{"id":"W4247078255","doi":"10.28945/4253","title":"Understanding Online Learning Based on Different Age Categories","year":2019,"lang":"en","type":"article","venue":"Informing Science and IT Education Conference","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Psychology; Sample (material); Online learning; Knowledge management; Medical education; Mathematics education; Multimedia","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":[],"consensus_categories":[],"category_scores_codex":[0.001207166,0.0002072194,0.0002414728,0.001764717,0.0004589774,0.001927232,0.0003386154,0.0004968027,0.01109154],"category_scores_gemma":[0.009017493,0.00007129986,0.0004148767,0.0006715254,0.0003912864,0.00371494,0.001331401,0.0004834098,0.001429662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003891948,"about_ca_system_score_gemma":0.0003334574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002514758,"about_ca_topic_score_gemma":0.002599984,"domain_scores_codex":[0.9994581,0.0001372082,0.00006794449,0.00008060657,0.0001293065,0.000126909],"domain_scores_gemma":[0.9963426,0.001804798,0.0006713241,0.0001194868,0.0006223383,0.0004394706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001508458,0.0002102857,0.8073936,0.0002538431,0.00004974671,0.0001437016,0.02244553,0.0002603992,0.0008323767,0.004718097,0.006336549,0.1572052],"study_design_scores_gemma":[0.000009576502,0.0002196918,0.9202219,0.0003971461,0.00004168527,0.0003798318,0.04847735,0.001236945,0.0003999778,0.005278226,0.02330414,0.00003359641],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705494,0.0009282735,0.002354911,0.001584754,0.0001049324,0.0001285708,0.001025017,0.00004790872,0.02327619],"genre_scores_gemma":[0.9943809,0.0005148828,0.001023252,0.0002334059,0.00002780316,0.0000769878,0.0006701673,0.00001087812,0.00306158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01109154,"threshold_uncertainty_score":0.03710485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05973115345982866,"score_gpt":0.3063258647120755,"score_spread":0.2465947112522468,"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."}}