{"id":"W1837013670","doi":"10.1186/s12896-015-0217-x","title":"Defining the complementarities between antibodies and haptens to refine our understanding and aid the prediction of a successful binding interaction","year":2015,"lang":"en","type":"article","venue":"BMC Biotechnology","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Precision BioLogic (Canada)","funders":"Science and Technology Facilities Council","keywords":"Hapten; Panning (audio); Biology; Antibody; Epitope; Paratope; Antigen; Affinity maturation; Computational biology; Biochemistry; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.0003848958,0.0001013601,0.0002161954,0.0002062297,0.00020951,0.00002406134,0.00009257952,0.0001029041,0.00000443691],"category_scores_gemma":[0.0001718938,0.00005726006,0.00002564069,0.0001835937,0.0002854705,0.00005317368,0.0002566518,0.0002914554,0.000003488037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006104012,"about_ca_system_score_gemma":0.00003553434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007891289,"about_ca_topic_score_gemma":0.000562416,"domain_scores_codex":[0.9991798,0.00004932673,0.0002161363,0.0001723616,0.0001829128,0.0001994581],"domain_scores_gemma":[0.9994814,0.0001863425,0.00007117236,0.00014921,0.0000509926,0.00006083271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003803934,0.00002150753,0.9419445,0.0001453291,0.0001407549,0.000004792033,0.001441035,0.000002824063,0.004485702,0.04598078,0.001484599,0.003967753],"study_design_scores_gemma":[0.005469094,0.005697877,0.4890152,0.001267905,0.0006086866,0.001287145,0.3395852,0.002780161,0.07258922,0.01010938,0.07101624,0.0005738463],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9603123,0.0006657348,0.001774922,0.0364531,0.00008959109,0.0002620055,0.00006153972,0.00004422338,0.0003365884],"genre_scores_gemma":[0.9978389,0.0002336638,0.001596363,0.0001109744,0.00006947892,0.000007859457,0.00002310154,0.00000826966,0.0001113829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4529293,"threshold_uncertainty_score":0.2334997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1502058066850006,"score_gpt":0.362601798103817,"score_spread":0.2123959914188165,"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."}}