{"id":"W2326805836","doi":"10.1126/science.346.6213.1068","title":"China's ecological steps forward","year":2014,"lang":"en","type":"letter","venue":"Science","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biodiversity; Reforestation; Subsidy; Logging; Forest management; Agroforestry; China; Geography; Intact forest landscape; Stock (firearms); Land use; Environmental protection; Forest ecology; Ecosystem; Environmental resource management; Natural resource economics; Ecology; Forestry; Environmental science; Political science; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002408425,0.001125538,0.0004103862,0.001133015,0.002746344,0.003612754,0.001035832,0.003148635,0.02180162],"category_scores_gemma":[0.001599326,0.0001999532,0.0006423958,0.001358807,0.001021241,0.002286715,0.003484368,0.003255657,0.003495832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003144953,"about_ca_system_score_gemma":0.03266295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06506601,"about_ca_topic_score_gemma":0.106481,"domain_scores_codex":[0.9990072,0.0001314002,0.00003506744,0.00009591674,0.0003279653,0.0004025065],"domain_scores_gemma":[0.9990699,0.00005322683,0.00002601543,0.00004898979,0.0002223575,0.000579637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008560885,0.00006640098,0.003929804,0.000661351,0.00005371482,0.0006372983,0.0009321983,0.000445082,0.0006066379,0.07480971,0.772827,0.1449452],"study_design_scores_gemma":[0.00002752134,0.0000622858,0.007890899,0.0001414623,0.00001789496,0.00009275043,0.0005050582,0.000272643,0.0002073856,0.005436035,0.9853237,0.00002240523],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.03408802,0.08260982,0.004178545,0.4290787,0.04204923,0.000287784,0.007939443,0.002059524,0.397709],"genre_scores_gemma":[0.3228674,0.03239311,0.01271405,0.1811544,0.004298664,0.0004355113,0.007637155,0.0003336405,0.4381662],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06506601,"threshold_uncertainty_score":0.1293746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009534109003370997,"score_gpt":0.2154108069026735,"score_spread":0.2058766978993025,"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."}}