{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":15,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":15,"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":"9b0d1f4fa117","filters":{"venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)"}},"results":[{"id":"W4206758809","doi":"10.1109/bibm52615.2021.9669735","title":"Heart Rate Monitoring Using PPG With Smartphone Camera","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Photoplethysmogram; Artificial intelligence; Computer vision; Computer science; SIGNAL (programming language); Pixel; Convolutional neural network; Noise (video); Filter (signal processing)","authors":[{"name":"Amtul Haq Ayesha","is_ca":true},{"name":"Donghao Qiao","is_ca":true},{"name":"Farhana Zulkernine","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04810541512609177,"gpt":0.2791273793029019,"spread":0.2310219641768101,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001651676,0.0004897607,0.0004924231,0.000663951,0.0001039084,0.0003504013,0.0002466537,0.000419817,0.002909021],"category_scores_gemma":[0.0006573864,0.000126262,0.0001943287,0.0004437949,0.0000645275,0.0002957055,0.0002686349,0.0001940022,0.001025987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001055105,"about_ca_system_score_gemma":0.0001284926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001113472,"about_ca_topic_score_gemma":0.001488262,"domain_scores_codex":[0.9996504,0.00005416934,0.0000210479,0.00009929914,0.0001549908,0.0000200392],"domain_scores_gemma":[0.999721,0.00005447624,0.00003846236,0.00003064484,0.0001386496,0.00001675843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008980201,0.0001878508,0.02456968,0.001233261,0.0001755035,0.0009195541,0.0001802974,0.003604339,0.4294358,0.0005443757,0.01049956,0.5277517],"study_design_scores_gemma":[0.00035345,0.003084372,0.3793057,0.0003207417,0.0004487663,0.008599832,0.0002415398,0.2418112,0.3330512,0.001065665,0.03147175,0.0002457988],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4868025,0.00469758,0.4684525,0.0004381949,0.000575713,0.0007602724,0.006173611,0.01052549,0.02157405],"genre_scores_gemma":[0.8917921,0.002050906,0.09531277,0.0003550348,0.0002783151,0.0003457325,0.001697128,0.0001245693,0.008043361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002909021,"threshold_uncertainty_score":0.00973171,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4206187231","doi":"10.1109/bibm52615.2021.9669849","title":"A Graph Attention Neural Network for Diagnosing ASD with fMRI Data","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":15,"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":"Science and Engineering Research Council","keywords":"Functional magnetic resonance imaging; Computer science; Autism spectrum disorder; Neuroimaging; Graph; Artificial intelligence; Graph theory; Resting state fMRI; Machine learning; Power graph analysis; Artificial neural network; Pattern recognition (psychology); Autism; Neuroscience; Psychology; Theoretical computer science; Psychiatry","authors":[{"name":"Wutao Yin","is_ca":true},{"name":"Longhai Li","is_ca":true},{"name":"Fang‐Xiang Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1355440082927074,"gpt":0.3293649262571772,"spread":0.1938209179644699,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007487854,0.0008795467,0.0004215494,0.001848065,0.0003990012,0.0004322726,0.0007004277,0.001036576,0.000899099],"category_scores_gemma":[0.002994888,0.0001897362,0.0005471717,0.000695538,0.0003677115,0.0006719884,0.0005860684,0.0006465967,0.0001363879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009449499,"about_ca_system_score_gemma":0.0005970877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01405649,"about_ca_topic_score_gemma":0.01676465,"domain_scores_codex":[0.9995924,0.0001301246,0.0000230243,0.0001365407,0.00006607033,0.00005191417],"domain_scores_gemma":[0.9992942,0.0003761128,0.00009601715,0.00003871386,0.000145731,0.00004924674],"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":[0.0008046,0.0003827633,0.04218785,0.0001653955,0.0002739921,0.001452531,0.0002187333,0.5493832,0.01896909,0.006407827,0.005857611,0.3738965],"study_design_scores_gemma":[0.000006044683,0.00004520513,0.002712031,0.000006485617,0.00002333561,0.00009079282,0.00002148957,0.9934103,0.001247034,0.002149438,0.0002807837,0.000007050955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3912351,0.0008901802,0.599869,0.00133746,0.0001018691,0.0002574275,0.001178629,0.001989953,0.003140495],"genre_scores_gemma":[0.934786,0.0002049544,0.0628196,0.0001450484,0.00003487364,0.00009650728,0.0008410702,0.00002875236,0.001043094],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01405649,"threshold_uncertainty_score":0.02794933,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4206792129","doi":"10.1109/bibm52615.2021.9669569","title":"Health Analytics on Big COVID-19 Data","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":10,"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":"Autoencoder; Computer science; Machine learning; Artificial intelligence; Identification (biology); Analytics; Predictive analytics; Big data; Test data; Coronavirus disease 2019 (COVID-19); Data mining; Data analysis; Predictive modelling; Deep learning; Data science; Disease; Infectious disease (medical specialty); Medicine","authors":[{"name":"Nguyen Tran","is_ca":true},{"name":"Carson K. Leung","is_ca":true},{"name":"Daryl L. X. Fung","is_ca":true},{"name":"Thanh Huy Daniel","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.244183654479877,"gpt":0.4297195157071462,"spread":0.1855358612272692,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001878253,0.0008804024,0.0006117293,0.00207167,0.0004966709,0.002035271,0.0007881904,0.0009340023,0.01083732],"category_scores_gemma":[0.006936654,0.0002682378,0.0006658264,0.002250528,0.0003613767,0.001605006,0.002079567,0.001257023,0.004392286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007485028,"about_ca_system_score_gemma":0.0007227627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005097535,"about_ca_topic_score_gemma":0.005664203,"domain_scores_codex":[0.9987875,0.0002987435,0.000126016,0.0002836034,0.0004151367,0.00008906199],"domain_scores_gemma":[0.9958609,0.001879209,0.0002477883,0.0007785461,0.0009359426,0.0002976773],"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":[0.0008931381,0.0002248152,0.03568192,0.001120482,0.0002741032,0.001305433,0.0002811986,0.03392049,0.007243352,0.007471801,0.4075314,0.5040519],"study_design_scores_gemma":[0.0001940951,0.0004740193,0.04920725,0.0005978745,0.0001709874,0.001103391,0.0007470937,0.5362813,0.01499018,0.03549611,0.360512,0.0002257445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1611286,0.01399152,0.3744345,0.04806057,0.009970713,0.002152551,0.2918547,0.05335003,0.04505687],"genre_scores_gemma":[0.4584562,0.006457957,0.2286142,0.004665751,0.003143141,0.0006387002,0.283613,0.001296614,0.01311443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01083732,"threshold_uncertainty_score":0.03625441,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4206597964","doi":"10.1109/bibm52615.2021.9669613","title":"Temporal Graph Representation Learning for Autism spectrum disorder Brain Networks","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Computer science; Graph embedding; Dynamic functional connectivity; Graph; Autism spectrum disorder; Artificial intelligence; Embedding; Discriminative model; Autism; Functional magnetic resonance imaging; Neuroimaging; Cluster analysis; Recurrent neural network; Pattern recognition (psychology); Artificial neural network; Theoretical computer science; Neuroscience; Psychology","authors":[{"name":"Peng Cao","is_ca":false},{"name":"Guangqi Wen","is_ca":false},{"name":"Lanting Li","is_ca":false},{"name":"Xiaoli Liu","is_ca":false},{"name":"Jinzhu Yang","is_ca":false},{"name":"Osmar R. Zai͏̈ane","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06542714607211436,"gpt":0.3198074140674891,"spread":0.2543802679953748,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005210107,0.001137372,0.0006614124,0.00113734,0.0003875812,0.0006220286,0.001178271,0.001124096,0.001746252],"category_scores_gemma":[0.0025178,0.0003475512,0.0008975621,0.001074064,0.0004486418,0.001646846,0.0009439907,0.001591175,0.0005416322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009587561,"about_ca_system_score_gemma":0.0007170578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007121894,"about_ca_topic_score_gemma":0.01164215,"domain_scores_codex":[0.9996808,0.00007452611,0.00001469275,0.000142742,0.00004551816,0.00004178152],"domain_scores_gemma":[0.9994172,0.0002664936,0.0001014905,0.00007864439,0.00009525996,0.00004085982],"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":[0.0001675024,0.000189222,0.002660354,0.0001465401,0.0001348288,0.0002457699,0.0001609602,0.6381413,0.009256709,0.01448862,0.007753734,0.3266544],"study_design_scores_gemma":[0.000003237344,0.00001506138,0.0002121028,0.000004371172,0.000008280302,0.00002157769,0.000009347121,0.9904778,0.0005128562,0.008412844,0.0003184061,0.000004162577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04019785,0.0007198289,0.955231,0.0005158182,0.00005493449,0.00005597216,0.0005413459,0.001527518,0.001155808],"genre_scores_gemma":[0.793199,0.0009873022,0.1970245,0.0003837598,0.0001365058,0.0002338694,0.003227809,0.0002451543,0.00456197],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007121894,"threshold_uncertainty_score":0.01416087,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4205272967","doi":"10.1109/bibm52615.2021.9669606","title":"Improving human essential protein prediction using only protein sequences via ensemble learning","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Machine Learning in Bioinformatics","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","keywords":"Computer science; Ensemble learning; Machine learning; Boosting (machine learning); Artificial intelligence; Centrality; Data mining; Mathematics","authors":[{"name":"Min Zeng","is_ca":false},{"name":"Nian Wang","is_ca":false},{"name":"Yifan Wu","is_ca":false},{"name":"Yiming Li","is_ca":false},{"name":"Fang‐Xiang Wu","is_ca":true},{"name":"Min Li","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02349242915637555,"gpt":0.2962368771833754,"spread":0.2727444480269999,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001058596,0.0006952633,0.0008924353,0.001587175,0.0003912842,0.0004165843,0.0004808157,0.0006063103,0.0007520871],"category_scores_gemma":[0.002146687,0.0002669246,0.0007389625,0.0009782615,0.0001652015,0.001286909,0.0006256,0.0007104113,0.0005240364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000412497,"about_ca_system_score_gemma":0.0005699149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003626262,"about_ca_topic_score_gemma":0.005466192,"domain_scores_codex":[0.9995117,0.0001157271,0.00002486752,0.0001566364,0.0001337355,0.00005735772],"domain_scores_gemma":[0.9991067,0.0004012938,0.00008187087,0.000116066,0.0002218848,0.00007218881],"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":[0.001096012,0.0005307174,0.05679134,0.0002961164,0.0004585379,0.0004799116,0.0001170142,0.410802,0.04555601,0.004180097,0.0199701,0.4597222],"study_design_scores_gemma":[0.00001127304,0.00003429015,0.001868374,0.000006725769,0.0000236392,0.00005505295,0.000008125664,0.9922414,0.003188882,0.001926323,0.0006289946,0.000006882226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4569233,0.002870041,0.5308772,0.0003951671,0.0001658425,0.0000694796,0.001972923,0.003493448,0.003232472],"genre_scores_gemma":[0.8865895,0.0008416556,0.1055597,0.0001715793,0.00007674379,0.00004758042,0.00514183,0.0001260856,0.001445291],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003626262,"threshold_uncertainty_score":0.007210314,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4206241450","doi":"10.1109/bibm52615.2021.9669670","title":"Combining a genetic algorithm and ensemble method to improve the classification of viruses","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Support vector machine; Computer science; Feature (linguistics); Kernel (algebra); Feature vector; Identification (biology); Artificial intelligence; Genome; Source code; Algorithm; Pattern recognition (psychology); Machine learning; Mathematics; Biology; Genetics; Gene","authors":[{"name":"Dylan Lebatteux","is_ca":true},{"name":"Abdoulaye Baniré Diallo","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04819413150641396,"gpt":0.3239262744786498,"spread":0.2757321429722359,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001645045,0.000941119,0.001398242,0.001931815,0.000587295,0.0009883515,0.001188371,0.001193769,0.0007981064],"category_scores_gemma":[0.003882934,0.0003535078,0.00112299,0.001278303,0.0004015249,0.001526208,0.0008025901,0.001337641,0.0005109176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000584826,"about_ca_system_score_gemma":0.0007722986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004538858,"about_ca_topic_score_gemma":0.005355737,"domain_scores_codex":[0.9991363,0.0002029285,0.00005759166,0.0002343743,0.0002830606,0.00008564291],"domain_scores_gemma":[0.9982411,0.0006739662,0.0001143061,0.0002608806,0.0006525166,0.00005723467],"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":[0.0001037892,0.0001437006,0.005342216,0.00005143973,0.0002097877,0.00007278675,0.0000983246,0.3169295,0.01160527,0.003689973,0.002138303,0.6596149],"study_design_scores_gemma":[0.000004288098,0.00003780715,0.0005332484,0.000005387721,0.00002078389,0.00004050618,0.00001106906,0.994404,0.00222826,0.001946209,0.0007585416,0.00001002378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03371462,0.0003057964,0.9632651,0.0001451844,0.0001017085,0.00003993325,0.0000501081,0.001327465,0.0010502],"genre_scores_gemma":[0.3953796,0.0003272905,0.6009117,0.0002041493,0.0001143912,0.000105487,0.0003634816,0.0002076492,0.00238618],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004538858,"threshold_uncertainty_score":0.009024918,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4206257130","doi":"10.1109/bibm52615.2021.9669598","title":"Dilated Convolutional Neural Network for Tongue Segmentation in Real-time Ultrasound Video Data","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Traditional Chinese Medicine Studies","field":"Medicine","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 Ottawa; National Research Council Canada","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Deep learning; Segmentation; Tongue; Computer vision; Artificial neural network; Pattern recognition (psychology); Image segmentation; Speech recognition","authors":[{"name":"M. Hamed Mozaffari","is_ca":true},{"name":"Won‐Sook Lee","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09115312497561046,"gpt":0.3492871065243836,"spread":0.2581339815487731,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005846273,0.0005621591,0.000407389,0.0007286883,0.0002402712,0.0004391454,0.0005947114,0.0007245312,0.001402946],"category_scores_gemma":[0.001383583,0.0002367395,0.0004278801,0.0007797758,0.0002396969,0.0005316087,0.0004709472,0.0007124447,0.0005746095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007761754,"about_ca_system_score_gemma":0.0008486374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0149369,"about_ca_topic_score_gemma":0.0147878,"domain_scores_codex":[0.9997802,0.00003115226,0.00001553225,0.00008016047,0.00005300968,0.00003989382],"domain_scores_gemma":[0.9997362,0.00008676039,0.0000365244,0.00003597584,0.00008946862,0.00001501491],"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":[0.0006699163,0.0001828774,0.006158711,0.0001822575,0.0001022218,0.0004118724,0.0001350068,0.3560188,0.05134222,0.002911441,0.005023857,0.5768608],"study_design_scores_gemma":[0.000003753384,0.00002450442,0.001358761,0.000007670103,0.000009184534,0.00003537182,0.00001034285,0.9916112,0.005970578,0.0004356694,0.0005264214,0.000006598209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2495704,0.002748279,0.7380503,0.0006762974,0.0002074866,0.00009500995,0.0012013,0.003346579,0.004104184],"genre_scores_gemma":[0.8740352,0.0007740306,0.1181563,0.0001405166,0.00004821157,0.00007599834,0.001474969,0.00008171413,0.005213083],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0149369,"threshold_uncertainty_score":0.02969992,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4205106657","doi":"10.1109/bibm52615.2021.9669377","title":"Prediction of hot spots in protein-protein interaction by Nine-Pipeline & Ensemble Learning strategy","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China","keywords":"Ensemble learning; Pipeline (software); AdaBoost; Support vector machine; Artificial intelligence; Random forest; Computer science; Naive Bayes classifier; Machine learning; Stacking; Perceptron; Pattern recognition (psychology); Multilayer perceptron; Artificial neural network; Data mining; Chemistry","authors":[{"name":"Jing Hu","is_ca":false},{"name":"Zonghao Li","is_ca":false},{"name":"Xiaolong Zhang","is_ca":false},{"name":"Nansheng Chen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08019003938843593,"gpt":0.3302280504378589,"spread":0.250038011049423,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001309575,0.0009096698,0.001207235,0.001372457,0.0007253108,0.0006059937,0.001328973,0.000733569,0.001298646],"category_scores_gemma":[0.001452841,0.0004859183,0.001155694,0.0008461839,0.0003351178,0.001666713,0.001029893,0.0007126579,0.0003714164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005248495,"about_ca_system_score_gemma":0.0009669642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004098339,"about_ca_topic_score_gemma":0.003980069,"domain_scores_codex":[0.9993493,0.0001160883,0.00004321698,0.0001810551,0.0002104857,0.00009975799],"domain_scores_gemma":[0.9994878,0.0001496531,0.00005688536,0.00006985531,0.0001810803,0.00005482718],"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":[0.000470447,0.0005196383,0.03166128,0.0001616669,0.0003760754,0.0004122384,0.0001392248,0.4090688,0.02895057,0.004586658,0.004813418,0.5188399],"study_design_scores_gemma":[0.00001016855,0.00004870426,0.001359944,0.000002630897,0.00002726866,0.00004984917,0.000008875373,0.9933302,0.003714299,0.001125176,0.0003133945,0.000009570948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1213714,0.0003238191,0.8745307,0.0001571893,0.0000426387,0.00009771466,0.000157954,0.001959332,0.001359234],"genre_scores_gemma":[0.7248539,0.0002460491,0.2711022,0.0001409087,0.00003201645,0.0001560241,0.0007724823,0.0001180687,0.002578224],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004098339,"threshold_uncertainty_score":0.008148968,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4205458099","doi":"10.1109/bibm52615.2021.9669521","title":"End-to-end chromosomal compartment prediction from reference genomes","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","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 Guelph","funders":"","keywords":"End-to-end principle; Computer science; Convolutional neural network; Deep learning; Artificial intelligence; Compartment (ship); Artificial neural network; Software; Machine learning","authors":[{"name":"Matthew Kirchhof","is_ca":true},{"name":"Christopher J. F. Cameron","is_ca":false},{"name":"Stefan C. Kremer","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03088058659516399,"gpt":0.2744242957918245,"spread":0.2435437091966605,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005816147,0.001013705,0.0005437713,0.001559842,0.0003275502,0.0007855934,0.001004906,0.00083917,0.00377525],"category_scores_gemma":[0.003122348,0.000334466,0.000649684,0.001049532,0.000200064,0.000884295,0.0009994131,0.0008811699,0.003649344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004944013,"about_ca_system_score_gemma":0.0006235149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004875212,"about_ca_topic_score_gemma":0.009526566,"domain_scores_codex":[0.9995579,0.00005315713,0.00002206068,0.000210898,0.0001063533,0.00004956434],"domain_scores_gemma":[0.9989079,0.0003907322,0.0001039445,0.0002235974,0.0003334812,0.00004024667],"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":[0.001645335,0.0002035602,0.03960672,0.0007512242,0.0002641823,0.0006016027,0.0001976751,0.1033333,0.2740828,0.005750273,0.02004337,0.55352],"study_design_scores_gemma":[0.00004304432,0.0001917785,0.01984744,0.0001271551,0.0001025068,0.000655029,0.0001150326,0.702852,0.2345335,0.009763759,0.03170425,0.00006452376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1805741,0.002195829,0.7545923,0.0002928599,0.0001476896,0.00008367658,0.03209404,0.02494318,0.005076297],"genre_scores_gemma":[0.4466898,0.001051387,0.4573804,0.0002208136,0.00006358763,0.0001473578,0.08482593,0.001163699,0.008457064],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004875212,"threshold_uncertainty_score":0.01262945,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4206514926","doi":"10.1109/bibm52615.2021.9669364","title":"Problem Oriented Diagnostic Service for Describing Clinical Cases based on the GraphQL POMR Approach","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Schema (genetic algorithms); Structuring; Workflow; SOAP; Service (business); Medical diagnosis; Artificial intelligence; Process (computing); Software engineering; World Wide Web; Machine learning; Programming language; Database; Medicine","authors":[{"name":"Sabah Mohammed","is_ca":true},{"name":"Jinan Fiaidhi","is_ca":true},{"name":"Darien Sawyer","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1490224584238955,"gpt":0.3475170971003448,"spread":0.1984946386764493,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003389212,0.00102455,0.0009325796,0.003834266,0.0009714665,0.005360026,0.002411589,0.001728022,0.01117624],"category_scores_gemma":[0.009271656,0.0004567278,0.002167958,0.003137826,0.001115028,0.004461716,0.003912922,0.001696063,0.006026434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002295746,"about_ca_system_score_gemma":0.003352036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01361502,"about_ca_topic_score_gemma":0.008108728,"domain_scores_codex":[0.9968349,0.0008091335,0.0006929058,0.0005297574,0.0009130662,0.0002202146],"domain_scores_gemma":[0.996964,0.001150184,0.0002380908,0.0007090832,0.0007156697,0.0002228994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007163529,0.0004113363,0.005822189,0.001944681,0.0002192672,0.004086234,0.003335001,0.0215758,0.01336184,0.4746548,0.150457,0.3234155],"study_design_scores_gemma":[0.0002216336,0.0001193353,0.001622378,0.0004468464,0.0001489555,0.002937584,0.001316987,0.2027863,0.01291164,0.2324311,0.5448444,0.0002126987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005410003,0.000508271,0.8948745,0.003540629,0.0002977426,0.001039117,0.01130225,0.06270497,0.02032248],"genre_scores_gemma":[0.1292186,0.001284824,0.8173453,0.002599795,0.0002295018,0.0009308017,0.03265341,0.003036397,0.01270138],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01361502,"threshold_uncertainty_score":0.03738832,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4205231300","doi":"10.1109/bibm52615.2021.9669527","title":"Predicting the Length of Stay of Patients in Hospitals","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Multilayer perceptron; Convolutional neural network; Artificial intelligence; Artificial neural network; Process (computing); Intensive care; Health care; Machine learning; Data mining; Pattern recognition (psychology); Medicine; Intensive care medicine","authors":[{"name":"Zhiwei Fu","is_ca":true},{"name":"Xinran Gu","is_ca":true},{"name":"Jia Fu","is_ca":true},{"name":"Mojtaba Moattari","is_ca":true},{"name":"Farhana Zulkernine","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02757696130064344,"gpt":0.3021302771997239,"spread":0.2745533158990804,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004292212,0.0004249265,0.0002698468,0.00109631,0.0001767436,0.0005440512,0.0003102261,0.0005137694,0.00144529],"category_scores_gemma":[0.003046,0.00013181,0.0004281584,0.0007397886,0.00007063604,0.0004654759,0.0003358856,0.0004999855,0.0005723161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005480178,"about_ca_system_score_gemma":0.0005432542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01248432,"about_ca_topic_score_gemma":0.0158264,"domain_scores_codex":[0.9997346,0.0000437308,0.00004179633,0.00006668793,0.0000619649,0.0000511699],"domain_scores_gemma":[0.9989198,0.0003291731,0.0002952262,0.0000448475,0.0002640157,0.0001470126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003359561,0.0002003241,0.8887524,0.00009338199,0.0001253,0.0002512131,0.00009978472,0.04609483,0.00139558,0.0001946886,0.00602319,0.05643326],"study_design_scores_gemma":[0.00001241062,0.0002583638,0.4133363,0.00004761224,0.00005689078,0.0002204339,0.0003239793,0.5817442,0.00197458,0.0005768724,0.001415262,0.00003300679],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816704,0.000498821,0.01034627,0.0004890471,0.0001072783,0.0000304185,0.004984123,0.0003625821,0.001511048],"genre_scores_gemma":[0.9901583,0.0002154476,0.004233704,0.00004203972,0.00003825724,0.00002479118,0.004527305,0.00001144465,0.0007488421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01248432,"threshold_uncertainty_score":0.02482331,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4205461463","doi":"10.1109/bibm52615.2021.9669356","title":"Prioritization of Multi-level Risk Factors, and Predicting Changes in Depression Ratings after Treatment Using Multi-Task Learning","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Mental Health Research Topics","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"NOSM University; Lakehead University; Adler; START Clinic; University of Toronto","funders":"","keywords":"Major depressive disorder; Population; Ranking (information retrieval); Depression (economics); Task (project management); Psychology; Disease; Rank (graph theory); Rating scale; Clinical psychology; Machine learning; Computer science; Medicine; Developmental psychology; Environmental health; Mood; Engineering","authors":[{"name":"Lu Wang","is_ca":true},{"name":"Mark Chignell","is_ca":true},{"name":"Haoyan Jiang","is_ca":true},{"name":"Sachinthya Lokuge","is_ca":true},{"name":"Geneva Mason","is_ca":true},{"name":"Kathryn Fotinos","is_ca":true},{"name":"Martin A. Katzman","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.192394825048569,"gpt":0.4248479741037218,"spread":0.2324531490551527,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002261979,0.0009109948,0.001132256,0.001257767,0.0002999791,0.0009032437,0.000558801,0.0007500366,0.0009866232],"category_scores_gemma":[0.007613201,0.000218277,0.0008311777,0.0006297922,0.0001787811,0.0006161651,0.0006756941,0.001132765,0.0002661643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006142801,"about_ca_system_score_gemma":0.000803943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005996037,"about_ca_topic_score_gemma":0.008858464,"domain_scores_codex":[0.9991893,0.000320186,0.00006936028,0.0002397657,0.00009763799,0.0000836758],"domain_scores_gemma":[0.997137,0.001950208,0.0003258777,0.0001116925,0.0002550565,0.0002201826],"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":[0.002827323,0.00512756,0.2968267,0.0003534201,0.0007208576,0.0002547622,0.0005002141,0.1192361,0.004039748,0.0004981347,0.006699243,0.5629159],"study_design_scores_gemma":[0.00009989271,0.0007871758,0.06385013,0.00003830921,0.0001390345,0.00007516963,0.0001568287,0.930554,0.001060739,0.002671225,0.0005223672,0.00004500688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8802204,0.002021215,0.1111164,0.001503976,0.0001470358,0.0005132284,0.001700309,0.0006734419,0.002104016],"genre_scores_gemma":[0.9763497,0.0002169057,0.02142242,0.0001964613,0.00006356948,0.0002058595,0.001035744,0.0000142707,0.0004951394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005996037,"threshold_uncertainty_score":0.01196265,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4205405116","doi":"10.1109/bibm52615.2021.9669510","title":"Performance Comparison of LASSO Variants with Genome-Wide Association Studies (GWAS)","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Genetic Associations and Epidemiology","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":"Thompson Rivers University","funders":"","keywords":"Lasso (programming language); Genome-wide association study; Genetic association; Computer science; Selection (genetic algorithm); Artificial intelligence; Single-nucleotide polymorphism; Population; Machine learning; Feature selection; Computational biology; Data mining; Biology; Genetics; Medicine; Genotype","authors":[{"name":"Nisha Puthiyedth","is_ca":true},{"name":"Nuoyi Zhang","is_ca":true},{"name":"Ziqing Wang","is_ca":true},{"name":"Yan Yan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05126243934673264,"gpt":0.3275380889531601,"spread":0.2762756496064275,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02121685,0.001321202,0.001559761,0.001257912,0.0005385507,0.001805046,0.001093378,0.001372331,0.002433114],"category_scores_gemma":[0.05195162,0.0003322319,0.00108767,0.001347625,0.0006729054,0.001440524,0.001557075,0.001182175,0.0007206282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004803105,"about_ca_system_score_gemma":0.001435361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003668505,"about_ca_topic_score_gemma":0.001883866,"domain_scores_codex":[0.9900181,0.006792941,0.000616299,0.000983195,0.00117722,0.0004121463],"domain_scores_gemma":[0.9679257,0.02533632,0.001432768,0.001806137,0.002646875,0.0008523055],"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":[0.01125813,0.0006347331,0.133034,0.001191945,0.003080487,0.0006434068,0.0004035957,0.4084316,0.004168867,0.01080783,0.02933247,0.3970129],"study_design_scores_gemma":[0.0002719919,0.0004707304,0.01052632,0.00006596229,0.0001872379,0.0001859829,0.0001577276,0.980222,0.001316654,0.003658399,0.002887773,0.0000491529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4314264,0.01868496,0.5217075,0.006107817,0.001903637,0.0004273875,0.00410601,0.006032941,0.009603349],"genre_scores_gemma":[0.7935719,0.002546823,0.1900901,0.001060785,0.0006422586,0.0003926939,0.008078249,0.0008170239,0.002800151],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02121685,"threshold_uncertainty_score":0.1122068,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4206745605","doi":"10.1109/bibm52615.2021.9669564","title":"Single Cell Clustering with Sparse Similarity Matrix Learning","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","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 Saskatchewan","funders":"Science and Engineering Research Council","keywords":"Similarity (geometry); Computer science; Cluster analysis; Subspace topology; Artificial intelligence; Construct (python library); Pattern recognition (psychology); Identification (biology); Hierarchical clustering; Image (mathematics); Biology","authors":[{"name":"Wenjing Zhang","is_ca":true},{"name":"Yuting Tan","is_ca":true},{"name":"Fang‐Xiang Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03764478567226619,"gpt":0.2702416417454061,"spread":0.2325968560731399,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001026565,0.0009401396,0.001317326,0.001451035,0.0006435058,0.0009296926,0.001661117,0.00134094,0.00128793],"category_scores_gemma":[0.002945187,0.0004415561,0.001311383,0.001863589,0.0006325518,0.000967115,0.001169784,0.001212857,0.00119288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007159969,"about_ca_system_score_gemma":0.001279052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00850016,"about_ca_topic_score_gemma":0.008788571,"domain_scores_codex":[0.99897,0.0002066466,0.00005321938,0.0003709397,0.0002916589,0.0001075059],"domain_scores_gemma":[0.9984381,0.0005024288,0.0001668162,0.0002759116,0.0005264181,0.00009024196],"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":[0.0003010177,0.0001696036,0.004160804,0.0002318554,0.0002690147,0.0001917639,0.0002798359,0.48053,0.03451264,0.00800332,0.009862239,0.4614879],"study_design_scores_gemma":[0.000005843091,0.00001663331,0.0003242056,0.00000258735,0.000007047487,0.00003152305,0.00002023145,0.9930599,0.002840869,0.003034938,0.0006448161,0.00001135271],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01465072,0.0002051607,0.9831139,0.0001323291,0.0000342327,0.00004766448,0.0001855244,0.001069849,0.0005606714],"genre_scores_gemma":[0.2947301,0.0003660528,0.6976654,0.000305918,0.0001353755,0.0002604613,0.002876673,0.0002623792,0.003397647],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00850016,"threshold_uncertainty_score":0.01690137,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3122665769","doi":"10.1109/bibm52615.2021.9669726","title":"Boosting Segmentation Performance across Datasets using Histogram Specification with Application to Pelvic Bone Segmentation","year":2021,"lang":"en","type":"preprint","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Mitacs","keywords":"Segmentation; Computer science; Artificial intelligence; Deep learning; Boosting (machine learning); Histogram; Dice; Pattern recognition (psychology); Machine learning; Image (mathematics)","authors":[{"name":"Prabhakara Subramanya Jois","is_ca":true},{"name":"Aniketh Manjunath","is_ca":false},{"name":"Thomas Fevens","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05006283796301823,"gpt":0.3597749553319904,"spread":0.3097121173689721,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00387603,0.00135408,0.001199897,0.002560138,0.0005996819,0.001346987,0.001645194,0.001713037,0.001360193],"category_scores_gemma":[0.01035758,0.000421118,0.0007690261,0.001975994,0.0008774725,0.001307866,0.001825721,0.001155745,0.000786373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009099598,"about_ca_system_score_gemma":0.001146379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00739784,"about_ca_topic_score_gemma":0.007647187,"domain_scores_codex":[0.9981987,0.0005318724,0.0001186304,0.0005409996,0.0003919706,0.0002178844],"domain_scores_gemma":[0.9966429,0.001523456,0.0002610852,0.0006371285,0.0007892229,0.0001460694],"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":[0.001915568,0.0006033005,0.01203981,0.0005840495,0.000378896,0.0002577219,0.0002371994,0.3112032,0.06009831,0.002018472,0.01073881,0.5999247],"study_design_scores_gemma":[0.00008807218,0.000331759,0.005054773,0.00002733432,0.00006250973,0.0001504267,0.00006851144,0.9568356,0.03297963,0.002424606,0.001937607,0.00003921321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5707743,0.004491806,0.3948433,0.001153711,0.0003702094,0.000380879,0.002362182,0.02089757,0.00472606],"genre_scores_gemma":[0.8279163,0.0006681903,0.1620481,0.0004536264,0.0001585755,0.0001449806,0.005578314,0.0009245946,0.002107267],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00739784,"threshold_uncertainty_score":0.02049863,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}