{"id":"W2805358780","doi":"10.3389/fpls.2018.00858","title":"Relating Bryophyte Assemblages to a Remotely Sensed Depth-to-Water Index in Boreal Forests","year":2018,"lang":"en","type":"article","venue":"Frontiers in Plant Science","topic":"Bryophyte Studies and Records","field":"Agricultural and Biological Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Ministry of Agriculture and Forestry; Royal Alberta Museum; University of New Brunswick; University of Alberta","funders":"Natural Resources Canada; Canadian Forest Service; Natural Sciences and Engineering Research Council of Canada; U.S. Forest Service; Forest Resource Improvement Association of Alberta","keywords":"Bryophyte; Taiga; Environmental science; Boreal; Ecology; Index (typography); Geography; Forestry; Physical geography; Remote sensing; Biology; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006467108,0.0001575052,0.0002304069,0.0001197976,0.000352358,0.00008176296,0.0004885074,0.00007872408,0.000008773393],"category_scores_gemma":[0.0001344183,0.00005927761,0.00003600516,0.00145868,0.0002514809,0.0001838122,0.0002663244,0.000161928,0.00003343742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001035957,"about_ca_system_score_gemma":0.00001919899,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001438601,"about_ca_topic_score_gemma":0.02023117,"domain_scores_codex":[0.9979884,0.00004243433,0.0002669065,0.0005642478,0.0003709111,0.0007671103],"domain_scores_gemma":[0.9995766,0.00004895346,0.00004335095,0.00008613963,0.00005860204,0.0001862998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001423271,0.00004504065,0.8840303,0.0000051012,0.000003682186,0.00005777069,0.001520882,0.00006205127,0.03330693,0.00001985169,0.01649634,0.06430966],"study_design_scores_gemma":[0.0001159146,0.0002519787,0.9874109,0.00007768356,0.000001240328,0.000009381165,0.0005744956,0.001697025,0.002194845,0.0002706214,0.007185168,0.0002107432],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918704,0.00002270104,0.0001195687,0.00109851,0.002910512,0.0002815277,0.00001469965,0.0000323408,0.003649745],"genre_scores_gemma":[0.9967886,0.00001086847,0.001941496,0.0004678,0.0005741619,0.000008796387,0.000004981071,0.000001258865,0.0002019864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1033805,"threshold_uncertainty_score":0.997647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01371977239351246,"score_gpt":0.2276205521722315,"score_spread":0.213900779778719,"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."}}