{"id":"W4409677615","doi":"10.24011/barofd.1611617","title":"Strengthening Wood Structures Against Climate Change: Approaches from Türkiye and Different Countries","year":2025,"lang":"en","type":"article","venue":"Bartın Orman Fakültesi Dergisi","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Geography; Political science; Biology; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001017173,0.0006083011,0.000318887,0.001665631,0.005008091,0.00199747,0.00083388,0.001068217,0.003490543],"category_scores_gemma":[0.0005818288,0.0001915206,0.0004204293,0.001813137,0.00245352,0.001491182,0.001818537,0.0008036271,0.0002256871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005512588,"about_ca_system_score_gemma":0.004018921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01841053,"about_ca_topic_score_gemma":0.05672848,"domain_scores_codex":[0.9995783,0.0001069471,0.00002919588,0.00004904269,0.00007550019,0.0001609783],"domain_scores_gemma":[0.9997872,0.00006701608,0.00002516149,0.0000136369,0.00006160465,0.00004540853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005499112,0.0008010533,0.06961082,0.004336145,0.0001535597,0.01189207,0.2320087,0.002706564,0.01380905,0.1066841,0.0119417,0.5455062],"study_design_scores_gemma":[0.00003785244,0.0004185667,0.1349611,0.002241881,0.0001131225,0.002800738,0.496414,0.0004287244,0.003821949,0.008225077,0.3504396,0.00009745357],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7804826,0.07465249,0.00285035,0.007196762,0.0005129118,0.0001709885,0.0001606803,0.00002991637,0.1339434],"genre_scores_gemma":[0.9656683,0.01959344,0.00331692,0.001022601,0.00005602573,0.00006505592,0.000119973,0.00001137029,0.01014628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01841053,"threshold_uncertainty_score":0.03999674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02303747141255035,"score_gpt":0.1993331923969014,"score_spread":0.176295720984351,"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."}}