{"id":"W2767132092","doi":"10.1093/bioinformatics/btx675","title":"ARCS: scaffolding genome drafts with linked reads","year":2017,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":234,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Human Genome Research Institute; National Institutes of Health; Genome British Columbia; Genome Canada","keywords":"Computer science; Genome; Scaffold; Computational biology; Programming language; Biology; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007793593,0.003695384,0.001404757,0.005035722,0.001982569,0.004050106,0.003758897,0.002081852,0.05152974],"category_scores_gemma":[0.03250029,0.003054156,0.002657844,0.006031229,0.001139635,0.003252997,0.004995862,0.003645599,0.03978608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008535181,"about_ca_system_score_gemma":0.002504357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002716484,"about_ca_topic_score_gemma":0.003857567,"domain_scores_codex":[0.9962681,0.0009704576,0.0004246547,0.001333281,0.0008426237,0.0001608058],"domain_scores_gemma":[0.9858977,0.007415901,0.001471389,0.003064336,0.001559067,0.0005917239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004160422,0.0003745774,0.006969456,0.009915764,0.001387423,0.00181829,0.002705104,0.02530848,0.05300394,0.02497798,0.5672627,0.3021159],"study_design_scores_gemma":[0.001141465,0.0005251952,0.007179475,0.001213729,0.00059069,0.001381155,0.0007034118,0.1118853,0.09497113,0.03886047,0.7409914,0.0005567009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007610732,0.0006426892,0.5080303,0.0005791365,0.0005349344,0.0008302521,0.08480255,0.388838,0.008131449],"genre_scores_gemma":[0.02715029,0.0007281461,0.7056085,0.0002991158,0.0001930028,0.001075703,0.1973094,0.06234971,0.005286036],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05152974,"threshold_uncertainty_score":0.1723841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01595196669774098,"score_gpt":0.2397249491146277,"score_spread":0.2237729824168867,"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."}}