{"id":"W4210797700","doi":"10.14778/3489496.3489504","title":"LargeEA","year":2021,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Scalability; Benchmark (surveying); Exploit; Process (computing); Channel (broadcasting); Partition (number theory); Competitor analysis; Feature (linguistics); Data mining; Artificial intelligence; Database; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001895634,0.002281427,0.00122745,0.003648595,0.001245306,0.002707959,0.004456265,0.001765586,0.03773767],"category_scores_gemma":[0.008922828,0.000821218,0.002343537,0.003295084,0.0007285713,0.005875234,0.004218842,0.002382686,0.02099021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001489233,"about_ca_system_score_gemma":0.002156917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00473474,"about_ca_topic_score_gemma":0.01160768,"domain_scores_codex":[0.9978266,0.0005161927,0.0001170067,0.0008600304,0.0004787087,0.00020146],"domain_scores_gemma":[0.9972881,0.0007766431,0.0001127296,0.001239692,0.0004706604,0.0001122513],"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":[0.0003588291,0.0003108634,0.001851636,0.001267101,0.0003373738,0.0003373754,0.0001953886,0.04307691,0.006372924,0.04456819,0.1934102,0.7079133],"study_design_scores_gemma":[0.0002230555,0.0002757189,0.001742865,0.0002689819,0.000251415,0.0008150476,0.0003596174,0.4598619,0.01743945,0.1475069,0.3711597,0.00009535076],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00930729,0.002577831,0.860348,0.001167702,0.0005649751,0.0007639488,0.01304234,0.07794819,0.03427972],"genre_scores_gemma":[0.06660134,0.001213289,0.8335209,0.00124532,0.0001969284,0.0007520067,0.06387875,0.007501312,0.0250901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03773767,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007208047789126523,"score_gpt":0.2039609482731143,"score_spread":0.1967529004839878,"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."}}