{"id":"W2727324042","doi":"","title":"Deadlock Avoidance and Detection in Railway Simulation Systems","year":2013,"lang":"en","type":"article","venue":"Les Cahiers du GERAD","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Deadlock prevention algorithms; Computer science; Reservation; Scheduling (production processes); Train; Distributed computing; Deadlock; Real-time computing; Algorithm; Mathematical optimization; Computer network; Mathematics; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001040472,0.0001151567,0.0001351681,0.0001043191,0.00007612845,0.00006805201,0.00004961199,0.0001295407,0.000006866677],"category_scores_gemma":[0.00002042675,0.0001120642,0.00001979193,0.0001582009,0.00003086497,0.0001872243,0.00000550494,0.0001367132,0.00002910347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001081192,"about_ca_system_score_gemma":0.000003009739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007095568,"about_ca_topic_score_gemma":0.0000954092,"domain_scores_codex":[0.9993499,0.00002965768,0.0002014607,0.0001403484,0.0000898069,0.0001888094],"domain_scores_gemma":[0.9997324,0.0000544873,0.00002508313,0.0001136108,0.00002276774,0.0000516315],"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":[0.000001830245,0.000005802697,0.001348514,0.00008558256,0.000007442301,0.000002464744,0.000750514,0.9746933,0.006635786,0.0009014191,0.00005197688,0.01551539],"study_design_scores_gemma":[0.0002422171,0.00001762391,0.01569122,0.00003408409,0.000002620363,0.000009838432,0.000242487,0.9797927,0.0005352107,0.000128744,0.003129457,0.000173856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9649262,0.0009613774,0.03181637,0.00001496777,0.0004811522,0.000175762,7.35943e-7,0.0001628202,0.00146054],"genre_scores_gemma":[0.999363,0.00004271839,0.0001371099,0.000009643255,0.0001166467,0.00004996034,0.000001362808,0.00002105986,0.0002584912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03443674,"threshold_uncertainty_score":0.4569845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003984293277856587,"score_gpt":0.1665356641214028,"score_spread":0.1625513708435462,"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."}}