{"id":"W2555193411","doi":"","title":"Time Preference aware Dynamic Recommendation Enhanced with Location, Social Network and Temporal Information","year":2016,"lang":"en","type":"article","venue":"OpenMETU (Middle East Technical University)","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Recommender system; Preference; Friendship; Point of interest; Point (geometry); Social network (sociolinguistics); Information retrieval; World Wide Web; Data mining; Social media; Artificial intelligence","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":[0.0002428606,0.0001539143,0.0001913491,0.0001564747,0.0002731349,0.0001215676,0.0005749636,0.0001230252,0.00002791758],"category_scores_gemma":[0.00001303961,0.000117005,0.00002989357,0.0007078979,0.0000962039,0.002527065,0.0003636651,0.0001092788,0.00004567237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001684375,"about_ca_system_score_gemma":0.00008216301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002420779,"about_ca_topic_score_gemma":0.0000601296,"domain_scores_codex":[0.999001,0.00009727317,0.0002085436,0.0003007533,0.000159907,0.0002325762],"domain_scores_gemma":[0.9992025,0.00004460499,0.0002073819,0.0002793253,0.0001797822,0.00008640984],"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":[0.0002398463,0.000188386,0.001470066,0.0001004333,0.0001075669,0.00001180825,0.0008276788,0.00002065866,0.001420749,0.121273,0.00730611,0.8670337],"study_design_scores_gemma":[0.01181233,0.003583976,0.04210821,0.002898868,0.0001960784,0.0002617259,0.001485624,0.02734654,0.003324402,0.01613612,0.8857152,0.00513086],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002641692,0.000004011656,0.9870553,0.002076538,0.00004828366,0.000384764,0.000007782185,0.0004074166,0.00737423],"genre_scores_gemma":[0.9810304,0.00001366549,0.01764076,0.00007362271,0.00002350712,0.000006964947,0.0000217146,0.000006972292,0.001182374],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9783887,"threshold_uncertainty_score":0.4771326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02034860211846255,"score_gpt":0.1986574831224988,"score_spread":0.1783088810040362,"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."}}