{"id":"W4413368058","doi":"10.1007/978-3-031-90573-5_3","title":"Architectural Deep Dive into Large Language Models","year":2025,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Computer science; Artificial intelligence; Natural language processing","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":[0.001026594,0.0008393691,0.0007181854,0.0007187692,0.0007248676,0.003022384,0.001575773,0.000886902,0.01799924],"category_scores_gemma":[0.004701912,0.001128756,0.001488194,0.001266782,0.001430072,0.01077347,0.002916403,0.00441316,0.008802701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009494572,"about_ca_system_score_gemma":0.001217705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002209582,"about_ca_topic_score_gemma":0.005617263,"domain_scores_codex":[0.9994231,0.0001947881,0.0000386522,0.0001168591,0.0001866531,0.00003998037],"domain_scores_gemma":[0.9979316,0.001087929,0.00004181085,0.0007211116,0.0001473317,0.00007030759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006563213,0.00005604623,0.000448459,0.0002301139,0.00005505505,0.0001250684,0.0006875207,0.01594184,0.004224558,0.7402226,0.037034,0.2009092],"study_design_scores_gemma":[0.000007650416,0.00001714175,0.0000973277,0.00004829912,0.0000344765,0.0001242109,0.0001249991,0.1361219,0.002565855,0.7624114,0.09843268,0.00001388001],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.005202645,0.001041553,0.9571454,0.002257298,0.0001656991,0.00004772716,0.0005473117,0.005507024,0.02808526],"genre_scores_gemma":[0.170017,0.003126944,0.748627,0.00169453,0.0004332354,0.0002163779,0.003561474,0.005888005,0.06643549],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01799924,"threshold_uncertainty_score":0.06021345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06410466795799205,"score_gpt":0.3517674512652404,"score_spread":0.2876627833072484,"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."}}