{"id":"W2201496521","doi":"10.1016/j.ecolind.2015.11.049","title":"Two roles for ecological surrogacy: Indicator surrogates and management surrogates","year":2015,"lang":"en","type":"article","venue":"Ecological Indicators","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":103,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Australian Research Council","keywords":"Environmental resource management; Ecology; Abiotic component; Process (computing); Psychological resilience; Natural resource management; Ecosystem; Biodiversity; Ecological systems theory; Resource (disambiguation); Resilience (materials science); Natural resource; Computer science; Biology; Psychology; Environmental science","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":[],"consensus_categories":[],"category_scores_codex":[0.001103238,0.0002770591,0.0003767005,0.0001257877,0.0004355276,0.00004554836,0.0003522165,0.0002334953,0.0008113559],"category_scores_gemma":[0.0003073561,0.0002138243,0.00009235455,0.0002967359,0.0009546925,0.000165537,0.0006344619,0.0001994811,0.00045565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001982583,"about_ca_system_score_gemma":0.00001656724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009027391,"about_ca_topic_score_gemma":0.0007651548,"domain_scores_codex":[0.9979483,0.0001638173,0.0003848042,0.0006542266,0.0002443394,0.0006044926],"domain_scores_gemma":[0.9985919,0.0006365839,0.0001976922,0.0001847615,0.00001344509,0.0003756471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005036735,0.0004499462,0.9826301,0.00001332278,0.0000791092,0.00001674193,0.0002761799,0.0001650872,0.00001107632,0.01169073,0.003599718,0.001017571],"study_design_scores_gemma":[0.00159947,0.00052657,0.9733138,0.000004072546,0.00006489348,0.000008350214,0.0007485069,0.0005260729,0.00007239161,0.01366983,0.009136956,0.0003290777],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9834674,0.0001207215,0.0000833848,0.001306559,0.0002329111,0.0008052479,0.00002370999,0.0001539017,0.01380614],"genre_scores_gemma":[0.994208,0.0001465887,0.004093185,0.0005734915,0.00004253267,0.0004207418,0.00003436114,0.0000158545,0.0004652817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01334085,"threshold_uncertainty_score":0.8883778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01896297605746762,"score_gpt":0.2688250783974753,"score_spread":0.2498621023400077,"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."}}