{"id":"W3159496635","doi":"","title":"Mountain Forests Ecology, Anthropogenic Degradation And Ways To Improve","year":2018,"lang":"en","type":"article","venue":"Social Science Learning Education Journal","topic":"Botany and Plant Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Siltation; Environmental science; Biosphere; Forest cover; Environmental degradation; Environmental protection; Geography; Agroforestry; Ecology; Hydrology (agriculture); Forestry; Water resource management; Sediment; Geology","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":[0.0002800093,0.0001171626,0.00009569008,0.0004924735,0.0007031524,0.001204041,0.0001867927,0.0001957986,0.006159629],"category_scores_gemma":[0.0003965448,0.00004670713,0.0001181717,0.0006660193,0.0005423509,0.0005889017,0.0004165584,0.0003344405,0.0003016833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004519784,"about_ca_system_score_gemma":0.001204493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01252441,"about_ca_topic_score_gemma":0.03814339,"domain_scores_codex":[0.9998527,0.00004152793,0.000006416199,0.00001463599,0.00002311294,0.00006160881],"domain_scores_gemma":[0.9997458,0.00001355641,0.00006928689,0.0000110857,0.00006027228,0.0001000726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008719635,0.0002345984,0.5055648,0.0009247404,0.0001799214,0.0009560258,0.004189317,0.001271054,0.002191749,0.037037,0.03540017,0.4119635],"study_design_scores_gemma":[0.000009665781,0.0001635362,0.8032654,0.0004775746,0.00005517998,0.0006391196,0.01123342,0.0004219881,0.0002688084,0.007149538,0.1762983,0.00001753653],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7971321,0.05436133,0.002528758,0.03837588,0.0005206566,0.00007442789,0.001601102,0.0001475165,0.1052582],"genre_scores_gemma":[0.9812748,0.01061859,0.0008138039,0.0005999295,0.000140988,0.00001292796,0.000292795,0.000006503397,0.006239711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01252441,"threshold_uncertainty_score":0.024903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750579849346473,"score_gpt":0.2830289539072806,"score_spread":0.2655231554138159,"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."}}