{"id":"W4409317116","doi":"10.1021/acs.jmedchem.5c00071","title":"Development of Galectin-7-Specific Nanobodies: Implications for Immunotherapy and Molecular Imaging in Cancer","year":2025,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"Galectins and Cancer Biology","field":"Immunology and Microbiology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Institute of Cancer Research; Canadian Glycomics Network; Natural Sciences and Engineering Research Council of Canada; Québec Consortium for Drug Discovery; Canadian Institutes of Health Research; Canada Foundation for Innovation; Fonds de Recherche du Québec - Santé","keywords":"Chemistry; Cancer immunotherapy; Immunotherapy; Galectin; Cancer; Molecular imaging; Computational biology; Nanotechnology; Cancer research; Biochemistry; Internal medicine","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":[0.0002498766,0.00007742523,0.0002346393,0.00006614135,0.00004843954,0.000002331627,0.0001140696,0.00007541914,0.00005491485],"category_scores_gemma":[0.00003199751,0.00006405421,0.00004409589,0.00008582453,0.0001108532,0.000015507,0.00001640762,0.0001640788,1.097326e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007884609,"about_ca_system_score_gemma":0.0002858151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001004749,"about_ca_topic_score_gemma":0.000006400565,"domain_scores_codex":[0.9993298,0.00001480358,0.000409231,0.00009652942,0.00001822408,0.0001313921],"domain_scores_gemma":[0.999489,0.00006874468,0.000223061,0.00007224101,0.0001357601,0.00001115589],"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":[0.0001862111,0.00003557937,0.01070368,0.00006317334,0.00008049908,8.706226e-7,0.0002787803,8.210466e-7,0.9341189,0.00004587022,0.0008096349,0.05367604],"study_design_scores_gemma":[0.002064179,0.00003781958,0.02235199,0.0002625298,0.00002142057,0.000101231,0.000582986,3.413565e-7,0.8831731,0.0002992785,0.09103841,0.00006671855],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9244824,0.07130773,0.001592352,0.001698481,0.0002361529,0.00007505667,0.000004633634,0.000002771863,0.000600438],"genre_scores_gemma":[0.9973366,0.001466471,0.0007721629,0.0001759623,0.00002609099,0.00001955957,0.000003160795,0.000004865777,0.0001951677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09022878,"threshold_uncertainty_score":0.2612055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01209005919878,"score_gpt":0.3018220372956767,"score_spread":0.2897319780968968,"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."}}