{"id":"W2044815121","doi":"10.4028/www.scientific.net/amr.971-973.2198","title":"Physical Environment Assessment Tools for the Performance of Recreational Farm","year":2014,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Sustainable Building Design and Assessment","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental economics; Workload; Statistic; Sustainability; Government (linguistics); Recreation; Process (computing); Engineering; Environmental resource management; Computer science; Risk analysis (engineering); Business; Economics; Mathematics; Statistics","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":[0.001411341,0.0007990451,0.0003387961,0.004369581,0.0004243707,0.001538659,0.0004965811,0.0005761907,0.009391792],"category_scores_gemma":[0.007153355,0.0001586966,0.0007343381,0.00237299,0.0002274086,0.001518099,0.0009525206,0.0004323616,0.001973501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004402376,"about_ca_system_score_gemma":0.0006187739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002453523,"about_ca_topic_score_gemma":0.004868942,"domain_scores_codex":[0.9985429,0.0004078762,0.000167272,0.0001486891,0.0006248902,0.0001084004],"domain_scores_gemma":[0.99691,0.001190315,0.0004823567,0.0001665102,0.001093202,0.0001575143],"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":[0.0004812082,0.001091225,0.2614623,0.001169941,0.0001393079,0.0004876094,0.003320525,0.01130801,0.007898305,0.004369315,0.01271598,0.6955562],"study_design_scores_gemma":[0.00006505563,0.001141733,0.8604594,0.0009467078,0.0002610298,0.0007841552,0.01556466,0.07311808,0.008906233,0.005323492,0.03317925,0.0002502268],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7677182,0.001148941,0.1238915,0.0006591195,0.0002216784,0.001434912,0.006511445,0.003304428,0.09510978],"genre_scores_gemma":[0.936023,0.0004237605,0.05540431,0.00009776821,0.00003304775,0.0006975697,0.00188289,0.00006823786,0.005369502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009391792,"threshold_uncertainty_score":0.03141862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03782315611200567,"score_gpt":0.3497618150164289,"score_spread":0.3119386589044233,"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."}}