{"id":"W2368869429","doi":"","title":"Forestry information text classification algorithm based on GMM model","year":2014,"lang":"en","type":"article","venue":"Zhongnan Linye Keji Daxue xuebao","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Mixture model; Computer science; Artificial intelligence; Decision tree; Naive Bayes classifier; Gaussian; Classifier (UML); Pattern recognition (psychology); tf–idf; Statistical classification; Algorithm; Data mining; Machine learning; Support vector machine","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":[0.001018128,0.00101165,0.001150432,0.003112269,0.0009368419,0.001440705,0.001193856,0.001089939,0.002758771],"category_scores_gemma":[0.00282507,0.0002777311,0.001327203,0.002096972,0.0004741004,0.002544415,0.0007424315,0.001024123,0.00240521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102247,"about_ca_system_score_gemma":0.001435944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01253917,"about_ca_topic_score_gemma":0.006296907,"domain_scores_codex":[0.9987771,0.0001586611,0.0001032331,0.0004049226,0.0004319918,0.0001241683],"domain_scores_gemma":[0.9992423,0.0001857418,0.00004363001,0.00005304092,0.0004402346,0.00003508754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002113618,0.0001064551,0.003529907,0.0001973068,0.0001052752,0.0001765592,0.000361022,0.04416392,0.01347439,0.009181205,0.01489279,0.9135997],"study_design_scores_gemma":[0.00002746004,0.00006910554,0.003188056,0.0000314821,0.00006556829,0.0002791173,0.0001774861,0.9645264,0.0108857,0.01122095,0.009469366,0.00005932806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02101116,0.0006043027,0.9697768,0.0003628509,0.0002547308,0.0002472098,0.0004100816,0.004118916,0.003214007],"genre_scores_gemma":[0.3495885,0.001333221,0.6281397,0.0003189513,0.0003571244,0.0006466626,0.002460401,0.0003982744,0.01675727],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01253917,"threshold_uncertainty_score":0.02493238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01571889091668318,"score_gpt":0.2335009435446938,"score_spread":0.2177820526280106,"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."}}