{"id":"W4388699524","doi":"10.3390/app132212338","title":"Event Knowledge Graph: A Review Based on Scientometric Analysis","year":2023,"lang":"en","type":"review","venue":"Applied Sciences","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Beijing Association for Science and Technology; Ministry of Natural Resources of the People's Republic of China; China Scholarship Council; Strong","keywords":"Data science; Computer science; Citation; Field (mathematics); Event (particle physics); Knowledge graph; Graph; Network analysis; Power graph analysis; Information retrieval; World Wide Web; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.006651659,0.001920483,0.003488475,0.04322671,0.0009753133,0.003718275,0.002353511,0.001730035,0.00436004],"category_scores_gemma":[0.0279176,0.001024281,0.002626664,0.04756959,0.001466449,0.007234103,0.001922013,0.001564471,0.0008997177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003252813,"about_ca_system_score_gemma":0.006979063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006870249,"about_ca_topic_score_gemma":0.01023848,"domain_scores_codex":[0.9966081,0.0009099189,0.0006810566,0.0005530288,0.001132599,0.0001153009],"domain_scores_gemma":[0.9747412,0.0186724,0.002160316,0.0005014492,0.003529645,0.0003950068],"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":[0.00008663232,0.00006626816,0.002582949,0.1316143,0.001507046,0.0001978923,0.0004115062,0.001567355,0.0002908523,0.01131954,0.02282939,0.8275263],"study_design_scores_gemma":[0.00004729474,0.0001980664,0.01291439,0.1235104,0.008359506,0.001677891,0.0009447349,0.002948577,0.0009399391,0.02597829,0.8222566,0.0002242698],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004850498,0.9945471,0.001762298,0.0009983862,0.00033052,0.00004824363,0.0001832384,0.00003699165,0.001608206],"genre_scores_gemma":[0.004920402,0.9929907,0.001084764,0.0003023283,0.0002519019,0.00005611183,0.0001928154,0.00001228569,0.0001886564],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9567733,"threshold_uncertainty_score":0.03517771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1278573235042788,"score_gpt":0.4173282751491699,"score_spread":0.2894709516448911,"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."}}