{"id":"W2146160527","doi":"10.1111/j.1365-2486.2012.02744.x","title":"Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models","year":2012,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":131,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Center for Neuroscience and Regenerative Medicine; Commonwealth Scientific and Industrial Research Organisation; Polar Knowledge Canada","keywords":"Population; Climate change; Climatology; Sea ice; Climate model; Vital rates; Population model; Environmental science; Population growth; Emperor; Sea surface temperature; Geography; Physical geography; Ecology; Demography; Biology; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002438619,0.0001351148,0.0003509095,0.00008601989,0.00006846193,0.000001883189,0.000113714,0.000196709,0.0001651712],"category_scores_gemma":[0.000009201652,0.0001136931,0.00007787228,0.0004464964,0.0002168387,0.0001929156,0.0001307461,0.00004964976,0.00001201005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003875622,"about_ca_system_score_gemma":8.05366e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003747065,"about_ca_topic_score_gemma":0.0007678523,"domain_scores_codex":[0.9989662,0.0001358655,0.0001981398,0.0002360796,0.00007488263,0.0003888596],"domain_scores_gemma":[0.9995201,0.00003876967,0.0001559717,0.0001702897,0.000007639132,0.0001072879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005947463,0.0001924751,0.9948007,0.00001869801,0.00004090173,0.000001094763,0.0002240439,0.000002393326,0.000287832,0.0004855403,0.000001270008,0.003885598],"study_design_scores_gemma":[0.000247384,0.0003725459,0.9979929,0.000006474645,0.0004160527,0.000002047705,0.00002490791,0.0006951085,0.0000349046,0.00009433556,0.000006497701,0.0001068546],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988516,0.0003957246,0.00001024538,0.00003330914,0.0001372851,0.0003130358,0.0001490564,0.00001779743,0.00009196821],"genre_scores_gemma":[0.9990571,0.0003925218,0.0001245282,0.0002106743,0.00004903096,0.0000626148,0.00009807349,0.00000480339,6.853947e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003778744,"threshold_uncertainty_score":0.4636268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03335268623005373,"score_gpt":0.2931706076199628,"score_spread":0.2598179213899091,"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."}}