{"id":"W3127784665","doi":"10.21203/rs.3.rs-32975/v1","title":"Responses of Forest Carbon and Water Coupling to Thinning Treatments Across Multiple Spatial Scales","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Forest ecology and management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Thinning; Environmental science; Coupling (piping); Carbon fibers; Spatial ecology; Forestry; Geography; Ecology; Computer science; Materials science; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004781678,0.0002928679,0.0006436718,0.0002217639,0.0002211868,0.0006483,0.0005049704,0.0006983262,0.004464135],"category_scores_gemma":[0.002782752,0.000361715,0.000393917,0.0002944834,0.0005637463,0.0006310862,0.0006973559,0.0007093769,0.0002837143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005022687,"about_ca_system_score_gemma":0.0003234442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007318689,"about_ca_topic_score_gemma":0.007977327,"domain_scores_codex":[0.9995906,0.00009064438,0.00002595493,0.0001531534,0.0000305317,0.000109187],"domain_scores_gemma":[0.9973812,0.001474359,0.0003745288,0.0002073122,0.0001964757,0.0003662482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.02046702,0.001078673,0.1352764,0.0002384133,0.0005589182,0.0002007884,0.0005475337,0.01335625,0.8155104,0.0006152053,0.0007285472,0.01142185],"study_design_scores_gemma":[0.000124376,0.0006729489,0.9704333,0.000009112885,0.0001688326,0.000057561,0.0003951372,0.01000444,0.01678467,0.0008374653,0.0004783249,0.00003380927],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987295,0.00004642857,0.0003400166,0.00003424434,0.000007095095,0.000005852161,0.0002477562,0.00001742552,0.0005715386],"genre_scores_gemma":[0.9982161,0.00001998565,0.0001876611,0.00005159357,0.000004730035,0.00001562096,0.0002426328,0.00003335165,0.001228243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007318689,"threshold_uncertainty_score":0.01493406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05068828922508263,"score_gpt":0.3632579290468402,"score_spread":0.3125696398217576,"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."}}