{"id":"W4221131383","doi":"10.3390/cli10040052","title":"Identifying Forest Degradation and Restoration Opportunities in the Lancang-Mekong Region: A Tool to Determine Criteria and Indicators","year":2022,"lang":"en","type":"article","venue":"Climate","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Forest degradation; Identification (biology); Mechanism (biology); Environmental resource management; Mekong river; Process (computing); Land degradation; Environmental science; Environmental planning; Computer science; Land use; Ecology; Engineering; Civil engineering","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":[0.0003199855,0.00004697002,0.0000436107,0.00007186022,0.0003790879,0.00006500238,0.00008486158,0.00000979892,0.00005214366],"category_scores_gemma":[0.00001051387,0.00004036095,0.000007392371,0.0001478746,0.00004861228,0.0001192471,0.0003334839,0.00003864205,0.000003128632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005118854,"about_ca_system_score_gemma":0.000002216297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001718426,"about_ca_topic_score_gemma":0.0005543995,"domain_scores_codex":[0.9995122,0.00006409676,0.00008781118,0.0001105579,0.0001326655,0.00009269803],"domain_scores_gemma":[0.9998268,0.0000183565,0.00004073607,0.00009100961,0.000001705023,0.00002134649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001456966,0.00001229075,0.9855632,0.00001490429,0.00000139895,0.00002076172,0.005089889,0.00001822176,0.000151603,0.00006295601,0.0007112136,0.008338945],"study_design_scores_gemma":[0.000122887,0.00003255406,0.9730583,0.000005488321,0.000007058401,0.000008070429,0.008541573,0.0002651832,0.000003278135,0.00007379142,0.01782309,0.0000586841],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972127,0.00002487723,0.00002346535,0.001937594,0.00004041256,0.0001888268,0.00000544765,0.000009768029,0.0005569062],"genre_scores_gemma":[0.998895,0.00006427988,0.00007020566,0.0007662974,0.000009633894,0.00002905712,0.00001952864,0.000002488926,0.0001435303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01711188,"threshold_uncertainty_score":0.2915676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07294718537132061,"score_gpt":0.2532482052553232,"score_spread":0.1803010198840026,"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."}}