{"id":"W7099629824","doi":"","title":"Comparative Analysis of Boreal Forest Landscape Processes Using SELES: Russian Versus Finnish Karelia","year":2015,"lang":"en","type":"article","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Taiga; Boreal; Vegetation (pathology); Digital elevation model; Forest management; Biodiversity; Abundance (ecology); Forest ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000581981,0.0002197446,0.0002429258,0.001021546,0.0002324624,0.0009715937,0.0002511624,0.0002139726,0.0007522563],"category_scores_gemma":[0.001062224,0.0001484329,0.000583855,0.000837609,0.0003615203,0.0005800174,0.0004234589,0.0001323945,0.00008100471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006428325,"about_ca_system_score_gemma":0.0002505622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02821662,"about_ca_topic_score_gemma":0.0326892,"domain_scores_codex":[0.9998221,0.00007264306,0.00001088846,0.00004041333,0.0000217579,0.00003220419],"domain_scores_gemma":[0.999668,0.0001902174,0.00004391038,0.00002333509,0.00004519783,0.00002942818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007182177,0.0001965457,0.8004077,0.0001412487,0.0004058777,0.0004799931,0.002171622,0.1526502,0.007384344,0.004992925,0.0003466935,0.03010463],"study_design_scores_gemma":[0.00002605071,0.0001667465,0.8595452,0.00001810254,0.0001131622,0.0001322599,0.00231245,0.1350725,0.0009544455,0.0006844547,0.0009453594,0.0000293091],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987929,0.00003151217,0.0004269466,0.00000945991,8.174313e-7,0.000007530268,0.0001051745,0.00001132025,0.0006143983],"genre_scores_gemma":[0.9993898,0.00003034676,0.000320006,0.000001348316,7.198257e-7,0.000006274137,0.0001691651,0.000002920835,0.00007942625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02821662,"threshold_uncertainty_score":0.05610478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07128280372726849,"score_gpt":0.300612753709644,"score_spread":0.2293299499823755,"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."}}