{"id":"W4411403346","doi":"10.1145/3744746","title":"A Comprehensive Overview of Large Language Models","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Intelligent Systems and Technology","topic":"Topic Modeling","field":"Computer Science","cited_by":488,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Context (archaeology); Benchmarking; Frontier; Data science; Engineering ethics; Management science; Political science; Engineering; Management","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":[0.003503855,0.001737053,0.001459119,0.004465573,0.0007505256,0.004408585,0.002607852,0.001740491,0.0101801],"category_scores_gemma":[0.01213802,0.0009723078,0.002192413,0.005422747,0.0008275392,0.006518172,0.002088067,0.002954376,0.007107844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001757167,"about_ca_system_score_gemma":0.003431213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005581778,"about_ca_topic_score_gemma":0.006109043,"domain_scores_codex":[0.9973854,0.001045759,0.0002951229,0.0004219268,0.0007491369,0.0001026403],"domain_scores_gemma":[0.9939644,0.004345627,0.0002787711,0.0006233522,0.0006724796,0.0001154213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001097258,0.0001183819,0.002125902,0.004219814,0.0003959105,0.0003827566,0.0004809221,0.0510775,0.002023827,0.1914044,0.09091377,0.656747],"study_design_scores_gemma":[0.00002325386,0.00008463606,0.001411013,0.001423393,0.0001828638,0.0006307563,0.0001858462,0.1938123,0.001348266,0.3229011,0.4778834,0.000113182],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.002703269,0.1749848,0.7742202,0.008656428,0.001108882,0.0003236845,0.00836263,0.005980137,0.02365993],"genre_scores_gemma":[0.1168833,0.2717656,0.5455529,0.004233782,0.00604511,0.001974741,0.03205152,0.002558035,0.01893493],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.0101801,"threshold_uncertainty_score":0.03405577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04191685863724989,"score_gpt":0.307768274351576,"score_spread":0.2658514157143261,"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."}}