{"id":"W4205560377","doi":"10.7554/elife.68832.sa2","title":"Author response: A human-based multi-gene signature enables quantitative drug repurposing for metabolic disease","year":2021,"lang":"en","type":"peer-review","venue":"","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Drug repositioning; Signature (topology); Repurposing; Computational biology; Drug response; Computer science; Drug; Gene; Biology; Pharmacology; Genetics; Mathematics","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":[0.005743735,0.001058531,0.0009084253,0.001118195,0.001076995,0.002857984,0.001616605,0.005327028,0.1191188],"category_scores_gemma":[0.03226366,0.0005325393,0.001430036,0.001004377,0.000951294,0.001392573,0.001578674,0.004511167,0.03717315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001422923,"about_ca_system_score_gemma":0.003266757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001726581,"about_ca_topic_score_gemma":0.004041297,"domain_scores_codex":[0.9960583,0.001086894,0.0003349039,0.0004194097,0.001803671,0.0002969044],"domain_scores_gemma":[0.9779072,0.007635212,0.001029577,0.001067257,0.01065076,0.001709947],"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":[0.0001436181,0.00001842004,0.0002069799,0.0001206059,0.00001138192,0.00007693403,0.00001259881,0.00008097037,0.0002877043,0.0003361746,0.9888489,0.009855621],"study_design_scores_gemma":[0.0002170987,0.0001208497,0.0008275072,0.0002164417,0.00003299425,0.0001461497,0.0001280125,0.0005027198,0.00174406,0.001661164,0.9943631,0.00003986552],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002791773,0.003231002,0.01056749,0.5113843,0.4037676,0.001004515,0.01698278,0.0046704,0.04560013],"genre_scores_gemma":[0.02880422,0.006609502,0.02313251,0.5010992,0.1150263,0.001603881,0.01121901,0.002471643,0.3100337],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1191188,"threshold_uncertainty_score":0.398492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04310916037415424,"score_gpt":0.3527328442166772,"score_spread":0.3096236838425229,"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."}}