{"id":"W4414446263","doi":"10.1016/j.wasman.2025.115145","title":"Phage display screening for highly specific nickel- and cobalt-binding peptides for bio-recovery of metals","year":2025,"lang":"en","type":"article","venue":"Waste Management","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"K1-MET; Alberta Blue Cross; Coventry University; Universität für Bodenkultur Wien; Steirische Wirtschaftsförderungsgesellschaft; Helmholtz-Zentrum Dresden-Rossendorf","keywords":"Isothermal titration calorimetry; Phage display; Peptide; Nickel; Dissociation constant; Metal; Affinities; Titration; Peptide library","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001691653,0.0001097504,0.0001650884,0.0001867561,0.00007685192,0.00006015364,0.00007659663,0.00002902485,0.00001105551],"category_scores_gemma":[0.000009973295,0.0001110576,0.00006273602,0.000143735,0.00001624018,0.0001650141,0.00002997603,0.00002944378,0.000002926634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002144288,"about_ca_system_score_gemma":0.000002858823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.201673e-7,"about_ca_topic_score_gemma":0.000004757865,"domain_scores_codex":[0.9993742,0.000005602194,0.0002471449,0.0001566061,0.00007330175,0.0001431717],"domain_scores_gemma":[0.9996881,0.0000979587,0.00004845147,0.0001105435,0.0000307463,0.00002416052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005286763,0.0002277906,0.0003853056,0.01708891,0.002959643,0.000006815651,0.0005766035,0.1558304,0.07864828,0.3075135,0.2008964,0.2353376],"study_design_scores_gemma":[0.002712375,0.0001355497,0.0004987868,0.0004635493,0.0003330488,0.000001296041,0.003209449,0.07310658,0.1119319,0.001732014,0.8053927,0.0004827456],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06586847,0.001542379,0.9105803,0.0001569132,0.0005916225,0.00101205,0.00007762175,0.0001298291,0.02004085],"genre_scores_gemma":[0.9550869,0.0006555113,0.0223613,0.00006860615,0.00005616725,0.0002078195,0.0000625059,0.00002629664,0.02147483],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8892185,"threshold_uncertainty_score":0.4528799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01931636891137675,"score_gpt":0.2645241809375629,"score_spread":0.2452078120261862,"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."}}