{"meta":{"query_hash":"79a9cd8eaf8e","filters":{"venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)"},"cohort_total":12,"direct_labels_cover":0,"predictions_cover":12,"exported":12,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/79a9cd8eaf8e","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Research+Journal+on+Advanced+Engineering+Hub+%28IRJAEH%29"},"results":[{"id":"W4392655881","doi":"10.47392/irjaeh.2024.0029","title":"A Comparative Study on Machine Learning Approaches for Sentiment Analysis","year":2024,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Sentiment analysis; Computer science; Artificial intelligence; Natural language processing; Machine learning","score_opus":0.14146353702295014,"score_gpt":0.42063778960006276,"score_spread":0.2791742525771126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392655881","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09020769,0.0007298547,0.9034517,0.0020417261,0.001418573,0.00051376945,0.000013121073,0.00019501914,0.0014285779],"genre_scores_gemma":[0.98954046,0.000046575362,0.008226488,0.000020552245,0.00029312054,0.00007146138,0.000016884147,0.00002005656,0.0017644328],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969424,0.0001419817,0.0004169967,0.0005253905,0.0015509524,0.0004222894],"domain_scores_gemma":[0.9983013,0.00088896666,0.00008383721,0.0002484501,0.0002952978,0.00018210582],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0019698255,0.00021031978,0.00031945313,0.0022344328,0.00026361452,0.0010478938,0.00090657023,0.00003367107,0.000068374444],"category_scores_gemma":[0.00023755478,0.00017670428,0.0003284033,0.0014634774,0.000020282345,0.00044565293,0.0001692956,0.0009388003,0.000058139478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006667218,0.00028212802,0.0004517534,0.000009001926,0.0026785883,0.00007336642,0.0011941019,0.96523535,0.00042367735,0.018470226,0.00027443186,0.01084068],"study_design_scores_gemma":[0.00048504063,0.0006497399,0.0011252073,0.00010816446,0.00004913404,0.000009128042,0.00044642092,0.97664976,0.00065570633,0.00023452663,0.019410396,0.00017677387],"about_ca_topic_score_codex":0.0000043355017,"about_ca_topic_score_gemma":0.0000028343925,"teacher_disagreement_score":0.89933276,"about_ca_system_score_codex":0.00041320088,"about_ca_system_score_gemma":0.000059236525,"threshold_uncertainty_score":0.9999891},"labels":[],"label_agreement":null},{"id":"W4395000002","doi":"10.47392/irjaeh.2024.0137","title":"An Automated Billing System for Smart Shopping Using Internet of Things","year":2024,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Internet of Things; Computer science; The Internet; Computer security; World Wide Web; Internet privacy","score_opus":0.07432260681823637,"score_gpt":0.3879642978639627,"score_spread":0.3136416910457263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395000002","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93304336,0.0007715273,0.058497775,0.00047721597,0.004793911,0.00047107798,0.000013381049,0.0008659564,0.0010657714],"genre_scores_gemma":[0.99455214,0.000026472631,0.004636296,0.000019003386,0.0005381477,0.000030292129,0.000012103199,0.00007703816,0.00010851097],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99771255,0.00001784649,0.0005409365,0.00032074185,0.00095374876,0.000454171],"domain_scores_gemma":[0.9983566,0.00030421547,0.0001393145,0.00016997984,0.0009843925,0.000045519922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016005409,0.00021399713,0.00026249263,0.0016352283,0.00017561505,0.0007858199,0.000587184,0.000060458067,0.00004068224],"category_scores_gemma":[0.0006502556,0.00019644349,0.00015778023,0.0005384604,0.000051285027,0.0017818824,0.00016202356,0.0006108282,0.000026261021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087422493,0.00035991444,0.013954284,0.004783807,0.0016988914,0.0008520156,0.00076060905,0.24760179,0.41902605,0.13012552,0.0008398927,0.179123],"study_design_scores_gemma":[0.0003989302,0.00004942828,0.00068491534,0.002959317,0.000034828267,0.000056049335,0.00031160013,0.97291464,0.00094589876,0.00008105098,0.021344263,0.0002191096],"about_ca_topic_score_codex":0.000110079156,"about_ca_topic_score_gemma":0.000006861335,"teacher_disagreement_score":0.7253128,"about_ca_system_score_codex":0.0005804938,"about_ca_system_score_gemma":0.000069874375,"threshold_uncertainty_score":0.8010733},"labels":[],"label_agreement":null},{"id":"W4405187362","doi":"10.47392/irjaeh.2024.0373","title":"EDUSYNC – Smart Classroom Management System","year":2024,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Wireless Sensor Networks and IoT","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Business","score_opus":0.01766033814715414,"score_gpt":0.29780998448206997,"score_spread":0.28014964633491585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405187362","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19979708,0.019790443,0.3541487,0.004378459,0.07711366,0.0018108208,0.00017087952,0.0068730167,0.33591697],"genre_scores_gemma":[0.9894244,0.0020798834,0.003289653,0.000019558742,0.0017620164,0.00004748779,0.000011378555,0.00013759697,0.0032280246],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99724877,0.000035368037,0.00042996285,0.0002979434,0.0012854526,0.00070249755],"domain_scores_gemma":[0.9989971,0.00024689076,0.000022433755,0.00024254901,0.0001913504,0.00029968043],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007152262,0.00026419683,0.00020952107,0.0009736599,0.00012062796,0.0005355509,0.0005869678,0.000093239,0.0001573403],"category_scores_gemma":[0.000061002946,0.00024953645,0.00015350942,0.00049095444,0.000028886197,0.00036461148,0.00008665375,0.0015490347,0.00045737356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003083174,0.000020511896,0.0000098926075,0.0002742585,0.0003352004,0.0010929223,0.0000338134,0.891528,0.0018940856,0.036285173,0.012313615,0.056181695],"study_design_scores_gemma":[0.00028352524,0.00006747164,0.00021111152,0.0016856468,0.0000076062674,0.00025283298,0.00010120839,0.5093053,0.00057477667,0.00017830823,0.48709553,0.00023670564],"about_ca_topic_score_codex":0.0000025773197,"about_ca_topic_score_gemma":0.000001315411,"teacher_disagreement_score":0.7896273,"about_ca_system_score_codex":0.0013873748,"about_ca_system_score_gemma":0.000030636642,"threshold_uncertainty_score":0.9999957},"labels":[],"label_agreement":null},{"id":"W4405473900","doi":"10.47392/irjaeh.2024.0384","title":"Garbage Classification: A Deep Learning Perspective","year":2024,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Garbage; Computer science; Deep learning; Artificial intelligence; Convolutional neural network; Sorting; Process (computing); Machine learning","score_opus":0.03737325029338717,"score_gpt":0.37127714964717135,"score_spread":0.3339038993537842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405473900","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15017629,0.0027479082,0.10127762,0.021399856,0.00675007,0.001189922,0.000017212575,0.00078173465,0.7156594],"genre_scores_gemma":[0.9878427,0.00049985363,0.0017164716,0.000057721085,0.0004603777,0.0000429689,0.000003964468,0.000049896797,0.009326055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970182,0.00009801465,0.00028429105,0.00040737278,0.0016786619,0.0005134521],"domain_scores_gemma":[0.9990582,0.00032701239,0.000047341742,0.00021273126,0.00010714183,0.0002475795],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0012617388,0.00017568604,0.00012149922,0.00044156026,0.00021866923,0.00041232974,0.00073034153,0.000050516053,0.003437154],"category_scores_gemma":[0.0009458092,0.00016460125,0.00010507311,0.00056619785,0.0000947313,0.00049100356,0.00032464613,0.0016870761,0.0015837573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004590307,0.00005080301,0.000094535346,0.000011507903,0.00008320851,0.0002794897,0.00049233786,0.9350691,0.0025431116,0.036247388,0.0012783525,0.02380427],"study_design_scores_gemma":[0.00024162352,0.00017124065,0.0024221032,0.00019639627,0.000004836753,0.00007882162,0.00092415675,0.56741476,0.00015300912,0.0016374318,0.4265604,0.0001951886],"about_ca_topic_score_codex":0.000032779117,"about_ca_topic_score_gemma":0.000009889484,"teacher_disagreement_score":0.8376664,"about_ca_system_score_codex":0.0029300204,"about_ca_system_score_gemma":0.000025416455,"threshold_uncertainty_score":0.9991936},"labels":[],"label_agreement":null},{"id":"W4405559801","doi":"10.47392/irjaeh.2024.0386","title":"Predicting Used Car Prices Using Machine Learning: A Comparative Analysis of Regression and Ensemble Models","year":2024,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Ensemble learning; Regression analysis; Regression; Artificial intelligence; Machine learning; Computer science; Statistics; Mathematics","score_opus":0.06791038759328283,"score_gpt":0.3753696768005002,"score_spread":0.3074592892072174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405559801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9807321,0.0015458377,0.015538568,0.00012042722,0.00022708105,0.000063315965,0.000027311688,0.000057347064,0.0016880259],"genre_scores_gemma":[0.99581,0.0011972493,0.002342643,0.0000074450877,0.00010963786,0.0000073004335,0.000031233143,0.000026501477,0.0004680145],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998035,0.000072526556,0.00040137005,0.00025073555,0.0009577425,0.00028258274],"domain_scores_gemma":[0.99895763,0.0005024703,0.000115294286,0.00010900842,0.00016500585,0.0001505897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055358786,0.00016768355,0.00028146018,0.001363846,0.00014211045,0.00011592137,0.00019544449,0.00005693568,0.000072976916],"category_scores_gemma":[0.00014182636,0.00014339092,0.00012772846,0.0006444996,0.000065809254,0.00043963842,0.00003896936,0.0007130401,0.0000022921743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062729356,0.000030432988,0.0012385251,0.000028632518,0.0008200293,0.000039316816,0.0012483835,0.9242211,0.047712795,0.02402055,0.0000035537264,0.0005739615],"study_design_scores_gemma":[0.00031680512,0.00010432987,0.002491585,0.00040772636,0.00008751703,0.000017087523,0.0002939119,0.9823708,0.008860804,0.0006646177,0.0042544454,0.00013039567],"about_ca_topic_score_codex":0.0003267231,"about_ca_topic_score_gemma":0.00012305535,"teacher_disagreement_score":0.058149684,"about_ca_system_score_codex":0.00023360873,"about_ca_system_score_gemma":0.0000416549,"threshold_uncertainty_score":0.5847312},"labels":[],"label_agreement":null},{"id":"W4410095430","doi":"10.47392/irjaeh.2025.0225","title":"DUI (Driver Under Influence) Detection Using Open CV","year":2025,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science","score_opus":0.028271329878116955,"score_gpt":0.3651872239836145,"score_spread":0.3369158941054975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410095430","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82693267,0.0002550555,0.16457051,0.0005902054,0.0015873077,0.00026052783,0.000009194143,0.00034847626,0.005446041],"genre_scores_gemma":[0.9946377,0.0002835485,0.004195105,0.00007640339,0.0001259849,0.000019330639,0.0000025982106,0.000043870066,0.0006154037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983264,0.00004059128,0.0003825548,0.00024131255,0.00050773204,0.00050139095],"domain_scores_gemma":[0.99902797,0.00020450844,0.000046248566,0.0002536604,0.00033930832,0.00012832109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070978975,0.00020213827,0.000204909,0.0009858827,0.00028458764,0.00022969127,0.0010833635,0.0001737786,0.00011364854],"category_scores_gemma":[0.00037523784,0.0002113165,0.000077541736,0.0005646412,0.000064217464,0.00067476794,0.00026436767,0.001712837,0.000059707356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006456937,0.00002488602,0.00007445863,0.000013938368,0.0001416747,0.00003940616,0.000023261335,0.9099128,0.057851158,0.007979066,0.000065627086,0.023809155],"study_design_scores_gemma":[0.0022489089,0.00019411749,0.018523935,0.00089825224,0.000019513982,0.00028413656,0.00019789391,0.821258,0.05582195,0.013288512,0.086623624,0.0006411373],"about_ca_topic_score_codex":0.00001746876,"about_ca_topic_score_gemma":0.000010689352,"teacher_disagreement_score":0.16770507,"about_ca_system_score_codex":0.0013797,"about_ca_system_score_gemma":0.00010082337,"threshold_uncertainty_score":0.86172366},"labels":[],"label_agreement":null},{"id":"W4410100528","doi":"10.47392/irjaeh.2025.0129","title":"AI- Based Heart Disease Detection Using Machine Learning","year":2025,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning","score_opus":0.1513779749869514,"score_gpt":0.553785817858072,"score_spread":0.40240784287112064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410100528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74572057,0.0012339107,0.19845794,0.03766122,0.0127052935,0.0016491652,0.00006664297,0.00050311314,0.0020021244],"genre_scores_gemma":[0.9938662,0.000100566016,0.001755244,0.0015821214,0.00081217254,0.000086171676,0.000011655677,0.000056708475,0.0017291378],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9960807,0.0006366699,0.00077920826,0.00036696042,0.0012486896,0.00088778214],"domain_scores_gemma":[0.9956323,0.0018887504,0.00014767134,0.00026905385,0.001579659,0.00048259113],"candidate_categories":["sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002367987,0.00021964636,0.00024318178,0.0013909208,0.0014683568,0.00008831198,0.00048258324,0.00014589993,0.00051375356],"category_scores_gemma":[0.008327238,0.00021778954,0.00012758598,0.00072494854,0.0000646257,0.00035376937,0.00014814037,0.0048317565,0.00018222109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011803992,0.00010935325,0.03259139,0.00023546639,0.00006011795,0.00011171624,0.00015095738,0.92873126,0.021979392,0.0043439562,0.00042928613,0.01007669],"study_design_scores_gemma":[0.00047997778,0.00015422083,0.004150509,0.0019855876,0.000007859594,0.0000075211365,0.00029008483,0.8441864,0.0031427057,0.0021828802,0.14320208,0.0002101254],"about_ca_topic_score_codex":0.00032151604,"about_ca_topic_score_gemma":0.000115609204,"teacher_disagreement_score":0.24814564,"about_ca_system_score_codex":0.0024763418,"about_ca_system_score_gemma":0.000951755,"threshold_uncertainty_score":0.9998316},"labels":[],"label_agreement":null},{"id":"W4410415687","doi":"10.47392/irjaeh.2025.0334","title":"Deep Deception Detector: Exposing AI Generated Fake Video","year":2025,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Digital Media Forensic Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Deception; Detector; Computer security; Internet privacy; Fake news; Computer science; Psychology; Artificial intelligence; Social psychology; Telecommunications","score_opus":0.01832153045594137,"score_gpt":0.3311018492114223,"score_spread":0.31278031875548096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410415687","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050553802,0.0002409897,0.93741745,0.0019314196,0.006109337,0.00018850708,0.000002373586,0.00024278829,0.0033133554],"genre_scores_gemma":[0.9676334,0.00013768811,0.030545155,0.0003806508,0.000490368,0.00004496811,0.0000052909445,0.00003167774,0.0007307575],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99697244,0.00007327444,0.000460667,0.00042722875,0.0014702219,0.0005961445],"domain_scores_gemma":[0.99785465,0.00040877872,0.0000935063,0.00037100614,0.0010143662,0.00025767245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009266778,0.00021780872,0.00018429807,0.0015400987,0.0002290292,0.0009726831,0.0012384139,0.000091801536,0.00003637935],"category_scores_gemma":[0.0021962584,0.0002166985,0.000116591604,0.0011016214,0.000054533644,0.0015454659,0.0002665237,0.0011865201,0.00010495128],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010780582,0.00008861181,0.00004763669,0.000017965227,0.00011507157,0.00013380006,0.000100752506,0.32887587,0.07347137,0.028599562,0.0014297576,0.5670118],"study_design_scores_gemma":[0.00144975,0.0004608274,0.0016535738,0.000723578,0.0000055725222,0.0002680805,0.000046882495,0.78592247,0.092747495,0.009817571,0.10646906,0.00043514275],"about_ca_topic_score_codex":0.000005934527,"about_ca_topic_score_gemma":0.000010425175,"teacher_disagreement_score":0.9170796,"about_ca_system_score_codex":0.0012407821,"about_ca_system_score_gemma":0.00018936433,"threshold_uncertainty_score":0.9379605},"labels":[],"label_agreement":null},{"id":"W4410606112","doi":"10.47392/irjaeh.2025.0354","title":"An AI-Powered Intermediate Accessibility App for Visually Impaired Users with Real-Time Voice and Vibration Support","year":2025,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Visually impaired; Computer science; Vibration; Speech recognition; Human–computer interaction; Acoustics; Physics","score_opus":0.03333336505570189,"score_gpt":0.40693193001028183,"score_spread":0.37359856495457994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410606112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9758505,0.0000046314476,0.01913441,0.0018791207,0.0008970961,0.00053593074,0.00010837231,0.00015378358,0.0014361548],"genre_scores_gemma":[0.9968478,0.00013382435,0.0011738063,0.0003120982,0.00019522356,0.000071626775,0.000028186694,0.000035043468,0.0012023827],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9977982,0.000117914424,0.000412942,0.00048333826,0.00073554146,0.00045203243],"domain_scores_gemma":[0.99775773,0.0010219194,0.00012448628,0.00026166163,0.00056770566,0.00026650066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046608964,0.00020396842,0.00020543068,0.00075996626,0.00029563514,0.0005131306,0.00053136976,0.00007128736,0.00011765409],"category_scores_gemma":[0.0022923402,0.00017895225,0.000074931726,0.0003478477,0.00010001392,0.0015824205,0.00006692326,0.00076939864,0.000017908238],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024585302,0.00027598153,0.00036631728,0.00004284066,0.000069751375,0.0000820462,0.00023931838,0.01981906,0.9655919,0.0023,0.0007399338,0.00801431],"study_design_scores_gemma":[0.006237571,0.004948233,0.03439759,0.00087126304,0.00004176463,0.00044656912,0.00057016284,0.30968496,0.5939482,0.002981821,0.044913936,0.00095790974],"about_ca_topic_score_codex":0.0000126967525,"about_ca_topic_score_gemma":0.000016156193,"teacher_disagreement_score":0.3716437,"about_ca_system_score_codex":0.00044395338,"about_ca_system_score_gemma":0.00023936124,"threshold_uncertainty_score":0.7297461},"labels":[],"label_agreement":null},{"id":"W4414537366","doi":"10.47392/irjaeh.2025.0550","title":"Machine Learning Methods for Speech Emotion Recognition","year":2025,"lang":"en","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Semtech (Canada)","funders":"","keywords":"Convolutional neural network; Support vector machine; Robustness (evolution); Feature extraction; Emotion classification; Mel-frequency cepstrum; Random forest; Generalization; Feature (linguistics); Benchmark (surveying)","score_opus":0.07098266512585713,"score_gpt":0.43011916330131245,"score_spread":0.35913649817545534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414537366","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002022898,0.00020432034,0.98529637,0.003414904,0.0020646348,0.00024273277,0.000008714398,0.00015996596,0.0065854657],"genre_scores_gemma":[0.036329985,0.00078829343,0.9577475,0.00027186205,0.00039765768,0.00009359445,0.000026045422,0.000033428114,0.004311604],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978539,0.00024663025,0.00040325418,0.0003606376,0.00068883225,0.00044676507],"domain_scores_gemma":[0.99663657,0.0017775572,0.00010380976,0.00020481204,0.00111023,0.00016702793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032247787,0.00017168422,0.00019198284,0.001398335,0.0003052152,0.00045261704,0.000891952,0.00008493168,0.00014391073],"category_scores_gemma":[0.006476077,0.0001682059,0.00016638842,0.0006416403,0.000026402822,0.0006246408,0.0001376198,0.001032511,0.000069125796],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007304713,0.00006389247,0.000014763405,0.000018559998,0.0000738331,0.00002005822,0.0000314022,0.0049853316,0.009246807,0.010581255,0.00035363398,0.97453743],"study_design_scores_gemma":[0.0012816018,0.00029769394,0.00032455914,0.00055984396,0.0000073966494,0.00016402903,0.00005092597,0.5973336,0.05065658,0.032880902,0.31615883,0.00028401948],"about_ca_topic_score_codex":0.000005000834,"about_ca_topic_score_gemma":0.0000011931438,"teacher_disagreement_score":0.9742534,"about_ca_system_score_codex":0.0005203319,"about_ca_system_score_gemma":0.00011535025,"threshold_uncertainty_score":0.77529365},"labels":[],"label_agreement":null},{"id":"W7117294212","doi":"10.47392/irjaeh.2025.0619","title":"Vivaaha VR: Immersive Wedding Theme Selection Through Virtual Reality","year":2025,"lang":"","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Virtual reality; Theme (computing); Event (particle physics); Process (computing); Selection (genetic algorithm); Modular design; Transformative learning","score_opus":0.059103537947021764,"score_gpt":0.40990948368292174,"score_spread":0.35080594573589996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117294212","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009549806,0.00074832415,0.9457307,0.015138427,0.0047216653,0.00066199154,0.00007296165,0.0001240255,0.023252139],"genre_scores_gemma":[0.9828784,0.0039838357,0.006002471,0.00055587984,0.0011080381,0.00007586149,0.000016119679,0.00005974798,0.005319689],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9928324,0.00038232905,0.0012339593,0.0010603573,0.0029880789,0.0015028742],"domain_scores_gemma":[0.99415416,0.0014978563,0.0003668078,0.00082534406,0.0025588316,0.00059702434],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0033208937,0.00056612265,0.000529266,0.0016499707,0.0011712563,0.001653709,0.0030255157,0.00028332983,0.00027369862],"category_scores_gemma":[0.0045153196,0.00058157626,0.00036323917,0.0029201554,0.00022386784,0.0026042424,0.0008300127,0.0036690116,0.00019185313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038199444,0.00047444244,0.00003310767,0.00004755601,0.00044762777,0.00006224744,0.0008560953,0.31369603,0.026203783,0.47433075,0.006495193,0.17697118],"study_design_scores_gemma":[0.0021862565,0.0015499846,0.0016935708,0.0021165495,0.000029984667,0.00023716273,0.0007195812,0.47382373,0.02003229,0.019515727,0.4772726,0.00082255434],"about_ca_topic_score_codex":0.00014899543,"about_ca_topic_score_gemma":0.00001495502,"teacher_disagreement_score":0.97332853,"about_ca_system_score_codex":0.0037896936,"about_ca_system_score_gemma":0.0011859925,"threshold_uncertainty_score":0.9996636},"labels":[],"label_agreement":null},{"id":"W7117308881","doi":"10.47392/irjaeh.2025.0620","title":"An AI-Driven Placement Ecosystem for Automated Skill Matching","year":2025,"lang":"","type":"article","venue":"International Research Journal on Advanced Engineering Hub (IRJAEH)","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Matching (statistics); Ground truth; Embedding; Similarity (geometry); Quality (philosophy); Computation; Correlation; Precision and recall","score_opus":0.029111446027530033,"score_gpt":0.4078361739453983,"score_spread":0.37872472791786826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117308881","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011620097,0.00038446707,0.96966064,0.0057597705,0.0088770995,0.0013047194,0.000098363635,0.0007198079,0.0015750481],"genre_scores_gemma":[0.9372993,0.00046679055,0.059202716,0.00027861414,0.0008805592,0.00030370714,0.000018899607,0.00008135803,0.0014680243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9938921,0.00036310425,0.0014314564,0.0009336835,0.0020783644,0.0013013319],"domain_scores_gemma":[0.99503434,0.0010918274,0.00036456756,0.00084697176,0.0020980574,0.0005642152],"candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004132491,0.00053696544,0.00060580054,0.0024013175,0.0007136277,0.002371072,0.003523996,0.00023524981,0.00006245734],"category_scores_gemma":[0.00075058965,0.0005321436,0.00033237698,0.00085907266,0.000041163286,0.0017669756,0.0005131503,0.0019594228,0.00003467491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030017406,0.0005175056,0.00005532775,0.000383247,0.00067082426,0.00016802909,0.0007642128,0.79901123,0.007782609,0.120634854,0.010746315,0.058965698],"study_design_scores_gemma":[0.0014814093,0.0009515615,0.00017165634,0.0035778559,0.000009836106,0.00013025086,0.0002186122,0.8646715,0.0035382586,0.0026767754,0.12214365,0.00042860312],"about_ca_topic_score_codex":0.000028712437,"about_ca_topic_score_gemma":0.00001956667,"teacher_disagreement_score":0.9256792,"about_ca_system_score_codex":0.0028112622,"about_ca_system_score_gemma":0.0006498724,"threshold_uncertainty_score":0.999713},"labels":[],"label_agreement":null}]}