{"id":"W2147803109","doi":"10.1093/bioinformatics/btv274","title":"SpeeDB: fast structural protein searches","year":2015,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; National Research Foundation","keywords":"Protein Data Bank (RCSB PDB); Computer science; Protein Data Bank; Protein superfamily; Interface (matter); Computational biology; Function (biology); Protein structure; Identification (biology); Stability (learning theory); Data mining; Information retrieval; Chemistry; Biology; Machine learning; Stereochemistry; Biochemistry; Genetics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004484468,0.00542726,0.003273695,0.00470646,0.001697042,0.003188492,0.006545786,0.004034518,0.06782793],"category_scores_gemma":[0.01456681,0.002817587,0.002413632,0.005342362,0.0008807515,0.004832064,0.003691652,0.003247899,0.05606837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001320014,"about_ca_system_score_gemma":0.002579757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003016803,"about_ca_topic_score_gemma":0.004470311,"domain_scores_codex":[0.996982,0.000933293,0.0002027315,0.0005357156,0.001082961,0.0002632455],"domain_scores_gemma":[0.9960002,0.00229216,0.000261919,0.0005076063,0.0006883882,0.0002495919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001895742,0.0002904627,0.001728633,0.003225975,0.0006244935,0.000583367,0.0002259986,0.01220646,0.009297173,0.01278043,0.8430752,0.1140661],"study_design_scores_gemma":[0.004863543,0.000614949,0.003782402,0.001109819,0.00039788,0.002144754,0.0003220748,0.4155662,0.02015703,0.06626409,0.4843703,0.0004069268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.01880674,0.008657285,0.2582105,0.002188583,0.001236636,0.001489225,0.09853584,0.582022,0.02885321],"genre_scores_gemma":[0.08144568,0.004573799,0.5756159,0.001198533,0.0003578301,0.0035412,0.2583914,0.063021,0.01185462],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06782793,"threshold_uncertainty_score":0.226907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01925297353223119,"score_gpt":0.2571173499731011,"score_spread":0.2378643764408699,"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."}}