{"id":"W7133356592","doi":"10.65521/ijeecs.v13i1.65","title":"Natural Language Generation Systems for Automated Content Creation","year":2025,"lang":"","type":"article","venue":"International Journal of Electrical Electronics and Computer Systems","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Greenfield Research (Canada)","funders":"","keywords":"Leverage (statistics); Natural language generation; Adaptation (eye); Content (measure theory); Natural language; Key (lock); Controllability; Text generation","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001120517,0.0003296365,0.000653254,0.0006826746,0.000175822,0.001770586,0.001154044,0.0002117271,6.740909e-7],"category_scores_gemma":[0.0001206345,0.0002950365,0.0002548316,0.0003912776,0.00003490439,0.000558141,0.0001620767,0.0005242734,0.000001151066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008334072,"about_ca_system_score_gemma":0.0007771904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001200173,"about_ca_topic_score_gemma":0.000005638548,"domain_scores_codex":[0.9962361,0.0002776648,0.001634389,0.0005038555,0.0008263409,0.0005216121],"domain_scores_gemma":[0.9957975,0.0003255343,0.001047028,0.0002623307,0.002430766,0.0001368356],"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":[0.0004302527,0.0005059947,0.0002298782,0.0002471312,0.003030418,0.0001120769,0.0009837187,0.08074407,0.01269037,0.6177327,0.01223698,0.2710564],"study_design_scores_gemma":[0.001909971,0.0007065528,0.00009573275,0.0003471854,0.00009147391,0.0005132718,0.0000275318,0.9884323,0.0003929693,0.0001140245,0.00712402,0.0002449348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02300227,0.09519138,0.8617659,0.001112309,0.01822126,0.0005841717,0.000007665176,0.00006845723,0.00004656938],"genre_scores_gemma":[0.9905143,0.001567975,0.003014697,0.0003038422,0.003948793,0.00002496891,0.00001841198,0.00001777688,0.0005892715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.967512,"threshold_uncertainty_score":0.9999502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01872378971481812,"score_gpt":0.2858973520119067,"score_spread":0.2671735622970886,"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."}}