{"id":"W2786772699","doi":"10.1007/s10661-018-6494-9","title":"A criteria and indicators monitoring framework for food forestry embedded in the principles of ecological restoration","year":2018,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Social Sciences and Humanities Research Council of Canada; University of Victoria","keywords":"Sustainability; Environmental resource management; Food security; Adaptive management; Agriculture; Promotion (chess); Monitoring and evaluation; Environmental planning; Restoration ecology; Business; Geography; Forestry; Ecology; Environmental science; Political science","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":[],"consensus_categories":[],"category_scores_codex":[0.0003382998,0.000129359,0.0001205211,0.00004886011,0.0001794532,0.00004464238,0.0001459962,0.00007537325,0.00006384672],"category_scores_gemma":[0.00002014918,0.00009916013,0.00002512115,0.00008976604,0.0002941848,0.0001439963,0.0001958636,0.00012856,0.000004719589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009311691,"about_ca_system_score_gemma":0.000003524094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001719868,"about_ca_topic_score_gemma":0.000003459627,"domain_scores_codex":[0.9990664,0.00005792164,0.0002089781,0.0002445246,0.0002116404,0.0002105583],"domain_scores_gemma":[0.9995646,0.0001234469,0.00009816876,0.0001628745,8.126732e-7,0.0000500243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001774716,0.000119832,0.990827,0.00001564169,0.00000979954,9.828816e-7,0.001211874,0.00002031851,0.001325984,0.001311757,0.0000253794,0.005113638],"study_design_scores_gemma":[0.0002736757,0.000577088,0.9927463,0.00003684668,0.00001438618,0.00000117336,0.0008613323,0.0002052981,0.001647073,0.001239763,0.002285218,0.0001118233],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981871,0.00005011301,0.0001452374,0.0001168621,0.0001973994,0.0003624271,0.000007924671,0.000009836156,0.0009230741],"genre_scores_gemma":[0.9868677,0.00008774005,0.01257477,0.00001425933,0.0002767781,0.0001077861,0.000003156756,0.000009513681,0.00005831564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01242953,"threshold_uncertainty_score":0.4043633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03182136223169447,"score_gpt":0.3260592843492284,"score_spread":0.294237922117534,"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."}}