{"id":"W2900490737","doi":"10.1007/s13280-018-1127-7","title":"Assessing ecosystem service trade-offs and synergies: The need for a more mechanistic approach","year":2018,"lang":"en","type":"review","venue":"AMBIO","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":285,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Australian Research Council","keywords":"Ecosystem services; Ecosystem; Service (business); Environmental resource management; Process (computing); Business; Ecosystem management; Inference; Ecology; Computer science; Environmental science; Marketing; 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":[0.009878218,0.002697878,0.006018177,0.005207187,0.0005172389,0.005473662,0.003285509,0.003252432,0.003439583],"category_scores_gemma":[0.0154647,0.0005256763,0.001890671,0.006741394,0.002463838,0.01071383,0.002836693,0.005396499,0.0006147241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003037049,"about_ca_system_score_gemma":0.006645395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006924764,"about_ca_topic_score_gemma":0.01090788,"domain_scores_codex":[0.9974127,0.0009262044,0.0002389476,0.0004047978,0.0008873764,0.0001299335],"domain_scores_gemma":[0.986656,0.01044387,0.001018578,0.0003667318,0.001322519,0.0001923353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005491531,0.0001318118,0.00259448,0.03031293,0.001627632,0.0001545423,0.0002580683,0.008835068,0.001085513,0.115456,0.01042758,0.8290614],"study_design_scores_gemma":[0.00003435264,0.0001915614,0.006612734,0.03550024,0.001939831,0.0007087832,0.001837191,0.007837098,0.001318025,0.4508623,0.4928849,0.0002730961],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001042804,0.9834402,0.007347864,0.004810608,0.0003311208,0.00002556496,0.000165992,0.00002161052,0.002814286],"genre_scores_gemma":[0.01710852,0.9676436,0.01227686,0.001682641,0.0004683314,0.00007083287,0.0001768143,0.00002115021,0.0005513057],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009878218,"threshold_uncertainty_score":0.05224162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04709093978697954,"score_gpt":0.2909761733148226,"score_spread":0.243885233527843,"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."}}