{"id":"W4387672632","doi":"10.12688/f1000research.133696.2","title":"Identification of high-performing antibodies for Vacuolar protein sorting-associated protein 35 (hVPS35) for use in Western Blot, immunoprecipitation and immunofluorescence","year":2023,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Cellular transport and secretion","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Genentech; Government of Canada; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Bayer; Pfizer; Bristol-Myers Squibb; Mitacs; Ontario Genomics; Genome Canada; Michael J. Fox Foundation for Parkinson's Research","keywords":"Immunoprecipitation; Western blot; Immunofluorescence; Open peer review; Identification (biology); Antibody; Plant biology; Sorting; Biology; Cell biology; Medicine; Immunology; Computer science; Biochemistry; Gene; Algorithm; Botany","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001776064,0.0002332041,0.000342965,0.0002558413,0.0001327271,0.0001106233,0.0003138456,0.0004650515,0.000001759892],"category_scores_gemma":[0.0006778291,0.0002544447,0.0001354316,0.0001369551,0.0001222069,0.00002148152,0.0002521985,0.0002895272,0.000001174602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005378595,"about_ca_system_score_gemma":0.0001850226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001018535,"about_ca_topic_score_gemma":0.001024348,"domain_scores_codex":[0.997774,0.0001214424,0.0007540727,0.0006431948,0.0003125986,0.0003946602],"domain_scores_gemma":[0.9985326,0.0000692194,0.000380052,0.0004394132,0.0005349945,0.00004371251],"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":[0.0005926506,0.00009454026,0.0153557,0.00112415,0.00009465516,0.000001005484,0.0002953689,0.00009638015,0.9814279,0.00004561524,0.00001198719,0.0008600214],"study_design_scores_gemma":[0.001299425,0.0003930905,0.08904871,0.0008395303,0.0000395528,4.645451e-7,0.0001396157,0.003432257,0.9030584,0.001269899,0.0001422955,0.0003368329],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9739575,0.0006034492,0.01989893,0.00008263541,0.0001064915,0.004935114,0.0003888726,0.00002581078,0.00000118154],"genre_scores_gemma":[0.9826398,0.0003842016,0.001298195,0.000002614463,0.0000739203,0.001934586,0.012011,0.00007626823,0.001579411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0783696,"threshold_uncertainty_score":0.9999908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04088369240044896,"score_gpt":0.3137489663812531,"score_spread":0.2728652739808041,"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."}}