{"id":"W6982605712","doi":"","title":"Innovation in Forest Engineering : Adapting to Structural Change :
\\nofficial proceedings (Extended Abstracts) of the
\\n4th Forest Engineering Conference
\\nheld at White River, South Africa
\\nApril 5-7, 2011","year":2011,"lang":"en","type":"book","venue":"SUNScholar (Stellenbosch University)","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministero dello Sviluppo Economico; Forest and Wood Products Australia; European Commission; Ministère du Développement Économique, de l’Innovation et de l’Exportation","keywords":"White (mutation); Forest industry; White paper; Engineering education; Structural change; Climate change; Forest structure","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005367507,0.0009740148,0.001198092,0.002178187,0.0002665933,0.00007981586,0.00100716,0.001040981,0.0001761896],"category_scores_gemma":[0.0009751391,0.0009805269,0.0003434409,0.001365503,0.0001676409,0.0007390308,0.001012943,0.002161355,0.00006677084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007789342,"about_ca_system_score_gemma":0.0005323276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001111318,"about_ca_topic_score_gemma":0.002505758,"domain_scores_codex":[0.9958768,0.00003748045,0.001052525,0.001033183,0.0009383299,0.001061706],"domain_scores_gemma":[0.9969093,0.0001912604,0.0008842503,0.0006766569,0.000896608,0.0004418867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007669653,0.0008757797,0.8299513,0.008216695,0.002275595,0.001711864,0.07118507,0.0238694,0.00403063,0.034222,0.007601527,0.008390425],"study_design_scores_gemma":[0.00634134,0.001200953,0.913974,0.007956594,0.001096958,0.0001012329,0.001775204,0.006033284,0.001311277,0.0002774278,0.05710969,0.002821987],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9358097,0.0003373081,0.0003369967,0.0001156208,0.0008591026,0.002162485,0.0003040417,0.0003033009,0.05977147],"genre_scores_gemma":[0.962459,0.00008176963,0.0009525451,0.00005377951,0.0005458582,0.00001038164,0.0002489851,0.0001701669,0.03547755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08402269,"threshold_uncertainty_score":0.9992645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03064024165377279,"score_gpt":0.2016715393866391,"score_spread":0.1710312977328663,"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."}}