{"id":"W2526447170","doi":"10.1016/j.tcb.2016.09.009","title":"Enabling the Next 25 Years of Cell Biology","year":2016,"lang":"en","type":"editorial","venue":"Trends in Cell Biology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Sinai Health System; Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"","keywords":"Biology; CRISPR; Nanotechnology; Living cell; Computational biology; Data science; Computer science; Cell biology; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0009431407,0.0003802351,0.0005948158,0.0004008194,0.00005469589,0.00002045319,0.001334401,0.002398632,0.0001986536],"category_scores_gemma":[0.0006429861,0.0002503644,0.0002628579,0.0002566524,0.001015766,0.000003122239,0.000711506,0.0007148196,0.00006982545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004052519,"about_ca_system_score_gemma":0.0003662244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001724702,"about_ca_topic_score_gemma":0.0001708538,"domain_scores_codex":[0.9971007,0.0003158351,0.0008207698,0.000648596,0.0002739785,0.0008401825],"domain_scores_gemma":[0.9978292,0.0005335333,0.0004049326,0.000903834,0.0001893443,0.0001391864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001378531,0.0001288619,0.0001261405,0.0001340862,0.00006345235,0.000003768637,0.00009257537,0.000001564914,0.3757969,0.00001479468,0.4695888,0.1539112],"study_design_scores_gemma":[0.001018567,0.0008701755,0.00003750384,0.00002853321,0.0000226238,6.087068e-7,0.00005900301,0.0000132673,0.05229368,0.0001482565,0.9452087,0.0002991318],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.05369635,0.01600747,0.0005178118,0.0006076535,0.8634857,0.0008048085,0.002634671,0.00005037589,0.06219516],"genre_scores_gemma":[0.3341528,0.04327728,0.0009263907,0.0002819881,0.589829,0.0001180828,0.008498039,0.0001670954,0.02274933],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.4756198,"threshold_uncertainty_score":0.9999949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02320790864835498,"score_gpt":0.317416696351253,"score_spread":0.294208787702898,"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."}}