{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":19,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":19,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"e5449fd77a16","filters":{"venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)"}},"results":[{"id":"W4309344223","doi":"10.1109/smc53654.2022.9945513","title":"Multimodal Human Activity Recognition for Smart Healthcare Applications","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Activity recognition; Modalities; Convolutional neural network; Computer science; Wearable computer; Robustness (evolution); Sensor fusion; Artificial intelligence; Deep learning; Assisted living; Machine learning; Human–computer interaction; Embedded system","authors":[{"name":"Md. Milon Islam","is_ca":true},{"name":"Sheikh Nooruddin","is_ca":true},{"name":"Fakhri Karray","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1138413629557532,"gpt":0.3348314930241096,"spread":0.2209901300683564,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007150472,0.0002833406,0.0003572898,0.0003242246,0.0007201894,0.0004760539,0.0009172515,0.0001001831,0.0001231931],"category_scores_gemma":[0.00002727936,0.0003295414,0.0001231021,0.0002324295,0.00006362078,0.0003629102,0.0002830545,0.0004036765,0.0000632302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002904633,"about_ca_system_score_gemma":0.000159532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001171084,"about_ca_topic_score_gemma":0.0004402879,"domain_scores_codex":[0.9970731,0.0003571846,0.0005263464,0.0008655372,0.0008410558,0.0003367845],"domain_scores_gemma":[0.9979822,0.0002914559,0.0004625095,0.0005131478,0.0005840583,0.0001666271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000433753,0.002053792,0.003984689,0.0007271081,0.0006793553,0.00004425396,0.003740655,0.000312812,0.0204815,0.5808215,0.01124778,0.3754728],"study_design_scores_gemma":[0.008999851,0.003358079,0.009818907,0.0006506027,0.000153788,0.0007567825,0.006405264,0.4968469,0.004511528,0.04537359,0.4191611,0.003963558],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3417383,0.0004480987,0.5915523,0.01127596,0.01117302,0.009350258,0.004482999,0.001071177,0.02890785],"genre_scores_gemma":[0.9922442,0.00003679784,0.0003290771,0.0003672931,0.0003411339,0.003369372,0.0002285428,0.0000289805,0.003054538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6505059,"threshold_uncertainty_score":0.9999157,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309345280","doi":"10.1109/smc53654.2022.9945274","title":"A Deep Averaged Reinforcement Learning Approach for the Traveling Salesman Problem","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Reinforcement learning; Travelling salesman problem; Heuristics; Forgetting; Computer science; Artificial intelligence; Convergence (economics); Generalization; Mathematical optimization; Process (computing); Machine learning; Mathematics; Algorithm","authors":[{"name":"Sirvan Parasteh","is_ca":true},{"name":"Amin Khorram","is_ca":true},{"name":"Malek Mouhoub","is_ca":true},{"name":"Samira Sadaoui","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04134696800989715,"gpt":0.2538691343529126,"spread":0.2125221663430154,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003987417,0.0001596174,0.0001484893,0.00009814147,0.0003484229,0.0001315367,0.000262892,0.00004103461,0.0001804462],"category_scores_gemma":[0.000009937979,0.0001483819,0.00005480344,0.0001175906,0.00003435107,0.00005569989,0.00002075038,0.0003565408,0.000004677055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001035245,"about_ca_system_score_gemma":0.00003063671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005313172,"about_ca_topic_score_gemma":0.00003757375,"domain_scores_codex":[0.9987261,0.00004037851,0.0004159758,0.0002263987,0.0004096629,0.0001814724],"domain_scores_gemma":[0.9994901,0.00008578665,0.00009444232,0.0001459742,0.0001416994,0.00004202739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002577344,0.00002810066,0.0001559058,0.00007303798,0.0001234038,0.00000106798,0.001472416,0.8608704,0.0005805626,0.1352892,0.0004378513,0.0009422048],"study_design_scores_gemma":[0.0005541577,0.00008739528,0.0004063736,0.00002046849,0.00002976031,0.00001002684,0.003505809,0.9626601,0.00006159157,0.0001901674,0.03228529,0.0001888103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06334584,0.0003934338,0.855496,0.0006664166,0.002772121,0.002703036,0.0001556626,0.0004200705,0.07404742],"genre_scores_gemma":[0.9935671,0.0001304139,0.0003227464,0.0001038347,0.0001077823,0.0009219557,0.0003087073,0.00002647078,0.004511003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9302213,"threshold_uncertainty_score":0.605084,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309342498","doi":"10.1109/smc53654.2022.9945590","title":"Multi-Group Role Assignment with Constraints in Adaptive Collaboration","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Collaboration in agile enterprises","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Nipissing University","funders":"Nature; Fundamental Research Funds for the Central Universities; Natural Science Foundation of Chongqing","keywords":"Task (project management); Computer science; Set (abstract data type); Group (periodic table); Process (computing); Mathematical optimization; Scheme (mathematics); Operations research; Engineering; Mathematics","authors":[{"name":"Zhihang Yu","is_ca":false},{"name":"Ruisi Yang","is_ca":false},{"name":"Xiangjun Liu","is_ca":false},{"name":"Haibin Zhu","is_ca":true},{"name":"Libo Zhang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03347475054769768,"gpt":0.257146113009103,"spread":0.2236713624614053,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003761778,0.0002342848,0.000238667,0.0003997175,0.0002068632,0.0006009795,0.0003213047,0.00004975569,0.0009078846],"category_scores_gemma":[0.00002917556,0.0002358042,0.00002612443,0.0004276191,0.000104172,0.0004318426,0.0001577942,0.0002493634,0.00005798252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002726644,"about_ca_system_score_gemma":0.00009018563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006475231,"about_ca_topic_score_gemma":0.001181095,"domain_scores_codex":[0.9979783,0.00007379391,0.000438703,0.0004646568,0.0008287261,0.000215837],"domain_scores_gemma":[0.9989843,0.00005535033,0.0003784688,0.0001836478,0.0003736212,0.00002455419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001547924,0.001460385,0.06817675,0.0001594457,0.0003490086,0.0002198025,0.001904714,0.04027415,0.005986193,0.863687,0.01152675,0.004707908],"study_design_scores_gemma":[0.008849086,0.0006816982,0.01923159,0.0005921563,0.0001161336,0.00004961906,0.0805957,0.6585714,0.0001519894,0.002098226,0.2273193,0.001743161],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7029613,0.0005458902,0.01621222,0.004175176,0.0092389,0.004488413,0.0007553407,0.0003894921,0.2612333],"genre_scores_gemma":[0.9962062,0.00002762958,0.0001049209,0.0006160997,0.0002956768,0.0004356622,0.0001312055,0.00002667072,0.002155979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8615888,"threshold_uncertainty_score":0.9940699,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309374308","doi":"10.1109/smc53654.2022.9945151","title":"Portfolio Selection for SAT Instances","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Portfolio; Solver; Context (archaeology); Cluster analysis; Complement (music); Mathematical optimization; Greedy algorithm; Set (abstract data type); Boolean satisfiability problem; Limit (mathematics); Selection (genetic algorithm); Theoretical computer science; Artificial intelligence; Mathematics; Algorithm","authors":[{"name":"Armin Sadreddin","is_ca":true},{"name":"Malek Mouhoub","is_ca":true},{"name":"Samira Sadaoui","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04584683663469806,"gpt":0.2846385741773983,"spread":0.2387917375427002,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003262301,0.0001611469,0.0001700302,0.0002431392,0.0003252702,0.0003586017,0.0004465905,0.00004786893,0.0003630203],"category_scores_gemma":[0.00002068201,0.0001741637,0.00005584055,0.0002030552,0.00003975678,0.0002471888,0.0001015766,0.0001819942,0.00001508429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001599834,"about_ca_system_score_gemma":0.000119796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009227714,"about_ca_topic_score_gemma":0.00009398078,"domain_scores_codex":[0.9983641,0.00009078875,0.000350408,0.0004441385,0.0005614319,0.0001891464],"domain_scores_gemma":[0.9991964,0.00007496671,0.0002320217,0.0001769776,0.0002452502,0.0000743553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006037378,0.00008216593,0.002917061,0.00002618436,0.00007450455,0.000005229895,0.0004322334,0.007009826,0.0006811002,0.9653485,0.007774495,0.01558832],"study_design_scores_gemma":[0.00108845,0.0004354388,0.002380215,0.00004549076,0.00001846961,0.0001500863,0.001038171,0.8432764,0.0002505917,0.004923016,0.1459259,0.0004677265],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08101334,0.0003754857,0.7962163,0.004163848,0.01505554,0.00178622,0.0003373073,0.0005065603,0.1005454],"genre_scores_gemma":[0.9900216,0.0001516193,0.001187336,0.0003907945,0.0001635496,0.0002182977,0.00005802058,0.0000123716,0.00779641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9604255,"threshold_uncertainty_score":0.7102191,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309676745","doi":"10.1109/smc53654.2022.9945394","title":"Fault-Resilience Role Engine for an Autonomous Cooperative Multi-Robot System using E-CARGO","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Nipissing University","funders":"","keywords":"Robustness (evolution); Computer science; Redundancy (engineering); Fault tolerance; Distributed computing; Mobile robot; Resilience (materials science); Process (computing); Robot; Motion planning; Reliability engineering; Engineering; Artificial intelligence","authors":[{"name":"Behzad Akbari","is_ca":true},{"name":"Haibin Zhu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06881004630316598,"gpt":0.3101686550949578,"spread":0.2413586087917919,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007064119,0.0003795772,0.0004846798,0.0002131253,0.0006016262,0.0007752297,0.001556107,0.0001004493,0.00002896516],"category_scores_gemma":[0.00002695476,0.0003860659,0.00009693015,0.0002644661,0.00007816886,0.0004510489,0.0002880637,0.0003241212,0.00001834591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004235871,"about_ca_system_score_gemma":0.0002331637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006526691,"about_ca_topic_score_gemma":0.00007556431,"domain_scores_codex":[0.9966898,0.0002867412,0.0007281328,0.0009765876,0.0008582411,0.0004604735],"domain_scores_gemma":[0.9981235,0.0001043006,0.0004053195,0.0005968853,0.0005601319,0.0002099031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001296315,0.0005157578,0.0003889298,0.0002121612,0.0002257726,0.00007342114,0.002742108,0.2721509,0.01255136,0.7053981,0.001126591,0.004485317],"study_design_scores_gemma":[0.0009810209,0.0004163019,0.0001674046,0.0001313484,0.00001649244,0.0001595917,0.00339609,0.9792496,0.0003354965,0.00006782732,0.01462545,0.0004533693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1000889,0.0008884605,0.8801081,0.0002888023,0.006977902,0.002121127,0.001633061,0.0004117417,0.007481823],"genre_scores_gemma":[0.9936945,0.00002022248,0.002210693,0.0001298181,0.0002276939,0.000443379,0.00009874492,0.000031338,0.00314362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8936055,"threshold_uncertainty_score":0.9998592,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309344674","doi":"10.1109/smc53654.2022.9945351","title":"A Formal Theory of AI Trustworthiness for Evaluating Autonomous AI Systems","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Novelty; Computer science; Trustworthiness; Artificial intelligence; Context (archaeology); Robot; Human–computer interaction; Cognition; Intelligent decision support system; Psychology; Computer security","authors":[{"name":"Yingxu Wang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07171883577656224,"gpt":0.3280246335687882,"spread":0.256305797792226,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002120809,0.0002510085,0.0003890035,0.0002322302,0.0003623893,0.0003662888,0.001035306,0.00007200663,0.00004872496],"category_scores_gemma":[0.00007261983,0.0002518909,0.0001111657,0.0002020285,0.0000711977,0.0002141718,0.0004622784,0.0004074071,0.000005449236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001231804,"about_ca_system_score_gemma":0.0002299811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000104916,"about_ca_topic_score_gemma":0.000009457729,"domain_scores_codex":[0.9971425,0.0004000919,0.0006769209,0.00057341,0.0008467038,0.0003604092],"domain_scores_gemma":[0.9978385,0.0005133009,0.0004505356,0.0003565665,0.0007504344,0.00009066694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001648666,0.0001257569,0.0004675813,0.0001290745,0.0001536777,0.00001154046,0.000996116,0.02322708,0.0002032098,0.9484311,0.001436429,0.02465353],"study_design_scores_gemma":[0.0009172896,0.0005990454,0.0003316402,0.0001972847,0.00002899175,0.00008165936,0.0007592052,0.9858079,0.00006254323,0.005950527,0.004959468,0.0003044546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1298612,0.001175814,0.8411027,0.0009257648,0.01137982,0.001535387,0.0002708684,0.000215841,0.01353263],"genre_scores_gemma":[0.9950658,0.00002816827,0.0002475157,0.0003720664,0.0003233621,0.0003081298,0.00003945886,0.00002154245,0.003593958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9625808,"threshold_uncertainty_score":0.9999933,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309679509","doi":"10.1109/smc53654.2022.9945496","title":"Evolutionary Mapping with Multiple Unmanned Aerial Vehicles","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Drone; Computer science; Context (archaeology); Motion planning; Obstacle; Plan (archaeology); Real-time computing; Search and rescue; Evolutionary algorithm; Operations research; Artificial intelligence; Robot; Engineering","authors":[{"name":"Ali Moltajaei Farid","is_ca":true},{"name":"Malek Mouhoub","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04777489517899604,"gpt":0.2558853031340413,"spread":0.2081104079550453,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004032606,0.0002556623,0.0002702657,0.0002639215,0.0003960735,0.0003385477,0.001145204,0.00006131774,0.00006963668],"category_scores_gemma":[0.00003141473,0.0002504929,0.00004806259,0.000242107,0.0000898403,0.0002295052,0.0003834289,0.0003633037,0.00004600802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002013555,"about_ca_system_score_gemma":0.0001615941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002925188,"about_ca_topic_score_gemma":0.000009891851,"domain_scores_codex":[0.9972382,0.0002235892,0.0004091978,0.0006597203,0.001131029,0.0003382844],"domain_scores_gemma":[0.9988111,0.0001665041,0.0002655067,0.0004167533,0.0002144448,0.0001256825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006882317,0.00103284,0.03154827,0.0002053789,0.0009024777,0.001251485,0.008162128,0.1514981,0.008530772,0.7515868,0.03449373,0.0100998],"study_design_scores_gemma":[0.001402167,0.0004754734,0.008057256,0.0001467501,0.00001297712,0.0003639283,0.001368067,0.9658265,0.0001038909,0.001034719,0.02068503,0.0005232339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5763419,0.001318147,0.3337616,0.006974045,0.02417918,0.002404992,0.0007363372,0.001188626,0.05309511],"genre_scores_gemma":[0.9893414,0.0000370805,0.005740222,0.0002424492,0.0003304187,0.0001604736,0.00005838627,0.00002166455,0.004067937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8143284,"threshold_uncertainty_score":0.9999948,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309342487","doi":"10.1109/smc53654.2022.9945363","title":"Concurrent Consideration of Human and Machine Reliability in Human-Machine Systems - A Virtual Environment Approach","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Alberta Innovates","keywords":"Computer science; Human–machine system; Reliability (semiconductor); Virtual machine; Reliability engineering; Human–computer interaction; Operating system; Engineering","authors":[{"name":"Lida Ghaemi Dizaji","is_ca":true},{"name":"Yaoping Hu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07234148971773913,"gpt":0.3437149249937347,"spread":0.2713734352759956,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000888045,0.0002591815,0.0004366947,0.00031047,0.0002493483,0.000116952,0.0002448913,0.0000974353,0.002725168],"category_scores_gemma":[0.00002227007,0.000268327,0.00005929749,0.00007313672,0.0001731548,0.00009152649,0.000129573,0.0004965343,0.000021287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002390115,"about_ca_system_score_gemma":0.0000307124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001696764,"about_ca_topic_score_gemma":0.00009077571,"domain_scores_codex":[0.9967936,0.0007095291,0.00103621,0.0005943274,0.0006649045,0.0002014098],"domain_scores_gemma":[0.9988171,0.0001520718,0.0005120016,0.0003211361,0.0001052062,0.00009245546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001526922,0.001164437,0.01069823,0.0001440188,0.0001992057,0.00002160939,0.005469488,0.005040584,0.002893824,0.9710062,0.002299161,0.0009105818],"study_design_scores_gemma":[0.02051638,0.006611384,0.1114226,0.0007323477,0.0002737849,0.0008667454,0.07028092,0.659153,0.0004577948,0.003370701,0.1230858,0.003228547],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9206831,0.0006886477,0.001626877,0.0003479548,0.003453461,0.001271411,0.0007047432,0.00007076698,0.07115307],"genre_scores_gemma":[0.9915127,0.00006586263,0.000007747187,0.00008333955,0.00009525969,0.0003627251,0.0003314138,0.00002202634,0.007518902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9676355,"threshold_uncertainty_score":0.9999769,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309345270","doi":"10.1109/smc53654.2022.9945231","title":"Improving Time Series Generation of GANs through Soft Dynamic Time Warping Loss","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Dynamic time warping; Computer science; Series (stratigraphy); Metric (unit); Image warping; Time series; Sequence (biology); Function (biology); Algorithm; Generative grammar; Real-time computing; Artificial intelligence; Machine learning","authors":[{"name":"Xiaozhuo Yu","is_ca":true},{"name":"Fakhri Karray","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03317069649812149,"gpt":0.249819329936047,"spread":0.2166486334379255,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004264736,0.0002151294,0.000326213,0.0001528738,0.0003155025,0.0003472157,0.0007646607,0.00005438978,0.0004383787],"category_scores_gemma":[0.00002475467,0.0002210797,0.00009227303,0.0002194631,0.00008013625,0.0004577152,0.000375685,0.0002113513,0.00004251377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001263161,"about_ca_system_score_gemma":0.00008980963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000295228,"about_ca_topic_score_gemma":0.00003769363,"domain_scores_codex":[0.9978061,0.0001366605,0.0005697766,0.0005123765,0.0007316046,0.0002434375],"domain_scores_gemma":[0.9988166,0.00005641378,0.0004658811,0.0003477313,0.000258045,0.00005530729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001892833,0.0004696525,0.0008192477,0.0003149539,0.0009133174,0.0001488667,0.009691836,0.06442662,0.2206174,0.6679097,0.004871202,0.02962799],"study_design_scores_gemma":[0.0002382902,0.0002370624,0.00006345219,0.00004907719,0.00002333249,0.00007731355,0.0004785875,0.9932306,0.0007768901,0.0006811012,0.003878749,0.00026555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6102415,0.001288755,0.3379025,0.003218251,0.005425986,0.001132846,0.0005739964,0.0004060283,0.03981022],"genre_scores_gemma":[0.9845068,0.00007642143,0.001340517,0.0001008077,0.0001552029,0.0000397224,0.00008838851,0.00001969483,0.01367239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.928804,"threshold_uncertainty_score":0.9015369,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309374654","doi":"10.1109/smc53654.2022.9945605","title":"Managing Inconsistency With an Optimal Distribution of Information Granularity in Fuzzy Preference Relations","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Junta de Andalucía","keywords":"Granularity; Consistency (knowledge bases); Pairwise comparison; Preference; Data mining; Computer science; Fuzzy logic; Reliability (semiconductor); Matrix (chemical analysis); Process (computing); Artificial intelligence; Mathematics; Statistics","authors":[{"name":"Francisco Javier Cabrerizo","is_ca":false},{"name":"Juan Carlos Gonzalez-Quesada","is_ca":false},{"name":"Enrique Herrera‐Viedma","is_ca":false},{"name":"Artūras Kaklauskas","is_ca":false},{"name":"Witold Pedrycz","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1432377727312265,"gpt":0.3576604413775825,"spread":0.214422668646356,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002411354,0.0002200146,0.0003708581,0.0006825445,0.0002611855,0.0005386478,0.0009314092,0.0000694753,0.0004968846],"category_scores_gemma":[0.0003869411,0.0001967676,0.0000548776,0.0006120725,0.0001300469,0.0009785222,0.0002792372,0.0004148039,0.00003353012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002121824,"about_ca_system_score_gemma":0.0001566952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004872174,"about_ca_topic_score_gemma":0.0002672168,"domain_scores_codex":[0.9950296,0.0005291589,0.001292734,0.0005107233,0.002404456,0.0002332978],"domain_scores_gemma":[0.9973736,0.0004149302,0.0007983546,0.0005268857,0.0007792752,0.0001069028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002142882,0.0007546294,0.07630318,0.00008720661,0.0001317326,0.00007945039,0.006460811,0.1012469,0.0006980441,0.7755741,0.002111152,0.03440995],"study_design_scores_gemma":[0.002925236,0.001083195,0.1203944,0.0003513689,0.0000454373,0.0001748575,0.02125229,0.7977296,0.0001272573,0.03818414,0.0168957,0.0008364875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9612272,0.00006161668,0.0178744,0.0004460952,0.001067913,0.0005750729,0.0006840888,0.00003845964,0.01802518],"genre_scores_gemma":[0.9983356,0.00002421473,0.0005669819,0.00007873993,0.00003663538,0.00009773313,0.0002302181,0.0000102319,0.0006196324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7373899,"threshold_uncertainty_score":0.8023952,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309679321","doi":"10.1109/smc53654.2022.9945270","title":"A Data-Centric Approach to Evaluate Requirements Engineering in Multidisciplinary Projects","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Multidisciplinary approach; Computer science; Requirements engineering; Systems engineering; Engineering management; Requirements analysis; Software engineering; Engineering; Software","authors":[{"name":"Ali Salmani","is_ca":true},{"name":"Alireza Imani","is_ca":true},{"name":"Majid Bahrehvar","is_ca":true},{"name":"Linda Duffett‐Leger","is_ca":true},{"name":"Mohammad Moshirpour","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1477489476025574,"gpt":0.3454449707628305,"spread":0.1976960231602731,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001086712,0.000203881,0.0002077684,0.0004202343,0.00009885991,0.0003052488,0.001787123,0.00004351477,0.00003273226],"category_scores_gemma":[0.00008414244,0.0002146074,0.00002448492,0.0003975207,0.00001145724,0.0003752961,0.001260465,0.0003342812,0.00001112877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001903954,"about_ca_system_score_gemma":0.0000811256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000179418,"about_ca_topic_score_gemma":0.000007058646,"domain_scores_codex":[0.9976886,0.0001274226,0.0003778246,0.0006841644,0.0008478851,0.0002740828],"domain_scores_gemma":[0.9989015,0.0001200806,0.0001401169,0.0006548167,0.00008922401,0.00009430487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004126792,0.00247275,0.01072299,0.0007456803,0.0005521858,0.0005303492,0.01023262,0.2658281,0.002557074,0.6417586,0.04436712,0.01981987],"study_design_scores_gemma":[0.0004415464,0.0002029939,0.001312117,0.0000770864,0.000007772299,0.00005812102,0.0001973634,0.9783516,0.00003375831,0.0001783315,0.01885191,0.0002873877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2565137,0.001276166,0.671554,0.002593215,0.01089632,0.004857661,0.0005694457,0.001528948,0.0502106],"genre_scores_gemma":[0.988418,0.00009823956,0.00956393,0.00009826302,0.0001042911,0.000369361,0.00005793318,0.00002152052,0.001268414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7319043,"threshold_uncertainty_score":0.8751433,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309344919","doi":"10.1109/smc53654.2022.9945095","title":"Constructing Digital Twins for IEC61499 Based Distributed Control Systems","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Construct (python library); Computer science; Architecture; Automation; Digital control; Control (management); Distributed computing; Set (abstract data type); Reference architecture; Software architecture; Engineering; Artificial intelligence; Computer network; Operating system","authors":[{"name":"Jonathan Lesage","is_ca":true},{"name":"Robert W. Brennan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03479701560744958,"gpt":0.2453183827777518,"spread":0.2105213671703022,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002472832,0.0002774366,0.0003271398,0.0001824711,0.0001669822,0.0007728501,0.0003862551,0.00009919094,0.0001369271],"category_scores_gemma":[0.00003797587,0.0003103751,0.0000888461,0.000125911,0.00007459641,0.0002865314,0.0000315141,0.0003441366,0.00002171149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003292931,"about_ca_system_score_gemma":0.00006859178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002702942,"about_ca_topic_score_gemma":0.000004858015,"domain_scores_codex":[0.9980561,0.00004720662,0.0006459253,0.0003017174,0.0006364295,0.0003125811],"domain_scores_gemma":[0.99903,0.0002555156,0.0001600885,0.0002042053,0.0002253288,0.0001248804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002435154,0.0001924563,0.004127164,0.000754255,0.0007200345,0.00004039633,0.0003766161,0.4653156,0.0005648982,0.5057099,0.0182703,0.003684865],"study_design_scores_gemma":[0.00220628,0.0001819471,0.00007499362,0.0001732478,0.0000362244,0.00009524584,0.005511337,0.9092098,0.0001442158,0.0002664968,0.08157751,0.0005226599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.202368,0.0005727701,0.3086682,0.001042799,0.02708703,0.004522008,0.06164027,0.001462599,0.3926363],"genre_scores_gemma":[0.9971517,0.000009719023,0.00002663055,0.00005834833,0.0002374143,0.0005039122,0.0008649127,0.00004563096,0.001101788],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7947837,"threshold_uncertainty_score":0.9999349,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309344693","doi":"10.1109/smc53654.2022.9945117","title":"A Machine Learning Based Approach to Detect Fault Injection Attacks in IoT Software Systems","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Software; Fault injection; Exploit; Embedded system; Software system; Attack surface; Software fault tolerance; Fault (geology); Machine learning; Artificial intelligence; Real-time computing; Computer security; Operating system","authors":[{"name":"Aakash Gangolli","is_ca":true},{"name":"Qusay H. Mahmoud","is_ca":true},{"name":"Akramul Azim","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03888005311913169,"gpt":0.2813813537436144,"spread":0.2425013006244827,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007453206,0.0003072295,0.0003498326,0.0007544521,0.0002896149,0.0004089885,0.0009815056,0.0001004732,0.00003133235],"category_scores_gemma":[0.0001067118,0.0003373449,0.00006524621,0.000570024,0.00003668385,0.0001767485,0.0003610226,0.0007429236,0.00001758679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005176071,"about_ca_system_score_gemma":0.00009650655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009785369,"about_ca_topic_score_gemma":0.00007913725,"domain_scores_codex":[0.9967989,0.0004329509,0.0005827605,0.0008488019,0.0009982991,0.000338284],"domain_scores_gemma":[0.9987327,0.0001446323,0.0003092715,0.0004252162,0.0002569907,0.0001312244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002306927,0.0002932461,0.002636501,0.0002099399,0.00008167922,0.00007768202,0.001218521,0.9145691,0.002001735,0.05924548,0.001078758,0.01835663],"study_design_scores_gemma":[0.0006443623,0.0007894323,0.000323109,0.0001279569,0.000007062107,0.0001755415,0.0006038464,0.9660634,0.0005026655,0.0005245566,0.02972744,0.0005106083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01431255,0.0002531745,0.976255,0.000174668,0.002148301,0.0009436345,0.00007171142,0.0005690579,0.005271891],"genre_scores_gemma":[0.9912522,0.00003434034,0.00457627,0.0002319011,0.0001090005,0.0008548436,0.00003460253,0.00003497734,0.002871838],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9769397,"threshold_uncertainty_score":0.9999079,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309345632","doi":"10.1109/smc53654.2022.9945528","title":"Improving imbalanced dataset classification using Conditional Classifier-Generator (cCGen)","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Computer science; Classifier (UML); Machine learning; Artificial intelligence; Generator (circuit theory); Sampling (signal processing); Oversampling; Synthetic data; Data mining; Bandwidth (computing)","authors":[{"name":"Aniket Chakraborty","is_ca":true},{"name":"Anupama Vijaya Nadarja","is_ca":true},{"name":"Abbas S. Milani","is_ca":true},{"name":"Javier Perez Tobia","is_ca":true},{"name":"Apurva Narayan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07074704000648549,"gpt":0.2766460503492664,"spread":0.2058990103427809,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002656307,0.0002474253,0.0002243581,0.0001851724,0.0002842364,0.0002270364,0.0003483422,0.00007966725,0.000491484],"category_scores_gemma":[0.00001561316,0.0002791302,0.00004647663,0.0001254225,0.00005583421,0.000167848,0.00009260025,0.0003631014,0.00002319148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002517052,"about_ca_system_score_gemma":0.00007080984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001346848,"about_ca_topic_score_gemma":0.00003684067,"domain_scores_codex":[0.9981974,0.00008959376,0.0004586755,0.0003882843,0.0005947457,0.000271312],"domain_scores_gemma":[0.9993097,0.00005944218,0.0001745448,0.0002423741,0.0001053272,0.0001086096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001449,0.0002099795,0.002387924,0.0002940167,0.0005203267,0.00009737317,0.000631531,0.2721542,0.3229318,0.3571129,0.03902973,0.004485372],"study_design_scores_gemma":[0.0004987098,0.00007171712,0.0003796632,0.00005188651,0.0000264653,0.00008128239,0.0006556045,0.9413856,0.001019639,0.0002395058,0.05520105,0.0003888361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9152786,0.001011436,0.01814366,0.0003021526,0.01454685,0.0007321936,0.01577529,0.0004762666,0.03373352],"genre_scores_gemma":[0.994655,0.00009005053,0.0001694485,0.0001355968,0.000504756,0.0001053076,0.003385037,0.00004260902,0.000912232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6692314,"threshold_uncertainty_score":0.9999661,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309679519","doi":"10.1109/smc53654.2022.9945250","title":"Activity Ratio to Measure Physical Demand of Cognitive Workload","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Alberta Innovates","keywords":"Workload; Measure (data warehouse); Computer science; Cognition; Psychology; Data mining; Operating system","authors":[{"name":"Nusrat Zerin Zenia","is_ca":true},{"name":"Stanley Tarng","is_ca":true},{"name":"Yaoping Hu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07856786339092965,"gpt":0.3703474229794786,"spread":0.291779559588549,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003803247,0.0002043052,0.0003210279,0.0002338761,0.0001829573,0.00009206578,0.0002918233,0.00006407236,0.004367168],"category_scores_gemma":[0.00006278444,0.0002127626,0.00008940032,0.0001560619,0.0000727983,0.00008818739,0.00009540014,0.0003831879,0.0002485345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001121669,"about_ca_system_score_gemma":0.00006088254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002215114,"about_ca_topic_score_gemma":0.00005775585,"domain_scores_codex":[0.9977776,0.0004323062,0.0003978482,0.0004402257,0.000756145,0.0001959128],"domain_scores_gemma":[0.9987105,0.0002812057,0.0003013428,0.0002162653,0.000374169,0.0001165746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.004922765,0.003610723,0.005729642,0.0001285585,0.001979569,0.0001137186,0.0456676,0.002151727,0.01920288,0.8323806,0.04589804,0.03821419],"study_design_scores_gemma":[0.02578327,0.01126237,0.3211547,0.003555663,0.0009397431,0.000956197,0.1605736,0.1863023,0.0130651,0.007906824,0.2619595,0.006540834],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8267581,0.00007036211,0.002814364,0.0008461762,0.003843587,0.000614242,0.0003663743,0.00006553128,0.1646212],"genre_scores_gemma":[0.9796116,0.00001439802,0.000006187016,0.0003380102,0.0002708323,0.0002936668,0.00003390543,0.00001981833,0.01941153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8244737,"threshold_uncertainty_score":0.996543,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309345821","doi":"10.1109/smc53654.2022.9945362","title":"Enhancing Fresh Produce Yield Forecasting Using Vegetation Indices from Satellite Images","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Zayed University","keywords":"Normalized Difference Vegetation Index; Artificial neural network; Deep learning; Interpolation (computer graphics); Computer science; Satellite; Feed forward; Artificial intelligence; Feedforward neural network; Machine learning; Leaf area index; Engineering","authors":[{"name":"Islam Nasr","is_ca":true},{"name":"Lobna Nassar","is_ca":true},{"name":"Fakhri Karray","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05650344476441822,"gpt":0.2576504104452648,"spread":0.2011469656808466,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003835098,0.0002264157,0.000210194,0.00008161367,0.0003306502,0.0002848161,0.0003678765,0.00006947326,0.0006114964],"category_scores_gemma":[0.00006885693,0.0002137077,0.00004647474,0.0001619599,0.00009175699,0.0002033232,0.0002421592,0.0003608309,0.00005654372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003024433,"about_ca_system_score_gemma":0.00002322307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002823944,"about_ca_topic_score_gemma":0.0007309521,"domain_scores_codex":[0.9976429,0.0001520784,0.000420883,0.0005940464,0.0009402512,0.0002498646],"domain_scores_gemma":[0.9991463,0.0001426123,0.0003685885,0.0002096814,0.00005425051,0.00007856223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001286808,0.0002286695,0.03872429,0.0001077711,0.0002213807,0.0001576255,0.007495505,0.05796587,0.8762023,0.001885023,0.003103298,0.0137796],"study_design_scores_gemma":[0.002260577,0.0009642883,0.1477581,0.002259722,0.0003247165,0.0007649802,0.02648202,0.6294177,0.1331328,0.00468553,0.04830208,0.003647463],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9721966,0.0002951588,0.0004328873,0.0002210666,0.001875624,0.0003280175,0.00005987431,0.00004886177,0.02454192],"genre_scores_gemma":[0.9963046,0.00009624989,0.0008539087,0.0001621374,0.0003187126,0.00001253325,0.00006345293,0.00002205991,0.002166339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7430695,"threshold_uncertainty_score":0.8714749,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309342738","doi":"10.1109/smc53654.2022.9945530","title":"COVID-19 Self-Test Guidance System For Swab Collection Using Deep Learning","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Artificial intelligence; Generalization; Data collection; Telehealth; Software deployment; Test (biology); Sample (material); Sampling (signal processing); Quality (philosophy); Inference; Machine learning; Computer vision; Telemedicine; Statistics; Health care","authors":[{"name":"Youssef Abdelkareem","is_ca":true},{"name":"Islam Nasr","is_ca":true},{"name":"Lobna Nassar","is_ca":true},{"name":"Fakhri Karray","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07361408800445832,"gpt":0.3460364946927795,"spread":0.2724224066883212,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009384949,0.000307118,0.0004808938,0.0004198655,0.0007421823,0.0002250371,0.0003009011,0.0001155998,0.0002574408],"category_scores_gemma":[0.0006531921,0.0003426908,0.0001271653,0.0003037965,0.00006416446,0.0000837414,0.0001364241,0.0004366977,0.00001648456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00267496,"about_ca_system_score_gemma":0.0007349817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001058576,"about_ca_topic_score_gemma":0.00009885992,"domain_scores_codex":[0.9970484,0.0002451312,0.0006696996,0.000709529,0.0009771903,0.0003500368],"domain_scores_gemma":[0.9976764,0.0007554768,0.0004816671,0.0002961666,0.0004863802,0.0003039557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006233853,0.005450208,0.1602763,0.01932141,0.00418962,0.001505356,0.02048744,0.283555,0.07005349,0.2563235,0.1677648,0.004839001],"study_design_scores_gemma":[0.003281451,0.001117929,0.0006790691,0.0005137722,0.000244836,0.000605943,0.004765207,0.6634787,0.0004094341,0.0001017811,0.3243067,0.0004951644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8329151,0.004574821,0.06156966,0.03443663,0.02688571,0.0121433,0.001281711,0.002714799,0.02347822],"genre_scores_gemma":[0.9897343,0.0001586824,0.0004034485,0.002676115,0.0005220135,0.0005913508,0.0001138545,0.00006562547,0.005734615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3799237,"threshold_uncertainty_score":0.9999025,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309374658","doi":"10.1109/smc53654.2022.9945481","title":"Optimal Robust Control For Tremor Suppression in Parkinson’s Disease","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Neurological disorders and treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"","keywords":"Parkinson's disease; Control (management); Computer science; Control theory (sociology); Physical medicine and rehabilitation; Robust control; Disease; Neuroscience; Medicine; Psychology; Control system; Engineering; Artificial intelligence; Electrical engineering; Internal medicine","authors":[{"name":"Mobin Saeedi","is_ca":false},{"name":"Jafar Zarei","is_ca":false},{"name":"Hoda Balouchi","is_ca":false},{"name":"Roozbeh Razavi‐Far","is_ca":true},{"name":"Mehrdad Saif","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05637542897093505,"gpt":0.2966032195684166,"spread":0.2402277905974815,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001549833,0.0001869844,0.0003000317,0.0001375887,0.0001139609,0.00006209536,0.0001622736,0.00004708437,0.0004944243],"category_scores_gemma":[0.00004197608,0.0001590331,0.00008415877,0.00006090856,0.00004571992,0.00004039618,0.00005461907,0.0002097665,0.000009980562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009404688,"about_ca_system_score_gemma":0.0000633816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009091279,"about_ca_topic_score_gemma":0.00001669077,"domain_scores_codex":[0.9984432,0.0001012108,0.0003252021,0.0004398114,0.000467129,0.0002234504],"domain_scores_gemma":[0.9993602,0.0001061875,0.0001196479,0.0001701495,0.00008753004,0.0001562747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.05429035,0.01391107,0.5437607,0.001128576,0.001672273,0.004630461,0.001603969,0.06565636,0.006608309,0.2031917,0.08851671,0.01502949],"study_design_scores_gemma":[0.03431701,0.005527167,0.1851528,0.0004396099,0.0004178468,0.0001062019,0.00202973,0.59161,0.0001274521,0.00383438,0.175418,0.00101981],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9849958,0.000533366,0.0004321719,0.004171387,0.00138057,0.001573752,0.000824467,0.00004508158,0.006043374],"genre_scores_gemma":[0.9920567,0.0001704245,0.00003908481,0.0009789608,0.0001120158,0.0006249669,0.0001756458,0.00002004518,0.005822137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5259537,"threshold_uncertainty_score":0.6485182,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309346036","doi":"10.1109/smc53654.2022.9945386","title":"Investigating the addition of singing imagery as a control task in motor imagery BCI","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Motor imagery; Brain–computer interface; Singing; Computer science; Task (project management); Mental image; Electroencephalography; Psychology; Cognition; Engineering; Acoustics","authors":[{"name":"Hadi Mohammadpour","is_ca":true},{"name":"Sarah Power","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04224956867296505,"gpt":0.2796932368182106,"spread":0.2374436681452456,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006203163,0.0002034586,0.0002722192,0.0002504518,0.0002194874,0.0002567016,0.0005970615,0.00004340158,0.0002455577],"category_scores_gemma":[0.000270547,0.0001772699,0.00007068305,0.0001908932,0.0002524992,0.0001742964,0.0001739037,0.0004413055,0.00001837106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001056395,"about_ca_system_score_gemma":0.00009629259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003357479,"about_ca_topic_score_gemma":0.00001689375,"domain_scores_codex":[0.9974444,0.0004682123,0.0005745736,0.0004695363,0.0007938847,0.0002494051],"domain_scores_gemma":[0.9984648,0.00072467,0.0004090603,0.0002295989,0.0001093253,0.00006253905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001990417,0.0002823125,0.002387927,0.0001342548,0.00006926738,0.0001264172,0.003219905,0.004871984,0.8433059,0.1380428,0.004862787,0.002497402],"study_design_scores_gemma":[0.005902599,0.00184386,0.006994274,0.001854314,0.00009783553,0.0009205118,0.01401675,0.8210466,0.0928778,0.01743728,0.03518151,0.001826701],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824262,0.0001389247,0.000501325,0.001333096,0.001921755,0.0005022918,0.0004492975,0.0000486659,0.01267844],"genre_scores_gemma":[0.9961875,0.00004704401,0.00002602034,0.001208252,0.0001696388,0.0001320464,0.00001665962,0.00001947545,0.002193326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8161746,"threshold_uncertainty_score":0.7228858,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}