{"id":"W6967345244","doi":"10.5061/dryad.dr7sqvb7t","title":"The global footprint of drifting Fish Aggregating Devices","year":2025,"lang":"en","type":"dataset","venue":"DRYAD","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Fishing; Tuna; Footprint; Marine pollution; Ecological footprint; Marine life; Fish <Actinopterygii>; Fishing industry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009326923,0.0004033663,0.0005199631,0.00008325867,0.0003587263,0.0001891478,0.001639249,0.0002944501,0.00002460852],"category_scores_gemma":[0.002007885,0.00031329,0.0002191598,0.0007424635,0.0001905936,0.00004421026,0.0009979857,0.0005525406,0.0001295113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000277662,"about_ca_system_score_gemma":0.000354927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002187898,"about_ca_topic_score_gemma":0.01380262,"domain_scores_codex":[0.997343,0.0002258609,0.0007510455,0.0004978764,0.0006478799,0.0005343203],"domain_scores_gemma":[0.9965018,0.0006477909,0.001191051,0.001362368,0.0002226824,0.0000743332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001639733,0.00003024326,0.0006582888,0.0003495417,0.0001802296,0.00001134759,0.0000151819,0.00001279018,0.000005195395,0.0001644042,0.9916882,0.006868174],"study_design_scores_gemma":[0.0002032239,0.00001904183,0.0008100995,0.00115268,0.0001676651,0.000004075917,0.000141452,0.00002276173,0.0001010651,0.0001418346,0.9969689,0.000267155],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008344456,0.0007970544,0.000001571097,0.0001324203,0.0006447888,0.0003254979,0.9950942,0.00008836725,0.002081686],"genre_scores_gemma":[0.0004541612,0.00008213067,0.000182909,0.0001368552,0.0002576663,0.00003672296,0.9987462,0.00002469706,0.00007868102],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01161472,"threshold_uncertainty_score":0.9999319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01130484188401722,"score_gpt":0.2983811102034697,"score_spread":0.2870762683194525,"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."}}