{"id":"W1903290628","doi":"10.14742/ajet.1681","title":"Student perception of topic difficulty: Lecture capture in higher education","year":2015,"lang":"en","type":"article","venue":"Australasian Journal of Educational Technology","topic":"Innovations in Educational Methods","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Division of Undergraduate Education; University of Guelph; John D. and Catherine T. MacArthur Foundation","keywords":"Perception; Variety (cybernetics); Affect (linguistics); Psychology; Educational technology; Higher education; Mathematics education; Cognitive psychology; Computer science; Artificial intelligence; Communication","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001746122,0.0002120891,0.0002290201,0.0007209544,0.0002098219,0.001170228,0.0002617008,0.000410281,0.003523425],"category_scores_gemma":[0.01429238,0.0001260127,0.0004438573,0.0005094427,0.0001864932,0.0006357087,0.0007482486,0.0005458793,0.0004608736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002671777,"about_ca_system_score_gemma":0.0002583486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008850406,"about_ca_topic_score_gemma":0.001406445,"domain_scores_codex":[0.9986933,0.000373029,0.00017519,0.0001121217,0.0005218032,0.0001245155],"domain_scores_gemma":[0.9858219,0.00575426,0.005036579,0.0003520551,0.001198517,0.001836677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001547382,0.0002233347,0.9782888,0.00007385305,0.00004930063,0.0000995358,0.001503749,0.0001173566,0.001866556,0.00003127696,0.0001964069,0.01739521],"study_design_scores_gemma":[0.00000249871,0.0002934702,0.996327,0.00002409752,0.00001829057,0.0001848958,0.001886868,0.0003119285,0.0004591231,0.00003584523,0.0004442918,0.00001157053],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987405,0.0001187002,0.0003912173,0.00006119493,0.000008276417,0.00001075619,0.00006052076,0.00000577375,0.0006030715],"genre_scores_gemma":[0.9992336,0.00007669341,0.0002556918,0.00002207507,0.00001250022,0.000007071122,0.00008306767,0.000003503652,0.0003057223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003523425,"threshold_uncertainty_score":0.01178706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05286635453965881,"score_gpt":0.4228023887635898,"score_spread":0.369936034223931,"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."}}