{"id":"W1964880353","doi":"10.1093/nar/gkv399","title":"Pathways with PathWhiz","year":2015,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"Genome Alberta; Canadian Institutes of Health Research; Alberta Innovates; Genome Canada","keywords":"SBML; Biology; Computer science; Computational biology; DrugBank; Web server; The Internet; Markup language; World Wide Web; XML","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009661881,0.0001103297,0.0001028128,0.00005741322,0.0001147815,0.00006322038,0.0003230672,0.0001554375,0.00003103217],"category_scores_gemma":[0.00006419983,0.00008424924,0.00003368743,0.0001817977,0.0001887457,0.000004862965,0.000251756,0.0002600763,0.0001939326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002883885,"about_ca_system_score_gemma":0.0002592627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001552882,"about_ca_topic_score_gemma":0.00002058609,"domain_scores_codex":[0.9986638,0.00007611012,0.000142491,0.000236455,0.000419899,0.000461173],"domain_scores_gemma":[0.9989025,0.0000110572,0.00002880079,0.0004848581,0.0003100871,0.0002626952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002007129,0.0004899838,0.0123159,0.0001200158,0.0003102269,0.0001154351,0.002757675,0.0005714979,0.1841687,0.01080476,0.6348557,0.1514829],"study_design_scores_gemma":[0.002516447,0.003216993,0.001609494,0.0000396641,0.000009910223,0.00009972082,0.001986976,0.002193175,0.02140331,0.00375772,0.9626181,0.0005484906],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9043593,0.0007643166,0.002777408,0.0003624949,0.0001135122,0.0003166552,0.00001744112,0.00002626626,0.09126258],"genre_scores_gemma":[0.9953359,0.00007449974,0.002314071,0.0001749739,0.0003428598,0.00002270184,0.00005877604,0.00002821605,0.001647971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3277624,"threshold_uncertainty_score":0.3435585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05560748865350203,"score_gpt":0.3037519630372243,"score_spread":0.2481444743837223,"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."}}