{"id":"W2149177098","doi":"10.1111/j.0824-7935.2004.00253.x","title":"Purpose‐Based Expert Finding in a Portfolio Management System","year":2004,"lang":"en","type":"article","venue":"Computational Intelligence","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Expert system; Viewpoints; Intelligent agent; Variety (cybernetics); Subject-matter expert; Legal expert system; Context (archaeology); Knowledge management; Artificial intelligence; Data science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005885768,0.00044058,0.0005192432,0.001672523,0.001275708,0.003481649,0.001405018,0.001350957,0.002088189],"category_scores_gemma":[0.01018279,0.0007189579,0.0005021866,0.00111525,0.0007975544,0.005219333,0.002209886,0.0009093271,0.001001029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001073155,"about_ca_system_score_gemma":0.001567172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002677468,"about_ca_topic_score_gemma":0.003737541,"domain_scores_codex":[0.9972758,0.001344694,0.0002520506,0.0003929325,0.000568672,0.0001659499],"domain_scores_gemma":[0.9963531,0.001975578,0.0003423737,0.0006738939,0.0003818096,0.0002731068],"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":[0.001118923,0.001206454,0.04239986,0.0002612718,0.0001868131,0.002453051,0.01858286,0.1508324,0.02982606,0.1625401,0.009499623,0.5810925],"study_design_scores_gemma":[0.00006561427,0.0001901839,0.00353037,0.00007181077,0.00009370554,0.000775947,0.001956597,0.8766347,0.01791652,0.06677033,0.03189726,0.00009711078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1549352,0.0001595754,0.8215335,0.0009152311,0.00001881575,0.000347857,0.0001190114,0.002754084,0.01921681],"genre_scores_gemma":[0.5637159,0.0001264052,0.4280193,0.000149151,0.00001514119,0.0001440696,0.0002364871,0.0001161272,0.007477393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005885768,"threshold_uncertainty_score":0.03112727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04634554656754414,"score_gpt":0.3030290473205264,"score_spread":0.2566835007529822,"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."}}