{"id":"W2038649573","doi":"10.1038/nprot.2009.34","title":"Optimization of immunoprecipitation–western blot analysis in detecting GW182-associated components of GW/P bodies","year":2009,"lang":"en","type":"article","venue":"Nature Protocols","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"National Institute of Allergy and Infectious Diseases","keywords":"Immunoprecipitation; Biology; RNA; Polyclonal antibodies; Messenger RNA; Western blot; Molecular biology; RNA-binding protein; Gel electrophoresis; Cell biology; Biochemistry; Genetics; Antibody; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001324882,0.001636577,0.0009229638,0.0007057956,0.001101108,0.0008574639,0.0008406679,0.0005908493,0.002660481],"category_scores_gemma":[0.0007999307,0.001022399,0.0012424,0.00101502,0.0007812227,0.0006791418,0.0007277227,0.001958876,0.001761745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008891633,"about_ca_system_score_gemma":0.0007381267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002010892,"about_ca_topic_score_gemma":0.004922718,"domain_scores_codex":[0.9986497,0.0003079767,0.0002295806,0.0002574688,0.0003160361,0.0002393167],"domain_scores_gemma":[0.9992689,0.0002274936,0.00008156665,0.0002105164,0.0001527931,0.00005861817],"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":[0.000116164,0.00007608234,0.0002087454,0.00003345445,0.000008934072,0.00002636223,0.00002088505,0.00007353142,0.9981714,0.0001155522,0.0000736053,0.001075351],"study_design_scores_gemma":[0.000012898,0.00006541373,0.001930411,0.000002976886,0.000020652,0.00005356237,0.000009161964,0.0008368902,0.9956338,0.00003801239,0.001389302,0.000006875593],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7285794,0.001185401,0.2571154,0.0005833761,0.0002016299,0.002363567,0.003716119,0.002103881,0.00415129],"genre_scores_gemma":[0.5605472,0.001519124,0.4122045,0.00038116,0.00006426813,0.003472032,0.01163381,0.001331208,0.008846752],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002660481,"threshold_uncertainty_score":0.008900225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415094621837172,"score_gpt":0.3356092070174567,"score_spread":0.321458260799085,"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."}}