{"id":"W3107038546","doi":"10.1111/cobi.13676","title":"Building a better baseline to estimate 160 years of avian population change and create historically informed conservation targets","year":2020,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Breeding bird survey; Habitat; Population; Woodland; Ecology; Baseline (sea); Wildlife; Bird conservation; Land cover; Abundance (ecology); Wildlife conservation; Population decline; Conservation biology; Land use; Fishery; Demography; Biology","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":[0.0002654191,0.0001150181,0.0001983858,0.00005734545,0.00007982981,0.000008262429,0.0001022823,0.0001534215,0.0002636132],"category_scores_gemma":[0.0007260155,0.0001253001,0.00002337263,0.000278285,0.0001050678,0.0002590868,0.00009820527,0.00008751767,0.00005550803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008618186,"about_ca_system_score_gemma":0.00001607923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001241774,"about_ca_topic_score_gemma":0.000514934,"domain_scores_codex":[0.9989851,0.0001065006,0.0003704327,0.0002769984,0.00008455176,0.0001763971],"domain_scores_gemma":[0.9993416,0.0002039806,0.0001994901,0.0001135198,0.00003302853,0.00010838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007682029,0.00001368393,0.9773234,0.00001359902,0.00000780081,0.000001215114,0.0003943351,0.00003098504,0.006673084,0.0006992852,0.002383359,0.01238243],"study_design_scores_gemma":[0.0003253691,0.0001608541,0.9655545,0.000009637048,0.00001448763,0.000001971495,0.000007202974,0.00660864,0.0001400393,0.0007535982,0.02629581,0.0001278776],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9619145,0.00002077791,0.005180258,0.03227816,0.0001117786,0.0003566876,0.00001439354,0.00004958226,0.0000738177],"genre_scores_gemma":[0.9472398,0.00001049241,0.01718319,0.03520331,0.00006577463,0.00006121038,0.0001983849,0.00001020087,0.00002765199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02391245,"threshold_uncertainty_score":0.5109589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03521642881055942,"score_gpt":0.2731784727163059,"score_spread":0.2379620439057465,"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."}}