{"id":"W3100472575","doi":"10.1016/j.biocon.2020.108850","title":"Avian community response to landscape-scale habitat reclamation","year":2020,"lang":"en","type":"article","venue":"Biological Conservation","topic":"Rangeland and Wildlife Management","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Bureau of Land Management; Canada Foundation for Innovation","keywords":"Land reclamation; Habitat; Species richness; Abundance (ecology); Ecology; Geography; Environmental science; Wildlife; Revegetation; Vegetation (pathology); Landscape ecology; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005091153,0.00007557902,0.00008585298,0.00001153389,0.0001683705,0.0000250832,0.000157621,0.00005367913,0.0005034527],"category_scores_gemma":[0.0003047175,0.00005607735,0.00002764139,0.0002114723,0.00004314261,0.00007662511,0.0001532376,0.0001021075,0.0009977733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003064964,"about_ca_system_score_gemma":0.000002419057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009064647,"about_ca_topic_score_gemma":0.00009045882,"domain_scores_codex":[0.9990753,0.0004076175,0.000139269,0.0001505584,0.0001077704,0.000119475],"domain_scores_gemma":[0.9995936,0.000127057,0.00003650272,0.0001285507,0.00000650546,0.0001077748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005529174,0.00005312779,0.9272927,0.000004295957,0.000003168379,0.00000172017,0.0007177594,0.0001484058,0.02735439,0.00003796119,0.03926099,0.004572535],"study_design_scores_gemma":[0.0001854691,0.0003021889,0.9203238,0.000003966201,0.000002438338,3.331686e-7,0.000186812,0.000728752,0.0002173813,0.0001666978,0.0777923,0.0000898061],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9526774,0.000003266838,0.001568343,0.04198212,0.00003059895,0.0002167534,0.00000593818,0.00007912947,0.003436426],"genre_scores_gemma":[0.9789153,0.000003337007,0.001115501,0.01973849,0.00002911685,0.00002021244,0.00003606484,0.000003381214,0.0001386493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03853131,"threshold_uncertainty_score":0.9997801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05755110027179482,"score_gpt":0.245277534051777,"score_spread":0.1877264337799821,"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."}}