{"id":"W2075253077","doi":"10.1016/j.protis.2010.03.004","title":"Barcoding Tetrahymena: Discriminating Species and Identifying Unknowns Using the Cytochrome c Oxidase Subunit I (cox-1) Barcode","year":2010,"lang":"en","type":"article","venue":"Protist","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":69,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Genome Canada","keywords":"DNA barcoding; Biology; Tetrahymena; Intraspecific competition; Cytochrome c oxidase subunit I; Barcode; Zoology; Evolutionary biology; Mitochondrial DNA; Gene; Genetics","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":[0.0004415866,0.0004667175,0.0004188354,0.001603783,0.0009595064,0.0007144684,0.0007602017,0.0009741528,0.002405104],"category_scores_gemma":[0.001243683,0.0004498886,0.0003385181,0.001060454,0.0006371463,0.001118965,0.0006370079,0.0010677,0.001770847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006737242,"about_ca_system_score_gemma":0.0007871744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003260924,"about_ca_topic_score_gemma":0.009548633,"domain_scores_codex":[0.9995302,0.00003827016,0.00002771001,0.0001894811,0.0001622772,0.00005200365],"domain_scores_gemma":[0.9992219,0.0001928436,0.0002385506,0.0001237507,0.0001529542,0.00006990343],"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":[0.0001120951,0.00002454183,0.009528195,0.0001439482,0.00001827705,0.00009065703,0.0004074553,0.0002070953,0.9137993,0.0009659198,0.001092457,0.07361011],"study_design_scores_gemma":[0.00002675818,0.0002306175,0.08575844,0.000156719,0.0001002435,0.001262737,0.0008282256,0.01317747,0.8500271,0.00393439,0.04440056,0.00009676998],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6388314,0.003139742,0.3375217,0.001261337,0.0005371363,0.0002608324,0.01031796,0.001781987,0.006347951],"genre_scores_gemma":[0.5186821,0.001807464,0.4587877,0.000583878,0.0001237928,0.0002959726,0.008044438,0.0004326472,0.01124193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003260924,"threshold_uncertainty_score":0.008045912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05110503373217251,"score_gpt":0.3093905934090476,"score_spread":0.2582855596768751,"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."}}