{"id":"W4353017186","doi":"10.1007/s10142-023-01013-3","title":"Pilot study of a comprehensive resource estimation method from environmental DNA using universal D-loop amplification primers","year":2023,"lang":"en","type":"article","venue":"Functional & Integrative Genomics","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; University of Tokyo","keywords":"Biology; Nanopore sequencing; Computational biology; Haplotype; DNA sequencing; Mitochondrial DNA; Genome; Genetics; Gene; Genotype","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004854622,0.001671082,0.001241698,0.001822845,0.0007169119,0.001064365,0.001387578,0.001284341,0.002370672],"category_scores_gemma":[0.005515909,0.001152673,0.001501063,0.0009478909,0.0008511105,0.001163043,0.001392198,0.001748134,0.001670244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006226529,"about_ca_system_score_gemma":0.001783047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002201378,"about_ca_topic_score_gemma":0.004821082,"domain_scores_codex":[0.9955171,0.0008232596,0.0003279513,0.002061277,0.0009069857,0.0003634464],"domain_scores_gemma":[0.9973889,0.0009659194,0.0002743542,0.0002558866,0.0009293099,0.0001857211],"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":[0.0003840594,0.0003899773,0.0127895,0.0009244484,0.000191362,0.0003122757,0.0006493294,0.002929017,0.8942925,0.001830197,0.001471887,0.08383536],"study_design_scores_gemma":[0.0002339598,0.002284838,0.02822492,0.0002937201,0.0006994237,0.00170338,0.0004937535,0.06750458,0.8498333,0.002450289,0.04595035,0.0003274913],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1477992,0.00152454,0.8383797,0.0003430299,0.0002489992,0.00242275,0.003472129,0.002711328,0.003098399],"genre_scores_gemma":[0.0917222,0.0004516944,0.8994845,0.0004305994,0.00003940642,0.001362438,0.00454,0.0002982485,0.001670949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004854622,"threshold_uncertainty_score":0.02567399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05959332225314292,"score_gpt":0.2662182329459461,"score_spread":0.2066249106928032,"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."}}