{"id":"W4411403412","doi":"10.1145/3725404","title":"Fast Maximum Common Subgraph Search: A Redundancy-Reduced Backtracking Approach","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Backtracking; Computer science; Benchmark (surveying); Redundancy (engineering); Graph; Computation; Theoretical computer science; Algorithm","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":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.001270306,0.0001827505,0.0002574601,0.0002782763,0.0001706103,0.0001435047,0.01637764,0.00004390549,0.000003006775],"category_scores_gemma":[0.00006740235,0.00014034,0.0001000316,0.001477189,0.0001731702,0.0007980556,0.01247853,0.0002163292,0.000003073251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001586769,"about_ca_system_score_gemma":0.00001458262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006833125,"about_ca_topic_score_gemma":2.042138e-7,"domain_scores_codex":[0.9981715,0.00002336859,0.0003632919,0.0006190351,0.0005238135,0.0002989723],"domain_scores_gemma":[0.9969978,0.00005486634,0.000227081,0.00257591,0.0001043982,0.00003997439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007279967,0.0005887379,0.001750247,0.001496193,0.0003808226,0.00000130406,0.0004487869,0.00004173493,0.004021809,0.8587556,0.006022935,0.126419],"study_design_scores_gemma":[0.002335446,0.0003140251,0.03427992,0.003220172,0.0003324815,0.000008514791,0.003702649,0.02766301,0.09845387,0.8260511,0.002803063,0.00083578],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7299008,0.0006025948,0.04887603,0.01509469,0.001359688,0.003312208,0.0002076615,0.0005055756,0.2001408],"genre_scores_gemma":[0.8868071,0.00006974948,0.112451,0.0001420614,0.00001862063,0.00001470437,0.00001357894,0.00001160166,0.0004714934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1996693,"threshold_uncertainty_score":0.9955084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05965004820938316,"score_gpt":0.2988278835663659,"score_spread":0.2391778353569828,"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."}}