{"id":"W2786764113","doi":"10.1038/s41558-017-0061-1","title":"The role of supply-chain initiatives in reducing deforestation","year":2018,"lang":"en","type":"article","venue":"Nature Climate Change","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":480,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Deforestation (computer science); Supply chain; Business; Transparency (behavior); Private sector; Traceability; Natural resource economics; Reducing emissions from deforestation and forest degradation; Public sector; Climate change; Environmental resource management; Public economics; Economics; Economic growth; Marketing; Political science; Economy","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":[0.0002775544,0.000058734,0.00005466364,0.00003908091,0.000183557,0.00001275883,0.0001362703,0.00006589586,0.0001637859],"category_scores_gemma":[0.00003472422,0.00004168898,0.00002016352,0.000205063,0.0001824572,0.0001071412,0.0001756881,0.0001006973,0.00004255773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006214577,"about_ca_system_score_gemma":0.000001734199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003129959,"about_ca_topic_score_gemma":0.001988914,"domain_scores_codex":[0.9994241,0.00004055368,0.00009750786,0.0001284029,0.0001519409,0.0001574889],"domain_scores_gemma":[0.9997374,0.00004524412,0.00007065001,0.0001153533,0.00001226634,0.00001908411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000273858,0.00002726225,0.9754493,0.000009031532,0.000003200966,0.00000109936,0.008834206,0.000005579728,0.0007275811,0.0003260192,0.00009160906,0.0144977],"study_design_scores_gemma":[0.0001231538,0.00003734363,0.9851236,0.00002202534,0.000004375924,2.995043e-7,0.003490378,0.0004780917,0.001149469,0.0004530878,0.009064388,0.00005377763],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829126,0.0002745928,0.00000149158,0.0008401822,0.0001030707,0.0002043011,0.0000132914,0.00001125579,0.01563922],"genre_scores_gemma":[0.9992704,0.0003161172,0.00008502237,0.0002012928,0.00006960467,0.000009575513,0.00001069898,0.000003501263,0.0000337774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01635781,"threshold_uncertainty_score":0.1793341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01331383884081464,"score_gpt":0.2361226329106084,"score_spread":0.2228087940697938,"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."}}