{"id":"W2051460666","doi":"10.1590/s0100-67622010000300015","title":"Accuracy and efficiency evaluation of point-centered quarter method variations for vegetation sampling in an araucaria forest","year":2010,"lang":"en","type":"article","venue":"Revista Árvore","topic":"Forest ecology and management","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Quarter (Canadian coin); Araucaria; Forestry; Sampling (signal processing); Point (geometry); Vegetation (pathology); Statistics; Environmental science; Geography; Mathematics; Computer science; Telecommunications; Archaeology","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":[0.006698826,0.000288476,0.0003836925,0.001445319,0.000294214,0.0004546279,0.001034191,0.0004546935,0.0005098335],"category_scores_gemma":[0.01561882,0.0002952452,0.0003292183,0.0009579103,0.0004345307,0.0004618739,0.0007243421,0.0002087831,0.0002776011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005196433,"about_ca_system_score_gemma":0.0004603838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008940028,"about_ca_topic_score_gemma":0.01688916,"domain_scores_codex":[0.993493,0.003037116,0.0003578179,0.001184792,0.001794395,0.0001328718],"domain_scores_gemma":[0.9921509,0.003324271,0.0008194132,0.001393159,0.00218136,0.0001310124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008566241,0.0001490202,0.5260211,0.0003491119,0.0001941846,0.00006892932,0.001505719,0.01035947,0.03924568,0.0006525093,0.0007575812,0.4198402],"study_design_scores_gemma":[0.0000912823,0.001112345,0.7772813,0.0001197299,0.0001311294,0.0007252471,0.0008480992,0.1921931,0.02255676,0.0009471765,0.00387441,0.0001193574],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.84372,0.0007469211,0.1521634,0.00005729937,0.00002968782,0.0002823291,0.0005386165,0.0005080744,0.001953656],"genre_scores_gemma":[0.8635405,0.0002051518,0.1349628,0.00002289001,0.000007657473,0.0001984368,0.000427144,0.00003452191,0.0006010208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008940028,"threshold_uncertainty_score":0.03542721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03592828691486986,"score_gpt":0.3474648479239968,"score_spread":0.3115365610091269,"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."}}