{"id":"W2913168294","doi":"","title":"\"It's like sharpening a knife\": Instructors' Time in Blended Learning Courses","year":2018,"lang":"en","type":"article","venue":"EdMedia + Innovate Learning","topic":"Online and Blended Learning","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Sharpening; Blended learning; Mathematics education; Psychology; Computer science; Pedagogy; Medical education; Artificial intelligence; Educational technology; Medicine","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":[0.001987435,0.0001469749,0.0001924289,0.0006943121,0.001790433,0.003677052,0.0008839719,0.001225813,0.009174351],"category_scores_gemma":[0.02421011,0.0001913592,0.0002629416,0.0005093776,0.0008121008,0.002111256,0.002178926,0.001750368,0.001125602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001892084,"about_ca_system_score_gemma":0.001269531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005379725,"about_ca_topic_score_gemma":0.01209688,"domain_scores_codex":[0.9986349,0.0005474875,0.0000568405,0.000134204,0.0003072889,0.0003193483],"domain_scores_gemma":[0.9888905,0.004222967,0.001542062,0.0002316318,0.0008248892,0.004287978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00293776,0.003781203,0.5975283,0.0001245384,0.00008356458,0.0009232179,0.1374935,0.0004181219,0.005660729,0.006025125,0.0165649,0.2284591],"study_design_scores_gemma":[0.00009652316,0.0008552984,0.7692682,0.0001957317,0.00009237434,0.0004538658,0.2076395,0.001164121,0.001450475,0.002468133,0.01623796,0.00007784212],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989875,0.0001012721,0.000289106,0.0009685977,0.00006773736,0.00001200728,0.00004052091,0.00002462391,0.008621236],"genre_scores_gemma":[0.9966183,0.00004687012,0.000148662,0.0001597092,0.00001089052,0.00001327242,0.00002793932,0.00001574027,0.002958623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009174351,"threshold_uncertainty_score":0.03069127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142501950739508,"score_gpt":0.3070810954036521,"score_spread":0.2928309003297013,"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."}}