528,0.00021352655,0.00034287578,0.00013880928,0.00006702336,0.0070500164],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994709,0.00021033976,0.000033291377,0.000097222604,0.000157666,0.00003064799],"domain_scores_gemma":[0.99911445,0.00054608006,0.0001333812,0.000045407938,0.0001234842,0.000037142046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010095369,0.00073345687,0.00096152886,0.0007197699,0.00049749296,0.00094443053,0.0011432149,0.001534766,0.0005548241],"category_scores_gemma":[0.0028089776,0.00048490733,0.00046177706,0.0010109373,0.0010093128,0.0012425287,0.000792805,0.00092345855,0.00020847144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005631926,0.000030955085,0.00095800875,0.00021963855,0.00008309948,0.0002530798,0.00018141372,0.89427793,0.003759049,0.06407034,0.0012897135,0.034820408],"study_design_scores_gemma":[0.000017673301,0.00002986236,0.00012705047,0.000009917124,0.000010599042,0.00004336925,0.000016695494,0.98008543,0.000402571,0.016449183,0.0027932522,0.000014402439],"about_ca_topic_score_codex":0.0050661545,"about_ca_topic_score_gemma":0.00297306,"teacher_disagreement_score":0.0050661545,"about_ca_system_score_codex":0.0009864264,"about_ca_system_score_gemma":0.00056234584,"threshold_uncertainty_score":0.010073364},"labels":[],"label_agreement":null},{"id":"W2172503700","doi":"10.1186/s13634-015-0273-3","title":"Systematic network coding for two-hop lossy transmissions","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Queen's University","keywords":"Computer science; Linear network coding; Lossy compression; Decoding methods; Network packet; Computer network; Coding (social sciences); Encoding (memory); Hop (telecommunications); Algorithm; Mathematics","score_opus":0.061365036794802576,"score_gpt":0.3522335494749885,"score_spread":0.29086851268018593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172503700","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02298201,0.00033810825,0.97290534,0.00016825562,0.000046416455,0.000064175954,0.00006150883,0.00009606786,0.0033381132],"genre_scores_gemma":[0.8463493,0.00078584865,0.14824201,0.0001819291,0.00004909929,0.00034230918,0.00014401496,0.000053274165,0.0038521944],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936205,0.0002481373,0.000021377346,0.00006458546,0.00023283929,0.000071138114],"domain_scores_gemma":[0.9975401,0.0016607537,0.00024168675,0.00022562167,0.00030054775,0.000031324184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000993281,0.0005448338,0.00042781982,0.00044215887,0.0003697835,0.0004948046,0.00072435517,0.00058631087,0.0010929207],"category_scores_gemma":[0.0040087965,0.00025288065,0.00029525592,0.00055162044,0.0011836732,0.0010376396,0.00083424366,0.00078291976,0.00020534632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010364977,0.00002559737,0.0002852078,0.00012958137,0.000025576872,0.00022977797,0.00015386422,0.7896948,0.0067760143,0.17819051,0.0011744247,0.023210926],"study_design_scores_gemma":[0.000011282346,0.000026976992,0.00006119664,0.000013509873,0.0000058827177,0.00006641262,0.000012654224,0.97524124,0.0010349596,0.022708962,0.00080589094,0.000011064528],"about_ca_topic_score_codex":0.0031470114,"about_ca_topic_score_gemma":0.0025674675,"teacher_disagreement_score":0.0031470114,"about_ca_system_score_codex":0.0010110582,"about_ca_system_score_gemma":0.0012503172,"threshold_uncertainty_score":0.007335782},"labels":[],"label_agreement":null},{"id":"W2175351985","doi":"10.1186/s13634-015-0280-4","title":"A low complexity reweighted proportionate affine projection algorithm with memory and row action projection","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Algorithm; Computational complexity theory; Projection (relational algebra); Affine transformation; Action (physics); Computer science; Filter (signal processing); Norm (philosophy); Mathematics; Law; Computer vision; Geometry","score_opus":0.04465242267851142,"score_gpt":0.3010500504852102,"score_spread":0.2563976278066988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2175351985","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026909248,0.0001397552,0.9961591,0.000048489863,0.000034734214,0.000028816716,0.000020433372,0.000238108,0.000639607],"genre_scores_gemma":[0.08657166,0.00036822114,0.90850604,0.00012737002,0.00007998306,0.00019945894,0.000190349,0.00010742614,0.0038493606],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994854,0.00012601969,0.000035511126,0.00012175263,0.0001958751,0.00003540812],"domain_scores_gemma":[0.9993536,0.00021741872,0.000070070564,0.00010296691,0.00021894641,0.000036985777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059832365,0.0009857152,0.00096604205,0.00054097676,0.00040052593,0.0010316485,0.0013025971,0.00084888,0.0028339846],"category_scores_gemma":[0.001864374,0.00052665174,0.0007132867,0.0008605976,0.0005596072,0.0014106266,0.0011684474,0.0015134051,0.0015146716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033067883,0.000121225254,0.0009465315,0.00027641727,0.00015620147,0.00018882759,0.00012460332,0.20363802,0.0371708,0.019736163,0.0046585337,0.73265207],"study_design_scores_gemma":[0.000026642963,0.000114197275,0.0002063067,0.000011633789,0.000019514022,0.00023734954,0.00001764684,0.9851222,0.007256807,0.0030854312,0.0038795054,0.000022799977],"about_ca_topic_score_codex":0.0017061708,"about_ca_topic_score_gemma":0.0018566108,"teacher_disagreement_score":0.0028339846,"about_ca_system_score_codex":0.00025777775,"about_ca_system_score_gemma":0.0011917186,"threshold_uncertainty_score":0.009480655},"labels":[],"label_agreement":null},{"id":"W2178703507","doi":"10.1186/s13634-015-0283-1","title":"An overview on optimized NLMS algorithms for acoustic echo cancellation","year":2015,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii","keywords":"Echo (communications protocol); Computer science; Adaptive filter; Algorithm; Convergence (economics); Least mean squares filter; Filter (signal processing); Identification (biology); Parametric statistics; System identification; Adaptation (eye); Recursive least squares filter; Mathematics; Measure (data warehouse)","score_opus":0.07914966254349948,"score_gpt":0.3696111334799793,"score_spread":0.29046147093647984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2178703507","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00062391814,0.011989566,0.98360115,0.00016049335,0.00012990554,0.000032094962,0.0000725742,0.000287431,0.0031029303],"genre_scores_gemma":[0.032788306,0.034919124,0.9208726,0.00035157456,0.00084990106,0.0002543891,0.0007738961,0.0004444334,0.008745756],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990859,0.00021958946,0.00010762034,0.00015093687,0.00039387814,0.000042090225],"domain_scores_gemma":[0.9992817,0.00034011962,0.00006620942,0.00007931896,0.00021573079,0.00001687869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095297734,0.001491305,0.00091109454,0.0012203611,0.00028011564,0.001207927,0.0013612327,0.001330633,0.0043850048],"category_scores_gemma":[0.002733364,0.0006925816,0.00084724237,0.0021368493,0.0004932226,0.0013119464,0.0009543293,0.0018426813,0.004045742],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016212635,0.00009363781,0.0005186534,0.00154586,0.00015249822,0.00013895282,0.00012342018,0.16111349,0.015819967,0.06410469,0.0123473145,0.74387944],"study_design_scores_gemma":[0.000047683006,0.00024256871,0.0009034896,0.00044468915,0.00008906132,0.00057909417,0.000044898523,0.7074526,0.015006092,0.057858024,0.21720736,0.00012448046],"about_ca_topic_score_codex":0.0015052718,"about_ca_topic_score_gemma":0.0011155928,"teacher_disagreement_score":0.0043850048,"about_ca_system_score_codex":0.0005841102,"about_ca_system_score_gemma":0.000779095,"threshold_uncertainty_score":0.0146692395},"labels":[],"label_agreement":null},{"id":"W2551203424","doi":"10.1186/s13634-016-0415-2","title":"Introducing oriented Laplacian diffusion into a variational decomposition model","year":2016,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Laplace operator; Noise reduction; Noise (video); Weighting; Computer science; Curvature; Anisotropic diffusion; Texture (cosmology); Laplacian smoothing; Norm (philosophy); Artificial intelligence; Mathematics; Algorithm; Applied mathematics; Mathematical analysis; Image (mathematics); Acoustics; Physics; Geometry","score_opus":0.01164033136484952,"score_gpt":0.31356918546869367,"score_spread":0.3019288541038441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2551203424","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0057875086,0.00009622392,0.9925976,0.00011672456,0.000026412714,0.0000132750565,0.000029979634,0.000077022385,0.0012552831],"genre_scores_gemma":[0.4274791,0.0009382858,0.5562122,0.00025412187,0.00012648075,0.00017372123,0.00028850962,0.0002560616,0.0142716095],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975425,0.00007676368,0.000010219542,0.000053051033,0.00008248053,0.000023196511],"domain_scores_gemma":[0.9997123,0.00012525299,0.000038901795,0.0000299859,0.00006918459,0.000024414192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007306071,0.00065619266,0.00049741304,0.00066617195,0.00021114321,0.0007772941,0.00090068695,0.0011229129,0.0015681701],"category_scores_gemma":[0.0013939376,0.00040480704,0.00091739994,0.000601573,0.0006376885,0.00097083993,0.00085276936,0.001008138,0.00039384657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053771684,0.000033554705,0.0006900422,0.00008608308,0.000049875307,0.0001229775,0.00011839405,0.7614454,0.016815959,0.1794965,0.0016996688,0.039387774],"study_design_scores_gemma":[0.0000029770567,0.000009836424,0.000050670547,0.000002488347,0.0000036069723,0.000023391947,0.0000042271895,0.98975384,0.00035200955,0.0090525355,0.00073802634,0.0000063791595],"about_ca_topic_score_codex":0.0052586617,"about_ca_topic_score_gemma":0.0045612874,"teacher_disagreement_score":0.0052586617,"about_ca_system_score_codex":0.0007354834,"about_ca_system_score_gemma":0.0007142782,"threshold_uncertainty_score":0.010456085},"labels":[],"label_agreement":null},{"id":"W2560086602","doi":"10.1186/s13634-016-0431-2","title":"A novel sequential algorithm for clutter and direct signal cancellation in passive bistatic radars","year":2016,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Clutter; Computer science; Algorithm; Bistatic radar; Multipath propagation; Subspace topology; Passive radar; Computational complexity theory; Radar; Artificial intelligence; Telecommunications; Radar imaging","score_opus":0.012601428581831546,"score_gpt":0.26075117268774917,"score_spread":0.2481497441059176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2560086602","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0039419094,0.000095990305,0.9948666,0.000036016518,0.000038233466,0.000031188523,0.000022045915,0.0002966219,0.00067131524],"genre_scores_gemma":[0.0989788,0.00018553082,0.8972782,0.000085888576,0.00008269124,0.00014513069,0.00020021255,0.000080741505,0.0029627772],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946314,0.00007038601,0.000036358302,0.000093959374,0.00029122736,0.000045017114],"domain_scores_gemma":[0.999388,0.00021695935,0.00005005464,0.0000842077,0.0002181461,0.000042605992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005624748,0.0007295023,0.00067301316,0.00065750576,0.00044572522,0.000612004,0.0010877987,0.0005994273,0.002623344],"category_scores_gemma":[0.0016176616,0.0003395275,0.00044947094,0.0006937291,0.00040878402,0.0008528665,0.0008677296,0.0009142195,0.0012430204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005413462,0.00012899404,0.0007230647,0.00018483783,0.000053066073,0.00009739024,0.00010529171,0.104361765,0.103500776,0.016546385,0.003941915,0.7698152],"study_design_scores_gemma":[0.00010224709,0.0002452635,0.00035069612,0.0000107546275,0.000021604697,0.00025718793,0.000018478264,0.9651819,0.022940367,0.0051144003,0.0057295635,0.000027574599],"about_ca_topic_score_codex":0.0027495513,"about_ca_topic_score_gemma":0.0029928032,"teacher_disagreement_score":0.0027495513,"about_ca_system_score_codex":0.00035705164,"about_ca_system_score_gemma":0.0013671734,"threshold_uncertainty_score":0.0087759495},"labels":[],"label_agreement":null},{"id":"W2573133186","doi":"10.1186/s13634-018-0529-9","title":"Superimposed signaling inspired channel estimation in full-duplex systems","year":2018,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Australian Government; National Science Foundation","keywords":"Computer science; Estimator; Channel (broadcasting); Baseband; Communications system; Algorithm; Bit error rate; Modulation (music); Fading; Mean squared error; Bandwidth (computing); Telecommunications; Mathematics; Statistics","score_opus":0.020395680584070538,"score_gpt":0.2817212205739603,"score_spread":0.2613255399898898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2573133186","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043883294,0.0002217557,0.9545768,0.00009096802,0.000024303437,0.000014341423,0.000022343347,0.00014517306,0.0010211042],"genre_scores_gemma":[0.8082602,0.00031432643,0.18960139,0.000086373766,0.00003288408,0.000039696533,0.00006049098,0.000023085198,0.0015816446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958366,0.00015164608,0.000015775457,0.00005027722,0.00016677727,0.000031921743],"domain_scores_gemma":[0.99916434,0.000544738,0.00008811581,0.00008357012,0.00009770057,0.000021556529],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000505704,0.00044095877,0.00043884118,0.00031864477,0.00021020972,0.00047773114,0.0004870774,0.00061156315,0.00054713886],"category_scores_gemma":[0.0022662394,0.00029919844,0.00028761098,0.00043108893,0.00060603296,0.0008917252,0.00065497594,0.00053003774,0.00015482683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026797317,0.000050137227,0.0006836526,0.00013697079,0.000054707307,0.00020773991,0.00020274037,0.79372483,0.06237937,0.031295903,0.00048582457,0.1105102],"study_design_scores_gemma":[0.000006641905,0.000031532352,0.00014828378,0.0000057715556,0.0000062197087,0.00004999657,0.000007710477,0.9884494,0.007560461,0.0034391321,0.0002839823,0.000010841376],"about_ca_topic_score_codex":0.0008703546,"about_ca_topic_score_gemma":0.00091450167,"teacher_disagreement_score":0.0008703546,"about_ca_system_score_codex":0.0003360837,"about_ca_system_score_gemma":0.00056374626,"threshold_uncertainty_score":0.0026744604},"labels":[],"label_agreement":null},{"id":"W2619476407","doi":"10.1155/2010/874592","title":"Scale Mixture of Gaussian Modelling of Polarimetric SAR Data","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Space Agency; Danmarks Tekniske Universitet; European Space Agency","keywords":"Mixture model; Synthetic aperture radar; Computer science; Statistical model; Gaussian; Polarimetry; Scale (ratio); Remote sensing; Cluster analysis; Gaussian network model; Radar imaging; Radar; Pattern recognition (psychology); Artificial intelligence; Data mining; Geology; Geography","score_opus":0.022405717212798208,"score_gpt":0.28144024461754397,"score_spread":0.25903452740474575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2619476407","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005725035,0.00014758407,0.9932112,0.000048465423,0.00002722008,0.000019567728,0.000104472085,0.00021266298,0.0005038692],"genre_scores_gemma":[0.5253304,0.0015668293,0.46232593,0.00017255977,0.00020623728,0.00035152037,0.0015924925,0.000444242,0.00800972],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990721,0.00027938175,0.000043274773,0.00021709874,0.00031675491,0.00007136213],"domain_scores_gemma":[0.99907076,0.0004869074,0.00010749848,0.00017032633,0.00014293935,0.000021475393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013748942,0.0008755178,0.00087412907,0.0009889209,0.0002997958,0.0010954802,0.001399004,0.000783416,0.0010892753],"category_scores_gemma":[0.003818504,0.00044200337,0.0011250494,0.0019368782,0.0007297373,0.0015210492,0.00075995765,0.001035578,0.00078782585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105322695,0.000040749364,0.0015116499,0.0001425587,0.00009592467,0.00015263542,0.00021873023,0.82495964,0.00649926,0.08168626,0.0018388999,0.08274841],"study_design_scores_gemma":[0.000003675621,0.000011665269,0.00039844972,0.0000042250094,0.000009597072,0.00004361415,0.000008082446,0.9866007,0.00068506214,0.010947253,0.0012756265,0.000012093403],"about_ca_topic_score_codex":0.0030751957,"about_ca_topic_score_gemma":0.0035111515,"teacher_disagreement_score":0.0030751957,"about_ca_system_score_codex":0.0005373527,"about_ca_system_score_gemma":0.0005136771,"threshold_uncertainty_score":0.00727123},"labels":[],"label_agreement":null},{"id":"W2746773662","doi":"10.1186/s13634-017-0494-8","title":"A novel aliasing-free subband information fusion approach for wideband sparse spectral estimation","year":2017,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Matching pursuit; Aliasing; Computer science; Algorithm; Wideband; Binary number; Property (philosophy); Sparse approximation; Compressed sensing; Artificial intelligence; Mathematics; Arithmetic; Electronic engineering","score_opus":0.02434362569265652,"score_gpt":0.28103750281030815,"score_spread":0.2566938771176516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2746773662","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011745534,0.00012412654,0.9980531,0.000053270924,0.000018374822,0.000008392558,0.000017126058,0.000050573748,0.0005005178],"genre_scores_gemma":[0.11018689,0.00082343206,0.8854267,0.00020496923,0.00015156684,0.00009758659,0.00019609736,0.000056309913,0.0028564672],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950373,0.00010122328,0.000028702038,0.0001059343,0.00022377732,0.00003663237],"domain_scores_gemma":[0.99963677,0.00011435091,0.00006162706,0.000073607065,0.00009228698,0.000021467322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006172798,0.0008179686,0.0009726482,0.00076835847,0.0003659879,0.0007052745,0.00097523053,0.00113441,0.001471088],"category_scores_gemma":[0.0012203337,0.00034013332,0.0009965977,0.0010922935,0.00048521618,0.0017259151,0.0016122406,0.0013607104,0.0007933707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002153673,0.00013107703,0.0006441678,0.0004162471,0.00018086925,0.00029453493,0.00035505285,0.23379517,0.1051059,0.09859412,0.0046358416,0.5556317],"study_design_scores_gemma":[0.000008639174,0.00007799809,0.00017820175,0.000013185988,0.00002484178,0.00019376943,0.00002563279,0.97341466,0.009094858,0.0124128815,0.0045279097,0.000027373484],"about_ca_topic_score_codex":0.00057525944,"about_ca_topic_score_gemma":0.0006613778,"teacher_disagreement_score":0.001471088,"about_ca_system_score_codex":0.00028304692,"about_ca_system_score_gemma":0.00054966594,"threshold_uncertainty_score":0.004921317},"labels":[],"label_agreement":null},{"id":"W2783298029","doi":"10.1186/s13634-017-0526-4","title":"Joint frequency offset, time offset, and channel estimation for OFDM/OQAM systems","year":2018,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Orthogonal frequency-division multiplexing; Cramér–Rao bound; Estimator; Computer science; Carrier frequency offset; Algorithm; Upper and lower bounds; Joint (building); Frequency offset; Channel (broadcasting); Estimation theory; Telecommunications; Mathematics; Statistics; Engineering","score_opus":0.016325331640021343,"score_gpt":0.2714950399432098,"score_spread":0.2551697083031884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2783298029","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0098633375,0.0004024485,0.98918205,0.00004142909,0.00001447994,0.000008109082,0.000017485709,0.00012020967,0.0003505172],"genre_scores_gemma":[0.47878483,0.0013280794,0.5172457,0.00005580728,0.00011874777,0.0000690649,0.00020262651,0.00008152664,0.0021135856],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993988,0.00018252904,0.000032043936,0.00007673756,0.00025811145,0.000051743198],"domain_scores_gemma":[0.99919766,0.00042874593,0.000110756446,0.00011006141,0.00012993607,0.000022855558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008351218,0.0005955288,0.000623934,0.00042763245,0.00026332945,0.00052029506,0.00036419163,0.00042509713,0.00063564273],"category_scores_gemma":[0.0044086585,0.0002654567,0.00031748123,0.0005647396,0.0003907454,0.0008349224,0.0008675916,0.0007687609,0.00036347986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002688249,0.00006552818,0.0024579254,0.00023562115,0.00009092941,0.00017070815,0.00022263255,0.4736344,0.039222233,0.017391726,0.0013736775,0.46486577],"study_design_scores_gemma":[0.00001027463,0.000058889553,0.0010482715,0.000016938626,0.000021764214,0.00013077608,0.000028857326,0.9819173,0.010969309,0.0040335343,0.0017416138,0.000022512935],"about_ca_topic_score_codex":0.0018963262,"about_ca_topic_score_gemma":0.0028498906,"teacher_disagreement_score":0.0018963262,"about_ca_system_score_codex":0.00024096269,"about_ca_system_score_gemma":0.0010650352,"threshold_uncertainty_score":0.004416585},"labels":[],"label_agreement":null},{"id":"W3014172281","doi":"10.1155/s1110865704311078","title":"Upper Bounds on the BER Performance of MTCM-STBC Schemes over Shadowed Rician Fading Channels","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Space–time block code; Rician fading; Fading; Algorithm; Pairwise error probability; Coding gain; Computer science; Trellis modulation; Decoding methods; Block code; Bit error rate; Mathematics; Theoretical computer science","score_opus":0.014264817142493967,"score_gpt":0.2754820444045813,"score_spread":0.26121722726208735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014172281","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12623686,0.016631903,0.7970314,0.0012898701,0.00022672287,0.00013668882,0.00095239666,0.001384311,0.05610977],"genre_scores_gemma":[0.9195624,0.006738828,0.066226706,0.00041032655,0.00028662244,0.00025019067,0.0006871687,0.0003407285,0.0054969564],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952428,0.0010577256,0.00021141786,0.00033257555,0.0023857455,0.0007696769],"domain_scores_gemma":[0.96736175,0.02445804,0.0019304104,0.0024929985,0.0033943665,0.00036238146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053433096,0.0029491743,0.002342173,0.0022361383,0.0012124296,0.002490367,0.0013314576,0.0019330014,0.006092374],"category_scores_gemma":[0.032219872,0.0007834433,0.0009974698,0.0021436256,0.0023101335,0.0035692877,0.0027651214,0.002114572,0.0017780284],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024469884,0.00006363063,0.0009989208,0.0003826382,0.00009621509,0.00018899972,0.0001739912,0.891368,0.010275841,0.0673868,0.001300378,0.02751992],"study_design_scores_gemma":[0.00001887754,0.0001606724,0.0016067025,0.0002942728,0.00006476051,0.0004132422,0.00007552485,0.9369303,0.014173746,0.043951683,0.002226194,0.00008387261],"about_ca_topic_score_codex":0.0019238867,"about_ca_topic_score_gemma":0.0024681839,"teacher_disagreement_score":0.006092374,"about_ca_system_score_codex":0.0027538508,"about_ca_system_score_gemma":0.0015317919,"threshold_uncertainty_score":0.028258443},"labels":[],"label_agreement":null},{"id":"W3138975739","doi":"10.1186/s13634-021-00730-w","title":"Multi-source and multi-fault condition monitoring based on parallel factor analysis and sequential probability ratio test","year":2021,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China; Natural Science Foundation of Hubei Province; University of Alberta","keywords":"Aliasing; Computer science; Frequency domain; Wavelet; Algorithm; Time–frequency analysis; Time domain; Fault (geology); Transformation (genetics); Signal processing; Artificial intelligence; Digital signal processing","score_opus":0.022634920010114315,"score_gpt":0.3314184082728817,"score_spread":0.3087834882627674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138975739","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13431369,0.0002757217,0.8611671,0.0001251555,0.00009024125,0.00020986263,0.00015477193,0.0016129081,0.0020505153],"genre_scores_gemma":[0.88300085,0.00019193115,0.11574522,0.00003393862,0.000037687954,0.0001595762,0.00019145034,0.000059662085,0.00057969405],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975134,0.00055207004,0.00015628446,0.0005463662,0.0011086175,0.00012331596],"domain_scores_gemma":[0.9974254,0.00096795487,0.0003761823,0.00019145476,0.00093931373,0.0000997039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018275524,0.0013565226,0.0010796465,0.0025581173,0.0004073061,0.00089045113,0.0008425701,0.0007085918,0.0019165622],"category_scores_gemma":[0.006272375,0.000408458,0.0010714434,0.0017346151,0.00054336246,0.0018330372,0.0005502829,0.00063863397,0.00043319937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016863943,0.0008084119,0.03182426,0.0007378762,0.00053279096,0.0007214098,0.0004150243,0.2611495,0.059719857,0.005459954,0.0023096707,0.6346349],"study_design_scores_gemma":[0.00003742168,0.0002659674,0.0062620393,0.00001043381,0.00005556185,0.00017146455,0.000048276193,0.9826167,0.008577845,0.0015135764,0.00039142615,0.00004916872],"about_ca_topic_score_codex":0.002755275,"about_ca_topic_score_gemma":0.0015052833,"teacher_disagreement_score":0.002755275,"about_ca_system_score_codex":0.00045967952,"about_ca_system_score_gemma":0.0006760004,"threshold_uncertainty_score":0.009665132},"labels":[],"label_agreement":null},{"id":"W4213234291","doi":"10.1186/s13634-022-00844-9","title":"Free resources for forced phonetic alignment in Brazilian Portuguese based on Kaldi toolkit","year":2022,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Pró-Reitoria de Pesquisa e Pós-Graduação, Universidade Federal do Pará; Nvidia; Universidade Federal do Pará; Fundação Amazônia Paraense de Amparo à Pesquisa; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Computer science; Scripting language; Speech recognition; Phone; Portuguese; Natural language processing; Process (computing); Intersection (aeronautics); Artificial intelligence; Brazilian Portuguese; Linguistics; Programming language","score_opus":0.017650564225092733,"score_gpt":0.2759942747064355,"score_spread":0.25834371048134275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213234291","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028972061,0.0014546318,0.45503968,0.00064650027,0.0006316982,0.0006996224,0.07955144,0.40852112,0.024483277],"genre_scores_gemma":[0.19385372,0.0007472759,0.4730629,0.00051700475,0.0001156431,0.0019491338,0.26743236,0.050374463,0.0119473925],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99731356,0.0005642099,0.0005102416,0.000785894,0.0006174047,0.00020864143],"domain_scores_gemma":[0.99530965,0.0016510397,0.00026349004,0.0016584615,0.0008810098,0.00023635587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023648164,0.0023050562,0.0012312416,0.0025324372,0.0011787405,0.0021019503,0.0029069367,0.0012561136,0.026311146],"category_scores_gemma":[0.012742909,0.0013019708,0.001183349,0.0017531393,0.0008497949,0.003562519,0.0056190183,0.0022320133,0.025613856],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002698827,0.00039528945,0.0062684296,0.003994049,0.0002817364,0.0027090013,0.00339775,0.021293754,0.06478884,0.018806364,0.26644915,0.60891676],"study_design_scores_gemma":[0.00051351317,0.0003094556,0.011176566,0.00072884426,0.00021568216,0.0021641217,0.0012555514,0.16994116,0.13661838,0.024711588,0.65168506,0.00068003556],"about_ca_topic_score_codex":0.009823193,"about_ca_topic_score_gemma":0.01320727,"teacher_disagreement_score":0.026311146,"about_ca_system_score_codex":0.0009873088,"about_ca_system_score_gemma":0.002608476,"threshold_uncertainty_score":0.08801961},"labels":[],"label_agreement":null},{"id":"W4221041759","doi":"10.1186/s13634-022-00859-2","title":"A low complexity STPAP algorithm based on an alternating polarization-sensitive array","year":2022,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Polit National Laboratory for Marine Science and Technology; National Natural Science Foundation of China","keywords":"Algorithm; Space-time adaptive processing; Computer science; Computational complexity theory; Polarization (electrochemistry); Clutter; Radar; Telecommunications; Radar imaging; Continuous-wave radar","score_opus":0.014961150562046457,"score_gpt":0.26553504829293223,"score_spread":0.2505738977308858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221041759","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064306874,0.00005635802,0.9918234,0.000058738813,0.000032096923,0.000027893338,0.000018838333,0.00020675216,0.0013452958],"genre_scores_gemma":[0.1363582,0.00013743038,0.8590077,0.00014240516,0.000072283416,0.00018976755,0.00020256151,0.000059902886,0.0038297868],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99946874,0.000094538846,0.000034000535,0.00011172357,0.00023825179,0.00005281365],"domain_scores_gemma":[0.9993637,0.00020341764,0.000057503556,0.00007492143,0.0002556856,0.00004478027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038336212,0.0007014762,0.0006269801,0.0005084887,0.00044205177,0.0008690349,0.0008370278,0.000889576,0.0035859493],"category_scores_gemma":[0.0012723318,0.00038325033,0.00057566917,0.00067894,0.00043175663,0.00089229114,0.0009867925,0.001102515,0.0013442776],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037918688,0.00012892709,0.001271721,0.00015144976,0.00008766192,0.00021562456,0.00016878644,0.2775083,0.07871479,0.022602845,0.0042997994,0.6144709],"study_design_scores_gemma":[0.00001999423,0.000053893782,0.00014977565,0.000006421893,0.000008875482,0.000094980285,0.00001241567,0.99131155,0.0049557607,0.0017819338,0.0015936132,0.000010822863],"about_ca_topic_score_codex":0.0020421077,"about_ca_topic_score_gemma":0.0016076326,"teacher_disagreement_score":0.0035859493,"about_ca_system_score_codex":0.000277586,"about_ca_system_score_gemma":0.0011896912,"threshold_uncertainty_score":0.01199615},"labels":[],"label_agreement":null},{"id":"W4313829147","doi":"10.1186/s13634-022-00963-3","title":"A reconfigurable and compact subpipelined architecture for AES encryption and decryption","year":2023,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Computer science; Advanced Encryption Standard; Encryption; Key (lock); AES implementations; Cryptography; Computer hardware; Embedded system; Key size; Throughput; Public-key cryptography; Wireless; Computer network; Algorithm; Telecommunications; Operating system","score_opus":0.026170535895119102,"score_gpt":0.32895619395037423,"score_spread":0.30278565805525515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313829147","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4501492,0.0018639525,0.52132964,0.00030992163,0.00028135223,0.00022196953,0.000359135,0.0061703646,0.019314433],"genre_scores_gemma":[0.89511245,0.0002462619,0.09733904,0.00013543689,0.000040939587,0.000058426987,0.00024422433,0.000071637805,0.006751622],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998673,0.000019331912,0.000012770086,0.000034637895,0.000038001595,0.000027894188],"domain_scores_gemma":[0.99988556,0.000013216996,0.000026859578,0.000029274903,0.000033380613,0.000011747752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009652332,0.00034276058,0.00020838538,0.00038929848,0.00023320789,0.00030335464,0.00080403266,0.00022891905,0.0027034213],"category_scores_gemma":[0.00013657117,0.00016508433,0.00025763793,0.00024607373,0.00012110077,0.0005124205,0.00024054857,0.00026556355,0.00060850295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011698708,0.00013425882,0.0014429848,0.00034183208,0.00010337404,0.00060735416,0.00011443096,0.031022377,0.712717,0.007951052,0.005730966,0.23866442],"study_design_scores_gemma":[0.0003269848,0.0030982133,0.004542263,0.00005543188,0.00021157024,0.0018201137,0.00007517706,0.39688593,0.5437021,0.0033090673,0.045840815,0.00013235107],"about_ca_topic_score_codex":0.00072426547,"about_ca_topic_score_gemma":0.0011492666,"teacher_disagreement_score":0.0027034213,"about_ca_system_score_codex":0.00034360352,"about_ca_system_score_gemma":0.0003734229,"threshold_uncertainty_score":0.009043872},"labels":[],"label_agreement":null},{"id":"W4313889524","doi":"10.1186/s13634-022-00960-6","title":"Autoregressive graph Volterra models and applications","year":2023,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Science Foundation","keywords":"Identifiability; Computer science; Autoregressive model; Graph; Theoretical computer science; Volterra series; Identification (biology); Artificial intelligence; Machine learning; Nonlinear system; Mathematics; Econometrics","score_opus":0.020709863382114346,"score_gpt":0.3212073614156174,"score_spread":0.30049749803350306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313889524","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019491097,0.0019831124,0.9730709,0.0013859356,0.00012745355,0.000022431117,0.00018417045,0.00036361362,0.0033711577],"genre_scores_gemma":[0.87748516,0.0037521,0.10903896,0.00037917926,0.0002775614,0.00010970644,0.00046502097,0.00013252698,0.00835984],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954945,0.00021751257,0.000019381803,0.00009348883,0.00008115791,0.00003891052],"domain_scores_gemma":[0.9980136,0.001514377,0.00017755137,0.00008542504,0.00015984479,0.000049168724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011490958,0.00061900006,0.00076685345,0.0009594452,0.00027786137,0.001057627,0.0009805257,0.0012757599,0.002191956],"category_scores_gemma":[0.0049102916,0.0003555613,0.00079329655,0.0013250187,0.00061958766,0.00088990276,0.0007439435,0.0014445646,0.0005147321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001817299,0.00003062631,0.0011005775,0.00006331036,0.000050070015,0.00007764164,0.000054733842,0.86583734,0.00051603845,0.1039556,0.0017247504,0.026571084],"study_design_scores_gemma":[0.0000010164971,0.0000029413234,0.00011015372,0.0000047948583,0.0000025574454,0.0000066215885,0.000004415803,0.9753303,0.00003966714,0.024086509,0.0004079466,0.0000031054922],"about_ca_topic_score_codex":0.008118555,"about_ca_topic_score_gemma":0.0046805404,"teacher_disagreement_score":0.008118555,"about_ca_system_score_codex":0.000761389,"about_ca_system_score_gemma":0.00050750206,"threshold_uncertainty_score":0.016142607},"labels":[],"label_agreement":null},{"id":"W4321087067","doi":"10.1186/s13634-023-00981-9","title":"Broadband beamforming of multiplet line arrays using subband optimal beamformers eliminating port/starboard ambiguity","year":2023,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Office of Naval Research; Defence Science and Technology Group; Defence Science and Technology Laboratory; Ministère de la Défense Nationale","keywords":"Beamforming; Narrowband; Computer science; Sonar; Minimum-variance unbiased estimator; Broadband; Marine mammals and sonar; Ambiguity; Adaptive beamformer; Algorithm; Acoustics; Telecommunications; Mathematics; Artificial intelligence; Physics; Estimator","score_opus":0.04319419563339664,"score_gpt":0.32173671444402324,"score_spread":0.2785425188106266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321087067","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006977656,0.00004011725,0.99196905,0.00003073668,0.000012362046,0.000012570678,0.000018690589,0.0001553029,0.0007835297],"genre_scores_gemma":[0.1631638,0.00030114653,0.833128,0.00010251224,0.000044088203,0.0001331262,0.00015606226,0.000095985284,0.0028754317],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967027,0.00010411155,0.0000179219,0.000052300074,0.00013217547,0.000023276862],"domain_scores_gemma":[0.99953914,0.00017854957,0.00008482822,0.00005266758,0.00012439558,0.000020475465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042400134,0.0006099455,0.00040807796,0.0003097417,0.00011480598,0.00051944546,0.00027491874,0.00044182365,0.0027091727],"category_scores_gemma":[0.0011651469,0.00023545664,0.00043394143,0.0004357126,0.00030401332,0.000518218,0.00053484144,0.00042021074,0.0012445071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025968815,0.000079327976,0.0006231859,0.00019508046,0.00008455225,0.000089622874,0.00017759297,0.2549006,0.3583434,0.009955917,0.0013656939,0.37392533],"study_design_scores_gemma":[0.00004795469,0.00032825663,0.0010306977,0.000035902325,0.000039432834,0.00021285214,0.00006974412,0.9122082,0.075881444,0.00437668,0.0057345172,0.000034344044],"about_ca_topic_score_codex":0.00031396525,"about_ca_topic_score_gemma":0.00055972004,"teacher_disagreement_score":0.0027091727,"about_ca_system_score_codex":0.00014892692,"about_ca_system_score_gemma":0.00029791755,"threshold_uncertainty_score":0.009063125},"labels":[],"label_agreement":null},{"id":"W4381683333","doi":"10.1186/s13634-023-01025-y","title":"PFDI: a precise fruit disease identification model based on context data fusion with faster-CNN in edge computing environment","year":2023,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Qatar National Library; Taif University; Hamad Bin Khalifa University","keywords":"Context (archaeology); Computer science; RGB color model; Pruning; Artificial intelligence; Deep learning; Sensor fusion; Pattern recognition (psychology); Machine learning; Horticulture; Biology","score_opus":0.03784652449665259,"score_gpt":0.2700080675415432,"score_spread":0.23216154304489062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381683333","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33719322,0.0014778944,0.6479251,0.0006799238,0.00028356677,0.0001420962,0.0008608488,0.0044218493,0.0070155542],"genre_scores_gemma":[0.9622126,0.00023866892,0.033607226,0.0001733096,0.00002223109,0.00005672437,0.000502477,0.000033882134,0.0031527278],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998841,0.0000072302632,0.000005939953,0.00004757284,0.000025868972,0.000029190947],"domain_scores_gemma":[0.9998877,0.000018930763,0.000013697472,0.000012798437,0.000055995395,0.000010815914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023964369,0.0008086043,0.00048313607,0.00031297575,0.00022340189,0.00044953413,0.0010282319,0.00060873467,0.0012115032],"category_scores_gemma":[0.00042705788,0.00023532646,0.0006270957,0.0002049684,0.00018317628,0.00066906284,0.0004709963,0.0007187647,0.0002736533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002880162,0.000203623,0.007930113,0.000083223684,0.00012717683,0.00023103035,0.000052076226,0.7889365,0.019261291,0.0013272633,0.0026301302,0.17892951],"study_design_scores_gemma":[0.000002178039,0.000023177514,0.000510476,0.0000021610156,0.000008109248,0.000011346584,0.0000023715963,0.9974808,0.0016151452,0.00018886302,0.00015225713,0.0000031158947],"about_ca_topic_score_codex":0.020295452,"about_ca_topic_score_gemma":0.015984422,"teacher_disagreement_score":0.020295452,"about_ca_system_score_codex":0.0008557343,"about_ca_system_score_gemma":0.00064656953,"threshold_uncertainty_score":0.04035461},"labels":[],"label_agreement":null}]}