{"id":"W4400558524","doi":"10.15372/sjfs20240211","title":"ЛЕС В СРАВНИТЕЛЬНОМ ПРАВЕ: ГЕРМАНИЯ, КИТАЙСКАЯ НАРОДНАЯ РЕСПУБЛИКА, КАНАДА, НИГЕРИЯ, ТУРЦИЯ","year":2024,"lang":"en","type":"article","venue":"Сибирский лесной журнал","topic":"Forest Management and Policy","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006377317,0.0006098708,0.0004297633,0.0002782423,0.0003555358,0.000472492,0.001050522,0.0002510266,0.05008531],"category_scores_gemma":[0.00007472061,0.0005520377,0.0003466751,0.001299471,0.0004368134,0.0009316399,0.0008352342,0.0005251375,0.08878034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003761304,"about_ca_system_score_gemma":0.00005452662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001204946,"about_ca_topic_score_gemma":0.0005263882,"domain_scores_codex":[0.9959439,0.0001188766,0.0006074411,0.001148367,0.0009606159,0.001220778],"domain_scores_gemma":[0.9982514,0.0001569994,0.0001077505,0.001053749,0.00001485543,0.0004152214],"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":[0.00003991752,0.000137588,0.007496614,0.0001381571,0.0001098792,0.0001994835,0.001085499,0.0005140954,0.0008956529,0.01261687,0.9383072,0.0384591],"study_design_scores_gemma":[0.0004038734,0.0001385797,0.005951476,0.00009434605,0.00009642474,0.00003312834,0.0000621354,0.004693663,0.0005189186,0.003065575,0.9841945,0.0007474353],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.137989,0.001342632,0.0002740374,0.004804754,0.004564781,0.0009603739,0.00007813671,0.001343704,0.8486426],"genre_scores_gemma":[0.7297026,0.000234297,0.0006564814,0.001892232,0.001026335,0.000112387,0.000106146,0.0001474458,0.2661221],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5917136,"threshold_uncertainty_score":0.9996931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007218290917071771,"score_gpt":0.2315606952041901,"score_spread":0.2243424042871183,"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."}}