{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":8,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":8,"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":"2594f8f99907","filters":{"venue":"The International Arab Journal of Information Technology"}},"results":[{"id":"W4212924230","doi":"10.34028/iajit/19/2/11","title":"An Efficient Intrusion Detection Framework Based on Embedding Feature Selection and Ensemble Learning Technique","year":2022,"lang":"en","type":"article","venue":"The International Arab Journal of Information Technology","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":24,"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; Intrusion detection system; False positive rate; Feature selection; Boosting (machine learning); Artificial intelligence; Machine learning; Ensemble learning; Word error rate; Data mining; Feature (linguistics); Gradient boosting; Anomaly-based intrusion detection system; Network security; Binary classification; Pattern recognition (psychology); Support vector machine; Computer security; Random forest","authors":[{"name":"Fawaz Mokbal","is_ca":false},{"name":"Dan Wang","is_ca":false},{"name":"M. O. M. Osman","is_ca":false},{"name":"Ping Yang","is_ca":false},{"name":"Saeed Hamood Alsamhi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.003883803912945072,"gpt":0.2290534320307979,"spread":0.2251696281178528,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001130595,0.0008744781,0.001509431,0.001341368,0.0004030389,0.0006144569,0.001089644,0.0007160416,0.0006462076],"category_scores_gemma":[0.001177063,0.0003012924,0.001212787,0.001109225,0.0002315508,0.0009619311,0.0006856828,0.0009198055,0.0003220212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003115596,"about_ca_system_score_gemma":0.0005910086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002927223,"about_ca_topic_score_gemma":0.002360648,"domain_scores_codex":[0.9991711,0.0001732452,0.00005230497,0.0001777241,0.000327643,0.00009796808],"domain_scores_gemma":[0.9995746,0.0001018439,0.00004585525,0.00004828558,0.0002060349,0.0000233685],"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":[0.0001442606,0.0002456793,0.004885201,0.00007281831,0.0003004906,0.0002277621,0.00009008442,0.2520648,0.01861824,0.004755175,0.00441217,0.7141833],"study_design_scores_gemma":[0.000004980468,0.0000646394,0.0006758827,0.000004525419,0.00002772134,0.0000890289,0.000007048453,0.994984,0.002232438,0.001064592,0.0008359847,0.000009140264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0172516,0.0004421558,0.9807268,0.0001027834,0.00005878893,0.00003919195,0.00005180857,0.0007761772,0.0005507914],"genre_scores_gemma":[0.5532177,0.0008301632,0.4415439,0.0001801255,0.0001614433,0.0001969178,0.0006346347,0.00007551564,0.003159669],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002927223,"threshold_uncertainty_score":0.00597924,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4377200874","doi":"10.34028/iajit/20/3a/9","title":"A Comparative Study of Different Pre-Trained Deep Learning Models and Custom CNN for Pancreatic Tumor Detection","year":2023,"lang":"en","type":"article","venue":"The International Arab Journal of Information Technology","topic":"AI in cancer detection","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Deep learning; Artificial intelligence; Machine learning; Computer architecture","authors":[{"name":"Muhammed Talha Zavalsiz","is_ca":false},{"name":"Sleiman Alhajj","is_ca":false},{"name":"Kashfia Sailunaz","is_ca":true},{"name":"Tansel Özyer","is_ca":false},{"name":"Reda Alhajj","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02183243168160378,"gpt":0.275247938828781,"spread":0.2534155071471773,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001109557,0.001440985,0.0006966474,0.0009817895,0.0002776771,0.0009390599,0.001225793,0.001010906,0.001636216],"category_scores_gemma":[0.004170977,0.0003503159,0.0007615762,0.00057856,0.0002770054,0.001503875,0.0005799041,0.000942643,0.0006629223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001026876,"about_ca_system_score_gemma":0.0008917854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01558006,"about_ca_topic_score_gemma":0.01368771,"domain_scores_codex":[0.9993672,0.00008595754,0.0000483371,0.0001727015,0.0001834273,0.0001424029],"domain_scores_gemma":[0.9987705,0.000425333,0.00009192472,0.0001618763,0.0004688565,0.00008147241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003438603,0.0007695941,0.02044702,0.000976962,0.0006325071,0.0007340682,0.0001276958,0.3372841,0.01975289,0.002089878,0.01454359,0.5992031],"study_design_scores_gemma":[0.00004269698,0.0006206899,0.005249883,0.00007594273,0.0001548905,0.0002611275,0.00006393343,0.9752535,0.01482603,0.0007016837,0.002713532,0.00003610114],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8153852,0.01307253,0.1390246,0.001060755,0.001395694,0.0002510854,0.002108436,0.007703041,0.01999863],"genre_scores_gemma":[0.9450955,0.002831205,0.04028839,0.0003137213,0.0001213407,0.00008775239,0.003767195,0.000249536,0.00724534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01558006,"threshold_uncertainty_score":0.03097874,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3094131433","doi":"10.34028/iajit/17/6/6","title":"An Investigative Analysis on Finding Patterns in Co-Author and Co-Institution Networks for LIDAR Research","year":2020,"lang":"en","type":"article","venue":"The International Arab Journal of Information Technology","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Institute for Information and Communications Technology Promotion; Iran Telecommunication Research Center; Ministry of Science and ICT, South Korea; Yeungnam University","keywords":"Betweenness centrality; Social network analysis; Institution; Position (finance); China; Closeness; Library science; Centrality; Political science; Descriptive statistics; Set (abstract data type); Regional science; Computer science; Operations research; Data science; Geography; World Wide Web; Business; Law; Statistics; Engineering","authors":[{"name":"Imran Ashraf","is_ca":false},{"name":"Soojung Hur","is_ca":false},{"name":"Yongwan Park","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1025886792132026,"gpt":0.3435959753799383,"spread":0.2410072961667357,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.009575955,0.0003818144,0.0003637862,0.02252641,0.002064383,0.003496682,0.0007844925,0.0006693981,0.002936166],"category_scores_gemma":[0.0362995,0.0002198318,0.0006117331,0.0318202,0.001161853,0.005135151,0.001600468,0.0005697626,0.000609951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001803112,"about_ca_system_score_gemma":0.001453117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001797332,"about_ca_topic_score_gemma":0.004080805,"domain_scores_codex":[0.9912142,0.003663689,0.0009665255,0.001190535,0.002527574,0.0004374011],"domain_scores_gemma":[0.9351456,0.04739138,0.008952492,0.003035307,0.004712065,0.0007631539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001937627,0.0001447529,0.5212021,0.0037936,0.0003353925,0.004232452,0.08732901,0.001748307,0.004532706,0.06856189,0.02549886,0.2824271],"study_design_scores_gemma":[0.00001894328,0.0002273737,0.4556944,0.00387865,0.0003907591,0.005662706,0.1928732,0.01698964,0.007624212,0.04475751,0.2717163,0.000166404],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8743806,0.01700404,0.04066384,0.005907992,0.000385327,0.0007252492,0.01151242,0.0002492869,0.04917131],"genre_scores_gemma":[0.9603453,0.005053636,0.02429767,0.0002811408,0.0001937916,0.0004780014,0.004171539,0.0000526769,0.005126324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9774736,"threshold_uncertainty_score":0.05064309,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4313004348","doi":"10.34028/iajit/20/1/2","title":"On Satellite Imagery of Land Cover Classification for Agricultural Development","year":2022,"lang":"en","type":"article","venue":"The International Arab Journal of Information Technology","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Land cover; Computer science; Cluster analysis; Remote sensing; Satellite imagery; Fuzzy logic; Vegetation (pathology); Land use; Satellite; Fuzzy clustering; Segmentation; Cover (algebra); Geography; Artificial intelligence; Ecology","authors":[{"name":"Ali Alzahrani","is_ca":true},{"name":"Md. Al-Amin Bhuiyan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01116160511542641,"gpt":0.2054233810664855,"spread":0.1942617759510591,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002243907,0.0004169804,0.0002166275,0.002084751,0.0003141027,0.0005486973,0.0002311934,0.0002970262,0.001328976],"category_scores_gemma":[0.000573988,0.000089623,0.0003332496,0.002463535,0.0001561605,0.0003336326,0.0002127256,0.0002160415,0.0007864839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004128131,"about_ca_system_score_gemma":0.0004479992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01679204,"about_ca_topic_score_gemma":0.02768937,"domain_scores_codex":[0.9997726,0.00003517875,0.00001408273,0.00004991742,0.0001060454,0.000022159],"domain_scores_gemma":[0.9998271,0.00001882487,0.0000273413,0.00002558277,0.00008868871,0.00001260841],"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":[0.0003262342,0.0002234139,0.03845321,0.0004062619,0.0001462773,0.0003466558,0.0003647707,0.03333861,0.06860042,0.002215035,0.01169059,0.8438886],"study_design_scores_gemma":[0.00003040288,0.0003205514,0.3795508,0.0001641883,0.000209931,0.0009172629,0.001807201,0.521108,0.05984562,0.003605819,0.03236451,0.00007573251],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7738405,0.002007787,0.1836771,0.0006350006,0.0002331669,0.0007836155,0.00978756,0.002465559,0.02656966],"genre_scores_gemma":[0.8308017,0.0008164555,0.1527822,0.000101975,0.00004312707,0.0001341465,0.00961946,0.00005308025,0.005647877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01679204,"threshold_uncertainty_score":0.03338856,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4394983157","doi":"10.34028/iajit/21/3/5","title":"FPGA based Flexible Implementation of Light Weight Inference on Deep Convolutional Neural Networks","year":2024,"lang":"en","type":"article","venue":"The International Arab Journal of Information Technology","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Field-programmable gate array; Convolutional neural network; Inference; Computer science; Computer architecture; Deep neural networks; Artificial intelligence; Artificial neural network; Parallel computing; Embedded system","authors":[{"name":"Shefa Dawwd","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.005508000658289946,"gpt":0.2450666000922363,"spread":0.2395585994339464,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001819061,0.0006237318,0.0002619397,0.0004216324,0.0002020431,0.0005837443,0.001254326,0.0002691803,0.008068373],"category_scores_gemma":[0.0004450402,0.0002432913,0.0002285413,0.0003284665,0.0001578376,0.0005671408,0.0003724754,0.0003959509,0.001455459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005678878,"about_ca_system_score_gemma":0.0005419886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004982253,"about_ca_topic_score_gemma":0.006487117,"domain_scores_codex":[0.9998351,0.00001553532,0.00001047058,0.00004341832,0.00005716594,0.00003816184],"domain_scores_gemma":[0.9998518,0.00003441346,0.0000143233,0.00004174326,0.00004753058,0.00001008645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001046225,0.0002329285,0.003273269,0.0005683547,0.0001707362,0.0006375656,0.0001697303,0.09499901,0.1199826,0.01185407,0.0229581,0.7441075],"study_design_scores_gemma":[0.0002224898,0.0005489825,0.003359637,0.00007668274,0.0000847571,0.0005101159,0.00007498135,0.7983606,0.1619323,0.00456327,0.03021023,0.00005592019],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1497655,0.001322983,0.7935056,0.000322646,0.0003332398,0.0002555094,0.00110816,0.02682155,0.0265649],"genre_scores_gemma":[0.7794872,0.0003476343,0.2087578,0.0001783712,0.00003467332,0.000155382,0.001223633,0.0001979167,0.009617333],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008068373,"threshold_uncertainty_score":0.02699143,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415905037","doi":"10.34028/iajit/22/6/1","title":"Strategic Optimization of Convergence and Energy in Federated Learning Systems","year":2025,"lang":"en","type":"article","venue":"The International Arab Journal of Information Technology","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Convergence (economics); Raw data; Carbon footprint; Testbed; Efficient energy use; Information exchange; MNIST database; Process (computing); Green computing","authors":[{"name":"Ghassan Samara","is_ca":false},{"name":"Raed Alazaidah","is_ca":false},{"name":"Mohammad Aljaidi","is_ca":false},{"name":"Mahmoud Odeh","is_ca":false},{"name":"Alaa Elhilo","is_ca":false},{"name":"Sattam Almatarneh","is_ca":false},{"name":"Mo’ath Alluwaici","is_ca":false},{"name":"Essam Al-Daoud","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0123272465332334,"gpt":0.2427627449560217,"spread":0.2304354984227883,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003306968,0.001537629,0.001832576,0.0007081659,0.0009231094,0.001649467,0.001785334,0.001825625,0.001895246],"category_scores_gemma":[0.009775938,0.0006635964,0.0007857838,0.00052945,0.001519551,0.002001547,0.001885935,0.001510308,0.0003607135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001992227,"about_ca_system_score_gemma":0.001933588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009615934,"about_ca_topic_score_gemma":0.005997444,"domain_scores_codex":[0.9989403,0.0003448295,0.00005667161,0.0002765682,0.0001437255,0.000237919],"domain_scores_gemma":[0.9959621,0.002447928,0.0003641705,0.0003035249,0.0007166584,0.0002056773],"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":[0.00005832128,0.00002485137,0.0004959774,0.00002180134,0.00001661169,0.00003418345,0.00002081561,0.9908607,0.0001906821,0.002122849,0.0002379423,0.005915229],"study_design_scores_gemma":[0.000006711541,0.00002367987,0.0000816891,0.000004964729,0.000004693828,0.000007780306,0.000008431407,0.9974267,0.0001519159,0.002203911,0.00007650218,0.000003060382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1995662,0.0008324459,0.7912389,0.001013051,0.0001003432,0.0001473433,0.0002474585,0.001107535,0.005746731],"genre_scores_gemma":[0.9722728,0.0001252439,0.02544617,0.000134119,0.00001477705,0.00009998732,0.0001108914,0.00004179364,0.00175434],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009615934,"threshold_uncertainty_score":0.01911992,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415907908","doi":"10.34028/iajit/22/6/5","title":"Malware Detection through Memory Forensics and Windows Event Log Analysis","year":2025,"lang":"en","type":"article","venue":"The International Arab Journal of Information Technology","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Malware; Event (particle physics); Code (set theory); Cryptovirology; Identification (biology); Cybercrime","authors":[{"name":"Dinesh Patil","is_ca":false},{"name":"Akshaya Prabhu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.004690185249306763,"gpt":0.250424839135524,"spread":0.2457346538862173,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005258521,0.0005835863,0.0004201643,0.004671298,0.0003251025,0.0006633938,0.0005079919,0.0005364059,0.0005733772],"category_scores_gemma":[0.002253884,0.0001313296,0.0003887935,0.001071293,0.0002587166,0.001263552,0.000721895,0.0003318878,0.0005474261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002104731,"about_ca_system_score_gemma":0.0003954851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001259389,"about_ca_topic_score_gemma":0.001493099,"domain_scores_codex":[0.9995477,0.00006347078,0.00003198687,0.00009456217,0.00018505,0.00007724625],"domain_scores_gemma":[0.9990958,0.0002317404,0.0002461665,0.0001539049,0.0002267377,0.00004567402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007727125,0.000714554,0.0608408,0.0003314465,0.0001153902,0.001494446,0.0003668928,0.01547617,0.07177854,0.001991602,0.005830132,0.8402873],"study_design_scores_gemma":[0.00004134973,0.0007042237,0.08836196,0.0001870551,0.0001500167,0.004160658,0.0008174558,0.7115017,0.1776415,0.005872738,0.01045141,0.0001098781],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8365016,0.001458739,0.1483404,0.0002968379,0.00008615779,0.0002957219,0.001734148,0.006314199,0.004972218],"genre_scores_gemma":[0.9499404,0.0004227789,0.04708083,0.00003795246,0.00004167452,0.00006520101,0.001440617,0.00004996437,0.0009205753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004671298,"threshold_uncertainty_score":0.002780974,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4413497654","doi":"10.34028/iajit/22/5/1","title":"Exploring the Intersection of Information Theory and Machine Learning","year":2025,"lang":"en","type":"article","venue":"The International Arab Journal of Information Technology","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"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; Intersection (aeronautics); Artificial intelligence; Human–computer interaction; Machine learning; Transport engineering","authors":[{"name":"Yousef Jaradat","is_ca":false},{"name":"Mohammad Masoud","is_ca":false},{"name":"Ahmad Manasrah","is_ca":false},{"name":"Mohammad Alia","is_ca":false},{"name":"Khalid Suwais","is_ca":false},{"name":"Sally Almanasra","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01605510206480572,"gpt":0.2307704441606774,"spread":0.2147153420958717,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01589937,0.001594472,0.002540653,0.005203545,0.001455118,0.007798466,0.00240645,0.003301774,0.002204898],"category_scores_gemma":[0.03845114,0.0009052007,0.00164342,0.003497999,0.01465506,0.01622665,0.005847851,0.006597543,0.0004666223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003952095,"about_ca_system_score_gemma":0.003082994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002223399,"about_ca_topic_score_gemma":0.001345893,"domain_scores_codex":[0.9912274,0.005149504,0.0003860977,0.0009252653,0.001961059,0.0003507807],"domain_scores_gemma":[0.9385062,0.05285438,0.001730356,0.00445307,0.001882877,0.000573102],"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":[0.00002637176,0.00002987754,0.0009978749,0.0002973604,0.0000822783,0.00006959924,0.0001765267,0.01699958,0.0003412433,0.9503307,0.001004571,0.02964403],"study_design_scores_gemma":[0.000005371363,0.00002682339,0.0001832268,0.00008397924,0.00001092795,0.00003374683,0.0000405445,0.03025845,0.0002033439,0.9667889,0.0023441,0.00002045736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01873013,0.02290152,0.9151105,0.01922254,0.0004487194,0.00006920499,0.0003104423,0.0002653432,0.02294154],"genre_scores_gemma":[0.7342884,0.02898805,0.2242761,0.004618599,0.003828708,0.0004061153,0.0004861286,0.0002515358,0.002856401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01589937,"threshold_uncertainty_score":0.08408493,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}