{"meta":{"query_hash":"5b06860d95ab","filters":{"venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)"},"cohort_total":133,"direct_labels_cover":0,"predictions_cover":133,"exported":133,"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/5b06860d95ab","api":"https://metacan.xera.ac/api/v1/cohort?venue=IEEE+Transactions+on+Systems+Man+and+Cybernetics+Part+B+%28Cybernetics%29"},"results":[{"id":"W1965693572","doi":"10.1109/tsmcb.2012.2192270","title":"Tracking Control of a Closed-Chain Five-Bar Robot With Two Degrees of Freedom by Integration of an Approximation-Based Approach and Mechanical Design","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"University of Saskatchewan","keywords":"Bar (unit); Degrees of freedom (physics and chemistry); Chain (unit); Control theory (sociology); Robot; Tracking (education); Control engineering; Control (management); Computer science; Engineering; Artificial intelligence; Physics; Psychology","score_opus":0.019048722015434966,"score_gpt":0.21418125666369636,"score_spread":0.19513253464826139,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965693572","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":[0.019216962,0.0002824958,0.9773202,0.00009483736,0.000065993205,0.000032901,0.000010891438,0.00021026647,0.0027655212],"genre_scores_gemma":[0.91275847,0.00032820168,0.08299435,0.00005547532,0.00003908052,0.00015309194,0.000044105916,0.000016689643,0.003610506],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99973315,0.000050790168,0.00001642186,0.000065721964,0.00010449749,0.00002933589],"domain_scores_gemma":[0.99967694,0.0000942393,0.00009150194,0.000029235849,0.00008694806,0.000021051006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000583628,0.00069976354,0.00059411884,0.00031695774,0.0006257956,0.00068166957,0.0007685635,0.0010128958,0.0012755796],"category_scores_gemma":[0.00066024513,0.00030512078,0.0004464441,0.00039568663,0.0007609128,0.0005555045,0.0006603266,0.0006181832,0.00026459558],"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":[0.00016968772,0.000056589954,0.0006056895,0.00030452042,0.00005130812,0.00022640104,0.00023193806,0.88507545,0.03117492,0.017953582,0.00055902137,0.06359091],"study_design_scores_gemma":[0.0000119385895,0.000102922924,0.00009590964,0.000008203669,0.0000082909955,0.000026571826,0.0000070111632,0.99721044,0.0011549868,0.0007551742,0.0006113199,0.0000072426537],"about_ca_topic_score_codex":0.004471217,"about_ca_topic_score_gemma":0.0025399812,"teacher_disagreement_score":0.004471217,"about_ca_system_score_codex":0.00042947286,"about_ca_system_score_gemma":0.0008409591,"threshold_uncertainty_score":0.00889039},"labels":[],"label_agreement":null},{"id":"W1975842137","doi":"10.1109/tsmcb.2011.2161284","title":"Gaussian-Mixture-Model-Based Spatial Neighborhood Relationships for Pixel Labeling Problem","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":75,"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":"National Research Council Canada; Canada Research Chairs","keywords":"Mixture model; Pixel; Robustness (evolution); Artificial intelligence; Pattern recognition (psychology); Computer science; Gaussian; Markov chain; Expectation–maximization algorithm; Image segmentation; Segmentation; Markov random field; Maximization; Mathematics; Algorithm; Statistics; Maximum likelihood; Mathematical optimization; Machine learning","score_opus":0.05189248862871049,"score_gpt":0.24876436706854055,"score_spread":0.19687187843983006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975842137","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":[0.0018722705,0.00011624925,0.9973937,0.00006261304,0.000010061325,0.00001641958,0.000020418622,0.00027815244,0.00023001048],"genre_scores_gemma":[0.1496941,0.0004169421,0.84637994,0.00017477272,0.00009777307,0.00022578199,0.0003978099,0.0002558677,0.0023569749],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850273,0.0004401694,0.000056282606,0.0005072245,0.000378955,0.000114543094],"domain_scores_gemma":[0.9988778,0.00060672796,0.00011907199,0.00014528193,0.00020707925,0.00004396447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017575745,0.0008586048,0.002090996,0.0014833523,0.0008105932,0.0012049582,0.002749818,0.0024762328,0.0017285494],"category_scores_gemma":[0.004215756,0.0009413317,0.0014061743,0.0016201315,0.0010705328,0.0027035652,0.0014058514,0.0015803108,0.00089256035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019446178,0.00009861434,0.0014411117,0.00021165129,0.00011175535,0.00018345038,0.00024157186,0.61194974,0.0077817515,0.04105739,0.005424247,0.33130425],"study_design_scores_gemma":[0.000003991195,0.000011572533,0.000113266266,0.000004661074,0.000009980316,0.000052940315,0.000013027888,0.9904846,0.0010076392,0.007456595,0.00083308056,0.0000086412465],"about_ca_topic_score_codex":0.00805,"about_ca_topic_score_gemma":0.00797909,"teacher_disagreement_score":0.00805,"about_ca_system_score_codex":0.0013441541,"about_ca_system_score_gemma":0.001746062,"threshold_uncertainty_score":0.01600629},"labels":[],"label_agreement":null},{"id":"W1987597182","doi":"10.1109/tsmcb.2012.2192109","title":"A Globally Optimal Estimator for the Delta-Lognormal Modeling of Fast Reaching Movements","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Motor Control and Adaptation","field":"Neuroscience","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":"Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Estimator; Computer science; Benchmark (surveying); Noise (video); Set (abstract data type); Log-normal distribution; Algorithm; Artificial intelligence; Mathematics; Statistics","score_opus":0.04613963974013413,"score_gpt":0.26358419131419164,"score_spread":0.2174445515740575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987597182","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":[0.010945995,0.000043714408,0.9884321,0.00003444967,0.000004385075,0.000012248993,0.000013950475,0.00019966111,0.00031348914],"genre_scores_gemma":[0.2638236,0.00013605911,0.73415905,0.000053516073,0.000012187452,0.00012692934,0.00014539715,0.00021563422,0.0013276815],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968624,0.000098841156,0.000021196105,0.000076416196,0.000083181105,0.000034153607],"domain_scores_gemma":[0.9989512,0.0006142839,0.00010761917,0.00009989633,0.00018980457,0.000037137004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013935792,0.0008032049,0.0007124487,0.0006879249,0.00033808305,0.000868218,0.00061600446,0.0010673592,0.0012548215],"category_scores_gemma":[0.006102005,0.00049005024,0.00046805714,0.00038461934,0.00051396503,0.0010237898,0.00061379705,0.0010860644,0.0005487122],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013034245,0.00005657486,0.0021033757,0.00007995457,0.000044471977,0.000060114773,0.00015515156,0.79194343,0.018504769,0.014009827,0.0007962034,0.17211583],"study_design_scores_gemma":[0.0000064054475,0.000019270856,0.00030825843,0.000009233904,0.000005112023,0.000023051794,0.000012412085,0.9934042,0.002655496,0.0032358984,0.00031231833,0.000008448404],"about_ca_topic_score_codex":0.0032225854,"about_ca_topic_score_gemma":0.00377133,"teacher_disagreement_score":0.0032225854,"about_ca_system_score_codex":0.0006270545,"about_ca_system_score_gemma":0.0014928082,"threshold_uncertainty_score":0.0073700547},"labels":[],"label_agreement":null},{"id":"W1999720320","doi":"10.1109/tsmcb.2002.979953","title":"Editorial advances on uncertain reasoning in intelligent systems","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Cognitive science; Artificial intelligence; Psychology","score_opus":0.023200956140781777,"score_gpt":0.2412142747055978,"score_spread":0.21801331856481604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999720320","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":[0.0000674483,0.01804425,0.0007056257,0.04336345,0.93489945,0.000011481709,0.000072528586,0.00004034172,0.0027954758],"genre_scores_gemma":[0.0011766691,0.007794201,0.000247756,0.009066003,0.976756,0.000012049797,0.000025405898,0.000025114845,0.004896749],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976948,0.0004579357,0.00029672618,0.00030863413,0.0010901783,0.00015168522],"domain_scores_gemma":[0.9771985,0.013701704,0.0009090175,0.0005285617,0.006230697,0.0014316184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040583196,0.002070821,0.0023727189,0.0035167832,0.0015783154,0.0044370247,0.0020684474,0.0064298995,0.019144727],"category_scores_gemma":[0.01898045,0.00063986494,0.0015188045,0.0014352616,0.0020252177,0.0041223373,0.0010867293,0.009676054,0.006132753],"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":[0.000063424275,0.000015394531,0.000036457957,0.0005104193,0.000029158688,0.00012747353,0.000016359161,0.00007892436,0.00007041831,0.0022157643,0.98167163,0.015164494],"study_design_scores_gemma":[0.000054309003,0.00003303782,0.0002121388,0.00037144573,0.000064651496,0.00021391784,0.000022137963,0.00036489445,0.00012251569,0.004829546,0.9936946,0.00001675315],"about_ca_topic_score_codex":0.0004564917,"about_ca_topic_score_gemma":0.0010362546,"teacher_disagreement_score":0.019144727,"about_ca_system_score_codex":0.0011070584,"about_ca_system_score_gemma":0.0007203038,"threshold_uncertainty_score":0.06404543},"labels":[],"label_agreement":null},{"id":"W2015705737","doi":"10.1109/tsmcb.2011.2182646","title":"Learning of Fuzzy Cognitive Maps Using Density Estimate","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":73,"is_retracted":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":"Interpretability; Fuzzy cognitive map; Flexibility (engineering); Computer science; Adaptability; Artificial intelligence; Machine learning; Fuzzy logic; Data mining; Fuzzy control system; Mathematics; Neuro-fuzzy","score_opus":0.03491498848421518,"score_gpt":0.273088238924722,"score_spread":0.23817325044050683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015705737","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":[0.039129782,0.00014699184,0.9591909,0.00014046606,0.0000142770705,0.000051103587,0.0000390534,0.00028949586,0.0009977754],"genre_scores_gemma":[0.7700171,0.0002180139,0.22808075,0.00010859332,0.000036470003,0.00021577501,0.0001822975,0.000046874295,0.0010941335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953973,0.0001677807,0.000024612129,0.000105807165,0.00011328298,0.000048753867],"domain_scores_gemma":[0.9963186,0.002703606,0.00023666273,0.0001841627,0.00047589384,0.00008098042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017037116,0.0008127852,0.0009437087,0.0014760976,0.00045443245,0.0011006183,0.0013175807,0.0010995085,0.0011756686],"category_scores_gemma":[0.010199975,0.00053039525,0.0009104043,0.0006694018,0.000997178,0.001614378,0.001383317,0.0013096188,0.00018658247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006561233,0.000039156166,0.0013627051,0.00006942069,0.00006130702,0.000056366865,0.00014576026,0.8955871,0.0009648768,0.0141592,0.0006871482,0.08680132],"study_design_scores_gemma":[0.0000048812594,0.00000958414,0.00009337624,0.0000060543334,0.000003730799,0.000008168874,0.0000071220493,0.9936194,0.00025840424,0.0058847764,0.000100540354,0.0000039511997],"about_ca_topic_score_codex":0.009083093,"about_ca_topic_score_gemma":0.0048388313,"teacher_disagreement_score":0.009083093,"about_ca_system_score_codex":0.0012185484,"about_ca_system_score_gemma":0.001158452,"threshold_uncertainty_score":0.018060446},"labels":[],"label_agreement":null},{"id":"W2046746658","doi":"10.1109/tsmcb.2010.2042108","title":"Special Issue on Game Theory","year":2010,"lang":"en","type":"editorial","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Game theory; Focus (optics); Computer science; Management science; State (computer science); Engineering ethics; Data science; Mathematical economics; Mathematics; Engineering; Algorithm","score_opus":0.03175290586044338,"score_gpt":0.31558939871396324,"score_spread":0.28383649285351986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046746658","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":[0.000035016154,0.011064843,0.00055888324,0.02355826,0.9555195,0.000029269675,0.00007103594,0.00006783883,0.009095448],"genre_scores_gemma":[0.00089963287,0.012575877,0.00037508822,0.013973762,0.93700475,0.000065946755,0.000096509844,0.00012331219,0.034885116],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99608314,0.0006729414,0.00042347496,0.0005658051,0.0019512663,0.0003034055],"domain_scores_gemma":[0.98825246,0.0052828947,0.000504936,0.00042423268,0.004279722,0.0012557653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040155933,0.0038122784,0.0036758482,0.0033744501,0.002188191,0.007634106,0.002571339,0.008360378,0.033764925],"category_scores_gemma":[0.014379734,0.0008433882,0.002791398,0.0017645134,0.002511927,0.004861337,0.0016083308,0.014285599,0.020411758],"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":[0.000011313509,0.000008747432,0.000009772947,0.000097516415,0.00000836304,0.000028953138,0.000006146721,0.00005389432,0.000036442834,0.0018768265,0.9922455,0.005616531],"study_design_scores_gemma":[0.000030599283,0.000017516746,0.00011263028,0.00025507662,0.000018609988,0.00012725832,0.000014013796,0.0002845469,0.00006680777,0.0054627582,0.9935988,0.000011438862],"about_ca_topic_score_codex":0.0011928288,"about_ca_topic_score_gemma":0.0022190055,"teacher_disagreement_score":0.033764925,"about_ca_system_score_codex":0.0041017304,"about_ca_system_score_gemma":0.0028979063,"threshold_uncertainty_score":0.112954915},"labels":[],"label_agreement":null},{"id":"W2050183348","doi":"10.1109/tsmcb.2012.2191403","title":"Dynamic Sample Size Detection in Learning Command Line Sequence for Continuous Authentication","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"User Authentication and Security Systems","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; University of Victoria","funders":"","keywords":"Computer science; Authentication (law); Sequence (biology); Detector; Session (web analytics); Set (abstract data type); Naive Bayes classifier; Data mining; Vulnerability (computing); Process (computing); Window (computing); Real-time computing; Artificial intelligence; Computer security; Support vector machine; Telecommunications","score_opus":0.026255513301989913,"score_gpt":0.26713124208998,"score_spread":0.2408757287879901,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050183348","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":[0.120540604,0.00032728587,0.87704825,0.00017295327,0.00005203578,0.00016147143,0.00006192487,0.0010981208,0.00053740875],"genre_scores_gemma":[0.775029,0.00010770435,0.22368246,0.000114469556,0.000049067745,0.00019476085,0.00015342454,0.000035323636,0.0006338454],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978338,0.0008583151,0.00019460243,0.00044599434,0.00054096663,0.00012635265],"domain_scores_gemma":[0.98022753,0.015891032,0.0010065536,0.0008612787,0.0016336445,0.00038001995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048908913,0.0005496864,0.001143844,0.0013258493,0.0005643812,0.00067827286,0.0010964569,0.0009773043,0.000808869],"category_scores_gemma":[0.021879839,0.0003127303,0.0003607305,0.0006279528,0.0008048674,0.0012295744,0.00062570977,0.0010313754,0.00032357126],"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":[0.001689062,0.00060632743,0.027283214,0.00024629917,0.00014882689,0.00027669323,0.00044400897,0.31250373,0.025065757,0.007277258,0.0016728613,0.6227859],"study_design_scores_gemma":[0.000027010869,0.00016029569,0.0017546957,0.0000088486495,0.000013597677,0.00010270621,0.00002897036,0.9899351,0.0051569953,0.0025282635,0.0002669538,0.000016528174],"about_ca_topic_score_codex":0.0034751727,"about_ca_topic_score_gemma":0.0040983777,"teacher_disagreement_score":0.0048908913,"about_ca_system_score_codex":0.00074360054,"about_ca_system_score_gemma":0.001423334,"threshold_uncertainty_score":0.025865793},"labels":[],"label_agreement":null},{"id":"W2061490590","doi":"10.1109/tsmcb.2011.2176115","title":"Soft Object Deformation Monitoring and Learning for Model-Based Robotic Hand Manipulation","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"GRASP; Computer vision; Artificial intelligence; Object (grammar); Computer science; Position (finance); Controller (irrigation); Deformation (meteorology); Robot; Robotic hand; Robotic arm; Physics","score_opus":0.04264400909565564,"score_gpt":0.2328920430472234,"score_spread":0.19024803395156778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061490590","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":[0.018326877,0.00013194598,0.98004395,0.00004408473,0.000009698335,0.000024378845,0.000018603452,0.0010027204,0.0003977252],"genre_scores_gemma":[0.6487367,0.00027916068,0.3484522,0.00006721333,0.000026681082,0.00012901028,0.00011545431,0.000117481664,0.0020761352],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975926,0.00003150586,0.000011712329,0.00007396556,0.00009797294,0.000025607807],"domain_scores_gemma":[0.99968076,0.00011037862,0.00007784154,0.00006533259,0.000046790185,0.000018950233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041666187,0.00054744905,0.0006073534,0.00047458638,0.00023403896,0.00046071573,0.0008325014,0.0006082573,0.0010089662],"category_scores_gemma":[0.0014344192,0.00041391386,0.00042397509,0.00032455157,0.00049338693,0.00085630605,0.00062347506,0.00057055004,0.00027851542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001427179,0.00011844103,0.0011337221,0.0000679347,0.000048821712,0.00008816256,0.00006263872,0.5023793,0.060321797,0.0030642261,0.00063450285,0.43193772],"study_design_scores_gemma":[0.0000030091562,0.000027459566,0.00037491406,0.000003000568,0.000003950056,0.000024310735,0.000003608079,0.9904607,0.0077007706,0.0010891767,0.00030328706,0.0000058606356],"about_ca_topic_score_codex":0.0045455424,"about_ca_topic_score_gemma":0.0053002457,"teacher_disagreement_score":0.0045455424,"about_ca_system_score_codex":0.000667083,"about_ca_system_score_gemma":0.0005582003,"threshold_uncertainty_score":0.00903815},"labels":[],"label_agreement":null},{"id":"W2062450215","doi":"10.1109/tsmcb.2004.827609","title":"Face Recognition Using Fuzzy Integral and Wavelet Decomposition Method","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":91,"is_retracted":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":"Face (sociological concept); Wavelet; Artificial intelligence; Fuzzy logic; Consistency (knowledge bases); Pattern recognition (psychology); Diagonal; Choquet integral; Facial recognition system; Computer science; Decomposition; Mathematics; Wavelet transform; Geometry","score_opus":0.03513357894305298,"score_gpt":0.28622347201667353,"score_spread":0.25108989307362056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062450215","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":[0.009747482,0.00020792813,0.9892693,0.00003907711,0.00002007263,0.0000139751855,0.0000076105703,0.00012945294,0.0005650229],"genre_scores_gemma":[0.23546322,0.0004870023,0.7624708,0.00005125639,0.00005719209,0.000054066903,0.0000611898,0.000029686036,0.001325728],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993699,0.00009343175,0.000035767185,0.000098648976,0.00035990574,0.00004239636],"domain_scores_gemma":[0.9996805,0.0001284428,0.000026282427,0.00003447654,0.000115404386,0.000014935312],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010104505,0.00029983322,0.00092725287,0.0013031755,0.00028004672,0.00054104894,0.00050506333,0.0004750313,0.00087091373],"category_scores_gemma":[0.0017853183,0.00021756081,0.000729145,0.0007833902,0.00041438625,0.0010913678,0.0004887417,0.00066642155,0.00034458714],"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":[0.00015991286,0.00008395179,0.0012331733,0.00018640481,0.00008134962,0.00014181715,0.00022890298,0.07880174,0.071588546,0.03078527,0.0010606238,0.81564826],"study_design_scores_gemma":[0.00000840488,0.000049466766,0.00093825685,0.000015399228,0.000028203029,0.00016496124,0.000023742628,0.97575206,0.012749733,0.008543835,0.0017027407,0.000023194356],"about_ca_topic_score_codex":0.0011641785,"about_ca_topic_score_gemma":0.0007063746,"teacher_disagreement_score":0.0013031755,"about_ca_system_score_codex":0.00034992112,"about_ca_system_score_gemma":0.00035476446,"threshold_uncertainty_score":0.005343795},"labels":[],"label_agreement":null},{"id":"W2068705067","doi":"10.1109/tsmcb.2005.861878","title":"A control scheme for stable force-reflecting teleoperation over IP networks","year":2006,"lang":"en","type":"letter","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":88,"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":"Teleoperation; Control theory (sociology); Trajectory; Channel (broadcasting); Discontinuity (linguistics); Stability (learning theory); Computer science; Scheme (mathematics); Small-gain theorem; Filter (signal processing); Function (biology); Mathematics; Control (management); Telecommunications; Mathematical analysis","score_opus":0.018442973282048625,"score_gpt":0.2307007207438435,"score_spread":0.21225774746179488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068705067","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":[0.013167981,0.0002896852,0.97572476,0.00086936605,0.00034233733,0.00013624331,0.000019960884,0.0003960245,0.0090535525],"genre_scores_gemma":[0.75298136,0.00049685675,0.23476368,0.0004933674,0.00018724416,0.00028461817,0.000036341782,0.000031086613,0.010725378],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997882,0.00004004031,0.000010991644,0.000029400804,0.00011699055,0.000014391751],"domain_scores_gemma":[0.9997638,0.00007664547,0.000029083792,0.00004714318,0.00007022218,0.0000131296865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036115324,0.00025814716,0.000201713,0.00015942732,0.00037140277,0.0004925693,0.0007999613,0.00068213354,0.0021871221],"category_scores_gemma":[0.0009877209,0.00010353325,0.00015122337,0.00017516939,0.00050445256,0.0005467083,0.00047634947,0.0008326303,0.00038283493],"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":[0.00030073474,0.00009386322,0.0002638007,0.00045257484,0.00003294689,0.00089938147,0.00043467092,0.08664872,0.16894926,0.31402025,0.014497197,0.4134067],"study_design_scores_gemma":[0.00013368441,0.00036767655,0.0002620089,0.000057291916,0.000021613216,0.0006652545,0.00002868468,0.9400827,0.013572286,0.01585445,0.028921759,0.000032593583],"about_ca_topic_score_codex":0.0004962083,"about_ca_topic_score_gemma":0.00054305646,"teacher_disagreement_score":0.0021871221,"about_ca_system_score_codex":0.0004559081,"about_ca_system_score_gemma":0.00030921886,"threshold_uncertainty_score":0.0073167086},"labels":[],"label_agreement":null},{"id":"W2079624507","doi":"10.1109/tsmcb.2011.2171680","title":"Stochastic Subset Selection for Learning With Kernel Machines","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Data Stream Mining 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":"Carleton University","funders":"","keywords":"Computer science; Machine learning; Kernel (algebra); Support vector machine; Graph kernel; Kernel method; Tree kernel; Artificial intelligence; Radial basis function kernel; Multiple kernel learning; String kernel; Selection (genetic algorithm); Polynomial kernel; Quadratic programming; Algorithm; Data mining; Mathematical optimization; Mathematics","score_opus":0.028693774660058423,"score_gpt":0.23704981346793502,"score_spread":0.2083560388078766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079624507","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":[0.0020046711,0.00022118162,0.9968811,0.00007994632,0.000028619712,0.000042843432,0.00004225788,0.00038269494,0.0003165656],"genre_scores_gemma":[0.22044484,0.0012436616,0.77217555,0.0002448832,0.00037956025,0.0009293438,0.0010585554,0.00043367542,0.0030899346],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99741495,0.0011068924,0.00015560117,0.00040211843,0.0008147571,0.00010569699],"domain_scores_gemma":[0.9946239,0.00322102,0.00031833784,0.0007271859,0.0009899787,0.000119680364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002858454,0.001419139,0.0019968352,0.0016188473,0.0007086526,0.0014656326,0.0015209225,0.00091203046,0.0023546373],"category_scores_gemma":[0.01297951,0.0006493376,0.0013404181,0.0018704667,0.00091906753,0.0017394512,0.0016366994,0.0019059787,0.0013572638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020151984,0.00012341108,0.0017073915,0.00029253596,0.0002090101,0.00015937017,0.00015082132,0.5891465,0.0043894043,0.05967566,0.0069894143,0.33695486],"study_design_scores_gemma":[0.000009890662,0.000032485976,0.00012931565,0.000010096236,0.000009896974,0.00003151623,0.0000085167985,0.97908986,0.0011829921,0.017729193,0.0017580464,0.000008129251],"about_ca_topic_score_codex":0.0014475143,"about_ca_topic_score_gemma":0.0011449013,"teacher_disagreement_score":0.002858454,"about_ca_system_score_codex":0.0009703578,"about_ca_system_score_gemma":0.0010531518,"threshold_uncertainty_score":0.015117168},"labels":[],"label_agreement":null},{"id":"W2090571851","doi":"10.1109/tsmcb.2011.2170067","title":"An Optimization of Allocation of Information Granularity in the Interpretation of Data Structures: Toward Granular Fuzzy Clustering","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Rough Sets and Fuzzy Logic","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 Alberta","funders":"","keywords":"Granularity; Cluster analysis; Granular computing; Partition (number theory); Representation (politics); Computer science; Data mining; Theoretical computer science; Mathematics; Mathematical optimization; Algorithm; Artificial intelligence; Rough set","score_opus":0.045450194192103444,"score_gpt":0.25739798709449796,"score_spread":0.21194779290239452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090571851","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":[0.019289965,0.00022390764,0.9796525,0.00017885744,0.000007696918,0.000037730657,0.000019433342,0.000058243593,0.0005316055],"genre_scores_gemma":[0.28574833,0.00028488244,0.713271,0.00007483074,0.0000317385,0.0001296811,0.00006247818,0.0000552041,0.00034177498],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99684817,0.0013675096,0.00026951908,0.000547283,0.00079556904,0.00017187725],"domain_scores_gemma":[0.9951384,0.0029269792,0.0005896536,0.00073077093,0.0004855671,0.00012860629],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004212937,0.00071720436,0.0012904701,0.0019762283,0.0006421051,0.0022247212,0.0010611346,0.0012015308,0.00049187423],"category_scores_gemma":[0.016597496,0.00068750285,0.00080649275,0.002349546,0.0020400835,0.0030133817,0.0025034312,0.0011743607,0.00014562313],"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":[0.0003825636,0.00012214473,0.002096064,0.0005534672,0.00013322274,0.0002181955,0.0016835883,0.5067249,0.027327524,0.1660686,0.0014748642,0.29321483],"study_design_scores_gemma":[0.00004215876,0.00013753645,0.00058718777,0.00007180631,0.00004748552,0.0001108917,0.00026525283,0.8531181,0.0076936786,0.13557844,0.002307146,0.000040390816],"about_ca_topic_score_codex":0.001011234,"about_ca_topic_score_gemma":0.0008108809,"teacher_disagreement_score":0.004212937,"about_ca_system_score_codex":0.0011651886,"about_ca_system_score_gemma":0.0010117698,"threshold_uncertainty_score":0.022280395},"labels":[],"label_agreement":null},{"id":"W2095946149","doi":"10.1109/tsmcb.2003.814282","title":"Fusion of range camera and photogrammetry: A systematic procedure for improving 3-D models metric accuracy","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Photogrammetry; Metric (unit); Computer vision; Computer science; Artificial intelligence; Range (aeronautics); Object (grammar); Set (abstract data type); Computer graphics (images); Engineering","score_opus":0.01759995553874805,"score_gpt":0.21705837640027806,"score_spread":0.19945842086153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095946149","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":[0.0047502755,0.00014858747,0.99386966,0.000029737565,0.000016849557,0.000038164348,0.000016804368,0.00053457625,0.00059527135],"genre_scores_gemma":[0.11032226,0.00029717106,0.88814193,0.0000416486,0.000026520918,0.0000922766,0.0001273253,0.00018452546,0.00076623634],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99746907,0.00049831707,0.00015197434,0.000510251,0.0012661943,0.00010420537],"domain_scores_gemma":[0.9978829,0.0003786927,0.0002568896,0.0009499374,0.0004951374,0.00003638143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016918941,0.0010911818,0.0010799798,0.0017425972,0.00050909584,0.001132227,0.0015254572,0.00086357404,0.0014693331],"category_scores_gemma":[0.0050187563,0.00093668565,0.0010801362,0.0018211772,0.0008830795,0.0020240538,0.0026232367,0.0011389875,0.0011874614],"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":[0.00021117639,0.000109669774,0.0013559449,0.00040042243,0.0001561781,0.00017955052,0.0005896287,0.061999507,0.14417744,0.016828543,0.0014215467,0.7725703],"study_design_scores_gemma":[0.00009068296,0.0010766846,0.0059961937,0.00014873089,0.00025858264,0.0015971757,0.00028910182,0.59095776,0.3365475,0.024555039,0.038248252,0.00023433937],"about_ca_topic_score_codex":0.0010072422,"about_ca_topic_score_gemma":0.0009512727,"teacher_disagreement_score":0.0017425972,"about_ca_system_score_codex":0.0004301122,"about_ca_system_score_gemma":0.00093782955,"threshold_uncertainty_score":0.00894767},"labels":[],"label_agreement":null},{"id":"W2096060214","doi":"10.1109/tsmcb.2009.2013334","title":"Interpreting Concept Learning in Cognitive Informatics and Granular Computing","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":166,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Informatics; Computer science; Cognition; Cognitive science; Cognitive computing; Granular computing; Psychology; Artificial intelligence; Engineering; Neuroscience","score_opus":0.015164637305426845,"score_gpt":0.24311710066220624,"score_spread":0.22795246335677938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096060214","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":[0.07039802,0.0055966834,0.84259427,0.015571353,0.00048688395,0.00018845343,0.00024389174,0.00028973937,0.06463071],"genre_scores_gemma":[0.7983123,0.0014860504,0.19585837,0.0009305725,0.00025761203,0.00022689848,0.00016890181,0.00005357437,0.002705783],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99676406,0.0017825936,0.00019889767,0.0003753115,0.00063498114,0.00024408106],"domain_scores_gemma":[0.99407876,0.003519302,0.0007037194,0.0008198615,0.00056695665,0.00031154513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006076704,0.0007538476,0.0008427062,0.004086909,0.0015180765,0.008216658,0.001907173,0.0021025643,0.0027773224],"category_scores_gemma":[0.016337031,0.0004895693,0.0011060523,0.0028417732,0.012974961,0.013065841,0.0046515763,0.0029206479,0.00030436536],"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":[0.000023130453,0.000013229856,0.00030376134,0.0000637417,0.000015804677,0.00012808939,0.0012206621,0.0033712145,0.0001850656,0.9865151,0.00041019186,0.007750104],"study_design_scores_gemma":[0.0000075885555,0.000005596693,0.000111782065,0.000026529282,0.000007034509,0.000038576472,0.00032197856,0.0069708833,0.00009459347,0.9908153,0.0015929696,0.0000070671954],"about_ca_topic_score_codex":0.0031770018,"about_ca_topic_score_gemma":0.0016527522,"teacher_disagreement_score":0.008216658,"about_ca_system_score_codex":0.0028566753,"about_ca_system_score_gemma":0.001477796,"threshold_uncertainty_score":0.032137096},"labels":[],"label_agreement":null},{"id":"W2097476511","doi":"10.1109/3477.931512","title":"Neural network approaches to dynamic collision-free trajectory generation","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":187,"is_retracted":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; University of Guelph","funders":"","keywords":"Trajectory; Artificial neural network; Computer science; Workspace; Robot; Control theory (sociology); Collision; State space; Artificial intelligence; Mathematics; Control (management)","score_opus":0.07123373920932854,"score_gpt":0.24040196012512427,"score_spread":0.16916822091579573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097476511","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":[0.006599918,0.00080059987,0.9890961,0.0001561452,0.000036484726,0.000017649827,0.00001966387,0.00010838072,0.003165009],"genre_scores_gemma":[0.7667934,0.00235583,0.22109857,0.00016119471,0.00013910703,0.00034015957,0.00012971272,0.0001006749,0.008881357],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978346,0.00006426045,0.000011242232,0.000047715712,0.00006714173,0.000026331272],"domain_scores_gemma":[0.99954104,0.00027838812,0.000053358024,0.000026062298,0.00008546069,0.000015740012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005021503,0.00072553585,0.0005731461,0.00060257834,0.00044730416,0.00069585623,0.0013706349,0.0012549489,0.002053814],"category_scores_gemma":[0.0017353195,0.00046425776,0.00048156775,0.00079638074,0.0007908692,0.0013513126,0.000706978,0.0010056708,0.00031443377],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010624381,0.0000070368947,0.0000709602,0.000028121984,0.000012199479,0.000026345271,0.00002201427,0.97328305,0.00035366527,0.015844503,0.00014008579,0.0102012595],"study_design_scores_gemma":[0.0000017425576,0.000004227751,0.000012948533,0.0000021288981,0.0000018801746,0.000005685552,0.0000025434663,0.99422234,0.00012378853,0.005408434,0.00021206753,0.000002185611],"about_ca_topic_score_codex":0.005712631,"about_ca_topic_score_gemma":0.0034904047,"teacher_disagreement_score":0.005712631,"about_ca_system_score_codex":0.0011989207,"about_ca_system_score_gemma":0.00066106993,"threshold_uncertainty_score":0.011358738},"labels":[],"label_agreement":null},{"id":"W2097621701","doi":"10.1109/tsmcb.2007.913602","title":"A Solution to the Stochastic Point Location Problem in Metalevel Nonstationary Environments","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","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":"Carleton University","funders":"","keywords":"Oracle; Point (geometry); Computer science; Rendering (computer graphics); Learning automata; Discretization; Space (punctuation); Point location; Interval (graph theory); Automaton; Mathematical optimization; Theoretical computer science; Artificial intelligence; Mathematics; Combinatorics; Geometry; Mathematical analysis","score_opus":0.029084022566893915,"score_gpt":0.23439888387207194,"score_spread":0.20531486130517804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097621701","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":[0.011470649,0.00013614849,0.9844885,0.0006662922,0.000077961624,0.000026989903,0.00009903851,0.00019006664,0.002844364],"genre_scores_gemma":[0.49655426,0.00067919533,0.48463458,0.00057921093,0.0004019947,0.00029722895,0.00065704336,0.0002614338,0.01593514],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99869007,0.0003623777,0.00005789976,0.0003751214,0.000309184,0.00020537604],"domain_scores_gemma":[0.99591845,0.0025745363,0.00042394575,0.00036722334,0.00046162412,0.000254265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015783875,0.0008506252,0.0014342094,0.0006642716,0.0011316432,0.0013740859,0.0029922214,0.0034185636,0.004906509],"category_scores_gemma":[0.01051203,0.0007406496,0.0013694188,0.00087253464,0.0020544317,0.0026647612,0.0044892393,0.0030984918,0.0008246664],"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":[0.00019384218,0.000057115078,0.0012184683,0.00018224069,0.00007546168,0.00040584477,0.00033230826,0.68889874,0.0015049705,0.26787826,0.005762557,0.033490106],"study_design_scores_gemma":[0.00004015761,0.000054838827,0.00019480078,0.000019280737,0.000012929989,0.0000994465,0.000057323563,0.87167275,0.00043842636,0.124729946,0.0026542624,0.00002585459],"about_ca_topic_score_codex":0.0040239226,"about_ca_topic_score_gemma":0.002937205,"teacher_disagreement_score":0.004906509,"about_ca_system_score_codex":0.0010162687,"about_ca_system_score_gemma":0.0016317841,"threshold_uncertainty_score":0.016413867},"labels":[],"label_agreement":null},{"id":"W2097705935","doi":"10.1109/tsmcb.2005.862491","title":"Modeling emotional content of music using system identification","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Music and Audio Processing","field":"Computer Science","cited_by":90,"is_retracted":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":"Arousal; Valence (chemistry); Statistic; Ambiguity; Content (measure theory); Identification (biology); Computer science; Emotional valence; Emotion detection; Musical; Speech recognition; Psychology; Artificial intelligence; Pattern recognition (psychology); Cognitive psychology; Mathematics; Emotion recognition; Social psychology; Statistics; Cognition; Art","score_opus":0.056317447243700185,"score_gpt":0.23703171472770415,"score_spread":0.18071426748400396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097705935","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":[0.14906467,0.00017215255,0.8475429,0.00012553865,0.000028693103,0.00008370983,0.00008129344,0.00047210234,0.002428951],"genre_scores_gemma":[0.918844,0.0001928625,0.07919711,0.000027737406,0.000023043436,0.00011484157,0.00014117511,0.000029297962,0.0014299941],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968827,0.00011052343,0.000016238328,0.000078530415,0.00007860347,0.000027894725],"domain_scores_gemma":[0.99943703,0.00037233494,0.00005580408,0.000047325902,0.000078392404,0.000009137905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006379268,0.0004904965,0.00037203904,0.00043978193,0.00022653371,0.00063553243,0.0003483883,0.00043712623,0.0010417983],"category_scores_gemma":[0.0025810406,0.00022417429,0.00049692113,0.0003651534,0.0002457605,0.0008084787,0.00027564153,0.0005016056,0.00026055632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015481499,0.00014200038,0.010270311,0.00015003295,0.00020035196,0.00015538564,0.00048137884,0.81047636,0.03154671,0.011575397,0.0005312719,0.13431595],"study_design_scores_gemma":[0.000003784344,0.000040494695,0.0011499672,0.000003746292,0.000010856663,0.000021829443,0.000013008766,0.9951683,0.0014967829,0.0017754254,0.0003101514,0.000005665213],"about_ca_topic_score_codex":0.0017843762,"about_ca_topic_score_gemma":0.0012557236,"teacher_disagreement_score":0.0017843762,"about_ca_system_score_codex":0.0003713336,"about_ca_system_score_gemma":0.0003083522,"threshold_uncertainty_score":0.0035479665},"labels":[],"label_agreement":null},{"id":"W2098540440","doi":"10.1109/tsmcb.2010.2056367","title":"Enhanced Differential Evolution With Adaptive Strategies for Numerical Optimization","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":229,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Differential evolution; Benchmark (surveying); Computer science; Mathematical optimization; Scalability; Convergence (economics); Evolutionary algorithm; Optimization problem; Global optimization; Evolution strategy; Adaptive strategies; Adaptation (eye); Artificial intelligence; Algorithm; Mathematics","score_opus":0.017948645447076427,"score_gpt":0.2511247999847204,"score_spread":0.233176154537644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098540440","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":[0.0034981782,0.00058477937,0.99325126,0.00007864459,0.000046900594,0.00004326845,0.000010588274,0.000120516925,0.0023659489],"genre_scores_gemma":[0.2308707,0.0012553603,0.76392287,0.00015746713,0.000076406264,0.00043987308,0.000069126254,0.00008539283,0.0031228918],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993618,0.00023920432,0.00004190009,0.00006383677,0.0002677263,0.00002554154],"domain_scores_gemma":[0.99913067,0.0005287298,0.00007792776,0.00009259942,0.00014785185,0.000022326465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013534422,0.0009339147,0.0008265675,0.00072004576,0.00024942294,0.00070895423,0.0011070158,0.0010457345,0.0013625589],"category_scores_gemma":[0.0034710453,0.0003180414,0.00071743986,0.0009318406,0.00064096146,0.0007718186,0.0009911285,0.0012862313,0.00037998197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004150572,0.00005858081,0.0004269947,0.000175609,0.00007956914,0.00010876392,0.00007330392,0.86126876,0.0064439513,0.046646617,0.0009092612,0.08376703],"study_design_scores_gemma":[0.000011898363,0.000026236818,0.00005414963,0.00000907678,0.0000070735546,0.000024460976,0.0000024033484,0.9920994,0.0007431766,0.004530911,0.002485755,0.0000054714124],"about_ca_topic_score_codex":0.0009789887,"about_ca_topic_score_gemma":0.0009810303,"teacher_disagreement_score":0.0013625589,"about_ca_system_score_codex":0.00050920795,"about_ca_system_score_gemma":0.0004957977,"threshold_uncertainty_score":0.0071578026},"labels":[],"label_agreement":null},{"id":"W2098651198","doi":"10.1109/tsmcb.2004.826398","title":"Enhanced Sound Localization","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":133,"is_retracted":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; Reverberation; Acoustic source localization; Directivity; Acoustics; Orientation (vector space); Sound localization; Ranging; Microphone array; Computer science; Sound (geography); Noise-canceling microphone; Mathematics; Physics; Sound pressure; Telecommunications; Geometry","score_opus":0.016689888387789117,"score_gpt":0.23595521216203963,"score_spread":0.2192653237742505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098651198","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":[0.0014966697,0.00014079669,0.99699104,0.00002953903,0.000049383107,0.000015856405,0.000020593974,0.00048910826,0.00076698983],"genre_scores_gemma":[0.068169005,0.0005251678,0.924665,0.00014541208,0.000114736904,0.00009582349,0.00019097984,0.00019093542,0.0059029176],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990677,0.00013449912,0.00004472881,0.00021031547,0.00048013497,0.00006257104],"domain_scores_gemma":[0.99899644,0.00028204074,0.000112616086,0.00022712005,0.00035050232,0.00003131047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005907186,0.0010952271,0.0011485553,0.0013025054,0.00034318742,0.0013267341,0.0015178538,0.0012610658,0.004860011],"category_scores_gemma":[0.0025653949,0.00048484423,0.001024606,0.000967062,0.0006422422,0.0021394487,0.002147132,0.0010874657,0.0026527971],"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":[0.00024008684,0.000079429665,0.0007125073,0.0004537809,0.00011980296,0.00036966757,0.00014735987,0.06485381,0.11820011,0.02717871,0.0044980817,0.7831467],"study_design_scores_gemma":[0.00007740022,0.0003655948,0.00094210077,0.00007393635,0.00011021077,0.0020966951,0.00008478057,0.87123567,0.07306172,0.015634095,0.03621729,0.00010059832],"about_ca_topic_score_codex":0.0006818784,"about_ca_topic_score_gemma":0.000988791,"teacher_disagreement_score":0.004860011,"about_ca_system_score_codex":0.00037016175,"about_ca_system_score_gemma":0.000687453,"threshold_uncertainty_score":0.016258359},"labels":[],"label_agreement":null},{"id":"W2100286988","doi":"10.1109/tsmcb.2009.2038493","title":"Robust Classifiers for Data Reduced via Random Projections","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Sparse and Compressive Sensing 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":"University of British Columbia","funders":"","keywords":"Dimensionality reduction; Random projection; Curse of dimensionality; Pattern recognition (psychology); Random subspace method; Artificial intelligence; Classifier (UML); Subspace topology; Computer science; Robustness (evolution); k-nearest neighbors algorithm; Machine learning","score_opus":0.057345601118771676,"score_gpt":0.2547730542609776,"score_spread":0.19742745314220594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100286988","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":[0.0069825877,0.00042490396,0.99117553,0.00023535172,0.00004394775,0.000042819633,0.000064319494,0.00025755216,0.0007730166],"genre_scores_gemma":[0.32819855,0.0014372716,0.664224,0.0003219753,0.00038736095,0.0004334259,0.0007207707,0.0001221965,0.0041543934],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9964479,0.0009236968,0.00018472174,0.00065525837,0.0015911069,0.00019727314],"domain_scores_gemma":[0.99437153,0.0030818982,0.0006965482,0.00084419415,0.00091929286,0.000086533975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003447085,0.00086134166,0.0016215345,0.0014476031,0.0005954394,0.0016363895,0.0010403146,0.0013960047,0.0016839772],"category_scores_gemma":[0.016473705,0.000478917,0.0008726278,0.0012825314,0.0014203693,0.0024267328,0.0017710262,0.0019945048,0.00088877574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002732304,0.00007768866,0.0009123732,0.00023376787,0.000146317,0.00019288564,0.00019627388,0.4938033,0.011559632,0.12909222,0.0059596826,0.3575526],"study_design_scores_gemma":[0.000008354977,0.000038203292,0.00020142656,0.000013705211,0.000009852533,0.00005976749,0.000015406978,0.97079897,0.0023817804,0.024900828,0.0015580984,0.000013646443],"about_ca_topic_score_codex":0.001634731,"about_ca_topic_score_gemma":0.0011516173,"teacher_disagreement_score":0.003447085,"about_ca_system_score_codex":0.00091810786,"about_ca_system_score_gemma":0.0011563122,"threshold_uncertainty_score":0.01823014},"labels":[],"label_agreement":null},{"id":"W2101038569","doi":"10.1109/tsmcb.2007.911378","title":"Fixation Precision in High-Speed Noncontact Eye-Gaze Tracking","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":42,"is_retracted":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":"Gaze; Eye tracking; Fixation (population genetics); Computer vision; Artificial intelligence; Computer science; Tracking (education); Medicine; Psychology","score_opus":0.026057646484355823,"score_gpt":0.24637501475280496,"score_spread":0.22031736826844914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101038569","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":[0.37746358,0.0041543953,0.6144714,0.00014434685,0.00017197055,0.00015095714,0.0002373567,0.001002587,0.002203406],"genre_scores_gemma":[0.8542737,0.0014566031,0.14222266,0.000078665296,0.00007193923,0.00012544835,0.00022712316,0.00015388866,0.001389977],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972362,0.0007375558,0.00016430198,0.00049419544,0.0012522232,0.00011548475],"domain_scores_gemma":[0.99024755,0.0059451684,0.001041598,0.00085437065,0.001824065,0.00008715557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021610856,0.0006099014,0.00051988236,0.0010770233,0.00035805497,0.0009123611,0.0006508277,0.0008597837,0.0010797472],"category_scores_gemma":[0.013300319,0.00037722758,0.0003242086,0.0007513905,0.00037709143,0.0012338744,0.00074869016,0.00044096026,0.00035878294],"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":[0.0015086303,0.00010534233,0.017854176,0.0010555758,0.00016752332,0.00033019445,0.00074789324,0.0105713485,0.5838305,0.0013073401,0.00097508315,0.3815464],"study_design_scores_gemma":[0.00016224942,0.0031079142,0.26118514,0.00034063126,0.0004209405,0.0051593552,0.0004513311,0.120060734,0.59858966,0.002542388,0.007633989,0.00034566433],"about_ca_topic_score_codex":0.0023629665,"about_ca_topic_score_gemma":0.0026397954,"teacher_disagreement_score":0.0023629665,"about_ca_system_score_codex":0.00062442146,"about_ca_system_score_gemma":0.0004145727,"threshold_uncertainty_score":0.011429071},"labels":[],"label_agreement":null},{"id":"W2101249915","doi":"10.1109/tsmcb.2006.876163","title":"Customized Generalization of Support Patterns for Classification","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Data Mining Algorithms and Applications","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":"Western University","funders":"","keywords":"Generalization; Computer science; Artificial intelligence; Pattern recognition (psychology); Mathematics","score_opus":0.024899944962103012,"score_gpt":0.25060230510369846,"score_spread":0.22570236014159545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101249915","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":[0.025364406,0.00026924015,0.97085315,0.0003134711,0.000037526075,0.000113530084,0.0003574514,0.0017131508,0.000978022],"genre_scores_gemma":[0.42202657,0.00029011088,0.5721723,0.0004866215,0.00019057024,0.00057033973,0.0020974276,0.0002191238,0.0019469536],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99709785,0.00073161616,0.00019539752,0.0007686329,0.0010257066,0.00018079022],"domain_scores_gemma":[0.9904677,0.004797586,0.00077382417,0.0019880417,0.0017027543,0.00027005858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038236282,0.0011537127,0.0017634606,0.0031441613,0.00058118196,0.0013458194,0.0032297494,0.0016058153,0.0027621936],"category_scores_gemma":[0.016068144,0.00061364117,0.0014261778,0.0028957906,0.0009006728,0.0036558234,0.002435933,0.0028359648,0.0016972271],"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":[0.00035127424,0.000509039,0.014594305,0.0002812757,0.00024794883,0.00039073298,0.00025043343,0.10367685,0.006227886,0.012407147,0.010102372,0.8509607],"study_design_scores_gemma":[0.000041824303,0.00012703073,0.0008260519,0.000025392628,0.000026213022,0.00024024353,0.00003738274,0.96420527,0.0028930444,0.029220935,0.002335221,0.00002140169],"about_ca_topic_score_codex":0.00080890564,"about_ca_topic_score_gemma":0.0009243403,"teacher_disagreement_score":0.0038236282,"about_ca_system_score_codex":0.00044535656,"about_ca_system_score_gemma":0.00112656,"threshold_uncertainty_score":0.020221472},"labels":[],"label_agreement":null},{"id":"W2101251249","doi":"10.1109/tsmcb.2010.2098439","title":"On Random Transformations for Changeable Face Verification","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Biometric Identification and Security","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":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Biometrics; Random projection; Computer science; Template; Transformation (genetics); Domain (mathematical analysis); Multiplicative function; Face (sociological concept); Variety (cybernetics); Software deployment; Feature (linguistics); Theoretical computer science; Data mining; Artificial intelligence; Pattern recognition (psychology); Mathematics; Software engineering","score_opus":0.05089145960254462,"score_gpt":0.24380020693612783,"score_spread":0.1929087473335832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101251249","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":[0.0044012265,0.0004962898,0.99303424,0.00008779086,0.000026675047,0.00003137578,0.00001317875,0.00012585623,0.0017834038],"genre_scores_gemma":[0.42715207,0.0024660865,0.5635866,0.00025456902,0.00026051947,0.00024190907,0.0001514039,0.00018532552,0.0057015596],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99754685,0.000907149,0.00011674386,0.00034180135,0.0009760118,0.00011131472],"domain_scores_gemma":[0.9955159,0.0029165652,0.0003226886,0.00085808546,0.00033959033,0.000047161902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018077424,0.0006092155,0.0005729088,0.0010421586,0.00040638592,0.00090992637,0.00076404546,0.00079525384,0.002227052],"category_scores_gemma":[0.009588654,0.00031313216,0.00075085403,0.0008627767,0.0023159645,0.0020304923,0.0012301116,0.0013936092,0.0008384227],"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":[0.00027653962,0.00008191801,0.0006293113,0.00024450847,0.00006473133,0.00031980724,0.00030542805,0.18042156,0.03830051,0.4172313,0.0016437275,0.36048058],"study_design_scores_gemma":[0.000028463199,0.00018831778,0.0004107186,0.000056878514,0.00003106264,0.0007452912,0.00004919149,0.79330474,0.028950501,0.16535257,0.01082519,0.00005711202],"about_ca_topic_score_codex":0.0003893961,"about_ca_topic_score_gemma":0.00026037256,"teacher_disagreement_score":0.002227052,"about_ca_system_score_codex":0.0005529615,"about_ca_system_score_gemma":0.00045376644,"threshold_uncertainty_score":0.009560406},"labels":[],"label_agreement":null},{"id":"W2101344580","doi":"10.1109/tsmcb.2008.921002","title":"Real-Time Robot Path Planning via a Distance-Propagating Dynamic System with Obstacle Clearance","year":2008,"lang":"en","type":"letter","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":69,"is_retracted":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":"Offset (computer science); Motion planning; Robot; Obstacle; Computer science; Path (computing); Queue; Grid; Algorithm; Mathematical optimization; Real-time computing; Mathematics; Artificial intelligence; Geography","score_opus":0.014841814092926507,"score_gpt":0.21906228964306457,"score_spread":0.20422047555013806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101344580","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":[0.007870954,0.00005687897,0.99055016,0.00012072968,0.00001801663,0.000018070523,0.000015685006,0.00020930445,0.00114016],"genre_scores_gemma":[0.50986654,0.00020689439,0.48672524,0.000104059676,0.000021427673,0.00012305401,0.00008049111,0.000049507667,0.0028228615],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999813,0.000041495565,0.000011173174,0.000039550963,0.00007782029,0.000016961962],"domain_scores_gemma":[0.999629,0.00015750533,0.000057022404,0.00006308291,0.000063860054,0.000029438095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035686517,0.0003506784,0.0003932973,0.0002900953,0.0004096678,0.0005340378,0.0009617763,0.00051021995,0.0014039656],"category_scores_gemma":[0.0009377697,0.00026449646,0.0002008214,0.0006233046,0.0005073163,0.0006806886,0.00090929464,0.0007078723,0.00030699876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009407971,0.000027844144,0.00045182777,0.000060642295,0.000014544549,0.00012806927,0.00006203049,0.84869224,0.0077853594,0.027022403,0.0015404696,0.1141205],"study_design_scores_gemma":[0.000010269733,0.000017205834,0.000041868574,0.000002141563,0.0000016231452,0.000033777847,0.0000026880848,0.99707234,0.00056113023,0.001335384,0.00091792905,0.000003564178],"about_ca_topic_score_codex":0.00420884,"about_ca_topic_score_gemma":0.0036465188,"teacher_disagreement_score":0.00420884,"about_ca_system_score_codex":0.00073599356,"about_ca_system_score_gemma":0.0009839085,"threshold_uncertainty_score":0.008368671},"labels":[],"label_agreement":null},{"id":"W2101644100","doi":"10.1109/tsmcb.2009.2038357","title":"Comparative Analysis of 3-D Robot Teleoperation Interfaces With Novice Users","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":76,"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":"Canadian Institutes of Health Research","keywords":"Teleoperation; Modalities; Computer science; Human–computer interaction; Visualization; Robot; Metric (unit); Interface (matter); Telerobotics; User interface; Multimedia; Artificial intelligence; Mobile robot; Engineering","score_opus":0.015829194541217263,"score_gpt":0.2341311319243667,"score_spread":0.21830193738314943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101644100","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":[0.9955617,0.0001308102,0.0033071048,0.000015807087,0.0000054126576,0.000037879185,0.0000743979,0.000066184366,0.00080062624],"genre_scores_gemma":[0.99716175,0.00008823146,0.0018199225,0.000013293775,0.0000046141663,0.000045676243,0.00020129314,0.000016758046,0.00064858055],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9989851,0.0003286898,0.00015938116,0.00011522374,0.0002897219,0.0001219231],"domain_scores_gemma":[0.98634666,0.009394297,0.00052093697,0.0006637346,0.0022786502,0.0007957804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014404599,0.00050109235,0.0005006333,0.0010920194,0.00025826803,0.0007175458,0.00036115924,0.000603107,0.0022717274],"category_scores_gemma":[0.015420584,0.00013886039,0.0003971724,0.0003380595,0.00029714854,0.0006620933,0.0006596762,0.00022336908,0.0004542681],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011834006,0.0029624074,0.26178613,0.0020319573,0.00056583737,0.0016552497,0.022646932,0.014922423,0.18185298,0.00072560157,0.002752273,0.49626422],"study_design_scores_gemma":[0.00019519421,0.013372494,0.8979907,0.000097820506,0.00025936682,0.0029380724,0.010089088,0.028160209,0.043381035,0.00043527555,0.0028604346,0.00022024059],"about_ca_topic_score_codex":0.0006699041,"about_ca_topic_score_gemma":0.00079899566,"teacher_disagreement_score":0.0022717274,"about_ca_system_score_codex":0.00016836064,"about_ca_system_score_gemma":0.00013957298,"threshold_uncertainty_score":0.00761801},"labels":[],"label_agreement":null},{"id":"W2101745110","doi":"10.1109/3477.907575","title":"Kinematic control of redundant robots and the motion optimizability measure","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Mechanisms and Dynamics","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":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Kinematics; Measure (data warehouse); Inverse kinematics; Robot; Motion (physics); Control theory (sociology); Degrees of freedom (physics and chemistry); Computer science; Kinematic chain; Robot kinematics; Control engineering; Mathematics; Control (management); Artificial intelligence; Engineering; Classical mechanics; Physics; Mobile robot","score_opus":0.010735066346283937,"score_gpt":0.19260891355579696,"score_spread":0.18187384720951302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101745110","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":[0.03365825,0.0006392634,0.95903575,0.00018757263,0.000035667596,0.000022228402,0.00001620949,0.00012194799,0.006283076],"genre_scores_gemma":[0.929717,0.00062062126,0.06550493,0.00005547925,0.00010469668,0.00013649398,0.00006866124,0.00006880479,0.0037232924],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919266,0.00029143636,0.000038294285,0.00010793507,0.000304973,0.00006482113],"domain_scores_gemma":[0.99919885,0.0002932084,0.00025689547,0.00008153806,0.00013685902,0.00003259167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012581996,0.00077678845,0.00052806194,0.00075193594,0.00023586399,0.00081500557,0.000579078,0.0003977394,0.0013206908],"category_scores_gemma":[0.002727901,0.00026196867,0.00040203563,0.00045622195,0.0017075902,0.0012995809,0.0008796837,0.00068001624,0.00020424598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008518371,0.000043268337,0.00032440686,0.00007771117,0.000040030107,0.00010666818,0.00012740373,0.5158501,0.010571557,0.42001736,0.0005208405,0.052235477],"study_design_scores_gemma":[0.000030916195,0.00021011708,0.0004211027,0.000026201978,0.000010161688,0.000048546615,0.000035194917,0.72780025,0.0026088816,0.2670794,0.0017050683,0.000024227484],"about_ca_topic_score_codex":0.00067730783,"about_ca_topic_score_gemma":0.00035618487,"teacher_disagreement_score":0.0013206908,"about_ca_system_score_codex":0.0005667825,"about_ca_system_score_gemma":0.00038529056,"threshold_uncertainty_score":0.006654024},"labels":[],"label_agreement":null},{"id":"W2102391083","doi":"10.1109/tsmcb.2005.856724","title":"Analysis of a master-slave architecture for distributed evolutionary computations","year":2006,"lang":"en","type":"letter","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Evolutionary Algorithms and Applications","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":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Workstation; Computation; Architecture; Computer science; Mainstream; Distributed computing; Beagle; Master/slave; Parallel computing; Programming language; Operating system; Geography; Archaeology; Ecology; Biology","score_opus":0.018192874081714584,"score_gpt":0.23260940997893226,"score_spread":0.21441653589721768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102391083","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":[0.06059536,0.00043620417,0.9020472,0.0018767213,0.00013639053,0.00007387275,0.000046722977,0.00023039784,0.034557],"genre_scores_gemma":[0.9380302,0.00037605778,0.049900163,0.00026486287,0.000078920464,0.00014224948,0.000046031353,0.000099225115,0.011062355],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966395,0.000095979885,0.00000828889,0.000037268735,0.00015502938,0.000039416977],"domain_scores_gemma":[0.99954814,0.00021209402,0.00003071195,0.00008188128,0.00009590463,0.000031212883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062438933,0.0002260101,0.00044839,0.00026423836,0.00055779313,0.0009212646,0.0010213912,0.0010268096,0.0043741846],"category_scores_gemma":[0.002397065,0.00024624553,0.0003121917,0.00025221918,0.0009365135,0.0014138697,0.0007165478,0.0008844635,0.0005377931],"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":[0.000050299008,0.00002716219,0.00034753678,0.000047536432,0.000016042299,0.00023217351,0.00010853164,0.31137392,0.008002007,0.66821134,0.0023601826,0.009223343],"study_design_scores_gemma":[0.000008258869,0.000010384026,0.000061067505,0.0000033745575,0.0000017087568,0.00003951273,0.00000839368,0.9559726,0.00035707452,0.04183356,0.0017010006,0.0000030986712],"about_ca_topic_score_codex":0.0012295897,"about_ca_topic_score_gemma":0.0009386131,"teacher_disagreement_score":0.0043741846,"about_ca_system_score_codex":0.0010972264,"about_ca_system_score_gemma":0.0006314676,"threshold_uncertainty_score":0.0146330595},"labels":[],"label_agreement":null},{"id":"W2102753033","doi":"10.1109/tsmcb.2005.861862","title":"Inference in multiply sectioned Bayesian networks: methods and performance comparison","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Inference; Bayesian network; Computer science; Probabilistic logic; Artificial intelligence; Domain (mathematical analysis); Bayesian inference; Approximate inference; Machine learning; Bayesian probability; Algorithm; Theoretical computer science; Mathematics","score_opus":0.02599985738985396,"score_gpt":0.2902282019021529,"score_spread":0.264228344512299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102753033","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":[0.010950501,0.00056333764,0.9859913,0.00011723325,0.000035061305,0.00006601916,0.00005119627,0.0013759055,0.0008494102],"genre_scores_gemma":[0.17839071,0.00083576946,0.8188788,0.00006297282,0.00004946424,0.00017464014,0.00021697309,0.0003221336,0.001068394],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977483,0.0010085888,0.000119754666,0.00031972484,0.0007103351,0.00009328095],"domain_scores_gemma":[0.9881314,0.008883678,0.00044460816,0.0011176302,0.0011918745,0.00023084904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050933817,0.0009149074,0.0010154354,0.0014495372,0.00042241244,0.0011578916,0.001993297,0.001090297,0.003255854],"category_scores_gemma":[0.017466478,0.0005150317,0.0005522402,0.0011435252,0.0005276285,0.002202437,0.0014383427,0.0014560554,0.0007419077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080948503,0.00021645987,0.0032629562,0.00036070074,0.00032913228,0.000105019964,0.00020926306,0.50286984,0.00482134,0.026051011,0.0021476944,0.45881703],"study_design_scores_gemma":[0.000029249804,0.000042422267,0.00026326257,0.000013803091,0.000020688058,0.00004252,0.000014685077,0.99085873,0.0017013774,0.006289883,0.0007076233,0.000015789894],"about_ca_topic_score_codex":0.005012343,"about_ca_topic_score_gemma":0.005673377,"teacher_disagreement_score":0.0050933817,"about_ca_system_score_codex":0.0012336752,"about_ca_system_score_gemma":0.0015954685,"threshold_uncertainty_score":0.02693671},"labels":[],"label_agreement":null},{"id":"W2103535650","doi":"10.1109/tsmcb.2005.863371","title":"Rough–Fuzzy Collaborative Clustering","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":258,"is_retracted":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":"Cluster analysis; Data mining; Partition (number theory); Fuzzy clustering; Computer science; Fuzzy logic; Cluster (spacecraft); Measure (data warehouse); Consensus clustering; Artificial intelligence; Mathematics; CURE data clustering algorithm","score_opus":0.01446450397479102,"score_gpt":0.2229931761474985,"score_spread":0.20852867217270749,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103535650","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":[0.004914925,0.00034246355,0.9918046,0.00011234287,0.00004390223,0.00009264297,0.000053570053,0.00013677453,0.002498782],"genre_scores_gemma":[0.20346306,0.0006794886,0.79019976,0.00013672892,0.00016124346,0.0002676287,0.00055398664,0.00006603693,0.0044721],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99588335,0.0010541197,0.00025058,0.0009771605,0.0016531042,0.00018164396],"domain_scores_gemma":[0.9970566,0.00084690895,0.00029547466,0.00083731953,0.0008522019,0.00011142588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035573146,0.0010690301,0.0020348567,0.0029612319,0.0014236626,0.0025213545,0.0026942627,0.0016605471,0.0022938205],"category_scores_gemma":[0.008274814,0.0006184369,0.0017674371,0.002452258,0.0012637362,0.0023219658,0.00212801,0.0011184935,0.0015305715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017244325,0.00017604306,0.0020823085,0.0006375775,0.00057309016,0.00033220262,0.00073586556,0.433554,0.00904761,0.16593045,0.0074672564,0.37929118],"study_design_scores_gemma":[0.000025905656,0.00009207383,0.00079854496,0.00004595767,0.00008640623,0.00021229421,0.00012427519,0.89306074,0.0038162775,0.087746374,0.013917697,0.000073516385],"about_ca_topic_score_codex":0.0026922545,"about_ca_topic_score_gemma":0.002588254,"teacher_disagreement_score":0.0035573146,"about_ca_system_score_codex":0.0011705289,"about_ca_system_score_gemma":0.0014336264,"threshold_uncertainty_score":0.018813074},"labels":[],"label_agreement":null},{"id":"W2103717630","doi":"10.1109/tsmcb.2009.2038895","title":"An Object-Based Visual Attention Model for Robotic Applications","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":68,"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":"Artificial intelligence; Gestalt psychology; Computer science; Coding (social sciences); Object (grammar); Computer vision; Perception; Cognitive neuroscience of visual object recognition; Pattern recognition (psychology); Visual processing; Top-down and bottom-up design; Psychology; Mathematics","score_opus":0.021030091536718053,"score_gpt":0.2822144131704359,"score_spread":0.26118432163371785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103717630","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":[0.01566438,0.0013040291,0.96955127,0.00047591492,0.00012768108,0.000057605124,0.00010207232,0.00073376944,0.01198337],"genre_scores_gemma":[0.77771664,0.0018033601,0.1968377,0.0004260511,0.00023896257,0.0003305908,0.0002955035,0.00017313634,0.02217811],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998048,0.000027146563,0.000008644104,0.00006741567,0.00006223785,0.000029725434],"domain_scores_gemma":[0.9998604,0.000039799084,0.000016853824,0.000021246795,0.000045512355,0.000016214843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031928884,0.00062924536,0.00049029087,0.0004869853,0.00033536612,0.00083017955,0.001948074,0.0008495399,0.0035200869],"category_scores_gemma":[0.00064985646,0.00025396165,0.00085100025,0.0003937784,0.00047426327,0.0014701834,0.00086624635,0.00068432913,0.00076615805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018413,0.00012082902,0.0011104036,0.0003520373,0.00015851692,0.0004422902,0.00033237712,0.45977274,0.034335744,0.3096833,0.0073470133,0.18616065],"study_design_scores_gemma":[0.00001259037,0.00006007298,0.00044963928,0.000009365956,0.000024641817,0.00007797528,0.000013516039,0.9476674,0.0010795315,0.04651981,0.0040720566,0.000013421822],"about_ca_topic_score_codex":0.0054639135,"about_ca_topic_score_gemma":0.0032593748,"teacher_disagreement_score":0.0054639135,"about_ca_system_score_codex":0.0009475157,"about_ca_system_score_gemma":0.00059810217,"threshold_uncertainty_score":0.011775911},"labels":[],"label_agreement":null},{"id":"W2104804909","doi":"10.1109/tsmcb.2008.924587","title":"Uncertainty Modeling of Improved Fuzzy Functions With Evolutionary Systems","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Fuzzy logic; Robustness (evolution); Artificial intelligence; Computer science; Generalization; Fuzzy control system; Machine learning; Data mining; Mathematics","score_opus":0.020104206148593744,"score_gpt":0.2005195084522612,"score_spread":0.18041530230366748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104804909","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":[0.013183174,0.00013829595,0.9851892,0.00005115409,0.000017963574,0.000011520064,0.000011870706,0.00005233213,0.001344558],"genre_scores_gemma":[0.7033994,0.00039210616,0.2932883,0.00006176722,0.000048849317,0.000102746904,0.00006330464,0.000035917077,0.0026076],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967813,0.00012045706,0.000018444029,0.00004982995,0.000112610964,0.000020557562],"domain_scores_gemma":[0.99967945,0.00016171983,0.00004442476,0.000033450717,0.00007233076,0.0000085650445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009266744,0.000589493,0.0005209687,0.00056346797,0.00032371044,0.0007043499,0.0008203783,0.000863591,0.0009038751],"category_scores_gemma":[0.0022267194,0.00022533855,0.00066344655,0.00045924596,0.00037744376,0.0011959563,0.0005600738,0.0006687632,0.00016067998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021274858,0.000011955175,0.00026150048,0.00002343428,0.000019474503,0.000051563606,0.000052182917,0.9401342,0.0014547409,0.028989917,0.0001597373,0.028820021],"study_design_scores_gemma":[0.0000018013592,0.00000876713,0.000047135116,0.000003048025,0.0000023222299,0.000010108743,0.0000021377803,0.99569845,0.00028589534,0.0035996796,0.00033763394,0.0000029986497],"about_ca_topic_score_codex":0.0024468468,"about_ca_topic_score_gemma":0.0013231505,"teacher_disagreement_score":0.0024468468,"about_ca_system_score_codex":0.00051767397,"about_ca_system_score_gemma":0.00032779266,"threshold_uncertainty_score":0.0049007535},"labels":[],"label_agreement":null},{"id":"W2104971205","doi":"10.1109/tsmcb.2005.861860","title":"On optimizing syntactic pattern recognition using tries and AI-based heuristic-search strategies","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Algorithms and Data Compression","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":"Carleton University","funders":"","keywords":"Trie; Benchmark (surveying); Beam search; Heuristic; A priori and a posteriori; String (physics); String searching algorithm; Algorithm; Computer science; Search tree; Matching (statistics); Search algorithm; Levenshtein distance; Tree (set theory); Mathematics; Combinatorics; Artificial intelligence; Pattern matching; Data structure; Statistics","score_opus":0.03161134660042626,"score_gpt":0.25953851493120134,"score_spread":0.2279271683307751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104971205","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":[0.03490215,0.00054842955,0.95902294,0.00017799817,0.000032017324,0.0000939551,0.000052167423,0.001007638,0.004162749],"genre_scores_gemma":[0.26608932,0.00047826327,0.72954035,0.00026816537,0.000046554513,0.00033023162,0.00023747885,0.0002406575,0.0027689578],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923396,0.00029183726,0.000058050082,0.00011901498,0.00022320097,0.0000739207],"domain_scores_gemma":[0.99805295,0.0013642864,0.00015036152,0.00015706051,0.00023607344,0.000039258317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013949244,0.0010417025,0.0011150052,0.0011909764,0.00032449185,0.0011031628,0.0013935334,0.0011357745,0.0025015634],"category_scores_gemma":[0.0044292314,0.0005283426,0.00061231264,0.0014764891,0.0010531618,0.001633152,0.0009680137,0.0006515203,0.0007960474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022268706,0.00009646429,0.0013975281,0.00026144978,0.000110697525,0.000111198526,0.00015601565,0.7421343,0.004874746,0.025961714,0.0015268968,0.22314623],"study_design_scores_gemma":[0.00002416831,0.00007799119,0.00012856378,0.000016322963,0.000017121823,0.00004478837,0.000037004906,0.9909018,0.0012885439,0.00665529,0.0008014635,0.0000069223825],"about_ca_topic_score_codex":0.0028246455,"about_ca_topic_score_gemma":0.0035040877,"teacher_disagreement_score":0.0028246455,"about_ca_system_score_codex":0.0006213537,"about_ca_system_score_gemma":0.001403201,"threshold_uncertainty_score":0.008368611},"labels":[],"label_agreement":null},{"id":"W2105439786","doi":"10.1109/tsmcb.2009.2032528","title":"Solving Multiconstraint Assignment Problems Using Learning Automata","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":42,"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":"Universitetet i Oslo","keywords":"Set (abstract data type); Computer science; Class (philosophy); Theoretical computer science; Constraint (computer-aided design); Automaton; Artificial intelligence; Algorithm; Information retrieval; Mathematics; Programming language","score_opus":0.03392984717873745,"score_gpt":0.25925422343491816,"score_spread":0.2253243762561807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105439786","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":[0.025147267,0.0002463828,0.97166294,0.00029199896,0.0000401911,0.00007925959,0.00005229953,0.00060236274,0.0018771571],"genre_scores_gemma":[0.5711128,0.00038037924,0.42396474,0.00023800835,0.00008730007,0.00039531628,0.00033744544,0.00014776387,0.0033363167],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986663,0.00040088096,0.00011463005,0.00045092657,0.00020178805,0.00016549222],"domain_scores_gemma":[0.9948548,0.004085327,0.00028669866,0.00034728704,0.0002789335,0.00014697433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014909245,0.0012251355,0.001427186,0.0008090317,0.0010125244,0.0016287062,0.002383002,0.002049378,0.0024818256],"category_scores_gemma":[0.0063094804,0.0007109102,0.0014470911,0.0010506394,0.0016168846,0.0024971804,0.0020847516,0.0023008764,0.00035752938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004689724,0.000077017416,0.00082276535,0.00010544827,0.00004899275,0.00006647654,0.00013440955,0.9335958,0.00087346736,0.019687587,0.0005153248,0.04402575],"study_design_scores_gemma":[0.000010364343,0.000018440423,0.000044220546,0.00000556321,0.0000064227556,0.000013484022,0.000020653537,0.98326206,0.0004258608,0.0157747,0.0004130867,0.0000051211555],"about_ca_topic_score_codex":0.0071313344,"about_ca_topic_score_gemma":0.007159012,"teacher_disagreement_score":0.0071313344,"about_ca_system_score_codex":0.0014215478,"about_ca_system_score_gemma":0.0020599714,"threshold_uncertainty_score":0.014179647},"labels":[],"label_agreement":null},{"id":"W2106445620","doi":"10.1109/3477.875444","title":"Supervisory control of multiworkcell manufacturing systems with shared resources","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Petri Nets in System Modeling","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Workcell; Flexibility (engineering); Automaton; Computer science; Deadlock; Distributed computing; Variety (cybernetics); Set (abstract data type); Supervisory control; Control (management); Robot; Theoretical computer science; Programming language; Artificial intelligence; Mathematics","score_opus":0.021051744832355442,"score_gpt":0.20793018508481634,"score_spread":0.1868784402524609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106445620","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":[0.1553547,0.00023388899,0.83977515,0.00012426087,0.00007675088,0.00006919616,0.000039701805,0.0007987762,0.003527574],"genre_scores_gemma":[0.9830456,0.000042928135,0.01627161,0.000012891663,0.0000100442985,0.00006231929,0.000014541491,0.000008622847,0.0005315033],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963427,0.000083575615,0.000023931165,0.00010548195,0.0001023285,0.00005031334],"domain_scores_gemma":[0.99920803,0.00040435532,0.00017057927,0.00006344099,0.000108053624,0.000045560464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006039324,0.00039775154,0.00038947613,0.0002272348,0.0003924763,0.0008298663,0.00074436975,0.00031742436,0.00093952386],"category_scores_gemma":[0.0009968213,0.0001892511,0.000312744,0.00014886743,0.0007867526,0.00045697516,0.0007090508,0.0005217484,0.000084595704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025544275,0.00012008152,0.001040851,0.00016653807,0.000057511217,0.0003515245,0.000514656,0.8607775,0.036481574,0.036172476,0.0006055762,0.063456304],"study_design_scores_gemma":[0.000035209247,0.00009356988,0.00018783378,0.000006768064,0.000011183335,0.000021011592,0.000025241072,0.98629993,0.006148741,0.00650735,0.0006566878,0.000006555386],"about_ca_topic_score_codex":0.0016863139,"about_ca_topic_score_gemma":0.0022794716,"teacher_disagreement_score":0.0016863139,"about_ca_system_score_codex":0.0004415285,"about_ca_system_score_gemma":0.00073933904,"threshold_uncertainty_score":0.0033530593},"labels":[],"label_agreement":null},{"id":"W2108064091","doi":"10.1109/tsmcb.2006.890293","title":"Desynchronizing a Chaotic Pattern Recognition Neural Network to Model Inaccurate Perception","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Chaotic; Computer science; Rendering (computer graphics); Artificial intelligence; Perception; Lyapunov exponent; Noise (video); Artificial neural network; Image (mathematics); Computer vision; Psychology","score_opus":0.03841195354700823,"score_gpt":0.25524168044264706,"score_spread":0.21682972689563884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108064091","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":[0.29844794,0.0005165637,0.6872099,0.000714675,0.00013138933,0.000062828934,0.00010664369,0.0003335407,0.012476393],"genre_scores_gemma":[0.97805756,0.00017437736,0.01816012,0.000053546326,0.00002474759,0.000051645886,0.000034334284,0.000023580353,0.0034201345],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998627,0.000038289094,0.00000783755,0.000038514252,0.00003479469,0.00001783494],"domain_scores_gemma":[0.9996964,0.00012544477,0.00007796542,0.000036319267,0.000049926137,0.000014043005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034288756,0.00038538701,0.00028209566,0.0002477461,0.0001795706,0.00043797775,0.00062432303,0.00056114787,0.0012482282],"category_scores_gemma":[0.0013841465,0.00019773818,0.00037666626,0.00020950701,0.0005073371,0.00060635706,0.00058141246,0.00072555663,0.00013835207],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046364927,0.000022737315,0.0006148248,0.000026904636,0.000022576363,0.00009248861,0.00008370916,0.9699402,0.00608546,0.0162713,0.00021237909,0.006581131],"study_design_scores_gemma":[0.0000015412503,0.000007174342,0.00006157542,8.0813936e-7,0.000001405254,0.000005514999,0.0000015470213,0.99861515,0.0001232691,0.0011041522,0.000076632794,0.0000011749032],"about_ca_topic_score_codex":0.004459054,"about_ca_topic_score_gemma":0.00289929,"teacher_disagreement_score":0.004459054,"about_ca_system_score_codex":0.000658678,"about_ca_system_score_gemma":0.00036337748,"threshold_uncertainty_score":0.008866191},"labels":[],"label_agreement":null},{"id":"W2108346947","doi":"10.1109/tsmcb.2002.999814","title":"Dynamic page based crossover in linear genetic programming","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Crossover; Genetic programming; Pairwise comparison; Generalization; Computer science; Population; Linear programming; Tree (set theory); Block (permutation group theory); Constant (computer programming); Algorithm; Combinatorics; Mathematics; Artificial intelligence; Programming language; Medicine","score_opus":0.017164744051282526,"score_gpt":0.2353421798431268,"score_spread":0.2181774357918443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108346947","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":[0.02049441,0.0007364465,0.9719507,0.00022368947,0.000075055104,0.000048053083,0.00003216384,0.00048629238,0.005953161],"genre_scores_gemma":[0.6390866,0.001256305,0.34414613,0.00034720806,0.0001591324,0.00041960547,0.00021977337,0.00026193625,0.014103364],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992803,0.00033335583,0.000025615782,0.00010629077,0.00019674299,0.00005771653],"domain_scores_gemma":[0.99901116,0.0006992215,0.00007000402,0.00007975664,0.00010401136,0.00003581827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011022699,0.00048398678,0.00082879834,0.0006374035,0.0003615892,0.0010771577,0.0010164164,0.0012189309,0.002154443],"category_scores_gemma":[0.0040996196,0.0003797864,0.0005236519,0.0013824609,0.0011564002,0.0012952781,0.0008543236,0.001208773,0.0005799261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096220974,0.00006609028,0.0004942063,0.00009668568,0.000045085995,0.0001761097,0.00014533354,0.7729333,0.0026795634,0.10548008,0.002035399,0.11575189],"study_design_scores_gemma":[0.000032555043,0.00007464571,0.00015314159,0.000016365959,0.000020911171,0.00007467077,0.000010870311,0.93983656,0.0011335997,0.05609564,0.0025326032,0.000018498622],"about_ca_topic_score_codex":0.0015497347,"about_ca_topic_score_gemma":0.0010842945,"teacher_disagreement_score":0.002154443,"about_ca_system_score_codex":0.0009346321,"about_ca_system_score_gemma":0.00056556077,"threshold_uncertainty_score":0.007207334},"labels":[],"label_agreement":null},{"id":"W2108540055","doi":"10.1109/3477.931507","title":"Continuous and discretized pursuit learning schemes: various algorithms and their comparison","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":140,"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); Carleton University","funders":"Indian Institute of Science","keywords":"Learning automata; Discretization; Computer science; Action (physics); Algorithm; Artificial intelligence; Automaton; Reinforcement learning; Class (philosophy); Machine learning; Mathematics","score_opus":0.022965798842747593,"score_gpt":0.25349352982921325,"score_spread":0.23052773098646565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108540055","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":[0.016125366,0.003463638,0.9741823,0.0003718153,0.000105898456,0.00007653921,0.000049971106,0.00031468883,0.005309787],"genre_scores_gemma":[0.44622025,0.0042960052,0.5445971,0.00022857926,0.00025050517,0.00031512935,0.00017010908,0.00014005901,0.003782306],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99797136,0.00067094195,0.0001704039,0.0002738887,0.00080698525,0.00010647375],"domain_scores_gemma":[0.9941103,0.0037892219,0.00040505032,0.00077711866,0.0006941427,0.00022419501],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027455194,0.0006506959,0.00095619546,0.0014241223,0.00046414422,0.0020922448,0.0019575283,0.0019866289,0.0024223272],"category_scores_gemma":[0.01335633,0.00034551116,0.0006156552,0.0017383322,0.0021797877,0.0035241968,0.0021660507,0.0018152783,0.00045279125],"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":[0.00043307513,0.00016221835,0.0014762714,0.00044890674,0.00009502671,0.00004356407,0.00022101327,0.31317243,0.0025016216,0.2911112,0.0018324672,0.3885022],"study_design_scores_gemma":[0.00007669522,0.00026421784,0.00042314205,0.00006706479,0.000021861159,0.000104967985,0.00005323533,0.934468,0.0016189273,0.059694383,0.0031727287,0.000034733683],"about_ca_topic_score_codex":0.0014109947,"about_ca_topic_score_gemma":0.0007697663,"teacher_disagreement_score":0.0027455194,"about_ca_system_score_codex":0.0014938285,"about_ca_system_score_gemma":0.0009679556,"threshold_uncertainty_score":0.01451987},"labels":[],"label_agreement":null},{"id":"W2109470906","doi":"10.1109/3477.979968","title":"Robust damping control of mobile manipulators","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":54,"is_retracted":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":"Control theory (sociology); Mobile manipulator; Kinematics; Controller (irrigation); Robust control; Control engineering; Bounded function; Computer science; Motion control; Stability (learning theory); Mobile robot; Manipulator (device); Control (management); Control system; Engineering; Robot; Mathematics; Artificial intelligence; Physics","score_opus":0.018295348739912246,"score_gpt":0.19032520813862697,"score_spread":0.17202985939871474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109470906","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":[0.018646913,0.0010868167,0.97541136,0.00012145532,0.00009372014,0.000026590986,0.000014996995,0.0006655854,0.003932538],"genre_scores_gemma":[0.90173364,0.0008453663,0.09290437,0.000076719414,0.00013474836,0.00013580792,0.000060587114,0.00006179116,0.004047005],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998041,0.00003277041,0.000009053548,0.000047082678,0.00008387457,0.000023076618],"domain_scores_gemma":[0.9998511,0.000040589017,0.00004707214,0.000015608486,0.00003609669,0.000009520253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024382773,0.0007086631,0.00043668645,0.00030312192,0.00022817076,0.00044999566,0.0005505877,0.00044660774,0.0011913457],"category_scores_gemma":[0.0006099008,0.00021289506,0.00027612023,0.00013767288,0.00043304163,0.00033231676,0.00061861024,0.0005007135,0.00038795714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024856938,0.00005724425,0.00031779945,0.0005019183,0.00008314823,0.00048242803,0.00028153186,0.37705466,0.30226576,0.04774092,0.0027239283,0.26824212],"study_design_scores_gemma":[0.00006809933,0.00034993092,0.00030108046,0.00002546286,0.000017001583,0.0001599438,0.000017766975,0.9721237,0.010644602,0.0065032635,0.009769731,0.000019496074],"about_ca_topic_score_codex":0.00060799974,"about_ca_topic_score_gemma":0.00047910446,"teacher_disagreement_score":0.0011913457,"about_ca_system_score_codex":0.00017758402,"about_ca_system_score_gemma":0.00019162982,"threshold_uncertainty_score":0.0039854646},"labels":[],"label_agreement":null},{"id":"W2110183025","doi":"10.1109/tsmcb.2009.2024166","title":"Selecting Discrete and Continuous Features Based on Neighborhood Decision Error Minimization","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":263,"is_retracted":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":"Feature selection; Decision boundary; Feature (linguistics); Pattern recognition (psychology); Linear subspace; Categorical variable; Artificial intelligence; Mathematics; Greedy algorithm; Boundary (topology); Computer science; Data mining; Machine learning; Algorithm; Support vector machine","score_opus":0.012769416375401525,"score_gpt":0.23766335809324288,"score_spread":0.22489394171784136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110183025","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":[0.045749538,0.0001601164,0.95344734,0.000056898625,0.000015333493,0.00005289039,0.000026203224,0.0001444397,0.0003472893],"genre_scores_gemma":[0.4800417,0.00015518969,0.51868045,0.000054528053,0.000038436105,0.000170984,0.00016636042,0.000047833408,0.0006443951],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986755,0.0003471557,0.00011318611,0.00023738372,0.0005524324,0.00007430001],"domain_scores_gemma":[0.9977291,0.0014340704,0.00018169155,0.00017544655,0.00041836043,0.00006128637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020910415,0.00050757366,0.0019412596,0.0014069115,0.0003231779,0.00085060095,0.0008378233,0.0006223479,0.0005195222],"category_scores_gemma":[0.006719634,0.00028060665,0.00064478745,0.00091666257,0.0005511128,0.0010993634,0.00064101734,0.00048266636,0.0001672078],"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":[0.00053260766,0.00019636941,0.005912098,0.00022910927,0.0001608013,0.00023518248,0.00015481196,0.25860494,0.026486218,0.011808335,0.0019572503,0.6937223],"study_design_scores_gemma":[0.000024799421,0.000084877654,0.0012375717,0.000009855304,0.000024950177,0.00008229371,0.000021994361,0.9885593,0.005055118,0.0043933094,0.0004902495,0.000015589765],"about_ca_topic_score_codex":0.0010475018,"about_ca_topic_score_gemma":0.0008256237,"teacher_disagreement_score":0.0020910415,"about_ca_system_score_codex":0.00038743808,"about_ca_system_score_gemma":0.000549148,"threshold_uncertainty_score":0.011058569},"labels":[],"label_agreement":null},{"id":"W2111377750","doi":"10.1109/tsmcb.2003.810949","title":"A width-invariant property of curves based on wavelet transform with a novel wavelet function","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Image and Signal Denoising Methods","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":"Wavelet; Wavelet transform; Stationary wavelet transform; Harmonic wavelet transform; Mathematics; Discrete wavelet transform; Second-generation wavelet transform; Invariant (physics); Continuous wavelet transform; Function (biology); Property (philosophy); Characterization (materials science); Orthogonal wavelet; Mathematical analysis; Algorithm; Artificial intelligence; Computer science; Physics; Optics","score_opus":0.024017926522631967,"score_gpt":0.22806829489417446,"score_spread":0.2040503683715425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111377750","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":[0.03429236,0.00056400074,0.9613885,0.00013440804,0.000114765695,0.000027120048,0.00006925056,0.00020343025,0.003206106],"genre_scores_gemma":[0.4643558,0.002427806,0.5262355,0.00019841875,0.00060335494,0.000094324925,0.00031836593,0.00039358184,0.0053727557],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996093,0.000048053975,0.000036052395,0.000107484855,0.0001715025,0.000027568693],"domain_scores_gemma":[0.99909437,0.00023903222,0.00017804003,0.00021721645,0.000203149,0.0000680967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005053443,0.0006094757,0.00054888293,0.0013257419,0.00026909506,0.0010748657,0.00057350897,0.0007466496,0.0010637996],"category_scores_gemma":[0.0023482107,0.00026081307,0.000624201,0.0013525635,0.0013007333,0.0031495222,0.00080615544,0.0012664264,0.0005726702],"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":[0.00028260384,0.00007886481,0.0015919808,0.00038795065,0.000062413565,0.00040255458,0.00035111903,0.018047478,0.3536282,0.26729956,0.0018269861,0.35604027],"study_design_scores_gemma":[0.00006242986,0.0008911655,0.0058054756,0.00010311347,0.00013602478,0.004627031,0.00022394466,0.52781415,0.24610117,0.17113695,0.042929377,0.00016911938],"about_ca_topic_score_codex":0.00016175666,"about_ca_topic_score_gemma":0.00011619369,"teacher_disagreement_score":0.0013257419,"about_ca_system_score_codex":0.00021315362,"about_ca_system_score_gemma":0.0002339292,"threshold_uncertainty_score":0.003558755},"labels":[],"label_agreement":null},{"id":"W2111966567","doi":"10.1109/tsmcb.2009.2037511","title":"A Probabilistic Model of Overt Visual Attention for Cognitive Robots","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland; University of Waterloo","funders":"","keywords":"Covert; Computer science; Artificial intelligence; Gaze-contingency paradigm; Eye movement; Computer vision; Robot; Visual field; Cognition; Visual attention; Probabilistic logic; Particle filter; Focus (optics); Visual search; Visual perception; Psychology; Perception; Filter (signal processing); Neuroscience","score_opus":0.0268905056180335,"score_gpt":0.2766845054299137,"score_spread":0.2497939998118802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111966567","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":[0.023255022,0.00033950017,0.97227365,0.0005612988,0.000050008082,0.000034493612,0.000082565995,0.00024186537,0.0031616436],"genre_scores_gemma":[0.88751715,0.0007140461,0.10224956,0.00024807398,0.00019222927,0.00021521718,0.0001362261,0.00006854348,0.008658931],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994929,0.0001254715,0.000017586424,0.00014866529,0.00013417438,0.000081197984],"domain_scores_gemma":[0.9986273,0.00081574195,0.00017829501,0.000097667245,0.0002159002,0.0000650305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092916144,0.00055790663,0.00077684794,0.0006232398,0.00044799031,0.0010587197,0.0018895133,0.0015271615,0.0021866988],"category_scores_gemma":[0.004338022,0.000634419,0.00088085927,0.00057790114,0.0010810482,0.0019131035,0.0008560267,0.0012931266,0.00047326207],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022747747,0.0001183398,0.0019526702,0.00016581676,0.00008995994,0.0002892166,0.00052449777,0.74226207,0.008025475,0.18319693,0.0027287079,0.060418848],"study_design_scores_gemma":[0.000019100122,0.00003930668,0.00061038404,0.000006597987,0.000014021377,0.00004736789,0.000012442312,0.9741366,0.00023184362,0.02439726,0.00046990195,0.0000151323675],"about_ca_topic_score_codex":0.013100707,"about_ca_topic_score_gemma":0.009332999,"teacher_disagreement_score":0.013100707,"about_ca_system_score_codex":0.0014321179,"about_ca_system_score_gemma":0.0010460991,"threshold_uncertainty_score":0.026048899},"labels":[],"label_agreement":null},{"id":"W2112289227","doi":"10.1109/tsmcb.2009.2020213","title":"A Multifaceted Perspective at Data Analysis: A Study in Collaborative Intelligent Agents $^{\\ast}$","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Perspective (graphical); Computer science; Data science; Psychology; Artificial intelligence","score_opus":0.04637901439065827,"score_gpt":0.3147114452960959,"score_spread":0.2683324309054376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112289227","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":[0.014826929,0.010025211,0.94347066,0.018263537,0.00014995711,0.00010911922,0.00004674314,0.00009810877,0.01300974],"genre_scores_gemma":[0.2606975,0.0057172207,0.7289037,0.0014160429,0.00047776345,0.00033822263,0.000064968415,0.00009043537,0.0022940477],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97643584,0.016100436,0.0010942483,0.0027071878,0.0031586727,0.00050360383],"domain_scores_gemma":[0.9494832,0.043214228,0.001820155,0.0029522006,0.0016294973,0.0009007267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024404895,0.000975073,0.0013554881,0.004996416,0.0038464826,0.011696945,0.0035598474,0.006213776,0.0014919377],"category_scores_gemma":[0.034960434,0.0009131982,0.0021739646,0.006092302,0.020679133,0.0154632125,0.0053738044,0.0054695704,0.00034709985],"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":[0.00001755004,0.000047023175,0.0009100493,0.0002274427,0.000065230444,0.00022467568,0.00555175,0.008287836,0.00047978573,0.9590607,0.000776852,0.024351101],"study_design_scores_gemma":[0.000021344154,0.00006390281,0.0007603507,0.00023745056,0.000045509103,0.00030052112,0.002196481,0.083916165,0.0006527382,0.8904008,0.021347623,0.000057038273],"about_ca_topic_score_codex":0.004843134,"about_ca_topic_score_gemma":0.0031517672,"teacher_disagreement_score":0.024404895,"about_ca_system_score_codex":0.004309525,"about_ca_system_score_gemma":0.0027932276,"threshold_uncertainty_score":0.129067},"labels":[],"label_agreement":null},{"id":"W2112468437","doi":"10.1109/tsmcb.2003.818534","title":"Formulation of Radiometric Feasibility Measures for Feature Selection and Planning in Visual Servoing","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Advanced Vision and Imaging","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":"Toronto Metropolitan University","funders":"University of Waterloo","keywords":"Visual servoing; Robustness (evolution); Artificial intelligence; Computer science; Feature (linguistics); Computer vision; Context (archaeology); Radiometric dating; Selection (genetic algorithm); Feature selection; Image (mathematics); Pattern recognition (psychology); Remote sensing; Geography","score_opus":0.03160695501582079,"score_gpt":0.3015046772836494,"score_spread":0.2698977222678286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112468437","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":[0.002634057,0.00028865784,0.9957766,0.00011021798,0.000027436472,0.00005730557,0.0000348877,0.00004346667,0.001027393],"genre_scores_gemma":[0.23499495,0.0008315607,0.7604456,0.00016991222,0.00029594667,0.0010914814,0.00024421365,0.00014582329,0.0017805733],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99590164,0.0017530457,0.00039311996,0.00053709943,0.0012050426,0.00021015342],"domain_scores_gemma":[0.9869468,0.0077911345,0.0021428657,0.0004374104,0.002318698,0.0003631347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00806179,0.0017914524,0.0015959031,0.0032761605,0.00048796923,0.0029916484,0.001985408,0.0018151633,0.0018243341],"category_scores_gemma":[0.022374475,0.00070880156,0.0009904612,0.0019233805,0.0022457712,0.0037819564,0.0021292586,0.0020425958,0.00042336382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014023672,0.00012229377,0.00083150686,0.00063283526,0.00008501837,0.00025917173,0.00023124875,0.50318915,0.0063721044,0.3831066,0.002132509,0.102897316],"study_design_scores_gemma":[0.00001892685,0.0002509598,0.0003962164,0.00010642146,0.000021619699,0.000098801065,0.000047201815,0.9118647,0.0026906368,0.08209923,0.0023521176,0.000053118732],"about_ca_topic_score_codex":0.0009123946,"about_ca_topic_score_gemma":0.00067582127,"teacher_disagreement_score":0.00806179,"about_ca_system_score_codex":0.0018174034,"about_ca_system_score_gemma":0.0011984543,"threshold_uncertainty_score":0.04263538},"labels":[],"label_agreement":null},{"id":"W2112724657","doi":"10.1109/tsmcb.2009.2014245","title":"Color Face Recognition for Degraded Face Images","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":111,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"National Institute of Standards and Technology","keywords":"Face (sociological concept); Computer vision; Artificial intelligence; Facial recognition system; Computer science; Pattern recognition (psychology); Sociology","score_opus":0.03242392006122321,"score_gpt":0.2534927829636623,"score_spread":0.22106886290243907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112724657","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":[0.27573457,0.0010436714,0.71333504,0.00029612708,0.0001624087,0.00013644501,0.0003879498,0.0024227228,0.006481023],"genre_scores_gemma":[0.721555,0.00066539884,0.27352238,0.00019820998,0.000064782296,0.00007847222,0.0004891519,0.00010273806,0.003323853],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99948287,0.00011004275,0.00001693553,0.00011797017,0.00021439703,0.000057876077],"domain_scores_gemma":[0.9994981,0.00014492185,0.000054797958,0.00009922543,0.00018253118,0.000020415177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007056537,0.00044744895,0.0005657497,0.0008900054,0.0002510898,0.00052999426,0.00042443225,0.00042493158,0.0032242492],"category_scores_gemma":[0.0024603747,0.0001236958,0.0004734791,0.00047395483,0.00031353036,0.0006721206,0.00046416634,0.00043323918,0.0013855605],"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":[0.0005831693,0.00011647407,0.0034674532,0.00018285697,0.00006516988,0.00024221122,0.00015506662,0.018374605,0.2352996,0.0034439866,0.0035871784,0.7344822],"study_design_scores_gemma":[0.000025248593,0.00044591332,0.034290392,0.00004957645,0.000106305815,0.0021207125,0.00021822442,0.7104915,0.23731567,0.006516817,0.008328894,0.000090839945],"about_ca_topic_score_codex":0.0015022219,"about_ca_topic_score_gemma":0.0017804132,"teacher_disagreement_score":0.0032242492,"about_ca_system_score_codex":0.00036930927,"about_ca_system_score_gemma":0.0003178677,"threshold_uncertainty_score":0.010786176},"labels":[],"label_agreement":null},{"id":"W2113516501","doi":"10.1109/tsmcb.2004.843278","title":"Fuzzy OLAP Association Rules Mining-Based Modular Reinforcement Learning Approach for Multiagent Systems","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Online analytical processing; Computer science; Modular design; Association rule learning; Reinforcement learning; Fuzzy logic; Data mining; Artificial intelligence; Machine learning; Data warehouse; Programming language","score_opus":0.022201967909970022,"score_gpt":0.23933210750748174,"score_spread":0.2171301395975117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113516501","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":[0.012764073,0.00013744562,0.9859936,0.000111644724,0.000014299398,0.00006415834,0.00003821575,0.00022224536,0.00065434206],"genre_scores_gemma":[0.6810333,0.00023169628,0.31665143,0.00011421116,0.000039253122,0.00029986916,0.00018517909,0.000040947638,0.0014040793],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882287,0.0003093363,0.00011037712,0.00032502462,0.00032726282,0.0001050325],"domain_scores_gemma":[0.9977708,0.001006659,0.00033094175,0.0002066457,0.0005802434,0.00010478807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019051796,0.00093149085,0.0013169986,0.0011112647,0.00062770385,0.0011642865,0.0020287489,0.00079197704,0.0014233711],"category_scores_gemma":[0.0037080452,0.0004306349,0.001030898,0.0009843047,0.00065774017,0.0014045495,0.0015069311,0.001216059,0.0002382428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000067192836,0.00011115477,0.0019614846,0.000106061176,0.00013118307,0.00017123831,0.0001544344,0.88431716,0.0018555942,0.011571127,0.0006973043,0.098856054],"study_design_scores_gemma":[0.0000036262218,0.0000123510135,0.00006456883,0.0000021649007,0.000005568254,0.000009531889,0.000007802883,0.9965534,0.00024744798,0.002944668,0.00014570041,0.0000031475308],"about_ca_topic_score_codex":0.004984653,"about_ca_topic_score_gemma":0.0033977684,"teacher_disagreement_score":0.004984653,"about_ca_system_score_codex":0.0010279024,"about_ca_system_score_gemma":0.0012977151,"threshold_uncertainty_score":0.010075629},"labels":[],"label_agreement":null},{"id":"W2114383673","doi":"10.1109/3477.990878","title":"Granular clustering: a granular signature of data","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":161,"is_retracted":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":"Cluster analysis; Granular computing; Granulation; Data mining; Computer science; Signature (topology); Mathematics; Artificial intelligence; Engineering; Rough set","score_opus":0.04866022349014384,"score_gpt":0.24510514748128714,"score_spread":0.1964449239911433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114383673","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":[0.03346179,0.0016973804,0.9574826,0.0013156874,0.0001497908,0.00017982868,0.00039933357,0.00035010793,0.004963473],"genre_scores_gemma":[0.47814044,0.0022103477,0.5155943,0.00040912087,0.0003435389,0.0003087788,0.00047584387,0.0001684072,0.0023491785],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975279,0.0005647662,0.00025344407,0.0004960055,0.0009528861,0.0002050598],"domain_scores_gemma":[0.9945358,0.0026694464,0.0008001476,0.0012729872,0.0005024023,0.00021915066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021893033,0.00049160584,0.0010518313,0.0036437565,0.0010251269,0.005367551,0.00096373964,0.0010758588,0.0017692923],"category_scores_gemma":[0.011002716,0.0005169104,0.0011730733,0.004213837,0.0034526228,0.0057427026,0.002328335,0.001443954,0.0003308336],"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":[0.00016018191,0.000052774853,0.0062190206,0.00060974114,0.00014710001,0.0006786166,0.0016592147,0.069377236,0.011016274,0.7962166,0.003640538,0.11022271],"study_design_scores_gemma":[0.000022894608,0.00010375148,0.004453432,0.00021898931,0.00009040903,0.00090392085,0.00078083086,0.22232525,0.0051738466,0.7414248,0.024369938,0.00013189495],"about_ca_topic_score_codex":0.0013632533,"about_ca_topic_score_gemma":0.0008212963,"teacher_disagreement_score":0.005367551,"about_ca_system_score_codex":0.0012152612,"about_ca_system_score_gemma":0.0010107725,"threshold_uncertainty_score":0.011578321},"labels":[],"label_agreement":null},{"id":"W2115425990","doi":"10.1109/tsmcb.2007.908864","title":"An Enhanced Diagnostic System for Gear System Monitoring","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":41,"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":"Lakehead University","keywords":"Condition monitoring; Reliability (semiconductor); Predictive maintenance; Reliability engineering; Computer science; Engineering; Classifier (UML); Automotive engineering; Control engineering; Artificial intelligence","score_opus":0.014241980631905545,"score_gpt":0.2204190520453054,"score_spread":0.20617707141339986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115425990","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":[0.05579887,0.0006711079,0.93184835,0.00021308217,0.00025185922,0.00019333382,0.00029700447,0.0070543312,0.0036720324],"genre_scores_gemma":[0.6775072,0.00027517104,0.3152883,0.0003289698,0.0001431002,0.00015582061,0.00038540308,0.00006720982,0.0058487426],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99956495,0.00005234486,0.00003311218,0.00010395395,0.00021523926,0.00003047785],"domain_scores_gemma":[0.9993698,0.0001749788,0.00006281271,0.000110515524,0.00025481055,0.000027092863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000487203,0.00035435645,0.0004976516,0.0006524324,0.00018984806,0.00039104966,0.00075435353,0.0006609147,0.003321484],"category_scores_gemma":[0.0015434803,0.00018702277,0.00019829458,0.00024333259,0.00015488427,0.0006371305,0.00059377804,0.00044461514,0.0008454855],"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":[0.00057378464,0.00014851434,0.0030132008,0.0003275051,0.000041370076,0.0003650261,0.0001298357,0.010193041,0.31962392,0.0023765469,0.0047441027,0.6584632],"study_design_scores_gemma":[0.00016625892,0.001073022,0.013047381,0.00010659686,0.00018377298,0.0036977287,0.00005580758,0.64656,0.2736089,0.0029617227,0.058385685,0.0001531319],"about_ca_topic_score_codex":0.00049218984,"about_ca_topic_score_gemma":0.0005657454,"teacher_disagreement_score":0.003321484,"about_ca_system_score_codex":0.00027712298,"about_ca_system_score_gemma":0.000285485,"threshold_uncertainty_score":0.011111498},"labels":[],"label_agreement":null},{"id":"W2115472598","doi":"10.1109/tsmcb.2009.2035630","title":"Recourse-Based Facility-Location Problems in Hybrid Uncertain Environment","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fuzzy Systems and Optimization","field":"Mathematics","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematical optimization; Randomness; Metaheuristic; Fuzzy logic; Tabu search; Computer science; Hybrid algorithm (constraint satisfaction); Particle swarm optimization; Genetic algorithm; Facility location problem; Mathematics; Stochastic programming; Artificial intelligence; Constraint programming","score_opus":0.03389844303901974,"score_gpt":0.2494535062606692,"score_spread":0.21555506322164947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115472598","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":[0.064786255,0.0006376926,0.9314973,0.00031735798,0.000029236258,0.00003966356,0.00012495014,0.00011501181,0.0024525288],"genre_scores_gemma":[0.9480827,0.0004127495,0.048163228,0.000052208154,0.000026313393,0.00009979483,0.00013725454,0.000040145067,0.0029857075],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861956,0.0006707365,0.00004723347,0.00025436515,0.00020911418,0.00019885939],"domain_scores_gemma":[0.9960194,0.0030316804,0.00045000322,0.0000952179,0.00027387094,0.00012970188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019767212,0.0010876749,0.0022003413,0.0009375008,0.00058181543,0.0017833454,0.0019176488,0.0022048664,0.0014253454],"category_scores_gemma":[0.004066297,0.0009576355,0.0013595523,0.0013694331,0.0014615504,0.0016560599,0.0012151367,0.0012759063,0.00014542442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014563936,0.0000047212025,0.00009514402,0.000015860076,0.000014512332,0.00004514579,0.000008788762,0.996296,0.00008447836,0.0026149293,0.000034037133,0.000771757],"study_design_scores_gemma":[0.0000047907893,0.00001158694,0.00004237773,0.0000021857988,0.000004241778,0.000010789591,0.000007726233,0.9978529,0.000058954723,0.0019376588,0.00006258097,0.000004205334],"about_ca_topic_score_codex":0.017723884,"about_ca_topic_score_gemma":0.0083982125,"teacher_disagreement_score":0.017723884,"about_ca_system_score_codex":0.0021665567,"about_ca_system_score_gemma":0.0013253613,"threshold_uncertainty_score":0.035241425},"labels":[],"label_agreement":null},{"id":"W2115663543","doi":"10.1109/tsmcb.2009.2032363","title":"Random Early Detection for Congestion Avoidance in Wired Networks: A Discretized Pursuit Learning-Automata-Like Solution","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":80,"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":"Random early detection; Learning automata; Queue; Computer science; Active queue management; Network congestion; Packet loss; Network packet; Discretization; Mathematical optimization; Computer network; Automaton; Mathematics; Artificial intelligence","score_opus":0.010520426210779777,"score_gpt":0.21616616432632074,"score_spread":0.20564573811554096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115663543","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":[0.01833719,0.00017684967,0.97805595,0.00035111493,0.000042094787,0.00004349647,0.000020537442,0.00022305167,0.002749776],"genre_scores_gemma":[0.870674,0.0002215715,0.12405563,0.0002115214,0.000042794905,0.00023392394,0.000047711626,0.000041049036,0.0044718073],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995846,0.00013247179,0.000021058739,0.00009540157,0.000099054465,0.000067347944],"domain_scores_gemma":[0.9985927,0.0009338006,0.00012592778,0.00008014983,0.0001825083,0.00008493845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010913699,0.00052698015,0.00082569406,0.0004072715,0.00043781247,0.0009015013,0.0013076351,0.0011611278,0.0015861101],"category_scores_gemma":[0.0031357643,0.0003143148,0.0005811274,0.00032128274,0.0011036178,0.0007691834,0.0012843313,0.0014152277,0.00019816682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030946674,0.00003084928,0.00048124202,0.000035890687,0.000019963856,0.00003801173,0.00005285768,0.96448505,0.00081501325,0.020318557,0.00035568635,0.013335874],"study_design_scores_gemma":[0.0000043553914,0.000011494643,0.000018345156,0.0000019804702,0.0000020419016,0.0000045503643,0.0000028659786,0.9971481,0.00008678735,0.0026158136,0.000101444864,0.000002229669],"about_ca_topic_score_codex":0.005114462,"about_ca_topic_score_gemma":0.004016202,"teacher_disagreement_score":0.005114462,"about_ca_system_score_codex":0.0011581773,"about_ca_system_score_gemma":0.0013951382,"threshold_uncertainty_score":0.010169387},"labels":[],"label_agreement":null},{"id":"W2115969720","doi":"10.1109/tsmcb.2008.2009071","title":"Multimodal Biometric System Using Rank-Level Fusion Approach","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":199,"is_retracted":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":"Biometrics; Computer science; Rank (graph theory); Linear discriminant analysis; Artificial intelligence; Authentication (law); Pattern recognition (psychology); Data mining; Machine learning; Mathematics","score_opus":0.05091966737059919,"score_gpt":0.25750198462378876,"score_spread":0.20658231725318957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115969720","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":[0.019072125,0.0004995383,0.9769966,0.00017040143,0.00003945578,0.00007106492,0.000069205526,0.0010018387,0.0020798738],"genre_scores_gemma":[0.549616,0.0005708719,0.44478565,0.00014683185,0.00011115185,0.00014887695,0.0002732548,0.00005650754,0.0042909454],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99766374,0.0006468353,0.00013047835,0.0003785821,0.0010158375,0.00016458765],"domain_scores_gemma":[0.99922335,0.0001652348,0.00012093207,0.00012706756,0.00032985138,0.0000335757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019325064,0.0007289519,0.0012633596,0.0012365244,0.0005439125,0.001484726,0.00073176244,0.0009475562,0.002706412],"category_scores_gemma":[0.0026537296,0.000259312,0.00084371935,0.0010271275,0.0004898746,0.0015486961,0.0012098415,0.0006830869,0.0013885319],"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":[0.0005256182,0.00014874844,0.0017344981,0.000289294,0.00020280224,0.00016446857,0.00024926433,0.08501342,0.08662605,0.023085628,0.002870186,0.7990899],"study_design_scores_gemma":[0.00003192028,0.00052832154,0.0020503069,0.000031532152,0.00013783848,0.00039669836,0.00008270186,0.93421805,0.042932034,0.012674647,0.006800645,0.000115306604],"about_ca_topic_score_codex":0.0009454416,"about_ca_topic_score_gemma":0.0007936995,"teacher_disagreement_score":0.002706412,"about_ca_system_score_codex":0.0007325267,"about_ca_system_score_gemma":0.00057795044,"threshold_uncertainty_score":0.01022017},"labels":[],"label_agreement":null},{"id":"W2116046819","doi":"10.1109/tsmcb.2009.2029986","title":"On the Stability of Interval Type-2 TSK Fuzzy Logic Control Systems","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":297,"is_retracted":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":"Interval (graph theory); Control theory (sociology); Fuzzy logic; Stability (learning theory); Controller (irrigation); Inference; Fuzzy control system; Type (biology); Stability conditions; Computer science; Adaptive neuro fuzzy inference system; Mathematics; Control system; Control (management); Mathematical optimization; Artificial intelligence; Machine learning; Discrete time and continuous time; Engineering","score_opus":0.02540376974672306,"score_gpt":0.22881949318840936,"score_spread":0.2034157234416863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116046819","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":[0.03446532,0.00088799285,0.9577441,0.0001329432,0.00008101861,0.000035319925,0.000051402294,0.00018760373,0.0064142304],"genre_scores_gemma":[0.96815777,0.0006308239,0.029509427,0.000047686182,0.000049270526,0.000053229855,0.000047503083,0.000019133184,0.0014851638],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993375,0.00014654607,0.000043204112,0.00016141895,0.00025886053,0.00005236969],"domain_scores_gemma":[0.99911076,0.00048812202,0.00013333377,0.00006103778,0.00018881513,0.000017961955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001138802,0.0007218221,0.00056986825,0.0005159926,0.0004905131,0.0012658769,0.00069415197,0.0007028874,0.0015441137],"category_scores_gemma":[0.0031970977,0.00017400112,0.00057047006,0.0005081909,0.0009378198,0.0009698268,0.00048638057,0.00074824184,0.00027956412],"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":[0.0002957212,0.000038734175,0.0010831112,0.00037712773,0.00008215202,0.00047814104,0.00059073354,0.83154273,0.020016912,0.077903725,0.0006924557,0.066898435],"study_design_scores_gemma":[0.0000074628842,0.000051296814,0.00020439277,0.00001586515,0.000008830176,0.000033094202,0.000020056728,0.9893853,0.001405347,0.008391319,0.00046614994,0.0000109254515],"about_ca_topic_score_codex":0.0038975077,"about_ca_topic_score_gemma":0.001889937,"teacher_disagreement_score":0.0038975077,"about_ca_system_score_codex":0.00077551074,"about_ca_system_score_gemma":0.00061050185,"threshold_uncertainty_score":0.0077496767},"labels":[],"label_agreement":null},{"id":"W2116283693","doi":"10.1109/tsmcb.2004.824524","title":"Enhancing Prototype Reduction Schemes With Recursion: A Method Applicable for “Large” Data Sets","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":42,"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":"Reduction (mathematics); Recursion (computer science); Computer science; Data reduction; Algorithm; Data mining; Mathematics","score_opus":0.03595339579860602,"score_gpt":0.3036403519203792,"score_spread":0.2676869561217732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116283693","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":[0.0030336075,0.00007313748,0.99569964,0.000044022217,0.000018198727,0.00008582942,0.000021893276,0.0006892531,0.00033445333],"genre_scores_gemma":[0.045022845,0.00009111156,0.95315075,0.00008761686,0.000037082656,0.00029671882,0.00013300875,0.0002023026,0.0009785634],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971041,0.0008699496,0.00022198303,0.000566952,0.001040189,0.00019678014],"domain_scores_gemma":[0.9942052,0.002524572,0.00032940367,0.001848292,0.0009804594,0.00011206464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004000943,0.0009444494,0.0015400486,0.0018431409,0.0011414378,0.0015865421,0.0031792433,0.0017925237,0.0034398362],"category_scores_gemma":[0.016774224,0.00096523936,0.0019215279,0.0021231591,0.0015801084,0.0033454974,0.003490758,0.0021711614,0.0017319863],"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":[0.00030580632,0.00019206549,0.0017410982,0.0003813907,0.00013509527,0.00018381595,0.0010190901,0.09012059,0.049981132,0.06411886,0.0056450353,0.7861761],"study_design_scores_gemma":[0.000073345655,0.00020142557,0.0006061321,0.000041445197,0.00005634348,0.0002974082,0.00010918333,0.9273928,0.01735882,0.04113326,0.012671223,0.000058556663],"about_ca_topic_score_codex":0.002506716,"about_ca_topic_score_gemma":0.0027122665,"teacher_disagreement_score":0.004000943,"about_ca_system_score_codex":0.00076646876,"about_ca_system_score_gemma":0.0014841239,"threshold_uncertainty_score":0.021159291},"labels":[],"label_agreement":null},{"id":"W2116355994","doi":"10.1109/tsmcb.2008.2005910","title":"Comprehensive Unified Control Strategy for Underactuated Two-Link Manipulators","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":108,"is_retracted":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":"Control theory (sociology); Lyapunov function; Underactuation; Control-Lyapunov function; Lyapunov redesign; Swing; Stability (learning theory); Nonlinear system; Function (biology); Mathematics; State (computer science); Control (management); Computer science; Law; Engineering; Artificial intelligence; Physics","score_opus":0.049932787325157185,"score_gpt":0.25307078264935845,"score_spread":0.20313799532420126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116355994","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":[0.0163986,0.0004991105,0.9764896,0.00007952108,0.00007652355,0.000051546765,0.000023343218,0.00028828424,0.006093425],"genre_scores_gemma":[0.91884226,0.000704421,0.07178239,0.00013832656,0.0001185908,0.00031836232,0.00010455616,0.000044620243,0.007946417],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957174,0.000060775852,0.000035196044,0.000089104215,0.00017828809,0.00006490629],"domain_scores_gemma":[0.99982786,0.000028171811,0.00003666974,0.000019849567,0.000068261244,0.000019023537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056942843,0.001388858,0.0011858931,0.00063062017,0.0005588631,0.001181202,0.001256256,0.00060330646,0.0015705499],"category_scores_gemma":[0.00043611793,0.000373495,0.0005955753,0.00047719973,0.000726786,0.00095556263,0.0015009014,0.0006453404,0.0003399573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015166785,0.00008500001,0.0003636591,0.000464435,0.000112810725,0.00049753784,0.00045599544,0.7716332,0.03309698,0.07856096,0.002116517,0.11246121],"study_design_scores_gemma":[0.000036953938,0.00032637763,0.00017354559,0.000016988542,0.000031368767,0.000048211776,0.00003067547,0.98654616,0.0019469901,0.0074011455,0.0034217867,0.000019814303],"about_ca_topic_score_codex":0.0031762077,"about_ca_topic_score_gemma":0.002797038,"teacher_disagreement_score":0.0031762077,"about_ca_system_score_codex":0.00052127865,"about_ca_system_score_gemma":0.0008040932,"threshold_uncertainty_score":0.0063154697},"labels":[],"label_agreement":null},{"id":"W2116396438","doi":"10.1109/tsmcb.2009.2028871","title":"Multiinnovation Least-Squares Identification for System Modeling","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Control Systems and Identification","field":"Engineering","cited_by":219,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Toronto Metropolitan University","funders":"","keywords":"Interval (graph theory); Least-squares function approximation; Identification (biology); Algorithm; Integer (computer science); Key (lock); Recursive least squares filter; Mathematics; Estimation theory; Computer science; Statistics; Combinatorics; Adaptive filter","score_opus":0.018665903595463936,"score_gpt":0.22339414269407495,"score_spread":0.20472823909861101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116396438","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":[0.0006840654,0.00007239285,0.99881774,0.000024794412,0.000012620765,0.000006297652,0.0000070640012,0.0001294394,0.0002456333],"genre_scores_gemma":[0.2446736,0.00047383804,0.74942917,0.00010773638,0.00009327079,0.00028029393,0.00019607843,0.00013023936,0.0046157246],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994873,0.00018351834,0.000030097117,0.00011563378,0.0001526414,0.000030810523],"domain_scores_gemma":[0.9994405,0.00029755937,0.000082599705,0.00006297479,0.00010475022,0.0000116619685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084120035,0.0008595007,0.0007793252,0.00042112704,0.0003811329,0.0006616482,0.0008447929,0.00089063525,0.001996842],"category_scores_gemma":[0.0019417512,0.00039971765,0.0007926796,0.00059480837,0.00047981902,0.0007911707,0.00078186137,0.0015082073,0.0008884629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006268711,0.000033840395,0.0003120597,0.00015654982,0.00005798694,0.000054791934,0.00009568978,0.8096473,0.0064477245,0.02401279,0.0012624555,0.15785609],"study_design_scores_gemma":[0.0000023580249,0.000011639126,0.000036437003,0.0000039769147,0.0000028400004,0.000008106812,0.00000220426,0.9964484,0.00062610395,0.00199943,0.0008539715,0.000004580493],"about_ca_topic_score_codex":0.002073483,"about_ca_topic_score_gemma":0.0023119815,"teacher_disagreement_score":0.002073483,"about_ca_system_score_codex":0.0006024058,"about_ca_system_score_gemma":0.00076064013,"threshold_uncertainty_score":0.006680131},"labels":[],"label_agreement":null},{"id":"W2116871211","doi":"10.1109/tsmcb.2009.2013721","title":"Contemporary Cybernetics and Its Facets of Cognitive Informatics and Computational Intelligence","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":146,"is_retracted":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; Research Manitoba; University of Calgary","funders":"","keywords":"Cybernetics; Cognitive science; Computational intelligence; Computer science; Informatics; Cognition; Biocybernetics; Artificial intelligence; Cognitive architecture; Psychology; Engineering; Neuroscience","score_opus":0.03213895612954015,"score_gpt":0.2586853916812793,"score_spread":0.22654643555173914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116871211","genre_codex":"other","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":[0.028240664,0.18608002,0.26142788,0.040960148,0.0018702877,0.0000737859,0.00016431705,0.00024169576,0.48094115],"genre_scores_gemma":[0.79706967,0.10708892,0.06472852,0.0042505506,0.0042358655,0.00024675453,0.00023367621,0.00009423139,0.022051832],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99936086,0.00025571923,0.000030045478,0.00009360071,0.00019976037,0.00005999021],"domain_scores_gemma":[0.9989035,0.00060837483,0.00010484403,0.00016556468,0.00014261887,0.00007509676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008501038,0.0005742643,0.0004642898,0.0025330167,0.0013849905,0.0056373305,0.0005137126,0.0014714713,0.003618438],"category_scores_gemma":[0.0019215534,0.00022783967,0.00035953108,0.0026101784,0.012067097,0.0068649156,0.0019394497,0.0028343755,0.000474431],"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":[0.0000016869153,0.0000030532433,0.00010250695,0.000043127104,0.0000027691501,0.000021713318,0.00025817865,0.000307761,0.000079728256,0.9915486,0.0008509064,0.006779976],"study_design_scores_gemma":[0.0000010086576,0.0000048803718,0.00025753144,0.000065529595,0.0000028211532,0.00009399034,0.00030252273,0.00090937334,0.000060805978,0.9591045,0.039191835,0.000005163192],"about_ca_topic_score_codex":0.0017317218,"about_ca_topic_score_gemma":0.0014626873,"teacher_disagreement_score":0.0056373305,"about_ca_system_score_codex":0.0018757347,"about_ca_system_score_gemma":0.0015523584,"threshold_uncertainty_score":0.013609409},"labels":[],"label_agreement":null},{"id":"W2116876614","doi":"10.1109/tsmcb.2011.2119311","title":"Behavior Coordination of Mobile Robotics Using Supervisory Control of Fuzzy Discrete Event Systems","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Petri Nets in System Modeling","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Supervisory control; Supervisory control theory; Supervisor; Controllability; Fuzzy logic; Mobile robot; Observability; Control engineering; Controller (irrigation); Event (particle physics); Fuzzy control system; Control theory (sociology); Robotics; Computer science; Artificial intelligence; Robot; Engineering; Control (management); Mathematics","score_opus":0.05015066019943989,"score_gpt":0.2568957991932533,"score_spread":0.2067451389938134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116876614","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":[0.02862241,0.00010647998,0.96961695,0.000036090263,0.000024225652,0.000030355277,0.000013131049,0.00032008358,0.0012303053],"genre_scores_gemma":[0.9302718,0.00011351281,0.0689379,0.000018895866,0.00001611026,0.000072637806,0.000028929664,0.000012318826,0.0005278358],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996718,0.000083693776,0.00002661598,0.00007960095,0.00011380387,0.000024466532],"domain_scores_gemma":[0.99954295,0.00019754912,0.00008804965,0.000063956526,0.00008328936,0.000024218387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058355794,0.00043511635,0.00038512383,0.00026278093,0.00022579277,0.0005393362,0.0005854378,0.00032816883,0.00053092005],"category_scores_gemma":[0.0012466557,0.00015904287,0.0004474568,0.00017881353,0.0006493955,0.00045872707,0.00049181114,0.00046947543,0.00007394017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015168777,0.0000694415,0.001038981,0.00014914364,0.000069545815,0.00024485428,0.00026894262,0.87356216,0.029760089,0.028832745,0.00035309404,0.0654993],"study_design_scores_gemma":[0.00001625122,0.000060149912,0.00024037121,0.0000059995255,0.000009645238,0.000025261692,0.000012301366,0.99026805,0.003587019,0.0052303527,0.00053784245,0.000006713481],"about_ca_topic_score_codex":0.0019061547,"about_ca_topic_score_gemma":0.0014251011,"teacher_disagreement_score":0.0019061547,"about_ca_system_score_codex":0.00030632337,"about_ca_system_score_gemma":0.00050585467,"threshold_uncertainty_score":0.0037901402},"labels":[],"label_agreement":null},{"id":"W2117291086","doi":"10.1109/tsmcb.2008.2008196","title":"Robust and Efficient Feature Tracking for Indoor Navigation","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Subpixel rendering; Artificial intelligence; Robustness (evolution); Computer vision; Feature tracking; Computer science; Feature (linguistics); Computation; Planar; Invariant (physics); Feature extraction; Algorithm; Pixel; Mathematics; Computer graphics (images)","score_opus":0.019098141232957954,"score_gpt":0.21644428870738328,"score_spread":0.19734614747442533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117291086","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":[0.004955268,0.00007642472,0.9939681,0.000021665901,0.00001083065,0.0000069188764,0.000022005954,0.0006042359,0.0003344439],"genre_scores_gemma":[0.32490963,0.00018355959,0.6723415,0.000043012285,0.00002646791,0.00005744312,0.00022379088,0.00014791574,0.0020667242],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997973,0.000029480136,0.0000069280836,0.000060904058,0.00008171741,0.000023617555],"domain_scores_gemma":[0.99980277,0.00004362377,0.00003800987,0.000062494844,0.000044628094,0.000008530199],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021603159,0.0004118595,0.00042608622,0.0004427472,0.00022490154,0.00028109478,0.0005631692,0.0005083929,0.0013944748],"category_scores_gemma":[0.00078553346,0.00030523134,0.0002757375,0.0007300538,0.00031455432,0.00056253857,0.00054138555,0.0004266046,0.00071440305],"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":[0.00013101962,0.00004479431,0.00092631596,0.000089419744,0.00004252603,0.00009779807,0.00006971579,0.3346764,0.13408844,0.0084967185,0.004347733,0.5169891],"study_design_scores_gemma":[0.000009318905,0.000036275807,0.000667316,0.000005339172,0.000008097979,0.00008024764,0.000009106366,0.97108746,0.021687293,0.0032350845,0.0031608564,0.000013616356],"about_ca_topic_score_codex":0.002620425,"about_ca_topic_score_gemma":0.0040896465,"teacher_disagreement_score":0.002620425,"about_ca_system_score_codex":0.00039798024,"about_ca_system_score_gemma":0.00042244725,"threshold_uncertainty_score":0.0052102804},"labels":[],"label_agreement":null},{"id":"W2117847370","doi":"10.1109/tsmcb.2007.896406","title":"Scaling Genetic Programming to Large Datasets Using Hierarchical Dynamic Subset Selection","year":2007,"lang":"en","type":"letter","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Evolutionary Algorithms and Applications","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":"Dalhousie University","funders":"","keywords":"Computer science; RSS; Selection (genetic algorithm); Heuristics; Genetic programming; Block (permutation group theory); Benchmarking; Machine learning; Artificial intelligence; Genetic algorithm; Overhead (engineering); Binary classification; Data mining; Algorithm; Mathematics; Support vector machine","score_opus":0.020893965450406844,"score_gpt":0.2715984832799908,"score_spread":0.250704517829584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117847370","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":[0.059227064,0.0004712865,0.92821217,0.0027980634,0.00022660519,0.0001147325,0.0001007949,0.0014847412,0.0073645585],"genre_scores_gemma":[0.45076045,0.00075247104,0.5427303,0.0013874182,0.00029559666,0.0005743079,0.00033591824,0.000209128,0.0029544418],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993773,0.00025720242,0.000028868375,0.000099202174,0.0002063367,0.000031190026],"domain_scores_gemma":[0.9975688,0.0016635129,0.000086684806,0.0004183036,0.00022681129,0.000035904934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012032698,0.00042320462,0.00063651294,0.00045883044,0.00031105502,0.0007077317,0.0009156635,0.00073920225,0.0013410144],"category_scores_gemma":[0.0061150757,0.00021558776,0.00042383,0.0013327943,0.0004667226,0.0010013536,0.0008622565,0.0012211197,0.0008164949],"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":[0.00009701408,0.00009085694,0.0011522131,0.00010367386,0.000060011324,0.00023682733,0.00009472329,0.46882296,0.007426899,0.025712483,0.011094191,0.48510823],"study_design_scores_gemma":[0.000019958923,0.000034214947,0.00021943483,0.0000062327995,0.000005017584,0.000068226036,0.000013140387,0.97846895,0.0010243591,0.017354025,0.0027811106,0.000005300605],"about_ca_topic_score_codex":0.0013939774,"about_ca_topic_score_gemma":0.0021066575,"teacher_disagreement_score":0.0013939774,"about_ca_system_score_codex":0.0005805657,"about_ca_system_score_gemma":0.00038069932,"threshold_uncertainty_score":0.0063635707},"labels":[],"label_agreement":null},{"id":"W2119537429","doi":"10.1109/tsmcb.2009.2037131","title":"An Analysis of Random Projection for Changeable and Privacy-Preserving Biometric Verification","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Biometrics; Random projection; Computer science; Independent and identically distributed random variables; Data mining; Curse of dimensionality; Software deployment; Projection (relational algebra); Feature (linguistics); Random variable; Pattern recognition (psychology); Similarity (geometry); Feature vector; Information privacy; Gaussian; Domain (mathematical analysis); Artificial intelligence; Algorithm; Image (mathematics); Mathematics; Computer security; Statistics","score_opus":0.0293628581158245,"score_gpt":0.2740160634878878,"score_spread":0.2446532053720633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119537429","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":[0.00453945,0.00039039075,0.99371004,0.00006655247,0.000015931002,0.000025481642,0.000008389005,0.000058836682,0.0011849533],"genre_scores_gemma":[0.4437427,0.0026542707,0.54783356,0.00013508773,0.00023394811,0.00021177609,0.00011507425,0.00013416642,0.0049394034],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997136,0.0011782541,0.00010533098,0.00032812398,0.0011459923,0.00010627188],"domain_scores_gemma":[0.9957729,0.002790698,0.00030442205,0.0006611529,0.00039985657,0.000071024995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023725564,0.00059996685,0.0006908522,0.00064334215,0.00038833162,0.0009675412,0.0009479126,0.0008176792,0.002397187],"category_scores_gemma":[0.009525499,0.0004526139,0.00084900256,0.0007066423,0.001558467,0.0018149664,0.0011662851,0.0011544537,0.00058577966],"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":[0.00025356596,0.00010656437,0.0007142242,0.0005456634,0.00010946435,0.0004896756,0.0002602476,0.23191077,0.041466236,0.44391817,0.0017831627,0.27844226],"study_design_scores_gemma":[0.000013129056,0.00016595471,0.00042668014,0.00003115361,0.00002809182,0.0005523016,0.000022647406,0.9310452,0.014850484,0.04903775,0.0037945302,0.000032069507],"about_ca_topic_score_codex":0.00031425487,"about_ca_topic_score_gemma":0.00020157361,"teacher_disagreement_score":0.002397187,"about_ca_system_score_codex":0.00054810086,"about_ca_system_score_gemma":0.0005693383,"threshold_uncertainty_score":0.012547433},"labels":[],"label_agreement":null},{"id":"W2119586505","doi":"10.1109/tsmcb.2004.825930","title":"Facial Expression Recognition Using Constructive Feedforward Neural Networks","year":2004,"lang":"en","type":"letter","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":246,"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":"Instituto de Telecomunicações","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Facial expression; Sadness; Artificial neural network; Feedforward neural network; Facial recognition system; Feature (linguistics); Feed forward; Speech recognition; Anger; Psychology","score_opus":0.031808206359679334,"score_gpt":0.23696929931130678,"score_spread":0.20516109295162743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119586505","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":[0.013840036,0.00019503986,0.9836024,0.000058781647,0.000054711883,0.00004405436,0.000020396781,0.0008655984,0.0013188638],"genre_scores_gemma":[0.51096565,0.00053276593,0.48392493,0.00025104586,0.00008833535,0.0002174396,0.0002119265,0.000081316815,0.0037265732],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942005,0.00014515867,0.00002945783,0.00009593552,0.00025833884,0.00005116219],"domain_scores_gemma":[0.9993099,0.0002969374,0.00008046774,0.00006753147,0.00022783552,0.000017361343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075959926,0.00096688786,0.00053031486,0.0005988551,0.0002408125,0.0004624043,0.0013793815,0.00052188593,0.0009814636],"category_scores_gemma":[0.002177757,0.00040345156,0.00067692774,0.00042378678,0.0005032315,0.0006837457,0.000688465,0.0006984444,0.0004154037],"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":[0.00021102758,0.00015284943,0.0010283852,0.00016273855,0.0001233183,0.0002762042,0.0001245128,0.25088614,0.08238865,0.004778752,0.001861046,0.65800637],"study_design_scores_gemma":[0.0000066844295,0.00006776979,0.00031472737,0.000010355536,0.000021867794,0.000081004306,0.000007804463,0.9818148,0.015932398,0.0011532153,0.0005792414,0.000010150661],"about_ca_topic_score_codex":0.0016439345,"about_ca_topic_score_gemma":0.0022397744,"teacher_disagreement_score":0.0016439345,"about_ca_system_score_codex":0.00035004326,"about_ca_system_score_gemma":0.00033571402,"threshold_uncertainty_score":0.004017234},"labels":[],"label_agreement":null},{"id":"W2120426122","doi":"10.1109/tsmcb.2008.919232","title":"Design and Tuning of Standard Additive Model Based Fuzzy PID Controllers for Multivariable Process Systems","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Advanced Control Systems Design","field":"Engineering","cited_by":39,"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; University of British Columbia","funders":"Memorial University of Newfoundland","keywords":"Multivariable calculus; Control theory (sociology); PID controller; Fuzzy logic; Process (computing); Nonlinear system; Computer science; Mathematics; Fuzzy control system; Control engineering; Engineering; Control (management); Temperature control; Artificial intelligence","score_opus":0.02358266195978691,"score_gpt":0.22865585146980316,"score_spread":0.20507318951001624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120426122","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":[0.0079776095,0.00008754895,0.9906955,0.000014922667,0.00002068739,0.00002984814,0.0000096438625,0.00027413358,0.0008899955],"genre_scores_gemma":[0.69390786,0.00013367349,0.30434838,0.00004988905,0.000029899924,0.00016350021,0.000050928324,0.000041043644,0.0012748039],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991991,0.00009955834,0.0000547918,0.00016049165,0.0004304248,0.00005555506],"domain_scores_gemma":[0.9995098,0.00015509583,0.000077985285,0.000066251494,0.00017339057,0.00001740502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001000746,0.00063200376,0.00057617365,0.00047903508,0.00040400904,0.0009466345,0.0015258974,0.00061564497,0.0008780671],"category_scores_gemma":[0.001855603,0.00040105986,0.00043218033,0.00028330393,0.00038864682,0.00065224967,0.00069006684,0.00086462434,0.00029032523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003043542,0.00022397426,0.0010539573,0.00051372545,0.00012921024,0.00012249581,0.0003011643,0.49137953,0.08428743,0.016188275,0.001333508,0.40416238],"study_design_scores_gemma":[0.000030092016,0.00015780418,0.00030749498,0.000009882703,0.000020317362,0.00004456993,0.000010946669,0.98179483,0.014139017,0.001541799,0.0019265818,0.000016744292],"about_ca_topic_score_codex":0.0008149986,"about_ca_topic_score_gemma":0.0012824233,"teacher_disagreement_score":0.0015258974,"about_ca_system_score_codex":0.000428216,"about_ca_system_score_gemma":0.00045146383,"threshold_uncertainty_score":0.005292535},"labels":[],"label_agreement":null},{"id":"W2121115638","doi":"10.1109/tsmcb.2006.883423","title":"An Active Vision System for Multitarget Surveillance in Dynamic Environments","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Amorfix (Canada)","funders":"","keywords":"Computer science; Active vision; A priori and a posteriori; Control reconfiguration; Computer vision; Artificial intelligence; Orientation (vector space); Position (finance); Real-time computing; Embedded system","score_opus":0.01469768275098797,"score_gpt":0.28501057497515253,"score_spread":0.27031289222416455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121115638","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":[0.009400177,0.0005595211,0.9853107,0.00008747584,0.00011022006,0.00006255314,0.00002656154,0.0009859783,0.003456836],"genre_scores_gemma":[0.39820608,0.0007398825,0.59400034,0.00023816428,0.0001270207,0.00021805511,0.00014113836,0.0000672758,0.006261998],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999759,0.000039335024,0.000009788629,0.000062439205,0.00010972948,0.000019720504],"domain_scores_gemma":[0.9997943,0.00005855599,0.000022749437,0.000030145722,0.0000696882,0.000024563404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032959986,0.00041751313,0.00039175505,0.00040595786,0.0003544017,0.0006314014,0.0009897943,0.0007926754,0.0018586507],"category_scores_gemma":[0.0004925334,0.00021610864,0.00024800608,0.0002153205,0.00024014116,0.0008303203,0.00053468294,0.00078882114,0.00068874226],"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":[0.0002793051,0.00027824417,0.000777286,0.0002965916,0.00006901675,0.00022272466,0.00020352237,0.026102329,0.25857598,0.017625485,0.0049383477,0.6906312],"study_design_scores_gemma":[0.00012044845,0.00094169757,0.0020392886,0.000057143836,0.00010358757,0.0009339834,0.00007568813,0.7941503,0.11739645,0.006373382,0.07773523,0.00007277669],"about_ca_topic_score_codex":0.00071088545,"about_ca_topic_score_gemma":0.00092999305,"teacher_disagreement_score":0.0018586507,"about_ca_system_score_codex":0.00034128298,"about_ca_system_score_gemma":0.0004092342,"threshold_uncertainty_score":0.0062178373},"labels":[],"label_agreement":null},{"id":"W2121150791","doi":"10.1109/3477.846236","title":"Probabilistic winner-take-all segmentation of images with application to ship detection","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","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":"Queen's University","funders":"","keywords":"Artificial intelligence; Segmentation; Thresholding; Pattern recognition (psychology); Computer science; Cluster analysis; Image segmentation; Histogram; Probabilistic logic; Synthetic aperture radar; Scale-space segmentation; Backpropagation; Artificial neural network; Segmentation-based object categorization; Image (mathematics); Computer vision","score_opus":0.017870942451071167,"score_gpt":0.23584558026879607,"score_spread":0.21797463781772491,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121150791","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":[0.01446233,0.00024712994,0.98359376,0.00014691522,0.000029756176,0.00004612578,0.000019017527,0.000778127,0.00067692104],"genre_scores_gemma":[0.4273549,0.00031909833,0.5691053,0.00014093942,0.000056922407,0.00012042948,0.00009969531,0.0002699266,0.0025327203],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923575,0.0001913552,0.000041772844,0.00016494638,0.00027957011,0.00008662958],"domain_scores_gemma":[0.9991148,0.00035462488,0.00011405961,0.00011413544,0.0002586748,0.000043628857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014295093,0.0007755983,0.0012398703,0.0008483333,0.0008031096,0.0009242407,0.0020332092,0.0013106801,0.0009276699],"category_scores_gemma":[0.0032169048,0.000647776,0.00074057654,0.0013922964,0.0010996793,0.0012567629,0.0015813804,0.0008847754,0.00028477277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018510787,0.000069532995,0.00070994167,0.00013010038,0.00014089062,0.00012077684,0.00015267418,0.6688213,0.019131621,0.007534579,0.0012906529,0.30171287],"study_design_scores_gemma":[0.0000052951264,0.000025241934,0.0001781885,0.000001804938,0.000007526954,0.00003716702,0.000008289572,0.9918943,0.0045790668,0.0028448165,0.00041029498,0.000008067592],"about_ca_topic_score_codex":0.004598185,"about_ca_topic_score_gemma":0.005399733,"teacher_disagreement_score":0.004598185,"about_ca_system_score_codex":0.0010174443,"about_ca_system_score_gemma":0.00097634486,"threshold_uncertainty_score":0.009142816},"labels":[],"label_agreement":null},{"id":"W2121468570","doi":"10.1109/3477.875441","title":"On the complexity of supervisory control design in the RW framework","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Petri Nets in System Modeling","field":"Computer Science","cited_by":113,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"TD Bank Group; University of Toronto","funders":"","keywords":"Supervisory control; Intersection (aeronautics); Class (philosophy); Subject (documents); Set (abstract data type); Control (management); Field (mathematics); Point (geometry); Computer science; State space; Theoretical computer science; State (computer science); Time complexity; Space (punctuation); Work (physics); Polynomial; Algebra over a field; Algorithm; Mathematics; Engineering; Pure mathematics; Artificial intelligence; Programming language","score_opus":0.0766427817339873,"score_gpt":0.25256677207928857,"score_spread":0.17592399034530126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121468570","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":[0.11349124,0.00072398805,0.8710303,0.0024193379,0.000062226565,0.00021730125,0.00036963445,0.00065631996,0.011029654],"genre_scores_gemma":[0.8083671,0.0011818062,0.18303868,0.00026446447,0.0001464921,0.0005709176,0.00061961083,0.00021686684,0.005594078],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972652,0.0009584643,0.000168624,0.0005022985,0.0006887875,0.00041669022],"domain_scores_gemma":[0.9803867,0.017344976,0.000815402,0.00082881754,0.00036537074,0.0002587407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030317644,0.0007803296,0.0013432475,0.000650894,0.0008312866,0.0026459554,0.0014182349,0.0013079597,0.005789576],"category_scores_gemma":[0.0172975,0.0007016754,0.0012407233,0.0008122586,0.0019392798,0.0058761253,0.0019708907,0.0026178926,0.00044357646],"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":[0.0005388376,0.000128477,0.001661351,0.0005272995,0.00008871657,0.00030710708,0.0003660566,0.7618424,0.004286994,0.17894326,0.0022963188,0.04901325],"study_design_scores_gemma":[0.00006789213,0.000063381594,0.00048247317,0.000026751672,0.000028324519,0.00006456435,0.00009141279,0.80677676,0.0011318658,0.18998739,0.0012582386,0.000020960615],"about_ca_topic_score_codex":0.0034082022,"about_ca_topic_score_gemma":0.0028940206,"teacher_disagreement_score":0.005789576,"about_ca_system_score_codex":0.002015207,"about_ca_system_score_gemma":0.00194866,"threshold_uncertainty_score":0.019368052},"labels":[],"label_agreement":null},{"id":"W2123348485","doi":"10.1109/tsmcb.2007.913124","title":"New Delay-Dependent Exponential Stability for Neural Networks With Time Delay","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Neural Networks Stability and Synchronization","field":"Computer Science","cited_by":119,"is_retracted":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":"Exponential stability; Linear matrix inequality; Artificial neural network; Control theory (sociology); Mathematics; Stability (learning theory); Exponential function; Computer science; Applied mathematics; Mathematical optimization; Nonlinear system; Artificial intelligence; Mathematical analysis; Machine learning; Physics; Control (management)","score_opus":0.021561978129249447,"score_gpt":0.2136098762744489,"score_spread":0.19204789814519946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123348485","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":[0.012778859,0.0010075867,0.98052955,0.00018924709,0.0001460185,0.000025898618,0.000047607646,0.00005628038,0.0052190223],"genre_scores_gemma":[0.77612597,0.0033977283,0.20490839,0.00028957,0.0002952279,0.00020218328,0.00024640822,0.00009429542,0.014440173],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99975806,0.000047989222,0.000020275547,0.00007284618,0.00008095005,0.0000199064],"domain_scores_gemma":[0.9997079,0.000113947644,0.00003760183,0.000019076426,0.00010382088,0.000017568782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006535283,0.0008414957,0.0004524543,0.0004689148,0.0002898172,0.00089968473,0.00059258426,0.0006792228,0.0019051353],"category_scores_gemma":[0.0014485016,0.00022772171,0.0004112312,0.0003299394,0.0005692339,0.0017803132,0.00094466045,0.00077744346,0.00020699682],"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":[0.00016479872,0.00004115762,0.0007140202,0.0006095558,0.00010798481,0.00039475478,0.00031051363,0.33164796,0.041572582,0.53831977,0.00253422,0.08358268],"study_design_scores_gemma":[0.000011222521,0.000056956793,0.00012121455,0.00002854005,0.000016954924,0.00012900171,0.000021396801,0.9310069,0.0035197688,0.06027275,0.0047959075,0.000019399544],"about_ca_topic_score_codex":0.0005186524,"about_ca_topic_score_gemma":0.0005472445,"teacher_disagreement_score":0.0019051353,"about_ca_system_score_codex":0.00064575695,"about_ca_system_score_gemma":0.0004906785,"threshold_uncertainty_score":0.006373346},"labels":[],"label_agreement":null},{"id":"W2123448637","doi":"10.1109/tsmcb.2005.857095","title":"On the ternary spatial relation \"Between\"","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":72,"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":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Relation (database); Object (grammar); Spatial relation; Computer science; Convexity; Fuzzy logic; Space (punctuation); Visibility; Binary relation; Mathematics; Artificial intelligence; Data mining; Discrete mathematics; Geography","score_opus":0.019711911771190412,"score_gpt":0.2277495030253552,"score_spread":0.2080375912541648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123448637","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":[0.05020757,0.008372035,0.7525092,0.004649423,0.002116872,0.00024922396,0.001194892,0.0006027244,0.18009812],"genre_scores_gemma":[0.6032107,0.005475998,0.34916237,0.0029091197,0.0018534852,0.00070858153,0.001594441,0.00037296952,0.034712356],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965295,0.0009287687,0.00038762816,0.0010442577,0.0008002441,0.0003096553],"domain_scores_gemma":[0.9967307,0.0012845197,0.00042566095,0.0005248725,0.00084907154,0.00018527388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023578417,0.00092982466,0.000706551,0.0035465457,0.003128427,0.004540233,0.0011814322,0.0017542964,0.0074620103],"category_scores_gemma":[0.0051832474,0.00046333924,0.0010817364,0.0033645302,0.009594751,0.010234947,0.003695484,0.002300027,0.001812928],"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":[0.000039127666,0.0000063861003,0.00017359064,0.000091355876,0.000008805686,0.00014062277,0.0005152408,0.0005215003,0.0011369103,0.9822204,0.0019621279,0.013183983],"study_design_scores_gemma":[0.00002939283,0.00009360685,0.0011039091,0.00028269802,0.00007186251,0.0014278106,0.00073692336,0.008242185,0.0038118581,0.7790165,0.2051079,0.00007530422],"about_ca_topic_score_codex":0.0032842348,"about_ca_topic_score_gemma":0.0024007235,"teacher_disagreement_score":0.0074620103,"about_ca_system_score_codex":0.002293853,"about_ca_system_score_gemma":0.0013282589,"threshold_uncertainty_score":0.024962962},"labels":[],"label_agreement":null},{"id":"W2123761689","doi":"10.1109/tsmcb.2005.850172","title":"Solving Minimum Distance Problems With Convex or Concave Bodies Using Combinatorial Global Optimization Algorithms","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Path Planning Algorithms","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 New Brunswick","funders":"","keywords":"Mathematical optimization; Simulated annealing; Optimization problem; Regular polygon; Combinatorial optimization; Mathematics; Algorithm; Global optimization; Computer science; Geometry","score_opus":0.027052218396942124,"score_gpt":0.2511656824740416,"score_spread":0.22411346407709945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123761689","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":[0.003701847,0.00024765142,0.9937449,0.000090258785,0.000016774016,0.000033312226,0.000022884373,0.000141017,0.002001345],"genre_scores_gemma":[0.13833754,0.00070476136,0.8560537,0.00012358504,0.00007014773,0.00046021468,0.0002480969,0.00026790748,0.0037340801],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919504,0.0002939212,0.000050598737,0.00020101687,0.0001866398,0.000072729374],"domain_scores_gemma":[0.9982333,0.0013433726,0.00013411012,0.000101430895,0.00013869142,0.00004911206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012686773,0.0022383854,0.0023622091,0.0012811652,0.00076926034,0.00190215,0.0016566663,0.0024522254,0.0038981615],"category_scores_gemma":[0.0033839536,0.0011353245,0.0016824125,0.0017121832,0.0013655156,0.0020422623,0.0019393474,0.0019826274,0.0007150934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017488575,0.000029030321,0.00018208627,0.00008985557,0.000037455913,0.000042876833,0.000036850146,0.96468484,0.0006148003,0.012552832,0.0005634592,0.021148503],"study_design_scores_gemma":[0.000012006603,0.000018999042,0.000051294388,0.000011051658,0.000008386205,0.000019703984,0.000018255214,0.9841815,0.0003546572,0.01451062,0.0008062797,0.0000072049816],"about_ca_topic_score_codex":0.003770089,"about_ca_topic_score_gemma":0.0033774553,"teacher_disagreement_score":0.0038981615,"about_ca_system_score_codex":0.001148616,"about_ca_system_score_gemma":0.001373076,"threshold_uncertainty_score":0.013040662},"labels":[],"label_agreement":null},{"id":"W2123952665","doi":"10.1109/tsmcb.2009.2013723","title":"Achieving Microaggregation for Secure Statistical Databases Using Fixed-Structure Partitioning-Based Learning Automata","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Machine Learning and Algorithms","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":"Carleton University","funders":"","keywords":"Computer science; Learning automata; Database; Automaton; Data mining; Theoretical computer science","score_opus":0.021009208168299733,"score_gpt":0.2734805969734777,"score_spread":0.252471388805178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123952665","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":[0.051971257,0.00016026855,0.94630545,0.00021664385,0.000018054006,0.0000704182,0.00006718941,0.0004745612,0.00071609434],"genre_scores_gemma":[0.81218827,0.00012957433,0.18635435,0.00008850791,0.000024649073,0.00019565494,0.00015571607,0.00004458359,0.0008185999],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980755,0.00072509074,0.00021635683,0.000398541,0.00041227756,0.00017234903],"domain_scores_gemma":[0.9907987,0.005963999,0.0007615805,0.0014989967,0.000733342,0.00024336537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025032845,0.0005905846,0.0013746833,0.00078520225,0.00091511226,0.0016235767,0.0014858186,0.0011200886,0.001199721],"category_scores_gemma":[0.010303437,0.0003882067,0.0008464851,0.0010568348,0.0012710976,0.0023887656,0.0024379175,0.0011154265,0.0003094188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020235882,0.00009649015,0.0021881822,0.00009616751,0.00007306284,0.00015085445,0.0003032894,0.85578865,0.0045282827,0.036958624,0.0008826203,0.09873145],"study_design_scores_gemma":[0.000009210838,0.000037328697,0.000108224405,0.000004265383,0.000007261344,0.00003654858,0.000029129036,0.9809887,0.0016755579,0.016770808,0.0003257993,0.000007243575],"about_ca_topic_score_codex":0.001849482,"about_ca_topic_score_gemma":0.0018763177,"teacher_disagreement_score":0.0025032845,"about_ca_system_score_codex":0.0011455008,"about_ca_system_score_gemma":0.0015015862,"threshold_uncertainty_score":0.013238847},"labels":[],"label_agreement":null},{"id":"W2124227618","doi":"10.1109/tsmcb.2002.1018771","title":"COR: a methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Fuzzy rule; Set (abstract data type); Fuzzy logic; Simple (philosophy); Subspace topology; Artificial intelligence; Rule-based system; Data mining; Post hoc; Machine learning; Fuzzy set; Programming language","score_opus":0.06672284856173605,"score_gpt":0.30067016845736905,"score_spread":0.233947319895633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124227618","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":[0.0014725733,0.000058036585,0.99689734,0.00004399752,0.000027830645,0.00008704209,0.000015888489,0.00056765124,0.00082951615],"genre_scores_gemma":[0.057585496,0.0001108791,0.9401344,0.00019888658,0.000042065858,0.00032225912,0.00010428283,0.0001742363,0.0013275503],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99647444,0.0009824648,0.00022378779,0.0006055411,0.0015886899,0.00012501054],"domain_scores_gemma":[0.9934907,0.0028195486,0.00049435865,0.0016091478,0.0014385951,0.00014762967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00592327,0.0014173054,0.0011346996,0.0018893337,0.00070722535,0.0014462267,0.0036587615,0.0011948729,0.0035345508],"category_scores_gemma":[0.010840321,0.00067620847,0.0011304908,0.0010606025,0.0012662375,0.0019228964,0.0021958693,0.002115346,0.0012720192],"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":[0.00018684288,0.00035969116,0.0012596706,0.0005878686,0.00031143465,0.00033950264,0.00067419396,0.18479203,0.019749047,0.057528075,0.0050543286,0.7291573],"study_design_scores_gemma":[0.000088691915,0.0003223777,0.00024370088,0.00007485408,0.000081106475,0.000280907,0.00007472798,0.9270102,0.020195838,0.031814534,0.019760014,0.000053013828],"about_ca_topic_score_codex":0.0014478851,"about_ca_topic_score_gemma":0.001755281,"teacher_disagreement_score":0.00592327,"about_ca_system_score_codex":0.0006519585,"about_ca_system_score_gemma":0.0016008164,"threshold_uncertainty_score":0.03132564},"labels":[],"label_agreement":null},{"id":"W2124264087","doi":"10.1109/tsmcb.2010.2047257","title":"Fault Diagnosis in Discrete-Event Systems: Incomplete Models and Learning","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Petri Nets in System Modeling","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":"University of Waterloo; University of Toronto","funders":"","keywords":"Event (particle physics); Computer science; Abstraction; Process (computing); Set (abstract data type); Cover (algebra); Fault (geology); Artificial intelligence; Machine learning; Theoretical computer science; Engineering","score_opus":0.025975171594257048,"score_gpt":0.25463600858687424,"score_spread":0.2286608369926172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124264087","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":[0.014438451,0.0005209611,0.9834383,0.000620341,0.000018029097,0.000032321044,0.000051417705,0.00016763038,0.0007124087],"genre_scores_gemma":[0.73173606,0.0014571616,0.26486975,0.00020561142,0.00014653747,0.00018758235,0.0003107223,0.000064062064,0.0010224795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971396,0.0011431065,0.00018148567,0.00042135318,0.00094194885,0.00017253029],"domain_scores_gemma":[0.97873116,0.017361043,0.0013201054,0.0015305242,0.00077917054,0.0002780206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00466163,0.0010230552,0.0019735328,0.0014753663,0.0005955779,0.001870498,0.001980924,0.002026989,0.0010600681],"category_scores_gemma":[0.021578064,0.0008823432,0.0014167036,0.0009970564,0.0031008124,0.0043301983,0.0018965501,0.0023436295,0.000155215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008188404,0.00006900334,0.002045197,0.00022468166,0.00007414982,0.00022351432,0.00030020057,0.87678534,0.0007649692,0.08434285,0.00041742605,0.034670763],"study_design_scores_gemma":[0.000010524578,0.000022191572,0.0001777702,0.000026040534,0.000011727765,0.000050639723,0.000027794387,0.90304273,0.00077705056,0.09542544,0.0004155947,0.000012464013],"about_ca_topic_score_codex":0.0027063,"about_ca_topic_score_gemma":0.0019640042,"teacher_disagreement_score":0.00466163,"about_ca_system_score_codex":0.0016708307,"about_ca_system_score_gemma":0.0012676923,"threshold_uncertainty_score":0.024653375},"labels":[],"label_agreement":null},{"id":"W2124300031","doi":"10.1109/tsmcb.2009.2024949","title":"On Utilizing Association and Interaction Concepts for Enhancing Microaggregation in Secure Statistical Databases","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Data Mining Algorithms and Applications","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":"Carleton University","funders":"","keywords":"Association (psychology); Database; Computer science; Association rule learning; Information retrieval; Data mining; Psychology","score_opus":0.024928359286228944,"score_gpt":0.2984764440105066,"score_spread":0.27354808472427766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124300031","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":[0.016390553,0.0005317517,0.9817063,0.000263015,0.000027677777,0.00004977009,0.000038023936,0.00019686575,0.0007959927],"genre_scores_gemma":[0.43176627,0.0012145287,0.5644923,0.00034836924,0.00029839718,0.00019993405,0.00025193053,0.00007942901,0.0013488741],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9921928,0.002547954,0.00083779957,0.00088023307,0.0032439074,0.0002973081],"domain_scores_gemma":[0.9842329,0.008612474,0.002460311,0.0031031987,0.0012938969,0.00029724374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077068745,0.0010661945,0.0014392171,0.0028756643,0.0011046381,0.0032727197,0.0015739617,0.00088176917,0.001118784],"category_scores_gemma":[0.016823629,0.0004740375,0.0011816645,0.0046916027,0.0024748105,0.009656353,0.005829417,0.0023238952,0.0005103117],"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":[0.0005895489,0.0003327465,0.009405143,0.00032596348,0.0002505818,0.00031658477,0.0012921493,0.19438656,0.012875029,0.16780895,0.0016944173,0.6107223],"study_design_scores_gemma":[0.000030773077,0.00039093668,0.002143189,0.000061707164,0.000091710455,0.0006280037,0.00030576246,0.8712802,0.012697765,0.10469991,0.0075964397,0.000073667885],"about_ca_topic_score_codex":0.000861299,"about_ca_topic_score_gemma":0.0008407027,"teacher_disagreement_score":0.0077068745,"about_ca_system_score_codex":0.00093848165,"about_ca_system_score_gemma":0.0014251474,"threshold_uncertainty_score":0.04075837},"labels":[],"label_agreement":null},{"id":"W2127817500","doi":"10.1109/tsmcb.2005.862724","title":"An efficient dynamic system for real-time robot-path planning","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":130,"is_retracted":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":"Grid; Motion planning; Robot; Computer science; Path (computing); Point (geometry); Shortest path problem; Grid reference; Any-angle path planning; Dynamic programming; Mobile robot; Algorithm; Artificial intelligence; Mathematics; Theoretical computer science; Graph","score_opus":0.012962337982991106,"score_gpt":0.24434759832696715,"score_spread":0.23138526034397605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127817500","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":[0.00072157074,0.00006816011,0.9970925,0.00002978646,0.000023471885,0.000030336545,0.00002103011,0.00070654385,0.0013066719],"genre_scores_gemma":[0.08715501,0.00027970193,0.90767324,0.00007091267,0.000043235996,0.000430623,0.00024589885,0.00027362574,0.0038277276],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992343,0.00013357693,0.000039820316,0.00016922464,0.00034792218,0.000075209726],"domain_scores_gemma":[0.9996611,0.00013292374,0.000028043281,0.00006049244,0.00009117106,0.000026272617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055438635,0.0009108503,0.000945361,0.00066931127,0.000809992,0.0011276223,0.0018456304,0.00089500524,0.006697218],"category_scores_gemma":[0.0014399511,0.00054679584,0.00055137917,0.00069231936,0.000716626,0.001330835,0.001729341,0.0013059275,0.0022017697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016987546,0.000112625625,0.00033489135,0.00036097542,0.00005854497,0.00022338655,0.00019973375,0.5436459,0.021856505,0.09765265,0.008214015,0.3271709],"study_design_scores_gemma":[0.000045700028,0.000056850855,0.00008417354,0.000018132921,0.000016470298,0.00009005287,0.000020084584,0.9598457,0.0037421738,0.012459854,0.023597235,0.000023622355],"about_ca_topic_score_codex":0.0029552225,"about_ca_topic_score_gemma":0.0027484153,"teacher_disagreement_score":0.006697218,"about_ca_system_score_codex":0.0009001271,"about_ca_system_score_gemma":0.0013413324,"threshold_uncertainty_score":0.022404373},"labels":[],"label_agreement":null},{"id":"W2128610114","doi":"10.1109/tsmcb.2007.910534","title":"Stratification Approach for 3-D Euclidean Reconstruction of Nonrigid Objects From Uncalibrated Image Sequences","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Advanced Vision and Imaging","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":"University of Windsor","funders":"","keywords":"Artificial intelligence; Computer vision; Euclidean geometry; Stratification (seeds); Image (mathematics); Computer science; Mathematics; Pattern recognition (psychology); Geometry","score_opus":0.031389625646950504,"score_gpt":0.2511578457379745,"score_spread":0.219768220091024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128610114","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":[0.0039132494,0.000054798384,0.99574214,0.000019279714,0.0000052987016,0.000014359943,0.00000920028,0.00012801246,0.00011362515],"genre_scores_gemma":[0.08057986,0.0002544403,0.9178925,0.000050674153,0.000022235015,0.00006509005,0.0001711359,0.00008241849,0.0008815309],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944705,0.00012408035,0.00004015649,0.00013398689,0.00020523164,0.000049494138],"domain_scores_gemma":[0.99942005,0.00017844353,0.00011624694,0.00013388493,0.00011084197,0.00004061216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093760487,0.0008692229,0.0008982645,0.001134999,0.000344712,0.00060991646,0.0008165746,0.0007710735,0.0010919943],"category_scores_gemma":[0.0020364153,0.0006681567,0.001022696,0.0008415987,0.0007380205,0.0012544462,0.0010481686,0.0010178452,0.0007914112],"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":[0.00035703636,0.00008004716,0.0012590855,0.00027335362,0.0001034285,0.00033418922,0.00048311043,0.22791569,0.13110225,0.027239935,0.0017270205,0.6091248],"study_design_scores_gemma":[0.0000137874285,0.00008967651,0.00060358545,0.000014346341,0.000017544042,0.00019953655,0.000031520754,0.9693498,0.018852852,0.008245277,0.0025418187,0.000040223913],"about_ca_topic_score_codex":0.0021296283,"about_ca_topic_score_gemma":0.0023288457,"teacher_disagreement_score":0.0021296283,"about_ca_system_score_codex":0.0004949331,"about_ca_system_score_gemma":0.001027131,"threshold_uncertainty_score":0.0049586296},"labels":[],"label_agreement":null},{"id":"W2129479396","doi":"10.1109/tsmcb.2003.821869","title":"Modular Fuzzy-Reinforcement Learning Approach With Internal Model Capabilities for Multiagent Systems","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Modular design; Computer science; Reinforcement learning; Robustness (evolution); Fuzzy logic; Artificial intelligence; Multi-agent system; Architecture; State space; Domain (mathematical analysis); Internal model; Control (management); Mathematics","score_opus":0.022985664478799343,"score_gpt":0.22860031637009612,"score_spread":0.20561465189129677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129479396","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":[0.0076460233,0.00013414242,0.99059314,0.00008862891,0.000017131742,0.0000205412,0.00001008486,0.00014116526,0.0013492313],"genre_scores_gemma":[0.7936647,0.0002837783,0.20356183,0.00007015496,0.00006330518,0.00017770435,0.000045111457,0.000033692646,0.0020998635],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995572,0.00014994614,0.000023320512,0.00007905601,0.00014804085,0.000042398642],"domain_scores_gemma":[0.99941814,0.00025652503,0.00008404465,0.0000770668,0.00012411995,0.000040108866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010485346,0.0007266714,0.0007997185,0.0004124712,0.0003487507,0.000691304,0.0011207589,0.00078367244,0.0018001195],"category_scores_gemma":[0.0018573542,0.00027863227,0.0008056152,0.00032249247,0.0007384602,0.0009520357,0.0009751084,0.001121037,0.0003116056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003470994,0.00004782459,0.00031870577,0.00006832007,0.000059761067,0.000101602054,0.00009785381,0.9194805,0.00217043,0.04229224,0.00039997333,0.034928028],"study_design_scores_gemma":[0.000008460437,0.000025833051,0.0000411404,0.0000036936212,0.000007017582,0.000012472109,0.0000036177269,0.9877771,0.00030598865,0.011482173,0.00032825474,0.0000042422034],"about_ca_topic_score_codex":0.0024868276,"about_ca_topic_score_gemma":0.0019379146,"teacher_disagreement_score":0.0024868276,"about_ca_system_score_codex":0.00083518296,"about_ca_system_score_gemma":0.00061549037,"threshold_uncertainty_score":0.006059706},"labels":[],"label_agreement":null},{"id":"W2129785219","doi":"10.1109/tsmcb.2009.2018137","title":"Improved Face Representation by Nonuniform Multilevel Selection of Gabor Convolution Features","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Face and Expression Recognition","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 British Columbia; University of British Columbia Hospital","funders":"","keywords":"Gabor wavelet; Pattern recognition (psychology); Artificial intelligence; Computer science; Face (sociological concept); Principal component analysis; Facial recognition system; Curse of dimensionality; Dimensionality reduction; Gabor filter; Dimension (graph theory); Representation (politics); Linear discriminant analysis; Wavelet; Mathematics; Computer vision; Feature extraction; Wavelet transform; Discrete wavelet transform","score_opus":0.015201415605786616,"score_gpt":0.2477303234335937,"score_spread":0.23252890782780708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129785219","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":[0.17335688,0.00053588906,0.82322854,0.000091029964,0.000054755532,0.000039325205,0.00012824875,0.0007063819,0.0018589143],"genre_scores_gemma":[0.74215716,0.00040947145,0.25451458,0.0000710505,0.000059908856,0.0000574722,0.00039776912,0.000073082796,0.0022595366],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976987,0.000034538007,0.000011789701,0.000051181225,0.000098766126,0.000033788772],"domain_scores_gemma":[0.99980885,0.00004085861,0.000031145995,0.000045365065,0.00006328764,0.000010596476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022838273,0.000331791,0.00058034086,0.0005683805,0.00014659936,0.00029830865,0.00033678097,0.00019757572,0.0009187383],"category_scores_gemma":[0.00068069284,0.00012419042,0.00050333585,0.00064728817,0.00014523484,0.000492853,0.0003925287,0.00026317107,0.0003430237],"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":[0.00036331953,0.0001057544,0.0025184548,0.0000676054,0.00005027491,0.00015297541,0.000057799993,0.044124585,0.20282806,0.0033559243,0.0027993333,0.7435759],"study_design_scores_gemma":[0.000016297114,0.00018751473,0.0056701223,0.000007711659,0.00005055667,0.0003843771,0.00002659438,0.9348841,0.055345383,0.0010421822,0.0023652068,0.00002007564],"about_ca_topic_score_codex":0.0015133519,"about_ca_topic_score_gemma":0.0014067328,"teacher_disagreement_score":0.0015133519,"about_ca_system_score_codex":0.00019756083,"about_ca_system_score_gemma":0.000242113,"threshold_uncertainty_score":0.0030735135},"labels":[],"label_agreement":null},{"id":"W2129968541","doi":"10.1109/tsmcb.2009.2032414","title":"Modeling a Student–Classroom Interaction in a Tutorial-<i>Like</i> System Using Learning Automata","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Machine Learning and Algorithms","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":"Carleton University","funders":"","keywords":"Computer science; Hierarchy; Context (archaeology); Process (computing); Mathematics education; Learning environment; Psychology","score_opus":0.01987429936882729,"score_gpt":0.2702755236944176,"score_spread":0.2504012243255903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129968541","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":[0.17847139,0.0002607882,0.79019463,0.0009998888,0.00010753369,0.00022769332,0.00035301535,0.0012610713,0.028123999],"genre_scores_gemma":[0.9225824,0.00019453102,0.06259285,0.00016321446,0.000042476575,0.00031585564,0.00024340811,0.00008284451,0.013782429],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993036,0.0002870274,0.000037730493,0.00016371117,0.00010292514,0.00010503706],"domain_scores_gemma":[0.99876827,0.0006774642,0.00011329112,0.000101390346,0.00018537026,0.00015415454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010162784,0.0005070681,0.0005221208,0.00042512224,0.0006783094,0.002017624,0.0014950957,0.0016379209,0.0097686425],"category_scores_gemma":[0.0020553255,0.0002831017,0.00069994957,0.00024309955,0.0009409277,0.0017179921,0.0016052871,0.0009869477,0.0011059501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027910218,0.00035282227,0.005729884,0.00018977908,0.0001163065,0.00082859537,0.0012401022,0.77542937,0.00845993,0.18197227,0.0021415025,0.023260372],"study_design_scores_gemma":[0.000027474316,0.00009092853,0.00036943017,0.000015805681,0.000023095925,0.000053672396,0.00009647782,0.9826293,0.0010339102,0.012876629,0.0027667063,0.000016566391],"about_ca_topic_score_codex":0.008031436,"about_ca_topic_score_gemma":0.0057507893,"teacher_disagreement_score":0.0097686425,"about_ca_system_score_codex":0.0012168173,"about_ca_system_score_gemma":0.00136619,"threshold_uncertainty_score":0.03267932},"labels":[],"label_agreement":null},{"id":"W2130130539","doi":"10.1109/tsmcb.2008.927249","title":"Score-Based Resampling Method for Evolutionary Algorithms","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Evolutionary Algorithms and Applications","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 Alberta","funders":"Korea Institute of Industrial Technology","keywords":"Resampling; Chromosome; Evolutionary algorithm; Computer science; Fraction (chemistry); Algorithm; Realization (probability); Function (biology); Selection (genetic algorithm); Process (computing); Score; Artificial intelligence; Mathematical optimization; Mathematics; Machine learning; Gene; Statistics; Biology; Genetics","score_opus":0.04447657491174278,"score_gpt":0.2769372254744446,"score_spread":0.23246065056270182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130130539","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":[0.0026860612,0.000120958306,0.9965354,0.000045878336,0.000042565043,0.00004136912,0.000010455294,0.00015866604,0.00035862048],"genre_scores_gemma":[0.13408041,0.00021326811,0.8632622,0.000112034046,0.00013538705,0.00032994055,0.00016267749,0.000118873555,0.0015852378],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99739134,0.0011882923,0.00012294731,0.00029831173,0.0009236125,0.000075464086],"domain_scores_gemma":[0.99700516,0.0015332825,0.0002111499,0.00034512908,0.000821941,0.0000832211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034161669,0.0008833463,0.0011431283,0.0013964489,0.00056962605,0.0007879891,0.0015450596,0.0010789401,0.0014774224],"category_scores_gemma":[0.010869412,0.00027003136,0.0008595261,0.00089224573,0.00078196044,0.0009341131,0.0008048418,0.0011245314,0.0005362672],"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":[0.00023728194,0.00018080274,0.0020269707,0.00024030115,0.00020972725,0.00019554881,0.00019912368,0.2999377,0.020200068,0.06541905,0.00345951,0.6076939],"study_design_scores_gemma":[0.000019881507,0.000079159196,0.00042975546,0.000010178224,0.0000221892,0.00009504051,0.00000955699,0.98669344,0.003605065,0.0062462124,0.0027660597,0.000023478031],"about_ca_topic_score_codex":0.0017764195,"about_ca_topic_score_gemma":0.0017804786,"teacher_disagreement_score":0.0034161669,"about_ca_system_score_codex":0.0005926012,"about_ca_system_score_gemma":0.0007344976,"threshold_uncertainty_score":0.018066645},"labels":[],"label_agreement":null},{"id":"W2130323712","doi":"10.1109/tsmcb.2004.843180","title":"Designing Stable MIMO Fuzzy Controllers","year":2005,"lang":"en","type":"letter","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","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 Waterloo","funders":"","keywords":"Control theory (sociology); Fuzzy logic; Controller (irrigation); Fuzzy control system; Computer science; Nonlinear system; Control engineering; MIMO; Open-loop controller; Extension (predicate logic); Transformation (genetics); Control (management); Artificial intelligence; Engineering; Closed loop","score_opus":0.020883502475990398,"score_gpt":0.21472348435275154,"score_spread":0.19383998187676116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130323712","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":[0.008596566,0.000161665,0.98562384,0.0000852586,0.000049090057,0.00006566571,0.000017054712,0.00025749355,0.005143358],"genre_scores_gemma":[0.5667527,0.0003549386,0.42800242,0.00020219202,0.000057143137,0.0002518212,0.00006505092,0.00004922792,0.0042646243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996815,0.000040917737,0.000016375097,0.00006512101,0.00017323936,0.000022927503],"domain_scores_gemma":[0.9997814,0.00008245376,0.000029424758,0.00003159445,0.00006619409,0.000008951641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003910189,0.0003271377,0.00027632067,0.0002940191,0.0004184118,0.0005162337,0.0005290345,0.0005038547,0.0013617728],"category_scores_gemma":[0.001033149,0.00021284736,0.00022135075,0.00016922234,0.000387502,0.00035335674,0.0004478035,0.00047301626,0.0005840356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014771652,0.000063129206,0.0005082169,0.0005554345,0.0000489207,0.0005240255,0.00041134766,0.36397836,0.16571902,0.11876034,0.0028675974,0.34641585],"study_design_scores_gemma":[0.00005435896,0.00016048606,0.0002330189,0.00003982927,0.000017019769,0.00018039839,0.00004795213,0.9364626,0.03149666,0.016748864,0.01453684,0.000022024966],"about_ca_topic_score_codex":0.0006399896,"about_ca_topic_score_gemma":0.0009361107,"teacher_disagreement_score":0.0013617728,"about_ca_system_score_codex":0.0004167443,"about_ca_system_score_gemma":0.0003698413,"threshold_uncertainty_score":0.0045556426},"labels":[],"label_agreement":null},{"id":"W2131279287","doi":"10.1109/tsmcb.2009.2026730","title":"Optimal Consensus Seeking in a Network of Multiagent Systems: An LMI Approach","year":2009,"lang":"en","type":"letter","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":78,"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":"Mathematical optimization; Computer science; Constraint (computer-aided design); Multi-agent system; Consensus; Controller (irrigation); Graph; Function (biology); Set (abstract data type); Mathematics; Theoretical computer science; Artificial intelligence","score_opus":0.027244280402909625,"score_gpt":0.23608421679552896,"score_spread":0.20883993639261933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131279287","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":[0.0024833088,0.00031976914,0.9877791,0.0010684328,0.00006576299,0.000027091144,0.000015392176,0.00009113411,0.008150048],"genre_scores_gemma":[0.68793684,0.002084765,0.29469046,0.0013367592,0.0004397019,0.0005492454,0.000100614365,0.00012168812,0.012739898],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951947,0.00017523233,0.000021463738,0.00008820626,0.0001663255,0.000029370569],"domain_scores_gemma":[0.99957484,0.00024437913,0.00004946007,0.000031698823,0.00008713815,0.000012520645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067703484,0.00059264613,0.00073377,0.00033357946,0.00047391665,0.00089330383,0.0008843249,0.0013998717,0.0023682648],"category_scores_gemma":[0.0014897593,0.00031445295,0.00026693507,0.00036733173,0.00095433934,0.00114667,0.00070985843,0.0013127945,0.00055291696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056075653,0.0000436718,0.00026530772,0.00029048737,0.000030014675,0.00053104246,0.00017815114,0.70116377,0.0073915925,0.2222167,0.006827007,0.06100628],"study_design_scores_gemma":[0.000009447013,0.000022948878,0.000030501355,0.000013320393,0.000003386813,0.00005114538,0.00001700529,0.97122353,0.0007219753,0.0248626,0.0030383137,0.000005882702],"about_ca_topic_score_codex":0.001151359,"about_ca_topic_score_gemma":0.0010748396,"teacher_disagreement_score":0.0023682648,"about_ca_system_score_codex":0.0012504827,"about_ca_system_score_gemma":0.00061564933,"threshold_uncertainty_score":0.0090729},"labels":[],"label_agreement":null},{"id":"W2131314118","doi":"10.1109/3477.915351","title":"Two-level tuning of fuzzy PID controllers","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fuzzy Logic and Control Systems","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":"Memorial University of Newfoundland","funders":"","keywords":"Control theory (sociology); Fuzzy logic; PID controller; Nonlinear system; Fuzzy control system; Computer science; Heuristics; Control engineering; Mathematics; Control (management); Engineering; Mathematical optimization; Temperature control; Artificial intelligence; Physics","score_opus":0.030947125890790367,"score_gpt":0.23644416163696885,"score_spread":0.20549703574617847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131314118","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":[0.016069055,0.0001535908,0.9734397,0.00006721029,0.000059267742,0.00011502025,0.00002269954,0.00089198136,0.009181394],"genre_scores_gemma":[0.7646596,0.00013850207,0.22883922,0.00012544486,0.000035634483,0.00023894799,0.00006974192,0.00011981762,0.0057730866],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885774,0.00015472437,0.00007440881,0.0002626126,0.00053211855,0.00011834224],"domain_scores_gemma":[0.99925333,0.0002445404,0.00006473937,0.00015562342,0.00024077855,0.000041026007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082234794,0.0006630597,0.0006564745,0.0005801625,0.00064718205,0.0018501519,0.00128596,0.0011250607,0.0039037738],"category_scores_gemma":[0.002311536,0.00038482767,0.00048592847,0.00031844186,0.00052630174,0.000891193,0.00094188156,0.0012275431,0.0013471287],"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":[0.00073839637,0.0003229478,0.0015744676,0.0006513914,0.00010502593,0.00026631533,0.00047779395,0.34610036,0.21244286,0.03734837,0.0031622157,0.3968099],"study_design_scores_gemma":[0.00008117875,0.0003115478,0.0009121534,0.000034268767,0.000024605544,0.00016229908,0.000029914048,0.9361922,0.045692947,0.008271318,0.008215557,0.000071994225],"about_ca_topic_score_codex":0.0012040915,"about_ca_topic_score_gemma":0.0008227638,"teacher_disagreement_score":0.0039037738,"about_ca_system_score_codex":0.000707927,"about_ca_system_score_gemma":0.00070344034,"threshold_uncertainty_score":0.013059437},"labels":[],"label_agreement":null},{"id":"W2133600728","doi":"10.1109/tsmcb.2005.848491","title":"Toward a Systems- and Control-Oriented Agent Framework","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Toronto Metropolitan University","funders":"","keywords":"Computer science; Distributed computing; Hybrid system; Scheme (mathematics); Control (management); Intelligent control; Multi-agent system; Control system; Core (optical fiber); Control engineering; Artificial intelligence; Engineering; Telecommunications; Machine learning","score_opus":0.021097410789381668,"score_gpt":0.2352026835462921,"score_spread":0.21410527275691044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133600728","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":[0.0013648657,0.0006778848,0.9858743,0.0011407675,0.00010368462,0.00004440539,0.00003275154,0.00019995628,0.010561309],"genre_scores_gemma":[0.13855933,0.0020595824,0.8500046,0.00057847175,0.000357784,0.00036136285,0.00013799882,0.00011031422,0.007830511],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991178,0.00030101245,0.000048385038,0.00012999075,0.0003312846,0.00007159655],"domain_scores_gemma":[0.9993137,0.00022538095,0.000057108944,0.00011501699,0.00018068777,0.000108095875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022025534,0.0010541797,0.00081927446,0.000821389,0.0008197516,0.0029611208,0.002641246,0.0018081865,0.0020057925],"category_scores_gemma":[0.001278545,0.00052226067,0.0011454925,0.000635497,0.0030581423,0.0031400062,0.002148065,0.00358117,0.0008584326],"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":[0.0000054992047,0.000017584118,0.000075843906,0.00005175989,0.000015029923,0.000050119103,0.00011592166,0.03387804,0.0004360717,0.9563508,0.00079228776,0.008210954],"study_design_scores_gemma":[0.000026891235,0.000042281048,0.0000818603,0.00007794495,0.00003029923,0.00005290936,0.00009346395,0.3316076,0.0008189219,0.5972607,0.0698852,0.000021853122],"about_ca_topic_score_codex":0.0037907243,"about_ca_topic_score_gemma":0.0031751492,"teacher_disagreement_score":0.0037907243,"about_ca_system_score_codex":0.0011969074,"about_ca_system_score_gemma":0.0026306417,"threshold_uncertainty_score":0.011648357},"labels":[],"label_agreement":null},{"id":"W2134282191","doi":"10.1109/tsmcb.2008.2010523","title":"Fundamentals of a Fuzzy-Logic-Based Generalized Theory of Stability","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fuzzy Systems and Optimization","field":"Mathematics","cited_by":42,"is_retracted":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":"Stability (learning theory); Computer science; Boolean algebra; Fuzzy logic; Natural language; Dynamical systems theory; Semantics (computer science); Character (mathematics); Theoretical computer science; Mathematics; Artificial intelligence; Algorithm; Programming language; Machine learning","score_opus":0.05338992580566328,"score_gpt":0.27844689141143975,"score_spread":0.22505696560577648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134282191","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":[0.00766009,0.0052809925,0.94697803,0.0020221556,0.00039897708,0.0000855923,0.00027511164,0.00019111826,0.03710792],"genre_scores_gemma":[0.6146611,0.011468233,0.35446605,0.0013478497,0.0018365347,0.0004884182,0.0003886289,0.00009579618,0.015247302],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99869424,0.00030708217,0.00012028641,0.00024974174,0.0005371887,0.0000915473],"domain_scores_gemma":[0.99913484,0.00041413747,0.00010062817,0.00008878761,0.0002226907,0.00003887265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015803628,0.0007616694,0.000927872,0.002119236,0.0009516395,0.0027833607,0.0016444245,0.0016034746,0.003307169],"category_scores_gemma":[0.0020031312,0.00026722942,0.0015304091,0.0015375408,0.004147746,0.0031230783,0.0014069732,0.002305566,0.00065997115],"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":[0.000005381729,0.00000592936,0.00009534986,0.00007173025,0.000017706241,0.00008605455,0.00018731228,0.009546934,0.00085085444,0.9793571,0.00080008217,0.008975538],"study_design_scores_gemma":[0.000008914129,0.00003099963,0.00020271829,0.00008535446,0.000018914596,0.00014258675,0.000069437374,0.060073834,0.00046894306,0.9145688,0.024306353,0.000023214863],"about_ca_topic_score_codex":0.0029634065,"about_ca_topic_score_gemma":0.0014850886,"teacher_disagreement_score":0.003307169,"about_ca_system_score_codex":0.0022704613,"about_ca_system_score_gemma":0.0011211295,"threshold_uncertainty_score":0.016473413},"labels":[],"label_agreement":null},{"id":"W2135107686","doi":"10.1109/tsmcb.2002.999810","title":"Assigning cells to switches in cellular mobile networks using taboo search","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"graph theory and CDMA systems","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Taboo; Computer science; Heuristic; Process (computing); Mathematical optimization; Artificial intelligence; Mathematics","score_opus":0.02238897447906088,"score_gpt":0.21005568005814026,"score_spread":0.18766670557907938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135107686","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":[0.12573238,0.0011699182,0.8644271,0.00030988452,0.000060295002,0.00023582215,0.00015182627,0.0008176962,0.0070951614],"genre_scores_gemma":[0.58250266,0.00059124245,0.4135311,0.00018303761,0.000029159215,0.00038483285,0.0002541143,0.00013539715,0.0023884848],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917465,0.00053836306,0.000027023581,0.00007174012,0.00010790513,0.00008020694],"domain_scores_gemma":[0.9984475,0.0011234065,0.00013583763,0.000110589834,0.00012406032,0.00005878386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015853748,0.0007233942,0.0007870008,0.0015207067,0.0008686032,0.001373626,0.001279464,0.0012916194,0.002749483],"category_scores_gemma":[0.004778659,0.00047100958,0.00043443392,0.001910786,0.0011678921,0.0014770179,0.0008086498,0.0006196727,0.0004574585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013608274,0.000065149405,0.0007517773,0.00005506951,0.000033066022,0.000033070915,0.000107071515,0.9269849,0.0008679384,0.008217271,0.0009059306,0.061842598],"study_design_scores_gemma":[0.000039981816,0.00006528112,0.000113481794,0.000017886568,0.000013653803,0.000017259597,0.000060279785,0.98836374,0.00072194805,0.009626741,0.0009515307,0.000008297973],"about_ca_topic_score_codex":0.0060001877,"about_ca_topic_score_gemma":0.0061741653,"teacher_disagreement_score":0.0060001877,"about_ca_system_score_codex":0.0010819471,"about_ca_system_score_gemma":0.00112861,"threshold_uncertainty_score":0.011930525},"labels":[],"label_agreement":null},{"id":"W2135183970","doi":"10.1109/tsmcb.2003.817073","title":"A two-phase genetic K-means algorithm for placement of radioports in cellular networks","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Wireless Communication Networks Research","field":"Computer Science","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 Saskatchewan","funders":"","keywords":"Simplex algorithm; Algorithm; Genetic algorithm; Computation; Computer science; Simplex; Range (aeronautics); Channel (broadcasting); Phase (matter); Wireless; Mathematical optimization; Mathematics; Linear programming; Engineering; Telecommunications","score_opus":0.023276233523270358,"score_gpt":0.27910359022476505,"score_spread":0.2558273567014947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135183970","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":[0.0064096614,0.00006783983,0.992498,0.00005185932,0.000018124509,0.000038498423,0.0000103402,0.0002638863,0.00064191764],"genre_scores_gemma":[0.16342898,0.00010790445,0.83425146,0.000095636075,0.00002680951,0.00035986525,0.000077879806,0.00007922379,0.0015721753],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948657,0.00019454739,0.000023901444,0.000092389964,0.00015638064,0.00004618095],"domain_scores_gemma":[0.9994062,0.00033913532,0.00006187175,0.000042643962,0.00012218139,0.00002796174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007890122,0.00089948974,0.0010391066,0.00088824745,0.00083197554,0.00068556226,0.0013145492,0.0014449168,0.001335514],"category_scores_gemma":[0.0021028947,0.0006843083,0.0006390939,0.0008830732,0.00088513707,0.0007843404,0.0009206732,0.00077137374,0.00043472621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007398802,0.000058427115,0.00038082898,0.000050383074,0.000049528317,0.000036189136,0.000094043,0.87326074,0.002249625,0.0051369057,0.0011169967,0.117492385],"study_design_scores_gemma":[0.000025685795,0.000034300072,0.00005434603,0.0000037510672,0.000006398427,0.000018162422,0.00001126606,0.99668014,0.00061053724,0.0020381347,0.00050889683,0.00000835408],"about_ca_topic_score_codex":0.007835344,"about_ca_topic_score_gemma":0.0075504277,"teacher_disagreement_score":0.007835344,"about_ca_system_score_codex":0.00080968725,"about_ca_system_score_gemma":0.0016547312,"threshold_uncertainty_score":0.015579522},"labels":[],"label_agreement":null},{"id":"W2135219152","doi":"10.1109/tsmcb.2008.2006368","title":"Adaptive Neural Control for a Class of Uncertain Nonlinear Systems in Pure-Feedback Form With Hysteresis Input","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":214,"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":"Control theory (sociology); Nonlinear system; Tracking error; Hysteresis; Artificial neural network; Bounded function; Adaptive control; Lyapunov function; Function (biology); Class (philosophy); Mathematics; Backstepping; Computer science; Control (management); Mathematical analysis; Artificial intelligence; Physics","score_opus":0.014435978831177424,"score_gpt":0.20073398214645466,"score_spread":0.18629800331527724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135219152","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":[0.10550493,0.0012890946,0.8866704,0.00018816207,0.00009192352,0.000043781485,0.0000330023,0.00014672255,0.006032063],"genre_scores_gemma":[0.9763423,0.0005523919,0.019426597,0.000060642116,0.000076446595,0.000065433465,0.00003411103,0.000008293329,0.003433671],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998392,0.000029253844,0.000009422238,0.0000430802,0.00005906599,0.000019928357],"domain_scores_gemma":[0.99980205,0.00008462096,0.000043583776,0.000016006885,0.00004741277,0.0000063209973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029461086,0.00049604516,0.00038170416,0.00015806395,0.00023760967,0.00048079767,0.0006756619,0.00053021987,0.00071414403],"category_scores_gemma":[0.0006463471,0.00015236101,0.00026672852,0.00022079657,0.0005088043,0.0005686824,0.00043938617,0.00044949088,0.00009041186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011865837,0.00009863023,0.0011810749,0.00046312422,0.00009279141,0.00055390666,0.00023411757,0.8133431,0.034759354,0.053451438,0.0008231356,0.0948807],"study_design_scores_gemma":[0.0000072882735,0.000045383687,0.00028320964,0.000004784679,0.000007613566,0.000038806622,0.0000134411075,0.9948206,0.0009971646,0.0031038653,0.0006731013,0.000004698103],"about_ca_topic_score_codex":0.0014659027,"about_ca_topic_score_gemma":0.0017744893,"teacher_disagreement_score":0.0014659027,"about_ca_system_score_codex":0.0002605357,"about_ca_system_score_gemma":0.0002740457,"threshold_uncertainty_score":0.0029147863},"labels":[],"label_agreement":null},{"id":"W2135738110","doi":"10.1109/3477.979962","title":"The hierarchical expert tuning of PID controllers using tools of soft computing","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"PID controller; Soft computing; Gain scheduling; Computer science; Control engineering; Process (computing); Scheme (mathematics); Identification (biology); Control theory (sociology); Control (management); Engineering; Artificial intelligence; Artificial neural network; Temperature control","score_opus":0.026123611626484963,"score_gpt":0.22816000213491816,"score_spread":0.2020363905084332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135738110","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":[0.013425476,0.00010438833,0.98409295,0.00005020323,0.000014741857,0.00001945656,0.0000057010866,0.00012369757,0.0021633294],"genre_scores_gemma":[0.7732276,0.00020498701,0.224372,0.00009275755,0.000046291705,0.00009066882,0.000023651588,0.0000393063,0.0019028406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947816,0.00011608253,0.000024380093,0.00010461301,0.00021181237,0.00006494281],"domain_scores_gemma":[0.9979845,0.0013150078,0.0002018294,0.00024633962,0.00018785981,0.000064509964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087858975,0.0005119499,0.000516413,0.0005532641,0.00038929944,0.0008730382,0.00077113375,0.00063452113,0.001692069],"category_scores_gemma":[0.0044230605,0.0002514216,0.00051242346,0.0004376226,0.0011364497,0.0008486851,0.0009836906,0.0010543634,0.000302644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008166126,0.00008402261,0.00042051714,0.00011038941,0.00003409658,0.00009953877,0.00017197298,0.8366912,0.013548683,0.05947701,0.00046681767,0.08881418],"study_design_scores_gemma":[0.000005092274,0.000027197608,0.00008345732,0.0000035262692,0.0000036780941,0.000009654411,0.000006755419,0.983833,0.0018508136,0.013933074,0.00023852265,0.0000051366446],"about_ca_topic_score_codex":0.0012245231,"about_ca_topic_score_gemma":0.00093282305,"teacher_disagreement_score":0.001692069,"about_ca_system_score_codex":0.00056862086,"about_ca_system_score_gemma":0.0006320378,"threshold_uncertainty_score":0.0056604743},"labels":[],"label_agreement":null},{"id":"W2136345626","doi":"10.1109/tsmcb.2009.2027220","title":"Modeling a Student's Behavior in a Tutorial-<i>Like</i> System Using Learning Automata","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Artificial intelligence","score_opus":0.019950517543016643,"score_gpt":0.26852908187105234,"score_spread":0.2485785643280357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136345626","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":[0.12774983,0.00012879475,0.8650799,0.00023045,0.00004336308,0.00012407966,0.00020439766,0.0012672297,0.0051719663],"genre_scores_gemma":[0.8891138,0.00018096916,0.104081534,0.00009113222,0.00003298948,0.00029241346,0.00021399894,0.00010596172,0.0058872704],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927586,0.00021644113,0.000047539677,0.0002124516,0.000142647,0.00010513758],"domain_scores_gemma":[0.99848443,0.0007571575,0.0001945862,0.00023879406,0.00021816556,0.0001068918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007934429,0.0006615966,0.0005389197,0.00040789245,0.00046168573,0.0014739619,0.0015352936,0.0013145449,0.003237637],"category_scores_gemma":[0.002585514,0.00029464514,0.00082001835,0.00019676975,0.0010023538,0.001644819,0.0012820686,0.0012048153,0.00063068204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024349676,0.00023277452,0.008335304,0.0001798495,0.0000894054,0.0003902415,0.0007419079,0.87591755,0.020435765,0.0689727,0.0007334988,0.023727464],"study_design_scores_gemma":[0.00000966177,0.000057390065,0.0003220303,0.000008752955,0.000014425157,0.000029664769,0.000026533593,0.99013937,0.002341988,0.006056939,0.0009818091,0.000011422911],"about_ca_topic_score_codex":0.005033744,"about_ca_topic_score_gemma":0.0033754928,"teacher_disagreement_score":0.005033744,"about_ca_system_score_codex":0.0008749553,"about_ca_system_score_gemma":0.0012154834,"threshold_uncertainty_score":0.010830939},"labels":[],"label_agreement":null},{"id":"W2137188358","doi":"10.1109/tsmcb.2002.1033181","title":"An efficient algorithm for automatically generating multivariable fuzzy systems by Fourier series method","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fuzzy Logic and Control Systems","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 Northern British Columbia","funders":"","keywords":"Multivariable calculus; Algorithm; Fuzzy set; Fuzzy logic; Mathematics; Fuzzy control system; Fuzzy number; Fourier series; Membership function; Computer science; Artificial intelligence","score_opus":0.018087508734888718,"score_gpt":0.24142827675212042,"score_spread":0.2233407680172317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137188358","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":[0.00048496475,0.000011748051,0.9989255,0.000011852405,0.000004429304,0.000015641877,0.000006072796,0.00017790456,0.00036184493],"genre_scores_gemma":[0.026136823,0.000042926244,0.97277653,0.00002043773,0.000011983116,0.00010859589,0.000037781112,0.00006266793,0.00080225815],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999461,0.000120960365,0.000032484895,0.00007975603,0.00026893057,0.000036908634],"domain_scores_gemma":[0.9994535,0.0003156474,0.000030768788,0.000055647797,0.00013305566,0.000011455155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010019033,0.0006623662,0.0006714714,0.0008685465,0.0005618278,0.00065573043,0.0010520703,0.00064572773,0.005848563],"category_scores_gemma":[0.002176525,0.00041423895,0.00074844866,0.00054879615,0.00061795965,0.0009584512,0.00088246004,0.0010719534,0.001702314],"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":[0.000101246456,0.000067604444,0.0002950873,0.00027117637,0.000054868855,0.00018723219,0.00027994657,0.16084592,0.040305257,0.1194182,0.0032195516,0.67495394],"study_design_scores_gemma":[0.000051113366,0.00007050296,0.00013099443,0.000021256117,0.000021750233,0.00017055216,0.000030894982,0.94387406,0.01394372,0.032912098,0.0087453555,0.000027736003],"about_ca_topic_score_codex":0.0012193472,"about_ca_topic_score_gemma":0.0014595697,"teacher_disagreement_score":0.005848563,"about_ca_system_score_codex":0.00046511882,"about_ca_system_score_gemma":0.00076807407,"threshold_uncertainty_score":0.019565344},"labels":[],"label_agreement":null},{"id":"W2138041254","doi":"10.1109/tsmcb.2002.1049608","title":"Generalized pursuit learning schemes: new families of continuous and discretized learning automata","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":158,"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":"Action (physics); Learning automata; Discretization; Computer science; Scheme (mathematics); Artificial intelligence; Estimator; Algorithm; Automaton; Machine learning; Mathematical optimization; Mathematics; Statistics","score_opus":0.016794056746851457,"score_gpt":0.22871380987604678,"score_spread":0.2119197531291953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138041254","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":[0.014728171,0.000944629,0.98114246,0.00026182615,0.000071465576,0.00008322273,0.00006200646,0.0003292377,0.0023770265],"genre_scores_gemma":[0.4015464,0.0013897109,0.5914036,0.00029951372,0.00014706499,0.0005065124,0.00018148674,0.000111522575,0.004414235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99895704,0.00036255116,0.000073792966,0.00017163662,0.00036269554,0.00007223294],"domain_scores_gemma":[0.9970085,0.0017131466,0.0002649273,0.0005194044,0.00036344994,0.00013057346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020428163,0.00066682685,0.0008576555,0.0008474721,0.00052453333,0.0016526568,0.0019513553,0.0013872813,0.0022892142],"category_scores_gemma":[0.009335551,0.00038430103,0.0008622396,0.00087417365,0.0020431022,0.00284361,0.002414386,0.0021402328,0.00056381343],"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":[0.00014674978,0.00006735735,0.0011959877,0.00022510852,0.000072509094,0.00009499832,0.00027558027,0.48473603,0.004067981,0.32608324,0.0028449127,0.18018952],"study_design_scores_gemma":[0.000022716464,0.00006065736,0.000091285634,0.000020044743,0.0000074767054,0.000048453607,0.000015999072,0.9362759,0.00052272936,0.060591888,0.002328503,0.0000144471915],"about_ca_topic_score_codex":0.001377335,"about_ca_topic_score_gemma":0.0012471629,"teacher_disagreement_score":0.0022892142,"about_ca_system_score_codex":0.0010327799,"about_ca_system_score_gemma":0.0009688419,"threshold_uncertainty_score":0.01080358},"labels":[],"label_agreement":null},{"id":"W2138697946","doi":"10.1109/3477.979960","title":"Hybrid resistive tactile sensing","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Resistive touchscreen; Tactile sensor; STRIPS; Computer science; Proximity sensor; Surface (topology); Grid; Electronic engineering; Flexibility (engineering); Dimension (graph theory); Set (abstract data type); Robot; Acoustics; Engineering; Electrical engineering; Artificial intelligence; Computer vision; Physics; Mathematics","score_opus":0.024640498468169195,"score_gpt":0.20949414726404475,"score_spread":0.18485364879587557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138697946","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":[0.08021285,0.0019069806,0.88820523,0.00029861048,0.0003773588,0.00014864566,0.00014926474,0.0020906369,0.02661046],"genre_scores_gemma":[0.6773683,0.0008252033,0.30712458,0.0004430848,0.000161093,0.00018748897,0.00014492212,0.00008663488,0.013658808],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994295,0.00006710517,0.000027659506,0.000109978544,0.0003240397,0.000041604442],"domain_scores_gemma":[0.9995939,0.00017011902,0.000057625897,0.000074584765,0.0000722874,0.000031376734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022719169,0.00041480875,0.00043017862,0.00048522378,0.0002736353,0.000654579,0.0013156466,0.00073998503,0.0036526548],"category_scores_gemma":[0.00065554044,0.00028019867,0.00032090378,0.00040757196,0.00045797988,0.0012849224,0.001020673,0.00040713334,0.0011541938],"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":[0.00029254632,0.00012149876,0.0005917682,0.00060212624,0.00006025085,0.0006595277,0.00015611318,0.017352523,0.7384653,0.023871614,0.0023861853,0.21544062],"study_design_scores_gemma":[0.00012945214,0.0016381679,0.0024285358,0.00010099228,0.00011806935,0.0046353308,0.00015240307,0.3011275,0.58317065,0.024764458,0.08151974,0.00021466057],"about_ca_topic_score_codex":0.00008113087,"about_ca_topic_score_gemma":0.0001892327,"teacher_disagreement_score":0.0036526548,"about_ca_system_score_codex":0.00018820273,"about_ca_system_score_gemma":0.00011784961,"threshold_uncertainty_score":0.012219369},"labels":[],"label_agreement":null},{"id":"W2139893869","doi":"10.1109/tsmcb.2003.808190","title":"Recursive information granulation: aggregation and interpretation issues","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":65,"is_retracted":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":"Granulation; Cluster analysis; Data mining; Relevance (law); Computer science; Granular computing; Set (abstract data type); Fuzzy set; Interpretation (philosophy); Algorithm; Fuzzy logic; Data set; Rough set; Artificial intelligence; Engineering","score_opus":0.013233137728997068,"score_gpt":0.22800712878756157,"score_spread":0.2147739910585645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139893869","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":[0.0057969107,0.0020435282,0.9876013,0.0013792822,0.00007270948,0.00007751895,0.00006739043,0.00014863064,0.0028128221],"genre_scores_gemma":[0.29590827,0.002776097,0.69774944,0.0005629341,0.0006474529,0.0003871455,0.000234032,0.00017994805,0.001554631],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9917344,0.0032918612,0.00096997916,0.001278057,0.0023792998,0.00034638238],"domain_scores_gemma":[0.96660054,0.023521964,0.001928003,0.0053924,0.0022419104,0.0003152215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0102975555,0.0007317387,0.0021361236,0.003547169,0.001396244,0.0068817665,0.0022614044,0.0015357337,0.0021255983],"category_scores_gemma":[0.03925767,0.00081285404,0.0021111558,0.0039592003,0.0064011514,0.009430354,0.0037622724,0.0027411166,0.00036342582],"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":[0.000043530774,0.000019977433,0.0006183305,0.00029251963,0.0000643868,0.00015421097,0.00082930055,0.01911102,0.001267126,0.89807856,0.0014202165,0.078100875],"study_design_scores_gemma":[0.000016638709,0.000030587456,0.00047937516,0.00009786185,0.000042519645,0.00020930222,0.00016840005,0.068791784,0.0015679988,0.91867775,0.009873697,0.00004424136],"about_ca_topic_score_codex":0.0012675896,"about_ca_topic_score_gemma":0.0009059229,"teacher_disagreement_score":0.0102975555,"about_ca_system_score_codex":0.0020832056,"about_ca_system_score_gemma":0.0010622183,"threshold_uncertainty_score":0.054459333},"labels":[],"label_agreement":null},{"id":"W2140223269","doi":"10.1109/tsmcb.2009.2036443","title":"A Gradient-Descent-Based Approach for Transparent Linguistic Interface Generation in Fuzzy Models","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","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 Alberta","funders":"","keywords":"Interpretability; Interface (matter); Computer science; Fuzzy logic; Artificial intelligence; Gradient descent; Decision tree; Fuzzy set; Natural language processing; Machine learning; Linguistics","score_opus":0.05159735027703299,"score_gpt":0.25377701975022693,"score_spread":0.20217966947319393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140223269","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":[0.002285568,0.000030474286,0.9970299,0.00004977616,0.000010057541,0.000028928183,0.000006206526,0.00018112664,0.00037792776],"genre_scores_gemma":[0.16774988,0.0000861652,0.8294651,0.00016387484,0.00004161316,0.0002424661,0.00010449103,0.00019104885,0.0019552724],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992131,0.00036715282,0.00004642347,0.000093450326,0.00023037249,0.000049469625],"domain_scores_gemma":[0.9986737,0.000655791,0.00010921031,0.00013006898,0.0003750156,0.000056297933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020373545,0.00094599527,0.0011256745,0.00096260494,0.0006204782,0.00084196485,0.0013902435,0.0013487802,0.0018204446],"category_scores_gemma":[0.0051328447,0.00064251275,0.001035286,0.0006367089,0.0007233288,0.0011546974,0.0012386333,0.0014985144,0.0005086285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009996286,0.00016125567,0.0005556488,0.00013162068,0.00007070098,0.00018385019,0.0002270667,0.765315,0.007981029,0.03296769,0.0033614659,0.1889447],"study_design_scores_gemma":[0.000005020329,0.000015506868,0.000026502938,0.0000028420475,0.0000030001488,0.0000094401585,0.0000029680282,0.9969404,0.0003352035,0.0024176936,0.0002380011,0.0000034388383],"about_ca_topic_score_codex":0.0032186022,"about_ca_topic_score_gemma":0.0032004397,"teacher_disagreement_score":0.0032186022,"about_ca_system_score_codex":0.0006747391,"about_ca_system_score_gemma":0.00094831904,"threshold_uncertainty_score":0.010774732},"labels":[],"label_agreement":null},{"id":"W2140526691","doi":"10.1109/tsmcb.2003.820595","title":"Design of a Novel Knowledge-Based Fault Detection and Isolation Scheme","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fault detection and isolation; Artificial neural network; Cluster analysis; Computer science; Scheme (mathematics); Fault (geology); Pattern recognition (psychology); Artificial intelligence; Feature (linguistics); Matching (statistics); Wavelet; Data mining; Real-time computing; Mathematics","score_opus":0.019109052824004248,"score_gpt":0.2228192705765736,"score_spread":0.20371021775256937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140526691","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":[0.005920437,0.000080669044,0.99238354,0.00005746175,0.00003601778,0.00004707659,0.000012179471,0.00038056835,0.0010821737],"genre_scores_gemma":[0.60609865,0.00016557642,0.39011192,0.00015967808,0.00006088341,0.00021111616,0.000074468546,0.00002932506,0.0030883828],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966514,0.000026730628,0.000025785706,0.00012598526,0.00011273221,0.00004371021],"domain_scores_gemma":[0.9996567,0.000076544784,0.00007367322,0.000053424847,0.00011520601,0.000024527348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041684997,0.0005074532,0.0006193996,0.00039890973,0.0004336695,0.0005098714,0.0014977911,0.00093064725,0.0021274255],"category_scores_gemma":[0.000823199,0.00023684901,0.0003030534,0.00022807678,0.00043434618,0.0010964319,0.00073605985,0.0006057549,0.00056726945],"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":[0.00040095852,0.0002852235,0.00079428527,0.00050162233,0.000098278695,0.000379541,0.00025949127,0.19588229,0.19285737,0.03589662,0.0023146716,0.57032967],"study_design_scores_gemma":[0.000064959306,0.00024243385,0.00038683965,0.000019408946,0.000038336333,0.00022324492,0.000017846525,0.9559125,0.03483788,0.0039230073,0.004312507,0.00002107022],"about_ca_topic_score_codex":0.00087218016,"about_ca_topic_score_gemma":0.0008540469,"teacher_disagreement_score":0.0021274255,"about_ca_system_score_codex":0.0004547531,"about_ca_system_score_gemma":0.00069871,"threshold_uncertainty_score":0.0071169734},"labels":[],"label_agreement":null},{"id":"W2140782543","doi":"10.1109/tsmcb.2003.810909","title":"Benchmarking attribute cardinality maps for database systems using the tpc-d specifications","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Advanced Database Systems and Queries","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":"Carleton University","funders":"","keywords":"Benchmarking; Computer science; Cardinality (data modeling); Query optimization; Benchmark (surveying); Data mining; Database; Histogram; Set (abstract data type); Software; Relational database; Online aggregation; Information retrieval; Sargable; Search engine; Artificial intelligence; Programming language; Image (mathematics)","score_opus":0.08332196498803661,"score_gpt":0.2780936541775184,"score_spread":0.1947716891894818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140782543","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":[0.10936564,0.0008601053,0.869294,0.0007029006,0.00018557177,0.00074201386,0.0031016886,0.008476021,0.007272073],"genre_scores_gemma":[0.5042811,0.00060656224,0.4872221,0.00024375148,0.000042360967,0.0006914437,0.0049843146,0.0006700306,0.0012582799],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97716796,0.0049662055,0.0026806004,0.0012031205,0.013284147,0.00069801806],"domain_scores_gemma":[0.95134866,0.022191705,0.002269168,0.012298386,0.011213138,0.0006789648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010617024,0.0009621424,0.00095701066,0.0024629862,0.00082598015,0.0038506966,0.0030954545,0.0013015103,0.0019581888],"category_scores_gemma":[0.06714927,0.00060900097,0.0010954823,0.0043833414,0.0011217267,0.0044887727,0.0024160957,0.0019307496,0.00063018274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011958719,0.0004782397,0.02289551,0.0014850128,0.0001673063,0.0004715636,0.0007802523,0.51000446,0.024528984,0.11171377,0.014582045,0.31169695],"study_design_scores_gemma":[0.000055895125,0.0002982818,0.0027716924,0.000066638044,0.000028365062,0.00031244406,0.00028413648,0.94162846,0.026075019,0.013342896,0.015063035,0.00007326669],"about_ca_topic_score_codex":0.0105632795,"about_ca_topic_score_gemma":0.007830346,"teacher_disagreement_score":0.010617024,"about_ca_system_score_codex":0.0025279834,"about_ca_system_score_gemma":0.004057412,"threshold_uncertainty_score":0.056148827},"labels":[],"label_agreement":null},{"id":"W2141078840","doi":"10.1109/tsmcb.2008.2004501","title":"<i>BLGAN</i>: Bayesian Learning and Genetic Algorithm for Supporting Negotiation With Incomplete Information","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Gwangju Institute of Science and Technology","keywords":"Negotiation; Adversary; Computer science; Bayesian probability; Genetic algorithm; Complete information; Mathematical proof; Scheme (mathematics); Artificial intelligence; Space (punctuation); Bayesian inference; Machine learning; Mathematical optimization; Algorithm; Mathematics; Mathematical economics; Computer security","score_opus":0.014902721988509527,"score_gpt":0.2249916901844345,"score_spread":0.21008896819592496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141078840","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":[0.0039404714,0.0005404344,0.9899767,0.00067450263,0.00005879563,0.00005506078,0.000032802876,0.0005193385,0.004201959],"genre_scores_gemma":[0.24342157,0.0012730219,0.7469832,0.0009751544,0.00014474914,0.0004193941,0.00022748967,0.00020341211,0.006352084],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986602,0.0006122629,0.000057604524,0.00016393547,0.00041137353,0.00009468459],"domain_scores_gemma":[0.9985201,0.000891788,0.00016764534,0.00011559748,0.00023814873,0.00006671524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025139458,0.0007952823,0.00081369333,0.0012409402,0.00057976507,0.0014397639,0.0016221397,0.0018984888,0.0023163182],"category_scores_gemma":[0.006908659,0.0004888111,0.00062591315,0.0012764358,0.0013234358,0.002091977,0.0014655155,0.0020244545,0.0007043768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016046567,0.00013299545,0.00227953,0.00019269034,0.00015930699,0.00020113838,0.00025600803,0.5468393,0.0035793486,0.12030368,0.012208075,0.31368738],"study_design_scores_gemma":[0.00001853228,0.00003569007,0.00023732407,0.000029563429,0.000017575587,0.000043276304,0.000018852543,0.9671777,0.0012760127,0.023873663,0.0072496305,0.00002215597],"about_ca_topic_score_codex":0.012279641,"about_ca_topic_score_gemma":0.009492346,"teacher_disagreement_score":0.012279641,"about_ca_system_score_codex":0.0015797542,"about_ca_system_score_gemma":0.0019474224,"threshold_uncertainty_score":0.024416327},"labels":[],"label_agreement":null},{"id":"W2143317258","doi":"10.1109/tsmcb.2005.852983","title":"Highly scalable and robust rule learner: performance evaluation and comparison","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Scalability; Data mining; Missing data; Set (abstract data type); Business intelligence; Simplicity; State (computer science); Knowledge extraction; Artificial intelligence; Machine learning; Algorithm; Database","score_opus":0.0260826067644924,"score_gpt":0.2476861809748204,"score_spread":0.221603574210328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143317258","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":[0.45616147,0.02326797,0.4539287,0.0025417695,0.0017404008,0.0018437223,0.0077770134,0.03742441,0.015314484],"genre_scores_gemma":[0.6376303,0.004674929,0.33386526,0.0005989633,0.00042955732,0.0009028223,0.014529449,0.0012738619,0.0060949023],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98940724,0.0032613308,0.0011691103,0.0019726132,0.003688354,0.00050145254],"domain_scores_gemma":[0.9673661,0.022524403,0.0008796877,0.0033834416,0.0050257556,0.0008206394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015088104,0.002169662,0.0032125758,0.0032048603,0.00085911097,0.0021017932,0.0047909613,0.0034007244,0.004078977],"category_scores_gemma":[0.036708932,0.00059286447,0.0011429802,0.004004532,0.00087257003,0.0044333125,0.002268794,0.0024661252,0.0025091316],"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":[0.004727763,0.0016769762,0.009076509,0.00086144253,0.0010965967,0.00043772766,0.00013357885,0.38529754,0.002989774,0.0017898666,0.01894886,0.57296336],"study_design_scores_gemma":[0.0004939095,0.0008344757,0.0021093094,0.00004785321,0.00014494183,0.00027591377,0.00010327592,0.98300296,0.0076316437,0.0024142878,0.0028845323,0.00005696551],"about_ca_topic_score_codex":0.012348138,"about_ca_topic_score_gemma":0.0057204557,"teacher_disagreement_score":0.015088104,"about_ca_system_score_codex":0.0016856005,"about_ca_system_score_gemma":0.0024325266,"threshold_uncertainty_score":0.07979441},"labels":[],"label_agreement":null},{"id":"W2144303191","doi":"10.1109/tsmcb.2002.1049616","title":"Discretized learning automata solutions to the capacity assignment problem for prioritized networks","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Discretization; Learning automata; Computer science; Heuristic; Mathematical optimization; Simulated annealing; Network packet; Genetic algorithm; Set (abstract data type); Automaton; Class (philosophy); Focus (optics); Theoretical computer science; Artificial intelligence; Algorithm; Mathematics","score_opus":0.0454457620888802,"score_gpt":0.24205965216824274,"score_spread":0.19661389007936253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144303191","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":[0.04544496,0.00043044504,0.94387,0.0005481622,0.00006802149,0.00004806057,0.00015194365,0.00030415537,0.0091341995],"genre_scores_gemma":[0.7702318,0.00029189495,0.22444996,0.00015372441,0.000036644506,0.00021743528,0.00020306645,0.000054237542,0.0043612714],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999684,0.000108291235,0.000016920869,0.0000620345,0.00007454049,0.0000543201],"domain_scores_gemma":[0.9990096,0.00064812193,0.00009222425,0.000075722885,0.000111089525,0.000063228785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003636287,0.00053414935,0.0007808298,0.00036662628,0.00042339548,0.0009231046,0.0009945438,0.0012413493,0.0035384798],"category_scores_gemma":[0.0021630072,0.00033780822,0.0005541782,0.00044879084,0.0010044139,0.00078521646,0.0007872558,0.0011585982,0.00025229086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023690009,0.000020957903,0.00015717484,0.000036120196,0.000012262105,0.00003512651,0.000044631422,0.96803635,0.00062271603,0.023267118,0.00039882932,0.007345009],"study_design_scores_gemma":[0.000009391079,0.000010076522,0.000021304064,0.0000029005967,0.0000022936201,0.0000065207996,0.0000076007414,0.98775524,0.00013466523,0.011717047,0.00033032132,0.0000026428577],"about_ca_topic_score_codex":0.004625055,"about_ca_topic_score_gemma":0.004972913,"teacher_disagreement_score":0.004625055,"about_ca_system_score_codex":0.0010988531,"about_ca_system_score_gemma":0.0011646581,"threshold_uncertainty_score":0.011837423},"labels":[],"label_agreement":null},{"id":"W2144639743","doi":"10.1109/tsmcb.2005.843975","title":"Genetically Optimized Fuzzy Decision Trees","year":2005,"lang":"en","type":"letter","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canada Research Chairs","keywords":"Decision tree; Generalization; Computer science; Artificial intelligence; Machine learning; Tree (set theory); Incremental decision tree; Fuzzy logic; Fuzzy set; Decision tree learning; Fitness function; Membership function; Defuzzification; Fuzzy number; Fuzzy classification; Genetic algorithm; Mathematics; Data mining","score_opus":0.017643137802662284,"score_gpt":0.22537477600204775,"score_spread":0.20773163819938548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144639743","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":[0.05471963,0.0010255176,0.93227154,0.00091178034,0.00014951226,0.00006941563,0.00010095573,0.0002403652,0.01051136],"genre_scores_gemma":[0.6165531,0.0007462985,0.3769519,0.00065881474,0.00008257593,0.00017192011,0.00021298126,0.000058542148,0.0045638722],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993499,0.00026834782,0.000025884561,0.00010157379,0.00020307756,0.000051223527],"domain_scores_gemma":[0.9990596,0.0005659102,0.00009798078,0.00009662709,0.0001466595,0.000033203112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008497261,0.0003748158,0.00068862224,0.00042616017,0.00041601178,0.00072340807,0.00075897085,0.0011583798,0.001088573],"category_scores_gemma":[0.0035942888,0.0002149728,0.00038001873,0.00072397286,0.00081335846,0.0007524133,0.00047515176,0.0010942698,0.00041125625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001041918,0.000053493077,0.00080360385,0.000100824596,0.000051294075,0.00028130595,0.00009324402,0.7367972,0.009272975,0.14327072,0.0025021327,0.10666909],"study_design_scores_gemma":[0.00001938462,0.000042881056,0.00016374512,0.000014066587,0.000008271946,0.000099919795,0.000010299564,0.9429135,0.0016310044,0.050923575,0.004160644,0.000012717303],"about_ca_topic_score_codex":0.0008032749,"about_ca_topic_score_gemma":0.0011157347,"teacher_disagreement_score":0.0011583798,"about_ca_system_score_codex":0.0010367058,"about_ca_system_score_gemma":0.00045470046,"threshold_uncertainty_score":0.0075218678},"labels":[],"label_agreement":null},{"id":"W2147271331","doi":"10.1109/tsmcb.2004.830345","title":"Phase-Based Dual-Microphone Robust Speech Enhancement","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":104,"is_retracted":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; Speech recognition; Reverberation; Microphone; Speech enhancement; Word error rate; Beamforming; Multilateration; Noise (video); SIGNAL (programming language); Pattern recognition (psychology); Artificial intelligence; Acoustics; Noise reduction; Telecommunications; Physics","score_opus":0.02311683342707415,"score_gpt":0.24670320270218904,"score_spread":0.22358636927511488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147271331","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":[0.013748084,0.00028518765,0.9835824,0.0000578174,0.00007414759,0.00003693305,0.00004311985,0.000739064,0.0014331633],"genre_scores_gemma":[0.12679256,0.00035696177,0.866205,0.00011205141,0.00006555401,0.000064653635,0.00017200405,0.00009349683,0.006137648],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995486,0.000059013193,0.000027372193,0.000098774784,0.00023129069,0.0000349222],"domain_scores_gemma":[0.9995278,0.000115575625,0.000054875203,0.00006852268,0.00020969697,0.000023496068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051146507,0.00074335036,0.0006100921,0.00044133136,0.00019127439,0.0005165302,0.00088307454,0.00081379566,0.0030021814],"category_scores_gemma":[0.0011627626,0.00035550553,0.00043809615,0.00027200932,0.000250725,0.00077160605,0.00077787286,0.0006066236,0.0024757264],"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":[0.0005883938,0.00010892841,0.00045891595,0.0001771009,0.000040060564,0.00014064775,0.00006203856,0.013271346,0.5913645,0.004381751,0.0013183615,0.38808808],"study_design_scores_gemma":[0.00006506102,0.00039807678,0.0010110897,0.00002038856,0.00006345971,0.0013757632,0.000021791322,0.29469666,0.6883116,0.0013845689,0.012602124,0.000049463255],"about_ca_topic_score_codex":0.00023771483,"about_ca_topic_score_gemma":0.0004460249,"teacher_disagreement_score":0.0030021814,"about_ca_system_score_codex":0.00017758335,"about_ca_system_score_gemma":0.00031070053,"threshold_uncertainty_score":0.010043263},"labels":[],"label_agreement":null},{"id":"W2147481281","doi":"10.1109/tsmcb.2008.925747","title":"Robust Stability Analysis of Guaranteed Cost Control for Impulsive Switched Systems","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Stability and Control of Uncertain Systems","field":"Engineering","cited_by":95,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Control theory (sociology); Class (philosophy); Cost control; Stability (learning theory); Control (management); Robust control; Computer science; Control system; Mathematics; Engineering","score_opus":0.033954724224067055,"score_gpt":0.22263139001921975,"score_spread":0.1886766657951527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147481281","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":[0.05004155,0.00071027904,0.9383383,0.00028211193,0.00007375165,0.000028294082,0.00004167465,0.00020720944,0.010276887],"genre_scores_gemma":[0.9858261,0.00035118923,0.010623972,0.000059084574,0.000052152598,0.000059603775,0.000051172854,0.0000346908,0.0029421276],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995466,0.000110221175,0.000017998658,0.00006966907,0.00020476918,0.00005064126],"domain_scores_gemma":[0.99931836,0.00031762416,0.00013192586,0.000030414474,0.00017875545,0.000022868804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006748935,0.00054362824,0.00043978484,0.00060009497,0.0002534534,0.0010076929,0.0006595427,0.00052067556,0.0019454781],"category_scores_gemma":[0.0020343524,0.00019861171,0.0005030792,0.00034532152,0.00075823633,0.00055581407,0.0005988177,0.0005838781,0.00016599732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013875452,0.000033673838,0.0003813945,0.00018705039,0.00009182578,0.0002689951,0.0001836562,0.79541093,0.012186515,0.16792637,0.0009726983,0.02221817],"study_design_scores_gemma":[0.0000066634166,0.000032181655,0.00012727035,0.0000044923063,0.000007302805,0.000013824971,0.00000860873,0.9882869,0.0005785981,0.010561655,0.0003676882,0.0000047709564],"about_ca_topic_score_codex":0.004223153,"about_ca_topic_score_gemma":0.0012355343,"teacher_disagreement_score":0.004223153,"about_ca_system_score_codex":0.0008827696,"about_ca_system_score_gemma":0.0005681469,"threshold_uncertainty_score":0.008397162},"labels":[],"label_agreement":null},{"id":"W2148908878","doi":"10.1109/tsmcb.2003.808178","title":"Learning-based resource optimization in asynchronous transfer mode (ATM) networks","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Network Traffic and Congestion Control","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":"Intelligent Mechatronic Systems (Canada); University of Waterloo","funders":"","keywords":"Asynchronous Transfer Mode; Computer science; Dynamic bandwidth allocation; Bandwidth (computing); Bandwidth allocation; Distributed computing; Artificial neural network; Nonlinear system; Computational complexity theory; Mathematical optimization; Artificial intelligence; Computer network; Algorithm; Mathematics","score_opus":0.009300234053721032,"score_gpt":0.20545281323621106,"score_spread":0.19615257918249002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148908878","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":[0.073652774,0.0006632202,0.92181957,0.00045096432,0.00003492031,0.000041479616,0.00002590384,0.00015298293,0.0031581349],"genre_scores_gemma":[0.95255417,0.0003810612,0.045157317,0.0000789655,0.000057845446,0.0000872308,0.00002814858,0.000021326554,0.0016340467],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954945,0.00019368951,0.000017788761,0.00006965585,0.000101008525,0.00006843854],"domain_scores_gemma":[0.9988752,0.0008318522,0.0001254399,0.000025655703,0.000106335974,0.000035596226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012635347,0.0005714685,0.0008291127,0.00038718886,0.00042382575,0.00075549306,0.00083085574,0.0009168643,0.00069163344],"category_scores_gemma":[0.0027393664,0.00034335026,0.0002757806,0.00056282815,0.0010525901,0.0010262595,0.0007414359,0.0008615846,0.000079099715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002032182,0.000012740789,0.00009846123,0.000013344532,0.0000056115937,0.000012725223,0.000011000806,0.98834455,0.0002338841,0.003191603,0.00010748879,0.007948155],"study_design_scores_gemma":[0.0000042545616,0.000008562185,0.000026197215,0.0000010128693,0.000001249165,0.0000019374222,0.0000019107624,0.99751943,0.00008852284,0.0022868975,0.000058777463,0.0000012423743],"about_ca_topic_score_codex":0.0069196606,"about_ca_topic_score_gemma":0.0038033777,"teacher_disagreement_score":0.0069196606,"about_ca_system_score_codex":0.0010515011,"about_ca_system_score_gemma":0.0008266124,"threshold_uncertainty_score":0.013758779},"labels":[],"label_agreement":null},{"id":"W2149753900","doi":"10.1109/tsmcb.2007.907036","title":"Comparing Human and Automatic Face Recognition Performance","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Facial recognition system; Face (sociological concept); Computer science; Artificial intelligence; Computer vision; Speech recognition; Pattern recognition (psychology); Sociology","score_opus":0.03772601261753666,"score_gpt":0.2499326494810211,"score_spread":0.21220663686348443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149753900","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":[0.86102617,0.0023495543,0.11643923,0.00021564229,0.00017459912,0.00015688472,0.0012524845,0.001324769,0.017060632],"genre_scores_gemma":[0.9623224,0.00048346326,0.033327613,0.00009459953,0.00009092438,0.00008639991,0.0013369208,0.000103119106,0.0021545233],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9907803,0.003153334,0.00051392976,0.0010690342,0.0041898796,0.0002935481],"domain_scores_gemma":[0.9820884,0.012136085,0.0010213864,0.0013670652,0.0032166457,0.0001704786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008166412,0.00043462368,0.00051492226,0.0023222188,0.000270284,0.00089539343,0.0005571712,0.0007615004,0.002782888],"category_scores_gemma":[0.020380318,0.00013795093,0.00043022336,0.0010919091,0.00063109095,0.0013782281,0.0007935169,0.00024403264,0.0010175984],"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":[0.0021099523,0.0005626821,0.11452694,0.0006144517,0.0007548852,0.00011860217,0.0006097503,0.047862425,0.059590787,0.003798456,0.003844523,0.7656065],"study_design_scores_gemma":[0.00010656628,0.005294506,0.5897196,0.00010501212,0.00022540169,0.001153694,0.00059796113,0.26834276,0.11999862,0.0040022773,0.010133117,0.00032043585],"about_ca_topic_score_codex":0.0016343178,"about_ca_topic_score_gemma":0.0016563169,"teacher_disagreement_score":0.008166412,"about_ca_system_score_codex":0.00047251652,"about_ca_system_score_gemma":0.000391149,"threshold_uncertainty_score":0.04318863},"labels":[],"label_agreement":null},{"id":"W2149789917","doi":"10.1109/tsmcb.2005.858409","title":"Kinematic analysis of a flexible six-DOF parallel mechanism","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Mechanisms and Dynamics","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 Saskatchewan","funders":"Tsinghua University","keywords":"Workspace; Mechanism (biology); Kinematics; Underactuation; Computer science; Screw theory; Control theory (sociology); Inverse kinematics; Parallel manipulator; Serial manipulator; Singularity; Degrees of freedom (physics and chemistry); Motion (physics); Control engineering; Artificial intelligence; Mathematics; Engineering; Robot; Geometry; Physics; Control (management); Classical mechanics","score_opus":0.011208106743003654,"score_gpt":0.20532651801144117,"score_spread":0.1941184112684375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149789917","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":[0.04071274,0.0004725738,0.9515865,0.000044584005,0.000060417326,0.00004250476,0.00004721776,0.00016671992,0.0068668],"genre_scores_gemma":[0.79461896,0.0010682476,0.1953652,0.000040359708,0.000054718188,0.00012077681,0.0001448208,0.000038997994,0.008547847],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998381,0.000021314796,0.000010997876,0.00003378499,0.0000823075,0.000013442176],"domain_scores_gemma":[0.9998696,0.00002263137,0.00004063175,0.000029945235,0.000028638322,0.000008574807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026084564,0.00040107648,0.00038677882,0.0006076047,0.00027683986,0.00038786454,0.0006514551,0.00049546536,0.002638535],"category_scores_gemma":[0.0004593565,0.00023459077,0.0006743029,0.00034433987,0.00041426712,0.00059757906,0.0005276562,0.00035441355,0.00034595781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015976361,0.000043680688,0.0018154237,0.00034106214,0.00008164737,0.0020683173,0.0001991055,0.5763983,0.12784302,0.16754436,0.0008567966,0.12264862],"study_design_scores_gemma":[0.000036411424,0.0003490037,0.0017413239,0.000047244386,0.000032303495,0.0015535658,0.00004723137,0.95648515,0.0091143055,0.018777687,0.01174984,0.00006593999],"about_ca_topic_score_codex":0.00041988742,"about_ca_topic_score_gemma":0.00015321882,"teacher_disagreement_score":0.002638535,"about_ca_system_score_codex":0.00013860347,"about_ca_system_score_gemma":0.00034552635,"threshold_uncertainty_score":0.008826852},"labels":[],"label_agreement":null},{"id":"W2150433803","doi":"10.1109/3477.846233","title":"Discovering relevance knowledge in data: a growing cell structures approach","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Image Retrieval and Classification 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":"Trinity College","funders":"","keywords":"Relevance (law); Computer science; Search engine indexing; Similarity (geometry); Artificial intelligence; Machine learning; Data mining; Artificial neural network; Information retrieval; Image (mathematics)","score_opus":0.030855756440961828,"score_gpt":0.2570040329577513,"score_spread":0.22614827651678948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150433803","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":[0.01853074,0.0011779976,0.97679895,0.00090609054,0.000029279296,0.00016540712,0.00016969192,0.00020607053,0.0020158142],"genre_scores_gemma":[0.2866002,0.0016706263,0.7079652,0.0002815156,0.00021830683,0.00049387716,0.0006127661,0.00007896716,0.002078571],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99764603,0.00070785155,0.00017786537,0.0004141789,0.00093024434,0.00012379818],"domain_scores_gemma":[0.9827207,0.012378445,0.0012451966,0.0014951987,0.0018169992,0.0003435184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003434146,0.0005842903,0.0013415497,0.0045495913,0.0011121373,0.0031493518,0.0028056698,0.001903532,0.0015900385],"category_scores_gemma":[0.027327929,0.00092118257,0.0013798238,0.004138912,0.00257479,0.00622281,0.0026956943,0.0021073502,0.0006096872],"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":[0.00014398427,0.00018159531,0.0071627502,0.00042543202,0.00017401573,0.00091914355,0.0020682102,0.2457158,0.008357948,0.38993835,0.0051372307,0.33977562],"study_design_scores_gemma":[0.00002280033,0.000056713096,0.00081753393,0.000051861723,0.00005636295,0.0002835317,0.00017556445,0.7609693,0.002751831,0.22865583,0.0061202827,0.00003841497],"about_ca_topic_score_codex":0.004279249,"about_ca_topic_score_gemma":0.0037002622,"teacher_disagreement_score":0.0045495913,"about_ca_system_score_codex":0.0018892211,"about_ca_system_score_gemma":0.001330339,"threshold_uncertainty_score":0.018161774},"labels":[],"label_agreement":null},{"id":"W2151749331","doi":"10.1109/tsmcb.2005.848489","title":"MetricMap: An Embedding Technique for Processing Distance-Based Queries in Metric Spaces","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Data Management and Algorithms","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":"Western University","funders":"National Institute of General Medical Sciences; National Cancer Institute","keywords":"Embedding; Oracle; Euclidean distance; Metric space; Cluster analysis; Dimension (graph theory); Mathematics; Euclidean space; Tree (set theory); Edit distance; Class (philosophy); Distance measures; Computer science; Space (punctuation); Metric (unit); Data mining; Theoretical computer science; Algorithm; Artificial intelligence; Discrete mathematics; Combinatorics","score_opus":0.02385153451401728,"score_gpt":0.2732672958122047,"score_spread":0.24941576129818743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151749331","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":[0.0025466029,0.00028620704,0.9948827,0.00011374143,0.00005611686,0.000068554415,0.00018199749,0.0014225813,0.00044143267],"genre_scores_gemma":[0.08078514,0.00072237174,0.91529405,0.00016905491,0.00013803967,0.00029756434,0.0011337704,0.0002940889,0.0011659579],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968651,0.0007414598,0.00025536466,0.00037787735,0.0016354547,0.00012474794],"domain_scores_gemma":[0.9960949,0.0013552766,0.00031113194,0.0012706161,0.00082302996,0.0001451168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019486507,0.0013941819,0.0017418896,0.0029411176,0.00078343466,0.0018521951,0.0023121885,0.0015620423,0.0026003295],"category_scores_gemma":[0.010960575,0.00067640113,0.0011594285,0.004756554,0.0010299605,0.0076123616,0.0037238928,0.0022477712,0.001997724],"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":[0.00034090542,0.00019409374,0.0015693736,0.000574726,0.00017090137,0.00033033054,0.0006343813,0.043723807,0.01676821,0.04925516,0.019065669,0.8673724],"study_design_scores_gemma":[0.000064921805,0.00047421697,0.0011428995,0.000081845465,0.000058291567,0.0020178955,0.00040429135,0.7883068,0.031640913,0.11774258,0.05788877,0.00017670546],"about_ca_topic_score_codex":0.001382226,"about_ca_topic_score_gemma":0.0012085134,"teacher_disagreement_score":0.0029411176,"about_ca_system_score_codex":0.00060594577,"about_ca_system_score_gemma":0.0008154736,"threshold_uncertainty_score":0.0103055835},"labels":[],"label_agreement":null},{"id":"W2152324445","doi":"10.1109/tsmcb.2005.850180","title":"Dynamic Algorithms for the Shortest Path Routing Problem: Learning Automata-Based Solutions","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Shortest path problem; Shortest Path Faster Algorithm; K shortest path routing; Algorithm; Widest path problem; Computer science; Yen's algorithm; Euclidean shortest path; Distance; Graph; Mathematics; Dijkstra's algorithm; Theoretical computer science","score_opus":0.031070097432292325,"score_gpt":0.26320034852747093,"score_spread":0.2321302510951786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152324445","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":[0.0086804265,0.00021596001,0.98861176,0.0001987975,0.000041666954,0.000044245833,0.000042227806,0.00037635118,0.0017886708],"genre_scores_gemma":[0.48933607,0.0005671738,0.5046515,0.0002331528,0.00011112357,0.000529384,0.00043048698,0.00018967476,0.0039514424],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921405,0.00018618559,0.00005511861,0.00026301062,0.0001862607,0.000095335105],"domain_scores_gemma":[0.9976816,0.0015997542,0.00017336615,0.00016499402,0.00029743396,0.00008280817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093820586,0.0011225315,0.0011048034,0.0010380514,0.00070198474,0.0012698541,0.0021026933,0.0018188087,0.0025404994],"category_scores_gemma":[0.005828621,0.00055277,0.0008876421,0.0010434894,0.0009978956,0.0019433905,0.0015423328,0.0019249072,0.00046076573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003886647,0.00004600386,0.00046859946,0.00007574627,0.000034308992,0.00003494976,0.00007831598,0.91648906,0.0007479797,0.026068458,0.0010341619,0.054883506],"study_design_scores_gemma":[0.000006557857,0.000011474995,0.000024689332,0.00000482132,0.0000033476215,0.000009413714,0.000009399691,0.98798335,0.00017530558,0.01136198,0.00040570262,0.0000038730714],"about_ca_topic_score_codex":0.004993409,"about_ca_topic_score_gemma":0.0040946486,"teacher_disagreement_score":0.004993409,"about_ca_system_score_codex":0.0012681361,"about_ca_system_score_gemma":0.0017249582,"threshold_uncertainty_score":0.009928703},"labels":[],"label_agreement":null},{"id":"W2152474030","doi":"10.1109/tsmcb.2005.862728","title":"Real-time face detection and lip feature extraction using field-programmable gate arrays","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Face recognition and analysis","field":"Computer Science","cited_by":94,"is_retracted":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":"Face (sociological concept); Feature extraction; Computer science; Artificial intelligence; Face detection; Feature (linguistics); Pattern recognition (psychology); Field (mathematics); Gate array; Extraction (chemistry); Computer vision; Facial recognition system; Field-programmable gate array; Computer hardware; Mathematics; Chemistry; Chromatography","score_opus":0.01371545294379414,"score_gpt":0.2343036692976824,"score_spread":0.22058821635388826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152474030","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":[0.05123074,0.0006981001,0.9369294,0.00024463775,0.0002317317,0.00012109939,0.00012677304,0.00495327,0.005464218],"genre_scores_gemma":[0.48989588,0.00044081145,0.501474,0.00027809505,0.0001171394,0.00015406702,0.00021519493,0.00009061747,0.0073341937],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975365,0.000021356986,0.000012436337,0.000050122122,0.00013221422,0.000030258208],"domain_scores_gemma":[0.99976605,0.000096031814,0.000028254768,0.0000299497,0.00006432445,0.0000153893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021295862,0.00040720438,0.00034175903,0.00055669184,0.00019325408,0.00041316936,0.0009395043,0.00039784823,0.0034139145],"category_scores_gemma":[0.0005112745,0.00027655074,0.00022103777,0.00025028363,0.00018271855,0.0006578283,0.0002521997,0.00034222755,0.0009309195],"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":[0.0005233496,0.00013338462,0.00200535,0.00018721711,0.00005584654,0.00032311757,0.00007645563,0.0063617495,0.3394685,0.0032125358,0.0046008388,0.6430516],"study_design_scores_gemma":[0.0002461951,0.0012436995,0.007074661,0.00008959343,0.00013786582,0.003023258,0.00008211181,0.4233369,0.5177681,0.0029106098,0.043965947,0.00012104176],"about_ca_topic_score_codex":0.001000291,"about_ca_topic_score_gemma":0.001887411,"teacher_disagreement_score":0.0034139145,"about_ca_system_score_codex":0.00030217724,"about_ca_system_score_gemma":0.00027273464,"threshold_uncertainty_score":0.011420667},"labels":[],"label_agreement":null},{"id":"W2154962044","doi":"10.1109/tsmcb.2010.2042955","title":"Face Transformation With Harmonic Models by the Finite-Volume Method With Delaunay Triangulation","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Image Processing and 3D Reconstruction","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":"Delaunay triangulation; Transformation (genetics); Triangulation; Harmonic; Constrained Delaunay triangulation; Face (sociological concept); Finite volume method; Pitteway triangulation; Computer science; Mathematics; Applied mathematics; Algorithm; Geometry; Physics; Sociology; Acoustics; Mechanics; Social science","score_opus":0.014022752041561984,"score_gpt":0.22598124739165504,"score_spread":0.21195849535009306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154962044","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":[0.0011151074,0.000038687842,0.9978531,0.000016996557,0.000013836089,0.000019075365,0.000013515628,0.00013420613,0.00079536653],"genre_scores_gemma":[0.0659514,0.0001786571,0.93096,0.00003687645,0.00003069681,0.00016902352,0.0001599207,0.0002220476,0.0022913166],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993674,0.000109020526,0.000022900113,0.00010582465,0.00035896353,0.00003588963],"domain_scores_gemma":[0.9996772,0.00014155041,0.000025956208,0.000060728667,0.00008115202,0.0000134528345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005322803,0.0005822051,0.00075648836,0.0010242211,0.00047442105,0.0007809909,0.0015604285,0.00076694036,0.0034739594],"category_scores_gemma":[0.0014266119,0.0005078321,0.0011827056,0.0007416366,0.00061063626,0.001060612,0.0013504667,0.0011152884,0.0013112937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004419526,0.00003822739,0.0006151625,0.00021771852,0.000046627443,0.00009966683,0.00036901725,0.6150318,0.014575543,0.061769158,0.0031710123,0.3040219],"study_design_scores_gemma":[0.0000053872877,0.000015217043,0.00006821562,0.000008952038,0.0000052406103,0.000054267017,0.000027542996,0.98317105,0.0021130037,0.008344341,0.0061746803,0.000012105733],"about_ca_topic_score_codex":0.004364543,"about_ca_topic_score_gemma":0.00298922,"teacher_disagreement_score":0.004364543,"about_ca_system_score_codex":0.00064344576,"about_ca_system_score_gemma":0.00086344784,"threshold_uncertainty_score":0.011621594},"labels":[],"label_agreement":null},{"id":"W2155446094","doi":"10.1109/tsmcb.2006.876818","title":"On Impact Dynamics and Contact Events for Biped Robots via Impact Effects","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; McGill University","funders":"","keywords":"Kinematics; Slippage; Parametric statistics; Swing; Computer science; Robot; Control theory (sociology); Event (particle physics); Simulation; Contact force; Dynamics (music); Control (management); Mathematics; Engineering; Physics; Artificial intelligence; Structural engineering; Mechanical engineering; Classical mechanics","score_opus":0.005678294563105129,"score_gpt":0.22041074752637885,"score_spread":0.21473245296327373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155446094","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":[0.45212874,0.0021138072,0.5312194,0.000311244,0.000082384584,0.000058887937,0.00012727706,0.00026748516,0.013690707],"genre_scores_gemma":[0.9909123,0.0008088318,0.006489144,0.00002952059,0.0000323918,0.000014969813,0.00006143028,0.000021398691,0.0016300775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985945,0.000022399501,0.000005018829,0.000022369357,0.00006831322,0.000022439353],"domain_scores_gemma":[0.99938524,0.0003251487,0.00013373057,0.00004239475,0.00007456343,0.00003877271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001650996,0.00045395337,0.0004276995,0.0005831256,0.00036186885,0.000443002,0.00033569368,0.0004191869,0.002179689],"category_scores_gemma":[0.0013740825,0.00017404278,0.00035429027,0.0004736662,0.00077805744,0.001008101,0.0006956255,0.0004517921,0.00020939698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002503149,0.00016292137,0.005123927,0.0003725513,0.00006518157,0.0020388677,0.000540986,0.8289996,0.041810006,0.05809662,0.0008795687,0.06165942],"study_design_scores_gemma":[0.0000068697927,0.00008101046,0.00353023,0.000015483738,0.000013165928,0.00033169368,0.00008538094,0.9737412,0.0033621257,0.017797412,0.0010083477,0.000027095568],"about_ca_topic_score_codex":0.0013782916,"about_ca_topic_score_gemma":0.00084178563,"teacher_disagreement_score":0.002179689,"about_ca_system_score_codex":0.00021332136,"about_ca_system_score_gemma":0.00016275147,"threshold_uncertainty_score":0.007291734},"labels":[],"label_agreement":null},{"id":"W2156373593","doi":"10.1109/tsmcb.2006.877792","title":"Rendezvous-Guidance Trajectory Planning for Robotic Dynamic Obstacle Avoidance and Interception","year":2006,"lang":"en","type":"letter","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Rendezvous; Interception; Obstacle avoidance; Obstacle; Collision avoidance; Computer science; Trajectory; Position (finance); Robot; Motion planning; Control theory (sociology); Path (computing); Simulation; Artificial intelligence; Collision; Mobile robot; Engineering; Control (management); Aerospace engineering; Geography; Physics","score_opus":0.02571331981470601,"score_gpt":0.25282068338734087,"score_spread":0.22710736357263486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156373593","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":[0.0069494955,0.008283299,0.9499166,0.006726553,0.0011831145,0.000096472075,0.000045831424,0.0010719765,0.02572659],"genre_scores_gemma":[0.30208707,0.010767353,0.62865496,0.0036707514,0.0021853936,0.0004766424,0.00023700717,0.00029666015,0.051624082],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99943715,0.00016265591,0.000020208297,0.00005634054,0.00029757823,0.000026017375],"domain_scores_gemma":[0.9995129,0.00022074197,0.00004031685,0.000099687575,0.000109584835,0.000016763888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033368825,0.00032014717,0.00028570773,0.0002963657,0.00035276348,0.00046273833,0.00061437004,0.0009689544,0.0037195275],"category_scores_gemma":[0.0015495555,0.00015486551,0.00014801111,0.00037613415,0.00064773613,0.00066883425,0.0004679082,0.0011038592,0.0025311548],"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":[0.00028732858,0.000042488653,0.0004860867,0.00042609862,0.000025988178,0.0009136087,0.00014910789,0.017464962,0.019185597,0.13737877,0.055368856,0.7682712],"study_design_scores_gemma":[0.00016508998,0.00035865488,0.0008097955,0.00015162808,0.000029779165,0.005218841,0.00009049818,0.35862252,0.026892295,0.08507541,0.5225201,0.000065303604],"about_ca_topic_score_codex":0.0005497838,"about_ca_topic_score_gemma":0.0011477864,"teacher_disagreement_score":0.0037195275,"about_ca_system_score_codex":0.0007603528,"about_ca_system_score_gemma":0.0003890323,"threshold_uncertainty_score":0.012443125},"labels":[],"label_agreement":null},{"id":"W2156396274","doi":"10.1109/tsmcb.2010.2058103","title":"Applications of Artificial Intelligence in Safe Human–Robot Interactions","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Workspace; Robot; Computer science; Artificial intelligence; Artificial neural network; Rendering (computer graphics); Set (abstract data type); Human–robot interaction; Robotics; Control engineering; Engineering","score_opus":0.0249108356343648,"score_gpt":0.26697148368888074,"score_spread":0.24206064805451594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156396274","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":[0.015263164,0.021854501,0.89074266,0.005256083,0.0006907768,0.00010130736,0.00004408574,0.00041055767,0.0656369],"genre_scores_gemma":[0.6737205,0.022844927,0.29061073,0.0012476464,0.00085722085,0.00032055704,0.00009569061,0.000094242016,0.010208638],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99909735,0.00042247892,0.00004453205,0.00009532524,0.0002981155,0.000042239208],"domain_scores_gemma":[0.9987311,0.00090452936,0.000081975624,0.00012570477,0.00011821219,0.000038425344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010255357,0.0006903523,0.00052978215,0.0006364044,0.00058192445,0.0018647815,0.00090059335,0.0017736431,0.0027612098],"category_scores_gemma":[0.002593978,0.00031262654,0.0005107209,0.0005931049,0.0030760453,0.0018486847,0.0015211883,0.0013156941,0.00059954013],"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":[0.00009797703,0.000089173205,0.0013126545,0.0010388775,0.00017059523,0.0007064199,0.0007312742,0.16726358,0.009007918,0.5321644,0.0061055142,0.2813117],"study_design_scores_gemma":[0.00002939497,0.00013934821,0.0009321084,0.0002479055,0.00003909159,0.00041431678,0.0003575504,0.29927546,0.004369879,0.6385598,0.05557615,0.00005898383],"about_ca_topic_score_codex":0.0008379702,"about_ca_topic_score_gemma":0.00061960594,"teacher_disagreement_score":0.0027612098,"about_ca_system_score_codex":0.0006456117,"about_ca_system_score_gemma":0.0005855126,"threshold_uncertainty_score":0.00923717},"labels":[],"label_agreement":null},{"id":"W2156472550","doi":"10.1109/tsmcb.2003.818555","title":"Localization-Based Sensor Validation Using the Kullback–Leibler Divergence","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Unobservable; Divergence (linguistics); Metric (unit); Kullback–Leibler divergence; Mathematics; Event (particle physics); Probability distribution; Function (biology); Likelihood function; Statistics; Algorithm; Estimation theory; Physics","score_opus":0.029762399929311047,"score_gpt":0.24615573046299463,"score_spread":0.2163933305336836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156472550","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":[0.004860889,0.00010418577,0.9944502,0.00005149475,0.000012646776,0.000021026974,0.00001340472,0.00013837629,0.00034783792],"genre_scores_gemma":[0.6703477,0.00032910716,0.32740593,0.0001494428,0.000059336737,0.000256455,0.00023427494,0.00012302658,0.0010947575],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99213773,0.0035680863,0.00071914255,0.0008841097,0.0024029866,0.00028799602],"domain_scores_gemma":[0.97637784,0.014926581,0.002222058,0.0019519296,0.0041725957,0.0003490048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011947789,0.0014080583,0.0023209741,0.0020258934,0.0010853662,0.002656572,0.0024215772,0.0020287219,0.00090859615],"category_scores_gemma":[0.03965705,0.00060014444,0.0012172764,0.0014728184,0.0023746362,0.0044575706,0.00380566,0.0019750164,0.00035637832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030149723,0.0000924818,0.0046224217,0.00029188982,0.0002036233,0.00035726035,0.00025207605,0.7680485,0.009739065,0.062713526,0.0010562307,0.1523214],"study_design_scores_gemma":[0.00001167992,0.000076282806,0.0005056342,0.000021455879,0.000014497271,0.00013812716,0.000022034472,0.9806395,0.0037935374,0.014353223,0.0003879654,0.000036031313],"about_ca_topic_score_codex":0.0017509934,"about_ca_topic_score_gemma":0.0012057521,"teacher_disagreement_score":0.011947789,"about_ca_system_score_codex":0.0016200083,"about_ca_system_score_gemma":0.002209853,"threshold_uncertainty_score":0.063186765},"labels":[],"label_agreement":null},{"id":"W2157321916","doi":"10.1109/tsmcb.2005.863379","title":"Parameter learning from stochastic teachers and stochastic compulsive liars","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Oracle; Learning automata; Computer science; Point (geometry); Artificial intelligence; Interval (graph theory); Mechanism (biology); Automaton; Machine learning; Mathematics; Epistemology","score_opus":0.0175080524577038,"score_gpt":0.22762643723040316,"score_spread":0.21011838477269934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157321916","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":[0.17057656,0.0001749049,0.82359004,0.0005611221,0.000029724288,0.0000828858,0.000035251338,0.00037999405,0.004569519],"genre_scores_gemma":[0.9654256,0.000067032306,0.031643912,0.000111991736,0.000025011335,0.00007226249,0.000028770633,0.000024469211,0.002600993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982016,0.00077332056,0.00011921969,0.00036972115,0.0003356399,0.00020035563],"domain_scores_gemma":[0.992359,0.0043007615,0.0012865594,0.0011024474,0.00047008198,0.00048105596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023240724,0.00067735335,0.0009546498,0.00044522394,0.00051412504,0.0011749314,0.0015883656,0.0017652644,0.0016772345],"category_scores_gemma":[0.013625398,0.00043980248,0.0006074358,0.00032146904,0.0025593548,0.002706354,0.0025601683,0.0016167253,0.00032149538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036993707,0.000118310956,0.003929607,0.00014304792,0.00008607157,0.00041702567,0.0006805609,0.80982876,0.0060071,0.13639578,0.00050458615,0.041519273],"study_design_scores_gemma":[0.000031880696,0.00014312784,0.00029211506,0.000012532603,0.000013918987,0.00008184544,0.000049543163,0.9572766,0.001617071,0.039854188,0.0006038883,0.000023253675],"about_ca_topic_score_codex":0.0010897845,"about_ca_topic_score_gemma":0.00084021816,"teacher_disagreement_score":0.0023240724,"about_ca_system_score_codex":0.0008170113,"about_ca_system_score_gemma":0.0008591164,"threshold_uncertainty_score":0.012291014},"labels":[],"label_agreement":null},{"id":"W2157423047","doi":"10.1109/3477.907568","title":"Abstraction and specialization of information granules","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":88,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Space Agency; University of Alberta","funders":"","keywords":"Generalization; Fuzzy logic; Abstraction; Computer science; Theoretical computer science; Fuzzy set; Granular computing; Mathematics; Artificial intelligence; Rough set; Epistemology","score_opus":0.016440901478077374,"score_gpt":0.21939896628558314,"score_spread":0.20295806480750578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157423047","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":[0.03901798,0.0006548,0.94590133,0.0007310623,0.00006598336,0.00007657687,0.00012544187,0.00023393067,0.013192904],"genre_scores_gemma":[0.70503825,0.00081072457,0.28711262,0.00033638504,0.00014212637,0.00018684349,0.0002456403,0.0000786379,0.006048807],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983353,0.00043578172,0.00014363186,0.000395182,0.00050541677,0.00018466699],"domain_scores_gemma":[0.99790144,0.0007522209,0.00020752933,0.0006870671,0.00030769315,0.00014393259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017724109,0.00056949304,0.00083456124,0.0016202187,0.000753719,0.0027885695,0.0008307303,0.0007593789,0.00242516],"category_scores_gemma":[0.0047392403,0.00036349666,0.0019300155,0.0013043911,0.0027265032,0.0056441887,0.002706596,0.0015577793,0.00036113997],"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":[0.000061017334,0.000017978078,0.0005776077,0.000115218965,0.000053762633,0.00039575354,0.0010349755,0.012652639,0.004279743,0.9538399,0.0010723055,0.025899181],"study_design_scores_gemma":[0.000023722981,0.00005588201,0.0006804161,0.000044065466,0.00005021006,0.00039099215,0.00024464118,0.092784636,0.0037883993,0.8891697,0.012734816,0.00003252501],"about_ca_topic_score_codex":0.001154131,"about_ca_topic_score_gemma":0.0007686401,"teacher_disagreement_score":0.0027885695,"about_ca_system_score_codex":0.0009459466,"about_ca_system_score_gemma":0.0005843198,"threshold_uncertainty_score":0.009373486},"labels":[],"label_agreement":null},{"id":"W2158304715","doi":"10.1109/tsmcb.2007.899419","title":"Positive Impact of State Similarity on Reinforcement Learning Performance","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Reinforcement learning; Similarity (geometry); Artificial intelligence; Context (archaeology); Computer science; Reinforcement; Function (biology); Bellman equation; Tree (set theory); State (computer science); Action (physics); Machine learning; Value (mathematics); Mathematics; Mathematical optimization; Algorithm; Engineering","score_opus":0.01715931351416537,"score_gpt":0.2565818502936981,"score_spread":0.23942253677953276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158304715","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":[0.6549893,0.0010058216,0.33172902,0.0009371417,0.00018184049,0.00016369538,0.00007587703,0.0014464505,0.009470782],"genre_scores_gemma":[0.989744,0.000058373895,0.009695958,0.0000621413,0.000030889347,0.000025590542,0.000039411138,0.000032297998,0.00031135548],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99583924,0.001362264,0.0003194651,0.00081167987,0.0013024558,0.00036501093],"domain_scores_gemma":[0.9497266,0.039184302,0.0036691786,0.0034781334,0.0024721448,0.0014695657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005013166,0.0008216931,0.0014841888,0.00061307504,0.0006221985,0.0014097736,0.0009282367,0.0014368062,0.0021725914],"category_scores_gemma":[0.050867554,0.00028993684,0.0003792305,0.00040156025,0.0013536621,0.0030769506,0.0019297915,0.0020953533,0.0003985104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023011733,0.0020039116,0.03193978,0.0004015616,0.00040386617,0.00041945904,0.00034932693,0.594425,0.02118233,0.023799218,0.0014612285,0.32131314],"study_design_scores_gemma":[0.00010436873,0.0016720615,0.011001276,0.000032266504,0.00007951412,0.00023877306,0.00009125263,0.95402586,0.009196662,0.022914404,0.000596108,0.000047499252],"about_ca_topic_score_codex":0.0010803441,"about_ca_topic_score_gemma":0.0009696226,"teacher_disagreement_score":0.005013166,"about_ca_system_score_codex":0.0008439706,"about_ca_system_score_gemma":0.0011852283,"threshold_uncertainty_score":0.026512504},"labels":[],"label_agreement":null},{"id":"W2160135028","doi":"10.1109/tsmcb.2003.808187","title":"Adaptive control for a class of second-order nonlinear systems with unknown input nonlinearities","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Control theory (sociology); Lyapunov function; Nonlinear system; Adaptive control; Controller (irrigation); Convergence (economics); Constraint (computer-aided design); Artificial neural network; Monotonic function; Computer science; Monotone polygon; Tracking error; Stability (learning theory); Class (philosophy); Lyapunov stability; Mathematics; Control (management); Artificial intelligence","score_opus":0.01504355130357264,"score_gpt":0.21122331618751516,"score_spread":0.19617976488394254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160135028","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":[0.023220703,0.0008512358,0.9702928,0.00021062573,0.00016527096,0.000046122335,0.000028127011,0.0002672126,0.0049179876],"genre_scores_gemma":[0.9350191,0.0012274538,0.054766603,0.00011978593,0.00018957016,0.00025510037,0.00008744581,0.000032215143,0.008302648],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982786,0.00002208906,0.000009117188,0.00003841321,0.00007999513,0.000022618344],"domain_scores_gemma":[0.99980646,0.00007157549,0.00004181843,0.000012242027,0.000057988476,0.000009875339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028037452,0.0007449062,0.00044703836,0.00026264167,0.0002973523,0.00057250645,0.00066897675,0.00074054545,0.00081752136],"category_scores_gemma":[0.00058122014,0.00017984718,0.00034965586,0.0003103719,0.00050441886,0.00039518657,0.000510922,0.00083654857,0.00015506854],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000109714325,0.000080147016,0.0011786326,0.00042169934,0.00009016208,0.000621651,0.0002957935,0.73392063,0.06182639,0.05205492,0.002661195,0.146739],"study_design_scores_gemma":[0.000009146087,0.000052541673,0.0002665824,0.0000069285625,0.000006379191,0.00006290682,0.000007991034,0.99410456,0.0011754149,0.002557471,0.0017430485,0.0000070013684],"about_ca_topic_score_codex":0.0024564432,"about_ca_topic_score_gemma":0.0024188533,"teacher_disagreement_score":0.0024564432,"about_ca_system_score_codex":0.00032208872,"about_ca_system_score_gemma":0.00040240752,"threshold_uncertainty_score":0.004884243},"labels":[],"label_agreement":null},{"id":"W2160632603","doi":"10.1109/3477.826956","title":"Identification of a two-link flexible manipulator using adaptive time delay neural networks","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University","funders":"","keywords":"Nonlinear system; Control theory (sociology); Identifier; Computer science; Identification (biology); Artificial neural network; A priori and a posteriori; Link (geometry); MIMO; Nonlinear system identification; Input/output; System identification; Control (management); Artificial intelligence; Data modeling","score_opus":0.026029599531130324,"score_gpt":0.2514568415297994,"score_spread":0.2254272419986691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160632603","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":[0.123276345,0.0002483555,0.87400436,0.00012408866,0.000035126748,0.000045013225,0.000027964972,0.00017554667,0.0020632765],"genre_scores_gemma":[0.9459147,0.000110288966,0.051707108,0.00002785193,0.000011045142,0.000086754575,0.000029629204,0.000005851755,0.002106854],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998666,0.00002597539,0.000008378704,0.00004460567,0.000036916572,0.000017459619],"domain_scores_gemma":[0.9997701,0.0000934763,0.000059748825,0.00002357281,0.000039906543,0.000013166786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003100321,0.00059059274,0.000303141,0.00029802806,0.00037742846,0.0003719192,0.00039833228,0.0008624101,0.00069131487],"category_scores_gemma":[0.00075880124,0.00022572582,0.00033323397,0.00027595946,0.00043762653,0.0005553087,0.00056949793,0.00049658096,0.00012047053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013624759,0.000036441525,0.0014600708,0.00010065955,0.000050438346,0.0003815117,0.00014376114,0.90537345,0.027578956,0.0047672046,0.00016359737,0.05980781],"study_design_scores_gemma":[0.000009622028,0.00006927404,0.0004897048,0.0000074058876,0.000006701326,0.000053730866,0.000015306929,0.9950694,0.0025919564,0.0012398975,0.00043761588,0.000009331061],"about_ca_topic_score_codex":0.0025973753,"about_ca_topic_score_gemma":0.0021979536,"teacher_disagreement_score":0.0025973753,"about_ca_system_score_codex":0.00029186718,"about_ca_system_score_gemma":0.00037501042,"threshold_uncertainty_score":0.0051645637},"labels":[],"label_agreement":null},{"id":"W2161925873","doi":"10.1109/3477.836374","title":"Investigating a relevance of fuzzy mappings","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Rough Sets and Fuzzy Logic","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":"Canadian Space Agency; University of Alberta","funders":"","keywords":"Relevance (law); Property (philosophy); Fuzzy logic; Computer science; Fuzzy set; Data mining; Mathematics; Theoretical computer science; Algorithm; Artificial intelligence","score_opus":0.021684677024751933,"score_gpt":0.22670330989578144,"score_spread":0.2050186328710295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161925873","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":[0.2997191,0.0021153335,0.6646884,0.002051916,0.00014062235,0.00015751764,0.000044449764,0.00007345979,0.031009097],"genre_scores_gemma":[0.95513916,0.00052404095,0.042683538,0.00008082993,0.00009932338,0.000038999406,0.000016651764,0.000015182583,0.0014023449],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970547,0.0013040188,0.00011100894,0.00039625552,0.0009012298,0.00023284265],"domain_scores_gemma":[0.9904141,0.006772141,0.0009299726,0.000781352,0.0008060194,0.00029636614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041020657,0.00040448748,0.00071977853,0.0016507054,0.0010015583,0.0025522048,0.0006803721,0.0012344862,0.0017905588],"category_scores_gemma":[0.022679243,0.000354089,0.0007354677,0.0011240457,0.0034206081,0.0051021003,0.0023451406,0.0017059962,0.00018032265],"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":[0.000061899336,0.000034672743,0.0011480228,0.00014033008,0.000027124803,0.00040772874,0.0014094204,0.023741117,0.0054306653,0.95170873,0.00031399363,0.015576251],"study_design_scores_gemma":[0.000013993097,0.00013149869,0.0012281475,0.000043762913,0.0000183846,0.00036833674,0.0006142006,0.1248228,0.0024130004,0.86643565,0.0038818598,0.000028404327],"about_ca_topic_score_codex":0.0004808662,"about_ca_topic_score_gemma":0.00024635895,"teacher_disagreement_score":0.0041020657,"about_ca_system_score_codex":0.0013457271,"about_ca_system_score_gemma":0.0006414757,"threshold_uncertainty_score":0.021694064},"labels":[],"label_agreement":null},{"id":"W2162964807","doi":"10.1109/tsmcb.2006.879012","title":"Learning Automata-Based Solutions to the Nonlinear Fractional Knapsack Problem With Applications to Optimal Resource Allocation","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":99,"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":"Knapsack problem; Computer science; Learning automata; Discretization; Resource allocation; Scheme (mathematics); Mathematical optimization; Polling; Theoretical computer science; Automaton; Algorithm; Mathematics","score_opus":0.02106864386116119,"score_gpt":0.2554649759567687,"score_spread":0.2343963320956075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162964807","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":[0.008990971,0.0002800403,0.9866736,0.00022614922,0.000054588625,0.00003995854,0.00002773946,0.000176855,0.0035301328],"genre_scores_gemma":[0.61304426,0.0005710667,0.38049147,0.00022427923,0.00008593276,0.0003724389,0.000110954395,0.00010206022,0.0049975286],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995036,0.00015658388,0.000040596122,0.00010666449,0.00011863489,0.00007377977],"domain_scores_gemma":[0.9976107,0.0017133552,0.00019567688,0.00013617317,0.00024950484,0.00009465998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011348088,0.0008083358,0.0009844978,0.000620897,0.0006644397,0.0012698832,0.0012830488,0.0015509304,0.0031332162],"category_scores_gemma":[0.005410684,0.00042746353,0.0007701335,0.0005911478,0.0013184022,0.0010654574,0.0016752221,0.0017947645,0.00039042777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019607674,0.000022430928,0.0002605983,0.000047785925,0.0000130960025,0.000031930827,0.00005376965,0.96179765,0.00054477353,0.020772576,0.00029934384,0.016136536],"study_design_scores_gemma":[0.0000031814147,0.000010051888,0.000019998766,0.000004968392,0.000002140244,0.0000057718457,0.000007516758,0.9924314,0.00015449907,0.0070512677,0.00030594144,0.0000033320089],"about_ca_topic_score_codex":0.0054399306,"about_ca_topic_score_gemma":0.0053209276,"teacher_disagreement_score":0.0054399306,"about_ca_system_score_codex":0.000985288,"about_ca_system_score_gemma":0.0013049273,"threshold_uncertainty_score":0.010816574},"labels":[],"label_agreement":null},{"id":"W2162996718","doi":"10.1109/3477.826955","title":"Experimental results on discrete-time nonlinear adaptive tracking control of a flexible-link manipulator","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Control theory (sociology); Nonlinear system; Controller (irrigation); Feedback linearization; A priori and a posteriori; Adaptive control; Linearization; Payload (computing); Computer science; Tracking (education); Mathematics; Control (management); Network packet","score_opus":0.013887713978809902,"score_gpt":0.2196263293116801,"score_spread":0.20573861533287022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162996718","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":[0.9460072,0.00024381268,0.04875166,0.0001209094,0.000057744102,0.00010709221,0.00009659809,0.0005778302,0.0040371837],"genre_scores_gemma":[0.9896472,0.00008358671,0.008746166,0.0000128675165,0.0000053338313,0.000059116166,0.000058685666,0.0000098263445,0.0013772969],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974006,0.000043822845,0.000027524933,0.000036302845,0.000122017795,0.000030190753],"domain_scores_gemma":[0.9992067,0.00031223375,0.000110823494,0.00014588174,0.00018606955,0.000038296763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005844223,0.00031122053,0.00024122244,0.00023895805,0.00035780316,0.00027910102,0.00045758695,0.00056600245,0.002116933],"category_scores_gemma":[0.0012266606,0.00012559175,0.00019743486,0.0002259879,0.00037751228,0.00037359647,0.0002657877,0.0003169523,0.00021383453],"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":[0.0010597584,0.0011043473,0.0016412913,0.0008598296,0.00005077815,0.00043100762,0.00055000995,0.07370265,0.8572056,0.0014565705,0.00042149736,0.06151665],"study_design_scores_gemma":[0.00038696043,0.008557733,0.009641973,0.00006672572,0.00006842596,0.00027293855,0.00019983375,0.24363774,0.73266345,0.00071621244,0.0037296352,0.000058440874],"about_ca_topic_score_codex":0.00092332315,"about_ca_topic_score_gemma":0.0009038506,"teacher_disagreement_score":0.002116933,"about_ca_system_score_codex":0.00015926853,"about_ca_system_score_gemma":0.00017546462,"threshold_uncertainty_score":0.0070818067},"labels":[],"label_agreement":null},{"id":"W2164561380","doi":"10.1109/tsmcb.2005.850177","title":"A Layered Goal-Oriented Fuzzy Motion Planning Strategy for Mobile Robot Navigation","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":122,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Motion planning; Mobile robot; Fuzzy logic; Computer science; Robot; Mobile robot navigation; Artificial intelligence; Planner; Visibility; Computer vision; Real-time computing; Simulation; Robot control; Geography","score_opus":0.02858775443073196,"score_gpt":0.27600739365175353,"score_spread":0.24741963922102156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164561380","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":[0.0060992977,0.000088622044,0.9925011,0.00004283488,0.000011525246,0.00003199873,0.000014664372,0.00018500302,0.0010250023],"genre_scores_gemma":[0.4510261,0.0002321267,0.54657555,0.00007986021,0.000013628817,0.0001680454,0.00008798256,0.000019394189,0.0017973543],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998714,0.000020396872,0.000009809149,0.000025887128,0.00005726815,0.00001527989],"domain_scores_gemma":[0.99991274,0.000022073265,0.000014386517,0.000007620435,0.000034437027,0.000008657669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002378563,0.00048096638,0.00027491795,0.00030838657,0.00031248797,0.00042348896,0.00065523904,0.00046505142,0.0008719774],"category_scores_gemma":[0.00043223574,0.00017195282,0.0003959345,0.00022311388,0.0003291825,0.00048977236,0.0003628631,0.0004478558,0.00023566774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001206222,0.000090585054,0.00087367475,0.0002382421,0.00008987463,0.00036749386,0.0004526429,0.59977263,0.05788017,0.03838818,0.0017912433,0.29993472],"study_design_scores_gemma":[0.000026664233,0.0001220294,0.00023880828,0.000020385225,0.00003221361,0.000097014025,0.000028450704,0.9841576,0.005667263,0.007210351,0.0023747617,0.000024471463],"about_ca_topic_score_codex":0.0063904393,"about_ca_topic_score_gemma":0.0069301534,"teacher_disagreement_score":0.0063904393,"about_ca_system_score_codex":0.00052299217,"about_ca_system_score_gemma":0.0008672366,"threshold_uncertainty_score":0.012706518},"labels":[],"label_agreement":null},{"id":"W2164626058","doi":"10.1109/tsmcb.2004.835081","title":"KASER: knowledge amplification by structured expert randomization","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"AI-based Problem Solving and Planning","field":"Computer Science","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":"Simon Fraser University","funders":"","keywords":"Computer science; Randomness; Dice; Object (grammar); Artificial intelligence; Inheritance (genetic algorithm); Expert system; Domain (mathematical analysis); Natural language processing; Theoretical computer science; Mathematics; Statistics","score_opus":0.015707687485655916,"score_gpt":0.23742177903690775,"score_spread":0.22171409155125182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164626058","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":[0.020838527,0.000121689925,0.9594087,0.00051739503,0.000059491882,0.0002624955,0.00014222883,0.009701629,0.008947871],"genre_scores_gemma":[0.24431637,0.0001536205,0.7436202,0.00055165135,0.00004152121,0.00028296473,0.00044329435,0.00050105684,0.010089256],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975924,0.00096195354,0.00010948781,0.0004539293,0.0007489791,0.00013325372],"domain_scores_gemma":[0.9953002,0.0029277413,0.00029145836,0.0008245376,0.00050561124,0.00015052965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002745591,0.00067336793,0.00054875715,0.000876575,0.00045501697,0.0011140556,0.0014913531,0.00087893225,0.01001645],"category_scores_gemma":[0.00962339,0.00033759556,0.00071379263,0.00041041244,0.0013089803,0.0023371251,0.0024418335,0.0011888931,0.0024325636],"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":[0.00077436905,0.00042066234,0.0016847047,0.00039718428,0.000096798394,0.0006863671,0.0015846589,0.06843312,0.05266636,0.11703664,0.021090582,0.7351286],"study_design_scores_gemma":[0.0003410756,0.0004565241,0.0010544613,0.00009377085,0.00009070068,0.00090340065,0.00027479083,0.695528,0.06798357,0.14545918,0.08767817,0.00013634484],"about_ca_topic_score_codex":0.0007836355,"about_ca_topic_score_gemma":0.0010221213,"teacher_disagreement_score":0.01001645,"about_ca_system_score_codex":0.0006849422,"about_ca_system_score_gemma":0.0009338915,"threshold_uncertainty_score":0.03350836},"labels":[],"label_agreement":null},{"id":"W2164832447","doi":"10.1109/tsmcb.2010.2048900","title":"A Bounded and Adaptive Memory-Based Approach to Mine Frequent Patterns From Very Large Databases","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Thrashing; Computer science; Demand paging; Physical address; Interleaved memory; Flat memory model; Virtual memory; Memory management; Memory map; Paging; Extended memory; Auxiliary memory; Block (permutation group theory); Page fault; Registered memory; Data structure; Shared memory; Parallel computing; Operating system; Overlay","score_opus":0.028074208801518157,"score_gpt":0.24433049619443922,"score_spread":0.21625628739292108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164832447","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":[0.014477799,0.00053540536,0.98337656,0.00015179977,0.00002787567,0.00008087398,0.00012787369,0.0008229294,0.0003988937],"genre_scores_gemma":[0.3416553,0.00065393985,0.6543651,0.00026832597,0.00013588699,0.0004057028,0.00062712695,0.000110212786,0.0017784509],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980483,0.0004100427,0.00022911091,0.0006520774,0.0005045882,0.0001558258],"domain_scores_gemma":[0.9969651,0.0016747513,0.00029945493,0.00051844795,0.00043144956,0.00011080225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015769011,0.0008699147,0.0014972513,0.0030562284,0.00065163703,0.0015746669,0.003734615,0.0012220464,0.0011422276],"category_scores_gemma":[0.006410302,0.00066922896,0.001377749,0.0027220324,0.00077661744,0.0020669184,0.0016398677,0.0011760236,0.00060456706],"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":[0.00063470635,0.000503644,0.006928874,0.00042151022,0.00048619878,0.0007495955,0.00041477825,0.33854473,0.017084626,0.014178538,0.0039109336,0.6161418],"study_design_scores_gemma":[0.000014365173,0.00007978122,0.00046148404,0.000018853261,0.00003609576,0.00016838635,0.00004478766,0.98828715,0.0014874989,0.008278705,0.0011090774,0.000013918821],"about_ca_topic_score_codex":0.0031494864,"about_ca_topic_score_gemma":0.0034258526,"teacher_disagreement_score":0.003734615,"about_ca_system_score_codex":0.0005305738,"about_ca_system_score_gemma":0.0010763156,"threshold_uncertainty_score":0.008339524},"labels":[],"label_agreement":null},{"id":"W2165056932","doi":"10.1109/tsmcb.2007.912744","title":"Video-on-Demand Network Design and Maintenance Using Fuzzy Optimization","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","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 Manitoba; Research Manitoba","funders":"","keywords":"Computer science; Problem statement; Fuzzy logic; Process (computing); Function (biology); Heuristic; Bundle; Cache; Mathematical optimization; Statement (logic); Optimization problem; Order (exchange); Operations research; Algorithm; Artificial intelligence; Computer network; Mathematics; Engineering; Management science","score_opus":0.042047637074989576,"score_gpt":0.24412478032640683,"score_spread":0.20207714325141726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165056932","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":[0.022195023,0.00040249046,0.9702612,0.00017251799,0.000039286824,0.00009397037,0.000044564527,0.00014014075,0.0066508376],"genre_scores_gemma":[0.8111324,0.0005824911,0.18300454,0.00008297517,0.000042236945,0.00021874874,0.00009196242,0.000054852553,0.004789748],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971586,0.0000690789,0.000013220048,0.00006624443,0.00008817632,0.00004742053],"domain_scores_gemma":[0.9995926,0.00019206759,0.000054979497,0.00001723165,0.00011412993,0.000029070467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075738603,0.0007450525,0.00082189596,0.00070816255,0.0005961126,0.0011623224,0.0014927036,0.0012793641,0.0021587177],"category_scores_gemma":[0.0013059083,0.00047290878,0.00067648693,0.00060308486,0.00049762265,0.0008209391,0.00065552513,0.00069597823,0.00020419204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002875261,0.000028352772,0.00021757296,0.000042285574,0.000012453188,0.000036838544,0.000026926939,0.97754467,0.0018158125,0.0032398896,0.00040405823,0.016602335],"study_design_scores_gemma":[0.0000027406586,0.000013436173,0.00003055113,0.0000021941228,0.0000036765746,0.000006720089,0.000006038763,0.99909997,0.00018911979,0.0005040216,0.0001398536,0.0000017520186],"about_ca_topic_score_codex":0.009100775,"about_ca_topic_score_gemma":0.0068028807,"teacher_disagreement_score":0.009100775,"about_ca_system_score_codex":0.0015243915,"about_ca_system_score_gemma":0.0010380282,"threshold_uncertainty_score":0.018095613},"labels":[],"label_agreement":null},{"id":"W2166177494","doi":"10.1109/tsmcb.2003.811769","title":"A Neural Network Approach to Complete Coverage Path Planning","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":443,"is_retracted":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":"Robot; Motion planning; Artificial neural network; Path (computing); Computer science; Workspace; Obstacle; Obstacle avoidance; Artificial intelligence; Mobile robot; Geography; Computer network","score_opus":0.03547404330118932,"score_gpt":0.24236988124271855,"score_spread":0.20689583794152921,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166177494","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":[0.007820025,0.00044203261,0.98774755,0.00018898153,0.000026791195,0.000019064973,0.00003385843,0.000113560396,0.0036081523],"genre_scores_gemma":[0.7331495,0.0013300946,0.25463238,0.00015721994,0.000114321374,0.00031214242,0.00015534529,0.00006790631,0.010081112],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985814,0.000032199667,0.00000679114,0.00003829243,0.000045512083,0.00001901051],"domain_scores_gemma":[0.9998247,0.00009545225,0.000018241059,0.000009939221,0.000042178384,0.00000952188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023383909,0.0004966692,0.00044018246,0.00040626488,0.00030472918,0.00051214756,0.0008492068,0.0009838847,0.001961136],"category_scores_gemma":[0.000791533,0.00035546336,0.00042123243,0.00055713934,0.0005603835,0.0010490728,0.000545306,0.00088018767,0.00021580534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009889247,0.00000764946,0.00007529907,0.000020508103,0.00001037188,0.000026559814,0.000014616364,0.9729067,0.000719244,0.01065631,0.00023910469,0.0153137725],"study_design_scores_gemma":[0.0000018429463,0.0000056792896,0.000021975347,0.0000015361665,0.0000019247386,0.0000067224582,0.0000014931054,0.9956393,0.0001404079,0.003959076,0.00021814182,0.0000019562929],"about_ca_topic_score_codex":0.0069895866,"about_ca_topic_score_gemma":0.0053529837,"teacher_disagreement_score":0.0069895866,"about_ca_system_score_codex":0.00085632654,"about_ca_system_score_gemma":0.00066573464,"threshold_uncertainty_score":0.013897836},"labels":[],"label_agreement":null},{"id":"W2166460071","doi":"10.1109/3477.938269","title":"A decomposition of fuzzy relations","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Advanced Algebra and Logic","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematics; Fuzzy logic; Fuzzy number; Fuzzy classification; Decomposition; Defuzzification; Fuzzy set operations; Fuzzy mathematics; Fuzzy set; Algebra over a field; Algorithm; Computer science; Artificial intelligence; Pure mathematics","score_opus":0.01729282291372276,"score_gpt":0.24876288116304518,"score_spread":0.23147005824932243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166460071","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":[0.014956846,0.0009419186,0.95949715,0.00059248233,0.00012041193,0.00006605963,0.00012955401,0.00011888862,0.023576604],"genre_scores_gemma":[0.27205658,0.0012768086,0.7122208,0.00032988607,0.00029291693,0.00014029331,0.00038629468,0.00007993383,0.013216434],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986817,0.00035912564,0.00009681252,0.00035565,0.00040928158,0.00009745084],"domain_scores_gemma":[0.99906546,0.00028989417,0.00009047537,0.00025810115,0.00021930033,0.000076790435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013659553,0.0005786965,0.0005613393,0.0013666976,0.00089178205,0.0022551708,0.0006414182,0.00081917725,0.0050606346],"category_scores_gemma":[0.002979919,0.00031443138,0.0009487655,0.0011831084,0.0024879824,0.0036876898,0.0014085243,0.0017957233,0.0010716772],"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":[0.000024112995,0.000012341166,0.00012404608,0.00006606718,0.000011686878,0.00006311435,0.00037102608,0.0074876244,0.0040330365,0.94698006,0.0012096341,0.03961721],"study_design_scores_gemma":[0.000010149109,0.000053449596,0.00019683335,0.000054266715,0.00001614011,0.00021564667,0.00015662168,0.06071358,0.0021968163,0.9072466,0.029122166,0.000017687771],"about_ca_topic_score_codex":0.0009969177,"about_ca_topic_score_gemma":0.00072720513,"teacher_disagreement_score":0.0050606346,"about_ca_system_score_codex":0.00090633857,"about_ca_system_score_gemma":0.000705453,"threshold_uncertainty_score":0.016929567},"labels":[],"label_agreement":null},{"id":"W2167813323","doi":"10.1109/tsmcb.2010.2073702","title":"Experimental Analysis of Mobile-Robot Teleoperation via Shared Impedance Control","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Division of Mathematical Sciences; Technische Universität München","keywords":"Teleoperation; Reflection (computer programming); Obstacle avoidance; Computer science; Controller (irrigation); Simulation; Electrical impedance; Obstacle; Telerobotics; Robot; Haptic technology; Mobile robot; MATLAB; Fuzzy logic; Control theory (sociology); Engineering; Control (management); Artificial intelligence","score_opus":0.009252708615305624,"score_gpt":0.2255700098261036,"score_spread":0.21631730121079795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167813323","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":[0.9590794,0.000089254434,0.03904406,0.000039982846,0.000031106494,0.00012291435,0.00005161031,0.00023138477,0.001310374],"genre_scores_gemma":[0.99523675,0.00003259073,0.0041473135,0.000009665643,0.0000045096217,0.00008543753,0.000024579997,0.0000082032975,0.00045096007],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993794,0.00012932112,0.00004963254,0.00008811688,0.00025495302,0.00009856189],"domain_scores_gemma":[0.99882084,0.00057870103,0.00016176936,0.0001943296,0.00017901797,0.000065355875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047052515,0.0004883533,0.0004449161,0.00036572808,0.00028571565,0.00036228757,0.00064295967,0.0005715545,0.0025380985],"category_scores_gemma":[0.0017848901,0.00015101011,0.00029469738,0.00020301483,0.0005067562,0.0005642895,0.00070453994,0.0003793699,0.00021119355],"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":[0.002264594,0.0013580025,0.0013836898,0.0007862773,0.000068032095,0.0005409176,0.00076149724,0.027357372,0.92476815,0.0010859249,0.00019578962,0.039429758],"study_design_scores_gemma":[0.0006141448,0.018832643,0.0143042365,0.00006695319,0.00014172665,0.00075252476,0.0007130131,0.15935296,0.80165356,0.0010795052,0.0023926354,0.00009619144],"about_ca_topic_score_codex":0.00033215998,"about_ca_topic_score_gemma":0.00020110288,"teacher_disagreement_score":0.0025380985,"about_ca_system_score_codex":0.00015244515,"about_ca_system_score_gemma":0.00020146216,"threshold_uncertainty_score":0.008490741},"labels":[],"label_agreement":null},{"id":"W2169244603","doi":"10.1109/3477.931540","title":"Classification of grasps by robot hands","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robot Manipulation and Learning","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":"Simon Fraser University","funders":"","keywords":"GRASP; Linear subspace; Object (grammar); Kinematics; Artificial intelligence; Interpretation (philosophy); Computer science; Robot; Contact force; Computer vision; Space (punctuation); Mathematics; Geometry; Physics","score_opus":0.025640641027343793,"score_gpt":0.2300902844383014,"score_spread":0.20444964341095762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169244603","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":[0.7585139,0.0014093865,0.22666496,0.0002390787,0.00004908691,0.00025005414,0.0007085843,0.0010261942,0.011138713],"genre_scores_gemma":[0.96248776,0.00034525775,0.03539998,0.00003141724,0.000038249782,0.00009553563,0.00051459664,0.00005747303,0.0010298438],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991423,0.00010613136,0.00009161196,0.00018229765,0.0003152817,0.00016243309],"domain_scores_gemma":[0.9978873,0.00082110375,0.0003645157,0.00030435043,0.00040924642,0.00021347174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045849907,0.00047643707,0.00073513767,0.0040959106,0.00048175053,0.0011784503,0.00045782689,0.00080645934,0.003267662],"category_scores_gemma":[0.004917533,0.00024130892,0.0007228643,0.0019141356,0.0012579155,0.0015128446,0.001117296,0.00031404643,0.00070167135],"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":[0.0010768762,0.00017458519,0.08393182,0.0007601487,0.00022227292,0.0017304064,0.0021744568,0.04674577,0.14294557,0.040167935,0.0042338315,0.6758364],"study_design_scores_gemma":[0.00014273725,0.0008699957,0.3132577,0.00040507436,0.00023005088,0.006440809,0.0034303232,0.41664925,0.02940209,0.21084937,0.018008161,0.00031436462],"about_ca_topic_score_codex":0.0008598792,"about_ca_topic_score_gemma":0.0005561307,"teacher_disagreement_score":0.0040959106,"about_ca_system_score_codex":0.0003543703,"about_ca_system_score_gemma":0.00033616557,"threshold_uncertainty_score":0.010931492},"labels":[],"label_agreement":null},{"id":"W2169937880","doi":"10.1109/tsmcb.2009.2014736","title":"Automated Large-Scale Control of Gene Regulatory Networks","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Curse of dimensionality; State space; Control (management); Gene regulatory network; Markov decision process; Reduction (mathematics); Dimensionality reduction; Space (punctuation); State (computer science); Scale (ratio); Mathematical optimization; Machine learning; Markov process; Artificial intelligence; Algorithm; Mathematics; Gene","score_opus":0.006217990682234753,"score_gpt":0.21510425167019398,"score_spread":0.20888626098795923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169937880","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":[0.05151735,0.00018164371,0.9455116,0.00023436114,0.000021304186,0.000052380536,0.00008122727,0.00097118603,0.0014289526],"genre_scores_gemma":[0.8853098,0.00017149987,0.113074854,0.00005617499,0.000019890527,0.00013130477,0.00014914283,0.00007485817,0.0010125326],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992386,0.00024833606,0.000027662189,0.0002299885,0.00015993921,0.00009546237],"domain_scores_gemma":[0.9964986,0.002744545,0.00032268325,0.00020709416,0.00015222661,0.00007496113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001348101,0.00074935326,0.0009792108,0.0004161984,0.0005288084,0.0008373177,0.0010760512,0.0007616044,0.0014763142],"category_scores_gemma":[0.00401221,0.00041465354,0.0006441775,0.00046965512,0.001343021,0.0010198919,0.00088510674,0.0011505312,0.00013053296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022116234,0.00001634342,0.00016185713,0.000024142104,0.00000824581,0.000027385171,0.000021300031,0.9813277,0.0013830828,0.004300739,0.00016690031,0.012540268],"study_design_scores_gemma":[0.0000064230185,0.0000068111185,0.000042942625,0.0000012205061,0.0000017445518,0.0000037923721,0.00000436915,0.995644,0.00056037714,0.0036043532,0.0001221178,0.000001912884],"about_ca_topic_score_codex":0.01235154,"about_ca_topic_score_gemma":0.010186101,"teacher_disagreement_score":0.01235154,"about_ca_system_score_codex":0.0014402405,"about_ca_system_score_gemma":0.001643444,"threshold_uncertainty_score":0.024559319},"labels":[],"label_agreement":null},{"id":"W2172167902","doi":"10.1109/tsmcb.2011.2132716","title":"Target-Motion Prediction for Robotic Search and Rescue in Wilderness Environments","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Terrain; Search and rescue; Wilderness; Motion (physics); Wilderness area; Computer science; Artificial intelligence; Modular design; Robot; Mechanism (biology); Space (punctuation); Simulation; Computer vision; Machine learning; Human–computer interaction; Geography; Ecology; Biology; Cartography; Physics","score_opus":0.03977241979494068,"score_gpt":0.23674941604695598,"score_spread":0.1969769962520153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172167902","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":[0.017849091,0.0001091931,0.9814021,0.000049450362,0.000006621952,0.000014324725,0.000028804856,0.00013592426,0.00040455736],"genre_scores_gemma":[0.78878975,0.00026080635,0.20943594,0.000036082365,0.000032449538,0.00010058511,0.00016618289,0.000057505637,0.0011206198],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977547,0.00007009854,0.000012462005,0.000050406663,0.00007269206,0.000018838917],"domain_scores_gemma":[0.9989735,0.00061626214,0.00017820041,0.00007307983,0.00012446457,0.00003455192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007006203,0.0005089481,0.00050775975,0.00068677956,0.00036177004,0.00035964302,0.0008979745,0.00049727224,0.0007147068],"category_scores_gemma":[0.0033925697,0.00025501373,0.00031024293,0.0004163355,0.0006178772,0.00087023893,0.0008194451,0.000606091,0.00015371725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024406509,0.000011822594,0.0010323196,0.00002329836,0.000013500178,0.000029132867,0.000031971733,0.94921124,0.00077978696,0.0057069887,0.00018698322,0.042948637],"study_design_scores_gemma":[0.0000012520829,0.000009923611,0.00017747808,0.0000020044972,0.000001367204,0.0000063834395,0.0000033156666,0.99605775,0.00024400726,0.0033582177,0.00013540116,0.000002833196],"about_ca_topic_score_codex":0.0060436395,"about_ca_topic_score_gemma":0.0040273657,"teacher_disagreement_score":0.0060436395,"about_ca_system_score_codex":0.0005631853,"about_ca_system_score_gemma":0.0006916338,"threshold_uncertainty_score":0.012016952},"labels":[],"label_agreement":null},{"id":"W260234364","doi":"10.1109/tsmcb.2010.2082525","title":"Automatically Detecting Pain in Video Through Facial Action Units","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Emotion and Mood Recognition","field":"Psychology","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 Northern British Columbia","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Facial Action Coding System; Facial expression; Computer science; Artificial intelligence; Coding (social sciences); Frame (networking); Set (abstract data type); Action (physics); Computer vision; Physical medicine and rehabilitation; Medicine; Mathematics","score_opus":0.047691252784643645,"score_gpt":0.3007200289280679,"score_spread":0.2530287761434242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W260234364","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":[0.48479515,0.0010252605,0.5047526,0.00027502366,0.0001864382,0.00026106808,0.001054288,0.0030921886,0.0045580543],"genre_scores_gemma":[0.81775457,0.00048680557,0.1783409,0.00010726363,0.00007117374,0.00013064563,0.0008568068,0.00007064007,0.002181189],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972516,0.00006455602,0.000015548256,0.00006805878,0.000091732305,0.00003491385],"domain_scores_gemma":[0.9996025,0.00016568243,0.000071397015,0.00003511927,0.000101456164,0.000023996769],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003530604,0.00041223716,0.00037315048,0.0009155039,0.00011486456,0.00041019323,0.0003568648,0.00047055478,0.001027776],"category_scores_gemma":[0.001736969,0.00013688604,0.00024082995,0.00045009906,0.00015318509,0.00047026802,0.0003562436,0.00033730766,0.00046059137],"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":[0.0006365401,0.00018787947,0.011211524,0.00016686316,0.000048704886,0.00032512934,0.00015030458,0.0061719157,0.29769763,0.0009684641,0.00310157,0.67933345],"study_design_scores_gemma":[0.000050516614,0.00061307865,0.0885187,0.000047356138,0.000074183896,0.0011184659,0.00029987714,0.738985,0.16211867,0.0025700869,0.0055513745,0.000052708157],"about_ca_topic_score_codex":0.0015543676,"about_ca_topic_score_gemma":0.0017516812,"teacher_disagreement_score":0.0015543676,"about_ca_system_score_codex":0.00020674158,"about_ca_system_score_gemma":0.00018588109,"threshold_uncertainty_score":0.0034382343},"labels":[],"label_agreement":null},{"id":"W4233690929","doi":"10.1109/tsmcb.2005.860556","title":"Editorial","year":2005,"lang":"en","type":"editorial","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","score_opus":0.012464942307364566,"score_gpt":0.25013610188142477,"score_spread":0.2376711595740602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233690929","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":[0.000031878983,0.004250296,0.00011785907,0.024977976,0.9635778,0.00002786778,0.00006855555,0.00006868001,0.0068790237],"genre_scores_gemma":[0.00079025916,0.0040781503,0.00018610236,0.028162623,0.9089659,0.000046959954,0.00010490215,0.00009088877,0.05757417],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99552804,0.000725499,0.00045331646,0.00054542435,0.0023260002,0.00042165327],"domain_scores_gemma":[0.9815532,0.0034878983,0.0013304427,0.00084132573,0.009322468,0.003464741],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005313186,0.0025633604,0.0028609396,0.0043003517,0.0028722985,0.007127692,0.0024758596,0.009791686,0.057088375],"category_scores_gemma":[0.025821574,0.0009231177,0.0016386969,0.0015034046,0.0015207742,0.00325614,0.0019604045,0.010321672,0.041702867],"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":[0.000009313824,0.000003022107,0.0000066952016,0.000045253575,0.0000039249007,0.00004165505,0.0000033822919,0.0000059371773,0.000015237343,0.00010752331,0.99576545,0.0039926507],"study_design_scores_gemma":[0.000022080269,0.000009028264,0.00007917118,0.00013018548,0.000016079828,0.00012481379,0.000012261762,0.000025594,0.000044692482,0.0003636356,0.9991659,0.000006518567],"about_ca_topic_score_codex":0.0013819226,"about_ca_topic_score_gemma":0.0038720444,"teacher_disagreement_score":0.9429116,"about_ca_system_score_codex":0.0023403373,"about_ca_system_score_gemma":0.0031976646,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4254983785","doi":"10.1109/tsmcb.2008.925728","title":"A Multifaceted Perspective at Data Analysis: A Study in Collaborative Intelligent Agents","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Context (archaeology); Perspective (graphical); Process (computing); Exploit; Consistency (knowledge bases); Heuristics; Focus (optics); Function (biology); Fuzzy logic; Cluster analysis; Data science; Human–computer interaction; Artificial intelligence","score_opus":0.06271541074539363,"score_gpt":0.29962480710807243,"score_spread":0.2369093963626788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254983785","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":[0.008397599,0.007668468,0.9583677,0.016072743,0.00014897858,0.00008819268,0.000034019275,0.00008078988,0.009141494],"genre_scores_gemma":[0.2118094,0.005182712,0.77825665,0.0012107872,0.00064049487,0.00031885927,0.000059711754,0.00008740932,0.0024339173],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97678035,0.015175486,0.0011403867,0.002831656,0.0036005876,0.0004715261],"domain_scores_gemma":[0.9544012,0.038089816,0.0015598857,0.003376729,0.0017169873,0.0008555171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02360547,0.0011814827,0.0015605252,0.0048592044,0.0038947393,0.0111731095,0.0037423917,0.006165613,0.0017192307],"category_scores_gemma":[0.03466119,0.0010698503,0.0024761716,0.0058016544,0.020632451,0.016989497,0.005892381,0.006435218,0.00040803765],"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":[0.000013850218,0.00003528934,0.00064794347,0.00018175246,0.00006433022,0.00017325566,0.002972855,0.009222335,0.0003543038,0.96641505,0.00067388377,0.019245308],"study_design_scores_gemma":[0.00001952595,0.000045333563,0.00039127804,0.00016249891,0.00003679075,0.00019757557,0.0010033697,0.07015552,0.00047300867,0.91314703,0.014326796,0.000041377927],"about_ca_topic_score_codex":0.0038665398,"about_ca_topic_score_gemma":0.002604773,"teacher_disagreement_score":0.02360547,"about_ca_system_score_codex":0.003798257,"about_ca_system_score_gemma":0.0026038897,"threshold_uncertainty_score":0.12483913},"labels":[],"label_agreement":null}]}