{"id":"W2007767180","doi":"10.2144/05385st01","title":"Management and Visualization of Whole Genome Shotgun Assemblies Using SAM","year":2005,"lang":"en","type":"article","venue":"BioTechniques","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia","funders":"Michael Smith Health Research BC; Genome British Columbia; Canada's Michael Smith Genome Sciences Centre; Genome Canada","keywords":"Perl; Genome; Shotgun sequencing; Sequence assembly; Visualization; Computational biology; Computer science; Interface (matter); Sequence (biology); Whole genome sequencing; Shotgun; Biology; Database; Programming language; Genetics; Data mining; Operating system; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000809247,0.00008155168,0.00008665244,0.00004555804,0.00004052407,0.000009908933,0.00006159862,0.00007610708,0.000002096135],"category_scores_gemma":[0.000003759314,0.00007953942,0.00002617917,0.00004260314,0.000048284,8.203093e-7,0.0001209569,0.00001579582,3.929503e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007019696,"about_ca_system_score_gemma":0.000006309463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000864457,"about_ca_topic_score_gemma":0.000005059022,"domain_scores_codex":[0.9995642,0.00001390116,0.0001261956,0.0001558295,0.00004928035,0.00009064679],"domain_scores_gemma":[0.999761,0.000001872329,0.00005196147,0.000133119,0.00003276533,0.00001927369],"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":[0.000007468525,0.00001944506,0.0009265614,0.00002038758,0.00003185516,2.181744e-7,0.00003244968,0.00002223371,0.9946859,0.0003806213,0.00009301578,0.003779846],"study_design_scores_gemma":[0.0001074638,0.000117948,0.009074908,0.00001209912,0.0000216585,0.000002878485,0.00004695069,0.00009830809,0.8836911,0.0001306806,0.1065676,0.0001284044],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825835,0.003337285,0.01287751,0.00005862025,0.0000176221,0.0001622569,0.00001570949,0.000008947802,0.0009385918],"genre_scores_gemma":[0.967907,0.001987515,0.02980666,0.00006527324,0.00007425157,0.000006643066,0.00001736811,0.00001106513,0.0001242205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1109948,"threshold_uncertainty_score":0.3243524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01742846397905996,"score_gpt":0.282382099360584,"score_spread":0.2649536353815241,"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."}}