{"id":"W3214260781","doi":"10.1139/cjfr-2020-0286","title":"Potential of typical highland and mountain forests in the Czech Republic for climate-smart forestry: ecosystem-scale drought responses","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Beech; Climate change; Environmental science; Forest ecology; Context (archaeology); Forestry; Ecosystem; Agroforestry; Deciduous; Productivity; Geography; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003465407,0.0001535795,0.000207721,0.0004326426,0.0005246408,0.0006825751,0.0002478602,0.0001498813,0.0009534854],"category_scores_gemma":[0.0004087969,0.0001158875,0.0002493763,0.0004790876,0.000270234,0.0003931477,0.0005562381,0.0001221019,0.00009575645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005720766,"about_ca_system_score_gemma":0.0005623038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01666554,"about_ca_topic_score_gemma":0.04451833,"domain_scores_codex":[0.999853,0.00002461527,0.00001249359,0.00003140786,0.00002054557,0.00005793485],"domain_scores_gemma":[0.9998413,0.00002154753,0.00004158655,0.00002197726,0.00002871313,0.00004483112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006810984,0.0001824748,0.8875355,0.0002221971,0.0003188827,0.0009313978,0.0006860414,0.01698412,0.05760289,0.001610463,0.0007308709,0.03251419],"study_design_scores_gemma":[0.00001446956,0.00003931143,0.9960274,0.000009862315,0.00002318656,0.0001873566,0.0004871824,0.001553865,0.0006898273,0.00009338623,0.0008640518,0.00001013306],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988298,0.00009894105,0.0001648399,0.00001260904,0.000001219331,0.000007911379,0.0002107211,0.0000102594,0.0006638421],"genre_scores_gemma":[0.999737,0.00002675609,0.00008349163,0.000003849456,3.452017e-7,0.000002556365,0.00009436017,0.000001324372,0.00005046119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01666554,"threshold_uncertainty_score":0.03313708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01865658675369659,"score_gpt":0.2714771961384173,"score_spread":0.2528206093847207,"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."}}