{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002941509,0.0005457043,0.0005882442,0.00272687,0.0007567321,0.001273914,0.0007995645,0.0006861734,0.002287157],"category_scores_gemma":[0.007379438,0.0004208439,0.0006094388,0.002162539,0.0002442687,0.002822963,0.0012636,0.0009478046,0.0006668298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001441272,"about_ca_system_score_gemma":0.001082789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03811817,"about_ca_topic_score_gemma":0.05470624,"domain_scores_codex":[0.9990829,0.0001757285,0.0001168867,0.000372513,0.0001485027,0.0001035199],"domain_scores_gemma":[0.9972282,0.0004378659,0.0005366864,0.0004247386,0.001228487,0.0001439642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001620337,0.0002788274,0.7332793,0.0002786168,0.0004108539,0.000169637,0.00128398,0.08562467,0.005668635,0.008060169,0.01057705,0.1542061],"study_design_scores_gemma":[0.00005208229,0.0003051873,0.7145496,0.0003050597,0.0001979444,0.0001918898,0.001429057,0.2163132,0.004406706,0.0106951,0.051411,0.000143201],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6976606,0.001633,0.2620903,0.0008281357,0.0002414501,0.0002273651,0.02346656,0.001501833,0.01235084],"genre_scores_gemma":[0.8515513,0.0004668112,0.1153815,0.000232083,0.0000692114,0.0004716445,0.03028742,0.0002027303,0.001337224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03811817,"threshold_uncertainty_score":0.07579261,"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."}}