{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":9,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":9,"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":"e77324c5d55c","filters":{"venue":"Journal of Machine and Computing"}},"results":[{"id":"W4406038522","doi":"10.53759/7669/jmc202505044","title":"An Innovative Artificial Intelligence Based Decision Making System for Public Health Crisis Virtual Reality Rehabilitation","year":2025,"lang":"en","type":"article","venue":"Journal of Machine and Computing","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Artificial intelligence; Computer science; Machine learning; Decision tree; Health care; Context (archaeology); Naive Bayes classifier; Triage; Random forest; Digital health; Big data; Clinical decision support system; Support vector machine; Decision support system; Data science; Data mining; Medicine; Medical emergency","authors":[{"name":"Hayder M. A. Ghanimi","is_ca":false},{"name":"Firas Tayseer Ayasrah","is_ca":false},{"name":"Vijaya Chandra Jadala","is_ca":true},{"name":"T. C. Manjunath","is_ca":false},{"name":"K. Balasaranya","is_ca":false},{"name":"B. Srinivasarao","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06537455759597292,"gpt":0.421275958274205,"spread":0.3559014006782321,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004436162,0.0001128997,0.0004151189,0.00051356,0.0002385447,0.00008782701,0.00009672958,0.00005341848,0.000001748397],"category_scores_gemma":[0.002328165,0.00009543671,0.00008350853,0.0006735894,0.00003343088,0.0001264767,0.00003643214,0.000251316,1.656126e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003727045,"about_ca_system_score_gemma":0.0006239312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005525866,"about_ca_topic_score_gemma":0.00001833494,"domain_scores_codex":[0.9981565,0.0002262529,0.0009745458,0.0002033478,0.0002585491,0.0001808347],"domain_scores_gemma":[0.9958145,0.002424472,0.0006099677,0.0001605675,0.0008934864,0.0000970133],"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":[0.0006960877,0.0003796236,0.006036885,0.0006688718,0.00005590911,0.000007664225,0.001684451,0.004861378,0.0001813464,0.005483155,0.00147973,0.9784649],"study_design_scores_gemma":[0.001208794,0.004408077,0.02679923,0.00514623,0.00008597234,0.00005550844,0.006873237,0.949864,0.0003983277,0.002600119,0.002378086,0.0001823983],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2735448,0.0001372337,0.6850252,0.04082491,0.0002376486,0.0001987488,0.000003851218,0.00002205412,0.000005529605],"genre_scores_gemma":[0.9507731,0.000002837927,0.04091602,0.008102174,0.000190449,0.000001614112,0.00000433322,0.000009036213,3.886688e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9782825,"threshold_uncertainty_score":0.3891796,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3185363836","doi":"10.53759/7669/jmc202101005","title":"An Assembly Approach for Determining the Maintainability index for Engineered Products","year":2021,"lang":"en","type":"article","venue":"Journal of Machine and Computing","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Maintainability; Reliability engineering; Index (typography); Systems engineering; Manufacturing engineering; Computer science; Engineering; Risk analysis (engineering); Business","authors":[{"name":"Jain Emadi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01032043673763786,"gpt":0.2359472002883251,"spread":0.2256267635506872,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004915996,0.00008074776,0.0001425601,0.00003144655,0.0001056386,0.0000773251,0.00008350056,0.00003030208,4.79964e-7],"category_scores_gemma":[0.0001411772,0.00005785218,0.00004105889,0.00005573548,0.000006668268,0.00009901379,0.00001495133,0.0001152323,8.440303e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001662559,"about_ca_system_score_gemma":0.00002481757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.176654e-7,"about_ca_topic_score_gemma":3.661644e-7,"domain_scores_codex":[0.9994842,0.00001646333,0.0002236696,0.0000866443,0.00006775205,0.0001212675],"domain_scores_gemma":[0.9994913,0.00009719013,0.00007834245,0.00008024887,0.0002183561,0.00003451749],"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":[0.00001932676,0.00003601754,0.001250546,0.0004581702,0.0000338563,8.508256e-7,0.0003110096,0.9335099,0.0001601153,0.0001155966,0.00003817302,0.0640664],"study_design_scores_gemma":[0.0004767951,0.00007042866,0.005888251,0.00001701091,0.00002314015,0.00002856979,0.0001160056,0.9904844,0.002314389,0.0002011847,0.000304317,0.00007555458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3325919,0.0002503125,0.6668703,0.00005643604,0.00008660925,0.00009816379,0.00000145221,0.00001541002,0.00002939858],"genre_scores_gemma":[0.933781,0.000008257716,0.06588015,0.0000306906,0.0002719232,0.00000243251,0.000006684042,0.00001401435,0.000004846052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6011891,"threshold_uncertainty_score":0.2359143,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403157457","doi":"10.53759/7669/jmc202404096","title":"Diabetic Retinopathy Image Lesion Segmentation with Feature Fusion Relation Transformer Network","year":2024,"lang":"en","type":"article","venue":"Journal of Machine and Computing","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Artificial intelligence; Relation (database); Lesion; Diabetic retinopathy; Segmentation; Feature (linguistics); Computer science; Computer vision; Medicine; Pattern recognition (psychology); Pathology; Diabetes mellitus; Data mining; Linguistics; Endocrinology","authors":[{"name":"Shaymaa Hussein Nowfal","is_ca":false},{"name":"V. Eswaramoorthy","is_ca":true},{"name":"Vishnu Priya Arivanantham","is_ca":false},{"name":"Bhaskar Marapelli","is_ca":false},{"name":"K. Swaroopa","is_ca":false},{"name":"Ezhil Dyana M V","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.00637080713580031,"gpt":0.2643803899944211,"spread":0.2580095828586208,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000458824,0.00008895381,0.0001963105,0.0001095811,0.0000970352,0.00006629787,0.00002217298,0.00003229238,0.000008318218],"category_scores_gemma":[0.00001309284,0.00005425972,0.0000799535,0.0002259406,0.00001975885,0.0001237858,0.000006545808,0.0003521287,0.000001285718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002270611,"about_ca_system_score_gemma":0.0000267102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004935377,"about_ca_topic_score_gemma":6.300902e-7,"domain_scores_codex":[0.9993095,0.00004451311,0.0002272072,0.00009932888,0.0002146078,0.0001048066],"domain_scores_gemma":[0.9996428,0.00005676229,0.0001147011,0.00004274142,0.00007959033,0.00006343821],"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":[0.0007255727,0.0001033782,0.1392618,0.0008157495,0.0003696342,0.0008735979,0.002484123,0.002476978,0.0911545,0.00007139809,0.002885723,0.7587776],"study_design_scores_gemma":[0.004099102,0.003125628,0.280868,0.01215294,0.003146454,0.005696983,0.001032661,0.6790581,0.006308618,0.000580052,0.003442741,0.0004886661],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9392296,0.004088231,0.05237568,0.003550222,0.0001044459,0.00005938203,4.258111e-7,0.00002110958,0.0005708997],"genre_scores_gemma":[0.9867516,0.0003194959,0.01218853,0.0001355839,0.000426581,1.353577e-7,0.000007967054,0.00001195964,0.0001581259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7582889,"threshold_uncertainty_score":0.2212647,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4411968996","doi":"10.53759/7669/jmc202505141","title":"MetaFusion-FL: A Cross Modality Federated Meta Learning Framework for Robust and Explainable Healthcare System","year":2025,"lang":"en","type":"article","venue":"Journal of Machine and Computing","topic":"Traditional Chinese Medicine Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Modality (human–computer interaction); Federated learning; Health care; Healthcare system; Computer science; Artificial intelligence; Political science","authors":[{"name":"K R Kalphana","is_ca":false},{"name":"V Maheskumar","is_ca":false},{"name":"R. Vijayarajeswari","is_ca":true},{"name":"K. Sasikala","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04430693491977215,"gpt":0.3504745748066068,"spread":0.3061676398868347,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001238535,0.0001717232,0.0008357706,0.000158891,0.0006397169,0.00006445677,0.00004853413,0.00006600969,0.000002747586],"category_scores_gemma":[0.000769302,0.00011382,0.0001509072,0.0001957776,0.00005595358,0.00007040032,0.00007507551,0.0005892665,9.350461e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005798938,"about_ca_system_score_gemma":0.0001008545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008180235,"about_ca_topic_score_gemma":0.00000717296,"domain_scores_codex":[0.9987069,0.000105221,0.0005834108,0.0001797021,0.0002296725,0.0001950501],"domain_scores_gemma":[0.9983123,0.0007105679,0.0003287047,0.00006835834,0.0004559113,0.0001241712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007858996,0.001026961,0.6062738,0.04027596,0.02688244,0.001164423,0.01221888,0.02107945,0.001342701,0.1787494,0.002648959,0.100478],"study_design_scores_gemma":[0.01687589,0.003639321,0.4145668,0.01136482,0.009236133,0.005352427,0.01635164,0.5021218,0.0002835422,0.01462907,0.004783736,0.0007947535],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8024489,0.0224626,0.1621216,0.01197551,0.0003162241,0.0003208398,0.000006983759,0.00004708001,0.000300285],"genre_scores_gemma":[0.9691058,0.0001155711,0.02981661,0.0005016298,0.0003517188,0.000003686611,0.00000451784,0.00001239937,0.00008806127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4810424,"threshold_uncertainty_score":0.492025,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4409185257","doi":"10.53759/7669/jmc202505098","title":"Advancing Health Diagnostics: AI-Powered CVD-REF Framework for Precise and Early Risk Assessment","year":2025,"lang":"en","type":"article","venue":"Journal of Machine and Computing","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Risk assessment; Risk analysis (engineering); Computer science; Medicine; Systems engineering; Engineering; Computer security","authors":[{"name":"Vishnu Priyan S","is_ca":false},{"name":"N. Vijayalakshmi","is_ca":false},{"name":"Gulivindala Suresh","is_ca":true},{"name":"Rajesh Kumar","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03797665696017907,"gpt":0.4986130230387605,"spread":0.4606363660785814,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002904568,0.00015439,0.0005213606,0.0001792288,0.001344481,0.00003783075,0.0001367549,0.000145362,0.00001112558],"category_scores_gemma":[0.002775457,0.0001286207,0.00007453939,0.0001573222,0.00003942886,0.0001283681,0.000156142,0.001597846,0.000001101315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001767389,"about_ca_system_score_gemma":0.0006089052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007695685,"about_ca_topic_score_gemma":0.0002672224,"domain_scores_codex":[0.997281,0.0005500198,0.001306169,0.0002039577,0.000187381,0.0004714311],"domain_scores_gemma":[0.9918987,0.006120924,0.001150285,0.0001488774,0.0004451138,0.0002361374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001134449,0.0000558685,0.7435668,0.0006479726,0.00005166626,0.000004905023,0.004074993,0.0002040616,0.000006780624,0.007211617,0.001406448,0.2426555],"study_design_scores_gemma":[0.002016513,0.002906224,0.53385,0.01615424,0.0002127983,0.00002817698,0.01526331,0.1254654,0.00006368345,0.286437,0.01704877,0.0005538804],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6166711,0.008591272,0.3603112,0.01210871,0.001456275,0.0006992245,0.00001767609,0.00002345451,0.0001210667],"genre_scores_gemma":[0.9377033,0.002497487,0.05644261,0.002705208,0.0005961838,0.000007683585,0.000001206006,0.0000180504,0.00002828093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3210322,"threshold_uncertainty_score":0.9999557,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4414188572","doi":"10.53759/7669/jmc202505153","title":"An Effective Content Based Image Retrieval Using Multi Feature Fusion Algorithm with Optimized Retrieval Technique of Soft Computing Approach","year":2025,"lang":"en","type":"article","venue":"Journal of Machine and Computing","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Image retrieval; Pattern recognition (psychology); Content-based image retrieval; Feature (linguistics); Fuzzy logic; Soft computing; Image fusion; Feature extraction; Adaptability","authors":[{"name":"N Pushpalatha","is_ca":false},{"name":"Sumendra Yogarayan","is_ca":false},{"name":"A Selvi","is_ca":true},{"name":"Gunapriya Devarajan","is_ca":false},{"name":"Abdul Razak","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01583764492158614,"gpt":0.2834559137680714,"spread":0.2676182688464853,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002392573,0.0002740438,0.000639882,0.0004232059,0.0002773555,0.0001705707,0.0005836285,0.000150579,6.464911e-7],"category_scores_gemma":[0.0001651026,0.0002012841,0.0001563393,0.0009236069,0.0001303121,0.00050282,0.0002224595,0.0006793607,5.73095e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000105324,"about_ca_system_score_gemma":0.0001726002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001871113,"about_ca_topic_score_gemma":8.18783e-8,"domain_scores_codex":[0.9978203,0.0004202169,0.0006716867,0.0003358673,0.000459591,0.0002923785],"domain_scores_gemma":[0.9973657,0.0003118749,0.001022602,0.0003167962,0.0008503126,0.0001327692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001699631,0.001523985,0.003533135,0.0005650516,0.0002902001,0.00007867521,0.001044627,0.002006954,0.8119635,0.0005735751,0.00002125766,0.1766994],"study_design_scores_gemma":[0.001633672,0.0004762724,0.002037378,0.0004430283,0.00005012911,0.0001951782,0.0001232778,0.7232758,0.2715579,0.00002999901,0.000009191118,0.000168201],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04287568,0.0005572621,0.9556952,0.0001269318,0.0001089594,0.0005040257,0.000003418556,0.00009202019,0.00003649518],"genre_scores_gemma":[0.3445199,0.000007239049,0.6553124,0.000086401,0.00005395833,2.802287e-7,0.000002161353,0.00001057091,0.000007155812],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7212688,"threshold_uncertainty_score":0.8208126,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4414374699","doi":"10.53759/7669/jmc202505209","title":"A Smart Shopping System for Modern E-Commerce Applications","year":2025,"lang":"en","type":"article","venue":"Journal of Machine and Computing","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Product (mathematics); Convergence (economics); Quality (philosophy); Adversarial system; Key (lock); Optimization problem; Purchasing; Scale (ratio); Noise (video); Variation (astronomy)","authors":[{"name":"P. Jyothi","is_ca":false},{"name":"Divya Kumari Tankala","is_ca":false},{"name":"Rajesh Kumar A","is_ca":true},{"name":"Nagarjuna Reddy S","is_ca":false},{"name":"Nagendar Yamsani","is_ca":false},{"name":"Jyotsna Devi Kosuru S N V","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01305472930926018,"gpt":0.2547379537675233,"spread":0.2416832244582631,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004490221,0.00009202885,0.0002039907,0.0004071157,0.0003491078,0.0001114127,0.0001906536,0.00005330839,0.00000160418],"category_scores_gemma":[0.00004494004,0.00008134278,0.00007001247,0.0004105361,0.00003310398,0.00022062,0.0001192786,0.0001959291,0.000001962111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001877664,"about_ca_system_score_gemma":0.00001769431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003133152,"about_ca_topic_score_gemma":0.00001129625,"domain_scores_codex":[0.9992892,0.000004622578,0.0004057962,0.0001000665,0.00006889681,0.0001314229],"domain_scores_gemma":[0.9991924,0.00009602768,0.0003450965,0.0001086135,0.0002518937,0.00000597671],"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":[0.00003618576,0.0001121025,0.0634078,0.0008257157,0.0001977806,0.00000401671,0.00004759154,0.0002818021,0.0008389224,0.5912454,0.004107475,0.3388952],"study_design_scores_gemma":[0.004515691,0.00006679922,0.02280315,0.00165283,0.0007314714,0.0001516729,0.003281431,0.6239466,0.0001552723,0.04534524,0.2967012,0.0006486677],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1736848,0.0007575733,0.8025088,0.0106551,0.0002831178,0.000292045,0.000001750702,0.0001071581,0.01170967],"genre_scores_gemma":[0.9949353,0.000004284894,0.002768333,0.001807252,0.0004031291,0.000006612018,0.000004121812,0.000008441364,0.00006248334],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8212505,"threshold_uncertainty_score":0.3317063,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4406019798","doi":"10.53759/7669/jmc202505001","title":"Efficient and Accurate Traffic Sign Detection Leveraging YOLOv8: A Cutting-Edge Deep Learning Framework","year":2024,"lang":"en","type":"article","venue":"Journal of Machine and Computing","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Computer science; Sign (mathematics); Deep learning; Artificial intelligence; Traffic sign; Computer vision; Mathematics","authors":[{"name":"Gunji Sreenivasulu","is_ca":false},{"name":"H. N. Lakshmi","is_ca":false},{"name":"Muni Kumari T","is_ca":false},{"name":"P. Anjaiah","is_ca":true},{"name":"A. Suresh","is_ca":false},{"name":"J. Avanija","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01204133315195603,"gpt":0.268863493785661,"spread":0.2568221606337049,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005378549,0.0001332249,0.0001798763,0.0001598726,0.0003517948,0.0003144729,0.0002038222,0.00004531709,0.000001122209],"category_scores_gemma":[0.00008520587,0.0001124964,0.00005730419,0.0004435909,0.00002843219,0.0001653742,0.0001791586,0.0007596317,0.000002031304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003085953,"about_ca_system_score_gemma":0.00001847119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000130469,"about_ca_topic_score_gemma":5.507536e-7,"domain_scores_codex":[0.9989254,0.00009069413,0.0003543852,0.000251349,0.0001698128,0.0002083283],"domain_scores_gemma":[0.9988925,0.0006309016,0.0002215635,0.00009953248,0.00005817351,0.00009727912],"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":[0.000004056324,0.00001003491,0.00007145807,0.00002110865,0.00001461742,0.000028388,0.001171604,0.3603535,0.0004687729,0.0007033784,0.000003806804,0.6371493],"study_design_scores_gemma":[0.0001218721,0.0001084267,0.0007773577,0.0001966661,0.00001558051,0.0007357824,0.00007359299,0.9957968,0.0001253071,0.00136779,0.0005665057,0.0001143112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3911503,0.003487094,0.6046737,0.0003679258,0.0001856912,0.00004111382,6.366556e-8,0.00006891842,0.00002514238],"genre_scores_gemma":[0.9628434,0.00009030855,0.03668467,0.00008381956,0.0002764279,6.825525e-7,1.2602e-7,0.00001158843,0.000008976262],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.637035,"threshold_uncertainty_score":0.4587471,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4414206936","doi":"10.53759/7669/jmc202505195","title":"Hybrid Fuzzy Neural Systems for Real Time Decision Making in Autonomous Vehicles","year":2025,"lang":"en","type":"article","venue":"Journal of Machine and Computing","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Fuzzy logic; Process (computing); Artificial neural network; Variety (cybernetics); Fuzzy control system; Neuro-fuzzy; Function (biology)","authors":[{"name":"R. Indhumathi","is_ca":false},{"name":"M. Jeyalakshmi","is_ca":true},{"name":"N. Hemalatha","is_ca":false},{"name":"Anurag Shrivastava","is_ca":false},{"name":"Heba Abdul-Jaleel Al-Asady","is_ca":false},{"name":"Kanchan Yadav","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.005628774387879456,"gpt":0.2431778608244808,"spread":0.2375490864366013,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003559246,0.00006931697,0.0001627212,0.0002207889,0.00003915089,0.00005021614,0.0000795899,0.00002196889,3.400829e-7],"category_scores_gemma":[0.000015497,0.00006252778,0.00003996865,0.00006132836,0.000005650423,0.00006965965,0.00003388302,0.0001200947,2.017159e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003796753,"about_ca_system_score_gemma":0.000006769842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000598723,"about_ca_topic_score_gemma":0.000001203266,"domain_scores_codex":[0.9994419,0.00001427338,0.0003267504,0.00005729533,0.00006112004,0.00009866882],"domain_scores_gemma":[0.9997393,0.0001105568,0.00006556579,0.00004365782,0.00002206367,0.00001878054],"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":[0.00005067196,0.00002255964,0.001345032,0.0001654991,0.00004872268,0.00002865105,0.00008626231,0.1926152,0.0004350722,0.0009289865,0.01141128,0.7928621],"study_design_scores_gemma":[0.0003955658,0.00004123,0.004884843,0.0003318118,0.00001349584,0.00003667618,0.0000204196,0.99265,0.00002752582,0.0002580167,0.001288294,0.00005206612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6711189,0.001384843,0.3248369,0.00005692336,0.0004498864,0.00012,0.000001719998,0.0003104421,0.001720309],"genre_scores_gemma":[0.9963745,0.0001247931,0.003366611,0.00003103497,0.00008159501,8.27329e-7,5.541998e-7,0.000007239069,0.00001288486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8000348,"threshold_uncertainty_score":0.2549809,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}