{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.009307927,0.0003327564,0.000510414,0.007105705,0.001477395,0.003626169,0.002515329,0.0002809964,0.00000948908],"category_scores_gemma":[0.001099898,0.0002810255,0.0001343397,0.01261355,0.002597365,0.04559055,0.0008581449,0.0004559359,0.00003650216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009055626,"about_ca_system_score_gemma":0.002126572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002429044,"about_ca_topic_score_gemma":0.00005246056,"domain_scores_codex":[0.993548,0.00002468447,0.003276195,0.0003832328,0.001986812,0.0007810187],"domain_scores_gemma":[0.99313,0.00009581899,0.001652019,0.0004143639,0.004490671,0.0002171004],"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":[0.00009366216,0.00005453772,0.001306474,0.00001685628,0.000006656311,0.000001637609,0.001351491,0.008542444,0.0001385956,0.1628696,0.00005444618,0.8255636],"study_design_scores_gemma":[0.0004536079,0.0003539788,0.004212501,0.0001639245,0.00003634731,0.00008584775,0.009854827,0.9623336,0.001183455,0.02064707,0.0003936213,0.0002812162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4585084,0.00004703384,0.5382065,0.001034087,0.001562425,0.0005232134,0.00001753477,0.00001875879,0.0000821447],"genre_scores_gemma":[0.9737691,0.00009160311,0.02499787,0.001074462,0.00003091983,0.00002158315,0.000005601159,0.000001758323,0.000007049832],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9537911,"threshold_uncertainty_score":0.9999642,"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."}}