{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001518383,0.0006539879,0.0007889618,0.001057599,0.0005220131,0.001026153,0.002123467,0.001212094,0.01059801],"category_scores_gemma":[0.006256606,0.0004478917,0.000554892,0.001095159,0.0001776155,0.001582548,0.0006048385,0.001262181,0.007966463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006131142,"about_ca_system_score_gemma":0.0009859641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008402419,"about_ca_topic_score_gemma":0.01755969,"domain_scores_codex":[0.9992068,0.0002590568,0.00004412233,0.0001561314,0.0002815328,0.00005228191],"domain_scores_gemma":[0.9971916,0.001098328,0.0001468499,0.0006410441,0.0006660269,0.0002561162],"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":[0.001040653,0.0008015403,0.006069378,0.0004216613,0.0001501645,0.0002022046,0.0002132378,0.06452419,0.007551839,0.009310205,0.09838611,0.8113288],"study_design_scores_gemma":[0.0002488127,0.0003490615,0.002420978,0.00003164991,0.00008447563,0.0003483995,0.00008350945,0.8970339,0.006842106,0.005751716,0.08670124,0.0001041925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03079198,0.0008681213,0.9038087,0.0006503324,0.0004087237,0.000510401,0.001906767,0.05070022,0.01035483],"genre_scores_gemma":[0.2494669,0.0006822677,0.7261307,0.000289694,0.0002729738,0.0004083838,0.002682301,0.0009218707,0.01914486],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01059801,"threshold_uncertainty_score":0.03545386,"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."}}