{"id":"W3171228183","doi":"10.1038/s41558-021-01062-1","title":"Biodiversity–productivity relationships are key to nature-based climate solutions","year":2021,"lang":"en","type":"article","venue":"Nature Climate Change","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":203,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Japan Society for the Promotion of Science; Liber Ero Foundation; Environmental Restoration and Conservation Agency; Agence Nationale de la Recherche; National Science Foundation","keywords":"Biodiversity; Climate change; Biome; Productivity; Reforestation; Natural resource economics; Environmental resource management; Agroforestry; Carbon sink; Geography; Ecology; Environmental science; Ecosystem; Biology; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002025989,0.0003593661,0.0003113968,0.001270656,0.0008296366,0.003959395,0.0005906296,0.001909804,0.01032806],"category_scores_gemma":[0.008895819,0.0002136487,0.0002509955,0.001824818,0.001966715,0.005883199,0.001924529,0.002129853,0.001083334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001448669,"about_ca_system_score_gemma":0.001270454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001614676,"about_ca_topic_score_gemma":0.003171308,"domain_scores_codex":[0.9993227,0.000239743,0.00003087654,0.0001333492,0.0001771283,0.0000962267],"domain_scores_gemma":[0.9965533,0.001506755,0.000951672,0.0001753963,0.0004890731,0.0003237324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001080836,0.000243645,0.04867359,0.0003156061,0.0002819734,0.0001663081,0.0004357132,0.04189057,0.003175277,0.7492777,0.01609819,0.1393333],"study_design_scores_gemma":[0.000008180557,0.00003616901,0.02886344,0.0000842369,0.00003763706,0.00006484218,0.000685936,0.009914029,0.0005824445,0.9181878,0.04150635,0.00002907315],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3459729,0.01877612,0.1703274,0.147465,0.001869021,0.00008618218,0.001547821,0.0004253467,0.3135303],"genre_scores_gemma":[0.9850121,0.004163514,0.005743833,0.001528352,0.0005181456,0.00002491987,0.0001236474,0.00004798037,0.002837516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01032806,"threshold_uncertainty_score":0.03455079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05341021507583515,"score_gpt":0.2638369024144895,"score_spread":0.2104266873386543,"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."}}