{"id":"W4391343146","doi":"10.1080/02827581.2024.2305186","title":"Temporal changes in forest floor carbon stocks following scarification in boreal lichen woodlands","year":2024,"lang":"en","type":"article","venue":"Scandinavian Journal of Forest Research","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université du Québec à Chicoutimi; Ministère des Ressources naturelles et des Forêts (Québec); Cégep de Baie-Comeau; Université du Québec à Rimouski","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scarification; Microsite; Forest floor; Environmental science; Afforestation; Taiga; Forestry; Coarse woody debris; Woodland; Boreal; Agroforestry; Ecology; Geography; Soil science; Agronomy; Biology; Seedling; Soil water; Habitat","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002577318,0.000140766,0.0001703308,0.0003893097,0.00032232,0.0003513306,0.0001975531,0.0002032649,0.0007558913],"category_scores_gemma":[0.000381176,0.00007139668,0.0001227139,0.0002547044,0.0002426276,0.0002206772,0.0002030226,0.0001767583,0.0001012285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021351,"about_ca_system_score_gemma":0.000340193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1167417,"about_ca_topic_score_gemma":0.3444151,"domain_scores_codex":[0.9999062,0.00001070788,0.000005081657,0.00002405158,0.00001800635,0.00003593587],"domain_scores_gemma":[0.9995316,0.00004349319,0.000160785,0.0000271653,0.0001388456,0.00009822002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006195182,0.0001238832,0.969262,0.00003235536,0.00004648272,0.000146778,0.0004705696,0.000284249,0.01875085,0.00001691007,0.0001054537,0.01014076],"study_design_scores_gemma":[6.268571e-7,0.00003414628,0.9996719,9.77598e-7,0.00000193897,0.000008745728,0.00006913966,0.00004143364,0.0001274701,0.000001826989,0.00004104472,8.598318e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996783,0.0000463843,0.00002142481,0.000002894593,5.705589e-7,0.000003634825,0.000113448,0.000001206096,0.0001321463],"genre_scores_gemma":[0.9993667,0.00002746966,0.0000550244,0.000007185577,9.063229e-7,0.000006258097,0.0003012388,5.988715e-7,0.0002346435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1167417,"threshold_uncertainty_score":0.2321244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05342106343672141,"score_gpt":0.3090643875805555,"score_spread":0.2556433241438341,"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."}}