{"id":"W4410057024","doi":"10.18103/mra.v13i4.6346","title":"GHR106, the First in Class Antibody-based GnRH Antagonist for Broad Clinical Applications","year":2025,"lang":"en","type":"article","venue":"Medical Research Archives","topic":"Sexual Differentiation and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Class (philosophy); Antibody; Antagonist; Medicine; Computer science; Pharmacology; Mathematics; Internal medicine; Artificial intelligence; Immunology; Receptor","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":[0.001101247,0.0000853453,0.0001245544,0.0001120327,0.0002709129,0.00003858811,0.0005369989,0.0001229719,0.00004392763],"category_scores_gemma":[0.002537764,0.0000605534,0.0001013925,0.0002310697,0.0008568186,0.000001576465,0.0001777913,0.0003365046,0.00001072436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006816062,"about_ca_system_score_gemma":0.0005551007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002946324,"about_ca_topic_score_gemma":0.0005558805,"domain_scores_codex":[0.9983688,0.0002945445,0.0002922797,0.0003509307,0.0003389225,0.0003544979],"domain_scores_gemma":[0.9982862,0.001125223,0.0000261407,0.0003700996,0.00005132954,0.000140975],"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":[0.002096112,0.00391926,0.2456855,0.0005264925,0.0002242224,0.000007697143,0.0002245614,0.00004369739,0.01753741,0.04172421,0.1017317,0.5862792],"study_design_scores_gemma":[0.001750824,0.0001935469,0.06519961,0.00004113617,0.000004628633,3.318197e-7,0.0001994364,0.004390459,0.001546207,0.003250102,0.923334,0.00008972795],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2805655,0.005008144,0.5103806,0.1467666,0.0006230701,0.005483447,0.0001859626,0.00007352146,0.05091318],"genre_scores_gemma":[0.99306,0.0006363077,0.0002682066,0.003081416,0.0002061921,0.0006533716,0.0006643456,0.00001226336,0.001417888],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8216023,"threshold_uncertainty_score":0.3156984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04634167391080934,"score_gpt":0.4702715513249667,"score_spread":0.4239298774141573,"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."}}