{"id":"W2023807793","doi":"10.1038/nmeth905","title":"A unique and universal molecular barcode array","year":2006,"lang":"en","type":"article","venue":"Nature Methods","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":121,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Barcode; Replicate; DNA microarray; Feature (linguistics); Computational biology; DNA barcoding; Biology; Computer science; Genetics; Pattern recognition (psychology); Gene; Artificial intelligence; Evolutionary biology; Mathematics; Gene expression","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":[0.001032607,0.001194529,0.001233931,0.001620847,0.0009252844,0.00171065,0.002930058,0.002544804,0.004005208],"category_scores_gemma":[0.002020822,0.001488486,0.0006823227,0.000790454,0.001072632,0.002003697,0.003306435,0.002668424,0.007831483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007623393,"about_ca_system_score_gemma":0.001337256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003645259,"about_ca_topic_score_gemma":0.0009577852,"domain_scores_codex":[0.996351,0.0002539219,0.0001457864,0.00103373,0.001865529,0.0003500368],"domain_scores_gemma":[0.9983097,0.0003162465,0.0002451548,0.0002840607,0.0004837448,0.0003609972],"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":[0.00008913213,0.00005127862,0.0003362191,0.0001527164,0.00001886104,0.00006800515,0.0000604393,0.0002353751,0.944977,0.004322099,0.003475295,0.04621363],"study_design_scores_gemma":[0.00001345053,0.0001424815,0.0004234217,0.00002248721,0.00002927958,0.0006362773,0.00001727169,0.002953647,0.9456733,0.0007586116,0.0492587,0.00007113701],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04945723,0.005531675,0.9062742,0.001834589,0.001873896,0.0005755305,0.001900215,0.01606853,0.01648413],"genre_scores_gemma":[0.1649715,0.002851984,0.7792479,0.003176136,0.0005892253,0.001257243,0.003172652,0.001368574,0.04336471],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004005208,"threshold_uncertainty_score":0.01339871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004110590542590914,"score_gpt":0.3212436099363319,"score_spread":0.3171330193937411,"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."}}