{"id":"W4401863344","doi":"10.1145/3637528.3671895","title":"RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network","year":2024,"lang":"en","type":"article","venue":"","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"End-to-end principle; Computer science; Placer mining; Graph; Artificial neural network; Parallel computing; Artificial intelligence; Geology; Theoretical computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0002049139,0.0002645268,0.0002146963,0.000123907,0.00005976747,0.00018969,0.0001890193,0.0001102239,0.0006963015],"category_scores_gemma":[0.000002923332,0.0002033851,0.00006864271,0.000518069,0.00003212383,0.0003602153,0.0000329111,0.0002837531,0.00006970204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000645849,"about_ca_system_score_gemma":0.00001883548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007623708,"about_ca_topic_score_gemma":0.0002979146,"domain_scores_codex":[0.9987729,0.00003477749,0.0001989439,0.0003569924,0.0001949131,0.000441485],"domain_scores_gemma":[0.9993023,0.00006674386,0.00000727959,0.0003994125,0.00002559116,0.0001986551],"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":[0.0002662382,0.0001675526,0.0178004,0.0009345184,0.0006458663,0.0005280871,0.003888103,0.4748893,0.004390176,0.01356118,0.2431043,0.2398242],"study_design_scores_gemma":[0.0006933728,0.001680007,0.005617918,0.0004003151,0.0002089921,0.000249074,0.0005404856,0.8782606,0.01215893,0.00446614,0.09303194,0.002692226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3064137,0.001431708,0.632189,0.0005464983,0.00126896,0.001342081,0.00006988782,0.01960123,0.03713697],"genre_scores_gemma":[0.9935985,0.00001763156,0.005096155,0.0001723872,0.0003037937,0.00008064999,0.00002345198,0.00009186522,0.0006155359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6871849,"threshold_uncertainty_score":0.8293804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008779542969212524,"score_gpt":0.2203513715379239,"score_spread":0.2115718285687114,"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."}}