{"id":"W1863037484","doi":"10.1111/j.1365-2427.2010.02410.x","title":"Effects of upland clearcutting and riparian partial harvesting on leaf pack breakdown and aquatic invertebrates in boreal forest streams","year":2010,"lang":"en","type":"article","venue":"Freshwater Biology","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Laurentian University; Natural Resources Canada; Canadian Forest Service","funders":"Anhui University of Science and Technology; Agence Nationale pour le Développement de la Recherche Universitaire; Ministry of Natural Resources","keywords":"Clearcutting; Logging; Riparian zone; Environmental science; Basal area; Litter; Taiga; Boreal; Riparian buffer; Ecology; Invertebrate; STREAMS; Plant litter; Riparian forest; Ecosystem; Biology; Habitat","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002441341,0.0001720728,0.0002666891,0.00007641593,0.0001067446,0.00002602482,0.0001482383,0.0002073452,0.0001554447],"category_scores_gemma":[0.0001059211,0.0001402272,0.00002248635,0.00008287496,0.0007057134,0.0001452103,0.0002653772,0.0002692477,0.00006698964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001759075,"about_ca_system_score_gemma":0.000006653345,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01744345,"about_ca_topic_score_gemma":0.1699847,"domain_scores_codex":[0.9987819,0.0001268638,0.000223521,0.0003905678,0.00006407891,0.0004130825],"domain_scores_gemma":[0.9994559,0.0002069349,0.00008220749,0.0001373673,0.00000296451,0.0001146575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000679367,0.00006571049,0.9416351,0.00003218379,0.00001202202,0.00002668329,0.0005499755,0.00001406176,0.05143009,0.0002707084,0.000391875,0.005503627],"study_design_scores_gemma":[0.00255095,0.00110081,0.8920619,0.00004400106,0.00003311693,0.00004692093,0.00009289294,0.03401935,0.06188906,0.005243932,0.002530813,0.0003862855],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985349,0.00001434275,0.00001418184,0.0002382303,0.0001711761,0.0001944205,0.0000158428,0.00001875729,0.0007981298],"genre_scores_gemma":[0.9990249,0.00001219507,0.0005260685,0.0002709809,0.00003436748,0.00000843547,0.00004091743,0.000009975432,0.00007213698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1525413,"threshold_uncertainty_score":0.9890995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005724732589994968,"score_gpt":0.1947606752322761,"score_spread":0.1890359426422812,"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."}}