{"id":"W4396948208","doi":"10.19173/irrodl.v25i2.7621","title":"Decoding Video Logs: Unveiling Student Engagement Patterns in Lecture Capture Videos","year":2024,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Communication in Education and Healthcare","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Decoding methods; Computer science; Multimedia; World Wide Web; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007437766,0.00009174848,0.0001956797,0.0002494519,0.0001361412,0.0001936471,0.001088039,0.00005063061,0.001885246],"category_scores_gemma":[0.0009495053,0.00006832581,0.00004059009,0.0005724381,0.0000691674,0.0001047222,0.0006699316,0.001480734,0.00003639274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002636295,"about_ca_system_score_gemma":0.0001842402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001782367,"about_ca_topic_score_gemma":0.0004305521,"domain_scores_codex":[0.9971066,0.001432287,0.0004976087,0.0002748284,0.0004547207,0.0002340216],"domain_scores_gemma":[0.9976435,0.001711717,0.00008220272,0.0003091441,0.000196569,0.00005692188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001346025,0.0005404027,0.6033388,0.005980801,0.0002114464,0.00008934439,0.02315917,0.0003738902,0.00006141762,0.1158316,0.01478778,0.2354908],"study_design_scores_gemma":[0.001116518,0.000117531,0.2637759,0.04947786,0.00001985074,0.0000460149,0.07489322,0.002219971,0.00001934572,0.003319851,0.6047059,0.000287969],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2969003,0.4208548,0.002068162,0.22818,0.001675884,0.003910332,0.000150427,0.00007479338,0.04618529],"genre_scores_gemma":[0.9578983,0.04058665,0.00005459081,0.0005532705,0.00005791423,0.0002457666,0.0001551852,0.00001014197,0.0004381892],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.660998,"threshold_uncertainty_score":0.9990272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.191049017977342,"score_gpt":0.5761590575990283,"score_spread":0.3851100396216863,"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."}}