{"id":"W2066452988","doi":"10.1586/14789450.2.6.891","title":"Emerging challenges in ligand discovery: new opportunities for chromatographic assay","year":2005,"lang":"en","type":"review","venue":"Expert Review of Proteomics","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Drug discovery; Function (biology); Ligand (biochemistry); Computational biology; Small molecule; False discovery rate; Chromatography; Data science; Chemistry; Computer science; Nanotechnology; Biology; Biochemistry; Materials science; Receptor","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001254688,0.0005972055,0.00395738,0.0004546454,0.00005038896,0.00002313843,0.00039321,0.00029666,0.00007654756],"category_scores_gemma":[0.0003364717,0.00041376,0.00135763,0.0003096431,0.000125739,0.0001532953,0.0001555274,0.0005062467,0.00000907769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001102015,"about_ca_system_score_gemma":0.001245478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005976509,"about_ca_topic_score_gemma":0.00002968974,"domain_scores_codex":[0.996761,0.0002110522,0.00146695,0.0005457341,0.0005028961,0.0005123471],"domain_scores_gemma":[0.9982041,0.0002857082,0.0005586573,0.0005823438,0.0001219588,0.0002472687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002894389,0.00008535908,0.00000106511,0.2695692,0.0001600652,0.00002272744,0.00005938968,8.674881e-9,0.000006239352,0.0007105686,0.004738176,0.7246182],"study_design_scores_gemma":[0.0002442061,0.0001896461,9.315181e-7,0.2888834,0.0002031034,0.00009487889,0.00004032645,0.000002455749,0.0000205466,0.00003576497,0.7100166,0.0002680823],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000002578111,0.9875048,0.0000969813,0.00559077,0.0001392193,0.00526705,0.00007517914,0.00002274494,0.001300648],"genre_scores_gemma":[1.975123e-7,0.9852775,0.008682208,0.0003833367,0.001157107,0.00104854,0.0002790704,0.00009639139,0.003075651],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7243501,"threshold_uncertainty_score":0.9998314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2375703645534478,"score_gpt":0.4434574008996733,"score_spread":0.2058870363462254,"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."}}