{"id":"W6960334526","doi":"10.1371/journal.pgen.1011002.s014","title":"Illumina indexes and barcodes used for demultiplexing.","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Agricultural Practices and Plant Genetics","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Strain (injury); Genome; Index (typography); Identifier; Sample (material); Accession number (library science)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002853584,0.002808594,0.003247483,0.00464584,0.003038612,0.002946919,0.003946141,0.001860976,0.1693128],"category_scores_gemma":[0.009180369,0.001571044,0.001623714,0.01086163,0.0006688553,0.001723707,0.001958052,0.00354212,0.1768738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002625993,"about_ca_system_score_gemma":0.005127063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02850231,"about_ca_topic_score_gemma":0.0579637,"domain_scores_codex":[0.9971745,0.0004052272,0.0002575255,0.00124441,0.0005352363,0.0003830758],"domain_scores_gemma":[0.9961646,0.001017354,0.0003521029,0.001103054,0.001025673,0.0003372678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002634391,0.00005986306,0.002049829,0.002958998,0.0001583243,0.00005785274,0.000224752,0.0006250913,0.005095257,0.002068656,0.9747781,0.01165982],"study_design_scores_gemma":[0.000183411,0.00003227689,0.006346028,0.0002682265,0.0001007043,0.00004381463,0.00009324827,0.00018717,0.002572931,0.001836239,0.9882798,0.00005613182],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001869344,0.00006965589,0.0006610781,0.00002277224,0.00002384638,0.00003855924,0.9970556,0.000569213,0.001372337],"genre_scores_gemma":[0.0004472158,0.00006852174,0.002288859,0.00007367726,0.000005494444,0.0003706091,0.9940321,0.0006797742,0.002033739],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1693128,"threshold_uncertainty_score":0.5664077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07883204390698681,"score_gpt":0.2704376154567777,"score_spread":0.1916055715497909,"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."}}