{"id":"W4210749931","doi":"10.47068/ctns.2021.v10i19.045","title":"APPLICATION OF METAGENOMICS IN ECOLOGY: A BRIEF OVERVIEW","year":2021,"lang":"en","type":"article","venue":"CURRENT TRENDS IN NATURAL SCIENCES","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canada Excellence Research Chairs, Government of Canada","keywords":"Metagenomics; Biology; Ecology; Data science; Niche; Computational biology; Computer science; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004856182,0.0000769883,0.0001385768,0.000150095,0.00002954173,0.00001513587,0.0002888334,0.00007423776,0.00001760447],"category_scores_gemma":[0.0001754871,0.00006203481,0.00005611107,0.0006999698,0.0003115571,0.000004932014,0.0001750135,0.0001209871,0.000002360275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001976743,"about_ca_system_score_gemma":0.0001245716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002013552,"about_ca_topic_score_gemma":0.0007572432,"domain_scores_codex":[0.9989668,0.0000549054,0.0002853506,0.0002425867,0.0002154687,0.000234871],"domain_scores_gemma":[0.9996594,0.00002147257,0.0000689529,0.0001464045,0.00005609665,0.0000477263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00001591524,0.0001659579,0.05170705,0.00008374072,0.0000085863,0.000001680603,0.00009334213,0.00005330808,0.04446512,0.0007855853,0.0004597621,0.9021599],"study_design_scores_gemma":[0.001831998,0.0004811089,0.7362593,0.000118982,0.00001889276,0.00001670974,0.0004443025,0.01321068,0.1417207,0.001634218,0.1037092,0.0005538464],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754043,0.02247415,0.00009502663,0.0004719108,0.0004251293,0.00008722668,0.00001595917,0.000003097649,0.001023176],"genre_scores_gemma":[0.9955672,0.003444493,0.0007087936,0.00005321112,0.00004499914,0.000008294662,0.00008709613,0.000002112503,0.00008379546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9016061,"threshold_uncertainty_score":0.2529706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04132714722584632,"score_gpt":0.3685232942713047,"score_spread":0.3271961470454584,"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."}}