{"id":"W4409238785","doi":"10.56028/aetr.13.1.915.2025","title":"Bibliometric research on clustering based on Citespace","year":2025,"lang":"en","type":"article","venue":"Advances in Engineering Technology Research","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cluster analysis; Bibliometrics; Computer science; Library science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.00162893,0.0001409047,0.0001649423,0.08619792,0.0002268087,0.0000814734,0.00192096,0.0001696066,0.000002187962],"category_scores_gemma":[0.001065711,0.0001459215,0.00002596752,0.1714649,0.000168663,0.0002595857,0.0006569952,0.001537289,0.00003206254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003318305,"about_ca_system_score_gemma":0.0001046763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002933887,"about_ca_topic_score_gemma":0.000005270177,"domain_scores_codex":[0.9976086,0.0000781833,0.0002259329,0.0006605147,0.0007040464,0.0007227074],"domain_scores_gemma":[0.9964905,0.002013213,0.00002323672,0.001028644,0.0003937023,0.00005071725],"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":[0.00000832683,0.00008810357,0.0002883114,0.00003623986,0.000001995915,0.00001421583,0.000004335312,0.4300645,0.000358219,0.4925789,0.0001741473,0.07638271],"study_design_scores_gemma":[0.0002647321,0.0002871764,0.0007040686,0.0003371603,3.193643e-7,0.000002195834,0.0000151063,0.8413231,0.005552826,0.09864021,0.05271615,0.0001569078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001507258,0.0008351135,0.983806,0.007091668,0.00009524682,0.0004145546,0.000001182104,0.0007487644,0.005500255],"genre_scores_gemma":[0.8376896,0.0003649308,0.1610088,0.00008785762,0.00001862614,0.0006465046,0.000001308262,0.00001525611,0.0001670921],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8361823,"threshold_uncertainty_score":0.9241592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05588037147441101,"score_gpt":0.4538631514107412,"score_spread":0.3979827799363302,"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."}}