{"id":"W2398890826","doi":"10.1007/978-1-62703-992-5_6","title":"Screening Hybridomas for Cell Surface Antigens by High-Throughput Homogeneous Assay and Flow Cytometry","year":2014,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Public Health Agency of Canada","funders":"","keywords":"Flow cytometry; Homogeneous; Monoclonal antibody; High-throughput screening; Computer science; Computational biology; Throughput; Antibody; Cytometry; Work flow; Antigen; Immunology; Biology; Bioinformatics; Mathematics; Engineering","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":[0.001230734,0.0006373401,0.0005668217,0.001222414,0.0005026327,0.0006294817,0.0006801303,0.0003367853,0.001301666],"category_scores_gemma":[0.0009438822,0.0003182995,0.0005634446,0.000559565,0.0004016334,0.0007583718,0.0005762848,0.0007514879,0.001014091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003579638,"about_ca_system_score_gemma":0.0003952015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003679882,"about_ca_topic_score_gemma":0.0008553744,"domain_scores_codex":[0.9993284,0.0001692785,0.00005597998,0.00009035395,0.0003006928,0.00005536796],"domain_scores_gemma":[0.999234,0.0003736191,0.00006838459,0.0001518609,0.0001330486,0.00003911332],"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":[0.0001059637,0.0001012619,0.001004308,0.000233838,0.00003867678,0.0001296256,0.00007985131,0.0007888859,0.9209775,0.004005103,0.001728917,0.07080606],"study_design_scores_gemma":[0.00002263679,0.0002143569,0.001587507,0.00001888981,0.00006000564,0.0004085161,0.00002429797,0.004704266,0.9768838,0.001170823,0.01487538,0.00002954247],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05329687,0.002537487,0.9369338,0.0002671026,0.0001519019,0.0006705158,0.0004789287,0.001573164,0.004090288],"genre_scores_gemma":[0.1974216,0.007356172,0.7844266,0.0004227265,0.0001853391,0.001491068,0.001750125,0.0002556321,0.006690684],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001301666,"threshold_uncertainty_score":0.006508827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0231098029846995,"score_gpt":0.3990695819414953,"score_spread":0.3759597789567958,"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."}}