{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":13,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":13,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"d94ed28ac976","filters":{"venue":"Current Bioinformatics"}},"results":[{"id":"W2900911708","doi":"10.2174/1574893614666181120095038","title":"Analysis of Single-Cell RNA-seq Data by Clustering Approaches","year":2018,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"Guangxi University; Natural Science Foundation of Guangxi Province; National Natural Science Foundation of China","keywords":"Cluster analysis; Computer science; Feature selection; Similarity (geometry); Population; Data mining; Selection (genetic algorithm); Feature (linguistics); Artificial intelligence; Machine learning","authors":[{"name":"Xiaoshu Zhu","is_ca":false},{"name":"Hong‐Dong Li","is_ca":false},{"name":"Lilu Guo","is_ca":false},{"name":"Fang‐Xiang Wu","is_ca":true},{"name":"Jianxin Wang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0949642181142041,"gpt":0.2732860420844115,"spread":0.1783218239702075,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003495611,0.001517735,0.001504393,0.005805812,0.0008349256,0.001928706,0.001956686,0.001106429,0.001265339],"category_scores_gemma":[0.007597535,0.0006333041,0.002396563,0.004576368,0.0009640032,0.00151439,0.001215008,0.001517404,0.00161619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001355728,"about_ca_system_score_gemma":0.001427216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002054995,"about_ca_topic_score_gemma":0.00295826,"domain_scores_codex":[0.997061,0.0007130788,0.0003221604,0.001002053,0.0007830921,0.0001187805],"domain_scores_gemma":[0.9944198,0.002590647,0.0006785868,0.0009289429,0.001233026,0.000149076],"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":[0.0005070317,0.0003600575,0.01766271,0.003092592,0.001624266,0.0005804489,0.0008742879,0.1812349,0.1930698,0.01734539,0.01098055,0.572668],"study_design_scores_gemma":[0.00003191287,0.0001280288,0.01384637,0.0001421409,0.000206933,0.0004672944,0.000335042,0.8526251,0.06419483,0.05494885,0.01286883,0.0002046094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008836335,0.0005045944,0.9874182,0.0001336591,0.00004426075,0.0001385034,0.0008775031,0.001686732,0.0003602162],"genre_scores_gemma":[0.05526268,0.0006883683,0.939773,0.0001049875,0.00007969567,0.000388561,0.002851891,0.0004208856,0.0004298615],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005805812,"threshold_uncertainty_score":0.0184868,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2940275179","doi":"10.2174/1574893614666190410155603","title":"Computational Approaches for Transcriptome Assembly Based on Sequencing Technologies","year":2019,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"Ministry of Education of the People's Republic of China; Hunan Provincial Science and Technology Department; National Natural Science Foundation of China","keywords":"Transcriptome; De novo transcriptome assembly; Computational biology; Sequence assembly; DNA sequencing; Computer science; Genome; Hybrid genome assembly; Biology; Reference genome; Gene; Genetics; Gene expression","authors":[{"name":"Yuwen Luo","is_ca":false},{"name":"Xingyu Liao","is_ca":false},{"name":"Fang‐Xiang Wu","is_ca":true},{"name":"Jianxin Wang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04642059490391494,"gpt":0.2598677564614635,"spread":0.2134471615575486,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002077697,0.001631898,0.001595712,0.001900737,0.001419082,0.002487661,0.002399562,0.001326132,0.004057535],"category_scores_gemma":[0.003668408,0.001375705,0.003088014,0.00256982,0.0007477707,0.002073019,0.001529048,0.002199434,0.001959301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00116639,"about_ca_system_score_gemma":0.0019138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003686431,"about_ca_topic_score_gemma":0.003813081,"domain_scores_codex":[0.9990487,0.0003790357,0.00008613371,0.0001978288,0.0002204249,0.00006796584],"domain_scores_gemma":[0.9984875,0.001004627,0.0001050021,0.0001573723,0.0001950643,0.00005037957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001500643,0.00009487529,0.001568697,0.001075694,0.000350194,0.0003904918,0.0002147159,0.8251711,0.01619797,0.05830598,0.004348845,0.09213141],"study_design_scores_gemma":[0.00001416457,0.00001686299,0.0002424567,0.00003792093,0.0000373849,0.00006224809,0.0000406854,0.96262,0.002846354,0.02759333,0.006463056,0.00002564474],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.003819222,0.0005240424,0.9917573,0.0001486848,0.00008977741,0.00006339151,0.0003902132,0.001438486,0.001768745],"genre_scores_gemma":[0.04881714,0.00173765,0.9437367,0.0001814017,0.0001007538,0.0006068288,0.002573078,0.0009023444,0.00134409],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004057535,"threshold_uncertainty_score":0.01357377,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2912168960","doi":"10.2174/1574893614666190204150918","title":"Gene Selection Method for Microarray Data Classification Using Particle Swarm Optimization and Neighborhood Rough Set","year":2019,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Science Foundation of Anhui Province; National Natural Science Foundation of China; Federation for the Humanities and Social Sciences","keywords":"Particle swarm optimization; Computer science; Classifier (UML); Data mining; Gene selection; Feature selection; Rough set; Artificial intelligence; Selection (genetic algorithm); Identification (biology); Microarray analysis techniques; Pattern recognition (psychology); Machine learning; Gene; Biology; Gene expression; Genetics","authors":[{"name":"Mingquan Ye","is_ca":false},{"name":"Weiwei Wang","is_ca":false},{"name":"Chuanwen Yao","is_ca":false},{"name":"Rong Fan","is_ca":false},{"name":"Peipei Wang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1258119524448318,"gpt":0.3493777500366137,"spread":0.2235657975917819,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00117494,0.0006210844,0.001579156,0.001891063,0.0005612837,0.0006712884,0.0009116203,0.0006884221,0.0009034701],"category_scores_gemma":[0.002485656,0.000283298,0.001295547,0.001156702,0.0003785791,0.0005526374,0.0003367922,0.0004812566,0.0002332308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007542709,"about_ca_system_score_gemma":0.0009630219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002901702,"about_ca_topic_score_gemma":0.001968981,"domain_scores_codex":[0.998915,0.0002598654,0.00008321369,0.0001904965,0.0004876237,0.00006383708],"domain_scores_gemma":[0.9993267,0.0003332604,0.00007588292,0.00003746702,0.0002040114,0.00002264365],"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":[0.0003480722,0.0002154375,0.004597228,0.0003390795,0.0002359487,0.0002869892,0.0002185226,0.4680502,0.02057649,0.006233044,0.004768674,0.4941303],"study_design_scores_gemma":[0.0000280869,0.00008025331,0.001039221,0.000008992338,0.00003891311,0.00006304666,0.00002171124,0.993558,0.00268991,0.001468763,0.0009902124,0.00001296791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02806097,0.0004763212,0.9697453,0.0002182934,0.0000620709,0.0001347229,0.00007138855,0.0004303105,0.0008006057],"genre_scores_gemma":[0.4442343,0.0005425135,0.552316,0.0001548367,0.000116864,0.0006803147,0.0004144732,0.00005113145,0.001489652],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002901702,"threshold_uncertainty_score":0.006213784,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3216512054","doi":"10.2174/1574893616666211119093100","title":"Machine Learning and Deep Learning Strategies in Drug Repositioning","year":2021,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Drug repositioning; Computer science; Drug; Drug discovery; Machine learning; Artificial intelligence; Preprocessor; Drug target; Data pre-processing; Data science; Medicine; Bioinformatics; Pharmacology","authors":[{"name":"Fei Wang","is_ca":true},{"name":"Yulian Ding","is_ca":true},{"name":"Xiujuan Lei","is_ca":false},{"name":"Bo Liao","is_ca":false},{"name":"Fang‐Xiang Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01732519701801303,"gpt":0.3018280753820009,"spread":0.2845028783639879,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001723246,0.0009742624,0.001277839,0.002126778,0.0004983378,0.001454101,0.001893078,0.001283642,0.002640804],"category_scores_gemma":[0.00488389,0.0004823777,0.000805142,0.002411746,0.001241426,0.003167463,0.001745968,0.002008873,0.0007374321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001500953,"about_ca_system_score_gemma":0.002092493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004308847,"about_ca_topic_score_gemma":0.004774427,"domain_scores_codex":[0.9991725,0.0002621105,0.00008739038,0.0001855417,0.0002041003,0.0000882825],"domain_scores_gemma":[0.9981843,0.001114033,0.0001827616,0.0001661767,0.0002619524,0.00009083257],"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":[0.0001280488,0.000276507,0.00271956,0.0008911113,0.0001709195,0.000164055,0.0001392809,0.3268434,0.002562508,0.07105265,0.005480763,0.5895712],"study_design_scores_gemma":[0.00001909052,0.00007509431,0.0003296435,0.0000806413,0.00003638284,0.00008911446,0.000032446,0.9346744,0.002104004,0.05765748,0.004883377,0.00001821235],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01729287,0.01069602,0.9615294,0.00248603,0.0001747339,0.0001304476,0.0002369842,0.0006539121,0.006799578],"genre_scores_gemma":[0.5718412,0.01373869,0.4047368,0.001570245,0.0003707618,0.0003608368,0.000759459,0.0001216773,0.006500333],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004308847,"threshold_uncertainty_score":0.01089019,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3125773464","doi":"10.2174/1574893616999210120181506","title":"MDAPlatform: A Component-based Platform for Constructing and Assessing miRNA-disease Association Prediction Methods","year":2021,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"National Natural Science Foundation of China-Zhejiang Joint Fund for the Integration of Industrialization and Informatization; Higher Education Discipline Innovation Project; Guizhou Science and Technology Department; Hunan Provincial Science and Technology Department; National Natural Science Foundation of China","keywords":"Construct (python library); Computer science; Disease; Association (psychology); Predictive modelling; Machine learning; Component (thermodynamics); Data mining; Artificial intelligence; Bioinformatics; Medicine; Biology; Pathology; Psychology","authors":[{"name":"Yayan Zhang","is_ca":false},{"name":"Guihua Duan","is_ca":false},{"name":"Cheng Yan","is_ca":false},{"name":"Haolun Yi","is_ca":false},{"name":"Fang‐Xiang Wu","is_ca":true},{"name":"Jianxin Wang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03489496998192523,"gpt":0.3378416190919664,"spread":0.3029466491100412,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003674752,0.002875696,0.001066316,0.002366235,0.0007939019,0.001948489,0.003575469,0.001312499,0.01708879],"category_scores_gemma":[0.01235909,0.001680431,0.003099595,0.001111316,0.0006262569,0.002019659,0.003632784,0.002213328,0.007603545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009867079,"about_ca_system_score_gemma":0.002741694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007014625,"about_ca_topic_score_gemma":0.006276721,"domain_scores_codex":[0.9986553,0.0003357968,0.0001789649,0.0003122186,0.000410441,0.0001072429],"domain_scores_gemma":[0.9952331,0.002691241,0.0003870237,0.0006850493,0.0007699876,0.0002336197],"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":[0.003801536,0.001175683,0.0244599,0.003285255,0.002246551,0.001796808,0.001307053,0.1741049,0.04957017,0.03472628,0.2403207,0.4632051],"study_design_scores_gemma":[0.0006447438,0.0003278814,0.004155434,0.0002358166,0.0003690328,0.0006056147,0.0001011489,0.8279395,0.03208269,0.0307567,0.1024808,0.000300583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005437067,0.0001912217,0.8097002,0.0002721262,0.0001174295,0.0005174645,0.003825692,0.1783927,0.001546086],"genre_scores_gemma":[0.07409071,0.0005901093,0.8785237,0.0006644677,0.00006631545,0.002546326,0.01941501,0.02033965,0.003763668],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01708879,"threshold_uncertainty_score":0.05716771,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4353070816","doi":"10.2174/1574893618666230320144630","title":"piRSNP: A Database of piRNA- related SNPs and their Effects on CancerrelatedpiRNA Functions","year":2023,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"Natural Science Basic Research Program of Shaanxi Province; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Piwi-interacting RNA; Single-nucleotide polymorphism; Computational biology; Biology; Genetics; Genome; Transposable element; Bioinformatics; Gene; Genotype","authors":[{"name":"Yajun Liu","is_ca":false},{"name":"Aimin Li","is_ca":false},{"name":"Yingda Zhu","is_ca":false},{"name":"Xinchao Pang","is_ca":false},{"name":"Xinhong Hei","is_ca":false},{"name":"Guo Xie","is_ca":false},{"name":"Fang‐Xiang Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02355227866720897,"gpt":0.2344430041566112,"spread":0.2108907254894022,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001116666,0.001337205,0.001665924,0.005154794,0.0006232674,0.001181488,0.001286799,0.001078823,0.01610094],"category_scores_gemma":[0.004784509,0.0006024526,0.001419755,0.00529461,0.0002464268,0.0008906518,0.001631721,0.0009372217,0.00796992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003795021,"about_ca_system_score_gemma":0.001491887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00186302,"about_ca_topic_score_gemma":0.003221988,"domain_scores_codex":[0.9987544,0.0001557642,0.0002341422,0.0004951971,0.0002700584,0.00009048154],"domain_scores_gemma":[0.9976137,0.0009125537,0.0006409535,0.0003466675,0.0002495065,0.0002366233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006871034,0.0007747776,0.1875052,0.02030559,0.003238201,0.005380007,0.000948235,0.008724529,0.0900659,0.005269387,0.3242557,0.3466615],"study_design_scores_gemma":[0.00104961,0.0009843457,0.2707224,0.001220624,0.002388314,0.006556928,0.0003642514,0.01554949,0.04399266,0.01047998,0.6462887,0.0004027875],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.04834862,0.003820495,0.01842853,0.0002376989,0.0001372841,0.0002448754,0.9131185,0.01232172,0.003342212],"genre_scores_gemma":[0.04623896,0.001712797,0.02784264,0.0002193102,0.00007157703,0.0006005192,0.9200084,0.001263262,0.002042614],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01610094,"threshold_uncertainty_score":0.05386305,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401263354","doi":"10.2174/0115748936308564240712053215","title":"Recent Progress of Deep Learning Methods for RBP Binding Sites Prediction on circRNA","year":2024,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"Middle-aged and Young Teachers' Basic Ability Promotion Project of Guangxi; Shaanxi Normal University; Guilin University of Technology; Guangxi Key Laboratory of Embedded Technology and Intelligent System; National Natural Science Foundation of China","keywords":"Deep learning; Artificial intelligence; Computer science; Computational biology; Machine learning; Biological data; Process (computing); Bioinformatics; Biology","authors":[{"name":"Zhengfeng Wang","is_ca":false},{"name":"Xiujuan Lei","is_ca":false},{"name":"Yuchen Zhang","is_ca":false},{"name":"Fang‐Xiang Wu","is_ca":true},{"name":"Yi Pan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03634858733627625,"gpt":0.3519020612183485,"spread":0.3155534738820723,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001166859,0.001348199,0.001132651,0.001075472,0.0003251455,0.001039489,0.001511628,0.001056243,0.001805218],"category_scores_gemma":[0.001969108,0.0005444874,0.001004137,0.001254615,0.0005301114,0.001512243,0.0009237402,0.002240652,0.0006639703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009037456,"about_ca_system_score_gemma":0.001293585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007347517,"about_ca_topic_score_gemma":0.005623366,"domain_scores_codex":[0.9995273,0.00009210051,0.00004187043,0.0001735952,0.0001140273,0.00005114939],"domain_scores_gemma":[0.9992788,0.0003731397,0.00006499194,0.00005419002,0.0001850666,0.00004372425],"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":[0.0001892812,0.0001899039,0.005489444,0.0007479963,0.0002420197,0.0001226914,0.0001144521,0.2387868,0.0108579,0.01536182,0.01084735,0.7170504],"study_design_scores_gemma":[0.00001261725,0.00003074986,0.0006134982,0.00004795382,0.00004684512,0.00002916629,0.00001672396,0.9834178,0.002708926,0.008349597,0.004710857,0.00001523876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.02197797,0.02236054,0.9496953,0.001197301,0.0002239646,0.00005028567,0.000451468,0.001413989,0.002629136],"genre_scores_gemma":[0.3988682,0.05509124,0.5216112,0.002479987,0.0009340571,0.0004074123,0.005600645,0.0006489406,0.01435852],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.007347517,"threshold_uncertainty_score":0.01460952,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2980421046","doi":"10.2174/1574893614666191017100657","title":"Finding Community of Brain Networks Based on Neighbor Index and DPSO with Dynamic Crossover","year":2019,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"Natural Science Foundation of Guangxi Province; National Natural Science Foundation of China","keywords":"Crossover; Computer science; Particle swarm optimization; Modularity (biology); Convergence (economics); Artificial neural network; Coding (social sciences); Artificial intelligence; Machine learning; Mathematics; Statistics","authors":[{"name":"Jie Zhang","is_ca":false},{"name":"Junhong Feng","is_ca":false},{"name":"Fang‐Xiang Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01075751317308179,"gpt":0.2708412936275963,"spread":0.2600837804545145,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001092976,0.0008010768,0.001066685,0.001825041,0.000908124,0.0008719014,0.001554337,0.001051841,0.001383563],"category_scores_gemma":[0.004293809,0.0003829832,0.0009892394,0.001178458,0.0007524542,0.001259102,0.001417227,0.0007647663,0.0001200311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001117852,"about_ca_system_score_gemma":0.001193856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005317486,"about_ca_topic_score_gemma":0.003744335,"domain_scores_codex":[0.999446,0.0001535761,0.00003369601,0.0001440537,0.000146075,0.0000766073],"domain_scores_gemma":[0.9985735,0.0008026173,0.0001689747,0.0001073604,0.0002285162,0.0001189884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001158725,0.0001331739,0.004253206,0.0001515778,0.00008996475,0.0001732081,0.0002284471,0.85798,0.004971046,0.01832179,0.001398567,0.112183],"study_design_scores_gemma":[0.0000214753,0.00004309406,0.0002618823,0.000006789103,0.00001384467,0.00004027837,0.00002656199,0.9943404,0.00056149,0.004351898,0.0003244547,0.000007656071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08311293,0.0003562089,0.913211,0.000261992,0.00005586116,0.0002006503,0.00008961595,0.0002153635,0.00249634],"genre_scores_gemma":[0.611867,0.0003066438,0.3843883,0.0001126156,0.00004654446,0.0004573836,0.0002818539,0.00006443684,0.002475323],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005317486,"threshold_uncertainty_score":0.01057303,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391485226","doi":"10.2174/0115748936289420240117100823","title":"P4PC: A Portal for Bioinformatics Resources of piRNAs and circRNAs","year":2024,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"Natural Science Basic Research Program of Shaanxi Province; National Natural Science Foundation of China","keywords":"Computer science; Computational biology; Bioinformatics; Biology","authors":[{"name":"Yajun Liu","is_ca":false},{"name":"Ru Li","is_ca":false},{"name":"Yulian Ding","is_ca":false},{"name":"Xin Hong Hei","is_ca":true},{"name":"Fang‐Xiang Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02635354725007235,"gpt":0.2522798527518311,"spread":0.2259263055017588,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002582802,0.002475833,0.001900435,0.01260965,0.001265294,0.003785452,0.002604414,0.001592951,0.06762287],"category_scores_gemma":[0.01123542,0.001118621,0.001493966,0.01723054,0.0004330782,0.00446344,0.004980878,0.00179765,0.06732535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008499399,"about_ca_system_score_gemma":0.004090138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002731034,"about_ca_topic_score_gemma":0.0026683,"domain_scores_codex":[0.9985257,0.0002651754,0.0002993439,0.000342932,0.0003843212,0.0001825343],"domain_scores_gemma":[0.9942862,0.00198095,0.0006322786,0.0009304167,0.00105153,0.001118639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001382982,0.0002134226,0.005209646,0.0107668,0.0003065908,0.0008988284,0.0005642831,0.00090038,0.008438814,0.009535399,0.8245543,0.1372286],"study_design_scores_gemma":[0.000283695,0.00008665065,0.005132894,0.0007172843,0.0001460388,0.000629553,0.0002777487,0.003711543,0.006537906,0.009384975,0.9729508,0.0001408382],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.005519356,0.002956218,0.06217373,0.001224563,0.0003851043,0.0007845353,0.7200274,0.1807528,0.0261762],"genre_scores_gemma":[0.01271197,0.001999204,0.08051205,0.0005034845,0.0001312606,0.0008493825,0.8832574,0.0143172,0.005718071],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.06762287,"threshold_uncertainty_score":0.226221,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3169631076","doi":"10.2174/1574893616666210531101550","title":"Identification of Risk Molecular Subtype of Colon Cancer with Lymphovascular Invasion","year":2021,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Colorectal Cancer Treatments and Studies","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"National Natural Science Foundation of China","keywords":"Colorectal cancer; Lymphovascular invasion; Micrometastasis; Oncology; Metastasis; Medicine; Internal medicine; Stage (stratigraphy); Adjuvant chemotherapy; microRNA; Cancer; Biology; Gene; Genetics","authors":[{"name":"Qing Jin","is_ca":false},{"name":"Binhua Liang","is_ca":true},{"name":"Xiujie Chen","is_ca":false},{"name":"Huiwen Liu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01745944249339284,"gpt":0.2873822911494141,"spread":0.2699228486560213,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002217196,0.0002298168,0.0002784384,0.0009000371,0.0002355588,0.0003214589,0.0001832276,0.0002089313,0.0008124688],"category_scores_gemma":[0.000814457,0.00008788215,0.0004116002,0.0006585527,0.0001165618,0.0001324094,0.0002477676,0.0002209807,0.0001844434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002457694,"about_ca_system_score_gemma":0.0003270931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001709164,"about_ca_topic_score_gemma":0.003182809,"domain_scores_codex":[0.9998488,0.00002354786,0.00001401956,0.00004941304,0.00003352019,0.00003065499],"domain_scores_gemma":[0.9995528,0.00008491162,0.0001990133,0.0000412205,0.00005645867,0.00006556914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002916419,0.00002969515,0.9681158,0.00006490082,0.00007944576,0.000249106,0.00004677043,0.0007876604,0.02019287,0.0000747591,0.0001825999,0.009884889],"study_design_scores_gemma":[0.00001454785,0.0001452894,0.9831038,0.00001535426,0.0001629661,0.001529209,0.0001279402,0.008737944,0.005127478,0.0003158666,0.0007112504,0.000008416034],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982557,0.0002109026,0.0009002551,0.00001869281,0.000002134528,0.00001468066,0.0003648684,0.00001309617,0.0002196195],"genre_scores_gemma":[0.9972926,0.00009074044,0.00153445,0.000007763295,0.000003175085,0.00001394946,0.0009415069,0.000003817765,0.0001119542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001709164,"threshold_uncertainty_score":0.003398418,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225163880","doi":"10.2174/1574893617666220428140637","title":"Deep Learning for Aging Research with DNA Methylation","year":2022,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"","keywords":"DNA methylation; Computational biology; Psychology; Artificial intelligence; Biology; Computer science; Genetics; Gene; Gene expression","authors":[{"name":"Hongyu Guo","is_ca":true},{"name":"Fang‐Xiang Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06024735989320856,"gpt":0.3541544203013262,"spread":0.2939070604081176,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001253984,0.0008877056,0.001073908,0.000843064,0.0003301197,0.0008490398,0.001208657,0.00102006,0.003192893],"category_scores_gemma":[0.003448681,0.0003698039,0.001007959,0.0009146464,0.000434646,0.001189687,0.001315334,0.002192943,0.001259159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008155296,"about_ca_system_score_gemma":0.001459442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005618528,"about_ca_topic_score_gemma":0.008162558,"domain_scores_codex":[0.9996955,0.00009383247,0.00001573095,0.00009779335,0.00005628722,0.00004089647],"domain_scores_gemma":[0.9991282,0.0004499992,0.00007491706,0.00013267,0.0001249122,0.0000893501],"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":[0.0005318241,0.0003039109,0.01351971,0.0007656015,0.0008847985,0.0001559463,0.00008646611,0.1008213,0.01268081,0.02594158,0.04133028,0.8029778],"study_design_scores_gemma":[0.00004450897,0.0001153469,0.003032515,0.0001263839,0.0002275917,0.00009185878,0.0000295451,0.8297342,0.00852525,0.1388703,0.01916854,0.000033986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04363588,0.01749899,0.9151542,0.006650313,0.0005922763,0.000090105,0.006446587,0.006106623,0.003824973],"genre_scores_gemma":[0.5971417,0.01151906,0.3585477,0.003457555,0.0010007,0.0003378313,0.01313479,0.0005475443,0.01431303],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005618528,"threshold_uncertainty_score":0.0111717,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4404047929","doi":"10.2174/0115748936312589240910071837","title":"Robust Somatic Copy Number Estimation using Coarse-to-fine Segmentation","year":2024,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"AbCellera (Canada); Canada's Michael Smith Genome Sciences Centre; University of British Columbia; BC Cancer Agency","funders":"Canadian Institutes of Health Research; Genome British Columbia; Canada Foundation for Innovation","keywords":"Somatic cell; Estimation; Segmentation; Computer science; Artificial intelligence; Pattern recognition (psychology); Biology; Genetics; Gene; Engineering","authors":[{"name":"Luka Culibrk","is_ca":true},{"name":"Jasleen Grewal","is_ca":true},{"name":"Erin Pleasance","is_ca":true},{"name":"Laura Williamson","is_ca":true},{"name":"Karen Mungall","is_ca":true},{"name":"Janessa Laskin","is_ca":true},{"name":"Marco A. Marra","is_ca":true},{"name":"Steven J.M. Jones","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0595775188455197,"gpt":0.329495560016003,"spread":0.2699180411704833,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009924372,0.0007280938,0.0008337403,0.003019805,0.0003864985,0.001006557,0.0009720942,0.0008435843,0.002171179],"category_scores_gemma":[0.005254687,0.0003496082,0.0008258857,0.001507738,0.0005245711,0.0006058819,0.0009658429,0.0006554386,0.0009512478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006661085,"about_ca_system_score_gemma":0.0007942538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005147976,"about_ca_topic_score_gemma":0.006106901,"domain_scores_codex":[0.9993415,0.0001004866,0.00004575213,0.0002673836,0.0001994835,0.00004542185],"domain_scores_gemma":[0.9983956,0.000919412,0.0002396859,0.0001931914,0.0001965126,0.00005555922],"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":[0.0007550339,0.0001206782,0.03214143,0.0003106839,0.0003389119,0.0004657462,0.0002832264,0.1956107,0.149958,0.00425518,0.007144077,0.6086164],"study_design_scores_gemma":[0.00004198275,0.00008156977,0.01582312,0.0000221706,0.00005375275,0.0006496697,0.00004735474,0.9273113,0.04264933,0.009749616,0.003513695,0.00005643328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08998805,0.0005400336,0.896908,0.0001687074,0.00003476431,0.0001099179,0.001740726,0.00929084,0.001218856],"genre_scores_gemma":[0.3843283,0.0002363935,0.6068275,0.0001725156,0.00005885456,0.0002077626,0.005624793,0.0007340634,0.001809695],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005147976,"threshold_uncertainty_score":0.01023602,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4386785953","doi":"10.2174/1574893618666230913110025","title":"Network Propagation-based Identification of Oligometastatic Biomarkersin Metastatic Colorectal Cancer","year":2023,"lang":"en","type":"article","venue":"Current Bioinformatics","topic":"Ferroptosis and cancer prognosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Medicine; Colorectal cancer; Oncology; Internal medicine; Disease; Biomarker; Cancer","authors":[{"name":"Qing Jin","is_ca":false},{"name":"Ke‐Xin Yu","is_ca":false},{"name":"Xianze Zhang","is_ca":false},{"name":"Diwei Huo","is_ca":false},{"name":"Denan Zhang","is_ca":false},{"name":"Lei Liu","is_ca":false},{"name":"Hongbo Xie","is_ca":false},{"name":"Binhua Liang","is_ca":true},{"name":"Xiujie Chen","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04574016093754182,"gpt":0.3270200395527983,"spread":0.2812798786152565,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006762517,0.0007792914,0.0004837663,0.001775787,0.0003137735,0.0006633113,0.0003936893,0.0003602264,0.0009027218],"category_scores_gemma":[0.001981009,0.0002058458,0.0006817579,0.0008438536,0.0002588232,0.0006220698,0.0004968657,0.0004471735,0.0001615948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007311424,"about_ca_system_score_gemma":0.0005428451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003961532,"about_ca_topic_score_gemma":0.004465104,"domain_scores_codex":[0.999737,0.00007274086,0.00001650073,0.00008753529,0.0000450691,0.00004126054],"domain_scores_gemma":[0.9991074,0.0004106303,0.0002491783,0.00003732893,0.0001405417,0.00005487661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00136955,0.0004442191,0.3606945,0.0005027771,0.0008109273,0.0005359808,0.0003547678,0.4107298,0.0352702,0.00344986,0.002978668,0.1828587],"study_design_scores_gemma":[0.00001718929,0.0001041586,0.03551285,0.00001671322,0.0001064667,0.0001004025,0.00004560413,0.9599129,0.001634951,0.002045028,0.0004861329,0.00001766573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7905746,0.00119332,0.2036814,0.000398046,0.00003989119,0.0001806224,0.002002713,0.0004280384,0.001501464],"genre_scores_gemma":[0.9684319,0.0003214123,0.02809353,0.00004170527,0.00003321475,0.000131218,0.002221192,0.00002176055,0.0007040097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003961532,"threshold_uncertainty_score":0.007876933,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}