{"id":"W2112611875","doi":"10.2316/j.2010.210-1023","title":"ALIGNMENT-BASED EXTENSION TO DDPIN FEATURE EXTRACTION","year":2010,"lang":"en","type":"article","venue":"International Journal of Computational Bioscience","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Grantová Agentura České Republiky","keywords":"Extension (predicate logic); Computer science; Feature extraction; Feature (linguistics); Artificial intelligence; Pattern recognition (psychology); Programming language; Linguistics","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":[0.0003330044,0.0005962106,0.0007124833,0.001197394,0.0003085901,0.0007022748,0.0008712984,0.000369019,0.006649978],"category_scores_gemma":[0.001210444,0.000237972,0.0005376298,0.001335405,0.0001507464,0.0007496786,0.0009069152,0.0005149691,0.003971891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001901664,"about_ca_system_score_gemma":0.000421786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009171496,"about_ca_topic_score_gemma":0.001142045,"domain_scores_codex":[0.9997144,0.00002659727,0.00002940329,0.00008100351,0.00010168,0.00004683265],"domain_scores_gemma":[0.9995946,0.00006729276,0.00003042695,0.00009750578,0.0001909513,0.00001928713],"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":[0.0001682341,0.0001086348,0.001941526,0.0001584844,0.00003693294,0.0002458343,0.00002907677,0.008732933,0.08078488,0.00338614,0.008955529,0.8954518],"study_design_scores_gemma":[0.00005309478,0.0001865213,0.008409541,0.00002669908,0.00006482204,0.001446015,0.00005827569,0.7639769,0.1662347,0.007231797,0.05225098,0.00006069268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01349174,0.0001501616,0.977512,0.00005585519,0.00009573314,0.00008722339,0.0006324612,0.005960022,0.002014771],"genre_scores_gemma":[0.2247171,0.0002566894,0.762338,0.0001574106,0.0001147905,0.0003210604,0.004411905,0.0004023352,0.007280598],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006649978,"threshold_uncertainty_score":0.02224636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005835325165920761,"score_gpt":0.3079265576214354,"score_spread":0.3020912324555146,"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."}}