{"id":"W2731797971","doi":"10.1007/978-3-319-62389-4_6","title":"Constrained Routing Between Non-Visible Vertices","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Routing (electronic design automation); Static routing; Combinatorics; Equal-cost multi-path routing; Set (abstract data type); Line segment; Line (geometry); Routing table; Algorithm; Mathematics; Computer network; Artificial intelligence; Routing protocol","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003998724,0.001354602,0.000968041,0.0006140387,0.0008346813,0.002008382,0.002791052,0.001676927,0.0228081],"category_scores_gemma":[0.002563677,0.000912432,0.0008929214,0.001328942,0.000653723,0.002898952,0.002030904,0.002279127,0.003860914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008305763,"about_ca_system_score_gemma":0.0008767767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001305945,"about_ca_topic_score_gemma":0.001899816,"domain_scores_codex":[0.9994641,0.00009841217,0.0000250518,0.0002030256,0.0001280037,0.00008152494],"domain_scores_gemma":[0.9991498,0.0003746623,0.00008468004,0.0002056404,0.000104031,0.00008121216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004569424,0.0001394294,0.0003550447,0.001142287,0.000123057,0.0005209411,0.0001580313,0.3505491,0.02099452,0.3894953,0.02124373,0.2148216],"study_design_scores_gemma":[0.00006581551,0.0001467933,0.0003677114,0.0002473673,0.00008568649,0.0004326105,0.0001415153,0.5138845,0.01594934,0.4187415,0.04987455,0.0000625533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02659166,0.0008474661,0.916011,0.0005219957,0.0004257756,0.0001313669,0.0008722338,0.0005349417,0.05406357],"genre_scores_gemma":[0.3433311,0.002751753,0.5364249,0.0004092794,0.0001894461,0.0004266353,0.001859665,0.0009447228,0.1136626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0228081,"threshold_uncertainty_score":0.07630074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03226791445916056,"score_gpt":0.2866327263484828,"score_spread":0.2543648118893223,"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."}}