{"id":"W4283369068","doi":"10.3389/fgene.2022.886494","title":"Application of Omics Tools in Designing and Monitoring Marine Protected Areas For a Sustainable Blue Economy","year":2022,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada","keywords":"Metagenomics; Population; Omics; Data science; Environmental resource management; Biology; Computer science; Bioinformatics; Environmental science","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":[0.0001791272,0.00007425254,0.0001180422,0.00005794208,0.0001099834,0.000008624846,0.0001336031,0.00002637022,0.000008418047],"category_scores_gemma":[0.00001426375,0.00009607554,0.00001462054,0.0001394585,0.00009318723,0.00006861862,0.0005969969,0.00007666464,4.351428e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000542375,"about_ca_system_score_gemma":0.000003255712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001346029,"about_ca_topic_score_gemma":0.000005158625,"domain_scores_codex":[0.9993659,0.00002634293,0.0001459747,0.0002024376,0.00007739728,0.0001819152],"domain_scores_gemma":[0.9997792,0.00002230608,0.00006769203,0.0001066341,0.000002888498,0.0000212904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003146865,0.00003919191,0.9682959,0.00002458023,0.000005589601,0.000001506892,0.0005228344,0.02065668,0.001209343,0.000005759015,0.0001338127,0.009073392],"study_design_scores_gemma":[0.0007642736,0.0001368573,0.9630443,0.000003558381,0.00001188068,0.000001018299,0.009450768,0.009005526,0.01141498,0.00152982,0.004461457,0.0001755503],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855043,0.0001720686,0.01297364,0.0000275839,0.00003910244,0.001063894,0.00000879596,0.000006031923,0.0002045492],"genre_scores_gemma":[0.8369663,0.00009057225,0.1624239,0.00001196157,0.000007554632,0.0003643674,0.000008979904,0.000008523564,0.0001179033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1494503,"threshold_uncertainty_score":0.3917847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01047256497753808,"score_gpt":0.1977315306451858,"score_spread":0.1872589656676478,"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."}}