{"id":"W1992331963","doi":"10.1071/wr11106","title":"Choosing cost-effective locations for conservation fences in the local landscape","year":2012,"lang":"en","type":"article","venue":"Wildlife Research","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Department of Environment and Conservation","funders":"Australian Research Council; Australian Government","keywords":"Exclosure; Fence (mathematics); Wildlife conservation; Environmental resource management; Wildlife management; Process (computing); Context (archaeology); Geography; Computer science; Ecology; Environmental science; Wildlife; Engineering; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00288182,0.0009096608,0.0008658668,0.001584038,0.0008883804,0.002845395,0.001794845,0.001382183,0.006271364],"category_scores_gemma":[0.006539916,0.000540661,0.000822134,0.00086559,0.0009226903,0.001612703,0.001739944,0.0009312313,0.0004035031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00198015,"about_ca_system_score_gemma":0.003086569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004640809,"about_ca_topic_score_gemma":0.01575445,"domain_scores_codex":[0.9984861,0.0007069883,0.00008840613,0.0003111644,0.0002052965,0.0002020247],"domain_scores_gemma":[0.9971846,0.001760748,0.0003919807,0.0001852384,0.0002456174,0.0002318421],"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":[0.0004415359,0.0007423219,0.04299221,0.0008648936,0.0002228296,0.0008137171,0.001321434,0.7317169,0.01191899,0.01666208,0.002046952,0.1902561],"study_design_scores_gemma":[0.0001698639,0.000933662,0.01305976,0.0002483191,0.0002365411,0.0003242554,0.004112546,0.9485384,0.006069883,0.02034951,0.005820928,0.0001363784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6759131,0.0003463918,0.3093257,0.000823272,0.00002234053,0.001085361,0.0003530857,0.0004669077,0.01166393],"genre_scores_gemma":[0.6978269,0.0001157742,0.3001356,0.00006140635,0.000005579508,0.0003934516,0.0001988276,0.00005449523,0.001208072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006271364,"threshold_uncertainty_score":0.02097982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3287901104236605,"score_gpt":0.3606483256875823,"score_spread":0.03185821526392185,"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."}}