{"id":"W2165516252","doi":"10.1186/1471-2164-14-320","title":"Sequencing platform and library preparation choices impact viral metagenomes","year":2013,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Bacteriophages and microbial interactions","field":"Environmental Science","cited_by":116,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Région Bretagne; Fondation EDF; Fondation Veolia Environnement; Gordon and Betty Moore Foundation; Stazione Zoologica Anton Dohrn; Centre National de la Recherche Scientifique; Fonds Wetenschappelijk Onderzoek; Agence Nationale de la Recherche","keywords":"Metagenomics; Biology; Ion semiconductor sequencing; DNA sequencing; Computational biology; Deep sequencing; Pyrosequencing; Sequence assembly; DNA microarray; Genomics; Environmental DNA; Illumina dye sequencing; Genome; Genetics; Gene; Ecology; Transcriptome; Biodiversity","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":[0.00770137,0.001187302,0.0008060241,0.0007266371,0.0007644221,0.003363162,0.0009125576,0.001313909,0.003227415],"category_scores_gemma":[0.01213419,0.0006339055,0.001070907,0.001080674,0.0008137794,0.002103703,0.00136652,0.001425175,0.001307119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005887395,"about_ca_system_score_gemma":0.0009421051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001781776,"about_ca_topic_score_gemma":0.003018476,"domain_scores_codex":[0.9929348,0.002469972,0.0009944256,0.001656148,0.001488226,0.0004564518],"domain_scores_gemma":[0.9911964,0.00514283,0.0008059817,0.0007870247,0.00168348,0.0003844249],"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":[0.001132336,0.0002932023,0.01032574,0.001218872,0.000298321,0.00008979115,0.0003372392,0.004438387,0.9501799,0.000440408,0.0008951708,0.03035068],"study_design_scores_gemma":[0.00003225217,0.001180255,0.01723122,0.0001718405,0.000268618,0.0001727335,0.0002640503,0.003996138,0.9675556,0.0005859089,0.008446589,0.00009478716],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9458222,0.005130372,0.03352435,0.001110428,0.000232514,0.0005546976,0.005096844,0.001654961,0.00687361],"genre_scores_gemma":[0.9004914,0.003363786,0.07944309,0.001459295,0.00007993217,0.0007201622,0.009643,0.00153108,0.003268264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00770137,"threshold_uncertainty_score":0.04072922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01841957563204615,"score_gpt":0.2458386789775381,"score_spread":0.2274191033454919,"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."}}