{"id":"W1966519876","doi":"10.1109/foci.2014.7007805","title":"Test problems and representations for graph evolution","year":2014,"lang":"en","type":"article","venue":"","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Benchmark (surveying); Adjacency list; Scalability; Theoretical computer science; Computer science; Graph; Representation (politics); Adjacency matrix; Algorithm; Mathematics","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":[0.004076717,0.001288895,0.0008697647,0.001592146,0.0008404019,0.002339594,0.002152642,0.002220688,0.004683052],"category_scores_gemma":[0.04181496,0.0005357164,0.001762556,0.002003348,0.002520603,0.004917468,0.002216146,0.002973305,0.000514711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002113953,"about_ca_system_score_gemma":0.001279161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00161424,"about_ca_topic_score_gemma":0.00111108,"domain_scores_codex":[0.9960098,0.002094442,0.0002359567,0.0005723676,0.0008478993,0.0002395148],"domain_scores_gemma":[0.9691703,0.02545158,0.001347512,0.002610748,0.001001719,0.0004182018],"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":[0.0002556109,0.000430831,0.002179545,0.0005171738,0.00006750356,0.0001690802,0.0002544969,0.7005398,0.002577835,0.1966869,0.006704084,0.08961716],"study_design_scores_gemma":[0.00008010378,0.0001893468,0.000329627,0.00006850288,0.00002007729,0.0001133486,0.0001217888,0.792294,0.002566398,0.2002838,0.003913516,0.00001948049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1572822,0.0007414718,0.8129897,0.002636362,0.0001627691,0.0006555467,0.001279939,0.001788745,0.02246335],"genre_scores_gemma":[0.4693086,0.0006511683,0.5195349,0.0004319513,0.0001395563,0.001114156,0.003131181,0.000501268,0.005187264],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004683052,"threshold_uncertainty_score":0.02156001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1317087069389292,"score_gpt":0.3906623906985117,"score_spread":0.2589536837595825,"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."}}