{"id":"W2273009051","doi":"10.1073/pnas.1510090113","title":"Ocean-wide tracking of pelagic sharks reveals extent of overlap with longline fishing hotspots","year":2016,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Ichthyology and Marine Biology","field":"Environmental Science","cited_by":241,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação para a Ciência e a Tecnologia; Save Our Seas Foundation; Natural Environment Research Council; Sight Research UK","keywords":"Fishing; Pelagic zone; Overexploitation; Fishery; Bycatch; Habitat; Geography; Oceanography; Ecology; Biology; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001428017,0.00008571947,0.0001905466,0.00007281968,0.00007975398,0.000003381751,0.0007277115,0.00008751376,0.0001504126],"category_scores_gemma":[0.0007514618,0.00004320268,0.00005513236,0.0003833938,0.001894117,0.0004446129,0.0002435201,0.00009326761,0.00000182983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003231365,"about_ca_system_score_gemma":0.00001256993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001873667,"about_ca_topic_score_gemma":5.518484e-7,"domain_scores_codex":[0.9985787,0.00001026061,0.0003550828,0.0002247746,0.0006738071,0.0001573585],"domain_scores_gemma":[0.9990221,0.0002541582,0.0005990346,0.00001252582,0.00008561234,0.00002652502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000515336,0.00004753742,0.5923516,0.00003004572,0.00001061216,1.207126e-8,0.0001251729,0.00009450083,0.4018722,0.00430924,0.0005011589,0.0006064604],"study_design_scores_gemma":[0.0001969065,0.0001240329,0.8131201,0.0001246691,0.00001144717,0.000008150066,0.00007048736,0.00005359072,0.1702111,0.0159706,0.00004862958,0.00006029487],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922061,0.00003766682,0.000003502166,0.002411645,0.00001420711,0.0001130367,0.00001004311,0.000004372479,0.00519942],"genre_scores_gemma":[0.9986603,0.00002114693,0.0008517528,0.0001749953,0.00002059832,0.000001185782,6.677418e-8,0.000002755176,0.0002672472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2316611,"threshold_uncertainty_score":0.6978952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02328015367736988,"score_gpt":0.264873666523772,"score_spread":0.2415935128464022,"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."}}