{"id":"W4283075104","doi":"10.48550/arxiv.2206.08164","title":"LRGB: Long Range Graph Benchmark","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal","funders":"","keywords":"Computer science; Benchmarking; Transformer; Graph; Theoretical computer science; Attention network; Artificial intelligence; Limiting; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000243877,0.0004809059,0.0004459545,0.0004941939,0.0004013762,0.0001269304,0.004080827,0.0002670582,0.0002236753],"category_scores_gemma":[0.0000157634,0.0005963446,0.0004726452,0.00178381,0.0001589674,0.0006156882,0.00464063,0.001512035,0.00004613394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002370118,"about_ca_system_score_gemma":0.0001039141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000064369,"about_ca_topic_score_gemma":0.00006367433,"domain_scores_codex":[0.9968141,0.0002627869,0.0002580487,0.001821281,0.0002031677,0.000640616],"domain_scores_gemma":[0.9968606,0.0001858746,0.0003479178,0.00224161,0.0001035392,0.0002604422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004561385,0.0001284573,0.01915666,0.00007477037,0.000140155,0.002849878,0.000290887,0.7690551,0.000007112136,0.2052131,0.001649086,0.001389157],"study_design_scores_gemma":[0.001770197,0.0002531474,0.02180818,0.0001778618,0.0002053663,0.00005128004,0.0001331136,0.5057799,0.00004903687,0.4564407,0.01039976,0.002931508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1885458,0.0004406105,0.8021528,0.0001203651,0.002356773,0.0005433671,0.00002595365,0.0007280644,0.005086266],"genre_scores_gemma":[0.9938704,0.0006653013,0.00278837,0.0003032344,0.000112604,0.000004364548,0.00003869722,0.00003555224,0.002181476],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8053246,"threshold_uncertainty_score":0.9996488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05388534934177568,"score_gpt":0.1854765147608865,"score_spread":0.1315911654191108,"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."}}