{"id":"W4412163806","doi":"10.1158/1557-3265.aimachine-a025","title":"Abstract A025: PicoGen: A structure-grounded generative AI model for drugging undruggable targets, including the TEAD–YAP axis","year":2025,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Medicine; Computational biology; Cancer research; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004274075,0.0007255359,0.0006447714,0.000403803,0.0003180011,0.0008981589,0.001596223,0.001284831,0.006442282],"category_scores_gemma":[0.0014791,0.0004380473,0.0009634551,0.0003151898,0.0009267635,0.0006469153,0.001097264,0.001737826,0.0009825666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009512043,"about_ca_system_score_gemma":0.001085253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008105157,"about_ca_topic_score_gemma":0.007638396,"domain_scores_codex":[0.999869,0.00003300206,0.000004927354,0.000037097,0.00003354073,0.00002246552],"domain_scores_gemma":[0.9995713,0.0002642904,0.00003035725,0.00003159444,0.00005778881,0.00004470017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003760664,0.00001786824,0.0004494507,0.00003404019,0.00001974974,0.00004730787,0.00001622534,0.9780411,0.0006665663,0.009912364,0.001995282,0.008762296],"study_design_scores_gemma":[0.000004029125,0.000006679177,0.00001803397,0.00000297008,0.000002437759,0.000005755186,0.000001306278,0.9971769,0.0001285915,0.002233002,0.0004186578,0.000001681851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06355046,0.001467475,0.9061649,0.002123189,0.000256892,0.000137262,0.001709593,0.003553522,0.02103671],"genre_scores_gemma":[0.85897,0.0007787195,0.118297,0.001093035,0.0001853048,0.0003680649,0.002099269,0.0005421158,0.01766637],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008105157,"threshold_uncertainty_score":0.02155155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1359265961266201,"score_gpt":0.5229733592768661,"score_spread":0.387046763150246,"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."}}