{"id":"W2945962433","doi":"10.1101/gr.244830.118","title":"Recompleting the <i>Caenorhabditis elegans</i> genome","year":2019,"lang":"en","type":"article","venue":"Genome Research","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":169,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Core Research for Evolutional Science and Technology; National Institute of General Medical Sciences; National Institutes of Health; National Institute of Food and Agriculture; Japan Science and Technology Corporation; National Institute of Allergy and Infectious Diseases; Japan Agency for Medical Research and Development; Gordon and Betty Moore Foundation; Michigan State University; College of Engineering, Michigan State University; U.S. Department of Agriculture; National Science Foundation","keywords":"Biology; Caenorhabditis elegans; Genome; Genetics; Gene; Caenorhabditis; Genomics; Whole genome sequencing; Sequence assembly; Multicellular organism; Computational biology","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":[0.0004888899,0.0009063554,0.0004843717,0.0007571201,0.0006183488,0.0007274582,0.0009765285,0.0005217275,0.003249293],"category_scores_gemma":[0.00128952,0.0005400378,0.0007449076,0.0007409923,0.0002389517,0.0003800417,0.0006786644,0.001568458,0.002142997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000697297,"about_ca_system_score_gemma":0.001124665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007416618,"about_ca_topic_score_gemma":0.01503018,"domain_scores_codex":[0.9996724,0.00002420626,0.00004083586,0.0000917447,0.0001196708,0.00005108047],"domain_scores_gemma":[0.9993274,0.0001379281,0.00009810326,0.0001699151,0.0001606392,0.0001059536],"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":[0.0003571936,0.00005201617,0.001250296,0.00034318,0.00004321522,0.0004387431,0.0001216248,0.0007096507,0.9734115,0.0006134736,0.003909086,0.01875011],"study_design_scores_gemma":[0.0001113409,0.0003171753,0.03503651,0.0001978412,0.0002550755,0.002000669,0.000151768,0.007629006,0.7498817,0.0005453013,0.2037405,0.000133119],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7675139,0.001880796,0.1098007,0.0006978809,0.001705766,0.001045074,0.0861254,0.009146024,0.02208445],"genre_scores_gemma":[0.4280185,0.001759368,0.2852077,0.0009474853,0.0001252115,0.0006885957,0.2599221,0.005656266,0.01767478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007416618,"threshold_uncertainty_score":0.01474684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03355998618102909,"score_gpt":0.3037409373668502,"score_spread":0.2701809511858211,"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."}}