{"meta":{"query_hash":"2358a6b26349","filters":{"venue":"IEEE Transactions on Learning Technologies"},"cohort_total":13,"direct_labels_cover":0,"predictions_cover":13,"exported":13,"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/2358a6b26349","api":"https://metacan.xera.ac/api/v1/cohort?venue=IEEE+Transactions+on+Learning+Technologies"},"results":[{"id":"W2111205609","doi":"10.1109/tlt.2009.40","title":"Recommendations in Online Discussion Forums for E-Learning Systems","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":93,"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 Saskatchewan","funders":"","keywords":"Personalization; Computer science; Collaborative filtering; Recommender system; World Wide Web; Online discussion; Order (exchange); Architecture; Information retrieval; Multimedia; Human–computer interaction","score_opus":0.029436338750453907,"score_gpt":0.288465978733924,"score_spread":0.25902963998347006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111205609","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012909085,0.000076031974,0.96064365,0.03239274,0.00049837085,0.00053453626,0.000003969026,0.00442725,0.00013251723],"genre_scores_gemma":[0.94873023,0.00013921861,0.049420103,0.000054952245,0.000014917637,0.00021890017,0.000005987629,0.000016043088,0.0013996474],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844736,0.00010290458,0.00042449872,0.00047195258,0.00016106763,0.0003922353],"domain_scores_gemma":[0.99910736,0.00018373257,0.00016502675,0.00044903115,0.0000634958,0.000031327494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041911978,0.00021527227,0.00028610855,0.00067472487,0.00043481225,0.00018211317,0.0006963258,0.00024261499,0.0000020436953],"category_scores_gemma":[0.00005845991,0.00016068052,0.00011637295,0.000690255,0.00003101428,0.00046537843,0.0000076530405,0.0008461568,0.000006444228],"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":[0.00001392366,0.00028122967,0.000077437995,0.00002411619,0.000015689988,0.0000036548863,0.0004874677,0.025914278,0.00076005905,0.0066645527,0.0006523257,0.96510524],"study_design_scores_gemma":[0.0021182066,0.0048366934,0.0004009177,0.0014405531,0.0000308534,0.000089835514,0.010444233,0.6141636,0.027227465,0.016806824,0.32088614,0.0015547461],"about_ca_topic_score_codex":0.000032831515,"about_ca_topic_score_gemma":0.000022441556,"teacher_disagreement_score":0.9635505,"about_ca_system_score_codex":0.00013246409,"about_ca_system_score_gemma":0.000026111245,"threshold_uncertainty_score":0.6552361},"labels":[],"label_agreement":null},{"id":"W2138657316","doi":"10.1109/tlt.2012.9","title":"Ontology Extraction Tools: An Empirical Study with Educators","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":12,"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; Simon Fraser University","funders":"Athabasca University","keywords":"Ontology; Computer science; Domain (mathematical analysis); Ontology learning; Upper ontology; Data science; Process ontology; Empirical research; Information retrieval; Information extraction; Ontology-based data integration; World Wide Web; Knowledge management; Semantic Web; Suggested Upper Merged Ontology","score_opus":0.04537280766865238,"score_gpt":0.3298453082444168,"score_spread":0.28447250057576445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138657316","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":[0.47003883,0.000066888155,0.525023,0.0009230185,0.00049893535,0.0001798166,2.794597e-7,0.0031085676,0.00016067737],"genre_scores_gemma":[0.9789384,0.000017110167,0.020693472,0.000057353445,0.00002558164,0.00011722888,3.532283e-7,0.000016087539,0.00013442204],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9983443,0.00017035508,0.0002198523,0.00047186672,0.0002645529,0.0005290854],"domain_scores_gemma":[0.99871147,0.00029036426,0.00010326796,0.0007712842,0.000056532564,0.000067108485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031841162,0.00024166616,0.00026053548,0.0004089517,0.00044289159,0.000142578,0.000777716,0.0002267414,0.000013840346],"category_scores_gemma":[0.00006121697,0.00018616089,0.00005725998,0.0006237811,0.00017428634,0.0014476477,0.00000873571,0.00085926097,0.00007277041],"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":[0.00018373782,0.0056120907,0.10375672,0.000019072748,0.00021903738,0.000058871512,0.0140712485,0.0065479963,0.0007855102,0.0017653638,0.00019969945,0.86678064],"study_design_scores_gemma":[0.005307421,0.037968807,0.3957982,0.00019334891,0.00055769493,0.002271549,0.3636204,0.01954905,0.13289438,0.0026552868,0.03425391,0.0049299262],"about_ca_topic_score_codex":0.000056256875,"about_ca_topic_score_gemma":0.00008558967,"teacher_disagreement_score":0.86185074,"about_ca_system_score_codex":0.00008701401,"about_ca_system_score_gemma":0.000059683247,"threshold_uncertainty_score":0.7591421},"labels":[],"label_agreement":null},{"id":"W2139776525","doi":"10.1109/tlt.2012.15","title":"The Collaborative Lecture Annotation System (CLAS): A New TOOL for Distributed Learning","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":68,"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 British Columbia","funders":"","keywords":"Annotation; Computer science; Context (archaeology); Comprehension; Process (computing); Collaborative learning; Key (lock); Collaborative software; Human–computer interaction; Perception; Information extraction; Multimedia; World Wide Web; Information retrieval; Artificial intelligence; Knowledge management; Programming language","score_opus":0.026569215231115443,"score_gpt":0.3364128513103226,"score_spread":0.3098436360792072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139776525","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":[0.03389541,0.0005251409,0.957407,0.0016900124,0.0015170843,0.0006100466,0.000019647243,0.0038136805,0.0005219533],"genre_scores_gemma":[0.98400563,0.00001825776,0.011184888,0.00002599672,0.00012560954,0.00041834955,0.000019179814,0.000059365153,0.0041427463],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.997293,0.0010272261,0.00037450928,0.00038200035,0.00021197331,0.0007113235],"domain_scores_gemma":[0.9969606,0.0020654118,0.0003202727,0.00038213286,0.00022885941,0.000042735075],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0019044201,0.00031206998,0.00030118797,0.00026388824,0.0022162215,0.00011934574,0.0003210058,0.0004387807,0.000026798345],"category_scores_gemma":[0.0008525315,0.00023587262,0.00013711037,0.0011711777,0.00021317723,0.00015829115,0.0000039873976,0.0022538265,0.00009621566],"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":[0.00085102883,0.00018031812,0.0016683148,0.00005735452,0.0005301246,0.000003168786,0.016112557,0.06081598,0.0027077396,0.016571492,0.002709227,0.8977927],"study_design_scores_gemma":[0.0031257374,0.0025606938,0.0044119144,0.00028044693,0.00030703892,0.00008526884,0.10524359,0.0056275874,0.023111181,0.0006609978,0.85324925,0.0013362872],"about_ca_topic_score_codex":0.00003188134,"about_ca_topic_score_gemma":0.0000037609213,"teacher_disagreement_score":0.9501102,"about_ca_system_score_codex":0.00023363666,"about_ca_system_score_gemma":0.000070682036,"threshold_uncertainty_score":0.99908274},"labels":[],"label_agreement":null},{"id":"W2157958392","doi":"10.1109/tlt.2011.21","title":"An Approach to Folksonomy-Based Ontology Maintenance for Learning Environments","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Royal Military College of Canada; Athabasca University","funders":"","keywords":"Computer science; Ontology; Folksonomy; Usability; Upper ontology; Process ontology; Ontology-based data integration; World Wide Web; Semantic Web; Human–computer interaction","score_opus":0.03614750268683599,"score_gpt":0.24236956760111827,"score_spread":0.2062220649142823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157958392","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011339687,0.000030880743,0.98380595,0.00052229606,0.00024684638,0.000406602,0.0000014800794,0.002941928,0.00070434634],"genre_scores_gemma":[0.6742141,0.000007941991,0.3251037,0.000096269665,0.000004886452,0.00030404795,8.012758e-7,0.000016262631,0.00025195413],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99818957,0.000086631146,0.00024728465,0.0007501256,0.00015765778,0.00056873757],"domain_scores_gemma":[0.99889374,0.00016025767,0.0001110486,0.00074013753,0.000032134765,0.000062660365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002753902,0.00025910305,0.0002902152,0.00039897987,0.00045475026,0.00006689779,0.001366973,0.00026408033,0.000005489831],"category_scores_gemma":[0.00007811447,0.00024027628,0.00012052161,0.00033540823,0.00017902914,0.00030246115,0.000010623577,0.000583005,0.00005014047],"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":[0.00029418227,0.0014808361,0.0014181861,0.00006339047,0.00013664475,0.000020735848,0.0048032706,0.2834854,0.006182149,0.022952758,0.00014025667,0.6790222],"study_design_scores_gemma":[0.002881563,0.007979995,0.0035235358,0.00012546378,0.00010376958,0.000066851426,0.008853251,0.63060635,0.29706913,0.007781,0.03889502,0.0021140825],"about_ca_topic_score_codex":0.000038389473,"about_ca_topic_score_gemma":0.0000085219845,"teacher_disagreement_score":0.6769081,"about_ca_system_score_codex":0.00008380722,"about_ca_system_score_gemma":0.000037755384,"threshold_uncertainty_score":0.9798182},"labels":[],"label_agreement":null},{"id":"W2162174474","doi":"10.1109/tlt.2010.12","title":"Context-Aware Services for Smart Learning Spaces","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University; Thunder Bay Regional Research Institute","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Collaborative learning; Ubiquitous computing; Context (archaeology); Multimedia; Schedule; Context awareness; Ontology; Synchronous learning; Educational technology; Human–computer interaction; World Wide Web; Cooperative learning; Knowledge management; Teaching method","score_opus":0.011586466993685825,"score_gpt":0.2543860857676402,"score_spread":0.2427996187739544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162174474","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":[0.08855423,0.00003692975,0.8981279,0.004968296,0.001577132,0.0003768255,0.0000017512115,0.0061574425,0.00019947393],"genre_scores_gemma":[0.96676916,0.000032738364,0.030926911,0.00007567839,0.000038055758,0.00039266603,0.000003183157,0.00003623702,0.0017253915],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982613,0.00009344192,0.00026458022,0.0006572681,0.00025935008,0.0004640576],"domain_scores_gemma":[0.99828386,0.0005799501,0.00021277471,0.0006937854,0.00017837086,0.000051246876],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000489124,0.00027351818,0.00024471,0.00045515082,0.0009213654,0.00036225453,0.0012503443,0.0003786966,0.000031002408],"category_scores_gemma":[0.00012360088,0.00027037004,0.00013836854,0.00056913943,0.00017395381,0.0005566839,0.000013810839,0.0020429692,0.00013024737],"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":[0.00001979852,0.00017168326,0.0013524692,0.000097221804,0.00005990718,0.0000029345338,0.002623895,0.04442617,0.009399129,0.0035539668,0.0001089607,0.93818384],"study_design_scores_gemma":[0.0014093084,0.0018790518,0.0010611918,0.00027548315,0.00007773497,0.00008803963,0.016091514,0.3955758,0.20791458,0.0044981875,0.36956114,0.0015679938],"about_ca_topic_score_codex":0.000058640744,"about_ca_topic_score_gemma":0.00009411903,"teacher_disagreement_score":0.9366159,"about_ca_system_score_codex":0.000049861534,"about_ca_system_score_gemma":0.00006959108,"threshold_uncertainty_score":0.99997485},"labels":[],"label_agreement":null},{"id":"W2162376067","doi":"10.1109/tlt.2008.12","title":"Building Domain Ontologies from Text for Educational Purposes","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":97,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Ontology; Domain (mathematical analysis); Ontology learning; IDEF5; Bridge (graph theory); Domain analysis; Domain model; Domain knowledge; Formal concept analysis; Domain engineering; Artificial intelligence; Natural language processing; Information retrieval; Process ontology; Suggested Upper Merged Ontology; Software; Software development","score_opus":0.026016166726241942,"score_gpt":0.2651617681795095,"score_spread":0.23914560145326755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162376067","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.107569486,0.00046424964,0.8791174,0.008260348,0.00067722076,0.00024587743,0.000007341919,0.0034890221,0.00016903614],"genre_scores_gemma":[0.65530324,0.00012472166,0.34403095,0.000055426226,0.000021967715,0.0001839714,0.0000010562499,0.000011305915,0.0002674002],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99843675,0.000048087513,0.00027268633,0.00059124135,0.0002312199,0.00041999572],"domain_scores_gemma":[0.99789673,0.0012581762,0.00012476835,0.00060201803,0.0000879658,0.000030319867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012944048,0.0002467518,0.00028738056,0.0003569692,0.00087529415,0.00009971678,0.0012327932,0.0002527638,0.00001452839],"category_scores_gemma":[0.00021824225,0.0002219458,0.00016183354,0.00041140124,0.0003521828,0.0004169074,0.000015078686,0.000468521,0.000047161957],"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":[0.00019147353,0.0009682328,0.0026201655,0.00007019305,0.00046094006,0.00007022258,0.0056208367,0.033080023,0.026389847,0.16766876,0.0048091053,0.7580502],"study_design_scores_gemma":[0.002683556,0.0018425517,0.008553202,0.00027581406,0.00008987504,0.000341958,0.0075559407,0.023198131,0.46163577,0.4311346,0.060403287,0.002285317],"about_ca_topic_score_codex":0.000084854495,"about_ca_topic_score_gemma":0.000025714704,"teacher_disagreement_score":0.7557649,"about_ca_system_score_codex":0.00008675595,"about_ca_system_score_gemma":0.00011209039,"threshold_uncertainty_score":0.90506864},"labels":[],"label_agreement":null},{"id":"W2764061889","doi":"10.1109/tlt.2017.2762688","title":"Design and Empirical Validation of Effectiveness of LANGA, an Online Game-Based Platform for Second Language Learning","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Reading and Literacy Development","field":"Psychology","cited_by":25,"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":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University","keywords":"Computer science; Modular design; Multimedia; Empirical research; Human–computer interaction; Artificial intelligence","score_opus":0.06914866576946123,"score_gpt":0.3661203882899095,"score_spread":0.2969717225204483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2764061889","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":[0.6489721,0.000030517644,0.35040665,0.000040534505,0.000082240775,0.00020694593,0.000010836605,0.00021333856,0.000036830606],"genre_scores_gemma":[0.98947096,0.0000053488093,0.010121001,0.0000040873942,0.0000051208294,0.00007905905,0.000018645074,0.000019592751,0.0002762125],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999178,0.00013103028,0.00020218818,0.00024367082,0.00008757143,0.00015757204],"domain_scores_gemma":[0.9985996,0.00078014913,0.00022525057,0.00031466337,0.0000616317,0.00001870308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005683645,0.00012594697,0.0002476565,0.00024117136,0.00022448598,0.000028374188,0.00019381483,0.00019650659,0.000025231884],"category_scores_gemma":[0.00011073284,0.000114411385,0.000051793264,0.00006992129,0.00016958367,0.00011512383,0.0000026132545,0.00036315346,0.0000022225256],"study_design_candidate":"bench_or_experimental","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":[0.0031379731,0.0012423444,0.014535752,0.0009648273,0.00043575335,0.000015765418,0.01840035,0.0872182,0.12725836,0.00019075669,0.00002249105,0.74657744],"study_design_scores_gemma":[0.0023135135,0.0024204983,0.015860766,0.00038342839,0.00006972919,0.000009922486,0.005170495,0.0062961285,0.9661585,0.00022543292,0.00080029323,0.00029128115],"about_ca_topic_score_codex":0.000030231591,"about_ca_topic_score_gemma":0.0000039049523,"teacher_disagreement_score":0.83890015,"about_ca_system_score_codex":0.000026013773,"about_ca_system_score_gemma":0.00002588307,"threshold_uncertainty_score":0.46655607},"labels":[],"label_agreement":null},{"id":"W2797581104","doi":"10.1109/tlt.2018.2823710","title":"Adaptive Gamification for Learning Environments","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Educational Games and Gamification","field":"Psychology","cited_by":230,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; JDA Software (Canada)","funders":"Association Nationale de la Recherche et de la Technologie","keywords":"Computer science; Adaptation (eye); Relevance (law); Human–computer interaction; Process (computing); Learning environment; Multimedia; Game based learning; Mathematics education; Psychology","score_opus":0.03831075545932814,"score_gpt":0.31435929843865734,"score_spread":0.2760485429793292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797581104","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":[0.03499913,0.00008756493,0.9590643,0.0017032437,0.0007250059,0.00041554985,0.000007258142,0.0010731644,0.0019247733],"genre_scores_gemma":[0.97781885,0.00005244777,0.0050852112,0.00004515086,0.000068750516,0.00060608773,0.0000114198,0.00003364359,0.016278468],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99887145,0.00006874173,0.0002143728,0.0004348427,0.00013455747,0.00027602375],"domain_scores_gemma":[0.99920267,0.00023708706,0.00015019196,0.00032308305,0.000062080304,0.000024906001],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002042422,0.00015998645,0.00012951806,0.00024642993,0.00047450003,0.00002557127,0.00022062712,0.00023929263,0.00025036052],"category_scores_gemma":[0.00005388415,0.00016361213,0.00008412324,0.00024828556,0.00029517125,0.00008743971,0.0000016200644,0.0004865389,0.0007935885],"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":[0.00031868898,0.0005185038,0.0002973701,0.000009721401,0.000174471,6.326639e-7,0.0059121805,0.005904532,0.009226221,0.01001173,0.00075636496,0.9668696],"study_design_scores_gemma":[0.0020166202,0.006296953,0.012012265,0.000111166686,0.00020975436,0.000026999473,0.06790955,0.011373141,0.11378454,0.0054255985,0.77963954,0.0011938821],"about_ca_topic_score_codex":0.000014057995,"about_ca_topic_score_gemma":0.0000031363384,"teacher_disagreement_score":0.9656757,"about_ca_system_score_codex":0.000095161166,"about_ca_system_score_gemma":0.000016641845,"threshold_uncertainty_score":0.9999844},"labels":[],"label_agreement":null},{"id":"W4230947401","doi":"10.1109/tlt.2013.36","title":"Editorial","year":2013,"lang":"en","type":"editorial","venue":"IEEE Transactions on Learning Technologies","topic":"Innovative Teaching and Learning Methods","field":"Psychology","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":"University of Toronto","funders":"","keywords":"Computer science","score_opus":0.02055699600303383,"score_gpt":0.3420681995385221,"score_spread":0.32151120353548823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230947401","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006546358,0.00012567482,0.16031927,0.0002491864,0.82699996,0.00030310743,0.000034456858,0.007349681,0.004553211],"genre_scores_gemma":[0.0031984483,0.000084857005,0.0031971452,0.000015550457,0.94166315,0.00055615214,0.000045304194,0.00022286382,0.051016506],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9951847,0.0011723423,0.00061419123,0.0011635171,0.0009963369,0.00086892134],"domain_scores_gemma":[0.9946027,0.0032130717,0.0005101953,0.0011487136,0.00047338966,0.00005193274],"candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity","insufficient_payload"],"category_scores_codex":[0.0017593886,0.0007743433,0.0008266175,0.0011318864,0.0007937935,0.00017633001,0.001105049,0.0051225824,0.0011712196],"category_scores_gemma":[0.0015504663,0.00072840526,0.00031710532,0.0007861993,0.000490597,0.00012098656,0.000009085436,0.017260466,0.0039698645],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009604301,0.00015154837,0.0000014143376,0.000028317647,0.00025722818,0.000007542578,0.00089217385,0.0005739214,0.0000895648,0.000082189705,0.86248195,0.1353381],"study_design_scores_gemma":[0.000601282,0.00083507167,0.0000027586589,0.00014828329,0.00009599097,0.000002799429,0.0012023342,0.000025008589,0.0003361752,0.00023473814,0.9957924,0.000723142],"about_ca_topic_score_codex":0.0003390643,"about_ca_topic_score_gemma":0.0000031120965,"teacher_disagreement_score":0.15712212,"about_ca_system_score_codex":0.00027328022,"about_ca_system_score_gemma":0.00016547309,"threshold_uncertainty_score":0.99974185},"labels":[],"label_agreement":null},{"id":"W4287854572","doi":"10.1109/tlt.2022.3193751","title":"Automatic Learning Path Creation Using OER: A Systematic Literature Mapping","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Metadata; Path (computing); Focus (optics); Set (abstract data type); Scopus; Information retrieval; Artificial intelligence; Data science; World Wide Web","score_opus":0.018895426242973856,"score_gpt":0.25535027273298283,"score_spread":0.23645484649000897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287854572","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":[0.085240066,0.0004241398,0.90446115,0.0013661117,0.00079720694,0.0005872909,0.0000014231134,0.006578654,0.000543934],"genre_scores_gemma":[0.973417,0.00007416236,0.024645044,0.00006273452,0.0000133330295,0.00030539892,0.000004299511,0.000035618647,0.0014424318],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973065,0.00066606246,0.0004903975,0.0005968399,0.00048646505,0.0004537138],"domain_scores_gemma":[0.9985531,0.0003312267,0.00039339744,0.0005640942,0.00010796641,0.000050197385],"candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0008783255,0.00029703794,0.0003970988,0.0010523124,0.0026972531,0.00064870017,0.0010449927,0.00016003933,0.0000955884],"category_scores_gemma":[0.00022633446,0.00030145497,0.00016334592,0.0024175567,0.000085013104,0.0007103608,0.00004627766,0.0024832154,0.000066336455],"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":[0.000012932246,0.00027944476,0.00018985374,0.0026306014,0.00013657684,0.00004495932,0.025166918,0.92227644,0.0035895994,0.0043885824,0.000056169087,0.041227933],"study_design_scores_gemma":[0.00031774447,0.00044652415,0.000038762995,0.002140265,0.000045907884,0.00024240189,0.05325919,0.94010836,0.0012315011,0.00030524086,0.0013604688,0.0005036619],"about_ca_topic_score_codex":0.000015567532,"about_ca_topic_score_gemma":6.73421e-7,"teacher_disagreement_score":0.8881769,"about_ca_system_score_codex":0.00040879447,"about_ca_system_score_gemma":0.000113758964,"threshold_uncertainty_score":0.99994373},"labels":[],"label_agreement":null},{"id":"W4407168991","doi":"10.1109/tlt.2025.3539104","title":"Navigating the Textual Maze: Enhancing Textual Analytical Skills Through an Innovative GAI Prompt Framework","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Topic Modeling","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute for Christian Studies; University of Toronto","funders":"","keywords":"Computer science; Multimedia; Knowledge management; Natural language processing; Human–computer interaction; Artificial intelligence; Mathematics education; World Wide Web; Psychology","score_opus":0.018108583857922345,"score_gpt":0.3172257180081921,"score_spread":0.29911713415026975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407168991","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058481738,0.00006006534,0.9299799,0.0073496415,0.00028264392,0.00027892116,0.0000017634231,0.0030246256,0.0005406749],"genre_scores_gemma":[0.86332685,0.00003180616,0.13603272,0.00031126343,0.000023244873,0.00008093467,7.327446e-7,0.000014696067,0.00017777973],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99774736,0.00014812959,0.00046591033,0.0007509262,0.00036662997,0.0005210697],"domain_scores_gemma":[0.9977724,0.00079100684,0.0001429953,0.0010791975,0.00018926866,0.000025114823],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00050346035,0.00029029758,0.00029132917,0.00016724573,0.000835209,0.00029518636,0.0016006434,0.00037509642,0.000011996168],"category_scores_gemma":[0.00043624383,0.00022531576,0.00009095864,0.0025542465,0.00035379117,0.0007200859,0.000045986835,0.0036494047,0.000029499191],"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":[0.000014546469,0.00029482413,0.00013958207,0.000037722864,0.00013642294,0.000016376875,0.011758701,0.12631805,0.0012512949,0.124124795,0.000028430297,0.73587924],"study_design_scores_gemma":[0.00068729813,0.0009233852,0.00022045044,0.0017530943,0.00007657966,0.000049772203,0.034506064,0.75682044,0.15436591,0.044008758,0.005415789,0.0011724476],"about_ca_topic_score_codex":0.000053310734,"about_ca_topic_score_gemma":0.000016453903,"teacher_disagreement_score":0.8048451,"about_ca_system_score_codex":0.00013889275,"about_ca_system_score_gemma":0.00014273632,"threshold_uncertainty_score":0.99864924},"labels":[],"label_agreement":null},{"id":"W4416750071","doi":"10.1109/tlt.2025.3637864","title":"AI-Driven Learning Analytics for Applied Behavior Analysis Therapy","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":1,"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":"Learning analytics; Intervention (counseling); Applied behavior analysis; Autism spectrum disorder; Analytics; Autism; Predictive analytics; Personalized learning","score_opus":0.037226740018365546,"score_gpt":0.3364502111623157,"score_spread":0.29922347114395015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416750071","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":[0.08371221,0.00039108316,0.89661443,0.011707518,0.00043919383,0.0024568834,0.000051255483,0.003996162,0.0006312598],"genre_scores_gemma":[0.98621434,0.0049723787,0.0013076577,0.00022959973,0.000012253215,0.0013092532,0.000008121889,0.00010688219,0.005839519],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9944339,0.0003183956,0.0009161659,0.0019745412,0.00083046086,0.0015265823],"domain_scores_gemma":[0.99667495,0.0014111229,0.00038353752,0.0013257691,0.00011014715,0.00009449793],"candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0005673192,0.00080738385,0.001126692,0.0052514845,0.0029755896,0.0005531862,0.0018018141,0.0009945558,0.00018422882],"category_scores_gemma":[0.00029578336,0.00085861486,0.0010176727,0.010604158,0.001240633,0.0002646881,0.000033785367,0.005071509,0.00009868609],"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":[0.0005550015,0.0011884787,0.0015650892,0.00008844149,0.0012879467,0.00001818183,0.00073357875,0.69063944,0.037080396,0.003598805,0.000045260538,0.2631994],"study_design_scores_gemma":[0.0031068756,0.0020894238,0.0011070768,0.00013238896,0.0028778487,0.0000038655135,0.0049108346,0.2936727,0.67472255,0.0015600239,0.01434354,0.0014728925],"about_ca_topic_score_codex":0.00003680435,"about_ca_topic_score_gemma":0.000043834716,"teacher_disagreement_score":0.9025021,"about_ca_system_score_codex":0.0004440799,"about_ca_system_score_gemma":0.0003357365,"threshold_uncertainty_score":0.9993865},"labels":[],"label_agreement":null},{"id":"W4416922381","doi":"10.1109/tlt.2025.3639317","title":"Guest Editorial: Special Issue Intelligence Augmentation and the Future of Education: Transforming Learning Landscapes Across Modalities and Lifecycles","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Learning Technologies","topic":"Cognitive Abilities and Testing","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute for Christian Studies; University of Toronto","funders":"","keywords":"Modalities; Modality (human–computer interaction); Context (archaeology); Visualization; Computer aided instruction; Electronic learning","score_opus":0.011048533184921962,"score_gpt":0.31227159416691347,"score_spread":0.30122306098199153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416922381","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":[0.6280736,0.04293572,0.09617767,0.026649205,0.19180675,0.0035076216,0.00013348646,0.0022255473,0.008490455],"genre_scores_gemma":[0.97615165,0.01032345,0.00019621938,0.000036325484,0.011416783,0.00018148753,0.000004219432,0.000029114419,0.0016607492],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.9976759,0.0003825633,0.0006774331,0.0005915975,0.00024678904,0.00042571136],"domain_scores_gemma":[0.99677163,0.0023848792,0.00029544282,0.00027535454,0.000239633,0.000033064327],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00082642876,0.00038649308,0.00053387746,0.00034647278,0.001493452,0.0002097928,0.0002802187,0.0005347613,0.00009179798],"category_scores_gemma":[0.00030072604,0.00033047044,0.00014131643,0.0006312252,0.0016352505,0.00022601674,0.000017500553,0.0018200296,0.0000063694733],"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":[0.00060997653,0.00017945646,0.0008631052,0.0004271511,0.00024241197,0.0000010337932,0.038638778,0.0015052952,0.00009070955,0.0036431907,0.00043189916,0.953367],"study_design_scores_gemma":[0.0017438314,0.0006445106,0.00040870067,0.0010372985,0.00033074006,0.000023122664,0.75868684,0.0005729056,0.007924418,0.005187219,0.222993,0.0004474083],"about_ca_topic_score_codex":0.00031200482,"about_ca_topic_score_gemma":0.00018088358,"teacher_disagreement_score":0.9529196,"about_ca_system_score_codex":0.00006289131,"about_ca_system_score_gemma":0.00012693068,"threshold_uncertainty_score":0.9999147},"labels":[],"label_agreement":null}]}