{"id":"W4416850860","doi":"10.1111/rec.70277","title":"Adaptive governance and ecological restoration: lessons from three Australian regulatory frameworks","year":2025,"lang":"en","type":"article","venue":"Restoration Ecology","topic":"Environmental Conservation and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University","keywords":"Corporate governance; Restoration ecology; Enforcement; Adaptive management; Ecosystem services; Biodiversity; Climate change; Adaptive capacity","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.02148472,0.0003164568,0.0003807817,0.002273099,0.01228716,0.00868615,0.00214932,0.002778677,0.001821824],"category_scores_gemma":[0.01881913,0.0004005009,0.0005528801,0.002094998,0.02518425,0.004489661,0.01119397,0.004499298,0.00007636739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0252528,"about_ca_system_score_gemma":0.02443656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1317993,"about_ca_topic_score_gemma":0.2171201,"domain_scores_codex":[0.9866613,0.007670871,0.0005328663,0.0008427661,0.002499671,0.001792582],"domain_scores_gemma":[0.9821278,0.009828012,0.002049773,0.001476634,0.00262073,0.001897035],"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":[0.00004493026,0.0002389869,0.02646231,0.0002806436,0.00003796049,0.001943749,0.3429809,0.002547784,0.0008706442,0.5666631,0.002918503,0.05501052],"study_design_scores_gemma":[0.00005644137,0.0002681518,0.1655711,0.002031564,0.0001115967,0.0008620397,0.4594099,0.0102442,0.001190026,0.1801272,0.1799505,0.0001772469],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7676904,0.002216423,0.01414621,0.03470672,0.000117906,0.0003787167,0.00003431137,0.00002713634,0.1806821],"genre_scores_gemma":[0.9937304,0.0004629036,0.002314517,0.0008929459,0.000007762444,0.00007424052,0.000008654059,0.000004402556,0.002504139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1317993,"threshold_uncertainty_score":0.2620643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02183696947152251,"score_gpt":0.2597073900908445,"score_spread":0.237870420619322,"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."}}