{"id":"W2329779409","doi":"10.1016/j.tree.2016.03.019","title":"How Monkeys Sequester Carbon","year":2016,"lang":"en","type":"letter","venue":"Trends in Ecology & Evolution","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Livelihood; Wildlife; Climate change; Tropical forest; Geography; Ecology; Agroforestry; Natural resource economics; Environmental protection; Environmental science; Biology; Agriculture; Economics","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000213178,0.0003105524,0.0003475985,0.0003019889,0.00008921968,0.00001668754,0.0003299071,0.001779653,0.001766911],"category_scores_gemma":[0.00004319711,0.0002786252,0.00009025515,0.0002964688,0.00039984,0.0002531855,0.0001711054,0.001033329,0.000499189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001695188,"about_ca_system_score_gemma":0.00002992648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002534029,"about_ca_topic_score_gemma":0.004169639,"domain_scores_codex":[0.9978073,0.0003506998,0.0002911752,0.0006686305,0.0002008755,0.0006813472],"domain_scores_gemma":[0.9991704,0.0001276439,0.000233571,0.0004212458,0.000009833187,0.00003728495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007728715,0.00001319263,0.5285674,0.000003020979,0.00001009593,0.00005566898,0.0000217761,0.0000101013,0.00002144965,0.00001321265,0.4696001,0.001676282],"study_design_scores_gemma":[0.0003507075,0.00008910002,0.7619858,0.00001189925,0.00002972379,0.00002101964,0.000004335033,0.00016595,0.000005898336,0.001702442,0.2353689,0.0002642143],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2323948,0.00002325566,0.00003414034,0.7511052,0.001348376,0.0001534608,0.00001289266,0.0000860404,0.01484187],"genre_scores_gemma":[0.636474,0.00001850015,0.0001305623,0.2553689,0.002197368,0.0002633197,0.0002512997,0.00005712013,0.1052389],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.4957362,"threshold_uncertainty_score":0.9999666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0132737898235488,"score_gpt":0.2192414255238917,"score_spread":0.2059676357003429,"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."}}