{"id":"W2584465509","doi":"10.1109/icmla.2016.0070","title":"Recommendation Model Based on a Contextual Similarity Measure","year":2016,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec","funders":"","keywords":"Computer science; Information retrieval; Similarity (geometry); Personalized search; Process (computing); Recommender system; Measure (data warehouse); Similarity measure; World Wide Web; Data mining; Search engine; 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":[0.0004924831,0.0001053555,0.000115534,0.00007467864,0.00006649979,0.00007001333,0.0003790174,0.00006482878,0.00008982985],"category_scores_gemma":[0.00003572091,0.00006124545,0.00005451813,0.00008907868,0.00001123044,0.000357654,0.00006189555,0.00005656583,0.00003594956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006081883,"about_ca_system_score_gemma":0.00004816064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002405093,"about_ca_topic_score_gemma":0.000022534,"domain_scores_codex":[0.9991126,0.00008211604,0.0001727772,0.000298726,0.0001713005,0.0001624667],"domain_scores_gemma":[0.9992489,0.000107683,0.00005672892,0.0004438165,0.00007750889,0.00006539575],"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":[0.00001405582,0.0001329723,0.0003351293,0.000005730399,0.000009212163,0.000001514773,0.00006806622,0.00003281802,0.001182544,0.19447,0.05422844,0.7495195],"study_design_scores_gemma":[0.000646266,0.0001690982,0.0001386285,0.00004626319,0.000001718735,0.000002180055,0.000004331187,0.9613395,0.01049436,0.01063742,0.01629407,0.0002261787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00009506862,0.000001166269,0.9210437,0.01776656,0.0001127618,0.0001401214,0.000003431058,0.0004405743,0.06039661],"genre_scores_gemma":[0.9417979,0.000001515166,0.05507125,0.002599397,0.00002280932,0.00002776477,0.000001055087,0.000005874872,0.0004724968],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9613067,"threshold_uncertainty_score":0.2497517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04725208670466617,"score_gpt":0.2684620399446501,"score_spread":0.2212099532399839,"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."}}