{"id":"W1578634808","doi":"","title":"A Methodology Study for Metagenomics Using Next Generation Sequencers","year":2011,"lang":"en","type":"article","venue":"Europe PMC (PubMed Central)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; McGill University","funders":"","keywords":"Metagenomics; Computer science; DNA sequencing; Sample (material); Data science; Computational biology; DNA sequencer; Genomics; Throughput; Data mining; Biology; Genome; DNA; Genetics; Gene; Telecommunications","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":[0.01619296,0.000956401,0.0006621826,0.002307256,0.0008655092,0.002302648,0.001245569,0.0009244477,0.002328549],"category_scores_gemma":[0.009940412,0.0004111602,0.001261011,0.001800773,0.0009420288,0.002752242,0.0009729313,0.0008901648,0.0009742308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001317196,"about_ca_system_score_gemma":0.001731868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001158514,"about_ca_topic_score_gemma":0.0008679053,"domain_scores_codex":[0.9909945,0.005114437,0.0004316556,0.001010599,0.002210221,0.0002385871],"domain_scores_gemma":[0.9953102,0.00180946,0.0003376894,0.0009096652,0.001462752,0.0001702396],"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":[0.0005891965,0.0007514093,0.01304223,0.00174218,0.0003238133,0.001034594,0.001233613,0.005521824,0.6403731,0.06320152,0.001698978,0.2704877],"study_design_scores_gemma":[0.0001743294,0.006405304,0.01972145,0.0006682546,0.0003367673,0.003112864,0.001306621,0.05076564,0.7044828,0.04008628,0.1726639,0.0002757899],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1344515,0.01260201,0.8374879,0.002012047,0.0004334993,0.002160435,0.0005901463,0.0006588202,0.009603695],"genre_scores_gemma":[0.1231105,0.005753723,0.8654842,0.0005911132,0.0001042872,0.0008527277,0.0004650698,0.000232241,0.003406064],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01619296,"threshold_uncertainty_score":0.08563757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2368400292758885,"score_gpt":0.2983296200467956,"score_spread":0.06148959077090715,"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."}}