{"id":"W4213105947","doi":"10.1007/s00468-022-02273-5","title":"Trimming influences tree light interception and space exploration: contrasted responses of two cultivars of Fraxinus pennsylvanica at various scales of their architecture","year":2022,"lang":"en","type":"article","venue":"Trees","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais; Hydro-Québec; Université du Québec à Montréal; Natural Sciences and Engineering Research Council of Canada","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Interception; Trimming; Tree (set theory); Crown (dentistry); Cultivar; Computer science; Biology; Mathematics; Ecology; Botany; Materials science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0001432407,0.0002943492,0.0003577533,0.0004060334,0.0003373668,0.0003968689,0.0004540073,0.0004489045,0.0009547563],"category_scores_gemma":[0.0002628794,0.0003279812,0.0001999742,0.0001909418,0.0002966334,0.0003078819,0.0004159065,0.0006764006,0.0001483501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007826862,"about_ca_system_score_gemma":0.0002604995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01006509,"about_ca_topic_score_gemma":0.02262852,"domain_scores_codex":[0.9998512,0.00001825374,0.000007352529,0.00006664077,0.0000182964,0.00003812331],"domain_scores_gemma":[0.9995303,0.0001178031,0.00007925641,0.00003565546,0.00004645658,0.0001905223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005006009,0.000122371,0.01088023,0.00001623076,0.00001826265,0.00005203502,0.000159625,0.0001108416,0.9871256,0.00004438647,0.00002642878,0.000943544],"study_design_scores_gemma":[0.00003512196,0.0004573047,0.9322654,0.00000651351,0.00006458111,0.0001640501,0.0004742759,0.002038798,0.0639948,0.00005881046,0.0004247368,0.00001559138],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997781,0.00002060616,0.00005041795,0.000005356635,7.920358e-7,0.000001429888,0.00002149429,0.000004444591,0.0001173525],"genre_scores_gemma":[0.9986691,0.00002005488,0.0001870088,0.0000436717,0.000001381947,0.000006804763,0.0001530369,0.00001723178,0.0009017134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01006509,"threshold_uncertainty_score":0.02001297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517395579925062,"score_gpt":0.2491022371522747,"score_spread":0.2339282813530241,"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."}}