{"id":"W4408146702","doi":"10.1109/icmla61862.2024.00268","title":"iPEERS: A Multi-Layered Expert Recommender System for Enhanced Customer Support","year":2024,"lang":"en","type":"article","venue":"","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Recommender system; Computer science; World Wide Web","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":[0.001958783,0.001082824,0.0009315849,0.002053109,0.0005842717,0.001033005,0.00169865,0.001333841,0.002288142],"category_scores_gemma":[0.00388399,0.000458579,0.000817313,0.001140027,0.0001763519,0.001726362,0.0011446,0.001090268,0.001660912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000496848,"about_ca_system_score_gemma":0.0009146856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01889434,"about_ca_topic_score_gemma":0.04427125,"domain_scores_codex":[0.999072,0.0002061525,0.0000998645,0.000275402,0.0002682816,0.00007821265],"domain_scores_gemma":[0.9984194,0.0005920391,0.0001280671,0.0002335152,0.0004632508,0.0001637881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001495254,0.001734305,0.04939415,0.0006905403,0.000989234,0.0009601233,0.0007556872,0.06090293,0.0329881,0.002416742,0.04340727,0.8042658],"study_design_scores_gemma":[0.0002104536,0.0007737678,0.01309778,0.00007729621,0.000379006,0.0005652941,0.000246612,0.946645,0.01019062,0.002367716,0.02527048,0.0001760275],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2586038,0.003097781,0.6918941,0.002156146,0.0004640184,0.001092488,0.006702508,0.02771116,0.00827802],"genre_scores_gemma":[0.4749887,0.0008944807,0.5072889,0.0007514554,0.0002259384,0.0002553613,0.006129043,0.0001360298,0.009330019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01889434,"threshold_uncertainty_score":0.03756875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06032167456525388,"score_gpt":0.3730864647993418,"score_spread":0.3127647902340879,"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."}}