{"id":"W4417465128","doi":"10.1080/17576180.2025.2601855","title":"Accelerating the discovery of MET inhibitors powered by high-throughput hit identification","year":2025,"lang":"en","type":"editorial","venue":"Bioanalysis","topic":"Melanoma and MAPK Pathways","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Onex (Canada)","funders":"","keywords":"Identification (biology); Drug discovery; Key (lock); Drug industry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007150033,0.002203033,0.001776245,0.001554766,0.001146197,0.004437193,0.002656883,0.008244948,0.007061421],"category_scores_gemma":[0.01022405,0.001020294,0.001363501,0.0008446886,0.001303648,0.004064011,0.001688787,0.01533489,0.005737847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002289228,"about_ca_system_score_gemma":0.002270179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008045546,"about_ca_topic_score_gemma":0.003383189,"domain_scores_codex":[0.9971532,0.0004147041,0.0002635776,0.0002913312,0.001629744,0.0002475237],"domain_scores_gemma":[0.9929871,0.002279109,0.0003820506,0.0001640929,0.002815965,0.001371657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001425289,0.00002500558,0.00003664809,0.0003182655,0.00004742144,0.0001384213,0.00001453372,0.00006827419,0.0006257831,0.00127149,0.9797359,0.01757582],"study_design_scores_gemma":[0.0002616782,0.0001322785,0.000234629,0.000185656,0.0001102758,0.0002166496,0.0000234984,0.000468444,0.001155981,0.002086422,0.9950996,0.00002497649],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0005783388,0.05464528,0.001852168,0.08331256,0.8530596,0.0001085564,0.0002358549,0.000370859,0.005836738],"genre_scores_gemma":[0.005158053,0.05683561,0.001287241,0.0810393,0.8133194,0.0001211576,0.0002444081,0.0001479155,0.04184698],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.008244948,"threshold_uncertainty_score":0.03781348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005987982221905168,"score_gpt":0.2411850595054003,"score_spread":0.2351970772834951,"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."}}