{"id":"W4416345602","doi":"10.1016/j.lfs.2025.124087","title":"CRISPR's impact on cancer: From fundamental models to clinical solutions","year":2025,"lang":"en","type":"article","venue":"Life Sciences","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; Canadian Institute for Military and Veteran Health Research","keywords":"CRISPR; Genome engineering; Genome editing; Chimeric antigen receptor; Genome; Cancer; Synthetic biology; Prime (order theory)","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":[0.0001855155,0.00008638741,0.00009535827,0.00004308457,0.0001377944,0.00002926964,0.0002241993,0.00004599457,0.00003008874],"category_scores_gemma":[0.00004665494,0.00006865008,0.00008408721,0.0001728372,0.0000924604,0.00000314358,0.0001074872,0.00005292036,0.00001043828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001218235,"about_ca_system_score_gemma":0.0001758373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004964268,"about_ca_topic_score_gemma":0.0001552758,"domain_scores_codex":[0.9992064,0.00002155288,0.00014596,0.0003106414,0.0001036178,0.0002117995],"domain_scores_gemma":[0.9996569,0.00002423715,0.00001726321,0.0001653432,0.00001853645,0.0001176945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001979671,0.0002893803,0.100511,0.00001152831,0.0002550457,0.000001937252,0.0002560495,0.5849895,0.1425596,0.001464364,0.1418979,0.02756562],"study_design_scores_gemma":[0.002731196,0.00383013,0.4829715,0.0003423991,0.0001795517,0.000003259553,0.002203935,0.1213592,0.2557267,0.006237089,0.1225185,0.001896664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705287,0.001812908,0.02336856,0.001083482,0.0007764545,0.00009980108,0.0000775477,0.00001338341,0.002239183],"genre_scores_gemma":[0.9970752,0.0002579813,0.0007969688,0.001345756,0.0002571614,0.0000141704,0.000008017833,0.000003418335,0.0002413148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4636304,"threshold_uncertainty_score":0.2799469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05879693736548466,"score_gpt":0.4492888807345983,"score_spread":0.3904919433691136,"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."}}