{"id":"W2888698853","doi":"10.1139/cjfas-2018-0153","title":"Evaluating active genetic options for the control of sea lamprey (<i>Petromyzon marinus</i>) in the Laurentian Great Lakes","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Petromyzon; Lamprey; Fishery; Biology; Ecology; Risk analysis (engineering); Environmental planning; Business; Environmental resource management; Geography; Environmental science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.006262162,0.000512223,0.0002921041,0.001027548,0.0006945847,0.00136847,0.001121616,0.0007977609,0.001182012],"category_scores_gemma":[0.004946209,0.0002024336,0.0005232958,0.0004735028,0.001082205,0.0009342004,0.0007626899,0.0004695242,0.00005557625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003982858,"about_ca_system_score_gemma":0.002652353,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01068362,"about_ca_topic_score_gemma":0.04576585,"domain_scores_codex":[0.9956077,0.002613469,0.0002112599,0.0002415556,0.0009742593,0.0003517242],"domain_scores_gemma":[0.995895,0.002309168,0.0009919758,0.00007206094,0.0004284645,0.0003032554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01712111,0.008833404,0.2143378,0.008028722,0.002492115,0.003078326,0.006793117,0.106208,0.2393296,0.01659772,0.001779023,0.3754011],"study_design_scores_gemma":[0.002486804,0.2616112,0.4620599,0.002163986,0.005862424,0.00121531,0.02275271,0.04642821,0.1335574,0.01086158,0.0506351,0.0003654684],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991331,0.001596948,0.0009323239,0.0003563416,0.000007622047,0.0003170688,0.00006760353,0.000006508319,0.00538467],"genre_scores_gemma":[0.9936231,0.001478796,0.003868926,0.0001281671,0.000009493896,0.0001394461,0.00009307812,0.000001852033,0.0006571296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9893164,"threshold_uncertainty_score":0.03311789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02671105779449554,"score_gpt":0.2551073662593838,"score_spread":0.2283963084648883,"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."}}