{"id":"W6894249203","doi":"10.5683/sp3/um9zes","title":"Post-fire Recovery of Soil Organic Layer Carbon in Canadian Boreal Forests, 2015-2018","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Wilfrid Laurier University; University of Guelph","funders":"","keywords":"Transect; Boreal; Soil carbon; Taiga; Total organic carbon; Deciduous; Soil water; Soil horizon; Topsoil","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006752033,0.0008077783,0.0004588635,0.002964768,0.001982967,0.001153618,0.001367619,0.0003757005,0.005438615],"category_scores_gemma":[0.001488592,0.0002654023,0.0006975363,0.004526214,0.0003954321,0.0007290412,0.001082316,0.0006561742,0.001183975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01665098,"about_ca_system_score_gemma":0.02390328,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9928235,"about_ca_topic_score_gemma":0.997168,"domain_scores_codex":[0.9992931,0.00001227686,0.00003651365,0.0001296974,0.0003273888,0.000200991],"domain_scores_gemma":[0.9968966,0.00004548854,0.0002082428,0.0001167751,0.002360566,0.0003723164],"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":[0.0005473802,0.00009199486,0.6450495,0.0008044423,0.000490205,0.0002576897,0.000790777,0.001712778,0.002320623,0.0008286632,0.2987511,0.04835479],"study_design_scores_gemma":[0.00001994775,0.00001033585,0.9699943,0.00008590123,0.00003795452,0.00004263652,0.0002986627,0.0004121663,0.0002345261,0.00003831478,0.02879907,0.00002616549],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1777262,0.003144559,0.0004902688,0.0006543621,0.0002206919,0.00007960257,0.8064591,0.0004763867,0.01074879],"genre_scores_gemma":[0.3552704,0.002375999,0.00163301,0.0004620089,0.0000811373,0.0001180203,0.6305148,0.0001263935,0.009418163],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01665098,"threshold_uncertainty_score":0.1208119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02046698462366659,"score_gpt":0.3233601168471219,"score_spread":0.3028931322234553,"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."}}