{"id":"W224862179","doi":"","title":"Principle, method and application of FORECAST model.","year":2009,"lang":"en","type":"article","venue":"Zhejiang Linxueyuan xuebao","topic":"Forest, Soil, and Plant Ecology in China","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Process (computing); Forest ecology; Variety (cybernetics); Forest management; Computer science; Ecosystem model; Function (biology); Environmental resource management; Management science; Government (linguistics); Ecosystem management; Mathematical model; Ecosystem; Ecology; Environmental science; Economics; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.002021068,0.000878409,0.0006108135,0.001492429,0.0006763834,0.001730449,0.001616459,0.00157805,0.00434581],"category_scores_gemma":[0.004139881,0.0004226571,0.001085525,0.001487224,0.001061635,0.002815492,0.001444613,0.001883026,0.002374422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009815814,"about_ca_system_score_gemma":0.002179887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005921782,"about_ca_topic_score_gemma":0.001590114,"domain_scores_codex":[0.9988103,0.0003486593,0.00009911686,0.0001952042,0.0004904664,0.00005641194],"domain_scores_gemma":[0.9990898,0.0003993268,0.00007412117,0.0001386407,0.0002643448,0.00003367886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006264395,0.00004461621,0.001800875,0.0004900423,0.00006580468,0.0002310895,0.0003674181,0.1017879,0.002538628,0.6009555,0.02657418,0.2650813],"study_design_scores_gemma":[0.00004909635,0.00007329616,0.0009077778,0.0002485188,0.00006603921,0.0005160933,0.0001248392,0.4336385,0.002659357,0.3641723,0.197424,0.0001202799],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001052316,0.001959518,0.9814779,0.001081986,0.0004496122,0.0001266609,0.0003521312,0.0005160251,0.01298394],"genre_scores_gemma":[0.1660494,0.01197273,0.7884887,0.0007998662,0.001699554,0.001562428,0.001423762,0.0004803439,0.02752334],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005921782,"threshold_uncertainty_score":0.01453817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02137803427126157,"score_gpt":0.356942755772488,"score_spread":0.3355647215012264,"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."}}