{"id":"W4407895285","doi":"10.3389/fenvs.2024.1522979","title":"Situating the “human” in forest landscape restoration","year":2025,"lang":"en","type":"article","venue":"Frontiers in Environmental Science","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; Université de Lausanne; Parks Canada; UK Research and Innovation; Velux Stiftung","keywords":"Environmental science; Forest restoration; Agroforestry; Geography; Environmental resource management; Ecology; Forest ecology; Ecosystem; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007539946,0.00009698172,0.00008336856,0.0001499508,0.0004996348,0.00005537587,0.0005665593,0.00003345346,0.0001453485],"category_scores_gemma":[0.00002515265,0.00007772432,0.00002343238,0.0007936443,0.0008958626,0.0002854731,0.0005440703,0.0001209935,0.00003965196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006523393,"about_ca_system_score_gemma":0.0000104163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004465675,"about_ca_topic_score_gemma":0.0008883216,"domain_scores_codex":[0.9987561,0.00004815987,0.0001803524,0.0003519681,0.0003862142,0.0002772574],"domain_scores_gemma":[0.999648,0.00001788259,0.00005311768,0.0002452949,8.963679e-7,0.00003485697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004763529,0.00005040245,0.9869858,0.000001785407,0.00000114683,0.000002630904,0.0006472302,0.00518795,0.001308457,0.00002435537,0.001270105,0.00451536],"study_design_scores_gemma":[0.0002756525,0.00001199873,0.9830284,0.00001080623,0.00000362946,2.642395e-7,0.002606669,0.008014197,0.00009843931,0.0005768002,0.005282857,0.00009029997],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820971,0.00006078367,0.0006916801,0.0007337403,0.000237343,0.0002837626,0.000001366324,0.0000109186,0.01588327],"genre_scores_gemma":[0.9976173,0.00002368751,0.0007705596,0.0003633297,0.000008911727,0.00001409472,0.000004068761,0.000002503288,0.00119556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01552015,"threshold_uncertainty_score":0.3842837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00541061189134973,"score_gpt":0.1938418994775416,"score_spread":0.1884312875861919,"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."}}