{"id":"W1978602051","doi":"10.1139/x2012-018","title":"Estimating damage from selective logging and implications for tropical forest management","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Logging; Pantropical; Diameter at breast height; Environmental science; Forestry; Geography; Forest management; Agroforestry; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.02010226,0.0009489255,0.001280492,0.00381039,0.0003683468,0.00134629,0.001055937,0.0004614444,0.001647647],"category_scores_gemma":[0.06502693,0.0004279881,0.002511289,0.005630799,0.0008294418,0.001443189,0.001075374,0.0006857671,0.0001170798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069147,"about_ca_system_score_gemma":0.001157543,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02682025,"about_ca_topic_score_gemma":0.03319721,"domain_scores_codex":[0.9898975,0.00718401,0.0009209315,0.001064983,0.0007697166,0.0001629265],"domain_scores_gemma":[0.9377401,0.04967208,0.008642648,0.001721788,0.001743434,0.0004798969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000521736,0.00005624397,0.8073862,0.01051899,0.02306535,0.0003149114,0.0009348734,0.01300397,0.0003542214,0.000909735,0.001446912,0.1414869],"study_design_scores_gemma":[0.000158978,0.000619622,0.9373564,0.006514445,0.02231204,0.0006095477,0.001744804,0.01595422,0.0007613866,0.007471545,0.006375587,0.0001213705],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6770012,0.2873075,0.01885277,0.004465592,0.0003178958,0.0001980691,0.007302657,0.000113079,0.004441173],"genre_scores_gemma":[0.9789874,0.01563612,0.004113034,0.0002480787,0.00009511881,0.00005563226,0.0007341683,0.00001135077,0.0001191651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9731798,"threshold_uncertainty_score":0.1063121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04696443415246782,"score_gpt":0.3389490178796064,"score_spread":0.2919845837271385,"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."}}