{"id":"W2351532812","doi":"","title":"Application and Research of Decision Tree Algorithm in Protein Structure Prediction","year":2009,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Decision tree; ID3 algorithm; Pruning; Incremental decision tree; Decision tree learning; Algorithm; Alternating decision tree; Machine learning; Data mining; Artificial intelligence; Protein structure prediction; Decision tree model; Tree structure; Protein structure; Binary tree","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.003533958,0.0008122091,0.001405544,0.002750802,0.0007618386,0.00134352,0.001547714,0.001185999,0.001644869],"category_scores_gemma":[0.009221011,0.0003824559,0.0009926104,0.004057574,0.0007694088,0.002594832,0.0006063909,0.001521193,0.0007656647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000634546,"about_ca_system_score_gemma":0.001162698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003272987,"about_ca_topic_score_gemma":0.001310888,"domain_scores_codex":[0.9968065,0.001094745,0.0002130322,0.0004631481,0.001277862,0.0001446755],"domain_scores_gemma":[0.9949818,0.003182754,0.0001670303,0.0002388836,0.00129258,0.0001368858],"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":[0.0003301098,0.0002852265,0.005958237,0.0007338167,0.000249847,0.00038286,0.0002375768,0.1516626,0.008890393,0.03795937,0.006385943,0.7869241],"study_design_scores_gemma":[0.00006126479,0.0001969337,0.001656605,0.0001101426,0.0001001028,0.0003816126,0.00007429148,0.9391899,0.009333013,0.03693,0.01190905,0.00005716473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02134907,0.006717934,0.9672248,0.0005851606,0.0002966738,0.00007851086,0.0001111565,0.0006420746,0.002994709],"genre_scores_gemma":[0.2908375,0.009769232,0.695457,0.0003373835,0.0003987682,0.0001395706,0.0006678649,0.0001742434,0.002218368],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003533958,"threshold_uncertainty_score":0.01868957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01412512144849771,"score_gpt":0.3010578367047373,"score_spread":0.2869327152562396,"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."}}