{"id":"W2104024295","doi":"10.1525/bio.2013.63.7.7","title":"Ecosystem Services and Beyond: Using Multiple Metaphors to Understand Human–Environment Relationships","year":2013,"lang":"en","type":"article","venue":"BioScience","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":326,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Ecosystem services; Salient; Deliberation; Valuation (finance); Environmental resource management; Limiting; Ecosystem management; Ecosystem valuation; Goods and services; Ecosystem; Business; Ecology; Computer science; Political science; Ecosystem health; Economics","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":[0.0003422985,0.0001429851,0.0001359091,0.00005232256,0.0006207952,0.0001534265,0.0002886515,0.00005503043,0.0005563344],"category_scores_gemma":[0.000006368183,0.0001108082,0.00002502509,0.0002392365,0.00003689342,0.0006713227,0.0002983026,0.00006139272,0.0009627153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001392656,"about_ca_system_score_gemma":0.000004127585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00170574,"about_ca_topic_score_gemma":0.002988021,"domain_scores_codex":[0.9986515,0.00006100209,0.0002174697,0.0004456983,0.0003137688,0.0003105329],"domain_scores_gemma":[0.9993615,0.00004310452,0.00008193,0.000268615,0.000004761654,0.0002400711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004755208,0.00008057888,0.8825911,0.00008892063,0.0000129303,0.000003654214,0.003652331,0.00571782,0.1069223,0.0001438439,0.0001774849,0.0006042828],"study_design_scores_gemma":[0.0006561037,0.0002043054,0.7933236,0.0001135204,0.00005793328,0.00003364264,0.01034519,0.1822058,0.005591582,0.001599291,0.00486716,0.001001916],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977674,0.00004602075,0.0004131836,0.000217575,0.00009241142,0.0003991861,0.000009624989,0.00003284329,0.001021793],"genre_scores_gemma":[0.9975568,0.00000901184,0.002104778,0.0002373464,0.00001878023,0.00001369876,0.000001865709,0.000009220635,0.00004851835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.176488,"threshold_uncertainty_score":0.9998152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03367607294534947,"score_gpt":0.2182412157084382,"score_spread":0.1845651427630887,"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."}}