{"id":"W7132944456","doi":"","title":"Accelerating Evidence-Based Learning Design Improvement with Adaptive Interventions","year":2025,"lang":"","type":"dissertation","venue":"TSpace","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Naval Research; Natural Sciences and Engineering Research Council of Canada; University of Toronto; National Science Foundation","keywords":"Psychological intervention; Affordance; Adaptive learning; Learning sciences; Digital learning; Workflow; Bridging (networking); Field (mathematics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002180822,0.001057433,0.001000266,0.0007117272,0.001735375,0.001591184,0.001441566,0.0003991688,0.0002336642],"category_scores_gemma":[0.0007267662,0.0009931198,0.0008220165,0.001319227,0.00006190292,0.0009948799,0.0002576408,0.002142078,0.0001188443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007244458,"about_ca_system_score_gemma":0.001980862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001418276,"about_ca_topic_score_gemma":0.0001273826,"domain_scores_codex":[0.9935383,0.001111459,0.001247923,0.001850118,0.001181295,0.001070963],"domain_scores_gemma":[0.9942025,0.001313814,0.001837789,0.0008630135,0.00155079,0.0002321016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001081893,0.0004532845,0.0004200434,0.003979558,0.001280357,0.0001599289,0.03623075,0.7519138,0.00768679,0.04459694,0.0002177801,0.1519788],"study_design_scores_gemma":[0.001524996,0.01186469,0.0006574747,0.1588873,0.0008723229,0.00001090756,0.03783282,0.7271531,0.05284699,0.0000764176,0.005333277,0.00293977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005968617,0.00325342,0.9840731,0.0003277074,0.001797794,0.002017138,0.000001231488,0.0003147177,0.002246281],"genre_scores_gemma":[0.5961859,0.000128332,0.09366187,0.0001121201,0.000370754,0.0005620159,0.00003918089,0.00009970299,0.3088401],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8904112,"threshold_uncertainty_score":0.9995642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1920234895384483,"score_gpt":0.3738901870691368,"score_spread":0.1818666975306885,"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."}}