{"id":"W2891398512","doi":"10.5815/ijisa.2018.09.01","title":"Context-Aware Recommendation Methods","year":2018,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems and Applications","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Recommender system; Preference; Context (archaeology); Focus (optics); Information retrieval; Context analysis; Contextual design; Machine learning; Data science; Artificial intelligence; Data mining; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001733567,0.001690072,0.001868041,0.003944569,0.001093168,0.002388013,0.003269228,0.002137132,0.007169086],"category_scores_gemma":[0.006636399,0.0007739024,0.001726129,0.004508185,0.0004981594,0.002807343,0.001314128,0.001717085,0.00594293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008231833,"about_ca_system_score_gemma":0.001314482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.014838,"about_ca_topic_score_gemma":0.01709597,"domain_scores_codex":[0.9970176,0.000719936,0.0002150898,0.0008800431,0.001018282,0.0001489285],"domain_scores_gemma":[0.9977735,0.0009032146,0.0001099516,0.0004849747,0.0006569277,0.00007149231],"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":[0.0001835847,0.0003268241,0.003184682,0.001027698,0.0006713396,0.000209938,0.000211516,0.04849185,0.004445428,0.02684157,0.0290777,0.8853279],"study_design_scores_gemma":[0.0001388052,0.0002300958,0.002896017,0.0005300379,0.0005233409,0.0009813354,0.0002238757,0.8410519,0.005744923,0.04867093,0.09881971,0.0001890561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005893278,0.01825588,0.9539376,0.0006953694,0.0007267389,0.0005137313,0.0009186284,0.002475149,0.01658358],"genre_scores_gemma":[0.2032187,0.01654087,0.7524999,0.0009692375,0.001158157,0.0008180776,0.002484517,0.0002836275,0.02202695],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.014838,"threshold_uncertainty_score":0.02950329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0437084495564524,"score_gpt":0.3858421175352179,"score_spread":0.3421336679787655,"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."}}