{"id":"W1905421268","doi":"10.1111/j.1755-0998.2010.02901.x","title":"The DNA Barcode Linker","year":2010,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Canada","keywords":"Barcode; DNA barcoding; Biology; Identification (biology); Exploit; Database; DNA sequencing; Computational biology; DNA; Information retrieval; Computer science; World Wide Web; Genetics; Evolutionary biology; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00198974,0.001581413,0.001561171,0.00402096,0.001497288,0.00204555,0.002765124,0.003407724,0.04355988],"category_scores_gemma":[0.005750816,0.001802796,0.001515744,0.002880419,0.001296046,0.002282341,0.003665718,0.003944541,0.06791221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135307,"about_ca_system_score_gemma":0.002400113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001290381,"about_ca_topic_score_gemma":0.002165653,"domain_scores_codex":[0.9971535,0.0003403782,0.0002143358,0.000929684,0.001005232,0.0003568468],"domain_scores_gemma":[0.9976694,0.0007128453,0.0004009426,0.0004649096,0.0004445231,0.0003073266],"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":[0.001113963,0.0003298576,0.003276161,0.002274665,0.0001696996,0.0008379789,0.0005542925,0.00148003,0.5037963,0.02319308,0.1059171,0.3570569],"study_design_scores_gemma":[0.00010703,0.0003676247,0.002078166,0.0003957007,0.00009970487,0.002217636,0.000110129,0.004856205,0.3106989,0.005419077,0.6734484,0.000201274],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02074093,0.007275071,0.84846,0.001184427,0.001929215,0.002742385,0.02050789,0.05919847,0.03796152],"genre_scores_gemma":[0.04738304,0.004936744,0.7944399,0.00348238,0.0003362072,0.005454869,0.04467599,0.006801518,0.09248944],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04355988,"threshold_uncertainty_score":0.1457223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005558088446059903,"score_gpt":0.240042923951521,"score_spread":0.2344848355054611,"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."}}