{"id":"W2970161480","doi":"10.1111/mms.12642","title":"Evaluating the power of photogrammetry for monitoring killer whale body condition","year":2019,"lang":"en","type":"article","venue":"Marine Mammal Science","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vancouver Aquarium; University of British Columbia","funders":"National Marine Fisheries Service; California Department of Fish and Wildlife; National Oceanic and Atmospheric Administration; Washington Department of Fish and Wildlife; National Fish and Wildlife Foundation; SeaWorld and Busch Gardens Conservation Fund","keywords":"Geography; Whale; Fishery; Archaeology; Research center; Marine fisheries; Library science; Oceanography; Fish <Actinopterygii>; Geology; Biology; Political science; Law","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001597763,0.0001312793,0.0001636989,0.00003231749,0.0003013869,0.00005079617,0.000650503,0.00002625634,0.004002979],"category_scores_gemma":[0.0002845325,0.00009152864,0.00007577625,0.000680809,0.0004610088,0.0002840595,0.001575421,0.00009371948,0.0001987156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000148743,"about_ca_system_score_gemma":0.00002173801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002648174,"about_ca_topic_score_gemma":0.0001420208,"domain_scores_codex":[0.9981326,0.00002950322,0.0002452362,0.0004102336,0.0007580151,0.0004244187],"domain_scores_gemma":[0.9992128,0.0001546959,0.0001512333,0.000364617,0.00004870035,0.00006795097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005139515,0.00006785698,0.8447973,0.0000330775,0.000009638101,6.246504e-7,0.0001906142,0.0002863697,0.06286035,0.0003539584,0.0002695147,0.09107925],"study_design_scores_gemma":[0.000387664,0.000608351,0.9740109,0.00001848737,0.00001579898,0.000004156953,0.0002513074,0.005241002,0.01114669,0.0003923187,0.007737827,0.0001854923],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.951492,0.00001767608,0.00008477459,0.0001342089,0.0004092435,0.0006568303,0.000002097756,0.00002035247,0.04718279],"genre_scores_gemma":[0.9957311,0.00000963085,0.002196165,0.00009402607,0.00003896346,0.00005440942,0.000001235809,0.000009282877,0.001865163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1292136,"threshold_uncertainty_score":0.9969075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0304313252661857,"score_gpt":0.3231686296319908,"score_spread":0.2927373043658051,"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."}}