{"id":"W4401485258","doi":"10.1101/2024.08.08.607024","title":"Caution when using network partners for target identification in drug discovery","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"","keywords":"Computational biology; Identification (biology); False discovery rate; Locus (genetics); Effector; Genome-wide association study; Gene; Genetic association; Biology; Exome; Drug target; Drug discovery; Exome sequencing; Interaction network; Genetics; Bioinformatics; Phenotype; Single-nucleotide polymorphism; Genotype; Pharmacology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1200178,0.001621633,0.003593044,0.004442087,0.001791012,0.008780607,0.00460908,0.002468043,0.003666388],"category_scores_gemma":[0.2526654,0.001198989,0.001574401,0.003980636,0.003551898,0.006739546,0.00557392,0.007762858,0.003612591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001461477,"about_ca_system_score_gemma":0.002286823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008862009,"about_ca_topic_score_gemma":0.001530045,"domain_scores_codex":[0.8643914,0.103219,0.007066586,0.00504773,0.01947033,0.0008048457],"domain_scores_gemma":[0.7472109,0.1843084,0.01190669,0.03919414,0.01524143,0.002138532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00575314,0.00054442,0.0538198,0.007682824,0.003895859,0.003431135,0.004836565,0.02094869,0.04629239,0.1318005,0.1715757,0.549419],"study_design_scores_gemma":[0.0005916352,0.0009346927,0.01809738,0.002747674,0.001269178,0.004577032,0.001371176,0.1285948,0.1002114,0.3535515,0.3875397,0.0005139908],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05503793,0.01487609,0.8365155,0.04640575,0.007223241,0.001084332,0.003449165,0.01652158,0.0188865],"genre_scores_gemma":[0.2906246,0.002481673,0.6841254,0.01355247,0.001333265,0.001280008,0.001202697,0.00209931,0.003300654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1200178,"threshold_uncertainty_score":0.6347224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01297879621369013,"score_gpt":0.2432397604377605,"score_spread":0.2302609642240704,"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."}}