{"id":"W1991682882","doi":"10.1016/j.nbt.2009.10.007","title":"Towards proteome scale antibody selections using phage display","year":2009,"lang":"en","type":"article","venue":"New Biotechnology","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"Structural Genomics Consortium; Lunenfeld-Tanenbaum Research Institute; University of Toronto; Mount Sinai Hospital","funders":"Canadian Institutes of Health Research; Wellcome Trust","keywords":"Panning (audio); Phage display; Computational biology; Proteome; Antibody; Antigen; Biology; Monoclonal antibody; Dot blot; Gene; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.00009065503,0.0001730492,0.0003133577,0.0003290976,0.000172803,0.00001711331,0.0001718171,0.0004075422,0.0002538112],"category_scores_gemma":[0.00005663769,0.0001381272,0.0001078409,0.0007018787,0.0001740515,0.00006008832,0.00006848853,0.0005937925,0.0001338648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007656574,"about_ca_system_score_gemma":0.0002505056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000480012,"about_ca_topic_score_gemma":0.00002908455,"domain_scores_codex":[0.9986712,0.00002123042,0.0002141399,0.0003419833,0.0002501904,0.0005013056],"domain_scores_gemma":[0.9993838,0.0000122254,0.00004528022,0.0003106067,0.00006007048,0.0001880274],"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":[0.0001497702,0.0001695632,0.00162391,0.00002293472,0.00003499215,0.00009401843,0.00003550131,0.000001936353,0.9408883,0.00240401,0.001144516,0.05343053],"study_design_scores_gemma":[0.001435449,0.001856683,0.03574266,0.0001027707,0.00007616124,0.001868196,0.00004270816,0.001551339,0.853678,0.002945981,0.1003851,0.0003149937],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9476175,0.0004801468,0.006448404,0.03985778,0.0001208011,0.0005106447,0.00001138852,0.0003181118,0.004635276],"genre_scores_gemma":[0.9756479,0.0002651056,0.01554654,0.0008694116,0.0004156314,0.000005403021,0.00003546939,0.00002028369,0.007194281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09924055,"threshold_uncertainty_score":0.5632664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02742932459812822,"score_gpt":0.3639000538176055,"score_spread":0.3364707292194773,"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."}}