{"id":"W3112537366","doi":"10.1177/016146811711900305","title":"Leveraging Big Data to Help Each Learner and Accelerate Learning Science","year":2017,"lang":"en","type":"article","venue":"Teachers College Record The Voice of Scholarship in Education","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Big data; Data science; Software; TRACE (psycholinguistics); Learning analytics; Raw data; Value (mathematics); Argument (complex analysis); Analytics; Software analytics; Software development; Machine learning; Software construction; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3560032,0.0009245455,0.001715058,0.003257992,0.003193526,0.007812133,0.00308941,0.004002462,0.009893676],"category_scores_gemma":[0.6000199,0.0009102933,0.002057873,0.002379337,0.01781988,0.01364697,0.007089762,0.007250504,0.001214138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004568518,"about_ca_system_score_gemma":0.01407584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001392999,"about_ca_topic_score_gemma":0.001804005,"domain_scores_codex":[0.5632634,0.3948182,0.01182428,0.007871934,0.02072085,0.00150138],"domain_scores_gemma":[0.2091522,0.7026499,0.02090189,0.05262125,0.01229369,0.002381084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003708516,0.001323402,0.01806472,0.01000766,0.002366014,0.0001555809,0.01480493,0.004272508,0.001448563,0.4616362,0.0507929,0.431419],"study_design_scores_gemma":[0.00419595,0.006314415,0.01039432,0.01789263,0.001733424,0.0003549508,0.006275657,0.01732285,0.01008649,0.6883292,0.2367193,0.0003807931],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0672513,0.009906766,0.6009567,0.2251179,0.011158,0.0229179,0.00161807,0.001772185,0.05930115],"genre_scores_gemma":[0.4690035,0.003387306,0.4444966,0.03793635,0.002339046,0.03838497,0.0003379334,0.0004983157,0.003615951],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3560032,"threshold_uncertainty_score":0.7941628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1203575729298185,"score_gpt":0.3645017029074231,"score_spread":0.2441441299776046,"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."}}