{"id":"W4382020887","doi":"10.12688/f1000research.133645.1","title":"The identification of high-performing antibodies for RNA-binding protein TIA1 for use in Western Blot, immunoprecipitation and immunofluorescence","year":2023,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Amyotrophic Lateral Sclerosis Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Mitacs; Ontario Genomics; Ontario Genomics Institute; Merck KGaA; Boehringer Ingelheim; ALS Society of Canada; Takeda Pharmaceuticals International; Bayer; Motor Neurone Disease Association; Pfizer; ALS Association","keywords":"Stress granule; Western blot; RNA-binding protein; Immunoprecipitation; Immunofluorescence; Antibody; Biology; Molecular biology; Gene knockdown; RNA; Messenger RNA; Virology; Gene; Immunology; Genetics; Translation (biology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002251985,0.00243638,0.0008491275,0.001936042,0.001205931,0.001143212,0.001356972,0.001175049,0.009934172],"category_scores_gemma":[0.0028386,0.001044642,0.000884461,0.001311923,0.0005823047,0.0007521437,0.000828514,0.002195652,0.01028047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009651521,"about_ca_system_score_gemma":0.0007297345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008908716,"about_ca_topic_score_gemma":0.002358573,"domain_scores_codex":[0.9984344,0.0003814941,0.0002879385,0.000281408,0.0004109882,0.0002038216],"domain_scores_gemma":[0.9982072,0.0004279463,0.0001560791,0.000469373,0.0006041809,0.0001351904],"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":[0.00008078842,0.00004305401,0.0002356412,0.0001828612,0.00001654713,0.00006974519,0.00004975631,0.00006573328,0.991477,0.0004620307,0.001675224,0.005641628],"study_design_scores_gemma":[0.00005597525,0.0001590475,0.005451746,0.00007515217,0.00007726706,0.0008766819,0.00004998456,0.001279481,0.9372555,0.000422239,0.05426702,0.0000299197],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2799879,0.01104629,0.6494741,0.002904312,0.001558393,0.002991915,0.01395085,0.006403391,0.03168285],"genre_scores_gemma":[0.1797141,0.00674652,0.7361259,0.0008793932,0.0002910504,0.004426755,0.03993972,0.002805302,0.02907118],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009934172,"threshold_uncertainty_score":0.03323305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1095589436657338,"score_gpt":0.3866751835567084,"score_spread":0.2771162398909747,"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."}}