{"id":"W2799824705","doi":"10.5751/es-10079-230211","title":"Adaptation in fire-prone landscapes: interactions of policies, management, wildfire, and social networks in Oregon, USA","year":2018,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Pacific Northwest Research Station; U.S. Department of Agriculture; U.S. Forest Service; National Science Foundation","keywords":"Adaptation (eye); Geography; Environmental resource management; Ecology; Climate change adaptation; Climate change; Environmental science; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0004874841,0.0001389587,0.0001903966,0.0005780259,0.0004973715,0.00105551,0.0005339302,0.0002673862,0.002050949],"category_scores_gemma":[0.001184292,0.0001252152,0.0002999905,0.0009782549,0.000449956,0.0008296291,0.001178014,0.0005684897,0.0001090389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001174911,"about_ca_system_score_gemma":0.0008570494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.15999,"about_ca_topic_score_gemma":0.4426011,"domain_scores_codex":[0.9997867,0.00006257375,0.00001925832,0.00004066373,0.00003018272,0.00006058555],"domain_scores_gemma":[0.9992415,0.0001541207,0.0002601616,0.00003859089,0.00007149071,0.0002342155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001438765,0.0002478711,0.9893825,0.00001855187,0.0001116967,0.0001348965,0.001140556,0.000231301,0.0002550304,0.0002133968,0.0008887618,0.007231748],"study_design_scores_gemma":[0.000006223158,0.00002502934,0.9949386,0.00002288003,0.00002693703,0.00003706665,0.003631971,0.0004695254,0.00005486728,0.0001256362,0.0006546894,0.000006557863],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986801,0.0001042077,0.0000372707,0.0002210425,0.000004068131,0.000004738737,0.0002787985,0.000002400728,0.0006674118],"genre_scores_gemma":[0.9986884,0.0002239911,0.00007016799,0.00006673546,0.000004961745,0.000008855041,0.000495462,0.000003322494,0.0004381344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.15999,"threshold_uncertainty_score":0.3181174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007138370090758213,"score_gpt":0.2282053402092833,"score_spread":0.2210669701185251,"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."}}