{"id":"W3003623037","doi":"10.1002/ece3.6052","title":"Complete tag loss in capture–recapture studies affects abundance estimates: An elephant seal case study","year":2020,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Census and Population Estimation","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mark and recapture; Abundance (ecology); Abundance estimation; Biology; Seal (emblem); Ecology; Geography; Fishery; Zoology; Demography; Population; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02547021,0.0006361354,0.00101937,0.0008970496,0.001386817,0.001406665,0.001384623,0.002122191,0.0007548365],"category_scores_gemma":[0.05616758,0.0004585528,0.001559308,0.001200279,0.001657412,0.002351291,0.001806686,0.001099597,0.0001665475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001109582,"about_ca_system_score_gemma":0.000769539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009589288,"about_ca_topic_score_gemma":0.01236359,"domain_scores_codex":[0.9907347,0.006423414,0.0006331968,0.001122755,0.0008086737,0.0002773773],"domain_scores_gemma":[0.9207069,0.0651949,0.005437783,0.005358172,0.00280853,0.0004937693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009225644,0.0006871414,0.8274975,0.0003904088,0.001564414,0.006876183,0.00300735,0.1064072,0.005399752,0.005477875,0.001465523,0.04030413],"study_design_scores_gemma":[0.0003390632,0.003142874,0.4197214,0.0005154937,0.002179527,0.01167396,0.004113445,0.5173429,0.01678597,0.01647045,0.007335506,0.0003794336],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820672,0.000615552,0.01611036,0.0004607227,0.00001825171,0.00003227955,0.0001394769,0.00003420395,0.0005219498],"genre_scores_gemma":[0.9830682,0.0002933113,0.0159522,0.0001348928,0.0000273753,0.00004543694,0.0001910427,0.00002902841,0.0002584704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02547021,"threshold_uncertainty_score":0.134701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07433035115526256,"score_gpt":0.3513041371842878,"score_spread":0.2769737860290252,"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."}}