{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009045028,0.0001024225,0.0001818205,0.0002276776,0.0000925663,0.0002888765,0.0007526677,0.00005437897,0.00002454883],"category_scores_gemma":[0.00002496314,0.00008260501,0.00007392112,0.0001357963,0.00004772876,0.0004000541,0.000122619,0.0001125401,0.00001804697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007281033,"about_ca_system_score_gemma":0.00004256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006908811,"about_ca_topic_score_gemma":0.000005075849,"domain_scores_codex":[0.9987363,0.0001127176,0.0006668626,0.0001694019,0.0002129004,0.000101857],"domain_scores_gemma":[0.997937,0.0001359301,0.0005610934,0.0001903576,0.001085375,0.00009029802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005781474,0.00006432945,0.0003055319,0.000008776385,0.0001243748,0.000001870428,0.0003239996,0.000002710344,0.0004622102,0.2448798,0.005177828,0.7486427],"study_design_scores_gemma":[0.000154639,0.000137369,0.0001568956,0.00009355607,0.000008692959,0.0005139259,0.0004048261,0.006114068,0.007352804,0.006086621,0.9788468,0.0001298286],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001962032,0.000382775,0.9934939,0.002117342,0.001453262,0.0002052365,0.000005060052,0.00004199293,0.002104237],"genre_scores_gemma":[0.9511771,0.0003073576,0.04662866,0.0003304066,0.001265183,0.0000622071,0.000004117941,0.000009514712,0.0002154083],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9736689,"threshold_uncertainty_score":0.3368534,"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."}}