{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":38,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":38,"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":"ebd31ada4450","filters":{"venue":"Computers, materials & continua/Computers, materials & continua (Print)"}},"results":[{"id":"W4296990086","doi":"10.32604/cmc.2023.028631","title":"Multilayer Neural Network Based Speech Emotion Recognition for燬mart燗ssistance","year":2022,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":85,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Majmaah University","keywords":"Computer science; Speech recognition; Buzzer; Word error rate; Surprise; Sadness; TIMIT; Biometrics; Lifelog; Artificial neural network; Artificial intelligence; Database; Hidden Markov model; Anger; Human–computer interaction","authors":[{"name":"Sandeep Kumar","is_ca":false},{"name":"MohdAnul Haq","is_ca":false},{"name":"Arpit Jain","is_ca":false},{"name":"C. Andy Jason","is_ca":false},{"name":"Nageswara Rao Moparthi","is_ca":false},{"name":"Nitin Mittal","is_ca":false},{"name":"Zamil S. Alzamil","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02864722750133414,"gpt":0.2657589560998064,"spread":0.2371117285984723,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004474931,0.000846358,0.0005340131,0.0004881328,0.0002497456,0.000581282,0.0006571931,0.000599595,0.002645025],"category_scores_gemma":[0.000820297,0.0002256884,0.0007339805,0.0003003345,0.0001381946,0.0006698559,0.0004721356,0.0007553221,0.001378878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005046625,"about_ca_system_score_gemma":0.0003354398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007468836,"about_ca_topic_score_gemma":0.007385305,"domain_scores_codex":[0.9995876,0.00005339854,0.00003937091,0.0001306828,0.0001192817,0.00006969558],"domain_scores_gemma":[0.9998029,0.00003469708,0.00002053618,0.00001824955,0.0001140696,0.000009630659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008829486,0.0003904096,0.004896266,0.0001927155,0.0002263602,0.0002177813,0.0001023763,0.05475437,0.05391137,0.000617551,0.01377377,0.8700341],"study_design_scores_gemma":[0.00001808977,0.0001582823,0.005880177,0.00002236984,0.00006963842,0.00006673714,0.00007171631,0.9722411,0.01769578,0.0005455176,0.0032092,0.00002148858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4272747,0.007670975,0.5319827,0.001492105,0.001396521,0.0002764387,0.003595797,0.008949132,0.01736149],"genre_scores_gemma":[0.9045975,0.001676593,0.07101125,0.0003664975,0.0001833104,0.0001521184,0.0055305,0.00010914,0.01637304],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007468836,"threshold_uncertainty_score":0.01485074,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4402888108","doi":"10.32604/cmc.2024.054378","title":"Wearable Healthcare and Continuous Vital Sign Monitoring with IoT Integration","year":2024,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":37,"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","funders":"","keywords":"Wearable computer; Internet of Things; Health care; Sign (mathematics); Computer science; Wearable technology; Embedded system","authors":[{"name":"Hamed Taherdoost","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01284663389904066,"gpt":0.2368719464841706,"spread":0.2240253125851299,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003813968,0.0005790024,0.0003435785,0.0005394948,0.0002313586,0.001355884,0.0005371852,0.001028558,0.004385735],"category_scores_gemma":[0.001140748,0.0003191205,0.0004037519,0.0005849776,0.0002975588,0.001683966,0.001367843,0.0008261387,0.001911787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001653115,"about_ca_system_score_gemma":0.0002324188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003375745,"about_ca_topic_score_gemma":0.0004871313,"domain_scores_codex":[0.9994192,0.0001172035,0.00004894037,0.0001167698,0.0002463461,0.00005148946],"domain_scores_gemma":[0.9996487,0.00009722395,0.00004684128,0.00006227527,0.0001130158,0.00003198455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006157002,0.0003413858,0.008506223,0.0008567551,0.0001578116,0.001590961,0.0004241267,0.004880109,0.1618515,0.03566937,0.03618717,0.748919],"study_design_scores_gemma":[0.0001838028,0.002723748,0.04187141,0.001758522,0.0005273186,0.01410923,0.000778398,0.1843035,0.2037233,0.07495937,0.4746172,0.0004442709],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07720782,0.0197948,0.7824293,0.008196675,0.005599974,0.0003424319,0.001302289,0.005082966,0.1000438],"genre_scores_gemma":[0.7611069,0.009944115,0.1835879,0.004873917,0.001927081,0.00026773,0.001245452,0.000286931,0.03676004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004385735,"threshold_uncertainty_score":0.01467174,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410131778","doi":"10.32604/cmc.2025.063643","title":"A Review of Deep Learning for Biomedical Signals: Current Applications, Advancements, Future Prospects, Interpretation, and Challenges","year":2025,"lang":"en","type":"review","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Current (fluid); Interpretation (philosophy); Computer science; Data science; Engineering ethics; Engineering; Electrical engineering","authors":[{"name":"Ali Mohammad Alqudah","is_ca":true},{"name":"Zahra Moussavi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02313516825356977,"gpt":0.3309866983757902,"spread":0.3078515301222204,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00196814,0.001118368,0.001049622,0.00253512,0.0002942793,0.001871965,0.001149476,0.001319537,0.004502287],"category_scores_gemma":[0.004972486,0.0005737322,0.000696755,0.003162781,0.000721084,0.002695831,0.00112655,0.001914962,0.002603731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007995032,"about_ca_system_score_gemma":0.001691897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001494951,"about_ca_topic_score_gemma":0.001705876,"domain_scores_codex":[0.9992315,0.0001617917,0.0001144421,0.0001285104,0.000320132,0.00004362039],"domain_scores_gemma":[0.9972881,0.001809988,0.0001396309,0.0001035848,0.0005891785,0.00006952438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000645922,0.00004967706,0.0005651124,0.01030407,0.0001070538,0.0001075632,0.00009981212,0.002623494,0.00207436,0.01497012,0.03405932,0.9349748],"study_design_scores_gemma":[0.00001899885,0.0002481725,0.001564724,0.00883279,0.000214549,0.0009568264,0.0001459897,0.009705267,0.003402987,0.02558756,0.949227,0.0000950884],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0009691416,0.961998,0.02885285,0.003035445,0.0007479521,0.00002891004,0.0002094968,0.0002050814,0.003953208],"genre_scores_gemma":[0.007443858,0.9739058,0.01299578,0.00194612,0.001257665,0.00004872396,0.0003349624,0.00006930323,0.001997725],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004502287,"threshold_uncertainty_score":0.01506168,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3145828488","doi":"10.32604/cmc.2021.016954","title":"Blockchain-Based Flexible Double-Chain Architecture and Performance Optimization for Better Sustainability in Agriculture","year":2021,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Blockchain; Supply chain; Sustainability; Computer science; Sustainable Value; Transparency (behavior); Process management; Supply chain management; Data management; Environmental economics; Business; Computer security; Database; Marketing","authors":[{"name":"Luona Song","is_ca":true},{"name":"Xiaojuan Wang","is_ca":true},{"name":"Peng Wei","is_ca":true},{"name":"Zikui Lu","is_ca":true},{"name":"Xiaojun Wang","is_ca":true},{"name":"Nicolás Merveille","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.007327149750292553,"gpt":0.2181776907511502,"spread":0.2108505410008576,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006622918,0.0005402121,0.0006806403,0.0005124078,0.001012027,0.00138193,0.001088941,0.0007736827,0.004574602],"category_scores_gemma":[0.001172874,0.000229438,0.0003706664,0.0007676793,0.0006369702,0.001992171,0.001449184,0.0006730128,0.000580441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001211199,"about_ca_system_score_gemma":0.001656074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003735947,"about_ca_topic_score_gemma":0.003871569,"domain_scores_codex":[0.999458,0.0001189723,0.00003378606,0.0001090026,0.0001662468,0.0001139918],"domain_scores_gemma":[0.9994782,0.0001471163,0.00005914182,0.00006804507,0.000176047,0.00007155724],"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":[0.0003195263,0.0001200963,0.001076314,0.0001589879,0.0000461216,0.0002404998,0.0001990431,0.8687396,0.01792801,0.04343499,0.00200839,0.06572836],"study_design_scores_gemma":[0.00002175348,0.0001031223,0.0001409057,0.00001021565,0.00001366854,0.00004170763,0.00003035545,0.980735,0.002338638,0.01455814,0.00199329,0.00001319093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.167467,0.001531609,0.80847,0.0007820638,0.0001624612,0.0002413102,0.0002316964,0.0008721362,0.02024186],"genre_scores_gemma":[0.9701872,0.0004637026,0.02496517,0.0000429265,0.00001977535,0.0001055358,0.0001274477,0.00002890374,0.004059421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004574602,"threshold_uncertainty_score":0.01530355,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4362009315","doi":"10.32604/cmc.2023.037386","title":"DDoS Attack Detection in Cloud Computing Based on Ensemble Feature Selection and Deep Learning","year":2023,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Computer science; Denial-of-service attack; Deep learning; Feature selection; Cloud computing; Artificial intelligence; Intrusion detection system; Convolutional neural network; Machine learning; Botnet; The Internet","authors":[{"name":"Yousef Sanjalawe","is_ca":false},{"name":"Turke Althobaiti","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01121299441610299,"gpt":0.2321570336028683,"spread":0.2209440391867653,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007974489,0.001178041,0.001364206,0.001685154,0.000459744,0.0007042979,0.0008176356,0.0005319308,0.0004159223],"category_scores_gemma":[0.001529425,0.0002344662,0.0007576015,0.001166779,0.0002515722,0.001013942,0.0007397939,0.0007970766,0.0001638186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001024081,"about_ca_system_score_gemma":0.001105063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01231716,"about_ca_topic_score_gemma":0.01000885,"domain_scores_codex":[0.9992114,0.0001053043,0.00006594848,0.0001864513,0.0002588397,0.000171904],"domain_scores_gemma":[0.9994728,0.000132214,0.0000787609,0.0000626984,0.0001994325,0.00005415869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007827962,0.0008741289,0.0292725,0.0001154887,0.000255539,0.0003611898,0.00007501414,0.3814115,0.01332519,0.001132448,0.007176197,0.565218],"study_design_scores_gemma":[0.000007720533,0.00004707881,0.001667237,0.00000304355,0.00001636987,0.00003188748,0.00001130045,0.9952509,0.002466812,0.0002532394,0.0002392698,0.000005104032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6124174,0.00246898,0.3761772,0.0008268608,0.0002532032,0.0002416675,0.0008502957,0.003669214,0.003095305],"genre_scores_gemma":[0.9636906,0.000401657,0.03360265,0.0001505109,0.00004922453,0.00006449213,0.0009912672,0.00002458762,0.001024992],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01231716,"threshold_uncertainty_score":0.02449089,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403341286","doi":"10.32604/cmc.2024.057094","title":"AI-Powered Innovations in High-Tech Research and Development: From Theory to Practice","year":2024,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":23,"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","funders":"","keywords":"Development (topology); Engineering ethics; High tech; Engineering; Engineering management; Sociology; Management science; Political science; Mathematics","authors":[{"name":"Mitra Madanchian","is_ca":true},{"name":"Hamed Taherdoost","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06015718674744946,"gpt":0.3286039589895827,"spread":0.2684467722421332,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01937618,0.0005997281,0.0009722678,0.005429348,0.001968118,0.01315751,0.001632285,0.003753136,0.003757141],"category_scores_gemma":[0.03223061,0.0004134138,0.0004601153,0.008939957,0.01516376,0.01463785,0.004595392,0.003912718,0.0007465428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008000235,"about_ca_system_score_gemma":0.01522435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002718545,"about_ca_topic_score_gemma":0.00280974,"domain_scores_codex":[0.9820642,0.01080098,0.001228879,0.0008766453,0.004300619,0.0007285809],"domain_scores_gemma":[0.9329034,0.05856704,0.002009487,0.001892638,0.003769371,0.0008580172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004219104,0.00007649595,0.000803649,0.008708674,0.00005144989,0.000211707,0.005390258,0.000972116,0.0001895186,0.741836,0.008872801,0.2328452],"study_design_scores_gemma":[0.0000380998,0.0001700605,0.002096994,0.04208224,0.00006108745,0.0004699704,0.0145903,0.0007809901,0.0007426512,0.2740304,0.6648851,0.00005211282],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.004697309,0.8965507,0.005595794,0.03799234,0.001120608,0.00003661164,0.00002473899,0.00002988834,0.05395197],"genre_scores_gemma":[0.1287051,0.8574829,0.004615659,0.00629162,0.0008365163,0.00009344387,0.00003967083,0.00002786651,0.001907375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01937618,"threshold_uncertainty_score":0.1024722,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4402151199","doi":"10.32604/cmc.2024.051611","title":"Information Centric Networking Based Cooperative Caching Framework for 5G Communication Systems","year":2024,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Computer science; Information-centric networking; Computer network; Distributed computing; Cache","authors":[{"name":"R Mahaveerakannan","is_ca":false},{"name":"T. Tamilvizhi","is_ca":false},{"name":"Sonia Jenifer Rayen","is_ca":false},{"name":"Osamah Ibrahim Khalaf","is_ca":false},{"name":"Habib Hamam","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01510032706809479,"gpt":0.2412657946959973,"spread":0.2261654676279025,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000740313,0.0004949046,0.0006799722,0.0004494963,0.0007574319,0.00164706,0.001525954,0.0007394405,0.002505228],"category_scores_gemma":[0.0006864372,0.000188974,0.0003439552,0.0007381099,0.0005248904,0.001764827,0.001073726,0.00070068,0.0005438757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001362161,"about_ca_system_score_gemma":0.001554685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006450247,"about_ca_topic_score_gemma":0.008729856,"domain_scores_codex":[0.9995843,0.0001254916,0.00001862641,0.00007229402,0.0001111592,0.00008824967],"domain_scores_gemma":[0.9996756,0.00007469386,0.00002425868,0.00006381006,0.0001273123,0.00003432801],"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":[0.0003098255,0.0001486138,0.0008634033,0.0003613449,0.0001107288,0.0005830202,0.0005096602,0.2570069,0.0178116,0.5752497,0.02803462,0.1190106],"study_design_scores_gemma":[0.00001874329,0.0001210902,0.0002533394,0.00004682135,0.00006142495,0.000221931,0.0001291877,0.8909621,0.0022072,0.08571414,0.02022834,0.00003558076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02798228,0.005791712,0.9409399,0.001403765,0.0003961617,0.0001942614,0.0002935759,0.001027365,0.02197096],"genre_scores_gemma":[0.8851983,0.003246892,0.09964304,0.0003966169,0.0002431584,0.0002038253,0.0002667014,0.00007077203,0.0107307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006450247,"threshold_uncertainty_score":0.01282537,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3014496600","doi":"10.32604/cmc.2020.05746","title":"Sliding-mode PID Control of UAV Based on Particle Swarm Parameter Tuning","year":2020,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Control theory (sociology); PID controller; Sliding mode control; Particle swarm optimization; Rotor (electric); Underactuation; Stability (learning theory); Engineering; Mode (computer interface); Control system; Computer science; Control engineering; Control (management); Nonlinear system; Artificial intelligence; Physics; Temperature control; Algorithm","authors":[{"name":"Yunping Liu","is_ca":true},{"name":"Xingxing Yan","is_ca":true},{"name":"Fei Yan","is_ca":true},{"name":"Ze Yin Xu","is_ca":true},{"name":"Weiyan Shang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01679771051524937,"gpt":0.2207596654909855,"spread":0.2039619549757361,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002727118,0.0004970434,0.0004710807,0.0002445786,0.0003721293,0.0006177956,0.0005817566,0.0004553274,0.0009879534],"category_scores_gemma":[0.0005446668,0.0002032374,0.0002903233,0.0002119068,0.0004099938,0.0003777033,0.0003237975,0.0004073744,0.000203168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002368919,"about_ca_system_score_gemma":0.0004189746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004065683,"about_ca_topic_score_gemma":0.002139583,"domain_scores_codex":[0.9998358,0.00002713912,0.00001240746,0.00004754179,0.00005895622,0.00001807612],"domain_scores_gemma":[0.9998745,0.00003256324,0.00001987514,0.00001166737,0.00005348226,0.000007887732],"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":[0.0002622302,0.0001015192,0.001274203,0.0002788177,0.00008264394,0.0002423261,0.000283528,0.7905406,0.03525078,0.00988114,0.002456688,0.1593454],"study_design_scores_gemma":[0.00002450134,0.00008318394,0.0003200764,0.000007052497,0.000009481841,0.00002258838,0.00001070974,0.9961076,0.001912866,0.0006074168,0.0008870021,0.000007477563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03639627,0.0005688635,0.9539168,0.00008984818,0.0001872111,0.00006271301,0.00002132181,0.000708652,0.008048258],"genre_scores_gemma":[0.9635121,0.0002910261,0.03289567,0.00003949361,0.00003349079,0.0001109273,0.00003794544,0.00002250662,0.003056881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004065683,"threshold_uncertainty_score":0.008084059,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4307875530","doi":"10.32604/cmc.2023.034190","title":"Crime Prediction Methods Based on Machine Learning: A Survey","year":2022,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Statistics Canada","funders":"","keywords":"Big data; Computer science; Field (mathematics); Machine learning; Ambiguity; Artificial intelligence; Process (computing); Data science; Stability (learning theory); Scale (ratio); Deep learning; The Internet; Crime analysis; Data mining; Geography; World Wide Web; Criminology","authors":[{"name":"Junxiang Yin","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04952523392624756,"gpt":0.3465057419489596,"spread":0.296980508022712,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003142213,0.001531063,0.001889669,0.005118244,0.000553097,0.002406085,0.002451805,0.001349812,0.001550613],"category_scores_gemma":[0.008511561,0.000643489,0.001461742,0.006825122,0.0009807115,0.004120122,0.001056205,0.002021919,0.001008439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001059417,"about_ca_system_score_gemma":0.001565538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00375085,"about_ca_topic_score_gemma":0.001990634,"domain_scores_codex":[0.9978985,0.0005503689,0.000248188,0.0003696078,0.0008469921,0.00008641461],"domain_scores_gemma":[0.9943922,0.004243035,0.0002060344,0.0002678981,0.0008250111,0.00006575125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007482248,0.0002812808,0.008696397,0.003275611,0.0001915514,0.0001103472,0.0001588103,0.02458861,0.000334012,0.03221651,0.01094814,0.9191238],"study_design_scores_gemma":[0.00006508612,0.0006004103,0.01643891,0.006181578,0.0004410224,0.00137704,0.0008846396,0.4753564,0.00449481,0.166613,0.3272473,0.000299739],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01636713,0.541059,0.4141914,0.006083585,0.001405883,0.0003176627,0.0008343385,0.0007525149,0.01898848],"genre_scores_gemma":[0.1524562,0.6621439,0.1747143,0.001379444,0.003021733,0.0005051235,0.001936066,0.0001513409,0.003691865],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005118244,"threshold_uncertainty_score":0.01661777,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4387442026","doi":"10.32604/cmc.2023.039020","title":"Detection of Different Stages of Alzheimer’s Disease Using CNN Classifier","year":2023,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Overfitting; Computer science; Artificial intelligence; Support vector machine; Random forest; Machine learning; Cognitive impairment; Binary classification; Preprocessor; Convolutional neural network; Oversampling; Deep learning; Pattern recognition (psychology); Prodromal Stage; Cognition; Artificial neural network; Psychology; Neuroscience","authors":[{"name":"Sakib Mahmud","is_ca":false},{"name":"Md. Mamun Ali","is_ca":false},{"name":"Mohammad Fahim Shahriar","is_ca":false},{"name":"Fahad Ahmed Al-Zahrani","is_ca":false},{"name":"Kawsar Ahmed","is_ca":true},{"name":"Dip Nandi","is_ca":false},{"name":"Francis M. Bui","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1310654931152556,"gpt":0.4005705361449948,"spread":0.2695050430297392,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005120953,0.001068724,0.0006895061,0.002391984,0.000359827,0.0006859456,0.0007106067,0.0007075004,0.001055949],"category_scores_gemma":[0.001260148,0.0002601016,0.0007860613,0.0009283353,0.0001942758,0.0006007029,0.0004664346,0.0006740945,0.0006733782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009073439,"about_ca_system_score_gemma":0.0006852996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02590998,"about_ca_topic_score_gemma":0.0343472,"domain_scores_codex":[0.9995286,0.00002471243,0.00004220198,0.0001572908,0.0001152615,0.0001320068],"domain_scores_gemma":[0.9995053,0.00007085971,0.00005994992,0.00005504945,0.0002661712,0.00004272546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001893637,0.0008532537,0.1948331,0.0004935794,0.0004937557,0.002140521,0.0003121394,0.02799443,0.04579913,0.001358741,0.03598049,0.6878473],"study_design_scores_gemma":[0.0000679632,0.0004326547,0.1632677,0.0002191942,0.0003843249,0.001695127,0.0003220794,0.7621455,0.05636744,0.002416749,0.01256667,0.0001144861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8931869,0.0047509,0.07094001,0.000613734,0.0005684925,0.0004002957,0.01436828,0.003563568,0.01160782],"genre_scores_gemma":[0.9332591,0.001301793,0.04515839,0.0002957,0.0001292356,0.000155532,0.01434078,0.00006808764,0.005291259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02590998,"threshold_uncertainty_score":0.05151838,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3162853854","doi":"10.32604/cmc.2021.014840","title":"A New Hybrid Feature Selection Method Using T-test and Fitness Function","year":2021,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Feature selection; Selection (genetic algorithm); Test (biology); Fitness function; Function (biology); Computer science; Artificial intelligence; Feature (linguistics); Pattern recognition (psychology); Machine learning; Biology; Genetic algorithm; Evolutionary biology; Ecology","authors":[{"name":"Husam Ali Abdulmohsin","is_ca":false},{"name":"Hala Bahjat Abdul Wahab","is_ca":false},{"name":"Abdul Mohssen Jaber Abdul Hossen","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01365653497227175,"gpt":0.2486228614086436,"spread":0.2349663264363718,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002171068,0.001460184,0.001996009,0.003087245,0.0005993384,0.001066186,0.00178879,0.001140351,0.002743703],"category_scores_gemma":[0.004876471,0.0003914329,0.001620658,0.002334023,0.0004786678,0.001206143,0.0006904954,0.0007590707,0.0008881193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006407089,"about_ca_system_score_gemma":0.0009985118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003924326,"about_ca_topic_score_gemma":0.002927642,"domain_scores_codex":[0.9978898,0.0004553033,0.0001639209,0.0004806989,0.0008900983,0.0001202386],"domain_scores_gemma":[0.9977732,0.000929251,0.000189658,0.0001525769,0.0008884391,0.00006684283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003506696,0.0002304197,0.005252999,0.000165939,0.0004005941,0.0002177764,0.00009556887,0.0874106,0.0238788,0.002228198,0.004147882,0.8756206],"study_design_scores_gemma":[0.00005843558,0.0002456738,0.003076019,0.00001117104,0.00006549786,0.000242391,0.000025806,0.9867266,0.006252185,0.0009939531,0.002262154,0.00004008083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01354915,0.0001566345,0.9843786,0.00006098119,0.00005430621,0.00009641887,0.00007502252,0.001126293,0.0005025659],"genre_scores_gemma":[0.2825392,0.0001611411,0.7111125,0.000181592,0.0001139373,0.00072343,0.0008046851,0.0003665184,0.003996949],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003924326,"threshold_uncertainty_score":0.01148182,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4386396915","doi":"10.32604/cmc.2023.040567","title":"Fusion of Feature Ranking Methods for an Effective Intrusion Detection System","year":2023,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Computer science; Random forest; Data mining; Feature (linguistics); Artificial intelligence; Support vector machine; Machine learning; Intrusion detection system; Oversampling; Constant false alarm rate; Decision tree; Pattern recognition (psychology)","authors":[{"name":"Seshu Bhavani Mallampati","is_ca":false},{"name":"Hari Seetha","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01424725346003531,"gpt":0.2819128998463004,"spread":0.2676656463862651,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002634472,0.0009466733,0.001466175,0.002502869,0.0004334963,0.0009408426,0.000845794,0.0006279279,0.001064044],"category_scores_gemma":[0.003876032,0.000332135,0.00110601,0.001582481,0.0003144179,0.001326651,0.0007777439,0.000784473,0.0006071687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005190886,"about_ca_system_score_gemma":0.0006720081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001600298,"about_ca_topic_score_gemma":0.001050417,"domain_scores_codex":[0.9982978,0.0003077766,0.000164359,0.0002667062,0.0007866917,0.0001766331],"domain_scores_gemma":[0.9988436,0.0003440566,0.0001156252,0.0001152142,0.0005332138,0.00004836419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00025621,0.0001895218,0.00249113,0.0001251132,0.0001424527,0.00009107987,0.00007149991,0.1099217,0.02488625,0.003312771,0.002430677,0.8560817],"study_design_scores_gemma":[0.00001432035,0.0001349979,0.001914585,0.00001127988,0.00004413427,0.00008923279,0.00002474075,0.985476,0.008472621,0.002300753,0.001496325,0.00002104777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02140359,0.0004949711,0.9763837,0.0001042847,0.0000543881,0.00006494764,0.00004730207,0.0007901707,0.0006565906],"genre_scores_gemma":[0.5729762,0.000486752,0.4240684,0.0001527457,0.0001291315,0.0001662729,0.0003799699,0.00009167577,0.001548861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002634472,"threshold_uncertainty_score":0.01393253,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403955213","doi":"10.32604/cmc.2024.058888","title":"Discrete Choice Models and Artificial Intelligence Techniques for Predicting the Determinants of Transport Mode Choice—A Systematic Review","year":2024,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Transport Canada","funders":"Silesian University of Technology","keywords":"Discrete choice; Mode choice; Mode (computer interface); Computer science; Artificial intelligence; Machine learning; Engineering; Public transport; Transport engineering; Human–computer interaction","authors":[{"name":"Mujahid Ali","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0201433426614659,"gpt":0.2712776441371779,"spread":0.251134301475712,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01067416,0.001300775,0.004115429,0.005067938,0.0002665012,0.001791422,0.001620604,0.001368744,0.003912779],"category_scores_gemma":[0.03444813,0.000796234,0.005223214,0.006622833,0.0007021985,0.001970682,0.0006521785,0.001463962,0.0003562559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001151958,"about_ca_system_score_gemma":0.004877234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006754001,"about_ca_topic_score_gemma":0.0106373,"domain_scores_codex":[0.995793,0.002045815,0.000826684,0.0003818538,0.0008956431,0.00005703282],"domain_scores_gemma":[0.9393534,0.0563442,0.002051089,0.000472388,0.001619701,0.0001592366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0002832836,0.0002552545,0.004020415,0.3112624,0.009245208,0.00007781998,0.0001505823,0.004597408,0.0001276536,0.003976411,0.004535936,0.6614677],"study_design_scores_gemma":[0.0008762928,0.001831894,0.03215009,0.6614619,0.07124896,0.0007446323,0.0007562899,0.02048769,0.00092741,0.02507122,0.1840412,0.0004025805],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006358212,0.9967331,0.001789037,0.0003082087,0.00005802088,0.00008278192,0.0002095021,0.000008574304,0.0001749838],"genre_scores_gemma":[0.00695048,0.9887749,0.003682201,0.0001501362,0.00006097058,0.0001475248,0.0001572795,0.00000385558,0.00007264158],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01067416,"threshold_uncertainty_score":0.05645102,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2910682868","doi":"10.32604/cmc.2019.03585","title":"GFCache: A Greedy Failure Cache Considering Failure Recency and Failure Frequency for an Erasure-coded Storage System","year":2019,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Cascades (Canada)","funders":"","keywords":"Computer science; Erasure; Cache; Parallel computing; Operating system; Programming language","authors":[{"name":"Mingzhu Deng","is_ca":false},{"name":"Fang Liu","is_ca":false},{"name":"Ming Zhao","is_ca":true},{"name":"Zhiguang Chen","is_ca":false},{"name":"Nong Xiao","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01543407361370614,"gpt":0.2308339737499236,"spread":0.2153999001362174,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001815088,0.001381975,0.001905786,0.001738271,0.002224397,0.001941649,0.005462494,0.001193624,0.003655603],"category_scores_gemma":[0.006035997,0.0005713818,0.0006066693,0.002337364,0.0009981452,0.004113459,0.00219373,0.001095228,0.0008584641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002085943,"about_ca_system_score_gemma":0.009023524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02353654,"about_ca_topic_score_gemma":0.04287708,"domain_scores_codex":[0.9986199,0.0002014699,0.0001068093,0.0001833393,0.0005578796,0.0003306333],"domain_scores_gemma":[0.9968677,0.0008726404,0.0002154587,0.0006464996,0.001042686,0.0003550076],"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":[0.002543425,0.0005907268,0.00796829,0.0006756214,0.0003604725,0.0003962822,0.0003497081,0.5047084,0.009667121,0.01585757,0.0685076,0.3883747],"study_design_scores_gemma":[0.00008321994,0.0002059708,0.000354527,0.00002310113,0.00006183449,0.0001066073,0.00007865967,0.9900123,0.00151648,0.004779791,0.002733864,0.00004354892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2013354,0.0096031,0.7510347,0.002103598,0.00155648,0.00108542,0.002573738,0.02238059,0.008326965],"genre_scores_gemma":[0.8276088,0.001148127,0.1640464,0.0004202551,0.0002775773,0.0003590932,0.00106666,0.0004343834,0.004638611],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02353654,"threshold_uncertainty_score":0.04679906,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4411160219","doi":"10.32604/cmc.2025.066212","title":"Multi-Scale Fusion Network Using Time-Division Fourier Transform for Rolling Bearing Fault Diagnosis","year":2025,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Gear and Bearing Dynamics Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Bearing (navigation); Division (mathematics); Fault (geology); Fusion; Scale (ratio); Fourier transform; Computer science; Artificial intelligence; Geology; Mathematics; Seismology; Geography; Cartography; Arithmetic; Mathematical analysis","authors":[{"name":"Ronghua Wang","is_ca":false},{"name":"Shibao Sun","is_ca":false},{"name":"Pengcheng Zhao","is_ca":false},{"name":"Chenyi Hu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01030098636029093,"gpt":0.2295765878455452,"spread":0.2192756014852542,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007348358,0.0007081473,0.0005569055,0.001134636,0.0003815581,0.0004715864,0.0005222918,0.0006982999,0.0008672675],"category_scores_gemma":[0.001385461,0.0001787312,0.0005944439,0.0009436036,0.0002778346,0.001220342,0.0005200657,0.0005847349,0.0002844008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004493054,"about_ca_system_score_gemma":0.000386485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004889851,"about_ca_topic_score_gemma":0.004010307,"domain_scores_codex":[0.9995971,0.00005740711,0.00002395261,0.0001105293,0.0001584936,0.00005252978],"domain_scores_gemma":[0.999678,0.0001154663,0.00004596017,0.00002721414,0.0001172697,0.00001605973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003921998,0.0001486224,0.004160004,0.0001326804,0.0001090112,0.0002321386,0.000141289,0.2191364,0.0344217,0.002734755,0.002643509,0.7357476],"study_design_scores_gemma":[0.000006026557,0.00004979041,0.001748727,0.000005798469,0.00002794633,0.00007426678,0.0000273679,0.9898779,0.006252504,0.001258279,0.0006592356,0.00001228656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06804492,0.001013045,0.9274585,0.0001873071,0.0001430799,0.00005417613,0.0001025479,0.001025768,0.001970602],"genre_scores_gemma":[0.8519883,0.0006438689,0.145138,0.000098531,0.00009598143,0.00005842002,0.0003267621,0.00004083886,0.001609376],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004889851,"threshold_uncertainty_score":0.009722769,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3135624155","doi":"10.32604/cmc.2021.015470","title":"An Efficient Genetic Hybrid PAPR Technique for 5G Waveforms","year":2021,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"PAPR reduction in OFDM","field":"Engineering","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 Ottawa","funders":"Prince Sattam bin Abdulaziz University","keywords":"Computer science; Noma; Waveform; Orthogonal frequency-division multiplexing; Transmission (telecommunications); Computational complexity theory; Minification; Reduction (mathematics); Power (physics); Electronic engineering; Algorithm; Telecommunications; Mathematics; Engineering","authors":[{"name":"Арун Кумар","is_ca":false},{"name":"Mahmoud A. Albreem","is_ca":false},{"name":"Mohammed H. Alsharif","is_ca":false},{"name":"Abu Jahid","is_ca":true},{"name":"Peerapong Uthansakul","is_ca":false},{"name":"Jamel Nebhen","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.008140237503124103,"gpt":0.221690237949941,"spread":0.2135500004468169,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002217413,0.0005186578,0.0003315146,0.0003877736,0.0002539849,0.0003290771,0.000445002,0.0004790474,0.001121979],"category_scores_gemma":[0.0005875127,0.0001600088,0.0004832259,0.0003765535,0.0002317028,0.0003538432,0.0002929472,0.0003501063,0.0002334025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003133403,"about_ca_system_score_gemma":0.0005228155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001483947,"about_ca_topic_score_gemma":0.001503536,"domain_scores_codex":[0.999848,0.00003236735,0.000005097816,0.00002613657,0.00007215685,0.00001617088],"domain_scores_gemma":[0.9999011,0.00003946044,0.0000177657,0.000008711228,0.00002806602,0.000004932167],"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":[0.0001024297,0.00008652222,0.001055436,0.0001514263,0.00006329769,0.0001574072,0.0001624484,0.6082714,0.0584576,0.01873585,0.001375267,0.311381],"study_design_scores_gemma":[0.00001225431,0.00009198556,0.0002302603,0.000008161746,0.0000128605,0.00007921064,0.00001164949,0.9907209,0.005391954,0.001553898,0.001877903,0.000009019439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0291691,0.0003011787,0.9662001,0.0001155629,0.00004877606,0.00003500249,0.00001867898,0.0002648015,0.003846873],"genre_scores_gemma":[0.4700903,0.000417096,0.523352,0.0001073325,0.00002965387,0.0001313023,0.00008043864,0.00006056271,0.005731412],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001483947,"threshold_uncertainty_score":0.003753364,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4388110899","doi":"10.32604/cmc.2023.036074","title":"Ontology-Based Crime News Semantic Retrieval System","year":2023,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Computer science; SPARQL; Information retrieval; RDF; Semantic analytics; Semantic query; Ontology; Semantic computing; Semantic similarity; Semantics (computer science); Semantic Web Stack; Named graph; Semantic Web Rule Language; Semantic Web; Semantic search; World Wide Web; Web search query; Search engine","authors":[{"name":"Fiaz Majeed","is_ca":false},{"name":"Afzaal Ahmad","is_ca":false},{"name":"Muhammad Shafiq","is_ca":false},{"name":"Jin-Ghoo Choi","is_ca":false},{"name":"Habib Hamam","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02102691528436334,"gpt":0.247121434270478,"spread":0.2260945189861147,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009508735,0.0007120764,0.0009195686,0.003776113,0.001294583,0.002065737,0.001626246,0.001027444,0.007333684],"category_scores_gemma":[0.002597388,0.0003700338,0.00132958,0.002428562,0.00052658,0.004348024,0.001607268,0.0008425299,0.004847942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001576707,"about_ca_system_score_gemma":0.002696717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01732499,"about_ca_topic_score_gemma":0.01106387,"domain_scores_codex":[0.9989268,0.00009257417,0.0002419604,0.0002262786,0.0004269143,0.00008540508],"domain_scores_gemma":[0.9992543,0.00009924446,0.00007838255,0.000161293,0.0003587412,0.00004800215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007605175,0.00116946,0.004135901,0.0020433,0.0002525376,0.002747893,0.001361295,0.02558353,0.04460484,0.09616795,0.2310369,0.5901359],"study_design_scores_gemma":[0.0002485803,0.0001350767,0.005796663,0.000241962,0.000417713,0.001896612,0.001294274,0.4117369,0.07052514,0.04732019,0.4600787,0.0003082682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03472279,0.0009146841,0.7851271,0.00198093,0.000417184,0.001792295,0.02570112,0.09995805,0.04938579],"genre_scores_gemma":[0.2472672,0.002138545,0.6306713,0.001377752,0.0001837567,0.001065806,0.08553565,0.002466928,0.02929306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01732499,"threshold_uncertainty_score":0.03444827,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4414937541","doi":"10.32604/cmc.2025.067733","title":"Machine Learning-Based Detection of DDoS Attacks in VANETs for Emergency Vehicle Communication","year":2025,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Network Security and Intrusion Detection","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":"Université du Québec en Outaouais","funders":"","keywords":"Denial-of-service attack; Boosting (machine learning); Robustness (evolution); Vehicular ad hoc network; Software deployment; Scalability; Artificial neural network; Intelligent transportation system; Gradient boosting","authors":[{"name":"Bappa Muktar","is_ca":true},{"name":"Vincent Fono","is_ca":true},{"name":"Adama Nouboukpo","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01007909038407209,"gpt":0.2449443351086038,"spread":0.2348652447245317,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001474859,0.0008291107,0.0008375084,0.001573778,0.0003758956,0.0006040812,0.00100312,0.0007996945,0.000538552],"category_scores_gemma":[0.003462943,0.0002020077,0.0005775727,0.0007491501,0.000336158,0.0008007857,0.000658275,0.0007844552,0.0003985412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000692417,"about_ca_system_score_gemma":0.0006885132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004803361,"about_ca_topic_score_gemma":0.003782077,"domain_scores_codex":[0.9991334,0.000232975,0.00006667243,0.0001859236,0.0002351805,0.000145773],"domain_scores_gemma":[0.9988611,0.0004203581,0.0001551303,0.000151621,0.000337405,0.00007439899],"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":[0.0003563651,0.0003684248,0.02151487,0.000119251,0.0001197514,0.0001540145,0.00003822457,0.8560973,0.00417351,0.001234886,0.005515686,0.1103078],"study_design_scores_gemma":[0.000006811998,0.00005524977,0.002345692,0.000006060537,0.000007055789,0.00002499441,0.00001863205,0.9947172,0.001679291,0.0005817286,0.0005515972,0.00000567259],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.762744,0.00142499,0.2227575,0.001069291,0.0004807128,0.0003099333,0.002200401,0.003871434,0.005141745],"genre_scores_gemma":[0.970421,0.0001519643,0.02578756,0.00007570282,0.00004078015,0.00006724549,0.002452516,0.00002670498,0.0009764676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004803361,"threshold_uncertainty_score":0.00955081,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401273062","doi":"10.32604/cmc.2024.053632","title":"A Novel Quantization and Model Compression Approach for Hardware Accelerators in Edge Computing","year":2024,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Chongqing University of Science and Technology; Chongqing Municipal Education Commission; Chongqing University; Chinese Academy of Sciences","keywords":"Computer science; Quantization (signal processing); Enhanced Data Rates for GSM Evolution; Hardware acceleration; Data compression; Computer hardware; Computer architecture; Computational science; Parallel computing; Field-programmable gate array; Artificial intelligence; Algorithm","authors":[{"name":"Fangzhou He","is_ca":false},{"name":"Ke Ding","is_ca":false},{"name":"Dingjiang Yan","is_ca":false},{"name":"Jie Li","is_ca":false},{"name":"Jiajun Wang","is_ca":false},{"name":"Mingzhe Chen","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0287741636614898,"gpt":0.2644025147763159,"spread":0.2356283511148261,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003082725,0.0006784921,0.0004245927,0.0004922377,0.0003391006,0.0007598396,0.001344324,0.000409227,0.005375328],"category_scores_gemma":[0.00108161,0.0002445835,0.0003314928,0.0007704294,0.0002867403,0.001613439,0.0007865034,0.001007283,0.001094764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004727089,"about_ca_system_score_gemma":0.0008087237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002415005,"about_ca_topic_score_gemma":0.004036013,"domain_scores_codex":[0.9997304,0.00002835461,0.00002428742,0.00004638973,0.0001428561,0.00002767464],"domain_scores_gemma":[0.9997182,0.00005947762,0.00002470137,0.00008024667,0.0001018223,0.00001550399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004611081,0.0001768363,0.00154328,0.0002646561,0.00006052265,0.0002828265,0.0001533507,0.1475964,0.0661202,0.03864615,0.02165482,0.7230398],"study_design_scores_gemma":[0.00003387995,0.0001216017,0.000258655,0.0000180139,0.00001451089,0.0001242922,0.00002796393,0.9627195,0.02169777,0.006109422,0.008857329,0.0000170551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01266527,0.0005328626,0.9799298,0.0002401252,0.0001244566,0.00007956308,0.0001457274,0.003126832,0.003155431],"genre_scores_gemma":[0.3630614,0.0005422435,0.6283143,0.0004009525,0.0001071901,0.0001849328,0.0008295087,0.0002058917,0.006353599],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005375328,"threshold_uncertainty_score":0.01798224,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407555785","doi":"10.32604/cmc.2024.054802","title":"Towards Net Zero Resilience: A Futuristic Architectural Strategy for Cyber-Attack Defence in Industrial Control Systems (ICS) and Operational Technology (OT)","year":2025,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"De Montfort University; Trent University; Nottingham Trent University","keywords":"Resilience (materials science); Industrial control system; Systems engineering; Control (management); Engineering; Computer science; Architectural engineering; Artificial intelligence","authors":[{"name":"Hariharan Ramachandran","is_ca":false},{"name":"K. David","is_ca":false},{"name":"Richard Smith﻿","is_ca":false},{"name":"Tawfik Al-Hadhrami","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01324357613207555,"gpt":0.2390177241069078,"spread":0.2257741479748322,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002097258,0.000848002,0.0002782505,0.0008206661,0.001445046,0.004646336,0.001368962,0.001736492,0.004538949],"category_scores_gemma":[0.001272798,0.0002732213,0.00045886,0.0003150591,0.003680182,0.009913956,0.005372482,0.002998943,0.001533747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001538756,"about_ca_system_score_gemma":0.002942767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009784885,"about_ca_topic_score_gemma":0.002044129,"domain_scores_codex":[0.9993339,0.0001957207,0.00002242863,0.00007982746,0.0002205369,0.0001476556],"domain_scores_gemma":[0.9992617,0.0001193321,0.00005436041,0.0001613182,0.0002088465,0.0001945506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003751794,0.00003192578,0.0003123969,0.0001351501,0.00001715045,0.0000706991,0.0006134235,0.008167732,0.003460715,0.9319885,0.007405205,0.04775964],"study_design_scores_gemma":[0.00001867585,0.0001887671,0.0003303252,0.0003272513,0.00003470811,0.000237011,0.001542004,0.02970161,0.005494243,0.7472913,0.2147802,0.00005386706],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03206504,0.003850422,0.7868094,0.03619255,0.001438264,0.0001351168,0.0001085912,0.002050883,0.1373497],"genre_scores_gemma":[0.6033316,0.006323475,0.3319469,0.004695382,0.0005352502,0.0002357628,0.000266528,0.0005713331,0.05209385],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004646336,"threshold_uncertainty_score":0.01518428,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4390299814","doi":"10.32604/cmc.2023.046772","title":"Deployment Strategy for Multiple Controllers Based on the Aviation On-Board Software-Defined Data Link Network","year":2023,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":3,"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; Distributed computing; Population; Software deployment; Node (physics); Genetic algorithm; Real-time computing; Engineering; Machine learning","authors":[{"name":"Yuting Zhu","is_ca":false},{"name":"Yanfang Fu","is_ca":false},{"name":"Ce Yang","is_ca":true},{"name":"Pan Deng","is_ca":false},{"name":"Jianpeng Zhu","is_ca":false},{"name":"Huankun Su","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04828861849111521,"gpt":0.26235610639184,"spread":0.2140674879007248,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000380011,0.000608516,0.0003583798,0.0005329039,0.0007510729,0.0009484586,0.001043786,0.0004389918,0.001851246],"category_scores_gemma":[0.000693029,0.000159153,0.0003121837,0.0003179523,0.000338852,0.0007404682,0.001000575,0.0004508263,0.0002863147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007756726,"about_ca_system_score_gemma":0.0007860329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005495687,"about_ca_topic_score_gemma":0.004966713,"domain_scores_codex":[0.9996454,0.00008030429,0.00001318585,0.00008675664,0.00009704141,0.00007740913],"domain_scores_gemma":[0.999705,0.00004772881,0.00004183939,0.00003000525,0.0001022868,0.00007310467],"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":[0.0003580705,0.0002129754,0.005772691,0.0001073726,0.00007927638,0.0008338316,0.0004333128,0.7344738,0.04364773,0.0264173,0.003579529,0.1840841],"study_design_scores_gemma":[0.0000169304,0.0001468736,0.000571512,0.00000575363,0.00001857098,0.00006695044,0.00009465723,0.9929668,0.003200964,0.001303341,0.001598948,0.000008651326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3020005,0.0004391242,0.674226,0.0005531777,0.0001755767,0.0003016372,0.00004600777,0.0005298036,0.02172813],"genre_scores_gemma":[0.9544458,0.00007906085,0.04231854,0.00004800545,0.00001811749,0.0000770142,0.00003824088,0.0000131136,0.002962118],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005495687,"threshold_uncertainty_score":0.01092744,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4396929802","doi":"10.32604/cmc.2024.049186","title":"Posture Detection of Heart Disease Using Multi-Head Attention Vision Hybrid (MHAVH) Model","year":2024,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning; Deep learning; Heart disease; Feature extraction; Transformer; Medicine; Engineering; Cardiology","authors":[{"name":"Hina Naz","is_ca":false},{"name":"Zuping Zhang","is_ca":false},{"name":"Mohammed Al‐Habib","is_ca":false},{"name":"Fuad A. Awwad","is_ca":false},{"name":"Emad A. A. Ismail","is_ca":false},{"name":"Zaid Khan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02788195652775291,"gpt":0.3168347513733436,"spread":0.2889527948455907,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003224411,0.0005841773,0.0005506615,0.0005777676,0.0002013625,0.0004885861,0.0009946896,0.0007870278,0.00139208],"category_scores_gemma":[0.0005502265,0.0002361417,0.0007603858,0.0002867494,0.0002628895,0.0003270906,0.0006202775,0.0007670402,0.0003357769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005507077,"about_ca_system_score_gemma":0.000640846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01398715,"about_ca_topic_score_gemma":0.01460769,"domain_scores_codex":[0.9998491,0.00001902274,0.000006398004,0.00005501621,0.00002735247,0.00004313999],"domain_scores_gemma":[0.9998816,0.00003579356,0.00001366211,0.000009484836,0.00004226793,0.00001704045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005699993,0.0004829961,0.01488791,0.000122191,0.0003615487,0.0004637736,0.0001197976,0.4089009,0.02692505,0.00257938,0.009570969,0.5350155],"study_design_scores_gemma":[0.000008378596,0.00005338434,0.002070406,0.000004685091,0.00002594354,0.00005888636,0.000006298445,0.9958019,0.001188031,0.0004932564,0.000281296,0.000007530176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2881182,0.002386726,0.6934645,0.0015262,0.0006379808,0.0001890472,0.0009544266,0.003893698,0.0088292],"genre_scores_gemma":[0.9690487,0.0002685445,0.0247868,0.0004629825,0.0001209442,0.00005732428,0.0004261228,0.00003058718,0.004797829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01398715,"threshold_uncertainty_score":0.02781147,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3208943602","doi":"10.32604/cmc.2022.021406","title":"Analysis of Flow Structure in Microturbine Operating at Low Reynolds Number","year":2021,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Turbomachinery Performance and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Reynolds number; Tip clearance; Mechanics; Aerodynamics; Laminar flow; Vortex; Casing; Chord (peer-to-peer); Degree Rankine; Flow (mathematics); Rotor (electric); Stator; Physics; Mechanical engineering; Engineering; Computer science; Turbulence; Thermodynamics","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.004186882660529934,"gpt":0.1998136446565966,"spread":0.1956267619960667,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008557632,0.0001875857,0.0002830078,0.0003275062,0.0004417999,0.0004013058,0.0002369907,0.0003298891,0.0009296382],"category_scores_gemma":[0.0003836844,0.0001363888,0.0002027767,0.0001620599,0.000411918,0.0003585969,0.0001593372,0.000206726,0.0001500088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004906574,"about_ca_system_score_gemma":0.0004533596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002969987,"about_ca_topic_score_gemma":0.002232538,"domain_scores_codex":[0.999957,0.000005292516,0.000001890107,0.000006762372,0.00001867095,0.00001029985],"domain_scores_gemma":[0.9999034,0.00004313481,0.0000165513,0.000007051342,0.000020509,0.000009299468],"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":[0.000283651,0.0001797138,0.01749301,0.0001979725,0.00002828563,0.0008037967,0.0005043995,0.707486,0.2371993,0.008881599,0.0004162265,0.02652608],"study_design_scores_gemma":[0.00001699541,0.00008752975,0.0102439,0.000009645574,0.000004380851,0.00009633931,0.00008795441,0.9680248,0.01976649,0.001105421,0.0005387558,0.00001774052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774902,0.0001275841,0.01916175,0.0000658553,0.000007618361,0.0000308378,0.00005834199,0.0001071725,0.002950716],"genre_scores_gemma":[0.9910716,0.00008262277,0.007934744,0.00000944368,0.000002745095,0.00002018348,0.00005603758,0.00001798257,0.0008046899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002969987,"threshold_uncertainty_score":0.00590539,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3169990404","doi":"10.32604/cmc.2021.017711","title":"Adaptive Cell Zooming Strategy Toward Next-Generation Cellular Networks with Joint Transmission","year":2021,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"Deanship of Scientific Research, Prince Sattam bin Abdulaziz University; Thailand Science Research and Innovation; Taif University; Prince Sattam bin Abdulaziz University","keywords":"Computer science; Computer network; Telecommunications link; Efficient energy use; Throughput; Energy consumption; Spectral efficiency; Zoom; The Internet; Transmitter power output; Cellular network; Wireless; Real-time computing; Telecommunications; Transmitter; Engineering","authors":[{"name":"Abu Jahid","is_ca":true},{"name":"Mohammed H. Alsharif","is_ca":false},{"name":"Raju Kannadasan","is_ca":false},{"name":"Mahmoud A. Albreem","is_ca":false},{"name":"Peerapong Uthansakul","is_ca":false},{"name":"Jamel Nebhen","is_ca":false},{"name":"Ayman A. Aly","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02571769504681292,"gpt":0.1977016572207587,"spread":0.1719839621739458,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003264012,0.0004742472,0.0003620751,0.0003289234,0.0003839609,0.0004002166,0.000858415,0.0003537514,0.0008697684],"category_scores_gemma":[0.0006384727,0.000138353,0.0002786294,0.0003915,0.0004167459,0.0005629653,0.0006178801,0.000387599,0.000140093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005294681,"about_ca_system_score_gemma":0.0004163678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003829923,"about_ca_topic_score_gemma":0.00383086,"domain_scores_codex":[0.9998091,0.00006345616,0.000004516221,0.00002954139,0.00004672524,0.00004667064],"domain_scores_gemma":[0.9998029,0.00007281986,0.00003482193,0.0000167384,0.00004249651,0.00003021082],"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":[0.0001227766,0.00008113384,0.0008094377,0.00003980599,0.00003712843,0.0001661944,0.0001098865,0.9279263,0.01142642,0.009760275,0.001303146,0.04821745],"study_design_scores_gemma":[0.000007485094,0.00005851847,0.0001470638,0.000002529231,0.000007394638,0.00003499156,0.00002919027,0.9965547,0.001025028,0.001667139,0.0004614532,0.000004502805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1251063,0.0006954396,0.8687383,0.0002058015,0.00004846774,0.00005604033,0.00002795684,0.000272196,0.004849494],"genre_scores_gemma":[0.9613497,0.0001570235,0.03734319,0.00006220367,0.00001708473,0.00003327043,0.00001795365,0.00001044134,0.001009145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003829923,"threshold_uncertainty_score":0.007615268,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4296990559","doi":"10.32604/cmc.2023.028058","title":"Deep Learning-Based Program-Wide Binary Code Similarity for Smart Contracts","year":2022,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Blockchain Technology Applications and Security","field":"Computer 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 Alberta","funders":"","keywords":"Computer science; Scalability; Control flow; Machine learning; Data mining; Artificial intelligence; Theoretical computer science; Programming language; Database","authors":[{"name":"Yuan Zhuang","is_ca":false},{"name":"Baobao Wang","is_ca":false},{"name":"Jianguo Sun","is_ca":false},{"name":"Haoyang Liu","is_ca":false},{"name":"Shuqi Yang","is_ca":false},{"name":"Qingan Da","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0119603758153709,"gpt":0.2414702453134278,"spread":0.2295098694980569,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006122555,0.0007299275,0.0007085206,0.002239036,0.0004592302,0.0007816736,0.00135099,0.001052214,0.002194136],"category_scores_gemma":[0.002869796,0.0002689025,0.0006141356,0.001768198,0.0006177053,0.002391167,0.001078141,0.001426212,0.0008076717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001546994,"about_ca_system_score_gemma":0.001645507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01645174,"about_ca_topic_score_gemma":0.0191599,"domain_scores_codex":[0.9991884,0.0001024879,0.00005929226,0.0002449523,0.000280085,0.0001248471],"domain_scores_gemma":[0.9989232,0.0002353254,0.0002563425,0.0001776768,0.0003334138,0.00007388744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003204893,0.0004246017,0.0166978,0.0001870311,0.00009578648,0.0002154316,0.0001951506,0.257889,0.008876891,0.01435693,0.01189087,0.68885],"study_design_scores_gemma":[0.000006462894,0.00002129669,0.0009539254,0.000007785575,0.000006264673,0.00002412757,0.00002764507,0.9917384,0.001439768,0.004725756,0.001042535,0.000006061411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3402252,0.001478426,0.6397922,0.00106862,0.0001518907,0.0002209118,0.001566331,0.006853613,0.008642809],"genre_scores_gemma":[0.8809429,0.0005312775,0.1030492,0.0003736126,0.00006632257,0.0001311725,0.005171121,0.0002657798,0.009468544],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01645174,"threshold_uncertainty_score":0.03271198,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4379930405","doi":"10.32604/cmc.2023.033332","title":"Generation of Low-Delay and High-Stability Multicast Tree","year":2023,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Peer-to-Peer Network Technologies","field":"Computer 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 British Columbia","funders":"Hainan University; National Natural Science Foundation of China","keywords":"Multicast; Computer science; Protocol Independent Multicast; Distance Vector Multicast Routing Protocol; Source-specific multicast; Xcast; Computer network; Tree (set theory); Pragmatic General Multicast; Stability (learning theory); Transmission delay; Distributed computing; Mathematics","authors":[{"name":"Deshun Li","is_ca":false},{"name":"Zhenchen Wang","is_ca":false},{"name":"Yucong Wei","is_ca":false},{"name":"Jiangyuan Yao","is_ca":false},{"name":"Yuyin Tan","is_ca":false},{"name":"Qiuling Yang","is_ca":false},{"name":"Zhengxia Wang","is_ca":false},{"name":"Xingcan Cao","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0333662388918437,"gpt":0.2483250191703,"spread":0.2149587802784563,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006295369,0.0004241133,0.000522993,0.0006967232,0.0009704175,0.0006470633,0.001016481,0.0008149702,0.001014452],"category_scores_gemma":[0.001751502,0.0002044576,0.0006022467,0.0005677178,0.0002734561,0.001225451,0.0009902857,0.0005067228,0.0002130864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006098836,"about_ca_system_score_gemma":0.0007383733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007372729,"about_ca_topic_score_gemma":0.0007710198,"domain_scores_codex":[0.9995232,0.00009343841,0.000031409,0.0001135206,0.0001663474,0.0000721343],"domain_scores_gemma":[0.9994586,0.0001562199,0.00008709088,0.00009771863,0.0001551268,0.00004528111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003191946,0.0001745147,0.004548406,0.0003534739,0.00009585121,0.0006774488,0.0005796889,0.3989249,0.1090392,0.05141856,0.007042637,0.4268261],"study_design_scores_gemma":[0.0000263759,0.00009195327,0.0004898605,0.00001283762,0.00002287922,0.0004043693,0.00007643075,0.9645633,0.01679425,0.01426426,0.003236886,0.00001654658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05337762,0.0002130622,0.94313,0.0001679452,0.0000446747,0.0001001409,0.00007906144,0.000558703,0.002328848],"genre_scores_gemma":[0.6101737,0.0002623564,0.3865404,0.0001346216,0.00004323133,0.0001574704,0.0003510581,0.0001021794,0.00223495],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001016481,"threshold_uncertainty_score":0.004425108,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4285286742","doi":"10.32604/cmc.2022.027236","title":"Automating Transfer Credit Assessment-A Natural Language Processing-Based Approach","year":2022,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Topic Modeling","field":"Computer 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":"Lakehead University","funders":"","keywords":"Computer science; Natural language processing; Transfer (computing); Artificial intelligence","authors":[{"name":"Dhivya Chandrasekaran","is_ca":true},{"name":"Vijay Mago","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01156782247205276,"gpt":0.2432532928695259,"spread":0.2316854703974731,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003722655,0.001326945,0.001034921,0.004438662,0.0008018967,0.003565222,0.002298702,0.001409139,0.002745397],"category_scores_gemma":[0.015872,0.0003188049,0.001556343,0.0026451,0.0007690096,0.004072067,0.002728185,0.002036884,0.001953975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001789904,"about_ca_system_score_gemma":0.002959181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007955666,"about_ca_topic_score_gemma":0.01025546,"domain_scores_codex":[0.995926,0.001205394,0.000376786,0.001153583,0.001096551,0.0002417082],"domain_scores_gemma":[0.992945,0.003340766,0.0007288776,0.001013061,0.001741784,0.0002304495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003319434,0.0008658395,0.01558529,0.000661852,0.0001616388,0.0006123675,0.00113373,0.07119151,0.01197473,0.01663956,0.009275997,0.8715656],"study_design_scores_gemma":[0.00004303075,0.0002303701,0.007652968,0.0001096795,0.00009100727,0.0002118589,0.001254978,0.8983514,0.01235171,0.06723361,0.01239904,0.00007032127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06233354,0.000310927,0.9197239,0.001013628,0.0001139917,0.001045029,0.001822381,0.006690025,0.006946581],"genre_scores_gemma":[0.4846809,0.000289304,0.5057064,0.0002417864,0.00007130758,0.0005745569,0.005136306,0.0002437551,0.003055655],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007955666,"threshold_uncertainty_score":0.01968753,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4362007664","doi":"10.32604/cmc.2023.032826","title":"A Privacy-Preserving System Design for Digital Presence Protection","year":2023,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Privacy protection; Path (computing); Access control; Resource (disambiguation); Computer vision; Real-time computing; Computer security; Computer network","authors":[{"name":"Eric Yocam","is_ca":true},{"name":"Ahmad I. Alomari","is_ca":true},{"name":"Amjad Gwanmeh","is_ca":true},{"name":"Wathiq Mansoor","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0454593471519713,"gpt":0.2805497010539806,"spread":0.2350903539020093,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001050753,0.0003884271,0.0003649319,0.0004155272,0.0007354526,0.001496498,0.001225029,0.0009371954,0.002924263],"category_scores_gemma":[0.001638192,0.0002605347,0.0004747755,0.000250846,0.0006008499,0.002379335,0.00132588,0.0009236285,0.001061207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005792687,"about_ca_system_score_gemma":0.0006699459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006223055,"about_ca_topic_score_gemma":0.0003941694,"domain_scores_codex":[0.9984331,0.000393,0.0001410145,0.0004000025,0.0005197437,0.0001130928],"domain_scores_gemma":[0.998944,0.0002011428,0.0001306966,0.0003431298,0.0003222177,0.00005878915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009015755,0.0004360753,0.003055872,0.0007718095,0.0002075127,0.001076175,0.001997762,0.04630949,0.4173104,0.1207993,0.00626067,0.4008735],"study_design_scores_gemma":[0.0001478297,0.001513486,0.002220072,0.0001099081,0.0002895541,0.002519877,0.0002931101,0.6356622,0.2611907,0.02124982,0.07467286,0.0001305267],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02091983,0.0001725033,0.9724054,0.0002178193,0.00005978561,0.000226471,0.00003670447,0.001329789,0.00463154],"genre_scores_gemma":[0.7154589,0.0002836027,0.2745801,0.0002637555,0.0000838339,0.0003567021,0.000110723,0.00006668459,0.008795725],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002924263,"threshold_uncertainty_score":0.009782612,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389144641","doi":"10.32604/cmc.2023.043168","title":"Shadow Extraction and Elimination of Moving Vehicles for Tracking Vehicles","year":2023,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Video Surveillance and Tracking Methods","field":"Computer 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 Saskatchewan","funders":"King Saud University","keywords":"Shadow (psychology); Artificial intelligence; Computer vision; Computer science; Tracking (education); Constant false alarm rate; Process (computing); Vehicle tracking system; Gaussian; Transformation (genetics); Intelligent transportation system; Engineering; Kalman filter","authors":[{"name":"Kalpesh Jadav","is_ca":false},{"name":"Vishal Sorathiya","is_ca":false},{"name":"Walid El‐Shafai","is_ca":false},{"name":"Torki Altameem","is_ca":false},{"name":"Moustafa H. Aly","is_ca":false},{"name":"Vipul Vekariya","is_ca":false},{"name":"Kawsar Ahmed","is_ca":true},{"name":"Francis M. Bui","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03055162177747794,"gpt":0.2957329756156452,"spread":0.2651813538381673,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003728328,0.0005670968,0.0005404302,0.001333564,0.0003564065,0.0006657972,0.0005499342,0.0003564328,0.001165131],"category_scores_gemma":[0.0009259512,0.000251103,0.0007265329,0.0007360199,0.000249185,0.0006519647,0.0004865589,0.0004472444,0.0008199668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003792245,"about_ca_system_score_gemma":0.0007616179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004742896,"about_ca_topic_score_gemma":0.006648739,"domain_scores_codex":[0.999559,0.00003950936,0.00001980948,0.0001199306,0.000195017,0.00006670369],"domain_scores_gemma":[0.9996701,0.00005003322,0.00004181217,0.00006195045,0.0001588979,0.00001719311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001908796,0.0001043129,0.007562619,0.0002171954,0.00007262122,0.0002336305,0.0001894674,0.02309974,0.1213163,0.002327273,0.003339147,0.8413468],"study_design_scores_gemma":[0.00002902902,0.0001839803,0.02647405,0.00005023912,0.0001615481,0.0009566905,0.000249644,0.7297464,0.2246505,0.002758451,0.01467671,0.00006277573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08113214,0.0007530316,0.9123936,0.0001062355,0.0001182081,0.0001078968,0.0002240086,0.00171155,0.003453315],"genre_scores_gemma":[0.6235111,0.001049324,0.3669512,0.0001080459,0.0000845162,0.00006427152,0.0009562006,0.0002419497,0.007033372],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004742896,"threshold_uncertainty_score":0.009430587,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4416393870","doi":"10.32604/cmc.2025.066421","title":"Error Analysis of Geomagnetic Field Reconstruction Model Using Negative Learning for Seismic Anomaly Detection","year":2025,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Earthquake Detection and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ; Universiti Putra Malaysia; Sveriges Geologiska Undersökning; Florida Institute of Technology; Alberta Agricultural Research Institute","keywords":"Earth's magnetic field; Sensitivity (control systems); Anomaly detection; Anomaly (physics); Field (mathematics); Pattern recognition (psychology); Magnetic anomaly","authors":[{"name":"Nur Syaiful Afrizal","is_ca":false},{"name":"Khairul Adib Yusof","is_ca":false},{"name":"Lokman Hakim Muhamad","is_ca":false},{"name":"Nurul Shazana Abdul Hamid","is_ca":false},{"name":"Mardina Abdullah","is_ca":false},{"name":"Mohd Amiruddin Abd Rahman","is_ca":false},{"name":"Syamsiah Mashohor","is_ca":false},{"name":"Hayakawa Masashi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01350375723359049,"gpt":0.2346721003626365,"spread":0.221168343129046,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001469995,0.0009389307,0.0005875144,0.0003745195,0.0002384608,0.0006755579,0.001007237,0.0006952103,0.00124901],"category_scores_gemma":[0.005215918,0.0002594534,0.0003923568,0.0001970296,0.0006047756,0.0008368993,0.0009622959,0.001163559,0.0002746093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004495547,"about_ca_system_score_gemma":0.000774461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003713571,"about_ca_topic_score_gemma":0.003590682,"domain_scores_codex":[0.9996728,0.00007070038,0.00002102277,0.00009326543,0.0001002028,0.00004205579],"domain_scores_gemma":[0.9987592,0.0006462093,0.0001491273,0.00009603725,0.0003047625,0.00004466841],"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":[0.0003673933,0.0001164979,0.006363418,0.0001598355,0.00007648572,0.0002040931,0.0001158614,0.8171517,0.01628618,0.00537313,0.001107128,0.1526782],"study_design_scores_gemma":[0.000001840449,0.00002320519,0.0002669848,0.000003331065,0.000003127003,0.00001718457,0.000004233192,0.9973481,0.001664721,0.0005841627,0.00007979672,0.000003369945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1563314,0.0003513246,0.8400857,0.000361091,0.00008408823,0.00003117969,0.00007433595,0.0008367649,0.001844056],"genre_scores_gemma":[0.9590343,0.0001127701,0.03903377,0.00009092691,0.00001778107,0.0000312838,0.000153136,0.00005002132,0.00147597],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003713571,"threshold_uncertainty_score":0.007774174,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4307874069","doi":"10.32604/cmc.2023.028597","title":"Analysis on D2D Heterogeneous Networks with State-Dependent Priority燭raffic","year":2022,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Advanced Wireless Network Optimization","field":"Engineering","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":"Government of Jiangsu Province","keywords":"Priority inheritance; Computer science; Priority queue; Priority ceiling protocol; Queueing theory; Queue; Correctness; Network packet; Computer network; Scheduling (production processes); Priority inversion; Real-time computing; Deadline-monotonic scheduling; Dynamic priority scheduling; Mathematical optimization; Algorithm; Round-robin scheduling; Rate-monotonic scheduling; Quality of service; Mathematics","authors":[{"name":"Guangjun Liang","is_ca":false},{"name":"Jianfang Xin","is_ca":false},{"name":"Linging Xia","is_ca":false},{"name":"Xueli Ni","is_ca":false},{"name":"Yi Cao","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.004609764940400173,"gpt":0.1865193322862308,"spread":0.1819095673458306,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00127514,0.000997065,0.0008132159,0.001021419,0.000900005,0.001409275,0.00148224,0.0009698786,0.002191008],"category_scores_gemma":[0.003363291,0.0004269455,0.0009155095,0.001037032,0.0009636919,0.002274408,0.001196107,0.0009397531,0.0001660944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002397702,"about_ca_system_score_gemma":0.001127143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01658578,"about_ca_topic_score_gemma":0.005813579,"domain_scores_codex":[0.9990501,0.0001993498,0.00003195513,0.0001960149,0.0002571957,0.0002654172],"domain_scores_gemma":[0.9982894,0.0008574865,0.0002390431,0.00006969932,0.0004346514,0.0001096743],"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":[0.00005590044,0.00003157987,0.001596054,0.00007561253,0.00004799437,0.0002946422,0.00006976789,0.9403764,0.001835338,0.04935956,0.0009357627,0.005321361],"study_design_scores_gemma":[0.000002097176,0.000006676492,0.000124896,0.000001745801,0.000005964257,0.00001252101,0.00001612418,0.9970062,0.00008539596,0.002626026,0.0001093008,0.000003175545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1117375,0.001585452,0.8746682,0.001024382,0.0001783241,0.00009013759,0.0002374424,0.0001644692,0.01031404],"genre_scores_gemma":[0.9820977,0.0009969902,0.01221123,0.0001256738,0.00007300862,0.00006653955,0.0001403045,0.00003043461,0.004258044],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01658578,"threshold_uncertainty_score":0.03297848,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4414755928","doi":"10.32604/cmc.2025.069134","title":"Prompt-Guided Dialogue State Tracking with GPT-2 and Graph Attention","year":2025,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Cognitive Functions and Memory","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Institute for Information and Communications Technology Promotion; Information Technology Research Centre; Ministry of Science and ICT, South Korea; Iran Telecommunication Research Center","keywords":"Leverage (statistics); Robustness (evolution); Generalizability theory; Graph; State (computer science); Flexibility (engineering); Key (lock); Component (thermodynamics)","authors":[{"name":"Muhammad Asif Khan","is_ca":false},{"name":"Bhuyan Kaibalya Prasad","is_ca":false},{"name":"Irfan Ullah","is_ca":false},{"name":"I.B. Khan","is_ca":false},{"name":"Jawad Khan","is_ca":false},{"name":"Yeong Hyeon Gu","is_ca":false},{"name":"Pavlos Kefalas","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01683025783187646,"gpt":0.2683501925890723,"spread":0.2515199347571959,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001407029,0.002048196,0.001018314,0.001259065,0.0005326495,0.001524218,0.002982134,0.001608443,0.005800489],"category_scores_gemma":[0.007054724,0.0006454551,0.001240245,0.0008758148,0.000651974,0.003112751,0.002600205,0.002812442,0.003080656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001322786,"about_ca_system_score_gemma":0.002062122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01531285,"about_ca_topic_score_gemma":0.02277973,"domain_scores_codex":[0.9989552,0.0002764964,0.00004905851,0.0005283459,0.0001212003,0.00006954357],"domain_scores_gemma":[0.9982244,0.001022387,0.00009220978,0.000325504,0.0002290052,0.0001065347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009874009,0.0003655373,0.004229135,0.000833794,0.0002331014,0.0003649087,0.001190997,0.1163208,0.02524923,0.01137178,0.0388751,0.7999783],"study_design_scores_gemma":[0.00007987509,0.0001023188,0.0006019068,0.00002599935,0.00005659878,0.0001095775,0.00008721129,0.9670938,0.007641881,0.01640642,0.007749395,0.00004500921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0172455,0.000952044,0.8905013,0.0004189029,0.0002796449,0.0002945072,0.002757551,0.08525343,0.002297151],"genre_scores_gemma":[0.3381613,0.0005234985,0.6438458,0.0007544901,0.0001405543,0.0009161751,0.008321822,0.002177536,0.005158828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01531285,"threshold_uncertainty_score":0.03044742,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4412040138","doi":"10.32604/cmc.2025.064414","title":"NADSA: A Novel Approach for Detection of Sinkhole Attacks Based on RPL Protocol in 6LowPAN Network","year":2025,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Network Security and Intrusion Detection","field":"Computer Science","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 New Brunswick","funders":"","keywords":"6LoWPAN; Sinkhole; Protocol (science); Computer network; Computer science; Computer security; Geography; Medicine; IPv6; World Wide Web; Archaeology; The Internet","authors":[{"name":"Atena Shiranzaei","is_ca":true},{"name":"Emad Alizadeh","is_ca":true},{"name":"Mahdi Rabbani","is_ca":true},{"name":"Sajjad Bagheri Baba Ahmadi","is_ca":true},{"name":"Mohsen Tajgardan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01327827972058689,"gpt":0.2531949490090319,"spread":0.2399166692884451,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008579105,0.0009742847,0.0007570786,0.001870973,0.0005274309,0.0009084651,0.001443792,0.0006442846,0.0006236768],"category_scores_gemma":[0.002082082,0.0002985758,0.0005365955,0.0006125952,0.0006459046,0.001978921,0.001063936,0.0006945828,0.0002516086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005358929,"about_ca_system_score_gemma":0.0006988099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009767988,"about_ca_topic_score_gemma":0.001021447,"domain_scores_codex":[0.9988274,0.0002626504,0.00009007891,0.0001876556,0.0005435353,0.00008861947],"domain_scores_gemma":[0.9988311,0.0003226966,0.0002663917,0.0001857923,0.0003435255,0.00005058701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008161586,0.0004419719,0.01282571,0.0008606996,0.0004000331,0.001213936,0.000596638,0.08345331,0.1467727,0.01642325,0.006816156,0.7293794],"study_design_scores_gemma":[0.00004673205,0.0005338004,0.00295003,0.00005413005,0.0001185084,0.001328463,0.0001834159,0.9161988,0.06543951,0.004562365,0.008487334,0.00009687124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04329138,0.0008186206,0.9488676,0.0002127216,0.0001540366,0.0002689792,0.00007946796,0.003964158,0.00234307],"genre_scores_gemma":[0.7634901,0.0005727475,0.2331505,0.0002012785,0.00005589543,0.0002032456,0.0001935385,0.00007926549,0.002053495],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001870973,"threshold_uncertainty_score":0.004537106,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4296990896","doi":"10.32604/cmc.2023.031282","title":"Fast Verification of Network Configuration Updates","year":2022,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Software-Defined Networks and 5G","field":"Computer Science","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 British Columbia","funders":"Fundamental Research Funds for the Central Universities; Hainan Association for Science and Technology; Hainan University; National Natural Science Foundation of China","keywords":"Correctness; Computer science; Distributed computing; Network simulation; Computer network; Algorithm","authors":[{"name":"Jiangyuan Yao","is_ca":false},{"name":"Zheng Jiang","is_ca":false},{"name":"Kaiwen Zou","is_ca":false},{"name":"Shuhua Weng","is_ca":false},{"name":"Yaxin Li","is_ca":false},{"name":"Deshun Li","is_ca":false},{"name":"Yahui Li","is_ca":false},{"name":"Xingcan Cao","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01007336000674494,"gpt":0.2100520161560818,"spread":0.1999786561493369,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003804979,0.0009431977,0.0008775046,0.001627932,0.001017176,0.001863731,0.002199495,0.0009386476,0.002535718],"category_scores_gemma":[0.01927655,0.0005872499,0.0008436639,0.0007370242,0.001485658,0.004224473,0.002476312,0.001369589,0.0006103136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001764415,"about_ca_system_score_gemma":0.002933154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004340556,"about_ca_topic_score_gemma":0.003714218,"domain_scores_codex":[0.9920567,0.001649469,0.0004116764,0.001640823,0.003537781,0.0007035549],"domain_scores_gemma":[0.9818512,0.006546666,0.001426336,0.006571938,0.003364024,0.0002398483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001169372,0.000194447,0.01486359,0.0005151341,0.0001456907,0.001189688,0.0008129454,0.2270377,0.07594988,0.07815249,0.01062183,0.5893472],"study_design_scores_gemma":[0.0001041647,0.0001959137,0.001537108,0.00006633699,0.00005776631,0.0004950658,0.0001555116,0.8519449,0.1075183,0.02739061,0.01046308,0.00007126687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04657014,0.0001982513,0.9363855,0.0001227043,0.00008932666,0.000184082,0.0002695842,0.01385457,0.002325865],"genre_scores_gemma":[0.7796755,0.0001539158,0.2160991,0.000150522,0.00003582686,0.0002019616,0.0007468893,0.0007576942,0.002178518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004340556,"threshold_uncertainty_score":0.02012289,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7115918670","doi":"10.32604/cmc.2025.074897","title":"A Comparative Benchmark of Machine and Deep Learning for Cyberattack Detection in IoT Networks","year":2025,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Benchmark (surveying); Deep learning; Metric (unit); Intrusion detection system; Internet of Things; Botnet; Selection (genetic algorithm); Precision and recall","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.008791581505577718,"gpt":0.2428821813819964,"spread":0.2340905998764187,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003982013,0.001688745,0.0006747745,0.002634434,0.0005932723,0.0009863056,0.001342024,0.001257616,0.0008354297],"category_scores_gemma":[0.007719308,0.0002563454,0.0004838901,0.001739604,0.0006701141,0.002099587,0.001256088,0.001024844,0.0004777266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001543235,"about_ca_system_score_gemma":0.0009102936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01154627,"about_ca_topic_score_gemma":0.0147468,"domain_scores_codex":[0.9977718,0.0007148786,0.000157399,0.0004519447,0.0006751164,0.0002288274],"domain_scores_gemma":[0.9967284,0.001444739,0.0002415613,0.0005276417,0.0008868577,0.0001707868],"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":[0.001121443,0.001125811,0.0285431,0.000603211,0.0003632776,0.0002512555,0.0001221952,0.6514143,0.006391462,0.005087973,0.02105357,0.2839225],"study_design_scores_gemma":[0.00004331402,0.0004188251,0.005942453,0.00006167599,0.00002796696,0.00008590378,0.0001048376,0.9803712,0.0071071,0.002657065,0.003158435,0.00002117887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8489116,0.006827005,0.1060657,0.002073104,0.0007353284,0.000440455,0.004648718,0.006340633,0.02395743],"genre_scores_gemma":[0.9236506,0.001181638,0.06354284,0.000398557,0.0001188825,0.0001748872,0.008291908,0.0002115356,0.002429157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01154627,"threshold_uncertainty_score":0.0229581,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4307873956","doi":"10.32604/cmc.2023.026607","title":"Identification and Visualization of Spatial and Temporal Trends in Textile Industry","year":2022,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Computer science; Data science; Visualization; Phrase; Field (mathematics); Identification (biology); Key (lock); Subject (documents); Textile; Information retrieval; Artificial intelligence; World Wide Web; Geography","authors":[{"name":"Umair Yousaf","is_ca":false},{"name":"Muhammad Asif","is_ca":false},{"name":"Shahbaz Ahmed","is_ca":false},{"name":"Noman Tahir","is_ca":false},{"name":"Azeem Irshad","is_ca":false},{"name":"Akber Abid Gardezi","is_ca":false},{"name":"Muhammad Sahfiq","is_ca":false},{"name":"Jin‐Ghoo Choi","is_ca":false},{"name":"Habib Hamam","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01137205358337471,"gpt":0.2688125094646664,"spread":0.2574404558812917,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007020239,0.000302747,0.0002034691,0.01328333,0.0003214868,0.001559563,0.0002006964,0.0003650474,0.003409565],"category_scores_gemma":[0.003117376,0.0001385933,0.000317261,0.01205088,0.00016886,0.001365733,0.0006557704,0.0003952358,0.0008774863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004019532,"about_ca_system_score_gemma":0.0006437135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01039418,"about_ca_topic_score_gemma":0.01675969,"domain_scores_codex":[0.9997268,0.00005422548,0.00004133914,0.00005445121,0.00007901116,0.00004414205],"domain_scores_gemma":[0.9976609,0.0007584249,0.0006937972,0.0001409027,0.0006180911,0.0001279073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009051155,0.0001978967,0.3613811,0.002230464,0.0002671401,0.001975987,0.01447148,0.009284291,0.03262967,0.01621436,0.08362398,0.4768185],"study_design_scores_gemma":[0.00004839809,0.0002263734,0.75857,0.000667446,0.0001695101,0.001038466,0.0119312,0.06563386,0.008679468,0.008383281,0.1445543,0.00009756788],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8291529,0.008109954,0.02610788,0.004590424,0.0004305903,0.0002020177,0.09211121,0.005957166,0.0333379],"genre_scores_gemma":[0.9232411,0.003744132,0.04370284,0.000128934,0.0002034128,0.0001888764,0.0226822,0.0002901724,0.005818394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01328333,"threshold_uncertainty_score":0.02066737,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4408001831","doi":"10.32604/cmc.2025.057792","title":"Amalgamation of Classical and Large Language Models for Duplicate Bug Detection: A Comparative Study","year":2025,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Computer science; Natural language processing; Artificial intelligence; Linguistics; Philosophy","authors":[{"name":"Sai Venkata Akhil Ammu","is_ca":true},{"name":"Sukhjit Singh Sehra","is_ca":true},{"name":"Sumeet Kaur Sehra","is_ca":true},{"name":"Jaiteg Singh","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01555918790220971,"gpt":0.2876918971537875,"spread":0.2721327092515777,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0186986,0.001524354,0.001458274,0.003745341,0.001113787,0.003693476,0.002536261,0.001554078,0.001831869],"category_scores_gemma":[0.0413302,0.0006344299,0.002360801,0.002459732,0.001077572,0.008155562,0.001973366,0.002245215,0.001041026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002489392,"about_ca_system_score_gemma":0.002313542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009304912,"about_ca_topic_score_gemma":0.007067529,"domain_scores_codex":[0.9906509,0.005840994,0.0006320685,0.00120703,0.001355851,0.0003132176],"domain_scores_gemma":[0.9081095,0.08055627,0.001538242,0.004032944,0.004843845,0.0009191902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00838262,0.003405563,0.05493775,0.001812303,0.002265145,0.0005287797,0.002154523,0.149373,0.0045565,0.007680241,0.01156797,0.7533355],"study_design_scores_gemma":[0.0002201693,0.001165582,0.008950223,0.0001068671,0.0008464818,0.0003469958,0.001034103,0.9753523,0.002498608,0.006834972,0.002507432,0.0001362465],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7758138,0.01166218,0.1979677,0.001650024,0.0004282075,0.0003851936,0.001425711,0.005993411,0.004673796],"genre_scores_gemma":[0.915404,0.001835481,0.07774428,0.0002437494,0.0001738293,0.000215872,0.002010459,0.0005660047,0.001806378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0186986,"threshold_uncertainty_score":0.09888887,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4393435355","doi":"10.32604/cmc.2024.048787","title":"Alternative Method of Constructing Granular Neural Networks","year":2024,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Neural Networks and Applications","field":"Computer Science","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 Alberta","funders":"","keywords":"Interpretability; Granular computing; Granularity; Computer science; Artificial neural network; Data mining; Interval (graph theory); Process (computing); Artificial intelligence; Fuzzy logic; Machine learning; Algorithm; Rough set; Mathematics","authors":[{"name":"Yushan Yin","is_ca":false},{"name":"Witold Pedrycz","is_ca":true},{"name":"Zhiwu Li","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01412023348945132,"gpt":0.2652711569541157,"spread":0.2511509234646644,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001157344,0.0006744115,0.0008518001,0.001323555,0.0004678649,0.001381167,0.001342363,0.0009553718,0.003030969],"category_scores_gemma":[0.003819159,0.0004538456,0.0007897565,0.001321866,0.0006691575,0.001928947,0.001326553,0.00120208,0.0004679149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008366992,"about_ca_system_score_gemma":0.000901436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00263152,"about_ca_topic_score_gemma":0.00219728,"domain_scores_codex":[0.999409,0.0001419596,0.00005489401,0.0001324628,0.0002028579,0.00005875378],"domain_scores_gemma":[0.9991054,0.0003576615,0.00009700426,0.0001562335,0.0002406756,0.0000430151],"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":[0.000177579,0.00005440634,0.001341395,0.0002499383,0.00009463268,0.0001837943,0.000163839,0.6820403,0.007160284,0.07932126,0.002043463,0.2271691],"study_design_scores_gemma":[0.00001027355,0.00001726125,0.00008967757,0.0000121917,0.0000105191,0.00002823197,0.0000116608,0.9830369,0.001320533,0.01430449,0.001151374,0.000006832711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006135463,0.0001037875,0.9916094,0.00007835092,0.00004033676,0.00003823176,0.00004457511,0.0002883114,0.001661602],"genre_scores_gemma":[0.3277473,0.0003178196,0.668325,0.0001554376,0.00006546712,0.0002660973,0.0002642158,0.0001338416,0.002724868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003030969,"threshold_uncertainty_score":0.01013958,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}