{"id":"W2186548078","doi":"10.1139/cjfr-2015-0237","title":"Mechanistic and statistical approaches to predicting wind damage to individual maritime pine (<i>Pinus pinaster</i>) trees in forests","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Tree Root and Stability Studies","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut National de la Recherche Agronomique; Agence Nationale de la Recherche; Natural Environment Research Council; Sight Research UK","keywords":"Pinus pinaster; Environmental science; Storm; Pinus <genus>; Climate change; Forestry; Ecology; Meteorology; Geography; 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":[0.003353347,0.0007677685,0.0003622606,0.001590303,0.0003351644,0.0007599714,0.0009287476,0.0007380012,0.0004481509],"category_scores_gemma":[0.006636119,0.0005213398,0.0007491812,0.0006074914,0.0005307106,0.001053259,0.0004850964,0.0004232758,0.00007317986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001114934,"about_ca_system_score_gemma":0.0009905485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01900211,"about_ca_topic_score_gemma":0.03538951,"domain_scores_codex":[0.9992633,0.0003151819,0.00006371894,0.0001313031,0.0001585554,0.00006784567],"domain_scores_gemma":[0.9961829,0.002372987,0.0008842485,0.0001692074,0.0002707745,0.0001199419],"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":[0.0001080781,0.0002722669,0.2568049,0.00005750831,0.0001674695,0.00006694183,0.0001275502,0.7179901,0.002034417,0.001570208,0.00009351174,0.020707],"study_design_scores_gemma":[0.000009144232,0.0002237066,0.1386964,0.00001237081,0.00003820944,0.00005785249,0.0001125467,0.8585884,0.0007771644,0.001319282,0.0001316235,0.00003328522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754038,0.00008989045,0.02365414,0.00006872089,0.000004820668,0.00004657263,0.0001272206,0.0000544252,0.0005504137],"genre_scores_gemma":[0.9944593,0.00004725075,0.005176559,0.000009190294,0.000005237655,0.00002610651,0.0001242215,0.00000355576,0.0001487095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01900211,"threshold_uncertainty_score":0.03778303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1630341758865833,"score_gpt":0.2995825195492083,"score_spread":0.136548343662625,"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."}}