{"id":"W4387362770","doi":"10.7554/elife.91645","title":"Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications","year":2023,"lang":"en","type":"article","venue":"eLife","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of General Medical Sciences; National Institute on Aging; Canadian Institutes of Health Research; Genentech; Mitacs; Motor Neurone Disease Association; Ontario Genomics Institute; Government of Canada; Merck KGaA; Ontario Genomics; Genome Canada; Bayer; ALS Society of Canada; McGill University; European Federation of Pharmaceutical Industries and Associations; Emory University; Bristol-Myers Squibb; Pfizer; ALS Association; Michael J. Fox Foundation for Parkinson's Research","keywords":"Antibody; Polyclonal antibodies; Proteome; Antibody Repertoire; Monoclonal antibody; Computational biology; Computer science; Biology; Immunology; Bioinformatics","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":[0.01593157,0.002657695,0.001452579,0.003128108,0.001351913,0.002574065,0.001742458,0.001908774,0.00337695],"category_scores_gemma":[0.01814563,0.0009977572,0.001586843,0.001782978,0.001538323,0.001388847,0.002212984,0.002623801,0.003796484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001226544,"about_ca_system_score_gemma":0.00174225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001656572,"about_ca_topic_score_gemma":0.002236056,"domain_scores_codex":[0.9837247,0.003315968,0.001600417,0.003230389,0.007408859,0.0007197885],"domain_scores_gemma":[0.9877996,0.002746237,0.001288788,0.002513838,0.005374823,0.0002766798],"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":[0.00021403,0.0004089947,0.005811191,0.0006061157,0.0001641415,0.0001145491,0.0003662995,0.00148956,0.9417282,0.001212878,0.002283725,0.04560016],"study_design_scores_gemma":[0.00003608434,0.001201157,0.01479878,0.0002612406,0.0002401409,0.0003506553,0.0001631197,0.01009612,0.9380335,0.001204411,0.03350601,0.0001086912],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.239393,0.0101665,0.7220929,0.001323685,0.001509068,0.004036741,0.003668949,0.006051417,0.01175783],"genre_scores_gemma":[0.3440563,0.006666415,0.623391,0.001869407,0.0003698606,0.00647556,0.007082579,0.001702319,0.008386449],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01593157,"threshold_uncertainty_score":0.08425516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09661445542964307,"score_gpt":0.4500663208041681,"score_spread":0.353451865374525,"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."}}