{"id":"W4403718841","doi":"10.1126/science.adi6884","title":"Impact of CRISPR in cancer drug discovery","year":2024,"lang":"en","type":"article","venue":"Science","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"CRISPR; Identification (biology); Computational biology; Drug discovery; Massively parallel; Gene; Cancer drugs; Cancer; Drug; Biology; Massive parallel sequencing; Genetics; Computer science; Bioinformatics; Genome; Pharmacology","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":[0.001970068,0.000537249,0.0007236066,0.0004296801,0.0003396918,0.001817743,0.0005848801,0.00107182,0.003409526],"category_scores_gemma":[0.002278385,0.0002436657,0.0004428956,0.0003618264,0.0009145993,0.0009676698,0.001114816,0.002125361,0.0007617841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007752218,"about_ca_system_score_gemma":0.0007964134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006499082,"about_ca_topic_score_gemma":0.001104329,"domain_scores_codex":[0.9988531,0.0003629955,0.00004742992,0.0001614431,0.000441561,0.0001335301],"domain_scores_gemma":[0.9986485,0.0008284412,0.00007884573,0.0001636734,0.0001445721,0.0001360896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001221955,0.0003202133,0.002378369,0.001132908,0.0002450461,0.0007071401,0.0001206307,0.01650402,0.5873266,0.07744585,0.01484485,0.2977525],"study_design_scores_gemma":[0.0003166028,0.002751552,0.003738843,0.0003011742,0.0003247287,0.002186313,0.0001870386,0.04096163,0.7347823,0.05194036,0.1623923,0.0001172226],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.4354796,0.1479686,0.279404,0.03516064,0.004262066,0.0004006195,0.003321482,0.005781172,0.08822179],"genre_scores_gemma":[0.900276,0.03696227,0.05078603,0.002729286,0.0003408461,0.00008386389,0.0009480127,0.0001647643,0.007709046],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.003409526,"threshold_uncertainty_score":0.011406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006698729458096745,"score_gpt":0.3763358344638261,"score_spread":0.3696371050057293,"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."}}