{"id":"W4417422255","doi":"10.48550/arxiv.2503.12331","title":"Carbon capture capacity estimation of taiga reforestation and afforestation at the western boreal edge using spatially explicit carbon budget modeling","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Afforestation; Reforestation; Taiga; Boreal; Carbon sequestration; Climate change; Tree planting; Permafrost; Carbon sink","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003414399,0.0002983634,0.0003404009,0.0001345103,0.0001760467,0.00005779939,0.0001959388,0.0002947558,0.00003020863],"category_scores_gemma":[0.00005209538,0.0002322837,0.00006769892,0.0001188718,0.00009236381,0.0001242239,0.0001198816,0.0003596772,0.000001968367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004988017,"about_ca_system_score_gemma":0.0001335969,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.192364,"about_ca_topic_score_gemma":0.2221822,"domain_scores_codex":[0.9983785,0.0001298861,0.0004555508,0.0004551796,0.0003103528,0.0002704968],"domain_scores_gemma":[0.9989461,0.0001253411,0.0003590961,0.0003651103,0.0001293813,0.00007494034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000047647,0.00000623169,0.7014313,0.0002526812,0.00001872444,0.000002466587,0.003878968,0.2934421,0.0001586565,0.00000257406,0.000003738997,0.0007548705],"study_design_scores_gemma":[0.0001442154,0.000024402,0.3253572,0.0002066372,0.00008584619,0.000004431839,0.0001691649,0.6733668,0.0002658122,0.000200851,0.000005773557,0.000168845],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951656,0.000487286,0.0005266461,0.0002192699,0.0005253871,0.0005074385,0.00165745,0.00003227415,0.0008786086],"genre_scores_gemma":[0.993203,0.0002796664,0.0001470349,0.00009169101,0.0001514812,0.000007449798,0.006029302,0.000009640926,0.0000807232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3799247,"threshold_uncertainty_score":0.9472253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07592767260428655,"score_gpt":0.2724287133642153,"score_spread":0.1965010407599287,"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."}}