{"id":"W2163262592","doi":"10.1093/bioinformatics/btp701","title":"Pandora, a PAthway and Network DiscOveRy Approach based on common biological evidence","year":2009,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Ontario Institute for Cancer Research","funders":"Michael Smith Health Research BC; Canadian Institutes of Health Research; Government of Ontario; Ontario Institute for Cancer Research","keywords":"Biological network; Biological pathway; KEGG; Computer science; Computational biology; Biological data; Systems biology; Biological database; Perl; Gene ontology; Ontology; UniProt; Domain (mathematical analysis); Biology; Bioinformatics; Gene; Genetics; World Wide Web","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":[0.001483506,0.00121682,0.0009092319,0.009888769,0.001198203,0.001872813,0.001263219,0.0006922646,0.007190502],"category_scores_gemma":[0.005446299,0.0005958286,0.001919677,0.003493438,0.0005317233,0.001713912,0.001898978,0.0009003498,0.0008747064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007124718,"about_ca_system_score_gemma":0.002590548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00438896,"about_ca_topic_score_gemma":0.009396606,"domain_scores_codex":[0.999172,0.0001931258,0.00004904534,0.0003284022,0.0002083355,0.00004918666],"domain_scores_gemma":[0.9978009,0.001280845,0.0002296694,0.000224301,0.0003223721,0.0001418634],"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":[0.001284971,0.0005040377,0.0420351,0.003778463,0.001906641,0.002444466,0.0005571803,0.1107997,0.02299817,0.05732106,0.02619044,0.7301797],"study_design_scores_gemma":[0.0001671975,0.0002011085,0.009374093,0.0002755562,0.0007223845,0.001729598,0.000229904,0.8641571,0.008344559,0.07673968,0.03796766,0.00009121208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04297464,0.001994261,0.9202984,0.0006190437,0.00009424639,0.0006335915,0.01304042,0.01535724,0.00498814],"genre_scores_gemma":[0.1580934,0.0008055171,0.823742,0.0001169846,0.00006318071,0.0005466695,0.01447369,0.0003738255,0.001784815],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009888769,"threshold_uncertainty_score":0.02405459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02156301975521621,"score_gpt":0.2361732331037945,"score_spread":0.2146102133485783,"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."}}