{"id":"W6948371132","doi":"10.5063/f1gx48s7","title":"Dataset for: Larger gains delivered by improved management over sparing-sharing for tropical forests","year":2019,"lang":"en","type":"dataset","venue":"UC Santa Barbara","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Biodiversity; Species richness; Logging; Forest management; Tropical forest; Biodiversity conservation; Tropics","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":[0.001127703,0.00137566,0.001139188,0.001859737,0.0005454466,0.001699124,0.001969653,0.00202358,0.1315187],"category_scores_gemma":[0.009872548,0.0004594353,0.001212276,0.004227709,0.0002209008,0.00118869,0.00138408,0.001425288,0.05906528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001579959,"about_ca_system_score_gemma":0.001780084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04096524,"about_ca_topic_score_gemma":0.07566234,"domain_scores_codex":[0.9991196,0.000152754,0.0001225644,0.0002562612,0.0002186108,0.0001302315],"domain_scores_gemma":[0.9966025,0.001350776,0.0004351133,0.0004704183,0.0009382752,0.000202849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00007656804,0.00001668974,0.0009448546,0.0007703277,0.00005201731,0.00001153027,0.00001052257,0.0004277476,0.0000398586,0.0003481088,0.9954295,0.001872266],"study_design_scores_gemma":[0.001233975,0.00003619619,0.01187425,0.001067222,0.0001139661,0.00005628838,0.00009950058,0.001193773,0.0002409303,0.002031779,0.9820099,0.00004206969],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007668534,0.00004585515,0.00002241196,0.00006336375,0.00001305661,0.000004922606,0.9992504,0.00005405119,0.0004692519],"genre_scores_gemma":[0.0008834522,0.00006067375,0.0002446888,0.00009853451,0.00001122319,0.00007405422,0.997763,0.00004719602,0.000817103],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1315187,"threshold_uncertainty_score":0.4399739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03768602290974827,"score_gpt":0.3256588185663324,"score_spread":0.2879727956565842,"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."}}