{"id":"W2062168656","doi":"10.1109/aiccsa.2007.370734","title":"HELP: A Recommender System to Locate Expertise in Organizational Memories","year":2007,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Recommender system; Key (lock); Collaborative filtering; Order (exchange); Contrast (vision); Case-based reasoning; Knowledge management; World Wide Web; Information retrieval; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015353,0.0007850552,0.0009858082,0.002850639,0.001026647,0.001310692,0.001830527,0.002039865,0.004726406],"category_scores_gemma":[0.006220602,0.0004710895,0.0006754413,0.001676086,0.0002267891,0.002238619,0.001007446,0.0007734571,0.003232607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004808249,"about_ca_system_score_gemma":0.0006316864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01119096,"about_ca_topic_score_gemma":0.02696469,"domain_scores_codex":[0.9993904,0.0001742969,0.00006536633,0.0001433555,0.0001825165,0.00004399072],"domain_scores_gemma":[0.9970029,0.001303746,0.0002167214,0.0004343124,0.0008524365,0.0001899329],"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":[0.001130878,0.0008476504,0.02219739,0.001305975,0.0006326708,0.00128687,0.001250217,0.01607849,0.01961195,0.00628694,0.09182549,0.8375455],"study_design_scores_gemma":[0.000995882,0.001566615,0.02891419,0.0004558971,0.001844057,0.003836689,0.001615384,0.6812139,0.02926746,0.01346597,0.2363347,0.0004892345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1875863,0.006063384,0.7486438,0.002987213,0.0007799045,0.001437189,0.004229022,0.02924664,0.01902664],"genre_scores_gemma":[0.336032,0.001977827,0.637772,0.0006365181,0.0003261229,0.0003986364,0.003917002,0.0002659837,0.01867396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01119096,"threshold_uncertainty_score":0.02225161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02371434803838136,"score_gpt":0.2575644237097692,"score_spread":0.2338500756713879,"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."}}