{"meta":{"query_hash":"216c079e42a3","filters":{"venue":"International Journal of Modern Education and Computer Science"},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"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/216c079e42a3","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Modern+Education+and+Computer+Science"},"results":[{"id":"W2120520504","doi":"10.5815/ijmecs.2015.01.01","title":"Semantic Question Generation Using Artificial Immunity","year":2015,"lang":"en","type":"article","venue":"International Journal of Modern Education and Computer Science","topic":"Topic Modeling","field":"Computer Science","cited_by":10,"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; Sentence; Preprocessor; Artificial intelligence; Natural language processing; Classifier (UML); Set (abstract data type); Test set; Matching (statistics); Semantic role labeling","score_opus":0.08427210239310003,"score_gpt":0.3489781839158917,"score_spread":0.2647060815227917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120520504","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":[0.39660475,0.000100712954,0.59902614,0.00079326984,0.003416549,0.000022056403,1.0417488e-7,0.000008645574,0.000027775275],"genre_scores_gemma":[0.8053064,0.000007182337,0.19359383,0.00030782344,0.0007750774,4.5051374e-7,4.360112e-7,0.0000021220296,0.000006674457],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855775,0.00006255333,0.0003197914,0.00018212483,0.0007700381,0.00010774116],"domain_scores_gemma":[0.9979163,0.000015778987,0.00025401468,0.00017461748,0.001489682,0.00014960028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012736566,0.00007143203,0.000084259394,0.00033040298,0.00010106328,0.0006090953,0.0010036875,0.000024400204,0.0000010052235],"category_scores_gemma":[0.00007126633,0.00006643989,0.000027016897,0.00018906074,0.00007787074,0.0017065082,0.00021479634,0.00010753896,0.0000019549561],"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":[0.0000063560715,0.0001996288,0.0005953797,0.0000020013376,0.00001187187,0.0000045612696,0.0027269493,0.020636205,0.008917362,0.0757753,0.00007556702,0.8910488],"study_design_scores_gemma":[0.00011118528,0.000035167148,0.0009076375,0.000028401695,0.0000030469128,0.00038693583,0.00004032774,0.964445,0.0014475561,0.03245091,0.00007361744,0.00007022009],"about_ca_topic_score_codex":0.000037009933,"about_ca_topic_score_gemma":0.0000031475481,"teacher_disagreement_score":0.9438088,"about_ca_system_score_codex":0.00018513066,"about_ca_system_score_gemma":0.0012607703,"threshold_uncertainty_score":0.58735204},"labels":[],"label_agreement":null},{"id":"W2333899602","doi":"10.5815/ijmecs.2016.04.03","title":"GCSTLPP: Face Recognition using Gabor Center-Symmetric Tensor Locality Preservative Projection Approach in Video","year":2016,"lang":"en","type":"article","venue":"International Journal of Modern Education and Computer Science","topic":"Face and Expression Recognition","field":"Computer Science","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":"Computer science; Facial recognition system; Artificial intelligence; Locality; Computer vision; Pattern recognition (psychology); Face (sociological concept); Classifier (UML); Feature (linguistics); Support vector machine","score_opus":0.049299599452376705,"score_gpt":0.31335504837727285,"score_spread":0.26405544892489613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2333899602","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":[0.3580494,0.000053876895,0.63956606,0.00096725975,0.0011402454,0.000094033494,0.00000289331,0.00001212475,0.000114094015],"genre_scores_gemma":[0.9003549,0.000071913215,0.09893965,0.00038437633,0.0002151592,0.000006504897,0.0000016532506,0.0000043347686,0.000021470421],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99814045,0.000111246685,0.00044765318,0.00037102393,0.00073752494,0.00019207511],"domain_scores_gemma":[0.9979415,0.00008387505,0.00040149468,0.00016237325,0.0012860228,0.00012471325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008440333,0.00012078985,0.00014251628,0.00091985444,0.00009458362,0.00030998554,0.0008797112,0.00004792732,0.000004736072],"category_scores_gemma":[0.00011860435,0.000086144566,0.00004871256,0.00071003917,0.00012580107,0.003145577,0.00022010393,0.00013091175,0.000004518898],"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":[0.000037254325,0.000624585,0.006166602,0.000008399438,0.000013398,0.000002896361,0.0013268084,0.00020617829,0.00399673,0.0004752392,0.00015976034,0.98698217],"study_design_scores_gemma":[0.0019049926,0.00022694885,0.07383962,0.00078193774,0.000008785059,0.00073897117,0.0002819312,0.89315486,0.007374655,0.020802267,0.00050190446,0.0003831526],"about_ca_topic_score_codex":0.000031326523,"about_ca_topic_score_gemma":0.0000020973423,"teacher_disagreement_score":0.98659897,"about_ca_system_score_codex":0.00026710675,"about_ca_system_score_gemma":0.000545969,"threshold_uncertainty_score":0.35128734},"labels":[],"label_agreement":null},{"id":"W2738730522","doi":"10.5815/ijmecs.2017.07.01","title":"A Classification Framework for Context-aware Mobile Learning Systems","year":2017,"lang":"en","type":"article","venue":"International Journal of Modern Education and Computer Science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Context (archaeology); Field (mathematics); Mobile device; Context awareness; Architecture; Mobile computing; Layer (electronics); Multimedia; Human–computer interaction; Ubiquitous computing; Data science; Artificial intelligence; World Wide Web; Telecommunications","score_opus":0.046611180291229716,"score_gpt":0.35192444014556445,"score_spread":0.3053132598543347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2738730522","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":[0.04204557,0.0003095765,0.9478845,0.0017884183,0.007607165,0.00021645467,0.000002315728,0.000027928312,0.00011808239],"genre_scores_gemma":[0.9759356,0.00003735376,0.022821177,0.00024628377,0.000810795,0.000039957704,0.000001118778,0.0000067907313,0.0001009646],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982852,0.00007102527,0.000437648,0.00034623212,0.00068737747,0.00017253222],"domain_scores_gemma":[0.9955541,0.00028042664,0.0011469318,0.00039765323,0.0024586497,0.00016223146],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001317348,0.000121493635,0.0001927994,0.0003304543,0.00058084144,0.0026828477,0.002404625,0.00005786004,0.0000021854019],"category_scores_gemma":[0.00034237606,0.00011320556,0.00008120399,0.00009204287,0.00019327745,0.002714003,0.0002738256,0.00020284986,0.000005275479],"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":[0.00001290862,0.0001356948,0.0024831377,0.000010450042,0.000029486593,0.0000017319336,0.0015981735,0.00014936135,0.00031598654,0.056622516,0.00016661664,0.93847394],"study_design_scores_gemma":[0.00064604013,0.000255354,0.020155145,0.0004956253,0.000011598164,0.00061819167,0.00061042677,0.9417397,0.00030609025,0.021087026,0.013798075,0.00027674585],"about_ca_topic_score_codex":0.00002183393,"about_ca_topic_score_gemma":0.0000025118427,"teacher_disagreement_score":0.9415903,"about_ca_system_score_codex":0.00015475352,"about_ca_system_score_gemma":0.00078047137,"threshold_uncertainty_score":0.99835247},"labels":[],"label_agreement":null},{"id":"W2752268817","doi":"10.5815/ijmecs.2017.08.05","title":"Building a Natural Disaster Management System based on Blogging Platforms","year":2017,"lang":"en","type":"article","venue":"International Journal of Modern Education and Computer Science","topic":"Public Relations and Crisis Communication","field":"Social Sciences","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":"Trinity College","funders":"","keywords":"Computer science; Social media; Microblogging; Information sharing; World Wide Web; Social network (sociolinguistics); Natural disaster; Data science; Natural (archaeology); Internet privacy","score_opus":0.01879207332595812,"score_gpt":0.3496435373488187,"score_spread":0.3308514640228606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2752268817","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":[0.50347143,0.00012562696,0.46172366,0.00975929,0.0062653823,0.00013202532,8.080178e-7,0.000023040895,0.018498756],"genre_scores_gemma":[0.97536135,0.000025008192,0.023864845,0.0003123077,0.00033702434,0.0000025766742,4.3844966e-7,0.000002563548,0.00009390516],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988069,0.000024496037,0.0002036893,0.00012429892,0.000727108,0.00011351528],"domain_scores_gemma":[0.99875724,0.00004066915,0.00038047237,0.00023948605,0.00049204315,0.00009009608],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0010577389,0.000056852976,0.00006777889,0.00029698777,0.00096783333,0.0011252171,0.0013910651,0.000020184765,0.0000040097952],"category_scores_gemma":[0.000051347266,0.000047091133,0.000039169012,0.00006987129,0.00025158696,0.0011831332,0.00013315272,0.000108153356,0.0000018845823],"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":[0.000011583593,0.00009945585,0.0017462231,0.0000035357148,0.0000149380985,0.0000019208856,0.00229793,0.00046331846,0.000022650462,0.3090324,0.00011648871,0.68618953],"study_design_scores_gemma":[0.0009377543,0.000074992924,0.12010677,0.00079748244,0.00002538217,0.00006239905,0.0034257479,0.8325855,0.000060653165,0.024975587,0.016666543,0.0002811518],"about_ca_topic_score_codex":0.000032564803,"about_ca_topic_score_gemma":0.0000072113426,"teacher_disagreement_score":0.8321222,"about_ca_system_score_codex":0.0002396422,"about_ca_system_score_gemma":0.00032268523,"threshold_uncertainty_score":0.9999117},"labels":[],"label_agreement":null},{"id":"W296311707","doi":"10.5815/ijmecs.2015.04.05","title":"An Empirical Investigation of the Relationships between Learning Styles based on an Arabic version of the Felder-Silverman Model","year":2015,"lang":"en","type":"article","venue":"International Journal of Modern Education and Computer Science","topic":"Learning Styles and Cognitive Differences","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Athabasca University","keywords":"Learning styles; Arabic; Dimension (graph theory); Computer science; Reliability (semiconductor); Mathematics education; Style (visual arts); Validity; Scale (ratio); Empirical research; Interdependence; Psychology; Artificial intelligence; Linguistics; Mathematics; Psychometrics; Statistics; Social science; Sociology","score_opus":0.08066150829641963,"score_gpt":0.3735638063292394,"score_spread":0.29290229803281975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W296311707","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":[0.9609883,0.000017111512,0.036783803,0.001356761,0.0005492531,0.000044539418,0.0000021297496,0.0000034313125,0.00025468384],"genre_scores_gemma":[0.9985106,8.6962416e-7,0.0010354706,0.00027102607,0.00013235357,9.137654e-7,0.000002577541,0.0000032280914,0.00004298824],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985905,0.00034721516,0.00024518138,0.00013493476,0.00061457424,0.00006759049],"domain_scores_gemma":[0.9983932,0.00010611393,0.00043234814,0.00013534742,0.0008435617,0.00008943686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008088031,0.000062056846,0.00008346825,0.00014926755,0.00013531363,0.00005304564,0.0006152302,0.000036312093,0.0000050660815],"category_scores_gemma":[0.000102950595,0.000038185306,0.000042329044,0.00016493959,0.00028651766,0.0003007742,0.000046819387,0.0002519768,7.946691e-7],"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":[0.000041440475,0.00020647442,0.9150796,0.0000022989168,0.000013989536,1.2699196e-7,0.013308011,0.033506542,0.0004055238,0.001589573,0.00009406033,0.035752356],"study_design_scores_gemma":[0.00022535361,0.00017429914,0.73818934,0.00006828967,0.000010460735,0.0000056503964,0.000818221,0.25593495,0.00034083083,0.0041781594,0.000016546177,0.00003788264],"about_ca_topic_score_codex":0.000016486503,"about_ca_topic_score_gemma":0.000002890545,"teacher_disagreement_score":0.22242843,"about_ca_system_score_codex":0.000046001904,"about_ca_system_score_gemma":0.0005782337,"threshold_uncertainty_score":0.15571517},"labels":[],"label_agreement":null},{"id":"W3198404677","doi":"10.5815/ijmecs.2021.04.06","title":"An Optimized Machine Learning Approach for Predicting Parkinson's Disease","year":2021,"lang":"en","type":"article","venue":"International Journal of Modern Education and Computer Science","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"Jagannath University","keywords":"Computer science; Machine learning; Artificial intelligence; AdaBoost; Parkinson's disease; Disease; Medicine; Support vector machine; Pathology","score_opus":0.017331484129236924,"score_gpt":0.3125239540317885,"score_spread":0.2951924699025516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3198404677","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":[0.20430407,0.0008172689,0.7927637,0.0014020054,0.00049381464,0.000075246906,0.0000017145258,0.000008480352,0.0001337135],"genre_scores_gemma":[0.8457482,0.00011213185,0.15266354,0.00085028604,0.0005002163,0.0000047616236,0.000017184733,0.000004655625,0.00009904354],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991478,0.000021562739,0.000182033,0.00016508003,0.00039431278,0.00008921838],"domain_scores_gemma":[0.9985771,0.00002439525,0.00013213753,0.000073749805,0.0009854392,0.0002071765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033571883,0.00005765377,0.00009956942,0.00014764555,0.000095081174,0.0001475365,0.00018330824,0.000014721276,0.000007789038],"category_scores_gemma":[0.000083321196,0.000049801656,0.000052445423,0.000091460635,0.000061393446,0.00038690603,0.000033399505,0.00010677811,1.9685363e-7],"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":[0.0004161277,0.001673351,0.08119125,0.000052277905,0.00008927478,0.000022354536,0.002182103,0.017452573,0.0022037372,0.00060913037,0.00011280127,0.89399505],"study_design_scores_gemma":[0.0010671269,0.00012331523,0.014594625,0.000060490493,0.00003115725,0.00035333945,0.00019608266,0.97904474,0.00021208271,0.0005404145,0.0037124525,0.00006417239],"about_ca_topic_score_codex":0.0000020557857,"about_ca_topic_score_gemma":3.168763e-7,"teacher_disagreement_score":0.9615922,"about_ca_system_score_codex":0.000042503045,"about_ca_system_score_gemma":0.0009516265,"threshold_uncertainty_score":0.20308526},"labels":[],"label_agreement":null},{"id":"W4229012956","doi":"10.5815/ijmecs.2022.01.05","title":"Visual Block-based Programming for ICT Training of Prospective Teachers in Morocco","year":2022,"lang":"en","type":"article","venue":"International Journal of Modern Education and Computer Science","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Scratch; Computer science; Coding (social sciences); Perception; Specialty; Training (meteorology); Computational thinking; Multimedia; Medical education; Artificial intelligence; Psychology; Medicine","score_opus":0.0191215293114502,"score_gpt":0.3236722891023322,"score_spread":0.304550759790882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229012956","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":[0.3732684,0.0000894162,0.6249157,0.0007145493,0.0008952534,0.00009386907,3.96693e-7,0.00001296434,0.000009457803],"genre_scores_gemma":[0.79789156,7.4994557e-7,0.2018453,0.0001423139,0.000089489455,0.000016443537,5.3273607e-7,0.0000035988483,0.000009975143],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985706,0.00006995416,0.0003335319,0.00023165238,0.00063158246,0.00016267008],"domain_scores_gemma":[0.99897915,0.00010116114,0.0003778031,0.00009120002,0.00038101364,0.00006967635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001627896,0.00007794148,0.00012851378,0.0005607313,0.00017340935,0.00019900608,0.0010318878,0.000013991933,0.0000011107571],"category_scores_gemma":[0.00008302043,0.000077315024,0.000058420635,0.00034152193,0.000096678195,0.0004587628,0.00017037657,0.00024082875,6.6723636e-8],"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":[0.00001789199,0.00035736331,0.0068126614,0.000003845438,0.0000109204575,0.0000020096234,0.021018721,0.014685128,0.00020534106,0.0021852397,0.000009351805,0.9546915],"study_design_scores_gemma":[0.0014918322,0.0010083762,0.03425087,0.00013578082,0.000008571931,0.00031455662,0.0019076249,0.9518959,0.00044200537,0.0025936991,0.005710085,0.00024069952],"about_ca_topic_score_codex":0.000017708839,"about_ca_topic_score_gemma":0.0000019341553,"teacher_disagreement_score":0.95445085,"about_ca_system_score_codex":0.00019108166,"about_ca_system_score_gemma":0.001126355,"threshold_uncertainty_score":0.31528154},"labels":[],"label_agreement":null}]}