{"id":"W2052753388","doi":"10.1016/j.ejor.2013.07.026","title":"A spatial optimisation model for multi-period landscape level fuel management to mitigate wildfire impacts","year":2013,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":76,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Fogarty International Center; Bushfire Cooperative Research Centre","keywords":"Integer programming; Scheduling (production processes); Computer science; Environmental resource management; Operations research; Range (aeronautics); Environmental science; Operations management; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.003076626,0.0001550431,0.0001580334,0.0006300633,0.000346621,0.0007313723,0.0004679012,0.00002003487,0.0006271921],"category_scores_gemma":[0.0003981044,0.0001332068,0.0001055297,0.0003576905,0.00004080453,0.001247643,0.0002221077,0.0001931489,0.001158403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007320294,"about_ca_system_score_gemma":0.00006567612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001484513,"about_ca_topic_score_gemma":0.0001227697,"domain_scores_codex":[0.9977699,0.00008854805,0.0006015656,0.0002441093,0.0009204058,0.0003754642],"domain_scores_gemma":[0.99826,0.00001971817,0.00008188414,0.0001997544,0.001353741,0.00008494826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006883078,0.00100009,0.001807859,0.0008230896,0.0003688717,0.00007102482,0.002205496,0.5695893,0.003202441,0.01781617,0.3181538,0.08427361],"study_design_scores_gemma":[0.00158353,0.00008348798,0.04619003,0.00008257704,0.00001963756,0.000003622147,0.0006299395,0.9326068,0.00001644237,0.000218231,0.01836725,0.0001984662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3853392,0.0001485302,0.5500279,0.03551561,0.0007795212,0.003316662,0.00002824437,0.00005965366,0.02478469],"genre_scores_gemma":[0.9752427,0.00002497286,0.01844773,0.001287615,0.0007189493,0.00005286557,0.00004680556,0.00003402655,0.004144347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5899035,"threshold_uncertainty_score":0.9996193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1958944974755469,"score_gpt":0.351556659891163,"score_spread":0.1556621624156161,"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."}}