{"id":"W2264462087","doi":"10.5558/tfc2011-013","title":"Benefit–cost Analysis of Vegetation Management Alternatives: An Ontario Case Study","year":2011,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Forest Research Institute; Lakehead University","funders":"","keywords":"Vegetation (pathology); Environmental science; Net present value; Internal rate of return; Benefit–cost ratio; Forestry; Geography; Production (economics); Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.0002502139,0.0001148643,0.0001305177,0.00008354178,0.0001288386,0.00001785018,0.0003836727,0.00001895941,0.00369502],"category_scores_gemma":[0.000001451215,0.00008409693,0.00007426882,0.0004932127,0.0001293299,0.0002624711,0.0002303979,0.00006932551,0.0001845705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001991734,"about_ca_system_score_gemma":0.000005698043,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.207145,"about_ca_topic_score_gemma":0.4555477,"domain_scores_codex":[0.9990922,0.00004255955,0.0002044497,0.0002232183,0.0002294687,0.0002080662],"domain_scores_gemma":[0.9992662,0.00001196594,0.000112918,0.00054764,0.000005214439,0.00005602571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000421619,0.0008428602,0.919542,0.00001068802,0.0008938291,0.0002871927,0.03843166,0.03017244,0.00001166034,0.002373161,0.000148875,0.007243531],"study_design_scores_gemma":[0.0004612441,0.0002891901,0.9845687,0.00000350139,0.0008257814,0.0000091236,0.00171944,0.01106668,0.00005925819,0.0005312697,0.0003404937,0.0001253797],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9616349,0.000009204678,0.00004557225,0.000009002487,0.0000375102,0.0004746249,0.000002071422,0.00002055062,0.03776662],"genre_scores_gemma":[0.9973064,0.00000282055,0.000176987,0.00003910985,0.00001411299,0.00003788106,0.000006730476,0.000008878135,0.002407053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2484027,"threshold_uncertainty_score":0.9972157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03247150711931535,"score_gpt":0.2727271841151181,"score_spread":0.2402556769958027,"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."}}