{"id":"W2765810815","doi":"10.5038/2074-1235.38.1.875","title":"Modified Hoop-net Techniques for Capturing Birds at Sea and Comparison with Other Capture Methods","year":2010,"lang":"en","type":"article","venue":"Marine ornithology","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University; University of North Carolina Wilmington; U.S. Fish and Wildlife Service; Killam Trusts; Bird Studies Canada","keywords":"Seabird; Ornithology; Environmental science; Oceanography; Fishery; Ecology; Biology; Geology; Southern Hemisphere","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0003725684,0.0001610075,0.0002472633,0.00004418948,0.0002162266,0.00001019869,0.0001343657,0.0001433725,0.0008000935],"category_scores_gemma":[0.00004114392,0.0001227587,0.00002160231,0.00006774321,0.0004573888,0.00005704493,0.0006854861,0.0002086954,0.00002178365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002813711,"about_ca_system_score_gemma":0.000002054547,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002652775,"about_ca_topic_score_gemma":0.02153711,"domain_scores_codex":[0.999122,0.00006542877,0.0001325392,0.0003421394,0.00005574514,0.0002821536],"domain_scores_gemma":[0.9995685,0.00009958065,0.00007611721,0.000203119,0.000007962441,0.00004476885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001124869,0.00004978357,0.9751049,0.00001951095,0.0000390204,0.000006107289,0.0002361501,0.00003041395,0.002029864,0.0003321518,0.01430645,0.007733144],"study_design_scores_gemma":[0.0006563416,0.0002535082,0.80841,0.000002395904,0.00007623951,0.0000600458,0.00009273889,0.0003958025,0.003268679,0.001505283,0.1849868,0.0002920937],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8759893,0.00001141952,0.01800847,0.002276375,0.0002200351,0.0007386348,0.000009738867,0.00020806,0.1025379],"genre_scores_gemma":[0.8074136,0.000009142309,0.1807121,0.001502565,0.0000495714,0.0002720971,0.00001209195,0.0000328376,0.009996045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1706804,"threshold_uncertainty_score":0.9963173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01468649031101531,"score_gpt":0.2849690884290767,"score_spread":0.2702825981180614,"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."}}