{"id":"W2884853868","doi":"10.1126/sciadv.aat7159","title":"Global hot spots of transshipment of fish catch at sea","year":2018,"lang":"en","type":"article","venue":"Science Advances","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Google","keywords":"Transshipment (information security); Fish <Actinopterygii>; Fishery; Spots; Computer science; Environmental science; Biology; Computer security","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003931467,0.00007026726,0.0001125633,0.00002352284,0.0001447046,0.0000101791,0.0006118694,0.00001874299,0.004560846],"category_scores_gemma":[0.00004905339,0.00005684233,0.00002984516,0.0009590551,0.003764799,0.0004963041,0.0003069532,0.0000298124,0.00003327419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001321341,"about_ca_system_score_gemma":0.00004156812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005230993,"about_ca_topic_score_gemma":0.001555466,"domain_scores_codex":[0.9984153,0.00001520939,0.0001670018,0.0002818267,0.0008046973,0.0003159918],"domain_scores_gemma":[0.9995336,0.00001742308,0.0000646444,0.0002478165,0.00003360764,0.0001029264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006953229,0.00006558008,0.8440411,0.00001825441,0.000001959698,0.000001642254,0.0003380422,0.00004186571,0.01849282,0.00007830189,0.0006461305,0.1362047],"study_design_scores_gemma":[0.0002709507,0.0004825331,0.6650271,0.00001129337,0.000004261817,0.000005720987,0.0002759445,0.000155987,0.2172494,0.0008987051,0.1154407,0.0001774734],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8055068,0.00001023055,0.00005626368,0.0001870857,0.00009237473,0.00009091023,0.00002120383,0.000006610767,0.1940285],"genre_scores_gemma":[0.9980739,0.00003057485,0.0009212893,0.00008111652,0.00001721346,0.000003946905,0.000001005335,0.000002143706,0.0008688281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1987565,"threshold_uncertainty_score":0.9989464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01448277385271807,"score_gpt":0.2909244998508573,"score_spread":0.2764417259981392,"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."}}