{"id":"W7126377987","doi":"10.21428/594757db.4f758025","title":"SAT for Upward Book Embedding: An Empirical Study","year":2025,"lang":"en","type":"article","venue":"","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Embedding; Scalability; Benchmark (surveying); Speedup; Empirical research; Grid; Constraint (computer-aided design)","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":[0.004757703,0.001229702,0.0008864268,0.002338234,0.001050528,0.002270459,0.00208553,0.001584832,0.01561495],"category_scores_gemma":[0.05820479,0.0005913354,0.001202501,0.00510721,0.001371396,0.006207234,0.001316946,0.003200105,0.003501019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00119651,"about_ca_system_score_gemma":0.00101911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0067624,"about_ca_topic_score_gemma":0.009033596,"domain_scores_codex":[0.994698,0.002450567,0.0003162952,0.001197649,0.001049186,0.0002883402],"domain_scores_gemma":[0.9232189,0.06537186,0.002453981,0.00593837,0.002245406,0.0007714267],"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":[0.002556809,0.002510907,0.328425,0.003619165,0.001464842,0.00100111,0.001185551,0.1055165,0.002960213,0.03171266,0.1883645,0.3306828],"study_design_scores_gemma":[0.0004958113,0.001188373,0.1374756,0.0007517582,0.0008298547,0.00433188,0.003147764,0.6960084,0.006164064,0.05267921,0.0967811,0.0001461307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8729004,0.01244361,0.04631274,0.003886974,0.0004645046,0.000397815,0.03166021,0.003666965,0.02826679],"genre_scores_gemma":[0.9211535,0.002417312,0.02115457,0.0007870672,0.0001779954,0.000195624,0.04983699,0.000612752,0.003664161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01561495,"threshold_uncertainty_score":0.05223721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.026634184655245,"score_gpt":0.3685384664883077,"score_spread":0.3419042818330628,"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."}}