{"id":"W4224251062","doi":"10.3389/fmars.2022.867258","title":"Range-Wide Comparison of Gray Whale Body Condition Reveals Contrasting Sub-Population Health Characteristics and Vulnerability to Environmental Change","year":2022,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Marine Fisheries Service; Oregon Sea Grant, Oregon State University; Office of Science; National Oceanic and Atmospheric Administration; Oregon State University","keywords":"Foraging; Whale; Arctic; Predation; Geography; Fishery; Climate change; Population; Range (aeronautics); Habitat; Apex predator; Oceanography; Ecology; Biology; Geology; Demography","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":[0.001882542,0.0001478036,0.0004015401,0.0001099309,0.0005324638,0.0000219313,0.0003049623,0.00001818086,0.0002609448],"category_scores_gemma":[0.0002036657,0.0001612707,0.00002771034,0.0005873129,0.0004046196,0.0003187012,0.001652986,0.0001857298,0.000003874163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009225814,"about_ca_system_score_gemma":0.00001217548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002115247,"about_ca_topic_score_gemma":0.0002558032,"domain_scores_codex":[0.9977626,0.0001775118,0.0004979612,0.0005206733,0.0006406723,0.000400632],"domain_scores_gemma":[0.9992755,0.000058838,0.0002938886,0.0002200035,0.000006066467,0.0001456688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003167249,0.0001099826,0.9478617,0.00002731199,0.000002017476,0.000001102656,0.000568149,0.00004741371,0.001037896,0.00001175078,0.0006660733,0.0496349],"study_design_scores_gemma":[0.0002362152,0.0002487205,0.9949084,0.00001168408,0.00000499564,0.000002019324,0.0004347296,0.003000939,0.00009108135,0.0001828839,0.0007286276,0.0001496856],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979873,0.00006365051,0.0003282716,0.0003255432,0.0002617605,0.0007696875,0.00004344597,0.00001868417,0.0002016838],"genre_scores_gemma":[0.9936133,0.00005348069,0.005574461,0.0005744915,0.00001928742,0.0001012992,0.00003542317,0.000008545578,0.00001970624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04948521,"threshold_uncertainty_score":0.6576427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0196077591717861,"score_gpt":0.2754733343341269,"score_spread":0.2558655751623408,"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."}}