{"id":"W4416604601","doi":"10.5256/f1000research.136844.r148432","title":"Referee report. For: Identification of highly specific antibodies for Serine/threonine-protein kinase TBK1 for use in immunoblot, immunoprecipitation and immunofluorescence [version 1; peer review: 1 approved]","year":2022,"lang":"en","type":"article","venue":"Faculty of 1000 Research Ltd","topic":"T-cell and B-cell Immunology","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Genentech; Mitacs; Government of Canada; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Ontario Genomics; Genome Canada; ALS Society of Canada; Bayer; Motor Neurone Disease Association; Pfizer; Bristol-Myers Squibb","keywords":"Immunoprecipitation; Specific antibody; Immunofluorescence; Identification (biology); TANK-binding kinase 1; Antibody","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":[0.004580406,0.00080297,0.001219348,0.00340518,0.002563939,0.001976804,0.002375068,0.003395226,0.5552455],"category_scores_gemma":[0.04274902,0.0005234206,0.0009639321,0.002549332,0.0005869265,0.001925087,0.002327518,0.002652953,0.3168619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003118764,"about_ca_system_score_gemma":0.00352314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0252513,"about_ca_topic_score_gemma":0.03730599,"domain_scores_codex":[0.9968283,0.0004351035,0.0003901173,0.0004101958,0.00168632,0.0002499397],"domain_scores_gemma":[0.9544399,0.006464311,0.0007972065,0.002373657,0.03425821,0.00166658],"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":[0.0000140195,0.00001483859,0.00004869535,0.00005466654,0.00000276068,0.0000360037,0.00001721444,0.00001016252,0.0002701565,0.0003080337,0.9941625,0.005060981],"study_design_scores_gemma":[0.00002210714,0.00001740167,0.001378263,0.00006233657,0.00001004298,0.0001200443,0.00007382931,0.00008058493,0.0005928251,0.00113841,0.996474,0.00003014135],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"commentary","genre_scores_codex":[0.001757561,0.004508107,0.0139324,0.2600178,0.3986199,0.002706183,0.08307136,0.007981313,0.2274053],"genre_scores_gemma":[0.008104955,0.002865147,0.008387892,0.03614517,0.03337888,0.001042647,0.0251497,0.002252509,0.8826731],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.5552455,"threshold_uncertainty_score":0.6343883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05379090428294741,"score_gpt":0.336266478805368,"score_spread":0.2824755745224206,"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."}}