{"id":"W2510627467","doi":"10.20533/ijels.2046.4568.2011.0006","title":"Reducing Teachers' Cognitive Overload with a Recommender System in the Workplace","year":2011,"lang":"en","type":"article","venue":"International Journal for e-Learning Security","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Ministerio de Ciencia y Tecnología; Consejo Nacional para Investigaciones Científicas y Tecnológicas; Universidad de Costa Rica; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Recommender system; Information overload; Cognition; Computer science; Cognitive load; Psychology; Applied psychology; Cognitive psychology; Multimedia; World Wide Web; Psychiatry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002543088,0.0004976995,0.0009116082,0.00070764,0.0009621649,0.001400748,0.001200755,0.001138896,0.002647778],"category_scores_gemma":[0.01053601,0.0004374893,0.0003624106,0.0003642282,0.00024657,0.001693324,0.001272263,0.0007422189,0.00131438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003320859,"about_ca_system_score_gemma":0.000834632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002725493,"about_ca_topic_score_gemma":0.00470642,"domain_scores_codex":[0.9986475,0.0005719459,0.00008743914,0.0002607554,0.0003323083,0.0001001701],"domain_scores_gemma":[0.9937739,0.003710007,0.0003688449,0.0005904157,0.0009458589,0.0006109494],"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":[0.001464143,0.004286074,0.03967388,0.0006258865,0.0001820782,0.0007513762,0.00825769,0.01432249,0.05711802,0.001766649,0.009748145,0.8618036],"study_design_scores_gemma":[0.002823212,0.008958851,0.1160301,0.0003822428,0.00162099,0.002849135,0.009976847,0.6541563,0.07808691,0.009968995,0.1144509,0.0006954421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7495679,0.0006323199,0.2346997,0.001245697,0.0001448955,0.0002193517,0.00006578148,0.005793945,0.00763029],"genre_scores_gemma":[0.8414107,0.0002667573,0.1528134,0.0002279789,0.0001012353,0.0001649788,0.00008628291,0.0001166299,0.004812052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002725493,"threshold_uncertainty_score":0.01344931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03136923807681625,"score_gpt":0.2817671882216251,"score_spread":0.2503979501448088,"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."}}