{"id":"W3017946359","doi":"10.1002/ecs2.3082","title":"Estimating arthropod survival probability from field counts: a case study with monarch butterflies","year":2020,"lang":"en","type":"article","venue":"Ecosphere","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Nature Conservancy of Canada","funders":"National Institute of Food and Agriculture","keywords":"Monarch butterfly; Pupa; Statistics; Danaus; Population; Bayesian probability; Ecology; Mark and recapture; Biology; Geography; Larva; Demography; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005563732,0.0004039388,0.0002694057,0.0007427644,0.0004568055,0.0005461039,0.0006701222,0.0005515984,0.0005196534],"category_scores_gemma":[0.01178592,0.0002275935,0.0004056695,0.000773379,0.0003659622,0.0004765613,0.0003954191,0.0003912832,0.00006685549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001538926,"about_ca_system_score_gemma":0.0007442725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1260829,"about_ca_topic_score_gemma":0.182277,"domain_scores_codex":[0.9986111,0.0009557006,0.000067279,0.0001685327,0.0001377927,0.00005963513],"domain_scores_gemma":[0.9833257,0.01345493,0.001323268,0.0007832748,0.0009368325,0.0001759306],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002017548,0.0001687444,0.934673,0.00006701449,0.0002004667,0.0007259409,0.0005958452,0.03607978,0.001102663,0.0003691971,0.0003564446,0.02545911],"study_design_scores_gemma":[0.000048055,0.0005486702,0.7280275,0.00009154257,0.0001465677,0.00114977,0.001529107,0.2638693,0.002163727,0.0009535117,0.001412791,0.00005934867],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951903,0.0001238856,0.004158157,0.00008663893,0.000001580311,0.00002249414,0.0001086149,0.00002156021,0.0002868659],"genre_scores_gemma":[0.994521,0.00008705326,0.005055979,0.00002770147,0.000003186311,0.00001435487,0.0001197849,0.000005100925,0.0001657657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1260829,"threshold_uncertainty_score":0.250698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01839746358383815,"score_gpt":0.2457843959536138,"score_spread":0.2273869323697757,"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."}}