{"id":"W2150058683","doi":"10.1890/10-2026.1","title":"Spatial surplus production modeling of Atlantic tunas and billfish","year":2011,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Pew Charitable Trusts","keywords":"Stock assessment; Stock (firearms); Fishing; Tuna; Fishery; Spatial distribution; Spatial analysis; Population; Ecology; Geography; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001186443,0.00004513988,0.00007127383,0.00001284318,0.00007935132,0.000004912957,0.0001005662,0.00004044229,0.0052413],"category_scores_gemma":[0.0000350709,0.00003484169,0.00001583969,0.0001240493,0.0001588553,0.00005028332,0.0001733996,0.00006559595,0.0000638307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001821079,"about_ca_system_score_gemma":0.00000389077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008716983,"about_ca_topic_score_gemma":0.0003155908,"domain_scores_codex":[0.9994659,0.00001733855,0.0001205152,0.0001915655,0.00009223349,0.0001123991],"domain_scores_gemma":[0.9997568,0.00001688901,0.00002690623,0.0001395823,0.00001009626,0.00004973977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002543778,0.0004592398,0.9505762,0.00001462446,0.000007876742,0.000001093853,0.0002529733,0.0001637274,0.001598281,0.001585006,0.000323241,0.04499232],"study_design_scores_gemma":[0.0001891515,0.00021678,0.9360087,0.000001533846,0.00001560983,0.00000927003,0.0001022622,0.0309155,0.000574982,0.01627796,0.01548982,0.0001984662],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8603395,0.000002880219,0.01017684,0.0001920231,0.00001795665,0.0004495909,0.000001604872,0.0000289329,0.1287906],"genre_scores_gemma":[0.9975809,0.00002973407,0.001848208,0.0000202406,0.00002465744,0.0001526558,0.000004775111,0.000002939039,0.0003359177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1372413,"threshold_uncertainty_score":0.9956681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04290654252298053,"score_gpt":0.2372916018237045,"score_spread":0.194385059300724,"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."}}