{"id":"W4409576537","doi":"10.61091/jcmcc127a-150","title":"A study on the application of graph convolutional network based joint model in entity relationship extraction","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Graph; Entity–relationship model; Artificial intelligence; Natural language processing; Theoretical computer science; Information retrieval; Relational database","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":[0.001778331,0.001074782,0.0007122464,0.001355529,0.0004529551,0.000868577,0.001297739,0.001016848,0.001401223],"category_scores_gemma":[0.003817898,0.0003210118,0.001041048,0.002022524,0.0004491955,0.00410129,0.0007904164,0.001164783,0.0004554247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001128754,"about_ca_system_score_gemma":0.001126303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01367558,"about_ca_topic_score_gemma":0.01349735,"domain_scores_codex":[0.9993479,0.000174527,0.00003903698,0.0002384746,0.0001197299,0.00008032465],"domain_scores_gemma":[0.9988045,0.0005764352,0.00008081223,0.0002493473,0.0002468046,0.00004212361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004163666,0.0004259369,0.0111299,0.000300302,0.0003845205,0.0004850872,0.000176684,0.4418186,0.01602371,0.02081608,0.009090559,0.4989322],"study_design_scores_gemma":[0.000003877397,0.00002218754,0.0006002579,0.000004791939,0.00002907685,0.00003211863,0.00001000484,0.99375,0.002153502,0.002554343,0.0008346944,0.000005068426],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2222313,0.003242177,0.7634693,0.001422674,0.0002397616,0.0001508117,0.000738213,0.002764651,0.005741105],"genre_scores_gemma":[0.830954,0.002016585,0.1571728,0.0004017966,0.0001002478,0.0001205567,0.002983264,0.0001714787,0.0060794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01367558,"threshold_uncertainty_score":0.02719194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05529836613890533,"score_gpt":0.3606994750947332,"score_spread":0.3054011089558279,"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."}}