{"id":"W2087904752","doi":"10.1038/nmeth.3170","title":"A robust pipeline for rapid production of versatile nanobody repertoires","year":2014,"lang":"en","type":"article","venue":"Nature Methods","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":535,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Montreal Clinical Research Institute","funders":"National Institute of General Medical Sciences; Fonds de Recherche du Québec - Santé; National Institute of Allergy and Infectious Diseases; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health; Howard Hughes Medical Institute","keywords":"Single-domain antibody; Computational biology; Epitope; Phage display; Recombinant DNA; Protein engineering; Antigen; Biology; Antibody; Chemistry; Molecular biology; Biochemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002686061,0.001293388,0.001310315,0.001310804,0.0008655463,0.001888132,0.001461349,0.0009775837,0.006168188],"category_scores_gemma":[0.002774482,0.001514074,0.0009852101,0.0008630781,0.0006486013,0.001623506,0.002809828,0.003657712,0.005150788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006775767,"about_ca_system_score_gemma":0.001116048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004526104,"about_ca_topic_score_gemma":0.001250324,"domain_scores_codex":[0.997866,0.0002524014,0.0001652552,0.0004911419,0.0009328212,0.0002924096],"domain_scores_gemma":[0.9986065,0.0003886686,0.0001281265,0.0003569858,0.0003076766,0.0002120279],"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":[0.0001245587,0.00008094947,0.0002486666,0.0002367486,0.00003431849,0.00008188026,0.000122944,0.0008978117,0.940495,0.002079282,0.004242738,0.05135508],"study_design_scores_gemma":[0.00006549945,0.000260526,0.0005265158,0.0000393962,0.00003594904,0.0002803253,0.00004910878,0.006514154,0.9373404,0.00244394,0.05239248,0.00005176371],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07230794,0.001874555,0.9018854,0.0007827667,0.0003759708,0.001379167,0.003241255,0.01125435,0.006898573],"genre_scores_gemma":[0.2288675,0.002958039,0.7353868,0.001033654,0.0001913736,0.002741028,0.01280804,0.003466048,0.01254749],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006168188,"threshold_uncertainty_score":0.02063465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05483255117589513,"score_gpt":0.4154840297407529,"score_spread":0.3606514785648577,"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."}}