{"id":"W4408568537","doi":"10.61091/jcmcc124-24","title":"Design and implementation of intelligent library personalized information recommendation model based on reinforcement learning","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Digital Media and Visual Art","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reinforcement learning; Computer science; Reinforcement; Human–computer interaction; Computer architecture; World Wide Web; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005086178,0.0004838687,0.0008830904,0.0003752364,0.0004429802,0.0007304345,0.001731883,0.0008293683,0.002685984],"category_scores_gemma":[0.001017857,0.0003800113,0.0005768344,0.000364235,0.0003595023,0.0009452673,0.0007474647,0.0009743288,0.0008581427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009007994,"about_ca_system_score_gemma":0.001744995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01903507,"about_ca_topic_score_gemma":0.01217958,"domain_scores_codex":[0.999669,0.00005565587,0.00002109189,0.00009680938,0.00009766511,0.00005981592],"domain_scores_gemma":[0.999689,0.0000725234,0.00003518862,0.00003391126,0.0001355691,0.00003381444],"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":[0.000135044,0.0001678334,0.002646986,0.00008773299,0.00006147818,0.0001182892,0.00008634332,0.8543578,0.006000109,0.006457668,0.003616174,0.1262644],"study_design_scores_gemma":[0.000006095235,0.000009940879,0.00006002846,0.000001565864,0.000004361705,0.000006291568,0.000002801444,0.9988335,0.0004769812,0.000350922,0.0002446375,0.000002885692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02284898,0.0002138085,0.9699545,0.0002848186,0.00004844314,0.0000849177,0.00007159064,0.002306805,0.004186098],"genre_scores_gemma":[0.836674,0.0002605211,0.155194,0.0002343388,0.00003356906,0.0002973048,0.0002506265,0.00008929871,0.00696628],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01903507,"threshold_uncertainty_score":0.03784853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.019723700578176,"score_gpt":0.2909097171920895,"score_spread":0.2711860166139135,"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."}}