{"id":"W2035596374","doi":"10.1089/cmb.2009.0047","title":"Maximum Likelihood Genome Assembly","year":2009,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":129,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Genome; De Bruijn graph; De Bruijn sequence; Contig; Hybrid genome assembly; Sequence assembly; Computational biology; Biology; Genetics; Computer science; Algorithm; Mathematics; Combinatorics; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001466822,0.001681123,0.001695535,0.001675711,0.001294167,0.001947961,0.003029036,0.002186728,0.01166609],"category_scores_gemma":[0.006892235,0.00127681,0.002014368,0.001750994,0.0006506745,0.001677322,0.002181247,0.00200291,0.008093952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009806864,"about_ca_system_score_gemma":0.001487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001690473,"about_ca_topic_score_gemma":0.002036442,"domain_scores_codex":[0.9984946,0.0004547762,0.00007927237,0.000531494,0.0003185975,0.0001211278],"domain_scores_gemma":[0.998094,0.0008986538,0.0001464566,0.0004195721,0.0003681942,0.00007307679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009728312,0.0003606631,0.004877008,0.001589781,0.0004513798,0.0009904291,0.0006324538,0.3989322,0.0734472,0.09078088,0.03504722,0.391918],"study_design_scores_gemma":[0.00008865822,0.00007293849,0.0006822787,0.00005597462,0.00005522935,0.0003576179,0.00007307461,0.8931926,0.02035451,0.05400991,0.03098061,0.00007656072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004990659,0.0002345778,0.9862141,0.000122121,0.00006025357,0.0001199691,0.001582669,0.003896135,0.002779506],"genre_scores_gemma":[0.05191153,0.0002538793,0.9343426,0.0001151305,0.00003090952,0.000321692,0.007346047,0.00138651,0.004291811],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01166609,"threshold_uncertainty_score":0.03902698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009191157194856088,"score_gpt":0.2570611932085001,"score_spread":0.247870036013644,"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."}}