{"id":"W2175690527","doi":"10.1650/condor-14-184.1","title":"Using local dispersal data to reduce bias in annual apparent survival and mate fidelity","year":2015,"lang":"en","type":"article","venue":"Ornithological Applications","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Biological dispersal; Fidelity; Philopatry; Statistics; Mark and recapture; Sampling (signal processing); Ecology; Vital rates; Geography; Biology; Demography; Mathematics; Population; Physics; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0004928365,0.00009870049,0.0001319211,0.0000200328,0.00009244598,0.00001423175,0.0003506857,0.0000938143,0.0002226493],"category_scores_gemma":[0.00007275388,0.00008007793,0.0000105,0.00024326,0.0003852845,0.0001310786,0.0008426485,0.0001455852,0.0004592107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009821168,"about_ca_system_score_gemma":0.00001322473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003225606,"about_ca_topic_score_gemma":0.0004681404,"domain_scores_codex":[0.9989025,0.00009295587,0.0001853261,0.0004654007,0.0001293955,0.0002244335],"domain_scores_gemma":[0.9992892,0.00004997158,0.00003683149,0.0004058338,0.000009264939,0.0002089205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002277659,0.0002205806,0.9859882,0.000001056601,0.000001161712,0.000009316174,0.00009521524,0.0004172687,0.0005248804,0.00004891749,0.0005545471,0.01211608],"study_design_scores_gemma":[0.0001681603,0.00003792944,0.9929618,0.00000175931,0.00001059724,0.00002336628,0.0005850345,0.0001683093,0.00005136276,0.0003061879,0.005562907,0.0001225884],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9648775,0.0000108906,0.03316016,0.0005785368,0.00003083592,0.0003649248,0.0001625988,0.00003447996,0.0007800076],"genre_scores_gemma":[0.9922466,0.000002240801,0.007355309,0.000151865,0.00002475859,0.00008600701,0.00005338953,0.000005291638,0.00007448079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02736909,"threshold_uncertainty_score":0.5902377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2506588825503566,"score_gpt":0.3803736380373734,"score_spread":0.1297147554870168,"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."}}