{"id":"W4410067600","doi":"10.1002/hyp.70134","title":"Impacts of Drought on Water Fluxes and Water‐Use Efficiency in an Age‐Sequence of Temperate Conifer Forests","year":2025,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Global Water Futures; Ministry of Environment; Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; McMaster University; Ontario Innovation Trust; Ontario Ministry of Natural Resources and Forestry; Social Sciences and Humanities Research Council of Canada; Ministry of Natural Resources","keywords":"Temperate climate; Environmental science; Temperate rainforest; Sequence (biology); Temperate forest; Hydrology (agriculture); Physical geography; Ecology; Geography; Geology; Ecosystem; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002232166,0.0001466406,0.0001402012,0.0004381498,0.0003487805,0.0002895509,0.0001186669,0.0001199029,0.000395608],"category_scores_gemma":[0.0003659928,0.00008131204,0.0001137966,0.0003415439,0.0002021643,0.0001645185,0.0001548878,0.0001000841,0.00006489424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001026364,"about_ca_system_score_gemma":0.0004724133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1432483,"about_ca_topic_score_gemma":0.3447466,"domain_scores_codex":[0.9999267,0.000009399573,0.000004779722,0.00001583563,0.00001387614,0.00002950812],"domain_scores_gemma":[0.9997149,0.00002924686,0.00007846193,0.00001296809,0.00007270873,0.00009170609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008085645,0.00002291024,0.9939883,0.000004480244,0.00002289334,0.00009209076,0.0001795739,0.0002022101,0.003901055,0.0000121073,0.00005872202,0.001434876],"study_design_scores_gemma":[3.846471e-7,0.00000458259,0.9997885,3.121006e-7,0.000001485179,0.00001233833,0.00004122455,0.00007634599,0.00004070912,0.00000194836,0.00003167843,5.121747e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998206,0.00001283489,0.00001022844,0.000001861373,3.167295e-7,5.953081e-7,0.00008090988,7.042945e-7,0.00007189468],"genre_scores_gemma":[0.9996709,0.00001369596,0.0000212764,0.000002764033,6.634551e-7,0.000001377125,0.0002040353,4.111449e-7,0.0000848276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1432483,"threshold_uncertainty_score":0.2848289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01608008995261343,"score_gpt":0.2452112547661055,"score_spread":0.229131164813492,"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."}}