{"meta":{"query_hash":"ea979cf91b79","filters":{"venue":"Computer Science & IT Research Journal"},"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/ea979cf91b79","api":"https://metacan.xera.ac/api/v1/cohort?venue=Computer+Science+%26+IT+Research+Journal"},"results":[{"id":"W4401053250","doi":"10.51594/csitrj.v5i7.1358","title":"Role of pandemic in driving adoption of artificial intelligence in healthcare industry","year":2024,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Triage; Health care; Pandemic; Artificial intelligence; Psychology; Population; Preference; Neglect; Sample (material); Coronavirus disease 2019 (COVID-19); Medicine; Political science; Computer science; Environmental health; Psychiatry; Disease; Pathology; Economics","score_opus":0.3183185432312885,"score_gpt":0.5334858567153423,"score_spread":0.21516731348405382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401053250","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918493,0.000225152,0.00020463153,0.0023647428,0.000014738473,0.000024445926,0.00005158961,0.000003429653,0.0052619698],"genre_scores_gemma":[0.99942505,0.00011154314,0.00010486336,0.00017744608,0.0000061592364,0.0000049204905,0.00001601083,0.000001505062,0.00015239103],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9959632,0.00200072,0.0003628574,0.00031038525,0.0007757644,0.0005869996],"domain_scores_gemma":[0.9640626,0.017393187,0.011049231,0.0011238365,0.0028755274,0.0034955991],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005061593,0.0001332527,0.00015823028,0.0006708052,0.0014727406,0.002736056,0.00045496816,0.0009741348,0.0038986132],"category_scores_gemma":[0.031988427,0.00019463192,0.00021863883,0.00084146165,0.0016683771,0.0013573058,0.0015085728,0.0019228196,0.00026412023],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007067318,0.00009322599,0.9758818,0.000043220894,0.000025915662,0.0002470786,0.011305936,0.00012133027,0.00018548302,0.0010438949,0.00057727913,0.01040408],"study_design_scores_gemma":[0.0000056025747,0.000080176025,0.9620566,0.00012674004,0.000017305614,0.00026184294,0.033240475,0.0008992083,0.00013127999,0.0005150553,0.0026439643,0.000021798978],"about_ca_topic_score_codex":0.033243913,"about_ca_topic_score_gemma":0.031249806,"teacher_disagreement_score":0.033243913,"about_ca_system_score_codex":0.0021558714,"about_ca_system_score_gemma":0.0037298135,"threshold_uncertainty_score":0.066100836},"labels":[],"label_agreement":null},{"id":"W4402096237","doi":"10.51594/csitrj.v5i8.1492","title":"Assessing the transformative impact of cloud computing on software deployment and management","year":2024,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"TD Bank Group","funders":"","keywords":"Software deployment; Cloud computing; Transformative learning; Computer science; Software; Software as a service; Software engineering; Software development; Operating system; Sociology","score_opus":0.07026905720929764,"score_gpt":0.41329610408723383,"score_spread":0.34302704687793617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402096237","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.113524064,0.7977102,0.0125842085,0.020858508,0.0012776172,0.0003277727,0.00063641,0.00013396612,0.05294725],"genre_scores_gemma":[0.4015539,0.5845964,0.008543524,0.0023028094,0.0005480141,0.00017207855,0.00045087375,0.00004470353,0.0017877466],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9923424,0.0029100005,0.00059229217,0.0003156434,0.0032185512,0.0006210218],"domain_scores_gemma":[0.9720935,0.015567931,0.0028130508,0.0005220117,0.008290099,0.00071333867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007913358,0.00047689077,0.0004374224,0.0025720175,0.00045456068,0.0032956302,0.0006339167,0.0006357824,0.002149212],"category_scores_gemma":[0.02801735,0.00022291335,0.00077386963,0.0030983754,0.0007074498,0.004948528,0.0011862189,0.0010848794,0.0003636835],"study_design_candidate":"not_applicable","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":[0.00022619337,0.00010945833,0.038170382,0.023348736,0.00068836525,0.0005280669,0.0018034335,0.008422598,0.0035681436,0.04241081,0.017597148,0.86312664],"study_design_scores_gemma":[0.000058388807,0.0016549324,0.1446807,0.030332426,0.0015791741,0.0013093498,0.007959814,0.010948012,0.006389333,0.030971192,0.76394874,0.00016805354],"about_ca_topic_score_codex":0.0056414646,"about_ca_topic_score_gemma":0.008422056,"teacher_disagreement_score":0.007913358,"about_ca_system_score_codex":0.0031249346,"about_ca_system_score_gemma":0.00599346,"threshold_uncertainty_score":0.04185033},"labels":[],"label_agreement":null},{"id":"W4402096273","doi":"10.51594/csitrj.v5i8.1491","title":"Developing crossplatform software applications to enhance compatibility across devices and systems","year":2024,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"TD Bank Group","funders":"","keywords":"Compatibility (geochemistry); Computer science; Systems engineering; Software engineering; Engineering","score_opus":0.13893338721154538,"score_gpt":0.48565218315351916,"score_spread":0.34671879594197375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402096273","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059908655,0.00060514396,0.8526541,0.0010179597,0.0005247751,0.0014710504,0.00034481788,0.059848055,0.02362552],"genre_scores_gemma":[0.16733955,0.0010285518,0.7816279,0.0016376668,0.00018344348,0.0012138648,0.0025947029,0.024068842,0.020305518],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99668,0.0006936808,0.00034747855,0.0005408469,0.0013331474,0.00040476784],"domain_scores_gemma":[0.98929554,0.0027119778,0.0009481073,0.0031346977,0.0031235411,0.0007861464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047146734,0.0020511514,0.0006152918,0.001715529,0.00081255514,0.0027626744,0.0029587848,0.0016114233,0.006621644],"category_scores_gemma":[0.020161675,0.0014971487,0.0015459432,0.0007249833,0.00092801295,0.0047320575,0.006052821,0.0037672084,0.0062422147],"study_design_candidate":"not_applicable","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":[0.00073284697,0.0017785939,0.017961085,0.0019834847,0.00041233454,0.004184624,0.0090960115,0.030261327,0.15753166,0.02900978,0.05881577,0.6882325],"study_design_scores_gemma":[0.00042039357,0.0017299041,0.020026784,0.0015251813,0.00041981944,0.005150969,0.0020603058,0.16151468,0.18040521,0.047621615,0.57862675,0.0004983858],"about_ca_topic_score_codex":0.0012031925,"about_ca_topic_score_gemma":0.0018142868,"teacher_disagreement_score":0.006621644,"about_ca_system_score_codex":0.00056783744,"about_ca_system_score_gemma":0.0015248401,"threshold_uncertainty_score":0.024933815},"labels":[],"label_agreement":null},{"id":"W4408074120","doi":"10.51594/csitrj.v6i2.1818","title":"AI and data-driven innovations in healthcare: Enhancing cancer detection, workforce optimization, and comprehensive care for people living with HIV","year":2025,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","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":"Child, Adolescent and Family Mental Health","funders":"","keywords":"Workforce; Health care; Human immunodeficiency virus (HIV); Cancer; Nursing; Medicine; Business; Political science; Family medicine","score_opus":0.0725394133560295,"score_gpt":0.36768898883633977,"score_spread":0.2951495754803103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408074120","genre_codex":"commentary","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17164358,0.05499981,0.21183008,0.44989657,0.0032488904,0.0003981096,0.00123515,0.0003371213,0.106410705],"genre_scores_gemma":[0.931237,0.027691532,0.03122217,0.004789596,0.00096433435,0.00010693425,0.00020340527,0.000025994861,0.0037590566],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99854255,0.0009366858,0.000051687133,0.00008993624,0.00027686334,0.000102277794],"domain_scores_gemma":[0.99320376,0.0053505707,0.0004839913,0.00015973144,0.00053952157,0.00026236844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036984135,0.00033628833,0.000210232,0.0012383154,0.00069979654,0.0032487526,0.0006668224,0.0010833101,0.002637558],"category_scores_gemma":[0.013214381,0.0001583376,0.00039038237,0.0015146963,0.0014076439,0.0024956593,0.0020184154,0.001646378,0.00022540236],"study_design_candidate":"not_applicable","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":[0.00019195328,0.00041508043,0.0444702,0.0017468665,0.00023433074,0.00033907162,0.0013189724,0.055318873,0.0011846839,0.38830516,0.035042074,0.47143278],"study_design_scores_gemma":[0.0000677554,0.00033002577,0.027697597,0.0028466177,0.00018833457,0.00045794708,0.0054767844,0.1680432,0.0033657718,0.6287158,0.1626693,0.00014086223],"about_ca_topic_score_codex":0.004067367,"about_ca_topic_score_gemma":0.005804471,"teacher_disagreement_score":0.004067367,"about_ca_system_score_codex":0.0025555342,"about_ca_system_score_gemma":0.0041174404,"threshold_uncertainty_score":0.019559264},"labels":[],"label_agreement":null},{"id":"W4409209934","doi":"10.51594/csitrj.v6i3.1873","title":"Cybersecurity and DevOps in Cloud-Based Telecom and BI Systems: Advancing Risk Mitigation Strategies","year":2025,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Information and Cyber Security","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":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"DevOps; Cloud computing; Computer security; Telecommunications; Business; Computer science; Operating system","score_opus":0.0172329149505852,"score_gpt":0.33037627354810917,"score_spread":0.31314335859752396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409209934","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22379829,0.031182485,0.54849327,0.06048824,0.0007109,0.0005014607,0.00012415834,0.0006082715,0.13409284],"genre_scores_gemma":[0.87389964,0.016709415,0.10152534,0.0010488658,0.00022167241,0.0001652932,0.00011508761,0.00008465473,0.0062299403],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969273,0.001309577,0.00017052493,0.0002648835,0.0009345328,0.0003931456],"domain_scores_gemma":[0.99075234,0.0035381755,0.0015432059,0.0010678893,0.0019595933,0.0011387473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056173485,0.0011488857,0.0003622499,0.0025049034,0.002101419,0.008346732,0.0013912871,0.0018125379,0.0018384745],"category_scores_gemma":[0.008381032,0.00046629945,0.0005298541,0.0015230464,0.0034866403,0.0102654,0.007432445,0.0031239975,0.00038346686],"study_design_candidate":"not_applicable","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":[0.000085914304,0.00029924177,0.023917064,0.00082560244,0.00010483403,0.00092985964,0.008946046,0.046581104,0.0059684343,0.53843856,0.007003981,0.36689937],"study_design_scores_gemma":[0.000030897896,0.00058011094,0.01552799,0.0029170576,0.00011197965,0.0016189995,0.029378846,0.23125562,0.011152272,0.44750088,0.25970966,0.00021574496],"about_ca_topic_score_codex":0.0036235582,"about_ca_topic_score_gemma":0.0027436516,"teacher_disagreement_score":0.008346732,"about_ca_system_score_codex":0.0036350174,"about_ca_system_score_gemma":0.0054716123,"threshold_uncertainty_score":0.02970773},"labels":[],"label_agreement":null},{"id":"W4411092512","doi":"10.51594/csitrj.v6i5.1935","title":"Predictive modelling and spatial flow analysis of United States of America crude oil imports","year":2025,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Crude oil; Environmental science; Flow (mathematics); Econometrics; Economics; Natural resource economics; Petroleum engineering; Geology; Mechanics; Physics","score_opus":0.02894711834949038,"score_gpt":0.3469392937631478,"score_spread":0.31799217541365743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411092512","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98567665,0.00017676022,0.009750779,0.00016412414,0.000023546216,0.000028045893,0.0017307925,0.00032854438,0.0021207982],"genre_scores_gemma":[0.99491936,0.00010156584,0.0028708363,0.000009471948,0.000005023725,0.000016850247,0.0014524456,0.000012529518,0.00061186415],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998417,0.000039006467,0.00001081587,0.000045047564,0.000034278746,0.000029034345],"domain_scores_gemma":[0.9993204,0.00034798516,0.00007501133,0.00003711167,0.00020288455,0.000016596132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070130266,0.0004864012,0.00033387222,0.0013794105,0.00027806728,0.0005930066,0.00047266358,0.00046290792,0.0012575327],"category_scores_gemma":[0.0017818308,0.00022444547,0.0008402422,0.0014114918,0.00030826812,0.00041153296,0.00026482475,0.00046455965,0.00021082898],"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":[0.00006691332,0.000059098857,0.024979763,0.000029670387,0.000033888686,0.00009967014,0.000052569525,0.9642976,0.0003849961,0.0005004794,0.00073333335,0.008762118],"study_design_scores_gemma":[0.0000015016217,0.0000071667887,0.0048691607,0.0000046360915,0.0000038497274,0.0000067952938,0.000032582248,0.9945298,0.00023521944,0.00013254343,0.00017238654,0.000004331586],"about_ca_topic_score_codex":0.22514598,"about_ca_topic_score_gemma":0.0939453,"teacher_disagreement_score":0.22514598,"about_ca_system_score_codex":0.0013535061,"about_ca_system_score_gemma":0.00073231454,"threshold_uncertainty_score":0.447671},"labels":[],"label_agreement":null},{"id":"W4413724970","doi":"10.51594/csitrj.v6i7.2000","title":"AI-Driven continuous compliance and threat intelligence model for adaptive GRC in complex digital ecosystems","year":2025,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Network Security and Intrusion Detection","field":"Computer Science","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":"Glycemic Index Laboratories; JDA Software (Canada); Alberta Energy","funders":"","keywords":"Compliance (psychology); Complex adaptive system; Ecosystem; Computer science; Artificial intelligence; Psychology; Ecology; Biology; Social psychology","score_opus":0.14955262853090628,"score_gpt":0.3925803921421376,"score_spread":0.2430277636112313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413724970","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08707505,0.0006361309,0.8347606,0.005422584,0.00015684767,0.00022540058,0.00032487971,0.00054297794,0.07085553],"genre_scores_gemma":[0.93685603,0.0006397069,0.052808464,0.00041828162,0.00008889102,0.00025275623,0.00018234923,0.00004860678,0.008704877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872094,0.0003836547,0.00007578111,0.0002961009,0.00034593572,0.0001774129],"domain_scores_gemma":[0.99708885,0.0014248033,0.00058297993,0.00017768113,0.00052794756,0.00019767959],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016885641,0.0005808679,0.00045920894,0.0011226123,0.0007373298,0.0029961616,0.0014277622,0.001707248,0.0037847636],"category_scores_gemma":[0.004953849,0.00027149066,0.0007934194,0.0007619337,0.002353122,0.0028864283,0.0017140826,0.0019688248,0.000494303],"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":[0.000039943516,0.00013626156,0.0052869455,0.00013420763,0.00006921143,0.00053118425,0.0008943392,0.5002096,0.0017026144,0.4625049,0.0030563714,0.025434421],"study_design_scores_gemma":[0.000008267621,0.00003368163,0.0008570119,0.000030495463,0.000018320874,0.000108404776,0.00015725955,0.874327,0.00020883496,0.12076119,0.0034706404,0.00001879165],"about_ca_topic_score_codex":0.0060469923,"about_ca_topic_score_gemma":0.004091556,"teacher_disagreement_score":0.0060469923,"about_ca_system_score_codex":0.0019576307,"about_ca_system_score_gemma":0.002563214,"threshold_uncertainty_score":0.014203608},"labels":[],"label_agreement":null},{"id":"W4414035765","doi":"10.51594/csitrj.v6i8.2012","title":"Privacy-First security models for AI-integrated identity governance in multi-access cloud and edge environments","year":2025,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Energy; Glycemic Index Laboratories","funders":"","keywords":"Cloud computing; Identity (music); Enhanced Data Rates for GSM Evolution; Computer security; Internet privacy; Corporate governance; Cloud computing security; Computer science; Business; Telecommunications; Operating system","score_opus":0.10653918691766251,"score_gpt":0.4072856183912132,"score_spread":0.3007464314735507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414035765","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012520911,0.0050824657,0.94554687,0.010409891,0.00026490004,0.00013863937,0.00014347499,0.0002420837,0.025650809],"genre_scores_gemma":[0.76749724,0.009897699,0.21288115,0.0024806329,0.00050667516,0.0004861816,0.00031805894,0.00009119383,0.0058411774],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9917223,0.0035845558,0.0007102435,0.0010392896,0.0023518978,0.0005916749],"domain_scores_gemma":[0.98403084,0.008716648,0.0015436828,0.004026774,0.0014113203,0.0002707575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009608005,0.0006190868,0.0007221454,0.001450144,0.0015651218,0.006433812,0.0020208142,0.0029143183,0.0021409316],"category_scores_gemma":[0.01500616,0.00048040322,0.0016155181,0.0014106601,0.00863861,0.014950281,0.004142916,0.005809683,0.0006035796],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000064897263,0.000009505535,0.00014271776,0.00007997996,0.000011457676,0.000030783343,0.00014113002,0.0024873742,0.00016427797,0.9905129,0.00039326635,0.0060200053],"study_design_scores_gemma":[0.000012415997,0.000028995586,0.00015672846,0.00020996321,0.000022911272,0.00015323532,0.00012216019,0.020302674,0.0011874712,0.95941263,0.01836816,0.000022524186],"about_ca_topic_score_codex":0.0011909192,"about_ca_topic_score_gemma":0.00067726494,"teacher_disagreement_score":0.009608005,"about_ca_system_score_codex":0.003947821,"about_ca_system_score_gemma":0.00397256,"threshold_uncertainty_score":0.050812542},"labels":[],"label_agreement":null},{"id":"W4414035811","doi":"10.51594/csitrj.v6i8.2011","title":"Self-Learning autonomous cyber defense agents in AI-empowered security operations","year":2025,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Glycemic Index Laboratories","funders":"","keywords":"Computer security; Computer science; Business","score_opus":0.03942766099948037,"score_gpt":0.36676359807974174,"score_spread":0.3273359370802614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414035811","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06086959,0.0005770467,0.9213504,0.0013538213,0.00005878371,0.00019045104,0.00003189535,0.00087809644,0.014689894],"genre_scores_gemma":[0.77006155,0.00058853737,0.22320552,0.00027393945,0.000034257864,0.00018609407,0.000050023387,0.000093914234,0.005506116],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990527,0.00032857008,0.00007095539,0.00018138044,0.0002643299,0.000102056765],"domain_scores_gemma":[0.99782217,0.0010045333,0.00033624697,0.00037074645,0.00028383045,0.00018243653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021200257,0.00040543926,0.00031460228,0.00045407843,0.00062929565,0.0024788927,0.0013021468,0.0011852283,0.0014653361],"category_scores_gemma":[0.0037437573,0.0004896935,0.00042402078,0.00031489815,0.0027007947,0.0026871096,0.0018121938,0.0013954552,0.0004196465],"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":[0.00009672182,0.00022776097,0.0033711616,0.00020099548,0.00007048879,0.00035667702,0.0014274336,0.55214816,0.009958955,0.3537197,0.0011480049,0.077273935],"study_design_scores_gemma":[0.000032763277,0.00010533989,0.00042881252,0.000057533376,0.000020758167,0.00009331191,0.00017264187,0.8492932,0.0053275004,0.13316976,0.011269292,0.000028988094],"about_ca_topic_score_codex":0.0018094426,"about_ca_topic_score_gemma":0.0017411138,"teacher_disagreement_score":0.0024788927,"about_ca_system_score_codex":0.00088458194,"about_ca_system_score_gemma":0.0017835778,"threshold_uncertainty_score":0.011211932},"labels":[],"label_agreement":null},{"id":"W4414040257","doi":"10.51594/csitrj.v6i8.2013","title":"Resilient infrastructure management systems using real-time analytics and AI-driven disaster preparedness protocols","year":2025,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Glycemic Index Laboratories; JDA Software (Canada)","funders":"","keywords":"Critical infrastructure; Geospatial analysis; Interoperability; Resilience (materials science); Analytics; Emergency management; Critical infrastructure protection; Preparedness; Risk management; Big data","score_opus":0.038806848584699766,"score_gpt":0.3940413549324722,"score_spread":0.3552345063477724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414040257","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0129623,0.081826724,0.8100455,0.016138226,0.0015779391,0.00047043237,0.00042050955,0.0025784331,0.07397998],"genre_scores_gemma":[0.47531107,0.19276693,0.31374407,0.0030025756,0.002083214,0.00093038793,0.0014122574,0.0003528792,0.010396613],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985759,0.00036732657,0.00016959153,0.00017839146,0.0005989946,0.00010969971],"domain_scores_gemma":[0.9972583,0.0013595505,0.00030319998,0.0003000834,0.0006681844,0.00011068821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026582086,0.0010536576,0.00052806776,0.0019142721,0.00048946554,0.0035750854,0.0017507818,0.0013406344,0.002217589],"category_scores_gemma":[0.005086507,0.0003898052,0.00066040404,0.0016953625,0.0013725655,0.0060048876,0.0026454872,0.0019224709,0.00086648157],"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":[0.00005438722,0.000106974905,0.0016562255,0.004000978,0.00023343149,0.00028652526,0.00084349525,0.10258797,0.0077452213,0.4047989,0.018277712,0.45940813],"study_design_scores_gemma":[0.00002774508,0.00024495574,0.0014958429,0.0035950013,0.0001694659,0.0005044107,0.0010758232,0.14648366,0.0090592755,0.2772045,0.559981,0.00015836381],"about_ca_topic_score_codex":0.0013448962,"about_ca_topic_score_gemma":0.00085646316,"teacher_disagreement_score":0.0035750854,"about_ca_system_score_codex":0.0014113582,"about_ca_system_score_gemma":0.0022889813,"threshold_uncertainty_score":0.014058113},"labels":[],"label_agreement":null},{"id":"W4415192037","doi":"10.51594/csitrj.v6i9.2067","title":"Cloud compliance for SMBs: Navigating HIPAA, PCI-DSS and CMMC requirements","year":2025,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University of Edmonton","funders":"","keywords":"Cloud computing; Accountability; Cloud computing security; Corporate governance; Audit; Data breach; Information security standards; Certification; Service (business)","score_opus":0.35297415065607163,"score_gpt":0.4822652739523255,"score_spread":0.12929112329625386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415192037","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6864232,0.0004529541,0.13814068,0.026265286,0.00017122185,0.0022388634,0.0002044888,0.0008615067,0.14524186],"genre_scores_gemma":[0.95432645,0.00016517688,0.03966049,0.0012170044,0.00002009656,0.0002582866,0.00011343891,0.000055097382,0.0041838805],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9770512,0.010519336,0.0012671164,0.00090700586,0.006497252,0.0037581301],"domain_scores_gemma":[0.9868596,0.0035079317,0.0021854935,0.0021029313,0.003738753,0.0016051977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0149818985,0.00038698644,0.00023786422,0.001435915,0.006368991,0.007016355,0.0013425753,0.0037178826,0.0025978028],"category_scores_gemma":[0.02111354,0.0003296778,0.0005997307,0.0017193174,0.0039764754,0.006256799,0.0063054757,0.0026905688,0.0006324668],"study_design_candidate":"not_applicable","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":[0.00024621992,0.001274557,0.08660276,0.0004359687,0.000039856142,0.010459129,0.029610299,0.035736877,0.014592457,0.6665572,0.017805364,0.1366394],"study_design_scores_gemma":[0.0002533765,0.0017890586,0.07770129,0.0022191624,0.000096996155,0.007327272,0.13134986,0.24961475,0.025614204,0.20757577,0.29595736,0.0005009162],"about_ca_topic_score_codex":0.029348,"about_ca_topic_score_gemma":0.037158366,"teacher_disagreement_score":0.029348,"about_ca_system_score_codex":0.009238598,"about_ca_system_score_gemma":0.01766459,"threshold_uncertainty_score":0.07923281},"labels":[],"label_agreement":null},{"id":"W4415192046","doi":"10.51594/csitrj.v6i9.2066","title":"Cybersecurity on a budget: Affordable cloud security tools for SMBs","year":2025,"lang":"en","type":"article","venue":"Computer Science & IT Research Journal","topic":"Cloud Data Security Solutions","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":false,"ca_institutions":"Concordia University of Edmonton","funders":"","keywords":"Cloud computing security; Cloud computing; Guard (computer science); Security service; Security through obscurity; Security information and event management; Phishing; Identity management; Security controls; Security guard","score_opus":0.08142720153010234,"score_gpt":0.40161913411146505,"score_spread":0.3201919325813627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415192046","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23146513,0.004543041,0.21047977,0.07355959,0.0011374253,0.0009589454,0.00048045875,0.0038470123,0.47352856],"genre_scores_gemma":[0.8762222,0.0029899993,0.08816724,0.0027305663,0.00024499328,0.00020678919,0.00037660243,0.00041656956,0.028645104],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99840456,0.00030855194,0.000050862996,0.0001181109,0.0005609685,0.00055705005],"domain_scores_gemma":[0.99777395,0.00035446216,0.00024868656,0.00034832038,0.00045373142,0.00082076783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015882433,0.0005662104,0.00025731415,0.0012687612,0.00250176,0.0063001565,0.0015130521,0.0014509741,0.017991474],"category_scores_gemma":[0.004089252,0.00032559378,0.0004852125,0.0013526317,0.0011449107,0.0084194485,0.0053637465,0.002126616,0.0031359266],"study_design_candidate":"not_applicable","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":[0.0004091369,0.0007405588,0.009323875,0.0005340089,0.000043795364,0.0016592848,0.0020717478,0.010938192,0.018489745,0.4141241,0.06786303,0.47380245],"study_design_scores_gemma":[0.00019025785,0.0007490405,0.01717234,0.0016392424,0.00007986824,0.0017103867,0.008817013,0.049968965,0.011794129,0.10101609,0.8066928,0.0001699223],"about_ca_topic_score_codex":0.006705143,"about_ca_topic_score_gemma":0.011538408,"teacher_disagreement_score":0.017991474,"about_ca_system_score_codex":0.003094416,"about_ca_system_score_gemma":0.004859432,"threshold_uncertainty_score":0.06018752},"labels":[],"label_agreement":null}]}