{"id":"W2151224899","doi":"10.1109/cnsr.2005.24","title":"ARAS: Adaptive Recommender for Academic Scheduling","year":2005,"lang":"en","type":"article","venue":"","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Atlantic Canada Opportunities Agency","keywords":"Computer science; Recommender system; Fragment (logic); Scheduling (production processes); Multimedia; Information retrieval; World Wide Web; Programming language; Mathematical optimization","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002205826,0.00007058887,0.00008251421,0.00005108592,0.00007690353,0.00003820665,0.0003802604,0.00005847727,0.00001331491],"category_scores_gemma":[0.00005067906,0.00006013965,0.00005088767,0.0001242854,0.000009703323,0.0002586385,0.00007100032,0.0002059599,0.00008887263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002298449,"about_ca_system_score_gemma":0.00003458306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002176581,"about_ca_topic_score_gemma":0.000002454412,"domain_scores_codex":[0.9993662,0.00001543287,0.0001315141,0.000204686,0.00008483704,0.0001973164],"domain_scores_gemma":[0.9995715,0.0001141899,0.00004250209,0.000168775,0.00004640626,0.00005664808],"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":[0.000008260972,0.00006552136,0.0003906869,0.000008396806,0.00004012189,0.000001313651,0.000594049,0.02391514,0.0002349588,0.4748887,0.01252848,0.4873244],"study_design_scores_gemma":[0.000182747,0.00004294896,0.00003974892,0.0000099074,0.00000345894,0.000003562061,0.00005758896,0.9504154,0.0003595055,0.007336757,0.04144688,0.000101499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00193884,0.00009091325,0.9586022,0.03648663,0.00008444904,0.00005606437,5.509377e-7,0.000184825,0.002555516],"genre_scores_gemma":[0.3845482,0.00001528065,0.6103558,0.001933521,0.0002849167,0.000004201472,9.011455e-7,0.000005047754,0.002852126],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9265003,"threshold_uncertainty_score":0.2452424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04727799731047518,"score_gpt":0.3283804325154786,"score_spread":0.2811024352050034,"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."}}