{"id":"W2044931728","doi":"10.1111/j.1755-0998.2009.02638.x","title":"A high density <i>COX1</i> barcode oligonucleotide array for identification and detection of species of <i>Penicillium</i> subgenus <i>Penicillium</i>","year":2009,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Plant Pathogens and Fungal Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa; Agriculture and Agri-Food Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Canada","keywords":"Amplicon; Oligonucleotide; Biology; DNA barcoding; Penicillium; Computational biology; Subgenus; Polymerase chain reaction; DNA; Barcode; Digoxigenin; Genetics; Gene; Botany; Evolutionary biology; Taxonomy (biology); In situ hybridization","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002128771,0.000195453,0.0003446358,0.00008513027,0.00009823602,0.00001549774,0.0001893581,0.0002020277,0.000003811085],"category_scores_gemma":[0.0001819977,0.0001994704,0.0001725534,0.0001059393,0.0001900863,0.00000725688,0.00004840587,0.00006535275,0.000001296694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000103483,"about_ca_system_score_gemma":0.00003066672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000235617,"about_ca_topic_score_gemma":0.0001167388,"domain_scores_codex":[0.9986687,0.0001063377,0.0004165111,0.0004216522,0.0001282471,0.0002585416],"domain_scores_gemma":[0.9990542,0.00004437928,0.000297535,0.000340547,0.0001773683,0.000085996],"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":[0.0003659715,0.0001095213,0.003008328,0.00004950061,0.00006982522,0.00000486992,0.00004056147,0.000118512,0.99525,0.000112808,0.00009852735,0.0007715112],"study_design_scores_gemma":[0.0005364667,0.000602147,0.1102732,0.00001136461,0.0001211194,0.00002213491,0.00004470364,0.00002222073,0.8859357,0.0002796192,0.001979082,0.0001722162],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897773,0.001162269,0.007983455,0.0001093958,0.00008635483,0.0003737542,0.0003506332,0.0000136428,0.000143202],"genre_scores_gemma":[0.9983113,0.0002353144,0.000750003,0.0003376995,0.00006370949,0.00002143041,0.0001453111,0.00001778479,0.0001174202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1093144,"threshold_uncertainty_score":0.8134167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005079054249426096,"score_gpt":0.1997531730865575,"score_spread":0.1946741188371314,"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."}}