{"id":"W2044657107","doi":"10.3390/f4010001","title":"The Validation of the Mixedwood Growth Model (MGM) for Use in Forest Management Decision Making","year":2013,"lang":"en","type":"article","venue":"Forests","topic":"Forest ecology and management","field":"Environmental Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Forest Resource Improvement Association of Alberta","keywords":"Basal area; Deciduous; Site index; Forestry; Diameter at breast height; Environmental science; Boreal; Taiga; Forest management; Pinus contorta; Black spruce; Silviculture; Stand development; Geography; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.006596599,0.0009784927,0.0005907248,0.0004727677,0.0005059726,0.000944385,0.001196087,0.0006766723,0.0006141933],"category_scores_gemma":[0.01030811,0.000287497,0.00050887,0.0003426039,0.0004013371,0.0006649116,0.0007147245,0.0005408886,0.0001036298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001361381,"about_ca_system_score_gemma":0.002188316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04643532,"about_ca_topic_score_gemma":0.04183228,"domain_scores_codex":[0.9990726,0.0005025705,0.00005364731,0.0001322863,0.0001532639,0.00008571261],"domain_scores_gemma":[0.9948745,0.003690635,0.0003222913,0.0003349224,0.0006497488,0.0001277946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001231623,0.00006103098,0.02014257,0.00002686117,0.00005021133,0.0000531132,0.00002617026,0.9684629,0.0007150997,0.0006123471,0.0001720233,0.009554415],"study_design_scores_gemma":[0.00002167368,0.00007850306,0.003269437,0.000008494815,0.00001137773,0.00001142532,0.00001467562,0.9954286,0.0006787578,0.0003162047,0.0001520432,0.000008837474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9543775,0.0001094602,0.04196213,0.0001199891,0.00002699143,0.00009230482,0.0007448792,0.0003621591,0.002204626],"genre_scores_gemma":[0.9809111,0.00002147398,0.01841997,0.00003154783,0.000004026347,0.00004899531,0.000341365,0.00003177149,0.0001898387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04643532,"threshold_uncertainty_score":0.0923301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01264318884097196,"score_gpt":0.2304269689868882,"score_spread":0.2177837801459163,"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."}}