{"id":"W4380153196","doi":"10.1080/19420862.2023.2218951","title":"Affinity-controlled capture and release of engineered monoclonal antibodies by macroporous dextran hydrogels using coiled-coil interactions","year":2023,"lang":"en","type":"article","venue":"mAbs","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal; National Research Council Canada","funders":"Fonds de recherche du Québec – Nature et technologies; European Research Council; Natural Sciences and Engineering Research Council of Canada; Xunta de Galicia; Agencia Estatal de Investigación; Canada First Research Excellence Fund; Canada Research Chairs; Polytechnique Montréal","keywords":"Monoclonal antibody; Self-healing hydrogels; Chemistry; Dextran; Peptide; Antibody; Biophysics; Trastuzumab; Ligand (biochemistry); Biochemistry; Receptor; Polymer chemistry; Biology; Immunology","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":[0.0002844759,0.0001561412,0.000311011,0.0002162959,0.0000745257,0.00003549406,0.0001357643,0.00009528662,0.0001094908],"category_scores_gemma":[0.0003729295,0.0001497443,0.00007279007,0.0003608961,0.0001061137,0.00008299382,0.00007311433,0.0003405147,0.00003108623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004458851,"about_ca_system_score_gemma":0.00002490846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001282857,"about_ca_topic_score_gemma":0.0000194325,"domain_scores_codex":[0.9988666,0.00004065065,0.0003024688,0.0001736773,0.0002803779,0.0003362948],"domain_scores_gemma":[0.9991931,0.0003896252,0.00003592127,0.0001811033,0.00005916269,0.0001411147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002010231,0.00009671271,0.002325186,0.0007260315,0.0004550979,0.0001371125,0.0009746839,0.01852787,0.9540352,0.0001903761,0.01013514,0.01219558],"study_design_scores_gemma":[0.004429164,0.0000580788,0.003076706,0.0002998456,0.00009685074,0.00007287104,0.0003827011,0.9108633,0.07058768,0.0003572699,0.009222968,0.0005524956],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964052,0.000727289,0.001265879,0.0001866639,0.000220195,0.000178723,0.00007575042,0.000304414,0.0006359114],"genre_scores_gemma":[0.9981772,0.0002410193,0.001066511,0.00001181275,0.00005434948,0.00001567498,0.00003382764,0.00003908821,0.0003605094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8923355,"threshold_uncertainty_score":0.6106396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01732146013533491,"score_gpt":0.2752813047295818,"score_spread":0.2579598445942469,"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."}}