{"id":"W4409313808","doi":"10.3389/ffgc.2025.1493879","title":"Coordinating old-growth conservation across scales of space, time, and biodiversity: lessons from the US policy debate","year":2025,"lang":"en","type":"article","venue":"Frontiers in Forests and Global Change","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biodiversity; Biodiversity conservation; Space (punctuation); Environmental resource management; Geography; Environmental planning; Political science; Ecology; Environmental science; Biology; Computer science","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":[0.02880602,0.0006119089,0.00102823,0.001789752,0.01042794,0.01662867,0.004309967,0.01747914,0.006009665],"category_scores_gemma":[0.03151809,0.0004910446,0.001210212,0.003210152,0.01905048,0.01821664,0.009574255,0.01850026,0.0004569987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02265252,"about_ca_system_score_gemma":0.0513829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.170699,"about_ca_topic_score_gemma":0.1554645,"domain_scores_codex":[0.9881524,0.005456692,0.0005442114,0.001180953,0.00215172,0.002513971],"domain_scores_gemma":[0.969823,0.02031824,0.001111812,0.001199957,0.004071824,0.003475181],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005065157,0.00009118039,0.001211215,0.0002135099,0.00003229755,0.0002635794,0.005002576,0.001787618,0.0001608655,0.8557107,0.0907004,0.04477528],"study_design_scores_gemma":[0.0000385691,0.00003637794,0.001918647,0.001639243,0.00004048484,0.0001093109,0.01223666,0.001427429,0.0002775993,0.5976515,0.384546,0.0000782124],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.007836819,0.0154605,0.002441865,0.933184,0.001389244,0.0000194243,0.0001127498,0.00002205854,0.03953334],"genre_scores_gemma":[0.4866385,0.03890967,0.01186441,0.446397,0.003233051,0.0002349974,0.000261534,0.0001462763,0.01231463],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.170699,"threshold_uncertainty_score":0.3394109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01326077644977819,"score_gpt":0.2578487899462671,"score_spread":0.2445880134964889,"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."}}