{"id":"W4408170149","doi":"10.1186/s12859-025-06091-7","title":"GoldPolish-target: targeted long-read genome assembly polishing","year":2025,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"Canadian Institutes of Health Research","keywords":"DNA microarray; Computational biology; Genome; Polishing; Sequence assembly; Biology; Computer science; Genetics; Engineering; Gene; Gene expression; Mechanical engineering","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":[0.001652943,0.001683981,0.0009118298,0.0009656703,0.0007259422,0.001313091,0.001666241,0.00108299,0.005613176],"category_scores_gemma":[0.003624722,0.0008938223,0.001689753,0.0007096126,0.0007000263,0.001072717,0.002416053,0.00184057,0.005469233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006165151,"about_ca_system_score_gemma":0.00120874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001754693,"about_ca_topic_score_gemma":0.003604701,"domain_scores_codex":[0.9986237,0.0001404973,0.0001142019,0.0005765648,0.0004339925,0.0001109714],"domain_scores_gemma":[0.9985616,0.000399241,0.0002916008,0.0003952032,0.0002392424,0.000113099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001356983,0.0002074231,0.007978529,0.002075164,0.0004600113,0.0006950642,0.0008326903,0.01262209,0.6731577,0.004847562,0.03581593,0.2599509],"study_design_scores_gemma":[0.0001544676,0.0005154054,0.006570172,0.0001348398,0.0001663754,0.001264804,0.000123735,0.08398074,0.8201351,0.004486954,0.08224021,0.0002271618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06494977,0.001373495,0.8049518,0.0003125792,0.0002584376,0.0005286516,0.004767155,0.1190085,0.003849586],"genre_scores_gemma":[0.1256588,0.0005354656,0.8442991,0.0006890997,0.00005845121,0.0005515311,0.0115014,0.0117151,0.004991143],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005613176,"threshold_uncertainty_score":0.01877797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01112269841700279,"score_gpt":0.2427096950074732,"score_spread":0.2315869965904705,"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."}}