{"id":"W4405181977","doi":"10.1158/1538-8514.cancerchem24-ia002","title":"Abstract IA002: Leveraging synthetic lethality for the development of novel cancer therapies","year":2024,"lang":"en","type":"article","venue":"Molecular Cancer Therapeutics","topic":"Cancer-related gene regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Synthetic lethality; Genetic screen; Cancer; Lethal allele; Biology; RNA interference; Cancer cell; Gene; Population; Mutant; Cancer research; Computational biology; Genetics; Medicine","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":[0.001156589,0.0009301308,0.000760054,0.001396864,0.0005569118,0.002947813,0.001403,0.001789238,0.03086829],"category_scores_gemma":[0.001210207,0.0004443101,0.0006784646,0.0009738721,0.0006820217,0.001844755,0.001476218,0.003416091,0.01718661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001113058,"about_ca_system_score_gemma":0.001019809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004692432,"about_ca_topic_score_gemma":0.0007095443,"domain_scores_codex":[0.999535,0.0000771818,0.00003423837,0.0000790192,0.0002201514,0.00005446226],"domain_scores_gemma":[0.9994411,0.00007172908,0.00006283457,0.00007564449,0.0001812071,0.0001675591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006907001,0.0003356724,0.0004198429,0.002270664,0.00009060834,0.000651954,0.0001015172,0.00265988,0.3137678,0.06715084,0.3577103,0.2541502],"study_design_scores_gemma":[0.0002115378,0.0006134269,0.0007892378,0.0002604558,0.0000686159,0.0006984775,0.00004557745,0.002664919,0.1081609,0.01184946,0.8745512,0.00008618772],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05524982,0.2007073,0.181186,0.07075201,0.07333953,0.00146221,0.02149011,0.0215691,0.3742438],"genre_scores_gemma":[0.2840849,0.1639631,0.09216817,0.01567702,0.008920415,0.001394906,0.02167606,0.002166455,0.409949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03086829,"threshold_uncertainty_score":0.1032647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04465749761615503,"score_gpt":0.3207776675550195,"score_spread":0.2761201699388645,"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."}}