{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003938949,0.00008596927,0.00007096101,0.000168334,0.00005739973,0.00007517092,0.0004585225,0.00006466075,0.00003156142],"category_scores_gemma":[0.00049537,0.00007486738,0.00007205447,0.000103373,0.0000623524,0.00002155826,0.00006220764,0.0001942826,0.00001668263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002169824,"about_ca_system_score_gemma":0.0001801338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001978342,"about_ca_topic_score_gemma":0.000003601421,"domain_scores_codex":[0.998826,0.00002326099,0.0002592917,0.0001270572,0.0006632084,0.0001011455],"domain_scores_gemma":[0.9987093,0.00004148629,0.0002781705,0.00009670395,0.0007713372,0.0001030486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001271445,0.00008259685,0.002120902,0.000002636233,0.00002025855,0.000009687291,0.00003919398,0.09870267,0.8855678,0.0004666276,0.005619514,0.007240941],"study_design_scores_gemma":[0.002423629,0.001420317,0.1699465,0.0001305652,0.0000272885,0.001938225,0.0001062271,0.08856227,0.4091561,0.00213446,0.3234747,0.0006797543],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7512014,0.00001360103,0.2403616,0.005756842,0.00220369,0.00006551643,0.00001128882,0.000006224495,0.0003798],"genre_scores_gemma":[0.8658679,0.000002335227,0.1317623,0.00186867,0.0003670111,9.367781e-7,0.0000249549,0.000005415523,0.0001004529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4764117,"threshold_uncertainty_score":0.3053004,"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."}}