{"id":"W2054869065","doi":"10.1371/journal.pone.0024378","title":"Ecosystem Services in Conservation Planning: Targeted Benefits vs. Co-Benefits or Costs?","year":2011,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":136,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Nature Conservancy of Canada; Canada Research Chairs; Nature Conservancy","keywords":"Ecosystem services; Opportunity cost; Business; Environmental resource management; Recreation; Carbon sequestration; Biodiversity; Ecosystem; Cost–benefit analysis; Natural resource economics; Environmental economics; Environmental science; Ecology; Economics; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"category_scores_codex":[0.0002526759,0.0001949539,0.0003154779,0.00006859455,0.0001053161,0.0000420077,0.0003545614,0.0001304449,0.002728867],"category_scores_gemma":[0.00001026858,0.0001537236,0.00002871943,0.0003007615,0.000008685145,0.0005221544,0.000107754,0.0001044568,0.002007366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000138424,"about_ca_system_score_gemma":0.00001096029,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002514886,"about_ca_topic_score_gemma":0.03104701,"domain_scores_codex":[0.9984266,0.00006060368,0.0003853675,0.0003732643,0.000382974,0.0003712291],"domain_scores_gemma":[0.9993314,0.00005308015,0.0001722907,0.0002926502,0.00002027579,0.0001303366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002039136,0.0006195555,0.9959974,0.0002833409,0.00005209594,0.00001908945,0.001572491,0.0002117671,0.0007034551,0.00003307044,0.000138048,0.0001658114],"study_design_scores_gemma":[0.001146036,0.000279146,0.9576641,0.001370352,0.0000664889,0.000006538496,0.0004296183,0.01381831,0.02407973,0.00004399689,0.0006300344,0.0004656608],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915281,0.0001697072,6.632425e-7,0.0001135715,0.00006764288,0.000417513,0.00006143759,0.000100731,0.00754066],"genre_scores_gemma":[0.9988,0.00006879304,0.0003331514,0.0005069791,0.00005337639,0.00006615359,0.00006493017,0.00002420348,0.00008237072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03833328,"threshold_uncertainty_score":0.9987697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05856240992269911,"score_gpt":0.2185119763840868,"score_spread":0.1599495664613877,"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."}}