{"id":"W4416658694","doi":"10.5256/f1000research.144167.r173851","title":"Referee report. For: The identification of high-performing antibodies for transmembrane protein 106B (TMEM106B) for use in Western blot, immunoprecipitation, and immunofluorescence [version 1; peer review: 1 approved]","year":2023,"lang":"en","type":"article","venue":"Faculty of 1000 Research Ltd","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","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":"Immunofluorescence; Identification (biology); Antibody; Transmembrane protein; Cricetulus; Membrane protein","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008460217,0.0001711879,0.000516056,0.0003497691,0.0003174758,0.00004331536,0.0003308375,0.0001124073,0.00001235053],"category_scores_gemma":[0.005374687,0.0001168054,0.0001795037,0.0005509035,0.0004185882,0.0002443285,0.0001152752,0.0002982452,0.000005990131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006539253,"about_ca_system_score_gemma":0.0002089391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001369947,"about_ca_topic_score_gemma":0.0002518171,"domain_scores_codex":[0.9964781,0.0001350428,0.0009602069,0.0004304797,0.001481324,0.0005148057],"domain_scores_gemma":[0.9925645,0.001698441,0.0002442018,0.000504541,0.004909933,0.00007835459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.006955134,0.0003199972,0.007752758,0.02586822,0.0003134274,0.00001353503,0.001821668,0.0000210805,0.879248,0.0006533624,0.0491823,0.02785053],"study_design_scores_gemma":[0.006006022,0.002202075,0.1574409,0.008680505,0.0001875095,0.00005217001,0.001739163,0.004705882,0.4335023,0.001034703,0.3840284,0.0004203642],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.930294,0.003539897,0.0008398698,0.05564773,0.00006417499,0.00804485,0.001512818,0.00002827668,0.00002833855],"genre_scores_gemma":[0.7640877,0.01665512,0.005659112,0.00007273061,0.0001815165,0.003283262,0.007962872,0.00009446187,0.2020032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4457456,"threshold_uncertainty_score":0.6434391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08832974465368988,"score_gpt":0.4043724377707124,"score_spread":0.3160426931170225,"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."}}