{"id":"W4385271046","doi":"10.12688/f1000research.133899.2","title":"The identification of high-performing antibodies for Apolipoprotein E for use in Western Blot and immunoprecipitation","year":2023,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Nuclear Receptors and Signaling","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Genentech; Innovative Medicines Initiative; Mitacs; Government of Canada; Ontario Genomics Institute; Emory University; European Federation of Pharmaceutical Industries and Associations; Janssen Pharmaceuticals; Merck KGaA; Ontario Genomics; Genome Canada; Bristol-Myers Squibb; Bayer; Pfizer; Boehringer Ingelheim","keywords":"Western blot; Immunoprecipitation; Antibody; Apolipoprotein B; Disease; Apolipoprotein E; Biology; Immunology; Medicine; Cholesterol; Internal medicine; Endocrinology; Genetics; Gene","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":[0.003731265,0.00289796,0.001113799,0.002888046,0.001726063,0.001314149,0.001826727,0.001704991,0.0226362],"category_scores_gemma":[0.00534247,0.001494686,0.001160104,0.00168774,0.000867993,0.001094239,0.001373477,0.002895321,0.02453309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001050329,"about_ca_system_score_gemma":0.001235829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001465324,"about_ca_topic_score_gemma":0.003854062,"domain_scores_codex":[0.997328,0.0005962034,0.0005189034,0.0004511395,0.0007852016,0.000320468],"domain_scores_gemma":[0.9966786,0.0007429234,0.0002708656,0.0007497463,0.001322473,0.0002353496],"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":[0.0001960747,0.0000785028,0.0004262967,0.000446943,0.00003952205,0.0001973421,0.0001487015,0.0001279152,0.9704589,0.00129624,0.01043321,0.01615034],"study_design_scores_gemma":[0.0001263267,0.0002385882,0.006773392,0.0001876143,0.00008762114,0.001659107,0.0001086131,0.001584195,0.8114831,0.0008678051,0.1767998,0.00008380506],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1409111,0.008910546,0.7554473,0.004676735,0.00278331,0.004938724,0.02428781,0.009757464,0.048287],"genre_scores_gemma":[0.0785018,0.006994104,0.8043899,0.001143058,0.000359524,0.006681099,0.05420135,0.004545669,0.04318353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0226362,"threshold_uncertainty_score":0.07572567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1543236479531629,"score_gpt":0.382584974150828,"score_spread":0.2282613261976651,"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."}}