{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.002469885,0.002324651,0.0019842,0.000989008,0.001737958,0.001178942,0.004051933,0.00107611,0.02250852],"category_scores_gemma":[0.0002498296,0.002287661,0.001334391,0.004353524,0.001528548,0.001300088,0.005477519,0.001711244,0.1078028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001199256,"about_ca_system_score_gemma":0.000139988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003075379,"about_ca_topic_score_gemma":0.0007396599,"domain_scores_codex":[0.9841357,0.0006923145,0.002492658,0.004001563,0.003575442,0.005102281],"domain_scores_gemma":[0.9927342,0.0003810819,0.0009642795,0.00391164,0.0001027155,0.001906106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004799159,0.002427488,0.03494167,0.001080335,0.001350277,0.002761157,0.009579894,0.01038693,0.01063114,0.004093787,0.8183636,0.1039038],"study_design_scores_gemma":[0.002904351,0.0009070194,0.0623021,0.0004512917,0.00059122,0.00008189027,0.002832702,0.007457926,0.003238062,0.00277177,0.9132432,0.003218501],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7258378,0.003213294,0.00103408,0.02363788,0.009938168,0.006188161,0.0009655781,0.004311535,0.2248735],"genre_scores_gemma":[0.8352243,0.002832385,0.0009437474,0.003565404,0.00205776,0.000439738,0.0004674545,0.0006303914,0.1538389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1093865,"threshold_uncertainty_score":0.9998579,"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."}}