{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006194807,0.0008266353,0.0012878,0.002855488,0.003235485,0.002629503,0.002630668,0.005021819,0.5397615],"category_scores_gemma":[0.06820409,0.0005018038,0.001102869,0.002172078,0.0007244232,0.002162248,0.002651303,0.00358697,0.3101566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003511392,"about_ca_system_score_gemma":0.005183328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02476488,"about_ca_topic_score_gemma":0.03765224,"domain_scores_codex":[0.9954109,0.0006524505,0.0005427602,0.0006070354,0.002449535,0.0003373815],"domain_scores_gemma":[0.9276581,0.009217526,0.001032306,0.003675821,0.05598564,0.002430545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001195853,0.00001126216,0.00004826798,0.00003984682,0.000002236408,0.00004467951,0.00001798071,0.000007135848,0.0001523907,0.0003060538,0.9954116,0.003946467],"study_design_scores_gemma":[0.00002127806,0.00001453147,0.0009521656,0.00007712493,0.000008984025,0.0001445592,0.0001059589,0.00007113367,0.0004021694,0.001018325,0.9971558,0.00002807375],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"commentary","genre_scores_codex":[0.001318532,0.003164478,0.008427404,0.3312321,0.4197623,0.002363368,0.04765166,0.00623829,0.1798419],"genre_scores_gemma":[0.007832287,0.002264224,0.007034498,0.059992,0.03654464,0.001189976,0.01576157,0.002175368,0.8672054],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.5397615,"threshold_uncertainty_score":0.6564744,"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."}}