{"id":"W2907769543","doi":"10.1111/cobi.12886","title":"Assessing the shelf life of cost‐efficient conservation plans for species at risk across gradients of agricultural land use","year":2016,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Network for Innovation in Education; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; University of Ottawa","keywords":"Land use; Agriculture; Agricultural land; Business; Plan (archaeology); Prioritization; Environmental resource management; Natural resource economics; Environmental science; Geography; Economics; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0009950546,0.0002955804,0.000237859,0.0007070309,0.0004472683,0.0008820322,0.0005292983,0.0003489913,0.001886089],"category_scores_gemma":[0.003610186,0.0002230228,0.0004772582,0.0007988745,0.0003515122,0.0007391502,0.000429752,0.0004060128,0.0001149225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004645343,"about_ca_system_score_gemma":0.002660177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1260908,"about_ca_topic_score_gemma":0.1924999,"domain_scores_codex":[0.9997506,0.00006046988,0.00001775471,0.00005190862,0.00005869953,0.00006055742],"domain_scores_gemma":[0.9983668,0.000530109,0.0003651573,0.0001492049,0.0003996789,0.0001891166],"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":[0.0002687627,0.0001355795,0.2134152,0.0000699373,0.0002156377,0.00005299392,0.0001474286,0.7634409,0.002081157,0.002950176,0.0005687153,0.01665347],"study_design_scores_gemma":[0.00004653834,0.0007454909,0.2763982,0.00003760241,0.0001628607,0.00005887667,0.0005105191,0.7141493,0.001682748,0.003758218,0.002399773,0.00005003321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943981,0.00007117018,0.002646328,0.00004821824,0.000003326931,0.00003352793,0.0007629968,0.0000178744,0.002018407],"genre_scores_gemma":[0.9954064,0.00005697687,0.003210824,0.000008074936,8.347578e-7,0.00003598602,0.0007817479,0.000004864956,0.000494307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1260908,"threshold_uncertainty_score":0.2507138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1689489781538586,"score_gpt":0.2722552252117246,"score_spread":0.103306247057866,"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."}}