{"id":"W177663743","doi":"10.1007/978-1-61779-591-6_11","title":"DNA Barcoding Methods for Land Plants","year":2012,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":161,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"DNA barcoding; Biology; Barcode; Clade; Evolutionary biology; DNA extraction; Environmental DNA; Internal transcribed spacer; DNA sequencing; Computational biology; DNA; Polymerase chain reaction; Ecology; Genetics; Gene; Phylogenetics; Biodiversity; Computer science; Phylogenetic tree","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":[0.002720956,0.001299166,0.001083213,0.004694715,0.001924471,0.001661445,0.002714845,0.001526411,0.02165575],"category_scores_gemma":[0.008405316,0.001089792,0.001420162,0.003623816,0.001030989,0.00189791,0.001840333,0.003926458,0.02962367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008602946,"about_ca_system_score_gemma":0.001794526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001148358,"about_ca_topic_score_gemma":0.002446977,"domain_scores_codex":[0.9967592,0.0007437684,0.0003578214,0.0008309784,0.001136783,0.0001714772],"domain_scores_gemma":[0.9961755,0.001036776,0.0005346295,0.001017879,0.001104469,0.0001306875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002190233,0.0001503857,0.001176908,0.003594692,0.0001303949,0.0005951722,0.0008993349,0.001344048,0.4004581,0.02528313,0.04235655,0.5237924],"study_design_scores_gemma":[0.00005741481,0.000238456,0.003051348,0.001064418,0.0001133767,0.001557245,0.00024453,0.007762418,0.3356815,0.02373948,0.6263256,0.0001641629],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003169941,0.002852879,0.9739112,0.0004739802,0.0007654999,0.0007080814,0.005917737,0.003695654,0.008505072],"genre_scores_gemma":[0.008092212,0.002587612,0.9684484,0.0003742906,0.0001465658,0.001594101,0.006978545,0.0008795636,0.01089879],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02165575,"threshold_uncertainty_score":0.07244569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04289385290436788,"score_gpt":0.418568937045219,"score_spread":0.3756750841408511,"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."}}