{"id":"W1848347860","doi":"10.24059/olj.v3i2.1913","title":"Intelligent Agents for Online Learning","year":2019,"lang":"en","type":"article","venue":"Online Learning","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McMaster University; Vanderbilt University; Alfred P. Sloan Foundation","keywords":"Asynchronous communication; Computer science; Online learning; Facilitation; Asynchronous learning; Association (psychology); Online research methods; Intelligent agent; Knowledge management; Human–computer interaction; Multimedia; Artificial intelligence; Psychology; Synchronous learning; World Wide Web; Mathematics education; Cooperative learning; Teaching method","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":[],"consensus_categories":[],"category_scores_codex":[0.0004050896,0.0001724101,0.0002339941,0.0001336882,0.0001700501,0.0001140977,0.0004611027,0.00008669484,0.00009544483],"category_scores_gemma":[0.0001912044,0.000163192,0.0001246127,0.0002252576,0.000008784097,0.0003052168,0.000178992,0.000374842,0.0002964742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006237443,"about_ca_system_score_gemma":0.00003085589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003906263,"about_ca_topic_score_gemma":0.00001455875,"domain_scores_codex":[0.9984301,0.0001241833,0.0003554971,0.0004649388,0.0002770077,0.0003482972],"domain_scores_gemma":[0.9990851,0.0001598765,0.0002490803,0.0003000631,0.0001150611,0.00009078468],"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":[0.00004617074,0.0007091354,0.154642,0.0003671819,0.0001351964,0.00001303176,0.004988594,0.2044416,0.01194721,0.007431292,0.00112889,0.6141497],"study_design_scores_gemma":[0.0004957074,0.0002146269,0.01552464,0.00008912471,0.000006268217,0.000004833224,0.0002204919,0.7240501,0.0003036165,0.00003972451,0.2588395,0.0002113104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6259032,0.0001022761,0.3719119,0.0004212847,0.0007629272,0.0003842511,0.000003767876,0.0002477527,0.0002626037],"genre_scores_gemma":[0.9298241,0.0000447728,0.04501671,0.0002382836,0.0003970904,0.00001364712,0.000207591,0.00003423446,0.02422354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6139384,"threshold_uncertainty_score":0.6654777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03750722707022293,"score_gpt":0.313064772932281,"score_spread":0.2755575458620581,"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."}}