{"id":"W2391811543","doi":"","title":"A Comparative Study on Forestry Development Between China and Japan","year":2001,"lang":"en","type":"article","venue":"Contral South Forest Inventory and Planning","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"China; Forestry; Business; Community forestry; Forest management; Comparative advantage; Geography; International trade","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":[0.0006010663,0.000233253,0.0002733631,0.00326901,0.001567461,0.001122574,0.0001882826,0.0002257719,0.002071403],"category_scores_gemma":[0.0007240633,0.0001426897,0.0002437224,0.007135998,0.0007627124,0.0008552526,0.0009402551,0.0002270187,0.00005746832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002894517,"about_ca_system_score_gemma":0.003074829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1258529,"about_ca_topic_score_gemma":0.3508296,"domain_scores_codex":[0.9995472,0.00008163777,0.00003319829,0.00004610709,0.00008541665,0.0002064102],"domain_scores_gemma":[0.9992651,0.000132209,0.0001552082,0.00002752345,0.0001852442,0.0002347172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004856156,0.0001676537,0.8761784,0.0006989057,0.0001911425,0.004362749,0.03166866,0.0007002781,0.005280291,0.00528364,0.001656379,0.0733263],"study_design_scores_gemma":[0.000009636236,0.00008951641,0.9800396,0.0000450903,0.0000611089,0.0002434536,0.01300597,0.0001197185,0.0002336123,0.0001128027,0.006027461,0.00001195452],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923946,0.00187933,0.00003048596,0.0001568948,0.000007787755,0.000007242486,0.00006847713,0.000001593529,0.005453471],"genre_scores_gemma":[0.9974582,0.001505239,0.00006051146,0.00004328008,0.000006445937,0.000005865651,0.0001032962,0.000001229231,0.0008159113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1258529,"threshold_uncertainty_score":0.2502408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04974231193682309,"score_gpt":0.2809477035724266,"score_spread":0.2312053916356035,"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."}}