{"id":"W2735536468","doi":"10.5558/tfc2017-015","title":"The NEBIE plot network: Background and experimental design","year":2017,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Manitoba Environmental Industries Association; Ontario Forest Research Institute","funders":"FPInnovations; Ontario Innovation Trust; Canadian Forest Service; Ontario Ministry of Natural Resources and Forestry; Natural Resources Canada; Ministry of Natural Resources; Natural Sciences and Engineering Research Council of Canada; U.S. Forest Service; University of Pittsburgh","keywords":"Silviculture; Context (archaeology); Forest management; Forestry; Plot (graphics); Scale (ratio); Environmental science; Geography; Environmental resource management; Ecology; Cartography; Biology; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009918511,0.002085328,0.002509669,0.00157464,0.003558222,0.001764156,0.004683834,0.00211469,0.03511624],"category_scores_gemma":[0.007440565,0.002337353,0.0007629262,0.002857114,0.00164315,0.0007441548,0.00219171,0.002593132,0.007121884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006765523,"about_ca_system_score_gemma":0.01229264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04834174,"about_ca_topic_score_gemma":0.1202656,"domain_scores_codex":[0.9911515,0.003074678,0.000607949,0.001735003,0.002425821,0.001005079],"domain_scores_gemma":[0.9928632,0.001647997,0.0008167863,0.001388073,0.002143884,0.00114013],"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":[0.1207013,0.06706014,0.02650594,0.02029779,0.001211506,0.001030003,0.006427202,0.02266771,0.1068953,0.03665207,0.1101499,0.4804012],"study_design_scores_gemma":[0.02774529,0.0526017,0.07746856,0.001635275,0.001095678,0.0002584249,0.0007817544,0.01197269,0.01520294,0.009913011,0.8006724,0.0006523824],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"empirical","genre_scores_codex":[0.1106241,0.00362703,0.1348324,0.0008649857,0.0009802826,0.6565769,0.03250648,0.002058421,0.05792943],"genre_scores_gemma":[0.02530164,0.001333411,0.17547,0.0005076957,0.0001262015,0.7744858,0.004292653,0.0002846429,0.01819798],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04834174,"threshold_uncertainty_score":0.1174755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06800540047388609,"score_gpt":0.2577689661684718,"score_spread":0.1897635656945857,"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."}}