{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":66,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":66,"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":"d84a9a6e7621","filters":{"venue":"Artificial Intelligence Review"}},"results":[{"id":"W4366091323","doi":"10.1007/s10462-023-10466-8","title":"Deep learning modelling techniques: current progress, applications, advantages, and challenges","year":2023,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":960,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"University of Technology Sydney","keywords":"Computer science; Deep learning; Artificial intelligence; Machine learning; Field (mathematics); Convolutional neural network; Benchmark (surveying); Feature learning; Data science","authors":[{"name":"Shams Forruque Ahmed","is_ca":false},{"name":"Md. Sakib Bin Alam","is_ca":false},{"name":"Maruf Hassan","is_ca":false},{"name":"Mahtabin Rodela Rozbu","is_ca":false},{"name":"Taoseef Ishtiak","is_ca":true},{"name":"Nazifa Rafa","is_ca":false},{"name":"M. Mofijur","is_ca":false},{"name":"A. B. M. Shawkat Ali","is_ca":false},{"name":"Amir H. Gandomi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1141363797842169,"gpt":0.3639477050034945,"spread":0.2498113252192777,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003796856,0.001068617,0.0008233539,0.001320885,0.0002706319,0.002849582,0.002203513,0.001502395,0.002796464],"category_scores_gemma":[0.006176477,0.0006551723,0.001058022,0.00158937,0.001148647,0.004137725,0.001791341,0.0036023,0.001490247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001255476,"about_ca_system_score_gemma":0.001343777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004580695,"about_ca_topic_score_gemma":0.003134067,"domain_scores_codex":[0.9985928,0.0004206542,0.000129144,0.0002341682,0.0005399602,0.00008325931],"domain_scores_gemma":[0.9968628,0.001761558,0.0001504959,0.0002413094,0.0008936164,0.00009025076],"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":[0.00009958517,0.0001173885,0.002985549,0.002053844,0.0001577035,0.0001264431,0.0001902242,0.07410452,0.001656049,0.08967746,0.01438778,0.8144435],"study_design_scores_gemma":[0.00002963505,0.0001823131,0.001597676,0.002400733,0.0001388475,0.0003441041,0.0003269041,0.6527854,0.004802367,0.1514941,0.1857776,0.0001202409],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01926256,0.4898424,0.453209,0.01768154,0.0009279719,0.00009114303,0.0004642803,0.001017009,0.0175041],"genre_scores_gemma":[0.2825759,0.5564152,0.1468524,0.002441485,0.001471191,0.0001442972,0.001173081,0.000307568,0.008618986],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004580695,"threshold_uncertainty_score":0.02007997,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2883445328","doi":"10.1007/s10462-018-9646-y","title":"40 years of cognitive architectures: core cognitive abilities and practical applications","year":2018,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":516,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Air Force Office of Scientific Research; Canada Excellence Research Chairs, Government of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Cognition; Cognitive architecture; Variety (cybernetics); Set (abstract data type); Cognitive science; Perception; Field (mathematics); Selection (genetic algorithm); Data science; Rational analysis; Artificial intelligence; Psychology; Neuroscience","authors":[{"name":"Iuliia Kotseruba","is_ca":true},{"name":"John K. Tsotsos","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.107634902286158,"gpt":0.3884198155905721,"spread":0.2807849133044141,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003102739,0.001427463,0.001075038,0.005226342,0.001040167,0.003943071,0.001647466,0.002095449,0.006361276],"category_scores_gemma":[0.006390621,0.0007137229,0.0008174411,0.005385186,0.004648149,0.008340194,0.002525739,0.003037064,0.001573651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003616647,"about_ca_system_score_gemma":0.003137913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003927462,"about_ca_topic_score_gemma":0.00303533,"domain_scores_codex":[0.9985728,0.0004357217,0.0001477418,0.0002966751,0.0004460868,0.0001009966],"domain_scores_gemma":[0.9951836,0.003377654,0.0002120438,0.0003634688,0.0006700319,0.000193124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007092144,0.00006499508,0.001228524,0.004339494,0.00008870821,0.0001172567,0.001612546,0.003292379,0.0007461263,0.3832398,0.0167382,0.588461],"study_design_scores_gemma":[0.00001049167,0.00008988721,0.002486518,0.003933823,0.00004971002,0.000510091,0.0008235424,0.002058908,0.0006172372,0.302117,0.687238,0.00006493222],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004576968,0.9285637,0.02059332,0.00797759,0.0006329545,0.00003233218,0.0001215313,0.000133482,0.03736822],"genre_scores_gemma":[0.06068596,0.9081975,0.01876916,0.002274355,0.001527604,0.0001195653,0.0002452619,0.0001036924,0.008076908],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006361276,"threshold_uncertainty_score":0.02624071,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3201077663","doi":"10.1007/s10462-021-10068-2","title":"An automated essay scoring systems: a systematic literature review","year":2021,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":466,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Grading (engineering); Cohesion (chemistry); Relevance (law); Artificial intelligence; Evaluation methods; Data science","authors":[{"name":"Dadi Ramesh","is_ca":true},{"name":"Suresh Kumar Sanampudi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05070367394269971,"gpt":0.3469837066823772,"spread":0.2962800327396775,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03095992,0.001378987,0.007763783,0.01702374,0.0009596975,0.004178014,0.003798845,0.002281541,0.004062529],"category_scores_gemma":[0.1004118,0.001161882,0.005571404,0.01149013,0.001574879,0.004384035,0.002994222,0.001611146,0.0006507061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003233307,"about_ca_system_score_gemma":0.01598152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005014418,"about_ca_topic_score_gemma":0.01824266,"domain_scores_codex":[0.9726405,0.01067385,0.009409751,0.001916237,0.005064133,0.0002955766],"domain_scores_gemma":[0.9101601,0.06369889,0.01161603,0.001673333,0.01216163,0.0006900252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0004313559,0.0001285926,0.003926791,0.7374538,0.00943111,0.0001107198,0.000511479,0.00031506,0.0002776761,0.0004680298,0.00472138,0.242224],"study_design_scores_gemma":[0.0007193945,0.0007992567,0.01353697,0.8536056,0.08372382,0.000607087,0.001106427,0.0007844805,0.0005834319,0.001042053,0.04333518,0.0001564467],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002774685,0.9926935,0.001308536,0.0006224596,0.0002200845,0.0009526198,0.00074578,0.0000308462,0.0006514242],"genre_scores_gemma":[0.0460788,0.9412262,0.007871666,0.001236663,0.0002096376,0.001720484,0.001317391,0.00002515945,0.0003138997],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.03095992,"threshold_uncertainty_score":0.1637337,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3186240982","doi":"10.1007/s10462-021-10043-x","title":"News recommender system: a review of recent progress, challenges, and opportunities","year":2021,"lang":"en","type":"review","venue":"Artificial Intelligence Review","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":203,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Recommender system; Information overload; Focus (optics); Order (exchange); Data science; Deep neural networks; State (computer science); World Wide Web; Deep learning; Artificial intelligence","authors":[{"name":"Shaina Raza","is_ca":true},{"name":"Chen Ding","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4596284479293151,"gpt":0.4188895473862157,"spread":0.04073890054309942,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003341284,0.000600944,0.001930529,0.003699958,0.0004355104,0.00165273,0.001396322,0.001598962,0.00376379],"category_scores_gemma":[0.005553985,0.0004114435,0.0008134673,0.005531213,0.0004284128,0.002516506,0.0006650615,0.00186873,0.001937206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000851943,"about_ca_system_score_gemma":0.002160256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00361545,"about_ca_topic_score_gemma":0.008191985,"domain_scores_codex":[0.999121,0.0002065771,0.0001276319,0.0001404141,0.0003604209,0.00004387175],"domain_scores_gemma":[0.9936819,0.004121916,0.0003143437,0.00009554831,0.001544035,0.0002421137],"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":[0.0001043609,0.0001010274,0.0008127437,0.01869551,0.0001952375,0.00006428114,0.0000686781,0.0003585901,0.0005542351,0.002589541,0.05320696,0.9232489],"study_design_scores_gemma":[0.0000703426,0.0003421896,0.003640658,0.01060089,0.0009371378,0.0009105192,0.0002181394,0.001140316,0.0005223653,0.003391221,0.9781335,0.0000927103],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002070286,0.997317,0.0004874606,0.001014403,0.0003043718,0.00001052917,0.00005776157,0.00001780179,0.0005835879],"genre_scores_gemma":[0.001136241,0.9960056,0.001373872,0.0005094587,0.0005477082,0.00001054543,0.0000891504,0.000003345782,0.0003241091],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00376379,"threshold_uncertainty_score":0.01767063,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2782623435","doi":"10.1007/s10462-018-9612-8","title":"Application of artificial intelligence techniques in the petroleum industry: a review","year":2018,"lang":"en","type":"review","venue":"Artificial Intelligence Review","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":203,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Artificial intelligence; Artificial neural network; Petroleum industry; Fuzzy logic; Swarm intelligence; Machine learning; Applications of artificial intelligence; Engineering; Particle swarm optimization","authors":[{"name":"Hamid Rahmanifard","is_ca":true},{"name":"Tatyana Plaksina","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1310633767058561,"gpt":0.4162598069012182,"spread":0.2851964301953621,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001015833,0.0008277502,0.00142217,0.003902144,0.0002884081,0.001455625,0.001090912,0.001227469,0.003723364],"category_scores_gemma":[0.002481349,0.0003165105,0.000760121,0.004465564,0.0004738854,0.001774333,0.000751788,0.001122984,0.001015285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005248679,"about_ca_system_score_gemma":0.002137622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001603663,"about_ca_topic_score_gemma":0.00260286,"domain_scores_codex":[0.9996156,0.00006222791,0.0000773798,0.0000607682,0.0001615702,0.00002252764],"domain_scores_gemma":[0.9983551,0.001062559,0.0001666571,0.00003354828,0.0003239844,0.00005817746],"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":[0.00005964281,0.0001058765,0.0004542031,0.04172417,0.0001800485,0.0001792616,0.00007850389,0.0008747883,0.001149509,0.003909506,0.0150825,0.936202],"study_design_scores_gemma":[0.00003077615,0.0001903255,0.001876831,0.01516201,0.0006850687,0.001283287,0.0001674436,0.0007024093,0.001188077,0.004880211,0.97377,0.00006368088],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002243985,0.998008,0.0003911743,0.0002479269,0.0001598841,0.000007719169,0.00002504925,0.000007451931,0.000928445],"genre_scores_gemma":[0.0009431781,0.9979953,0.000508137,0.000122744,0.000152601,0.000006272006,0.0000259153,0.000001577473,0.0002442926],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003902144,"threshold_uncertainty_score":0.01245588,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2797143217","doi":"10.1007/s10462-018-9631-5","title":"Artificial intelligence test: a case study of intelligent vehicles","year":2018,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":148,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Test (biology); Computer science; Artificial intelligence; Artificial intelligence, situated approach; Applications of artificial intelligence; Machine learning","authors":[{"name":"Li Li","is_ca":false},{"name":"Nanning Zheng","is_ca":false},{"name":"Fei‐Yue Wang","is_ca":false},{"name":"Yuehu Liu","is_ca":false},{"name":"Dongpu Cao","is_ca":true},{"name":"Kunfeng Wang","is_ca":false},{"name":"Wuling Huang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1165053816690335,"gpt":0.3882024655908736,"spread":0.2716970839218401,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001171387,0.0005616184,0.0002755819,0.0017426,0.001600788,0.001491275,0.001571376,0.002353279,0.002907989],"category_scores_gemma":[0.007407921,0.0001615341,0.0004377479,0.001181848,0.001275716,0.001216558,0.0008804116,0.0007781742,0.0008992018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001181589,"about_ca_system_score_gemma":0.001067909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01016359,"about_ca_topic_score_gemma":0.0146801,"domain_scores_codex":[0.9985831,0.0004018412,0.00008783407,0.0001609118,0.000535009,0.0002314159],"domain_scores_gemma":[0.9951465,0.002984811,0.0003164783,0.0002896975,0.0009048548,0.0003577798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001291557,0.005056344,0.5395122,0.0009961001,0.000300574,0.1173657,0.01330325,0.01575775,0.01047227,0.01701613,0.02817157,0.2507565],"study_design_scores_gemma":[0.000379764,0.005246002,0.332291,0.001021872,0.0005866808,0.1868508,0.06020062,0.1556372,0.06583133,0.02250601,0.1691402,0.0003084536],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9742051,0.0006624479,0.00720967,0.001513016,0.00008696199,0.0002066706,0.000617155,0.0001487909,0.01535022],"genre_scores_gemma":[0.989111,0.0004104265,0.005301135,0.0002756837,0.00003005367,0.0000439438,0.000471324,0.00005080787,0.004305605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01016359,"threshold_uncertainty_score":0.02020884,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3118820303","doi":"10.1007/s10462-020-09948-w","title":"Machine learning towards intelligent systems: applications, challenges, and opportunities","year":2021,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":132,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Government of Ontario","keywords":"Process (computing); The Internet; Mechanism (biology); Work (physics); Field (mathematics); Cognition","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.257928733914214,"gpt":0.3262040223463608,"spread":0.06827528843214675,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005724401,0.000575413,0.001142684,0.00242012,0.0005228671,0.004162244,0.001273555,0.002465674,0.002713451],"category_scores_gemma":[0.007598519,0.0003622812,0.0004736653,0.003856444,0.003378333,0.007538345,0.001457041,0.005051501,0.001185146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002090911,"about_ca_system_score_gemma":0.002738904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001265824,"about_ca_topic_score_gemma":0.002115831,"domain_scores_codex":[0.9977682,0.00095994,0.0001210652,0.0001557191,0.0008626715,0.0001324705],"domain_scores_gemma":[0.9853276,0.01115106,0.000494312,0.0003495564,0.002337064,0.0003404468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005176031,0.0001188388,0.001104604,0.005285035,0.00007998047,0.00008374922,0.0002294174,0.002452764,0.0006680003,0.2640148,0.05090259,0.6750085],"study_design_scores_gemma":[0.00002099157,0.0001087219,0.001601677,0.004517058,0.0000494625,0.0003550509,0.0004724205,0.005123286,0.0005537934,0.246034,0.7411237,0.00003975114],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007408062,0.9582618,0.006118433,0.02831171,0.0009256668,0.000008346164,0.00001767714,0.00003083556,0.005584642],"genre_scores_gemma":[0.01189113,0.9763049,0.004198754,0.003442866,0.002893105,0.00001741802,0.00002536597,0.00001280835,0.001213568],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005724401,"threshold_uncertainty_score":0.03027385,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4283764803","doi":"10.1007/s10462-022-10226-0","title":"Deep learning in the stock market—a systematic survey of practice, backtesting, and applications","year":2022,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":118,"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":"","keywords":"Computer science; Portfolio; Volatility (finance); Mainstream; Deep learning; Stock (firearms); Stock market; Financial market; Artificial intelligence; Machine learning; Data science; Econometrics; Context (archaeology); Finance; Economics","authors":[{"name":"Kenniy Olorunnimbe","is_ca":true},{"name":"Herna L. Viktor","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2870549963427843,"gpt":0.4776395364419016,"spread":0.1905845400991173,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01157468,0.00110318,0.001453773,0.004370942,0.0003548631,0.002544232,0.001720864,0.001531993,0.001874109],"category_scores_gemma":[0.02654576,0.0007139981,0.001005702,0.005589747,0.001290351,0.003350634,0.001348327,0.002016233,0.0006793196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001669857,"about_ca_system_score_gemma":0.002457419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004251715,"about_ca_topic_score_gemma":0.004102601,"domain_scores_codex":[0.9968346,0.001194283,0.0004284717,0.0004827355,0.0009557612,0.0001041558],"domain_scores_gemma":[0.9787472,0.01739788,0.000701274,0.00070978,0.002215996,0.0002277815],"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":[0.0001030638,0.0001157714,0.003744429,0.008627831,0.0002257256,0.00005939218,0.0002224253,0.006151226,0.0006118328,0.0125072,0.005703564,0.9619275],"study_design_scores_gemma":[0.0001763482,0.001757576,0.01937931,0.05844127,0.001368862,0.00104073,0.001557181,0.04792343,0.01114884,0.08457888,0.7723387,0.0002889],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.006865231,0.9597566,0.02468149,0.003050786,0.0002288248,0.00008955703,0.0001689547,0.0001216156,0.005036993],"genre_scores_gemma":[0.06069374,0.9037544,0.03197134,0.001437836,0.0004546473,0.0001452744,0.0003227961,0.0000863574,0.001133671],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01157468,"threshold_uncertainty_score":0.06121349,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1487234737","doi":"10.1023/a:1015023512975","title":"Explanation and Argumentation Capabilities:Towards the Creation of More Persuasive Agents","year":2002,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":98,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Department of National Defence; Université Laval","funders":"","keywords":"Argumentative; Computer science; Argumentation theory; Argument (complex analysis); Credibility; Field (mathematics); Domain knowledge; Data science; Set (abstract data type); Management science; Knowledge management; Artificial intelligence; Epistemology","authors":[{"name":"Bernard Moulin","is_ca":true},{"name":"Hengameh Irandoust","is_ca":true},{"name":"Munroe Eagles Paul Bélanger","is_ca":true},{"name":"G. Desbordes","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1331654687198182,"gpt":0.3481229975697713,"spread":0.2149575288499532,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009385414,0.0008705196,0.001066133,0.002554574,0.0005387497,0.005857625,0.002793686,0.005246242,0.006679455],"category_scores_gemma":[0.02469731,0.0004771918,0.0008719338,0.001668187,0.003868669,0.01348436,0.002989595,0.002805946,0.001762066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008584486,"about_ca_system_score_gemma":0.001488236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004762085,"about_ca_topic_score_gemma":0.0003759086,"domain_scores_codex":[0.9944046,0.003226379,0.0003263376,0.0004792456,0.001408611,0.0001548581],"domain_scores_gemma":[0.9636522,0.03063169,0.001487849,0.001794592,0.001910654,0.000522961],"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":[0.0001159165,0.000219906,0.0009796264,0.005036015,0.0001479487,0.0002361272,0.002565901,0.003748141,0.003275191,0.4431724,0.005750322,0.5347524],"study_design_scores_gemma":[0.000189309,0.0002317098,0.001230856,0.00205666,0.0001864511,0.001156659,0.0009392768,0.02006656,0.003829348,0.7182906,0.251725,0.00009757083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02371243,0.3407732,0.5112689,0.03475128,0.001480008,0.0003212616,0.00009851899,0.0007700608,0.0868245],"genre_scores_gemma":[0.3835415,0.1388171,0.4517654,0.003804585,0.002976405,0.0005387393,0.0003268663,0.0002559509,0.01797344],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009385414,"threshold_uncertainty_score":0.04963547,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309349667","doi":"10.1007/s10462-022-10305-2","title":"Image denoising in the deep learning era","year":2022,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":93,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Computer science; Noise reduction; Artificial intelligence; Deep learning; Benchmark (surveying); Noise (video); Machine learning; Deep neural networks; Artificial neural network; Image (mathematics); Image denoising; Pattern recognition (psychology); Computer vision; Data science","authors":[{"name":"Saeed Izadi","is_ca":true},{"name":"Darren Sutton","is_ca":true},{"name":"Ghassan Hamarneh","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07066406562607672,"gpt":0.3549113393011013,"spread":0.2842472736750246,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001511539,0.00056441,0.0008319693,0.0008279281,0.0001724942,0.001043158,0.0007363222,0.001402884,0.001344028],"category_scores_gemma":[0.002698422,0.0002786169,0.000378841,0.0009815926,0.001321885,0.00191018,0.0007728898,0.002909286,0.00064822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00080669,"about_ca_system_score_gemma":0.0008414841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001682859,"about_ca_topic_score_gemma":0.001963834,"domain_scores_codex":[0.999678,0.00006525301,0.00002307609,0.00005422759,0.0001575085,0.00002191388],"domain_scores_gemma":[0.998667,0.0007514051,0.00006237315,0.00006040042,0.000410849,0.00004799788],"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":[0.00008471918,0.00006809917,0.0005340814,0.004028433,0.000139177,0.00008645812,0.00006994864,0.009164535,0.00545022,0.08613352,0.01954309,0.8746977],"study_design_scores_gemma":[0.00003252829,0.000233974,0.002373041,0.003394302,0.0001937435,0.001320341,0.0001240566,0.07801525,0.01835446,0.2102661,0.685598,0.00009423816],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003522795,0.8407949,0.1389706,0.008288662,0.001605776,0.00001409222,0.00006484845,0.0001138374,0.006624429],"genre_scores_gemma":[0.04781393,0.8819962,0.05326096,0.003965044,0.003807327,0.00003302039,0.0001217894,0.00009124049,0.008910503],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.001682859,"threshold_uncertainty_score":0.007993877,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2969402372","doi":"10.1007/s10462-019-09753-0","title":"Modeling empathy: building a link between affective and cognitive processes","year":2019,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":82,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Empathy; Simulation theory of empathy; Cognition; Variety (cybernetics); Computer science; Cognitive psychology; Field (mathematics); Cognitive science; Common ground; Psychology; Artificial intelligence; Social psychology; Neuroscience","authors":[{"name":"Özge Nilay Yalçın","is_ca":true},{"name":"Steve DiPaola","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1466042982666868,"gpt":0.44942087456389,"spread":0.3028165762972032,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001762888,0.001248143,0.0009626889,0.001429337,0.0003769215,0.002991472,0.002392541,0.001992925,0.002534111],"category_scores_gemma":[0.004825108,0.0005282983,0.0007051979,0.0009702099,0.002388397,0.004825007,0.001188782,0.002954753,0.0006595706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001352607,"about_ca_system_score_gemma":0.001280684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003893524,"about_ca_topic_score_gemma":0.002751962,"domain_scores_codex":[0.9996138,0.0001490663,0.00002284853,0.00009850155,0.00008404611,0.00003179225],"domain_scores_gemma":[0.9965549,0.002814481,0.0001886823,0.0001249338,0.0002414513,0.00007571626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000943365,0.0002933842,0.007732034,0.006597474,0.0006698365,0.0002304581,0.001560751,0.05475066,0.003653914,0.356321,0.006500843,0.5615953],"study_design_scores_gemma":[0.00004697646,0.0003207682,0.02263954,0.003899693,0.0006965734,0.0008617236,0.001370739,0.1880016,0.002720399,0.6291958,0.1500076,0.0002385846],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.03035129,0.6177298,0.3009026,0.01932368,0.001109376,0.0001097708,0.0001904165,0.0003877412,0.02989526],"genre_scores_gemma":[0.4516823,0.4259911,0.1117247,0.003012415,0.001564908,0.0001983872,0.0003092923,0.0001066318,0.005410209],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003893524,"threshold_uncertainty_score":0.009813905,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4210542188","doi":"10.1007/s10462-021-10124-x","title":"Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review","year":2022,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":82,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"Universiti Pendidikan Sultan Idris","keywords":"Multiple-criteria decision analysis; Context (archaeology); Multidisciplinary approach; Coronavirus disease 2019 (COVID-19); Management science; Computer science; Pandemic; Decision analysis; Data science; Operations research; Risk analysis (engineering); Medicine; Disease; Sociology; Infectious disease (medical specialty); Geography; Engineering; Social science; Mathematics","authors":[{"name":"M. A. Alsalem","is_ca":false},{"name":"A. H. Alamoodi","is_ca":false},{"name":"O. S. Albahri","is_ca":false},{"name":"Kareem Abbas Dawood","is_ca":false},{"name":"R. T. Mohammed","is_ca":false},{"name":"Alhamzah Alnoor","is_ca":false},{"name":"A. A. Zaidan","is_ca":false},{"name":"A. S. Albahri","is_ca":false},{"name":"B. B. Zaidan","is_ca":false},{"name":"F. M. Jumaah","is_ca":true},{"name":"Jameel R. Al‐Obaidi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3122358513913376,"gpt":0.5498448854277446,"spread":0.237609034036407,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005085122,0.0009068194,0.001432744,0.004233497,0.0004698226,0.003043629,0.001732724,0.001556979,0.002516794],"category_scores_gemma":[0.009664049,0.0003936022,0.001323888,0.004540416,0.0009725647,0.002110146,0.0009391359,0.001728518,0.0003945856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002664128,"about_ca_system_score_gemma":0.002656453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00262453,"about_ca_topic_score_gemma":0.002817294,"domain_scores_codex":[0.9981191,0.0008381107,0.0001476971,0.000144142,0.0006471624,0.000103844],"domain_scores_gemma":[0.9895729,0.009030038,0.0003553905,0.0001056141,0.0008688932,0.00006706232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001049802,0.0002467866,0.001107915,0.02366728,0.0005379905,0.0002386153,0.0003586591,0.0389103,0.000741741,0.1822611,0.01010624,0.7417182],"study_design_scores_gemma":[0.00007651794,0.0004975726,0.00435893,0.03519387,0.0009866102,0.0008554652,0.001232528,0.1079097,0.001741088,0.5556441,0.2912979,0.0002057284],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00225784,0.9556043,0.03100477,0.003541317,0.0002286729,0.00004165606,0.00004289098,0.00001708259,0.007261413],"genre_scores_gemma":[0.09145313,0.8751764,0.03084314,0.0008381688,0.0006446118,0.0001121475,0.00009288435,0.0000136919,0.0008258423],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005085122,"threshold_uncertainty_score":0.02689302,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391738567","doi":"10.1007/s10462-023-10678-y","title":"Optimizing long-short-term memory models via metaheuristics for decomposition aided wind energy generation forecasting","year":2024,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":75,"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":"Science Fund of the Republic of Serbia","keywords":"Computer science; Wind power; Benchmark (surveying); Metaheuristic; Hyperparameter; Artificial neural network; Renewable energy; Decomposition; Artificial intelligence; Machine learning","authors":[{"name":"M. Pavlov","is_ca":false},{"name":"Luka Jovanović","is_ca":false},{"name":"Nebojša Bačanin","is_ca":false},{"name":"Muhammet Deveci","is_ca":false},{"name":"Miodrag Živković","is_ca":false},{"name":"Milan Tuba","is_ca":false},{"name":"Ivana Strumberger","is_ca":false},{"name":"Witold Pedrycz","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1195371479184191,"gpt":0.3208487149796302,"spread":0.2013115670612111,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009786157,0.001127979,0.0008726668,0.000618574,0.0002222423,0.0007794659,0.0008149889,0.001174005,0.001261511],"category_scores_gemma":[0.001779203,0.0004274071,0.0009451443,0.0005826826,0.00037011,0.0005478546,0.0005734439,0.001081306,0.0001760575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005684404,"about_ca_system_score_gemma":0.000928043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006710251,"about_ca_topic_score_gemma":0.005376708,"domain_scores_codex":[0.9998294,0.00007405588,0.000011051,0.00002730734,0.00002682354,0.00003133884],"domain_scores_gemma":[0.9992915,0.0005350171,0.00005340401,0.00002171788,0.00007734189,0.00002104183],"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":[0.00001562416,0.00001896787,0.0001986141,0.00002298941,0.00002754497,0.00001735199,0.000006842023,0.9894289,0.0002597705,0.0009118009,0.0001752197,0.008916403],"study_design_scores_gemma":[0.000002700777,0.000008950096,0.00002690654,0.000003939975,0.000004219492,0.000001754532,0.000002602176,0.9994249,0.0000694472,0.000392056,0.00006150428,9.937971e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1007332,0.00275767,0.8890958,0.0006079425,0.0001654055,0.00009421354,0.0001575289,0.0004890933,0.005899094],"genre_scores_gemma":[0.858767,0.0008387004,0.1377513,0.0002152131,0.00007040833,0.0002114406,0.000209476,0.0000686282,0.001867803],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006710251,"threshold_uncertainty_score":0.01334238,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W152517204","doi":"10.1007/s10462-004-5899-8","title":"Relation Algebras and their Application in Temporal and Spatial Reasoning","year":2005,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Brock University","funders":"","keywords":"Binary relation; Relation (database); Spatial intelligence; Relational calculus; Converse; Relation algebra; Computer science; Spatial relation; Formalism (music); Algebra over a field; Mathematics; Relational model; Calculus (dental); Relational database; Discrete mathematics; Pure mathematics; Artificial intelligence; Information retrieval; Two-element Boolean algebra","authors":[{"name":"Ivo D�ntsch","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02811598587504287,"gpt":0.2862117436893437,"spread":0.2580957578143008,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007630852,0.001066973,0.002455231,0.00559603,0.001434049,0.006350071,0.003703449,0.002277818,0.004868493],"category_scores_gemma":[0.0144533,0.001399238,0.002510765,0.01450141,0.008700569,0.00973337,0.002821777,0.005976312,0.001200519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004328254,"about_ca_system_score_gemma":0.003547226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01200635,"about_ca_topic_score_gemma":0.009986214,"domain_scores_codex":[0.9956051,0.001537982,0.0004421686,0.0004757649,0.001797941,0.0001409463],"domain_scores_gemma":[0.9881285,0.00902312,0.0005253285,0.0008687112,0.001270676,0.0001836402],"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":[0.00001520609,0.00003150399,0.0002083148,0.0006910985,0.00008538979,0.00004221091,0.0001412291,0.008516769,0.0001844748,0.925532,0.003129874,0.0614218],"study_design_scores_gemma":[0.000009955276,0.00001453687,0.0002537011,0.0002167758,0.00003200241,0.0001092551,0.00006847387,0.01790512,0.0002461018,0.9426273,0.03848092,0.00003601619],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00453798,0.3587224,0.5897648,0.005552871,0.0009115765,0.0001799735,0.0004855153,0.0001960264,0.03964885],"genre_scores_gemma":[0.1092237,0.3246074,0.5510667,0.002044034,0.003547396,0.0004427459,0.0006573138,0.000109812,0.008300983],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01200635,"threshold_uncertainty_score":0.04035628,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4304698333","doi":"10.1007/s10462-022-10265-7","title":"Deep learning, graph-based text representation and classification: a survey, perspectives and challenges","year":2022,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Topic Modeling","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Artificial intelligence; Deep learning; Feature engineering; Recurrent neural network; Feature learning; Graph; Artificial neural network; Representation (politics); Machine learning; Natural language processing; Theoretical computer science","authors":[{"name":"Phu Pham","is_ca":false},{"name":"Loan T. T. Nguyen","is_ca":false},{"name":"Witold Pedrycz","is_ca":true},{"name":"Bay Vo","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2241822518724065,"gpt":0.3617897368252568,"spread":0.1376074849528502,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001868991,0.000970932,0.001923668,0.003571973,0.0003096634,0.002360596,0.002000944,0.00106614,0.001885044],"category_scores_gemma":[0.005013088,0.0003466739,0.0007629781,0.005667462,0.0006689742,0.005182645,0.001078061,0.001908405,0.001533872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001121925,"about_ca_system_score_gemma":0.002038116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006163466,"about_ca_topic_score_gemma":0.006127983,"domain_scores_codex":[0.9992576,0.0002070136,0.00006697037,0.0001718932,0.0002514961,0.00004509326],"domain_scores_gemma":[0.9969497,0.001999097,0.0001877502,0.0001882544,0.00057074,0.0001044802],"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":[0.0000574596,0.0001533633,0.001587162,0.002136995,0.00008586649,0.00001708756,0.00008679138,0.008438777,0.001089969,0.01441074,0.02733208,0.9446037],"study_design_scores_gemma":[0.00005204492,0.0004120107,0.007033188,0.002618586,0.0003608522,0.0004851271,0.0007035949,0.48309,0.005590341,0.2175808,0.2819315,0.0001419239],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01577996,0.5401441,0.4124046,0.01766042,0.001067827,0.0001921856,0.003018924,0.001894893,0.007837052],"genre_scores_gemma":[0.1374303,0.6576266,0.182899,0.00263705,0.004311638,0.0003094033,0.007835978,0.0002820894,0.006667778],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006163466,"threshold_uncertainty_score":0.01225519,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2793816938","doi":"10.1007/s10462-018-9616-4","title":"A comprehensive investigation into the performance, robustness, scalability and convergence of chaos-enhanced evolutionary algorithms with boundary constraints","year":2018,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Chaotic; Robustness (evolution); Computer science; Scalability; Evolutionary algorithm; Algorithm; Mathematical optimization; Convergence (economics); Heuristic; Mathematics; Machine learning; Artificial intelligence","authors":[{"name":"Ahmad Mozaffari","is_ca":true},{"name":"Mahdi Emami","is_ca":false},{"name":"Alireza Fathi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05226224469424341,"gpt":0.3155321147267129,"spread":0.2632698700324695,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001383575,0.0005396715,0.001019391,0.0007790105,0.0002373178,0.001080294,0.0007835855,0.0008024505,0.0006340466],"category_scores_gemma":[0.005207285,0.0002480439,0.0006083971,0.00119072,0.0003697327,0.001682667,0.0005638871,0.0008999303,0.0001418457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003381108,"about_ca_system_score_gemma":0.0005220874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004891218,"about_ca_topic_score_gemma":0.0003759438,"domain_scores_codex":[0.9995735,0.0001090716,0.00003123184,0.00005574978,0.0002009759,0.00002946168],"domain_scores_gemma":[0.9984916,0.001068157,0.0001019602,0.00006982756,0.0002467957,0.00002161229],"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":[0.0001593361,0.000147778,0.002474342,0.003250993,0.0003376247,0.0002000623,0.0001556853,0.2691856,0.01938237,0.1032939,0.002640227,0.5987721],"study_design_scores_gemma":[0.00004817635,0.0007247706,0.003377445,0.0009850593,0.0003865145,0.0006690534,0.0001197023,0.8783483,0.01935289,0.04261665,0.05329101,0.00008039754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09435219,0.3648917,0.5031517,0.001739844,0.0004800417,0.0001437423,0.00008056127,0.000204944,0.03495534],"genre_scores_gemma":[0.6241591,0.2183034,0.1506976,0.0004854138,0.0005734702,0.0001606175,0.0001875936,0.0001139272,0.005318865],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001383575,"threshold_uncertainty_score":0.007317126,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4320490631","doi":"10.1007/s10462-023-10395-6","title":"Games of GANs: game-theoretical models for generative adversarial networks","year":2023,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University; University of Alberta","funders":"","keywords":"Computer science; Generative grammar; Adversarial system; Artificial intelligence; Game theory; Nash equilibrium; Field (mathematics); Machine learning; Zero-sum game; Theoretical computer science; Mathematical economics; Mathematics","authors":[{"name":"Monireh Mohebbi Moghaddam","is_ca":false},{"name":"Bahar Boroomand","is_ca":true},{"name":"Mohammad Hossein Jalali","is_ca":false},{"name":"Arman Zareian","is_ca":false},{"name":"Alireza Daeijavad","is_ca":true},{"name":"Mohammad Hossein Manshaei","is_ca":false},{"name":"Marwan Krunz","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06814399205353684,"gpt":0.3202164580862003,"spread":0.2520724660326634,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002066404,0.001272625,0.001316273,0.0007809191,0.000298937,0.002092718,0.002147862,0.00206305,0.002959685],"category_scores_gemma":[0.00475478,0.0007561424,0.0008894666,0.0009599221,0.00257697,0.00311059,0.001311951,0.003583037,0.0005112776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001773576,"about_ca_system_score_gemma":0.0008769497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003106789,"about_ca_topic_score_gemma":0.002794476,"domain_scores_codex":[0.9992706,0.0003961273,0.00002615274,0.00009786997,0.0001596096,0.00004958669],"domain_scores_gemma":[0.9967812,0.002722858,0.0001281715,0.0001115114,0.0001836861,0.00007247843],"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":[0.00001833621,0.00002425213,0.0001797911,0.0002138543,0.00005970159,0.00003226328,0.00005603244,0.2582051,0.0003194441,0.711601,0.003632242,0.02565806],"study_design_scores_gemma":[0.00001008497,0.00002186817,0.0001108034,0.0001028952,0.00001415808,0.00004820976,0.00001666821,0.5339853,0.0001702636,0.4567192,0.008782804,0.00001773181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005138134,0.02642918,0.9431757,0.003595866,0.0003609179,0.00006411969,0.0001813388,0.0001637032,0.02089112],"genre_scores_gemma":[0.6680921,0.07716064,0.2268122,0.002161923,0.001945215,0.0004907208,0.0004613432,0.0002361399,0.02263971],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003106789,"threshold_uncertainty_score":0.01286829,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4392401953","doi":"10.1007/s10462-024-10724-3","title":"Resampling strategies for imbalanced regression: a survey and empirical analysis","year":2024,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco; Conselho Nacional de Desenvolvimento Científico e Tecnológico; École de technologie supérieure","keywords":"Resampling; Computer science; Regression; Regression analysis; Statistics; Machine learning; Artificial intelligence; Econometrics; Mathematics","authors":[{"name":"Juscimara Gomes Avelino","is_ca":false},{"name":"George D. C. Cavalcanti","is_ca":false},{"name":"Rafael M. O. Cruz","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2207092403690384,"gpt":0.4567738095203853,"spread":0.2360645691513469,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02832218,0.002565107,0.004071651,0.005348992,0.001011949,0.003705832,0.003971147,0.002179411,0.00212807],"category_scores_gemma":[0.07862383,0.0009054811,0.002266175,0.007843281,0.002136511,0.005145251,0.001994421,0.003396621,0.001795499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001661487,"about_ca_system_score_gemma":0.001748871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003408868,"about_ca_topic_score_gemma":0.001639419,"domain_scores_codex":[0.9855377,0.006917465,0.001090611,0.002380285,0.003731863,0.0003419746],"domain_scores_gemma":[0.9372021,0.05038884,0.002570084,0.004163463,0.005284733,0.0003907675],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003050379,0.0002846557,0.01064401,0.002291883,0.0006256482,0.00008467414,0.000310031,0.07773474,0.0009048624,0.03924732,0.01288784,0.8546793],"study_design_scores_gemma":[0.0001220992,0.0006398092,0.01109455,0.002856685,0.0006383603,0.0006731284,0.0006929279,0.7844228,0.004999368,0.1237231,0.06995545,0.0001818165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01454347,0.1972391,0.7762958,0.003593297,0.0009131249,0.0002810587,0.0004136283,0.001059604,0.005660912],"genre_scores_gemma":[0.3940245,0.1753898,0.4144164,0.002152998,0.005952294,0.0006734363,0.002501214,0.001085837,0.003803491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9716778,"threshold_uncertainty_score":0.1497838,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1583121608","doi":"10.1023/a:1022188514489","title":"Maximum Consistency of Incomplete Data via Non-Invasive Imputation","year":2003,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":43,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Brock University","funders":"","keywords":"Computer science; Imputation (statistics); Consistency (knowledge bases); Data mining; Algorithm; Artificial intelligence; Missing data; Machine learning","authors":[{"name":"Günther Gediga","is_ca":false},{"name":"Ivo Düntsch","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.3887878940414836,"gpt":0.4890945747855664,"spread":0.1003066807440829,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06157913,0.001677352,0.00659689,0.00295902,0.001223662,0.005202135,0.008828257,0.003909121,0.001751413],"category_scores_gemma":[0.2193518,0.002579184,0.004513952,0.004845796,0.004714244,0.007922324,0.006287714,0.005943368,0.0006096662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001196743,"about_ca_system_score_gemma":0.003180472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001655107,"about_ca_topic_score_gemma":0.00152434,"domain_scores_codex":[0.9446081,0.04300437,0.002429631,0.00526908,0.003976675,0.000712251],"domain_scores_gemma":[0.7410206,0.2214503,0.008070733,0.02263611,0.006147859,0.0006744041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007495286,0.0001956053,0.009369435,0.002086562,0.003160765,0.0005872582,0.0008579639,0.3808407,0.001205775,0.3639002,0.005731417,0.2313147],"study_design_scores_gemma":[0.0001174487,0.00008090722,0.001563324,0.0002561323,0.0002564587,0.0002294614,0.00005672179,0.4945493,0.001119508,0.4992562,0.002443957,0.00007063081],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0021257,0.0004926777,0.9966247,0.0002510728,0.00003701778,0.00002788474,0.0001061274,0.0001025694,0.0002323621],"genre_scores_gemma":[0.1625151,0.00164023,0.8316975,0.000397782,0.0004367783,0.0004861601,0.001249956,0.0003037116,0.001272889],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06157913,"threshold_uncertainty_score":0.3256654,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4402692326","doi":"10.1007/s10462-024-10932-x","title":"Review of medical image processing using quantum-enabled algorithms","year":2024,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":42,"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":"Jilin Scientific and Technological Development Program; Department of Science and Technology of Jilin Province","keywords":"Computer science; Image processing; Algorithm; Quantum; Image (mathematics); Computer vision; Artificial intelligence","authors":[{"name":"Fei Yan","is_ca":false},{"name":"Hesheng Huang","is_ca":false},{"name":"Witold Pedrycz","is_ca":true},{"name":"Kaoru Hirota","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06344783206658251,"gpt":0.375144445932643,"spread":0.3116966138660605,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006309093,0.0006643153,0.0008297251,0.002107418,0.0003760626,0.000997876,0.0009098549,0.0009920492,0.004023988],"category_scores_gemma":[0.001286349,0.0004391288,0.0006302215,0.002301233,0.0006717668,0.001558869,0.000580436,0.001325099,0.001912167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006620011,"about_ca_system_score_gemma":0.001041867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009505076,"about_ca_topic_score_gemma":0.0009661636,"domain_scores_codex":[0.9997111,0.0000587284,0.00003652432,0.00004624898,0.0001282506,0.00001917401],"domain_scores_gemma":[0.9993007,0.0003670963,0.00004735972,0.00003416418,0.0002283403,0.00002218855],"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":[0.00005917737,0.00007462358,0.0002585175,0.01631711,0.0001530884,0.0002116089,0.0001290343,0.004524088,0.005623571,0.06321467,0.05472047,0.854714],"study_design_scores_gemma":[0.000009394943,0.0001103695,0.0005504619,0.00219514,0.000077422,0.001077168,0.0000408327,0.003260694,0.002650061,0.02245474,0.9675252,0.00004845111],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005583119,0.9743726,0.01432768,0.001445589,0.0007646285,0.00002504651,0.00005745459,0.00006105647,0.008387712],"genre_scores_gemma":[0.005062111,0.9820031,0.00888171,0.0006569088,0.001065632,0.00003009895,0.00007848213,0.00002193779,0.002200005],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004023988,"threshold_uncertainty_score":0.01346159,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4412732533","doi":"10.1007/s10462-025-11291-x","title":"Cuckoo catfish optimizer: a new meta-heuristic optimization algorithm","year":2025,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministry of Education and Child Care","funders":"","keywords":"Meta heuristic; Computer science; Cuckoo; Cuckoo search; Catfish; Heuristic; Optimization algorithm; Mathematical optimization; Algorithm; Metaheuristic; Artificial intelligence; Fish <Actinopterygii>; Mathematics; Fishery; Biology; Zoology; Particle swarm optimization","authors":[{"name":"Tianlei Wang","is_ca":false},{"name":"Shao-Wei Gu","is_ca":true},{"name":"Renju Liu","is_ca":false},{"name":"L. Chen","is_ca":false},{"name":"Zhu Wang","is_ca":false},{"name":"Zhiqiang Zeng","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1065480924543893,"gpt":0.3755850223123636,"spread":0.2690369298579743,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008902272,0.001309164,0.001020965,0.001141148,0.0004647822,0.0009687541,0.001623367,0.001412722,0.001743228],"category_scores_gemma":[0.001432047,0.0004571764,0.0008063245,0.001032231,0.0005799908,0.0005326259,0.00071976,0.000725275,0.0002936913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001004479,"about_ca_system_score_gemma":0.002049255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01394217,"about_ca_topic_score_gemma":0.007880677,"domain_scores_codex":[0.9995321,0.000155297,0.00002942171,0.00007649642,0.0001644536,0.00004220483],"domain_scores_gemma":[0.9996331,0.0001385441,0.0000481029,0.00003254259,0.000123728,0.00002398391],"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":[0.00004938167,0.00002727955,0.0007252293,0.0001169686,0.00007699024,0.00005892112,0.00003210992,0.9607065,0.001500821,0.004120409,0.001307749,0.03127754],"study_design_scores_gemma":[0.0000191512,0.00002192081,0.00007480828,0.000009060478,0.0000100681,0.00001341121,0.000004068363,0.9984085,0.0002378191,0.000370286,0.0008262745,0.000004617275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07281812,0.002967903,0.9067523,0.0005751491,0.0002717984,0.0003755707,0.000204734,0.001245288,0.01478902],"genre_scores_gemma":[0.6468357,0.0009985259,0.3440956,0.0003292477,0.0001003522,0.0008915182,0.0004788408,0.0001879573,0.00608214],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01394217,"threshold_uncertainty_score":0.02772206,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391654576","doi":"10.1007/s10462-023-10670-6","title":"Learning team-based navigation: a review of deep reinforcement learning techniques for multi-agent pathfinding","year":2024,"lang":"en","type":"review","venue":"Artificial Intelligence Review","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; University of Victoria","funders":"","keywords":"Pathfinding; Reinforcement learning; Computer science; Artificial intelligence; Human–computer interaction; Shortest path problem","authors":[{"name":"Jaehoon Chung","is_ca":true},{"name":"Jamil Fayyad","is_ca":true},{"name":"Younes Al Younes","is_ca":true},{"name":"Homayoun Najjaran","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1632568166785285,"gpt":0.4231300236244041,"spread":0.2598732069458756,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001044372,0.0009919003,0.001079766,0.001305964,0.000232207,0.00103214,0.001474528,0.001031392,0.002419524],"category_scores_gemma":[0.002658497,0.0004638276,0.0008004263,0.002127844,0.0004575734,0.001536352,0.0007523864,0.00132912,0.001174542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007580474,"about_ca_system_score_gemma":0.001434593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00312733,"about_ca_topic_score_gemma":0.002732524,"domain_scores_codex":[0.9996959,0.00006315473,0.00004103714,0.00007954254,0.00009768637,0.00002273707],"domain_scores_gemma":[0.99884,0.0007416779,0.00007889546,0.00003854431,0.0002640811,0.00003676836],"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":[0.00003803272,0.0000836472,0.0003728748,0.008756222,0.0001749396,0.00004252611,0.00005980186,0.01388654,0.0005581117,0.008963571,0.00866535,0.9583984],"study_design_scores_gemma":[0.0000669602,0.0007303639,0.002965179,0.01478467,0.0008657484,0.001047875,0.0002441672,0.07280808,0.004017871,0.03893729,0.8633473,0.0001844562],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0009594826,0.9678753,0.02662078,0.0007213166,0.0003394502,0.00003167081,0.00005145015,0.00009555614,0.003305087],"genre_scores_gemma":[0.01422397,0.9684082,0.0152916,0.0002865631,0.000362225,0.00005282052,0.0001200292,0.00002923481,0.001225345],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00312733,"threshold_uncertainty_score":0.008094132,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2085103703","doi":"10.1007/s10462-010-9180-z","title":"Data mining applications in hydrocarbon exploration","year":2010,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Hydrocarbon exploration; Computer science; Data exploration; Data mining; Geology; Visualization; Geomorphology","authors":[{"name":"Muhammad Ashraf Shaheen","is_ca":false},{"name":"Muhammad Shahbaz","is_ca":false},{"name":"Zahoor Ur Rehman","is_ca":false},{"name":"Aziz Guergachi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1652530464656564,"gpt":0.356858352819086,"spread":0.1916053063534296,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001627141,0.0005770689,0.0009194775,0.003551517,0.0003641682,0.001764254,0.0008434465,0.001004116,0.002956368],"category_scores_gemma":[0.006847918,0.0002218265,0.0006026243,0.008596768,0.0006065201,0.002086097,0.0005833388,0.001386187,0.001262967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006420277,"about_ca_system_score_gemma":0.001137458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001758305,"about_ca_topic_score_gemma":0.002168117,"domain_scores_codex":[0.9993975,0.0001360615,0.0001023864,0.00008199146,0.0002619226,0.00002025718],"domain_scores_gemma":[0.9942186,0.003631241,0.00039828,0.0002196387,0.001428048,0.0001042451],"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":[0.00004546877,0.00008583454,0.004242151,0.004394161,0.0001049067,0.0002197708,0.000131783,0.004845758,0.001417857,0.02642667,0.03772176,0.9203639],"study_design_scores_gemma":[0.00002491203,0.0001484162,0.009434326,0.004044244,0.0002295504,0.001622169,0.0005044069,0.02979817,0.004072402,0.1171117,0.8329354,0.00007435317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.00674618,0.8794954,0.07309416,0.01863507,0.003143208,0.00008043824,0.0006911805,0.0002893437,0.01782495],"genre_scores_gemma":[0.04834906,0.8814121,0.05558697,0.002743781,0.004095023,0.00008190121,0.0006890203,0.00004772806,0.006994474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003551517,"threshold_uncertainty_score":0.00989002,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3091336037","doi":"10.1007/s10462-020-09915-5","title":"Modelling daily soil temperature by hydro-meteorological data at different depths using a novel data-intelligence model: deep echo state network model","year":2020,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Evapotranspiration; Mean squared error; Environmental science; Robustness (evolution); Echo state network; Computer science; Machine learning; Hydrology (agriculture); Artificial neural network; Recurrent neural network; Statistics; Mathematics; Geology","authors":[{"name":"Meysam Alizamir","is_ca":false},{"name":"Sungwon Kim","is_ca":false},{"name":"Mohammad Zounemat‐Kermani","is_ca":false},{"name":"Salim Heddam","is_ca":false},{"name":"Amin Hasanalipour Shahrabadi","is_ca":false},{"name":"Bahram Gharabaghi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2447111992971406,"gpt":0.3392468016239568,"spread":0.09453560232681615,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002993848,0.0005397635,0.0004595181,0.0002407602,0.0001705957,0.0007077749,0.0009611382,0.0008352876,0.0007318422],"category_scores_gemma":[0.001055994,0.0004300976,0.0005144709,0.0005735751,0.0003720763,0.001532821,0.0004096409,0.00118818,0.0001663611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006240074,"about_ca_system_score_gemma":0.0008342329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01677347,"about_ca_topic_score_gemma":0.0181212,"domain_scores_codex":[0.9999175,0.00001637568,0.000006221154,0.00003265719,0.00001634434,0.00001096005],"domain_scores_gemma":[0.9996948,0.0001618766,0.00004053231,0.00001897245,0.00006716396,0.00001667312],"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":[0.00001079104,0.00001295124,0.0008048818,0.00001888359,0.00002475806,0.0000110203,0.00001008304,0.9917326,0.0005780754,0.001573601,0.0001713612,0.005050969],"study_design_scores_gemma":[0.000001215442,0.000002391469,0.0001221069,0.000001135025,0.000002818666,0.00000190532,0.000001018775,0.9991122,0.0001037366,0.0005908381,0.0000582434,0.000002296824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1833093,0.0008889489,0.8092552,0.0009606329,0.0002245094,0.00003050506,0.0008999101,0.0004944364,0.003936505],"genre_scores_gemma":[0.9675569,0.0007408464,0.0270701,0.00009147547,0.00004772163,0.00005494601,0.0004727271,0.00004671406,0.003918506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01677347,"threshold_uncertainty_score":0.03335166,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4383721094","doi":"10.1007/s10462-023-10542-z","title":"AFOX: a new adaptive nature-inspired optimization algorithm","year":2023,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Metaheuristic; Meta-optimization; Computer science; Mathematical optimization; Multi-swarm optimization; Derivative-free optimization; Particle swarm optimization; Imperialist competitive algorithm; Convergence (economics); Optimization problem; Algorithm; Local optimum; Parallel metaheuristic; Benchmark (surveying); Continuous optimization; Engineering optimization; Optimization algorithm; Mathematics","authors":[{"name":"Hosam ALRahhal","is_ca":true},{"name":"Razan Jamous","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09369246705703665,"gpt":0.3716525507103665,"spread":0.2779600836533298,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006506103,0.0008583549,0.0008822872,0.0008747469,0.000430918,0.0009189502,0.001563833,0.001468044,0.002956182],"category_scores_gemma":[0.001164098,0.0002646591,0.0008292217,0.001032433,0.0004236668,0.0009917893,0.000959891,0.001354119,0.0006732973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003593252,"about_ca_system_score_gemma":0.0006993788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001488402,"about_ca_topic_score_gemma":0.001350962,"domain_scores_codex":[0.9997301,0.00006365916,0.00001261092,0.00004317375,0.0001258682,0.0000246209],"domain_scores_gemma":[0.9997788,0.0001057745,0.0000224313,0.00001838186,0.00005817615,0.00001650696],"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":[0.0001593258,0.0001085327,0.0008582437,0.0003680834,0.00017175,0.000112524,0.00007033026,0.3547045,0.005418526,0.04130326,0.01215211,0.5845729],"study_design_scores_gemma":[0.00005910962,0.0001406952,0.0002068066,0.00005296012,0.0000493458,0.0001408618,0.00001231583,0.9641938,0.00113904,0.01315013,0.02083745,0.00001766195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005567707,0.003471654,0.9809179,0.0003349856,0.0006172035,0.00007824176,0.00006817596,0.0005954065,0.008348702],"genre_scores_gemma":[0.1166445,0.003541356,0.8677446,0.0009218263,0.0004700263,0.0004078039,0.0002479751,0.0002772886,0.009744718],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002956182,"threshold_uncertainty_score":0.009889424,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4310193697","doi":"10.1007/s10462-022-10339-6","title":"A novel prospect-theory-based three-way decision methodology in multi-scale information systems","year":2022,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Weighting; Computer science; Prospect theory; Function (biology); Bellman equation; Object (grammar); Scope (computer science); Scale (ratio); Artificial intelligence; Point (geometry); Value (mathematics); Data mining; Machine learning; Mathematical optimization; Mathematics","authors":[{"name":"Jiang Deng","is_ca":false},{"name":"Jianming Zhan","is_ca":false},{"name":"Weiping Ding","is_ca":false},{"name":"Пэйдэ Лю","is_ca":false},{"name":"Witold Pedrycz","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2334702006659428,"gpt":0.3769548509421719,"spread":0.1434846502762291,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007096271,0.001203142,0.002580775,0.002935227,0.001008638,0.004958169,0.002935593,0.002189107,0.003079729],"category_scores_gemma":[0.008505941,0.0007044845,0.003089526,0.003360779,0.00235108,0.006714766,0.002808779,0.002387658,0.0003929216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001957637,"about_ca_system_score_gemma":0.002692099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00147562,"about_ca_topic_score_gemma":0.001250666,"domain_scores_codex":[0.9937208,0.003736044,0.0003325303,0.0005790959,0.001422113,0.00020943],"domain_scores_gemma":[0.99523,0.003482106,0.0002799065,0.0002197892,0.0006074816,0.0001808969],"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":[0.00009105192,0.0001424516,0.001141393,0.0005743879,0.0003410009,0.0002059148,0.0003119731,0.2257733,0.0009934882,0.6550399,0.001801422,0.1135839],"study_design_scores_gemma":[0.00002237999,0.0001116227,0.0003388346,0.0000605399,0.00006322348,0.00009292239,0.00006993764,0.6242634,0.000295533,0.3721209,0.002507523,0.00005314789],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003481171,0.0009412002,0.9923018,0.0004265792,0.00007267675,0.00006475567,0.00003418834,0.00004551423,0.002632122],"genre_scores_gemma":[0.3799053,0.002517814,0.6140285,0.0002143049,0.0002843365,0.0003862878,0.0001141241,0.00004491188,0.002504483],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007096271,"threshold_uncertainty_score":0.03752917,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403291952","doi":"10.1007/s10462-024-10978-x","title":"A systematic review of computer vision-based personal protective equipment compliance in industry practice: advancements, challenges and future directions","year":2024,"lang":"en","type":"review","venue":"Artificial Intelligence Review","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ontario Tech University","funders":"Science Fund of the Republic of Serbia","keywords":"Compliance (psychology); Personal protective equipment; Computer science; Risk analysis (engineering); Medicine; Psychology; Coronavirus disease 2019 (COVID-19); Pathology","authors":[{"name":"Arso M. Vukićević","is_ca":false},{"name":"Miloš Petrović","is_ca":false},{"name":"Pavle Milošević","is_ca":false},{"name":"Aleksandar Peulić","is_ca":false},{"name":"Kosta Jovanović","is_ca":false},{"name":"Aleksandar Novaković","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1188568554774351,"gpt":0.3976492832622018,"spread":0.2787924277847666,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006668574,0.001137611,0.003851673,0.01029352,0.0004975093,0.002335893,0.001927178,0.001700691,0.00463207],"category_scores_gemma":[0.02795969,0.0007214191,0.003964482,0.0093058,0.0007513432,0.002374445,0.001253032,0.00112129,0.0006701978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001961107,"about_ca_system_score_gemma":0.01070217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006485215,"about_ca_topic_score_gemma":0.01547357,"domain_scores_codex":[0.9955137,0.001321488,0.001469016,0.0004399958,0.001129576,0.0001261392],"domain_scores_gemma":[0.9776899,0.01615783,0.002523564,0.00040462,0.003026648,0.0001974084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00009516696,0.0000386241,0.0006095506,0.6735208,0.002032949,0.0001079962,0.0002437185,0.0002216284,0.0002769032,0.001178787,0.006882222,0.3147917],"study_design_scores_gemma":[0.00006346223,0.0002414803,0.004545632,0.8060333,0.01354379,0.0006547471,0.0004463663,0.0001854866,0.0003560951,0.001145283,0.1727258,0.00005863507],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002484724,0.9987722,0.000201239,0.0002395596,0.00009641669,0.00004834151,0.0001122446,0.000005997514,0.0002756102],"genre_scores_gemma":[0.002569396,0.9964167,0.000511937,0.0002106521,0.0000491471,0.00006453,0.0001003752,0.00000350944,0.00007375581],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01029352,"threshold_uncertainty_score":0.03526717,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1582058909","doi":"10.1023/a:1015179704819","title":"User Interfaces and Help Systems: From Helplessness to Intelligent Assistance","year":2002,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":34,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Université du Québec à Trois-Rivières","funders":"","keywords":"Computer science","authors":[{"name":"Sylvain Delisle","is_ca":true},{"name":"Bernard Moulin","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1728828165241004,"gpt":0.40665667862063,"spread":0.2337738620965297,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003133936,0.0007063067,0.001460976,0.003248192,0.0007521208,0.004044502,0.001547756,0.00388458,0.003145634],"category_scores_gemma":[0.007229115,0.000467265,0.0004734771,0.00360852,0.00442276,0.00478336,0.001279287,0.003510808,0.001242953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001712765,"about_ca_system_score_gemma":0.002384473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002744932,"about_ca_topic_score_gemma":0.003033856,"domain_scores_codex":[0.9981765,0.000608197,0.0001527234,0.0002160772,0.0007470439,0.00009955695],"domain_scores_gemma":[0.9880971,0.009260057,0.0003917337,0.0002338666,0.001782909,0.0002344065],"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":[0.0001036964,0.0001964065,0.001300344,0.01050681,0.0001309483,0.0001766296,0.0009956729,0.0007199763,0.0009719772,0.06040474,0.03431742,0.8901754],"study_design_scores_gemma":[0.00005265805,0.0002618854,0.00593924,0.007431406,0.0001674772,0.002203864,0.001219898,0.0008341421,0.0007270995,0.05451648,0.926557,0.00008887186],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004164714,0.9912391,0.001228364,0.002597011,0.0002792375,0.000007015579,0.000008374389,0.00001222539,0.00421219],"genre_scores_gemma":[0.01322803,0.9784226,0.001843092,0.003100296,0.001464023,0.00003531132,0.00003465857,0.00001282625,0.00185914],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004044502,"threshold_uncertainty_score":0.01657403,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3017300133","doi":"10.1007/s10462-020-09835-4","title":"Deep learning for face image synthesis and semantic manipulations: a review and future perspectives","year":2020,"lang":"en","type":"review","venue":"Artificial Intelligence Review","topic":"Face recognition and analysis","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Face (sociological concept); Deep learning; Artificial intelligence; Range (aeronautics); Image (mathematics); Perception; Psychology; Linguistics","authors":[{"name":"Mahla Abdolahnejad","is_ca":true},{"name":"Peter Liu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08388578943577576,"gpt":0.3615072453684832,"spread":0.2776214559327075,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008121549,0.0008630374,0.001251306,0.00112897,0.0001650842,0.0009661134,0.001004813,0.001006098,0.003669398],"category_scores_gemma":[0.001306822,0.0003003952,0.0006357554,0.001347097,0.0005025506,0.001533011,0.0007052497,0.001266878,0.001447043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004681446,"about_ca_system_score_gemma":0.00125005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002000453,"about_ca_topic_score_gemma":0.003245536,"domain_scores_codex":[0.9998531,0.0000248523,0.00001749422,0.00004205989,0.00004649065,0.00001596521],"domain_scores_gemma":[0.9995535,0.0002599832,0.00004123267,0.00001414017,0.0001070731,0.00002405455],"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":[0.00007131379,0.00007156048,0.0002004429,0.007676858,0.0001206519,0.00006183725,0.000019291,0.0007551698,0.001258181,0.002575892,0.01393447,0.9732543],"study_design_scores_gemma":[0.00008815397,0.0004951542,0.002201006,0.008475689,0.0008595891,0.001451492,0.000106857,0.003782524,0.004039503,0.01285424,0.9655386,0.0001072875],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002721064,0.9969764,0.001500791,0.0003608752,0.0001480029,0.000006673084,0.00003392727,0.00001827598,0.0006829922],"genre_scores_gemma":[0.002147007,0.9949129,0.001669298,0.0003745127,0.0002526459,0.00001219563,0.000060955,0.000005328983,0.0005651336],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003669398,"threshold_uncertainty_score":0.0122754,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391953812","doi":"10.1007/s10462-024-10703-8","title":"Fashion intelligence in the Metaverse: promise and future prospects","year":2024,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Fashion and Cultural Textiles","field":"Arts and Humanities","cited_by":28,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Metaverse; Extant taxon; Computer science; Possible world; Data science; Virtual reality; Human–computer interaction; Epistemology; Philosophy","authors":[{"name":"Xiangyu Mu","is_ca":false},{"name":"Haijun Zhang","is_ca":false},{"name":"Jianyang Shi","is_ca":false},{"name":"Jie Hou","is_ca":false},{"name":"Jianghong Ma","is_ca":false},{"name":"Yimin Yang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08534012757455763,"gpt":0.3168193937447195,"spread":0.2314792661701618,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002512541,0.0003552602,0.0005228088,0.002477029,0.0008400201,0.008720852,0.001008943,0.002347418,0.01077648],"category_scores_gemma":[0.002172989,0.0001593948,0.0004906253,0.003146555,0.002721925,0.008674071,0.001961023,0.002524829,0.002361834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001219143,"about_ca_system_score_gemma":0.001894644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007803871,"about_ca_topic_score_gemma":0.001657997,"domain_scores_codex":[0.9992272,0.0003838805,0.00004633039,0.00007309957,0.0001748406,0.00009463613],"domain_scores_gemma":[0.9977042,0.001288183,0.0001842745,0.0001336214,0.0004772902,0.0002124523],"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":[0.0000929886,0.0001529319,0.001324417,0.006962652,0.00006394208,0.0003585835,0.002795277,0.0004651922,0.0009522668,0.3836438,0.03206149,0.5711265],"study_design_scores_gemma":[0.000008131105,0.00008333648,0.001518197,0.007316181,0.00003561187,0.0005282435,0.003890274,0.0002789994,0.000359825,0.07155847,0.914399,0.00002371697],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005343509,0.8704405,0.002036111,0.02247673,0.00143919,0.00001690512,0.00003643866,0.00004802748,0.09816242],"genre_scores_gemma":[0.09084107,0.8850673,0.003657534,0.007781998,0.002256659,0.00004375872,0.0000798278,0.00003708226,0.01023474],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01077648,"threshold_uncertainty_score":0.03605098,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2082914115","doi":"10.1007/s10462-007-9055-0","title":"Just enough learning (of association rules): the TAR2 “Treatment” learner","year":2006,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"University of British Columbia; West Virginia University; National Aeronautics and Space Administration","keywords":"Pruning; Computer science; Set (abstract data type); Association rule learning; Contrast (vision); Class (philosophy); Association (psychology); Simple (philosophy); Machine learning; Domain (mathematical analysis); Artificial intelligence; Controller (irrigation); Psychology; Mathematics; Programming language","authors":[{"name":"Tim Menzies","is_ca":false},{"name":"Ying Hu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06132035250675822,"gpt":0.3248625355230162,"spread":0.263542183016258,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01041839,0.0009344465,0.001954646,0.00216344,0.0009096803,0.002676134,0.004301832,0.002663879,0.005278268],"category_scores_gemma":[0.03309882,0.0005306739,0.001468797,0.002756352,0.002502867,0.009644149,0.003657972,0.007118678,0.001826762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000775793,"about_ca_system_score_gemma":0.001903637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001015536,"about_ca_topic_score_gemma":0.0009976674,"domain_scores_codex":[0.9946944,0.002883986,0.0002905375,0.0007360134,0.001203513,0.000191484],"domain_scores_gemma":[0.9821798,0.01233424,0.0004396352,0.002745947,0.001911565,0.00038881],"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":[0.0004388533,0.0001845336,0.002311574,0.0006561549,0.0002364668,0.0002058619,0.0002894985,0.02165219,0.0006503264,0.4362719,0.03633912,0.5007635],"study_design_scores_gemma":[0.00007753568,0.000155409,0.0003956061,0.0001531456,0.00007845586,0.0004547196,0.00009161622,0.2009043,0.001379795,0.7720352,0.02423817,0.00003599124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00676245,0.00946199,0.9652786,0.009360678,0.0007942133,0.00005764496,0.0002840969,0.0006040169,0.007396231],"genre_scores_gemma":[0.3304878,0.01454978,0.6193068,0.00758177,0.004553709,0.0004752247,0.001826064,0.0005995026,0.0206193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01041839,"threshold_uncertainty_score":0.05509835,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400895761","doi":"10.1007/s10462-024-10865-5","title":"A Comprehensive review of data-driven approaches for forecasting production from unconventional reservoirs: best practices and future directions","year":2024,"lang":"en","type":"review","venue":"Artificial Intelligence Review","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Computer science; Production (economics); Robustness (evolution); Mean absolute percentage error; Predictive modelling; Big data; Data mining; Machine learning; Econometrics; Artificial neural network; Mathematics","authors":[{"name":"Hamid Rahmanifard","is_ca":true},{"name":"Ian D. Gates","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5533894886058799,"gpt":0.4615328802120601,"spread":0.09185660839381976,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005700302,0.002794287,0.003135967,0.006468241,0.0004769428,0.003610849,0.004289984,0.00242715,0.001994526],"category_scores_gemma":[0.01437688,0.001452658,0.003904269,0.008297882,0.0007478309,0.004277207,0.001497874,0.003046285,0.001153621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001785141,"about_ca_system_score_gemma":0.003515066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01071275,"about_ca_topic_score_gemma":0.007014509,"domain_scores_codex":[0.9981914,0.0004704757,0.0003392218,0.0003703941,0.0005516182,0.00007677258],"domain_scores_gemma":[0.9858269,0.009766958,0.0009521894,0.0005455777,0.002697243,0.000211188],"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":[0.000102553,0.0001638251,0.003930074,0.03182833,0.001291975,0.0002061117,0.0002140126,0.0898274,0.001557889,0.01764618,0.02853571,0.8246959],"study_design_scores_gemma":[0.00006794486,0.0004131754,0.006741534,0.05030658,0.002031993,0.0005775643,0.0005107521,0.225634,0.004967817,0.0526505,0.6553553,0.0007428888],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001866478,0.9374332,0.05347761,0.002828447,0.0008530954,0.00009053287,0.001036476,0.0004911397,0.001923021],"genre_scores_gemma":[0.01464805,0.9414446,0.04038372,0.0006857163,0.0008682378,0.0001313211,0.001220505,0.000118128,0.0004995748],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01071275,"threshold_uncertainty_score":0.03014648,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2012862892","doi":"10.1007/s10462-004-2901-4","title":"Statistical, Evolutionary, and Neurocomputing Clustering Techniques: Cluster-Based vs Object-Based Approaches","year":2005,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Saint Mary's University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Regina","keywords":"Cluster analysis; Computer science; Artificial neural network; Set (abstract data type); Self-organizing map; Artificial intelligence; Hierarchical clustering; Data mining; Genetic algorithm; Object (grammar); Machine learning; Correlation clustering; Cluster (spacecraft); Pattern recognition (psychology)","authors":[{"name":"Pawan Lingras","is_ca":true},{"name":"Xiandong Huang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.102172629225864,"gpt":0.3537774618947218,"spread":0.2516048326688577,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002848232,0.0006854215,0.00182339,0.002977301,0.0005491352,0.002290635,0.001965806,0.001460451,0.001528455],"category_scores_gemma":[0.005706265,0.0002861073,0.0007798523,0.00797277,0.001477728,0.002189368,0.0005525129,0.001160807,0.0008768472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001199404,"about_ca_system_score_gemma":0.001347315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002963891,"about_ca_topic_score_gemma":0.004264153,"domain_scores_codex":[0.998187,0.0004036551,0.00008284261,0.0002140997,0.001057201,0.00005511113],"domain_scores_gemma":[0.9969761,0.00136074,0.0001865852,0.000140202,0.001274487,0.00006185254],"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":[0.0001288242,0.00009896179,0.002974082,0.002631469,0.0004071274,0.00007818748,0.0002229998,0.01818401,0.002929193,0.09921184,0.01074977,0.8623835],"study_design_scores_gemma":[0.0001348882,0.0006028212,0.0297987,0.002630365,0.001059237,0.002799141,0.001759609,0.1991888,0.01201882,0.3911268,0.3585074,0.000373332],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01365166,0.49575,0.4599132,0.005437603,0.00188704,0.0001319306,0.0001758896,0.0003763585,0.02267643],"genre_scores_gemma":[0.1801836,0.4110892,0.3934439,0.001829952,0.004105698,0.0002397194,0.0003520988,0.0001713918,0.008584448],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002977301,"threshold_uncertainty_score":0.01506311,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391576353","doi":"10.1007/s10462-023-10647-5","title":"Three-way decisions in generalized intuitionistic fuzzy environments: survey and challenges","year":2024,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"Division of Graduate Education; Centre Scientifique et Technique du Bâtiment; Natural Science Foundation of Chongqing; China Postdoctoral Science Foundation; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Management science; Flexibility (engineering); Fuzzy set; Strengths and weaknesses; Set (abstract data type); Fuzzy logic; Boosting (machine learning); Context (archaeology); Artificial intelligence; Operations research; Mathematics","authors":[{"name":"Juanjuan Ding","is_ca":false},{"name":"Chao Zhang","is_ca":false},{"name":"Deyu Li","is_ca":false},{"name":"Jianming Zhan","is_ca":false},{"name":"Wentao Li","is_ca":false},{"name":"Yiyu Yao","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5391893118409208,"gpt":0.4773155601423373,"spread":0.0618737516985835,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004495332,0.0008144586,0.001126596,0.002938937,0.001048108,0.00435698,0.001637866,0.001852905,0.002288246],"category_scores_gemma":[0.003925299,0.0005737058,0.001241804,0.004650095,0.002402349,0.005902417,0.001409005,0.002451077,0.0006011185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002236112,"about_ca_system_score_gemma":0.002776153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004807744,"about_ca_topic_score_gemma":0.003489244,"domain_scores_codex":[0.9979049,0.0007516363,0.0001714436,0.0002992859,0.0007318578,0.0001408958],"domain_scores_gemma":[0.9970257,0.002017304,0.0001916626,0.0001107305,0.0005484328,0.0001061683],"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":[0.00005777631,0.0001352435,0.002630895,0.00450558,0.0001029449,0.0003670702,0.001597744,0.02328037,0.0005089293,0.5143782,0.008562079,0.4438731],"study_design_scores_gemma":[0.00001953847,0.0001691679,0.003066106,0.003580144,0.0001082832,0.001129851,0.004177464,0.06864175,0.0008893138,0.6281621,0.2898346,0.0002216916],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01574308,0.7101784,0.2148971,0.01064457,0.0007726161,0.00009443399,0.0001569708,0.0001401351,0.04737268],"genre_scores_gemma":[0.2075412,0.7061561,0.07756151,0.001272913,0.001881497,0.00009436857,0.000226066,0.00003511443,0.005231284],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004807744,"threshold_uncertainty_score":0.02377391,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2890460364","doi":"10.1023/a:1006500224529","title":"The Berkeley UNIX Consultant Project","year":2000,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"RTDS Technologies (Canada)","funders":"","keywords":"Computer science; Unix; Programming language; Utterance; Natural language; Component (thermodynamics); Artificial intelligence; Knowledge representation and reasoning; Natural language processing; Human–computer interaction","authors":[{"name":"Robert Wilensky","is_ca":false},{"name":"David N. Chin","is_ca":false},{"name":"Marc Luria","is_ca":true},{"name":"James Martin","is_ca":false},{"name":"James Mayfield","is_ca":false},{"name":"Dekai Wu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04995205201662418,"gpt":0.3552141471328705,"spread":0.3052620951162463,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002291495,0.0009046781,0.0007733882,0.003111538,0.001775349,0.004036281,0.001436422,0.002476882,0.367357],"category_scores_gemma":[0.00524267,0.0004457964,0.000446462,0.004472943,0.0008103946,0.003492487,0.0023281,0.002430658,0.2119471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002613521,"about_ca_system_score_gemma":0.006473449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01076166,"about_ca_topic_score_gemma":0.01264286,"domain_scores_codex":[0.9982805,0.000284864,0.00006277057,0.0002779156,0.0008010266,0.0002929367],"domain_scores_gemma":[0.9952519,0.0005636436,0.0002437138,0.0006444346,0.001935413,0.001360866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005110688,0.0000172769,0.00009270902,0.0000713815,0.000002010789,0.00001705688,0.00001458076,0.00003057163,0.00008659572,0.008477912,0.9106826,0.08045621],"study_design_scores_gemma":[0.00001624845,0.000009970219,0.0003137015,0.00004883764,0.000002622089,0.00002859229,0.00002653935,0.00004101774,0.00009940745,0.001171556,0.9982386,0.000002912514],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001979772,0.03584377,0.00290174,0.06963056,0.02069307,0.0001147987,0.005299337,0.003415499,0.8601214],"genre_scores_gemma":[0.004289146,0.007626456,0.002074529,0.001942544,0.001188277,0.00003862234,0.002059558,0.0003502023,0.9804307],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.367357,"threshold_uncertainty_score":0.9023885,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2059768731","doi":"10.1023/b:aire.0000007179.60276.39","title":"Reasoning with Numeric and Symbolic Time Information","year":2003,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Constraint satisfaction problem; Qualitative reasoning; Tabu search; Constraint satisfaction; Constraint satisfaction dual problem; Metric (unit); Constraint (computer-aided design); Scheduling (production processes); Constraint programming; Theoretical computer science; Local consistency; Mathematical optimization; Artificial intelligence; Mathematics; Probabilistic logic","authors":[{"name":"Malek Mouhoub","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01452773223888117,"gpt":0.2480979524556574,"spread":0.2335702202167762,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003684917,0.0009886548,0.001530109,0.002949897,0.0005769518,0.00461108,0.003250736,0.001615867,0.003757601],"category_scores_gemma":[0.01384313,0.0007742093,0.0017704,0.0058932,0.003103554,0.01008656,0.001499986,0.002804111,0.0007557735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002347613,"about_ca_system_score_gemma":0.002477967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00664838,"about_ca_topic_score_gemma":0.008306778,"domain_scores_codex":[0.995912,0.0009397329,0.000420878,0.0004253561,0.00215811,0.0001440278],"domain_scores_gemma":[0.9906971,0.006919782,0.0003725243,0.0007822888,0.001111884,0.0001164443],"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":[0.0000682049,0.00006682519,0.001100574,0.001916367,0.0002613474,0.0001701952,0.0002100394,0.04489389,0.0008866963,0.6008498,0.01417314,0.335403],"study_design_scores_gemma":[0.00002398995,0.00002378724,0.0006221997,0.0003725539,0.00009867645,0.0003044673,0.0001566252,0.0984124,0.001091855,0.843994,0.05485684,0.00004268607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01047198,0.1246909,0.8090029,0.01108337,0.0007872094,0.00007958779,0.0006932902,0.0003996603,0.04279121],"genre_scores_gemma":[0.217985,0.1800691,0.5864354,0.001782198,0.002481401,0.000208518,0.002444761,0.0001647091,0.008428889],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00664838,"threshold_uncertainty_score":0.01948798,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4413358968","doi":"10.1007/s10462-025-11346-z","title":"Deep learning for intrusion detection in emerging technologies: a comprehensive survey and new perspectives","year":2025,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Defence Research and Development Canada; National Research Council Canada; Research and Productivity Council","funders":"National Research Council Canada","keywords":"Computer science; Intrusion detection system; Deep learning; Data science; Emerging technologies; Artificial intelligence","authors":[{"name":"Euclides Carlos Pinto Neto","is_ca":true},{"name":"Shahrear Iqbal","is_ca":true},{"name":"Scott Buffett","is_ca":true},{"name":"Madeena Sultana","is_ca":true},{"name":"Adrian Taylor","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06294716237207329,"gpt":0.335509420769786,"spread":0.2725622583977128,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002152346,0.001066901,0.001065701,0.003015131,0.000288887,0.002073439,0.001269904,0.001039162,0.001987194],"category_scores_gemma":[0.004194718,0.0005458024,0.0009568799,0.002862194,0.0005931287,0.003221049,0.001226902,0.00177976,0.0007303426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008154852,"about_ca_system_score_gemma":0.001182374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002694631,"about_ca_topic_score_gemma":0.001997548,"domain_scores_codex":[0.9989917,0.0002622981,0.0001219489,0.0001819697,0.0003760445,0.00006602722],"domain_scores_gemma":[0.9976145,0.001659031,0.0001307356,0.00009784596,0.0004373387,0.00006066981],"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":[0.00006021962,0.0001622386,0.004949879,0.005569405,0.0002651957,0.0001166843,0.0001980156,0.01511366,0.0009526643,0.01916218,0.01505944,0.9383904],"study_design_scores_gemma":[0.00005618301,0.0006781687,0.0108804,0.01272469,0.0008916324,0.001078921,0.0008783511,0.3062517,0.006707935,0.08865868,0.5709347,0.0002587264],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.008800037,0.9029997,0.07238048,0.005186786,0.0005180997,0.00007996974,0.0002910682,0.0003125793,0.00943119],"genre_scores_gemma":[0.08833987,0.877369,0.0283633,0.001243319,0.0009817911,0.00009844542,0.0005904986,0.00006582033,0.002948047],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003015131,"threshold_uncertainty_score":0.01138282,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2039521808","doi":"10.1007/s10462-011-9285-z","title":"Genetic optimized artificial immune system in spam detection: a review and a model","year":2011,"lang":"en","type":"review","venue":"Artificial Intelligence Review","topic":"Artificial Immune Systems Applications","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"New York Institute of Technology","funders":"","keywords":"Computer science; Artificial immune system; Artificial intelligence; The Internet; Artificial neural network; Genetic algorithm; Machine learning; Computer security; World Wide Web","authors":[{"name":"Raed Abu Zitar","is_ca":true},{"name":"Adel Hamdan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09789027701188328,"gpt":0.3246031597684292,"spread":0.2267128827565459,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004736621,0.000607719,0.001125681,0.00135832,0.0002068654,0.0008401269,0.0009300298,0.001006279,0.001146585],"category_scores_gemma":[0.0008094257,0.0002428433,0.0005450805,0.001669721,0.0003235407,0.0008297489,0.0003949911,0.0006073169,0.0005797289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004014556,"about_ca_system_score_gemma":0.0006885107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001019103,"about_ca_topic_score_gemma":0.001194422,"domain_scores_codex":[0.9997926,0.00003656104,0.00002742518,0.00005293208,0.00007179956,0.00001869495],"domain_scores_gemma":[0.9997434,0.0001274851,0.00003315753,0.000008563363,0.00007779365,0.000009606458],"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":[0.0000999954,0.0001872384,0.000689237,0.009722029,0.0001786924,0.0002305141,0.00004787283,0.004856235,0.005051342,0.005482422,0.01159321,0.9618612],"study_design_scores_gemma":[0.0001368203,0.001291697,0.00431361,0.005988906,0.00147167,0.005210238,0.0002118224,0.0295915,0.0231634,0.01653221,0.9118887,0.0001992621],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002018234,0.9878696,0.007001169,0.0003686951,0.0003056725,0.00001981999,0.00002866842,0.00003880162,0.0023494],"genre_scores_gemma":[0.01967082,0.96716,0.009846664,0.0005403528,0.0004889592,0.00003876485,0.00009033079,0.00001407227,0.002150053],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00135832,"threshold_uncertainty_score":0.003835738,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2180467047","doi":"10.1007/s10462-015-9447-5","title":"Exponential moving average based multiagent reinforcement learning algorithms","year":2015,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Adaptive Dynamic Programming Control","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Nash equilibrium; Computer science; Reinforcement learning; Algorithm; Convergence (economics); Q-learning; Weighted Majority Algorithm; Mathematical optimization; Artificial intelligence; Mathematics; Wake-sleep algorithm; Unsupervised learning; Generalization error","authors":[{"name":"Mostafa D. Awheda","is_ca":true},{"name":"Howard M. Schwartz","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0888835926429212,"gpt":0.3256896554819136,"spread":0.2368060628389924,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001475053,0.0007967117,0.001122087,0.0005754697,0.0002724277,0.0008476349,0.001920846,0.0009036099,0.002058991],"category_scores_gemma":[0.003549219,0.0002840502,0.0003919424,0.0007205952,0.0005467906,0.001153807,0.0008146957,0.001376671,0.0003743491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006077897,"about_ca_system_score_gemma":0.0005448267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00214475,"about_ca_topic_score_gemma":0.001733788,"domain_scores_codex":[0.9994926,0.0001822362,0.00003299732,0.00007486495,0.0001803567,0.00003683905],"domain_scores_gemma":[0.9984549,0.001039564,0.00009548625,0.00006650971,0.0003057483,0.00003774615],"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":[0.00005878008,0.0001044633,0.0004362051,0.0001543401,0.00008809959,0.00003109443,0.000036358,0.7085257,0.0004903006,0.03254167,0.002216151,0.2553168],"study_design_scores_gemma":[0.00001411389,0.00003548747,0.0001020659,0.00001815832,0.00001465821,0.0000225797,0.000004998727,0.9886931,0.0002846867,0.009048709,0.001754977,0.000006516101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008172801,0.005466222,0.978992,0.0003517083,0.0002119652,0.00003162206,0.00001766059,0.0002510456,0.006504895],"genre_scores_gemma":[0.6313337,0.009593002,0.3414608,0.0004852742,0.0004104115,0.0002697038,0.0001321929,0.0001442199,0.01617068],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00214475,"threshold_uncertainty_score":0.007800937,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4226322152","doi":"10.1007/s10462-022-10177-6","title":"A trilevel analysis of uncertainty measuresin partition-based granular computing","year":2022,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"National Natural Science Foundation of China","keywords":"Granular computing; Computer science; Partition (number theory); Categorization; Uncertainty analysis; Granular material; Measure (data warehouse); Data mining; Mathematics; Artificial intelligence; Rough set; Simulation; Engineering","authors":[{"name":"Jiye Liang","is_ca":false},{"name":"Yiyu Yao","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1090109207828318,"gpt":0.3307509835698736,"spread":0.2217400627870418,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002900079,0.0008859565,0.001886455,0.004637688,0.0007588088,0.00544757,0.001624086,0.001136644,0.002091042],"category_scores_gemma":[0.006875323,0.0005586242,0.001559506,0.006062658,0.001829382,0.005564584,0.002168157,0.002378913,0.0002832586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002427363,"about_ca_system_score_gemma":0.0009212707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00255752,"about_ca_topic_score_gemma":0.001750568,"domain_scores_codex":[0.9977627,0.0005899194,0.0001737991,0.0002452681,0.001064959,0.0001633235],"domain_scores_gemma":[0.9976775,0.001075066,0.0002611133,0.0002706607,0.0006156323,0.0001001015],"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":[0.0001178491,0.00007774769,0.002493076,0.0009524642,0.0003083173,0.0001598753,0.0004043385,0.08801244,0.002359676,0.69281,0.004561874,0.2077423],"study_design_scores_gemma":[0.00001508516,0.00008787832,0.003003916,0.0003697988,0.000139193,0.0001980098,0.0001767252,0.4232307,0.001095933,0.5594214,0.01219147,0.0000699238],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01709719,0.03680716,0.9367241,0.001876751,0.0003830352,0.00009140401,0.0002240461,0.0001349352,0.006661415],"genre_scores_gemma":[0.4848168,0.02871873,0.4810718,0.0004967047,0.001163912,0.0002026651,0.0004498445,0.00007621819,0.003003327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00544757,"threshold_uncertainty_score":0.01761186,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1543603119","doi":"10.1007/s10462-009-9139-0","title":"A unified framework for improving the accuracy of all holistic face identification algorithms","year":2009,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Computer science; Identification (biology); Benchmark (surveying); Face (sociological concept); Process (computing); Machine learning; Algorithm; Artificial intelligence; Baseline (sea); Stability (learning theory); Data mining","authors":[{"name":"Liang Chen","is_ca":true},{"name":"Naoyuki Tokuda","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1581932759200924,"gpt":0.4015026794538817,"spread":0.2433094035337893,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00361168,0.002175859,0.003087277,0.002176078,0.001056703,0.002747681,0.00338498,0.0017299,0.002910503],"category_scores_gemma":[0.006601376,0.0006132798,0.001653925,0.001745816,0.001002416,0.004194655,0.003326648,0.002467083,0.00238168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003001,"about_ca_system_score_gemma":0.002313824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003217322,"about_ca_topic_score_gemma":0.00513115,"domain_scores_codex":[0.9971884,0.0005442319,0.0001673704,0.0004739276,0.001435843,0.0001901798],"domain_scores_gemma":[0.997525,0.0004087247,0.0001186281,0.0006289688,0.001247003,0.00007152373],"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":[0.0001225877,0.0001790504,0.0009780889,0.0005157018,0.0002348282,0.00008491558,0.0001017875,0.04673439,0.03315586,0.06648535,0.009425186,0.8419823],"study_design_scores_gemma":[0.00003564361,0.0003912396,0.00196999,0.0001645468,0.0003184084,0.0005742776,0.00009953634,0.8719336,0.04020254,0.05752315,0.02665968,0.0001273379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.001767447,0.001791195,0.9938765,0.000155364,0.0001194862,0.00005343561,0.0000371131,0.0005857636,0.001613624],"genre_scores_gemma":[0.04051603,0.002280924,0.9537062,0.0002118094,0.0002464993,0.0001588365,0.0001932134,0.000159336,0.002527212],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.00361168,"threshold_uncertainty_score":0.01910067,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3007616576","doi":"10.1007/s10462-020-09861-2","title":"Deep learning for biomedical image reconstruction: a survey","year":2020,"lang":"en","type":"preprint","venue":"Artificial Intelligence Review","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"CIHR Skin Research Training Centre; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Nvidia","keywords":"Computer science; Software deployment; Modalities; Medical imaging; Deep learning; Iterative reconstruction; Artificial intelligence; Mobile device; Data acquisition; Latency (audio); Computer vision; Machine learning; Medical physics; Data science; Medicine","authors":[{"name":"Hanene Ben Yedder","is_ca":true},{"name":"Ben Cardoen","is_ca":true},{"name":"Ghassan Hamarneh","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1918295006104636,"gpt":0.4351116203323829,"spread":0.2432821197219192,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001460102,0.0009888111,0.001287681,0.001321794,0.0001970501,0.001391041,0.001467037,0.001280325,0.002739124],"category_scores_gemma":[0.002893585,0.0005556563,0.0007474963,0.002491602,0.0006170674,0.001764209,0.001179109,0.001577871,0.001461454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005571917,"about_ca_system_score_gemma":0.001178295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002848452,"about_ca_topic_score_gemma":0.002807701,"domain_scores_codex":[0.999606,0.00007897569,0.00004468016,0.00008715491,0.0001591106,0.00002418045],"domain_scores_gemma":[0.9987418,0.0007870934,0.00006213836,0.00009090073,0.0002747083,0.00004337978],"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":[0.00006535139,0.000123003,0.0007368366,0.003017087,0.0001112318,0.00004217854,0.00003135041,0.008814912,0.001366888,0.01010419,0.01174421,0.9638427],"study_design_scores_gemma":[0.00009874895,0.0006528557,0.004767,0.005726961,0.0005019365,0.001680659,0.0002206204,0.2449643,0.01602723,0.1051101,0.6200734,0.000176146],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004511505,0.8142625,0.1713797,0.002390813,0.0004618014,0.00005153484,0.0002790296,0.0002900407,0.006373172],"genre_scores_gemma":[0.02862336,0.8764403,0.08805895,0.0008254341,0.001024042,0.0000671391,0.0005493459,0.0001157373,0.0042957],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002848452,"threshold_uncertainty_score":0.00916332,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403775493","doi":"10.1007/s10462-024-10911-2","title":"$$p,q,r-$$Fractional fuzzy sets and their aggregation operators and applications","year":2024,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":12,"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; Fuzzy logic; Applied mathematics; Mathematics; Artificial intelligence","authors":[{"name":"Muhammad Gulistan","is_ca":true},{"name":"Ying Hongbin","is_ca":false},{"name":"Witold Pedrycz","is_ca":true},{"name":"Muhammad Rahim","is_ca":false},{"name":"Fazli Amin","is_ca":false},{"name":"Hamiden Abd El‐Wahed Khalifa","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2577387114819631,"gpt":0.4798106051713636,"spread":0.2220718936894004,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002481787,0.0007556356,0.0007329957,0.002068026,0.0008866341,0.002471148,0.0008472892,0.001092801,0.002561248],"category_scores_gemma":[0.004366128,0.0002811144,0.001423905,0.00262478,0.001559542,0.002399494,0.0009199664,0.001615948,0.0004047117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002005521,"about_ca_system_score_gemma":0.00104014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009091122,"about_ca_topic_score_gemma":0.003936753,"domain_scores_codex":[0.9985999,0.0004157152,0.0001392331,0.0003033164,0.0004316447,0.0001101239],"domain_scores_gemma":[0.9989064,0.0005559461,0.0001590937,0.00008042964,0.0002629687,0.00003522625],"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":[0.0001094944,0.00006328498,0.002031852,0.0003268353,0.0001151296,0.0004490144,0.00081276,0.09771867,0.005189853,0.7050868,0.004857571,0.1832388],"study_design_scores_gemma":[0.00001539887,0.00008221796,0.001546515,0.0001971723,0.00006261963,0.0004191183,0.0003972939,0.5115811,0.0023501,0.4604656,0.02279578,0.00008707732],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02721952,0.008225578,0.9346585,0.0013774,0.0002839508,0.00008723521,0.0002696908,0.0001984536,0.02767968],"genre_scores_gemma":[0.5832363,0.00746321,0.3997576,0.0003176577,0.0003415883,0.0002034509,0.0002454121,0.00005141944,0.008383341],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009091122,"threshold_uncertainty_score":0.01807636,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410076467","doi":"10.1007/s10462-025-11214-w","title":"Machine learning innovations in CPR: a comprehensive survey on enhanced resuscitation techniques","year":2025,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo; University of Alberta; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Computer science; Interpretability; Software deployment; Psychological intervention; Artificial intelligence; Data science; Process management; Medicine; Software engineering","authors":[{"name":"Saidul Islam","is_ca":true},{"name":"Gaith Rjoub","is_ca":true},{"name":"Hanae Elmekki","is_ca":true},{"name":"Jamal Bentahar","is_ca":true},{"name":"Witold Pedrycz","is_ca":true},{"name":"S. Robin Cohen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07471890793677392,"gpt":0.3971085548490244,"spread":0.3223896469122505,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005221133,0.0007740374,0.0008736369,0.004082005,0.0004342184,0.002698478,0.001137682,0.001418879,0.003443738],"category_scores_gemma":[0.01461978,0.0005424248,0.000806256,0.004708661,0.001321946,0.005497861,0.001636564,0.002236178,0.0008416393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001301478,"about_ca_system_score_gemma":0.001965407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00111379,"about_ca_topic_score_gemma":0.0007774941,"domain_scores_codex":[0.9966373,0.001179978,0.0004686398,0.0004096253,0.001152383,0.0001520177],"domain_scores_gemma":[0.9833475,0.01402235,0.0005537237,0.0005278325,0.001380979,0.0001675818],"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":[0.00008190443,0.00008870087,0.002659199,0.008007555,0.00008021844,0.0001057397,0.0006619653,0.002676358,0.0007597715,0.03934556,0.007252159,0.9382809],"study_design_scores_gemma":[0.00002545009,0.0004591297,0.01097827,0.01800655,0.0001742888,0.001346697,0.001391244,0.006717281,0.002623156,0.0347795,0.9233766,0.0001219148],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.008532841,0.9410161,0.02532088,0.005737758,0.0005796582,0.000101884,0.0001695674,0.0001212599,0.01842009],"genre_scores_gemma":[0.04488088,0.9334792,0.01724138,0.001208157,0.001039776,0.00009126344,0.0002548868,0.00005577748,0.001748696],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005221133,"threshold_uncertainty_score":0.02761227,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401009456","doi":"10.1007/s10462-024-10853-9","title":"Knowledge transfer in lifelong machine learning: a systematic literature review","year":2024,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Wilfrid Laurier University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Lifelong learning; Knowledge transfer; Transfer of learning; Artificial intelligence; Systematic review; Machine learning; Knowledge management; Psychology; MEDLINE; Pedagogy; Chemistry","authors":[{"name":"Pouya Khodaee","is_ca":true},{"name":"Herna L. Viktor","is_ca":true},{"name":"Wojtek Michalowski","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06351313169488046,"gpt":0.3431309784109463,"spread":0.2796178467160658,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01414305,0.001129887,0.004563943,0.013504,0.0007911616,0.004055582,0.002439264,0.002225152,0.005541331],"category_scores_gemma":[0.07406946,0.0008066765,0.004358048,0.01173818,0.001207673,0.005419542,0.002818685,0.001863765,0.0005876978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004338776,"about_ca_system_score_gemma":0.01739077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00579847,"about_ca_topic_score_gemma":0.0138591,"domain_scores_codex":[0.9902776,0.003994062,0.002762386,0.0008481729,0.001863263,0.0002544559],"domain_scores_gemma":[0.9041204,0.08081933,0.00699428,0.001367208,0.00612678,0.0005720393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001456655,0.0001038396,0.001510602,0.6923883,0.004064528,0.0001422322,0.0006368167,0.0005993692,0.0001298628,0.00198618,0.004759749,0.2935329],"study_design_scores_gemma":[0.00009218469,0.0002850996,0.004097375,0.9298715,0.01088148,0.0003553747,0.0008644327,0.0005762621,0.0002673351,0.002513919,0.0501255,0.00006939023],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001065662,0.9964557,0.0006939726,0.000792024,0.00009775253,0.0001856245,0.0002143763,0.00001488385,0.0004799077],"genre_scores_gemma":[0.01981982,0.9757817,0.002245561,0.0008852127,0.0001370731,0.0006283288,0.0003305239,0.00001123319,0.0001604775],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01414305,"threshold_uncertainty_score":0.0747965,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4385700994","doi":"10.1007/s10462-023-10568-3","title":"RNN-AFOX: adaptive FOX-inspired-based technique for automated tuning of recurrent neural network hyper-parameters","year":2023,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan; University of Regina","funders":"","keywords":"Recurrent neural network; Computer science; Closing (real estate); Artificial neural network; Artificial intelligence; Machine learning; Economics","authors":[{"name":"Hosam ALRahhal","is_ca":true},{"name":"Razan Jamous","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.145204389540127,"gpt":0.3258933243596763,"spread":0.1806889348195494,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001171667,0.0008994408,0.0006165177,0.0005039976,0.0003224344,0.0004899253,0.001248549,0.001155441,0.00323181],"category_scores_gemma":[0.002155101,0.0003437323,0.0006044662,0.0003405399,0.000291053,0.0006180094,0.0006792234,0.001130758,0.0007504602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003886398,"about_ca_system_score_gemma":0.0004727587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004999513,"about_ca_topic_score_gemma":0.007414204,"domain_scores_codex":[0.9997906,0.00005793278,0.00001334839,0.0000542843,0.00006009367,0.00002376196],"domain_scores_gemma":[0.9996124,0.0001976275,0.00003641464,0.00003853565,0.00009934216,0.00001557057],"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":[0.0002290575,0.00009020729,0.00125926,0.0002950741,0.000157997,0.0001651369,0.0001795828,0.3121482,0.02795281,0.009301493,0.004678081,0.6435431],"study_design_scores_gemma":[0.00001260549,0.00003381702,0.0001780332,0.00001457001,0.00001400982,0.00003564303,0.000005924912,0.9942505,0.003039381,0.001084806,0.0013242,0.000006467622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007284707,0.0005087156,0.9891517,0.00004715004,0.0000543273,0.00003299388,0.00003546484,0.001808633,0.001076251],"genre_scores_gemma":[0.3062964,0.0004105976,0.6892608,0.0002054125,0.00005585072,0.0001524292,0.0001991853,0.0004767403,0.002942676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004999513,"threshold_uncertainty_score":0.01081151,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4411041682","doi":"10.1007/s10462-025-11203-z","title":"Web Intelligence (WI) 3.0: in search of a better-connected world to create a future intelligent society","year":2025,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina; York University","funders":"Japan Society for the Promotion of Science; Natural Sciences and Engineering Research Council of Canada; American Indian Graduate Center","keywords":"Computer science; World Wide Web; Information retrieval","authors":[{"name":"Hongzhi Kuai","is_ca":false},{"name":"Jimmy Xiangji Huang","is_ca":true},{"name":"Xiaohui Tao","is_ca":false},{"name":"Gabriella Pasi","is_ca":false},{"name":"Yiyu Yao","is_ca":true},{"name":"Jiming Liu","is_ca":false},{"name":"Ning Zhong","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05722965990088423,"gpt":0.3493319640979139,"spread":0.2921023041970296,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001781582,0.0007293723,0.0006308898,0.005015605,0.001169129,0.006793879,0.001025486,0.002690191,0.003440521],"category_scores_gemma":[0.003497767,0.0003443066,0.0005840248,0.006661923,0.002526776,0.01259558,0.002380676,0.002914608,0.001776141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001799411,"about_ca_system_score_gemma":0.002420672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002222115,"about_ca_topic_score_gemma":0.002472714,"domain_scores_codex":[0.9988884,0.000294538,0.00008905961,0.0001501501,0.0004725703,0.0001052618],"domain_scores_gemma":[0.9980367,0.001064134,0.0001709337,0.0001412693,0.0004239317,0.0001630037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002276376,0.00004355116,0.001307621,0.003785653,0.00007686338,0.0002312253,0.001222111,0.001097378,0.0009170668,0.4661426,0.05194299,0.4732103],"study_design_scores_gemma":[0.000003607753,0.00002501785,0.001140473,0.00223589,0.00003339395,0.0004375365,0.0008951844,0.001142535,0.0004305645,0.1097745,0.8838476,0.00003376465],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.00790651,0.7051201,0.05674899,0.03781528,0.003318627,0.0001422896,0.00036903,0.0007818529,0.1877972],"genre_scores_gemma":[0.09690118,0.8268324,0.03804348,0.01159361,0.003749666,0.0001974199,0.0006975888,0.000269256,0.02171549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006793879,"threshold_uncertainty_score":0.01305568,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4406814688","doi":"10.1007/s10462-025-11111-2","title":"HFA-Net: hybrid feature-aware network for large-scale point cloud semantic segmentation","year":2025,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"3D Shape Modeling and 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":"People's Government of Jilin Province; National Natural Science Foundation of China; Jiangsu University; Jilin Province Development and Reform Commission","keywords":"Computer science; Cloud computing; Feature (linguistics); Scale (ratio); Net (polyhedron); Segmentation; Semantic feature; Point cloud; Artificial intelligence; Pattern recognition (psychology); Cartography; Operating system; Mathematics","authors":[{"name":"Changji Wen","is_ca":false},{"name":"Long Zhang","is_ca":false},{"name":"Junfeng Ren","is_ca":false},{"name":"Rundong Hong","is_ca":false},{"name":"Chenshuang Li","is_ca":false},{"name":"Ce Yang","is_ca":false},{"name":"Yanfeng Lv","is_ca":false},{"name":"Hongbing Chen","is_ca":false},{"name":"Ning Yang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02559056250704876,"gpt":0.3005442089437189,"spread":0.2749536464366701,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005718997,0.001486663,0.0009929356,0.001627979,0.0006532678,0.0008950283,0.002088374,0.001435803,0.002611387],"category_scores_gemma":[0.001164772,0.0005780168,0.001142136,0.00136011,0.0005985493,0.002021133,0.001517316,0.0009429069,0.0009736796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001233288,"about_ca_system_score_gemma":0.0008260077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009227235,"about_ca_topic_score_gemma":0.01219081,"domain_scores_codex":[0.9997032,0.00003135342,0.00001351955,0.0001156963,0.00008648029,0.00004966155],"domain_scores_gemma":[0.9996933,0.00008661166,0.00003739365,0.00005343817,0.0001013246,0.0000279956],"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":[0.000326608,0.0002166456,0.002429009,0.0002150837,0.0002493112,0.0002070819,0.000154513,0.3588276,0.02537733,0.008186092,0.01092027,0.5928906],"study_design_scores_gemma":[0.000010941,0.00005464803,0.0006094233,0.00001247529,0.00003210108,0.00006514908,0.00002362572,0.9852871,0.005855413,0.005841104,0.002193911,0.00001419768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03262323,0.000876222,0.957258,0.0002641048,0.000100187,0.0001471669,0.0007132526,0.00510858,0.002909295],"genre_scores_gemma":[0.483183,0.0007996062,0.5039797,0.0005500293,0.000160571,0.0004045751,0.003215693,0.0004584414,0.007248411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009227235,"threshold_uncertainty_score":0.01834708,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4411535114","doi":"10.1007/s10462-025-11268-w","title":"Comprehensive review of reinforcement learning for medical ultrasound imaging","year":2025,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","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 Laval; École de Technologie Supérieure; Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Khalifa University of Science, Technology and Research; Concordia University","keywords":"Computer science; Reinforcement learning; Software portability; Artificial intelligence; Process (computing); Field (mathematics); Modalities; Data science; Human–computer interaction; Risk analysis (engineering); Machine learning","authors":[{"name":"Hanae Elmekki","is_ca":true},{"name":"Saidul Islam","is_ca":true},{"name":"Ahmed Alagha","is_ca":true},{"name":"Hani Sami","is_ca":true},{"name":"Amanda Spilkin","is_ca":true},{"name":"Ehsan Zakeri","is_ca":true},{"name":"Antonela Zanuttini","is_ca":true},{"name":"Jamal Bentahar","is_ca":true},{"name":"Lyes Kadem","is_ca":true},{"name":"Wenfang Xie","is_ca":true},{"name":"Philippe Pîbarot","is_ca":true},{"name":"Rabeb Mizouni","is_ca":false},{"name":"Hadi Otrok","is_ca":false},{"name":"Shakti Singh","is_ca":false},{"name":"Azzam Mourad","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03399191280276161,"gpt":0.3936243590070638,"spread":0.3596324462043022,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001410587,0.001042444,0.001098542,0.001831908,0.0002598062,0.001301485,0.001100401,0.001363936,0.004349951],"category_scores_gemma":[0.003280048,0.0004628607,0.0008592824,0.00241133,0.000485951,0.001497389,0.0006544393,0.001439471,0.001817877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009911106,"about_ca_system_score_gemma":0.001615544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002624038,"about_ca_topic_score_gemma":0.002081563,"domain_scores_codex":[0.9994061,0.0001711874,0.00007606328,0.0001122212,0.0001987069,0.00003577917],"domain_scores_gemma":[0.9979762,0.001504962,0.000100513,0.00005055774,0.0003239059,0.00004381522],"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":[0.00004523382,0.0000878191,0.0005085714,0.01426209,0.0001448178,0.0001402787,0.0001315624,0.007517769,0.0007559329,0.0290654,0.02883233,0.9185082],"study_design_scores_gemma":[0.00001713911,0.0002668179,0.001753037,0.009024981,0.00021413,0.0008053345,0.0001492209,0.009084526,0.0008808295,0.02421302,0.9535077,0.00008317671],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003014843,0.9888172,0.006378967,0.0006949813,0.0003086485,0.00001436293,0.00003082457,0.00003027063,0.00342321],"genre_scores_gemma":[0.0056704,0.9869767,0.004709455,0.000396148,0.0008102006,0.00002692948,0.00007753652,0.00001608815,0.001316529],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004349951,"threshold_uncertainty_score":0.014552,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4408707508","doi":"10.1007/s10462-025-11167-0","title":"Bibliometric analysis of artificial intelligence cyberattack detection models","year":2025,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":5,"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; Artificial intelligence","authors":[{"name":"Blessing Guembe","is_ca":false},{"name":"Sanjay Misra","is_ca":false},{"name":"Ambrose Azeta","is_ca":false},{"name":"Inés López-Baldominos","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1828336125369347,"gpt":0.3797865332793412,"spread":0.1969529207424065,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.008956952,0.000942797,0.00187142,0.152583,0.001404306,0.008353989,0.001803319,0.001138679,0.006676321],"category_scores_gemma":[0.08753436,0.0004145796,0.00208885,0.2234191,0.001049341,0.005435526,0.002250653,0.0007686533,0.002072772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003768642,"about_ca_system_score_gemma":0.004627723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01140039,"about_ca_topic_score_gemma":0.00737172,"domain_scores_codex":[0.9812626,0.003892843,0.002609596,0.001458368,0.009991334,0.0007852652],"domain_scores_gemma":[0.8904297,0.07001029,0.01735625,0.004147072,0.01676514,0.001291477],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003929207,0.0004704893,0.5733155,0.01472051,0.003284134,0.001080276,0.002524185,0.03071601,0.0009081398,0.03460202,0.0644586,0.2735273],"study_design_scores_gemma":[0.000152231,0.0003766657,0.6445904,0.005748629,0.003306143,0.002394889,0.006634241,0.1361555,0.00278651,0.042787,0.1546627,0.0004051761],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6583357,0.05419725,0.0205358,0.007487282,0.0005399394,0.0009944189,0.1134407,0.001417935,0.143051],"genre_scores_gemma":[0.9499515,0.01485187,0.00519116,0.0001487848,0.0004032073,0.0004102434,0.02521636,0.00009430766,0.003732515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.991043,"threshold_uncertainty_score":0.04736948,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}