{"id":"W4393657304","doi":"10.5281/zenodo.6975830","title":"LRGB: Long Range Graph Benchmark","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal","funders":"","keywords":"Benchmark (surveying); Graph; Computer science; Range (aeronautics); Combinatorics; Theoretical computer science; Mathematics; Geography; Materials science; Cartography; Composite material","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","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001389752,0.000317197,0.0002901027,0.000702625,0.004000054,0.001693038,0.006459899,0.0001356018,0.1341332],"category_scores_gemma":[0.000237245,0.000346461,0.0001691975,0.001590966,0.0001936146,0.0004894406,0.004717853,0.0009424274,0.005404717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001290175,"about_ca_system_score_gemma":0.000007353394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002141595,"about_ca_topic_score_gemma":5.064055e-7,"domain_scores_codex":[0.9963341,0.0009670345,0.000358698,0.0009193752,0.000827709,0.0005931116],"domain_scores_gemma":[0.9974623,0.00005522768,0.0002311709,0.001681872,0.0003079958,0.0002614577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001433645,0.0001367781,1.584575e-7,0.0000751962,0.00005359006,0.0001297876,0.0002582238,0.00001850352,0.000008726322,0.003342056,0.9785603,0.01740237],"study_design_scores_gemma":[0.0003265291,0.0002322026,0.00003578261,0.00002496956,0.00002108214,0.000222605,0.00004270546,0.00007660343,0.000007743033,0.001246897,0.9973824,0.0003804513],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004343919,0.000293912,0.01460066,0.0002935508,0.0008357191,0.0005886214,0.9740449,0.00113075,0.008168431],"genre_scores_gemma":[0.0001510524,0.0003559158,0.0002784391,0.0003258524,0.0001800023,1.465381e-7,0.9974739,0.0007785742,0.0004561119],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1287285,"threshold_uncertainty_score":0.9998987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02249260414222057,"score_gpt":0.2316505517257387,"score_spread":0.2091579475835181,"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."}}