{"id":"W2103192959","doi":"10.1111/nph.12859","title":"Xylem formation can be modeled statistically as a function of primary growth and cambium activity","year":2014,"lang":"en","type":"article","venue":"New Phytologist","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Chinese Academy of Sciences","keywords":"Xylem; Cambium; Phenology; Taiga; Ecosystem; Biology; Shoot; Botany; Secondary growth; Primary production; Ecology","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":[0.0005306481,0.0005530767,0.0003798277,0.0003451273,0.0003690773,0.0007158813,0.0007248814,0.0004611041,0.0009302075],"category_scores_gemma":[0.001120354,0.0004190597,0.0006555826,0.0003973063,0.0008186275,0.0006164587,0.0002445276,0.000429134,0.0001540503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001770158,"about_ca_system_score_gemma":0.001205256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1156798,"about_ca_topic_score_gemma":0.1264349,"domain_scores_codex":[0.9997733,0.00004526859,0.000007839729,0.0000908039,0.00002151186,0.00006125635],"domain_scores_gemma":[0.9996225,0.0001631021,0.0001076065,0.00004204721,0.00003562744,0.00002913425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002832754,0.000108737,0.1121004,0.00006978124,0.000281944,0.0001461729,0.0001800644,0.8438977,0.01897899,0.01242661,0.0005343595,0.010992],"study_design_scores_gemma":[0.00001856055,0.0000386817,0.04144868,0.000004655173,0.00005972867,0.00004664009,0.00002807428,0.9537683,0.0008207932,0.003208269,0.0005382734,0.00001934427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9261711,0.000333114,0.07056594,0.0002169883,0.00001366975,0.00002675474,0.0006407022,0.0002209549,0.001810651],"genre_scores_gemma":[0.9962621,0.0001140828,0.002258568,0.00001821219,0.000006299926,0.00002160984,0.000152099,0.00001505256,0.001151902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1156798,"threshold_uncertainty_score":0.2300129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01013508597938127,"score_gpt":0.2017109160693032,"score_spread":0.191575830089922,"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."}}