{"id":"W4364322167","doi":"10.1109/tsusc.2023.3263172","title":"Critical Path Awareness Techniques for Large-Scale Graph Partitioning","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Computing","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Graph partition; Computer science; Critical path method; Longest path problem; Graph; Partition (number theory); Theoretical computer science; Parallel computing; Algorithm; Mathematics; Shortest path problem; Combinatorics; Engineering","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":[0.0005672589,0.001234627,0.0006196317,0.00225833,0.0008401673,0.0008031321,0.00111543,0.0005791191,0.002221262],"category_scores_gemma":[0.00219084,0.0004763145,0.001003696,0.001773681,0.0006102488,0.001850845,0.001168634,0.001252288,0.0006956549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007917642,"about_ca_system_score_gemma":0.00141635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00337382,"about_ca_topic_score_gemma":0.005839551,"domain_scores_codex":[0.9994554,0.00008455323,0.00003000354,0.0001463003,0.0002162411,0.00006743782],"domain_scores_gemma":[0.9986513,0.0004658209,0.0002286365,0.0003213249,0.0002701223,0.00006279851],"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":[0.0002391614,0.0001584352,0.001941558,0.0004517967,0.0001252881,0.0004009654,0.0005007772,0.2623613,0.05608243,0.02948959,0.01676464,0.6314841],"study_design_scores_gemma":[0.00005635756,0.0001511008,0.001464921,0.00005985915,0.00008567439,0.000466718,0.0003074015,0.8859427,0.03124887,0.05354664,0.02662524,0.0000444801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0134615,0.0008674279,0.9813311,0.0001696501,0.00006222021,0.0001193932,0.0001622521,0.002198121,0.001628321],"genre_scores_gemma":[0.3132847,0.0009064364,0.6802438,0.0002287088,0.0001121195,0.0002779835,0.001330706,0.0005836444,0.003031924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00337382,"threshold_uncertainty_score":0.007430851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01474360344344892,"score_gpt":0.2775236043878273,"score_spread":0.2627800009443784,"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."}}