{"id":"W83615966","doi":"","title":"Comparison of Custom Target Enrichment Methods; Agilent vs. Nimblegen","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":"McGill University","funders":"","keywords":"Genome; DNA sequencing; Computer science; Computational biology; Data mining; Reference genome; Biology; Genetics; DNA; Gene","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":[0.004891662,0.001223756,0.000869807,0.002004914,0.0005494676,0.001376824,0.001935001,0.001245501,0.00583],"category_scores_gemma":[0.006351196,0.0007746621,0.001022778,0.001745422,0.0003648308,0.0008108577,0.00130034,0.0007398669,0.003108487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009169727,"about_ca_system_score_gemma":0.0005410918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002076497,"about_ca_topic_score_gemma":0.006510873,"domain_scores_codex":[0.9940372,0.001283834,0.0004036175,0.001274603,0.002739662,0.0002610635],"domain_scores_gemma":[0.9965026,0.001698826,0.0003195225,0.0006280288,0.0007483197,0.0001026898],"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":[0.002454103,0.0006325957,0.007614215,0.00186023,0.0008162296,0.0002080869,0.0002576782,0.003013726,0.7809746,0.0009885844,0.006385862,0.1947941],"study_design_scores_gemma":[0.0001669549,0.0007628367,0.03483269,0.00009317445,0.0007299309,0.001055987,0.0001305538,0.01356717,0.8956776,0.0006613642,0.05216761,0.0001541399],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3426403,0.01359341,0.5804482,0.001325993,0.0007727032,0.002194813,0.01239624,0.01527236,0.03135598],"genre_scores_gemma":[0.2210663,0.006618503,0.7224208,0.001503739,0.0001826107,0.002082152,0.02188447,0.003022051,0.02121935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00583,"threshold_uncertainty_score":0.02586991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03522694644547641,"score_gpt":0.2814087580968276,"score_spread":0.2461818116513512,"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."}}