{"id":"W2793698856","doi":"10.1016/j.pharmthera.2018.02.008","title":"The relaxin receptor as a therapeutic target – perspectives from evolution and drug targeting","year":2018,"lang":"en","type":"review","venue":"Pharmacology & Therapeutics","topic":"Pregnancy-related medical research","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of Winnipeg","funders":"National Health and Medical Research Council; State Government of Victoria; Natural Sciences and Engineering Research Council of Canada; Australian Research Council; Norges Forskningsråd; Medical Research Council","keywords":"Relaxin; G protein-coupled receptor; Agonist; Biology; Receptor; Signal transduction; Computational biology; Bioinformatics; Cell biology; Pharmacology; Genetics","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001634855,0.0007214056,0.00160473,0.0002295016,0.0006756419,0.0000658416,0.0006520365,0.0008382608,0.001136599],"category_scores_gemma":[0.00024337,0.0004550676,0.0004692592,0.0005534527,0.001705099,0.00009442824,0.000328518,0.003112295,0.0007735687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008544061,"about_ca_system_score_gemma":0.001693711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004889825,"about_ca_topic_score_gemma":0.000002592343,"domain_scores_codex":[0.9945883,0.001715312,0.0008720916,0.001015026,0.0007442406,0.00106503],"domain_scores_gemma":[0.9949799,0.003134749,0.0004787779,0.0005822366,0.0003741666,0.0004501545],"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":[0.0006298529,0.000493407,0.0000277243,0.00224601,0.01019657,0.00008538977,0.003215492,1.109025e-7,0.0008188189,0.0005012513,0.02746071,0.9543247],"study_design_scores_gemma":[0.001227956,0.0003279698,0.000005390234,0.006170085,0.006101263,0.00005080092,0.0006067588,0.0000921326,0.00008358186,0.001318376,0.9836214,0.0003943279],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00009981464,0.9915279,0.00008456834,0.003535523,0.001519361,0.002269038,0.00005078961,0.0001843271,0.0007286727],"genre_scores_gemma":[0.0002229303,0.9929461,0.0004207565,0.001354446,0.001703099,0.0003707865,0.0001069876,0.000179231,0.00269568],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9561607,"threshold_uncertainty_score":0.9997901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05281680800978449,"score_gpt":0.4102530642263474,"score_spread":0.3574362562165629,"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."}}