{"id":"W2520464109","doi":"10.1093/bioinformatics/btw597","title":"BOSS: a novel scaffolding algorithm based on an optimized scaffold graph","year":2016,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China; National Natural Science Foundation of China","keywords":"Boss; Scaffold; Computer science; Contig; Algorithm; Graph; Theoretical computer science; Genome; Database; Engineering; 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":[0.0007116429,0.001618447,0.001287147,0.002369839,0.001324356,0.001301756,0.002249875,0.001151252,0.007540658],"category_scores_gemma":[0.002526281,0.0007330595,0.001367869,0.002182507,0.0008879238,0.001882982,0.001971247,0.001094293,0.003380278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008949558,"about_ca_system_score_gemma":0.001758562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004847378,"about_ca_topic_score_gemma":0.00661785,"domain_scores_codex":[0.999404,0.00009096533,0.00003478838,0.0002170019,0.0001792148,0.00007416858],"domain_scores_gemma":[0.9987765,0.0004480672,0.0001154899,0.0002589875,0.000296112,0.0001048635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007009694,0.000231241,0.002870377,0.0006346715,0.0001297258,0.0004898558,0.0004254464,0.171876,0.05167838,0.0216092,0.03088805,0.7184662],"study_design_scores_gemma":[0.0001928531,0.0001850653,0.0006158966,0.00004491259,0.00006270081,0.0002767804,0.0001518665,0.9387695,0.01982022,0.02132356,0.01850657,0.00005014443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01208951,0.0001940418,0.9725896,0.0001203043,0.00006991603,0.0001267022,0.0005192137,0.01247579,0.001814949],"genre_scores_gemma":[0.05815796,0.0001229972,0.9344675,0.0001139819,0.00003582451,0.0001837106,0.002956092,0.001425306,0.002536724],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007540658,"threshold_uncertainty_score":0.02522594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01423703169381154,"score_gpt":0.2406790377023678,"score_spread":0.2264420060085562,"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."}}