{"id":"W4407736999","doi":"10.1109/ickg63256.2024.00052","title":"OrbitSI: An Orbit-based Algorithm for the Subgraph Isomorphism Search Problem","year":2024,"lang":"en","type":"article","venue":"","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Tezpur University; Queen's University; Engineering and Physical Sciences Research Council; Ministry of Education; Queen's University Belfast","keywords":"Subgraph isomorphism problem; Induced subgraph isomorphism problem; Isomorphism (crystallography); Computer science; Orbit (dynamics); Mathematics; Theoretical computer science; Engineering; Aerospace engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001189196,0.001730454,0.001621351,0.004399751,0.001303943,0.002038244,0.002841471,0.001680954,0.008717159],"category_scores_gemma":[0.005715221,0.000674515,0.001602486,0.005275248,0.001194701,0.00429678,0.002765437,0.001933149,0.003626553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001811987,"about_ca_system_score_gemma":0.003751309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007084743,"about_ca_topic_score_gemma":0.01320268,"domain_scores_codex":[0.9989046,0.0001807113,0.0001054919,0.0002805614,0.0004026556,0.0001260544],"domain_scores_gemma":[0.9984169,0.0006541084,0.0001272803,0.0004581775,0.0002577077,0.00008587098],"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":[0.0005769384,0.000378381,0.003539901,0.0005729474,0.0002070312,0.0001647101,0.0003449699,0.1008243,0.007536651,0.03567547,0.05747906,0.7926996],"study_design_scores_gemma":[0.0001985469,0.0001670543,0.000653762,0.00005459134,0.00005732094,0.0002513525,0.0002343024,0.9160553,0.006518921,0.05596703,0.01980219,0.0000396604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02676828,0.0008657094,0.9444027,0.0006785285,0.0003057565,0.0005182433,0.001860002,0.01546455,0.0091362],"genre_scores_gemma":[0.07585415,0.0003489348,0.9099457,0.0002380818,0.0001047353,0.0004806089,0.007195962,0.001240687,0.004591189],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008717159,"threshold_uncertainty_score":0.02916175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02838795631835037,"score_gpt":0.2904489951535391,"score_spread":0.2620610388351887,"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."}}