{"id":"W4393787602","doi":"10.5281/zenodo.7428804","title":"The potential for natural forest regeneration in tropical regions","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Regeneration (biology); Tropical forest; Natural regeneration; Natural forest; Natural (archaeology); Geography; Forest regeneration; Forestry; Agroforestry; Ecology; Environmental science; Biology; Archaeology","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":[0.0003819901,0.0001845235,0.000145437,0.0005135943,0.0002868916,0.001003253,0.0004049586,0.0002336686,0.00928997],"category_scores_gemma":[0.001466419,0.0001555559,0.0004769264,0.001138703,0.0002838603,0.000944629,0.0005237417,0.0002365231,0.0008152358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001212938,"about_ca_system_score_gemma":0.0008597607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09372678,"about_ca_topic_score_gemma":0.07693752,"domain_scores_codex":[0.9998602,0.00003065735,0.000005905729,0.00004156945,0.00002358553,0.00003797107],"domain_scores_gemma":[0.9995462,0.0002022847,0.00009364737,0.00004262237,0.00007661973,0.00003851543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002706781,0.00004456388,0.5504102,0.0007123817,0.0002117312,0.0004749577,0.0009464745,0.3431635,0.001663082,0.01578424,0.02053465,0.06578356],"study_design_scores_gemma":[0.00005835572,0.0001132258,0.6039976,0.0005521782,0.000165506,0.0006956416,0.003149893,0.3144092,0.001765675,0.01632541,0.05866505,0.0001022341],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.8977165,0.001445488,0.01317624,0.00158415,0.00003893242,0.00005252017,0.03586504,0.0006471567,0.04947397],"genre_scores_gemma":[0.9906595,0.0005075134,0.002542514,0.00004759636,0.00001029955,0.00003530802,0.004682796,0.00004615296,0.001468453],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.09372678,"threshold_uncertainty_score":0.1863624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02336963046002582,"score_gpt":0.2181256732025874,"score_spread":0.1947560427425616,"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."}}