{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004129014,0.0002382827,0.0002455729,0.00003439498,0.000148404,0.000131995,0.0002261269,0.0002455247,0.000003008943],"category_scores_gemma":[0.0000668478,0.0001776781,0.00009204745,0.0001064394,0.00009823951,0.00002306937,0.00009029028,0.0001597605,0.000009523314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001385384,"about_ca_system_score_gemma":0.00005537603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001643373,"about_ca_topic_score_gemma":0.000001364491,"domain_scores_codex":[0.9988192,0.00003640999,0.0004302304,0.0001878825,0.0001506206,0.0003756219],"domain_scores_gemma":[0.9991911,0.00004400613,0.0001652239,0.000436457,0.0000396656,0.0001235174],"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":[0.003815929,0.001449189,0.01944856,0.0008001237,0.0003309213,0.00002269129,0.001349867,0.08520991,0.01005453,0.02676826,0.1177334,0.7330166],"study_design_scores_gemma":[0.003352499,0.006890371,0.02055729,0.0005147893,0.00006881366,0.0001030509,0.00049343,0.9038707,0.002323571,0.003074034,0.05673192,0.002019523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5653009,0.004842609,0.3732218,0.001473442,0.0007123022,0.002268613,0.0001497374,0.000191006,0.05183958],"genre_scores_gemma":[0.9688389,0.0003470374,0.02493815,0.005297693,0.0002666883,0.00001143597,0.0001945444,0.000009765432,0.00009573831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8186608,"threshold_uncertainty_score":0.7245501,"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."}}