{"id":"W2931761232","doi":"10.1080/08874417.2002.11647067","title":"Designing a Knowledge-Based Interface for Intelligent Shopping Agents","year":2002,"lang":"en","type":"article","venue":"Journal of Computer Information Systems","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Interface (matter); Computer science; Human–computer interaction; Operating system","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":[0.001515585,0.0007822325,0.0006652625,0.0006034034,0.0008149314,0.00343022,0.002562776,0.002694139,0.008840358],"category_scores_gemma":[0.006121212,0.0007751435,0.0006900464,0.0004612669,0.0007672792,0.00409368,0.001787078,0.001567168,0.003680257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006375527,"about_ca_system_score_gemma":0.0006940558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001453282,"about_ca_topic_score_gemma":0.001132396,"domain_scores_codex":[0.9989392,0.0003116424,0.0001309734,0.0002238571,0.0003055864,0.00008874873],"domain_scores_gemma":[0.9983197,0.0009043728,0.0001034139,0.0001920461,0.0003581955,0.0001222536],"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":[0.001382379,0.001624044,0.00336064,0.001113096,0.0002447358,0.001700472,0.008122189,0.08935316,0.08220702,0.2088366,0.03507788,0.5669778],"study_design_scores_gemma":[0.0002273055,0.0002553716,0.0005192655,0.000135566,0.0001635975,0.0006267541,0.000470675,0.7945249,0.03767234,0.04475464,0.120502,0.0001476612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008248518,0.00007675878,0.9788449,0.0002293041,0.00004871617,0.0002774059,0.00005961958,0.004453053,0.007761616],"genre_scores_gemma":[0.1687963,0.0001309794,0.8194234,0.0004048327,0.00004164485,0.0007926701,0.000346301,0.000417021,0.009646859],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008840358,"threshold_uncertainty_score":0.02957392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07451325088048391,"score_gpt":0.2926030011179356,"score_spread":0.2180897502374517,"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."}}