{"id":"W2990022215","doi":"10.1371/journal.pone.0225183","title":"Population productivity of shovelnose rays: Inferring the potential for recovery","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Ichthyology and Marine Biology","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Shark Conservation Fund; Australian Government; National Oceanic and Atmospheric Administration; U.S. Department of Commerce","keywords":"Biology; Population; Overexploitation; Extinction (optical mineralogy); Productivity; Ecology; Estimator; Statistics; Demography; Economics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001898138,0.00004193258,0.00009327936,0.000008900527,0.0000382334,0.000001972925,0.00008066419,0.00004314382,0.0003632613],"category_scores_gemma":[0.00009090597,0.00003008576,0.00002509561,0.0000348423,0.00005813065,0.00008498482,0.00009589559,0.00004772072,0.0000865582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002123469,"about_ca_system_score_gemma":0.000002758433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001589114,"about_ca_topic_score_gemma":0.00007401445,"domain_scores_codex":[0.9996028,0.00002756957,0.00008299835,0.0001244638,0.00006652257,0.00009565317],"domain_scores_gemma":[0.999752,0.00003878471,0.00004673997,0.0001476265,0.000005602477,0.000009214949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001440327,0.0003750263,0.6813052,0.00002798541,0.00005182908,1.135791e-7,0.00005714416,0.0005526585,0.3148744,0.0002799345,0.00007581768,0.002255954],"study_design_scores_gemma":[0.0002132025,0.0001865309,0.9616769,0.000007111129,0.00004109322,8.843361e-7,0.000009827516,0.00066016,0.03282547,0.004216232,0.00009798841,0.0000645838],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980083,0.000006385611,0.0001349272,0.0003342767,0.00009260094,0.0003559074,0.000003220002,0.000009473742,0.001054979],"genre_scores_gemma":[0.9982045,0.000003033169,0.000825367,0.00005518173,0.00004992502,0.00001563838,0.00001166771,0.000003687316,0.0008310007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2820489,"threshold_uncertainty_score":0.3977457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0194349816257599,"score_gpt":0.2073201884022265,"score_spread":0.1878852067764666,"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."}}