{"id":"W4416622012","doi":"10.5256/f1000research.53939.r79888","title":"Referee report. For: Identifying potential drug targets and candidate drugs for COVID-19: biological networks and structural modeling approaches [version 1; peer review: 1 approved with reservations]","year":2021,"lang":"en","type":"article","venue":"Faculty of 1000 Research Ltd","topic":"Pharmacological Receptor Mechanisms and Effects","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Concordia University; Natural Sciences and Engineering Research Council of Canada; Mitacs; National Natural Science Foundation of China; Compute Canada","keywords":"Drug; Biological network; Drug candidate; Drug discovery; Drug repositioning; Precision medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00506362,0.001071138,0.001730244,0.003595061,0.002399208,0.003223571,0.002379968,0.00487937,0.6130666],"category_scores_gemma":[0.06279787,0.0006031797,0.001393168,0.003675859,0.0006306328,0.002487644,0.002434795,0.003425032,0.3913543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003407161,"about_ca_system_score_gemma":0.004584169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02931164,"about_ca_topic_score_gemma":0.03983758,"domain_scores_codex":[0.9969207,0.0004123138,0.0003087363,0.0003036998,0.001846013,0.0002086028],"domain_scores_gemma":[0.932538,0.01138674,0.00117141,0.002662152,0.04985313,0.00238857],"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":[0.00000641007,0.000005791833,0.00001316372,0.00002719948,0.000001345069,0.00001278868,0.000004728126,0.00001036415,0.00004927962,0.0001393992,0.9975486,0.002180733],"study_design_scores_gemma":[0.00004442269,0.00001716633,0.0006477815,0.0001019842,0.00001273323,0.00007329878,0.00006134735,0.0001922388,0.0002718476,0.001615679,0.9969253,0.00003625028],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0006139688,0.00423231,0.008404966,0.3313408,0.4035019,0.001813687,0.0831339,0.008345088,0.1586134],"genre_scores_gemma":[0.005969916,0.004135977,0.007324896,0.06873897,0.05711991,0.001298061,0.02529907,0.003097839,0.8270155],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6130666,"threshold_uncertainty_score":0.5519135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1131912012559993,"score_gpt":0.396314277349507,"score_spread":0.2831230760935077,"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."}}