{"id":"W2077570964","doi":"10.1145/2024288.2024295","title":"Constructing expert profiles over time for skills management and expert finding","year":2011,"lang":"en","type":"article","venue":"","topic":"Expert finding and Q&A systems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Profiling (computer programming); Computer science; Knowledge management; Recommender system; Identification (biology); Expert system; Data science; World Wide Web; 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":[0.0002297882,0.0001559285,0.0001800362,0.0001101357,0.0001624605,0.0001346023,0.000371638,0.00005909368,0.00008747784],"category_scores_gemma":[0.00001436304,0.0001259628,0.00005301592,0.0001071476,0.00004300118,0.000343443,0.0002354478,0.00004096624,0.00003103261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003658643,"about_ca_system_score_gemma":0.000009559038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005743387,"about_ca_topic_score_gemma":0.000001522271,"domain_scores_codex":[0.9988387,0.00002699421,0.0002270463,0.0004316596,0.0001535,0.0003220717],"domain_scores_gemma":[0.9993924,0.00008557447,0.00007607779,0.0003334476,0.00002765055,0.00008483163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002671999,0.0002773713,0.01217669,0.000168482,0.000269517,0.00005597063,0.06897826,6.474478e-7,0.008433588,0.5736442,0.07238138,0.2635871],"study_design_scores_gemma":[0.01270064,0.001659194,0.01320609,0.002693636,0.00006735139,0.0009886349,0.03305654,0.1289508,0.6521842,0.0162032,0.130887,0.007402768],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07686362,0.0009742443,0.7697843,0.0005339169,0.001899389,0.001767827,0.000006793636,0.001028095,0.1471418],"genre_scores_gemma":[0.4094881,0.00003228524,0.5789759,0.000603957,0.0002043377,0.0002346571,0.000003154999,0.00002677278,0.01043086],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6437506,"threshold_uncertainty_score":0.5136616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.028034756021939,"score_gpt":0.2618110816060652,"score_spread":0.2337763255841262,"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."}}