{"id":"W3206572665","doi":"","title":"The response of boreal peatland community composition and NDVI to hydrologic change, warming, and elevated carbon dioxide","year":2018,"lang":"en","type":"book-chapter","venue":"Wiley eBooks","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Normalized Difference Vegetation Index; Environmental science; Peat; Boreal; Climate change; Shrub; Forb; Ecosystem; Taiga; Global warming; Atmospheric sciences; Ecology; Physical geography; Grassland; Geography; Geology; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007575455,0.0002491947,0.0003251675,0.0000563748,0.0003443493,0.00001996175,0.0002211232,0.0002472153,0.0000464433],"category_scores_gemma":[0.00002225623,0.000176914,0.00003796763,0.00001338523,0.00075684,0.00002028108,0.0004881889,0.0003208909,0.00000832563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006137273,"about_ca_system_score_gemma":0.000009048455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001210897,"about_ca_topic_score_gemma":0.001907175,"domain_scores_codex":[0.9988542,0.000212422,0.0002508719,0.0002635765,0.0001634983,0.0002554061],"domain_scores_gemma":[0.9989817,0.0003079623,0.0001730015,0.0003899861,0.00001447797,0.000132858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0397153,0.0005589918,0.5037368,0.0005295398,0.001439067,0.0006530827,0.06460746,0.00002284019,0.278878,0.004566339,0.0248958,0.08039678],"study_design_scores_gemma":[0.004226815,0.01025333,0.682299,0.0009928948,0.0005919738,0.0005353798,0.0002221062,0.0008062304,0.006662158,0.02379856,0.2671799,0.002431632],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9087103,0.0001015923,0.000001814918,0.0001399442,0.00005419431,0.0004171517,0.00004022658,0.00002498084,0.09050979],"genre_scores_gemma":[0.9790515,0.0001674576,0.00003448502,0.0002997001,0.00006079276,0.0000312106,0.00004140354,0.00002518953,0.0202882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2722158,"threshold_uncertainty_score":0.7214344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02062854312876694,"score_gpt":0.2296511758995907,"score_spread":0.2090226327708238,"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."}}