{"id":"W4297990445","doi":"10.18280/ria.360411","title":"Big Data in Academia: A Proposed Framework for Improving Students Performance","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Computer science; Data science; Lifelong learning; Scalability; Comprehension; Knowledge management; Learning analytics; Key (lock); Order (exchange); Psychology; Pedagogy; Data mining; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001522742,0.000141553,0.0001952441,0.0001712537,0.0003872405,0.0001393743,0.003751838,0.0001382136,0.00001756286],"category_scores_gemma":[0.0003906008,0.0001490305,0.00004963887,0.0009507734,0.00003619923,0.0002803527,0.002108437,0.001525448,0.0000408333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009159241,"about_ca_system_score_gemma":0.0001205686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002097417,"about_ca_topic_score_gemma":0.000005104788,"domain_scores_codex":[0.9979764,0.00008066771,0.0004407194,0.0006922499,0.0003786418,0.0004313314],"domain_scores_gemma":[0.9981911,0.000259333,0.0001623791,0.001271745,0.00004711379,0.00006831806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004579409,0.000724106,0.02218328,0.0002936384,0.00002257206,0.00003090642,0.004146733,0.178557,0.0009477087,0.02662939,0.0003262449,0.7660926],"study_design_scores_gemma":[0.00005696851,0.0001936826,0.0002415529,0.00005043082,0.000006129443,0.00001027035,0.0005727095,0.9867142,0.001365842,0.004629734,0.005959847,0.0001986669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.131113,0.0001915638,0.8635183,0.003867492,0.0007097736,0.0004035383,0.00001475533,0.0001094478,0.00007217941],"genre_scores_gemma":[0.9616894,0.00003071735,0.03672662,0.0003278982,0.0001826225,0.00004659214,0.00001956299,0.00001651387,0.0009600995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8305764,"threshold_uncertainty_score":0.6971911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08871608109901573,"score_gpt":0.3458335707636226,"score_spread":0.2571174896646068,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}