{"id":"W4404121925","doi":"10.15372/gipr20230310","title":"РОЛЬ ЭКОЛОГИЧЕСКИХ РЕСУРСОВ БОРЕАЛЬНЫХ И НЕМОРАЛЬНЫХ ЛЕСОВ ВОЛЖСКОГО БАССЕЙНА В СМЯГЧЕНИИ ГЛОБАЛЬНОГО ПОТЕПЛЕНИЯ","year":2023,"lang":"ru","type":"article","venue":"География и природные ресурсы","topic":"Water Resources and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":[0.005441037,0.0009031615,0.00053817,0.002863151,0.006259528,0.01787949,0.001442515,0.00355525,0.03107262],"category_scores_gemma":[0.01137785,0.0007448298,0.0008758047,0.002820105,0.01130856,0.009881026,0.005153053,0.004910233,0.01245818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007869381,"about_ca_system_score_gemma":0.01273476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01111329,"about_ca_topic_score_gemma":0.01594829,"domain_scores_codex":[0.992145,0.002730333,0.0004057768,0.001195522,0.002767093,0.0007562391],"domain_scores_gemma":[0.9940184,0.001907855,0.0005955885,0.0007277808,0.00203215,0.0007183209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00005655242,0.00005208512,0.002418941,0.0003757772,0.00003019865,0.0003283708,0.0128248,0.0003591276,0.0009417268,0.8940768,0.02568432,0.06285134],"study_design_scores_gemma":[0.00002461813,0.00004791224,0.004364698,0.0007685013,0.00005049747,0.0004768958,0.01226404,0.0005351166,0.001717839,0.2411423,0.7385255,0.00008213615],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02504157,0.01555486,0.04289393,0.03720377,0.001879571,0.0002322552,0.0008262965,0.0003658301,0.8760019],"genre_scores_gemma":[0.6243317,0.02134894,0.0597717,0.006601917,0.001293956,0.0007567308,0.001054023,0.0007581055,0.284083],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03107262,"threshold_uncertainty_score":0.1039482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01514896622551861,"score_gpt":0.2124175605331382,"score_spread":0.1972685943076196,"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."}}