{"id":"W7155097387","doi":"10.70062/globalscience.v1i4.194","title":"Context Sensitive Artificial Intelligence for Dynamic User Behavior Modeling in Next Generation Smart Information Platforms","year":2025,"lang":"","type":"article","venue":"Global Science Journal of Information Technology and Computer Science","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Context (archaeology); Discoverability; Context model; Context awareness; Contextual design; User modeling; Key (lock); Reinforcement learning","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":[0.0007219893,0.0006116116,0.0005084671,0.0004790595,0.0003824529,0.001131695,0.001057376,0.0008361409,0.001299618],"category_scores_gemma":[0.002129182,0.0003980019,0.0006512741,0.0004140976,0.0005300087,0.00173307,0.0008352865,0.001663653,0.0002790561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001059905,"about_ca_system_score_gemma":0.0007351955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008548888,"about_ca_topic_score_gemma":0.009279408,"domain_scores_codex":[0.9995497,0.0001695993,0.00002101323,0.000109584,0.00009226495,0.00005793031],"domain_scores_gemma":[0.9994252,0.0003195645,0.00007085436,0.00005659156,0.00008986838,0.00003799243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009381006,0.0001442535,0.00404646,0.00007915526,0.0000720523,0.0001503493,0.0002428289,0.9415712,0.002697533,0.01940851,0.0009010989,0.0305928],"study_design_scores_gemma":[0.000001394705,0.00001348673,0.0002906146,0.000004487771,0.000004882485,0.000007893157,0.00001269604,0.9957199,0.0001741453,0.003356478,0.0004102059,0.000003883509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.140411,0.0009744958,0.8470424,0.001279501,0.0001241497,0.0001709645,0.0002921092,0.0008634484,0.008842058],"genre_scores_gemma":[0.943534,0.0004649173,0.05298994,0.0002153158,0.00003926181,0.0001406109,0.0001393732,0.00003239966,0.002444114],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008548888,"threshold_uncertainty_score":0.01699823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1088431362706944,"score_gpt":0.3737352199819819,"score_spread":0.2648920837112875,"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."}}