{"id":"W2111895662","doi":"10.1109/enabl.2001.953427","title":"Intelligent agent in electronic commerce-XMLFinder","year":2002,"lang":"en","type":"article","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Intelligent agent; XML; Key (lock); Recommender system; The Internet; Agent architecture; Architecture; Case-based reasoning; Term (time); World Wide Web; E-commerce; Computer security; 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":[0.003069661,0.0006197483,0.0008292301,0.002227698,0.001126864,0.005043782,0.002181309,0.004367123,0.006165668],"category_scores_gemma":[0.005326218,0.0006732572,0.0007965994,0.003022064,0.002452937,0.009255001,0.002011318,0.003267448,0.003620435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001205806,"about_ca_system_score_gemma":0.001094117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002110374,"about_ca_topic_score_gemma":0.00184805,"domain_scores_codex":[0.9972645,0.001186575,0.0002535106,0.0002798086,0.000906396,0.0001092515],"domain_scores_gemma":[0.9981805,0.0009662414,0.0001251235,0.0003452624,0.000283823,0.00009906806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000642314,0.0001169825,0.0005210596,0.0003612141,0.00003869066,0.0005052586,0.0004572831,0.009720886,0.00201166,0.7903289,0.02186794,0.1740058],"study_design_scores_gemma":[0.00007211691,0.0000596946,0.000369269,0.0003536415,0.00006269864,0.001489807,0.0001980303,0.08411358,0.007054764,0.4468564,0.4592944,0.00007566816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002883267,0.01176448,0.9269921,0.005626873,0.001071174,0.0003099837,0.0002445046,0.00324846,0.04785905],"genre_scores_gemma":[0.05631038,0.008693152,0.8940367,0.001952141,0.0007154315,0.0003437797,0.000779845,0.0005250582,0.03664361],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006165668,"threshold_uncertainty_score":0.02062619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04642892065454889,"score_gpt":0.2587757660812934,"score_spread":0.2123468454267445,"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."}}