{"id":"W2950363995","doi":"10.1007/978-3-030-23207-8_53","title":"Informing the Utility of Learning Interventions: Investigating Factors Related to Students’ Academic Achievement in Classroom and Online Courses","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Multilevel model; Context (archaeology); Construct (python library); Academic achievement; Psychological intervention; Sample (material); Variance (accounting); Computer science; Mathematics education; Psychology; Regression analysis; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001990533,0.0003406391,0.000491139,0.000718282,0.0001742981,0.0002035596,0.00236789,0.0002403584,0.000004037941],"category_scores_gemma":[0.0005717706,0.000257553,0.0001188521,0.0007620065,0.0004425032,0.0003652577,0.002226703,0.002187663,0.000003686242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001163577,"about_ca_system_score_gemma":0.00031553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004940605,"about_ca_topic_score_gemma":0.0001347129,"domain_scores_codex":[0.9968781,0.00009046869,0.0009520014,0.0007831252,0.0008829949,0.0004133233],"domain_scores_gemma":[0.9978225,0.0007761676,0.0005516026,0.0006022881,0.0001356104,0.0001118663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005156397,0.0001017865,0.4293992,0.0002682716,0.00004244628,0.0000109353,0.009401548,0.1693744,0.0001054806,0.005113489,0.000005071823,0.3861722],"study_design_scores_gemma":[0.0003326111,0.0003398564,0.06377254,0.003847925,0.00001764466,0.000009942618,0.00002984335,0.9122159,0.0001090593,0.01862763,0.0002385275,0.0004584788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3714923,0.0004774166,0.6243821,0.00242273,0.0005364388,0.0004951503,0.000005026842,0.00007447202,0.0001143678],"genre_scores_gemma":[0.9591464,0.00006046305,0.04008897,0.0003111177,0.00004140448,0.000001746287,0.000007361477,0.00001637879,0.000326149],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7428416,"threshold_uncertainty_score":0.9999877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03695099456256676,"score_gpt":0.3332734220278977,"score_spread":0.2963224274653309,"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."}}