{"id":"W2522168177","doi":"10.1038/srep33745","title":"Growth, productivity and relative extinction risk of a data-sparse devil ray","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Ichthyology and Marine Biology","field":"Environmental Science","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Wildlife Conservation Society; Disney Conservation Fund; John D. and Catherine T. MacArthur Foundation; National Science Foundation","keywords":"Fishing; Extinction (optical mineralogy); Population; Productivity; Biology; Mortality rate; CITES; Fishery; Geography; Demography; Economics","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":[0.002469556,0.00007787734,0.0001195647,0.00003498455,0.0001778305,0.000009280122,0.0001211547,0.00006268107,0.0006115537],"category_scores_gemma":[0.0008959267,0.00004805398,0.00001902346,0.0001650948,0.001304435,0.0005685588,0.0005216946,0.0000611077,0.00008362613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002715612,"about_ca_system_score_gemma":0.0000195493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001746244,"about_ca_topic_score_gemma":0.0003505613,"domain_scores_codex":[0.9985518,0.0001400493,0.0002342351,0.0007590402,0.0001515844,0.0001632899],"domain_scores_gemma":[0.9988103,0.00006606595,0.0002663665,0.0007860063,0.00002216673,0.00004908082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000253668,0.00006586339,0.8916361,0.000004437923,0.0000169231,0.00002585078,0.0001414701,0.000003041671,0.07217696,0.00007181599,0.0062582,0.02957396],"study_design_scores_gemma":[0.0002087643,0.00008174386,0.8609154,0.00001190044,0.00005918642,0.0002614276,0.00001682073,0.00002725885,0.02005486,0.04110037,0.07708117,0.0001810753],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934661,0.00002833747,0.001291698,0.0002218097,0.001584525,0.0001599072,0.000006218879,0.00002056002,0.003220789],"genre_scores_gemma":[0.9945824,0.00001057854,0.000921214,0.000004880591,0.00002488971,0.000005867547,0.00001141633,0.000003725901,0.004435079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07082298,"threshold_uncertainty_score":0.6696084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01852508047348849,"score_gpt":0.2365045849008762,"score_spread":0.2179795044273877,"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."}}