{"id":"W2098561597","doi":"10.1093/nar/gkl228","title":"The Path-A metabolic pathway prediction web server","year":2006,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Web server; Computer science; Metabolic pathway; Path (computing); Classifier (UML); Organism; Biology; Set (abstract data type); Computational biology; Artificial intelligence; Machine learning; Bioinformatics; The Internet; Genetics; World Wide Web; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000779623,0.002371516,0.001209828,0.002789282,0.0006916242,0.001388583,0.002145612,0.0009695769,0.04765392],"category_scores_gemma":[0.001594604,0.0009291375,0.001684403,0.002964273,0.0001655121,0.001490636,0.001244539,0.001591043,0.03859095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005859196,"about_ca_system_score_gemma":0.001938907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002400565,"about_ca_topic_score_gemma":0.0028244,"domain_scores_codex":[0.9996303,0.00005642596,0.00003139506,0.0001114532,0.0001309408,0.00003947038],"domain_scores_gemma":[0.9994057,0.0001603764,0.00006913819,0.0001204192,0.000175612,0.00006877446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001751624,0.0003508018,0.008187033,0.002608598,0.0004225038,0.0006037854,0.0001026723,0.01229698,0.02036193,0.006121539,0.837774,0.1094185],"study_design_scores_gemma":[0.001084649,0.0004693379,0.01436975,0.0004724705,0.0003455401,0.001553513,0.0001980241,0.234102,0.0496693,0.02612829,0.6713355,0.0002715542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.01390758,0.001068257,0.08801591,0.000366719,0.000184387,0.0005716057,0.6564642,0.2277018,0.01171949],"genre_scores_gemma":[0.02536279,0.0007463759,0.1127355,0.0001996751,0.00005378716,0.0007288592,0.847606,0.006615899,0.005951108],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04765392,"threshold_uncertainty_score":0.1594182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01429055804371951,"score_gpt":0.2930937066084847,"score_spread":0.2788031485647652,"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."}}