{"id":"W4410461307","doi":"10.1016/j.celrep.2025.115726","title":"Machine-guided cell-fate engineering","year":2025,"lang":"en","type":"article","venue":"Cell Reports","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Army Research Office; Intelligence Advanced Research Projects Activity; Office of the Director of National Intelligence","keywords":"Cell fate determination; Computer science; Computational biology; Cell biology; Biology; Transcription factor; Genetics; Gene","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":[0.0006323695,0.0005741207,0.0005202211,0.0004012373,0.0002977457,0.000736776,0.0008435806,0.0004829478,0.002209525],"category_scores_gemma":[0.001066968,0.0003219601,0.0006589636,0.0002491807,0.0006379635,0.0003585733,0.0008235713,0.001017828,0.001042652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005597906,"about_ca_system_score_gemma":0.0006003095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000712465,"about_ca_topic_score_gemma":0.001638549,"domain_scores_codex":[0.9996339,0.00004407729,0.00002320779,0.0001040638,0.0001418125,0.00005285503],"domain_scores_gemma":[0.999574,0.0001881956,0.0000476328,0.00009087173,0.00007324555,0.00002592654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001104877,0.0001082775,0.001425903,0.0002436592,0.0000434807,0.0002057079,0.0001276378,0.145865,0.6876751,0.01918418,0.003075652,0.141935],"study_design_scores_gemma":[0.00001945105,0.0001087368,0.0005742075,0.00002063213,0.00002196687,0.0001758325,0.0000274225,0.5737777,0.3995875,0.007013901,0.01864571,0.00002707388],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05787938,0.0002676755,0.932649,0.0002013267,0.0001105929,0.0001387977,0.0004147745,0.003600033,0.004738392],"genre_scores_gemma":[0.385104,0.0005179337,0.6047033,0.0002504577,0.0000275658,0.0004077512,0.001277505,0.0007444253,0.006967064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002209525,"threshold_uncertainty_score":0.007391572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004195654339543857,"score_gpt":0.2550729750604013,"score_spread":0.2508773207208574,"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."}}