{"id":"W2092899907","doi":"10.1016/j.jmb.2005.09.079","title":"Inferring Meaningful Pathways in Weighted Metabolic Networks","year":2005,"lang":"en","type":"article","venue":"Journal of Molecular Biology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":109,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Graph; Metabolic pathway; Metabolic network; Shortest path problem; Matching (statistics); Graph theory; Path (computing); Computer science; Power graph analysis; Mathematics; Combinatorics; Chemistry; Theoretical computer science; Biochemistry; Metabolism; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0004755468,0.0001497628,0.0002699478,0.0001712648,0.00002118919,0.00001006311,0.0001930643,0.0002082632,0.00001027001],"category_scores_gemma":[0.0001122925,0.0001285004,0.0001350438,0.0001590673,0.00003883735,0.000005780893,0.00005770937,0.0002378398,0.000002814014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001481288,"about_ca_system_score_gemma":0.00004582917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005948393,"about_ca_topic_score_gemma":0.00001073506,"domain_scores_codex":[0.9989455,0.0001083032,0.0004368584,0.0001903585,0.00006554218,0.0002533765],"domain_scores_gemma":[0.9994277,0.000003161455,0.0002004697,0.0001879714,0.0001098738,0.00007076153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004804657,0.00004782606,0.0007857381,0.000003120812,0.00005903899,0.00000940647,0.00002263876,0.004813231,0.9803686,0.0005718956,0.000116618,0.01315385],"study_design_scores_gemma":[0.0009849594,0.0002974033,0.001685166,0.00002556174,0.00003623674,0.000355735,0.00001607158,0.0004730027,0.8754565,0.0001411427,0.120289,0.0002392637],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9459573,0.009899906,0.04320528,0.0002053911,0.0005198363,0.00006177874,0.000001642856,0.000006548928,0.0001423323],"genre_scores_gemma":[0.9917948,0.0009912887,0.005806053,0.0002272751,0.001117647,0.000002008286,0.00001281271,0.00001878754,0.00002928431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1201724,"threshold_uncertainty_score":0.5240093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005751807712893399,"score_gpt":0.2284102025923473,"score_spread":0.2226583948794539,"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."}}