{"id":"W4392473090","doi":"10.1002/smll.202308950","title":"An Automated Single‐Cell Droplet‐Digital Microfluidic Platform for Monoclonal Antibody Discovery","year":2024,"lang":"en","type":"article","venue":"Small","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Monoclonal antibody; Microfluidics; Antibody; Cell; Cell sorting; Nanotechnology; Sorting; Chemistry; Computational biology; Materials science; Computer science; Biology; Immunology; Biochemistry","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":[0.0005961819,0.0005501767,0.0005843683,0.0005934671,0.0003646518,0.0005826098,0.00153614,0.0006511947,0.00192783],"category_scores_gemma":[0.0003877865,0.00038835,0.0003046668,0.0003516261,0.0002774101,0.0005229934,0.0007625046,0.0005370304,0.0009368709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005804932,"about_ca_system_score_gemma":0.001006353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005676216,"about_ca_topic_score_gemma":0.0009892056,"domain_scores_codex":[0.999305,0.00005172956,0.00004051218,0.0001604949,0.0003801815,0.0000620853],"domain_scores_gemma":[0.9997999,0.00005146086,0.00003784919,0.00003018913,0.00005165124,0.00002893694],"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":[0.0001103252,0.00008380452,0.0002701652,0.0001642504,0.00001791676,0.00009122462,0.00002608305,0.001048321,0.9533383,0.001622637,0.001820648,0.04140626],"study_design_scores_gemma":[0.00009185286,0.0004562154,0.001349787,0.00001570541,0.0000336217,0.0004670812,0.00001180783,0.04637046,0.9197832,0.0005046154,0.03083516,0.00008040828],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2213377,0.005281887,0.7485757,0.0009027129,0.00121076,0.001839459,0.003269862,0.008095047,0.0094869],"genre_scores_gemma":[0.3490704,0.001982363,0.638556,0.0004086335,0.0002205916,0.001287387,0.001315907,0.0001117571,0.007046897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00192783,"threshold_uncertainty_score":0.006449223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01727131481704984,"score_gpt":0.2654254541430896,"score_spread":0.2481541393260398,"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."}}