{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":75,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":75,"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"},"query_hash":"7963eb964230","filters":{"venue":"BMC Systems Biology"}},"results":[{"id":"W1999808266","doi":"10.1186/1752-0509-6-87","title":"Iteration method for predicting essential proteins based on orthology and protein-protein interaction networks","year":2012,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":154,"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":"Program for New Century Excellent Talents in University; National Natural Science Foundation of China; National Science Foundation","keywords":"Centrality; Identification (biology); Computational biology; False positive paradox; Systems biology; Computer science; Biological network; Biology; Bioinformatics; Machine learning; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.0144371141995003,"gpt":0.2837806279629868,"spread":0.2693435137634865,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000887785,0.0002052342,0.0002360378,0.00006780453,0.0001476848,0.00004018838,0.00009476417,0.0004455083,0.000004215573],"category_scores_gemma":[0.00008758433,0.0001775702,0.00007804848,0.00005002487,0.0000502052,0.00001102861,0.00005973668,0.0001335943,0.000002729354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000208158,"about_ca_system_score_gemma":0.0000398194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003293796,"about_ca_topic_score_gemma":0.00002892875,"domain_scores_codex":[0.9985293,0.0002973276,0.0004064305,0.0003106044,0.0000485758,0.0004077229],"domain_scores_gemma":[0.9992298,0.00005490785,0.0002800892,0.0002666641,0.00007609483,0.00009242564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002131656,0.0002920489,0.01870747,0.0007820225,0.0002237698,7.880262e-7,0.0002464752,0.01920549,0.9272941,0.01675656,0.0008830864,0.01347658],"study_design_scores_gemma":[0.002627718,0.002462449,0.0009658893,0.0002152362,0.00006528701,0.00008875896,0.0002432088,0.937202,0.0311732,0.0001837223,0.02406944,0.0007031109],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.212187,0.0003941015,0.7846857,0.00003880338,0.000672182,0.00176182,0.0000227986,0.0000212152,0.0002164001],"genre_scores_gemma":[0.9756207,0.000003261603,0.02100284,0.0001159312,0.001770137,0.0008772195,0.0004055733,0.00002613402,0.0001782008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9179965,"threshold_uncertainty_score":0.7241101,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2023627547","doi":"10.1186/1752-0509-4-29","title":"A novel approach to investigate tissue-specific trinucleotide repeat instability","year":2010,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Genetic Neurodegenerative Diseases","field":"Neuroscience","cited_by":152,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"National Institute of Neurological Disorders and Stroke; North Carolina Biotechnology Center; Hereditary Disease Foundation","keywords":"Genome instability; Somatic cell; Biology; Trinucleotide repeat expansion; Instability; Gene; Huntingtin; Genetics; Computational biology; Allele; DNA damage; DNA; Mutant","retraction":null,"screen_n_in":null,"score":{"opus":0.091758994814887,"gpt":0.2900203889167591,"spread":0.1982613941018721,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003914714,0.00028128,0.0003855601,0.0001422168,0.0001585525,0.0000775593,0.0006120404,0.000148213,0.00002502102],"category_scores_gemma":[0.001922475,0.0002383713,0.00007562892,0.0004131437,0.0003834899,0.00006019249,0.0002202595,0.0002431256,0.0002991542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003065628,"about_ca_system_score_gemma":0.0001168072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008301815,"about_ca_topic_score_gemma":0.00004234044,"domain_scores_codex":[0.9970465,0.0005128621,0.0005129351,0.001254155,0.00017761,0.0004958804],"domain_scores_gemma":[0.9980328,0.0002863359,0.0001422245,0.001069923,0.00008636521,0.000382332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003075228,0.0001615063,0.003540161,0.0000379607,0.000001710884,0.000001423316,0.00008785102,0.0001475256,0.980516,0.01478018,0.0005227209,0.0001722585],"study_design_scores_gemma":[0.0006053695,0.0001793625,0.01742408,0.000008955429,0.000007645006,0.0001191341,0.00007008645,0.0003983317,0.8974319,0.0001382022,0.08322011,0.000396854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860545,0.00005571955,0.006488197,0.00007739419,0.002096918,0.001216942,0.0002109768,0.0001728939,0.003626505],"genre_scores_gemma":[0.9942856,0.0000032796,0.004240552,0.0003873096,0.0003265456,0.0002740587,0.0000139367,0.00003513586,0.0004336209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08308409,"threshold_uncertainty_score":0.9720498,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2008087600","doi":"10.1186/1752-0509-4-12","title":"Transcriptional regulation of respiration in yeast metabolizing differently repressive carbon substrates","year":2010,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Fungal and yeast genetics research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":120,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of Toronto; Eidgenössische Technische Hochschule Zürich","keywords":"Respiration; Biochemistry; Galactose; Biology; Cellular respiration; Fermentation; Yeast; Transcriptional regulation; Transcription factor; Saccharomyces cerevisiae; Enzyme; Gene; Botany","retraction":null,"screen_n_in":null,"score":{"opus":0.02580878175974854,"gpt":0.2835711085591046,"spread":0.257762326799356,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002794777,0.000102234,0.0001723763,0.00009737189,0.00002280091,0.00001000876,0.000128664,0.000243003,0.00000985397],"category_scores_gemma":[0.00008655048,0.00008911396,0.00005138761,0.00009084294,0.00009024103,0.000002609041,0.00003059927,0.0001126412,0.000001811262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005816218,"about_ca_system_score_gemma":0.00007547028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002804826,"about_ca_topic_score_gemma":0.0008086194,"domain_scores_codex":[0.9989417,0.0001832361,0.0003128141,0.000289456,0.00009519436,0.000177564],"domain_scores_gemma":[0.9994706,0.00001641598,0.0001039215,0.0002445803,0.0001238224,0.00004065919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001024099,0.00003064155,0.09824166,0.0000350834,0.00001195618,2.044739e-7,0.00002849926,0.0002028772,0.8991849,0.002019685,0.000005796751,0.0001362191],"study_design_scores_gemma":[0.0005265174,0.0001400411,0.3000087,0.00001782763,0.000006506335,0.000009462757,0.00004781586,0.00129546,0.6967899,0.0001917706,0.0008518437,0.0001140746],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973136,0.0009931241,0.0002518245,0.00001709756,0.0004015038,0.0002252865,0.00003047412,0.000004976722,0.000762101],"genre_scores_gemma":[0.9991249,0.00002657423,0.0001455813,0.000004079483,0.0002861978,0.00004361832,0.0001637991,0.0000103885,0.0001948791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.202395,"threshold_uncertainty_score":0.3633962,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2169895124","doi":"10.1186/1752-0509-2-75","title":"Explaining oscillations and variability in the p53-Mdm2 system","year":2008,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Cancer-related Molecular Pathways","field":"Medicine","cited_by":117,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Canadian Institutes of Health Research","keywords":"DNA damage; Mechanism (biology); Negative feedback; Biological system; Mdm2; Positive feedback; Regulator; p14arf; Computer science; Feedback loop; Biophysics; Control theory (sociology); Neuroscience; Biology; DNA; Physics; Control (management); Cancer; Genetics; Voltage; Engineering; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.04445304588172314,"gpt":0.2724515373561128,"spread":0.2279984914743897,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001167408,0.0001160339,0.0003198481,0.0000989229,0.0001146174,0.00000714539,0.00007677088,0.000193433,0.000004441618],"category_scores_gemma":[0.0003579909,0.00007881503,0.00004627661,0.0002229411,0.0001621134,0.00002059556,0.00003081929,0.0001755779,0.0000182916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001411777,"about_ca_system_score_gemma":0.0001535143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005256604,"about_ca_topic_score_gemma":0.00008084404,"domain_scores_codex":[0.9983252,0.0007155215,0.0003540082,0.0002929644,0.00009592537,0.0002163451],"domain_scores_gemma":[0.9989961,0.0004071255,0.00008870064,0.0004004427,0.00005225373,0.00005531837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000267841,0.0001395949,0.9039415,0.001082626,0.0001138693,0.0002169261,0.006290579,0.0003416108,0.01688264,0.06935379,0.0009486005,0.0004204522],"study_design_scores_gemma":[0.01408144,0.002309991,0.7931182,0.00224969,0.0004050942,0.04087714,0.02383893,0.04877156,0.0006986312,0.0003069652,0.07194754,0.001394809],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784673,0.001833221,0.008195134,0.0001656116,0.0007290736,0.001086188,0.00001783447,0.00009842159,0.009407164],"genre_scores_gemma":[0.9993251,0.00002280349,0.0002149628,0.00005432756,0.000186269,0.0001152132,0.00002004648,0.0000111851,0.00005009193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1108233,"threshold_uncertainty_score":0.3213984,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2142446574","doi":"10.1186/1752-0509-5-56","title":"Systems biology approach to identify transcriptome reprogramming and candidate microRNA targets during the progression of polycystic kidney disease","year":2011,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Genetic and Kidney Cyst Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":87,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health; American Heart Association; Hospital for Sick Children; March of Dimes Foundation","keywords":"PKD1; Biology; Polycystic kidney disease; Transcriptome; microRNA; Autosomal dominant polycystic kidney disease; Gene expression profiling; Kidney development; KEGG; Genetics; Regulation of gene expression; Cell biology; Gene expression; Gene; Bioinformatics; Kidney; Embryonic stem cell","retraction":null,"screen_n_in":null,"score":{"opus":0.01893060053381275,"gpt":0.274937832551896,"spread":0.2560072320180833,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003836592,0.0003006349,0.0004088529,0.0001060097,0.0001636951,0.0000302943,0.0003905847,0.000238308,0.000004525621],"category_scores_gemma":[0.0002138483,0.000206415,0.0001253775,0.0001345458,0.0003094745,0.000004865164,0.0001854929,0.00008284891,0.000005419817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001205038,"about_ca_system_score_gemma":0.0001632064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004775009,"about_ca_topic_score_gemma":0.000006455114,"domain_scores_codex":[0.9976334,0.0004571764,0.0005544048,0.000753869,0.00009074978,0.0005104126],"domain_scores_gemma":[0.9984171,0.00001806259,0.0002448377,0.0006762047,0.0001020155,0.000541784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0007641195,0.0001493245,0.1171866,0.0009129871,0.000147227,0.000003578861,0.0002810893,0.00001136332,0.8798169,0.0003373407,0.000260386,0.0001290595],"study_design_scores_gemma":[0.008613821,0.003739023,0.7007414,0.00142407,0.001161496,0.00087101,0.00535913,0.000912305,0.1794793,0.0003042122,0.0939299,0.003464341],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9678684,0.0213992,0.00755542,0.00002755747,0.0008914701,0.001485084,0.0003665908,0.00003631755,0.000369889],"genre_scores_gemma":[0.9980124,0.00009540176,0.0006961865,0.0000574048,0.0002437924,0.0003857886,0.0002601492,0.0000348588,0.0002139677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7003376,"threshold_uncertainty_score":0.841736,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1990514789","doi":"10.1186/1752-0509-6-113","title":"Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks","year":2012,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":85,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Gene regulatory network; Boolean network; Computer science; Probabilistic logic; Systems biology; Computation; Biological network; Computational complexity theory; Stochastic matrix; Sequence (biology); Boolean function; Theoretical computer science; Algorithm; Computational biology; Gene; Biology; Markov chain; Artificial intelligence; Machine learning; Genetics","retraction":null,"screen_n_in":null,"score":{"opus":0.02244454250510567,"gpt":0.2457764000152073,"spread":0.2233318575101017,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001195326,0.0004313032,0.0005406706,0.0001471275,0.000203244,0.0000389492,0.0004834568,0.0005957006,0.000003893346],"category_scores_gemma":[0.00004182168,0.0004013728,0.0002214488,0.0003018046,0.00009032014,0.000006414644,0.0002655031,0.0001570728,0.00001981653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007055623,"about_ca_system_score_gemma":0.00006101105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004963659,"about_ca_topic_score_gemma":0.00001627634,"domain_scores_codex":[0.9966453,0.0005717666,0.0006136604,0.0008766911,0.0001645947,0.001128039],"domain_scores_gemma":[0.9978126,0.00002189983,0.0001897647,0.001249698,0.0001393854,0.0005866961],"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":[0.00006481321,0.0001331268,0.002671292,0.00001317839,0.0001174214,1.94462e-7,0.00004360648,0.9850395,0.01097506,0.0004317646,0.0002667931,0.0002431921],"study_design_scores_gemma":[0.0003137232,0.0001551195,0.0007923373,0.0000163836,0.00009641499,0.00005813843,0.0001759665,0.9971864,0.0002220829,0.000003138111,0.0004732413,0.0005071098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4281732,0.007466561,0.5631279,0.00000241035,0.0006975388,0.0003690844,0.000004896706,0.00004054733,0.0001178511],"genre_scores_gemma":[0.9917784,0.00001782902,0.002767616,0.0001122468,0.004448751,0.0001663322,0.0004576079,0.00008578888,0.0001653875],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5636052,"threshold_uncertainty_score":0.9998438,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2100765607","doi":"10.1186/1752-0509-3-15","title":"Genome-scale constraint-based modeling of Geobacter metallireducens","year":2009,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":82,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Office of Science; U.S. Department of Energy","keywords":"Chemistry; Geobacter sulfurreducens; Environmental chemistry; Biology","retraction":null,"screen_n_in":null,"score":{"opus":0.01948511541999249,"gpt":0.2229442515073792,"spread":0.2034591360873867,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002409521,0.0000970309,0.0001930612,0.00002791766,0.00003238483,0.000007300606,0.0001278998,0.0001110086,0.0003401207],"category_scores_gemma":[0.00001021536,0.00007613737,0.00006431798,0.00007919848,0.00009334778,0.00003141567,0.00002033697,0.00004319993,0.0001158614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004749768,"about_ca_system_score_gemma":0.00001656026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003175882,"about_ca_topic_score_gemma":0.00006847169,"domain_scores_codex":[0.9991497,0.00008151573,0.0002893782,0.0002169951,0.00006614075,0.0001962421],"domain_scores_gemma":[0.9996516,0.00001927876,0.0001076873,0.0001587344,0.00001189774,0.00005081245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001192343,0.00004086573,0.01130748,0.00001567185,0.000003743367,3.19904e-7,0.0000399616,0.0162683,0.9719533,0.00006221885,0.00002567156,0.0002705355],"study_design_scores_gemma":[0.00436177,0.00200765,0.1453448,0.0001563727,0.0002247468,0.00008584296,0.0008199984,0.698268,0.1159516,0.0009283353,0.02960134,0.002249543],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824154,0.0001407403,0.01320044,0.00004367314,0.000217774,0.0002334503,0.00002509541,0.0000223974,0.003700998],"genre_scores_gemma":[0.9984125,0.000008093538,0.001305609,0.00007038812,0.00007052668,0.000003277758,0.00004666775,0.000004215808,0.00007866165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8560017,"threshold_uncertainty_score":0.3724083,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2170432219","doi":"10.1186/1752-0509-4-117","title":"Curating the innate immunity interactome","year":2010,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":76,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Canadian Institutes of Health Research; Teagasc; Genome British Columbia; National Institutes of Health; Michael Smith Health Research BC; Foundation for the National Institutes of Health","keywords":"Innate immune system; Interactome; Biology; Computational biology; Acquired immune system; Systems biology; Immunity; Immunology; Immune system; Genetics; Gene","retraction":null,"screen_n_in":null,"score":{"opus":0.01232392681255914,"gpt":0.2590135533484794,"spread":0.2466896265359202,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005603419,0.0001361921,0.0001399927,0.0000240625,0.0001542324,0.00004547717,0.0003819968,0.0002586408,0.00001290716],"category_scores_gemma":[0.0001085691,0.00008762014,0.00007194099,0.00005498688,0.0001290576,0.000002351715,0.0002198022,0.0002824199,0.00003634906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004373598,"about_ca_system_score_gemma":0.00005282024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001162802,"about_ca_topic_score_gemma":0.000252624,"domain_scores_codex":[0.9991009,0.0001284648,0.0003126464,0.0001695825,0.00003783785,0.0002505458],"domain_scores_gemma":[0.9991367,0.00004455014,0.0001677757,0.0005446982,0.00005895853,0.00004732096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004697348,0.000025703,0.0147565,0.00003959447,0.00007589888,4.36816e-7,0.0001759744,0.00008067068,0.9717242,0.00710869,0.003380432,0.002584937],"study_design_scores_gemma":[0.001622914,0.0007311173,0.01703809,0.00006310709,0.00004681509,0.0005741576,0.001635681,0.01301291,0.02209547,0.001412908,0.9406443,0.001122592],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860406,0.0006164956,0.007233112,0.00007940222,0.002502933,0.0002745409,0.00001945586,0.00001622781,0.003217221],"genre_scores_gemma":[0.9979174,0.00002279275,0.0003444224,0.0001976591,0.0008713196,0.00003433563,0.0001237574,0.00001337092,0.0004750095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9496287,"threshold_uncertainty_score":0.3573045,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1992383350","doi":"10.1186/1752-0509-4-67","title":"An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer","year":2010,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":75,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Canadian Centre for Applied Research in Cancer Control","funders":"Canadian Institutes of Health Research; Canadian Breast Cancer Research Alliance","keywords":"Epigenetics; Biology; Computational biology; Genomics; DNA methylation; Systems biology; Genome; Gene; Epigenomics; Transcriptome; Gene expression profiling; Gene regulatory network; Cancer; Genetics; Gene expression","retraction":null,"screen_n_in":null,"score":{"opus":0.02431953621380379,"gpt":0.3006551688896911,"spread":0.2763356326758873,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001605968,0.0001762011,0.0002086172,0.00007368428,0.00007161826,0.00003700296,0.0001143362,0.0002202837,0.00001406234],"category_scores_gemma":[0.00002051361,0.0001439513,0.00002359822,0.00005035887,0.0001029486,0.000004551483,0.00008056258,0.00008878613,0.000003261179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009719715,"about_ca_system_score_gemma":0.0001105586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001871313,"about_ca_topic_score_gemma":0.01127089,"domain_scores_codex":[0.9988583,0.0001469878,0.0002771138,0.0004404816,0.0000392323,0.0002378958],"domain_scores_gemma":[0.999508,0.00001845285,0.00006761117,0.0002176717,0.00006776614,0.0001205322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002172493,0.00003540116,0.1524943,0.00002206762,0.00001646894,0.000001638735,0.0001969459,0.0004390055,0.8453128,0.0003134656,0.00000961934,0.001136623],"study_design_scores_gemma":[0.001387749,0.001172648,0.9226627,0.00004895433,0.00002809067,0.0001930376,0.001771946,0.003284051,0.06706185,0.0001860298,0.00158948,0.0006134213],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939091,0.004320038,0.000906477,0.00001489943,0.0003902349,0.0003187247,0.0001135125,0.000007390399,0.00001962924],"genre_scores_gemma":[0.9974383,0.0001946561,0.001803445,0.00004547455,0.0001938961,0.0001471709,0.00005991052,0.00001480282,0.0001023606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7782509,"threshold_uncertainty_score":0.6289424,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2045336896","doi":"10.1186/1752-0509-4-111","title":"Modeling the global effect of the basic-leucine zipper transcription factor 1 (bZIP1) on nitrogen and light regulation in Arabidopsis","year":2010,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Plant nutrient uptake and metabolism","field":"Agricultural and Biological Sciences","cited_by":75,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"National Institute of General Medical Sciences; York University; U.S. Department of Energy; National Institutes of Health; National Science Foundation","keywords":"Leucine zipper; Arabidopsis; Zipper; Transcription factor; Basic helix-loop-helix leucine zipper transcription factors; Computational biology; Systems biology; Biology; ATF3; Cell biology; Transcription (linguistics); Genetics; Computer science; Promoter; DNA-binding protein; Gene; Gene expression; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.01826000544037574,"gpt":0.2194898161779423,"spread":0.2012298107375665,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003677518,0.0001065064,0.000200343,0.000009425125,0.00008328276,0.00001316583,0.0001531963,0.0001548712,0.000009552918],"category_scores_gemma":[0.00005531914,0.00002670982,0.00006777135,0.0001584523,0.00004070091,0.00003509453,0.00001824093,0.0001027934,0.000003199395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009561738,"about_ca_system_score_gemma":0.00000446131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005193957,"about_ca_topic_score_gemma":0.001531088,"domain_scores_codex":[0.999052,0.0003157244,0.0002114515,0.0001899696,0.00007891225,0.0001519226],"domain_scores_gemma":[0.9996623,0.0001398256,0.00007107186,0.00007675899,0.00002285058,0.00002713389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001082907,0.00001803879,0.2651758,0.0000100618,0.00000689734,1.014147e-7,0.00004742661,0.00005413814,0.7281405,0.002431093,0.00001905452,0.003988538],"study_design_scores_gemma":[0.001114675,0.0005758854,0.9272458,0.000119552,0.0000569549,0.00004442161,0.0001797302,0.008797027,0.03275516,0.001225929,0.02759693,0.0002879135],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977471,0.0006436659,0.000009630617,0.0003229594,0.0006458986,0.0004062715,0.00009332298,0.00001290228,0.0001182712],"genre_scores_gemma":[0.9996352,0.00004083668,0.000002775986,0.00003280311,0.0002203223,0.00002094586,0.00002203522,5.591819e-7,0.00002453389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6953853,"threshold_uncertainty_score":0.1194509,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2111805188","doi":"10.1186/1752-0509-8-35","title":"Improving protein function prediction using domain and protein complexes in PPI networks","year":2014,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":74,"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":"Protein function prediction; Domain (mathematical analysis); Computational biology; Computer science; In silico; Context (archaeology); Protein domain; Similarity (geometry); Protein–protein interaction; Protein function; Structural similarity; Function (biology); Protein Interaction Networks; Systems biology; Data mining; Machine learning; Biology; Artificial intelligence; Genetics; Mathematics; Gene","retraction":null,"screen_n_in":null,"score":{"opus":0.01036805990849688,"gpt":0.209650216361589,"spread":0.1992821564530921,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006761664,0.0001675224,0.0002184443,0.0000631678,0.0000937608,0.00003625077,0.00009030355,0.0003627313,0.000001671624],"category_scores_gemma":[0.00002991529,0.0001508595,0.00003704467,0.00007188733,0.00008434351,0.000006465764,0.0001003814,0.0001185247,0.000001576427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002480838,"about_ca_system_score_gemma":0.00003321637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002480609,"about_ca_topic_score_gemma":0.0001825983,"domain_scores_codex":[0.9987134,0.0002280813,0.0004003392,0.0003111674,0.00004389943,0.0003031406],"domain_scores_gemma":[0.999464,0.00001161804,0.0001938694,0.0002355977,0.00003629471,0.00005863768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002170699,0.00003076916,0.0182702,0.0002287171,0.00003585438,3.394199e-7,0.00003936705,0.004943568,0.9652941,0.006622722,0.00007652402,0.00424081],"study_design_scores_gemma":[0.003526472,0.001859395,0.007861475,0.0003447386,0.00003620547,0.0001102963,0.0004508284,0.9604403,0.002763534,0.003400855,0.01833778,0.000868139],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5890409,0.000652859,0.4093161,0.000005675949,0.000222819,0.0005945018,0.000006888577,0.00001282403,0.0001474247],"genre_scores_gemma":[0.9967625,0.00000490703,0.002230825,0.00003248439,0.0006573088,0.0000983885,0.0001122852,0.00001744235,0.00008392721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9625306,"threshold_uncertainty_score":0.6151873,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1970772422","doi":"10.1186/1752-0509-2-80","title":"The use of Gene Ontology terms for predicting highly-connected 'hub' nodes in protein-protein interaction networks","year":2008,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":66,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Genome British Columbia; Michael Smith Health Research BC; Genome Canada","keywords":"Computational biology; Caenorhabditis elegans; Protein–protein interaction; Drosophila melanogaster; Biology; Systems biology; Gene ontology; In silico; Interaction network; Computer science; Proteomics; Protein Interaction Networks; Classifier (UML); Gene; Bioinformatics; Genetics; Artificial intelligence; Gene expression","retraction":null,"screen_n_in":null,"score":{"opus":0.03677625194090396,"gpt":0.249243568244365,"spread":0.2124673163034611,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003758177,0.0001886087,0.0003175107,0.00005687703,0.0001591559,0.00001940935,0.0002311924,0.0004286121,0.000001046492],"category_scores_gemma":[0.0002198429,0.000137198,0.0001057213,0.00008532898,0.0001758491,0.000008449755,0.00008109579,0.0001394072,0.000001256336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002871233,"about_ca_system_score_gemma":0.00006512527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003158114,"about_ca_topic_score_gemma":0.000667386,"domain_scores_codex":[0.9983269,0.0002166222,0.0007159999,0.0002934731,0.0000464066,0.0004005835],"domain_scores_gemma":[0.9988639,0.0001556337,0.0004296971,0.0003914866,0.0001123606,0.00004693664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001708618,0.0001302603,0.05430786,0.0002423725,0.0002776705,0.000003722639,0.0002210989,0.01745847,0.9166256,0.004131895,0.0009933031,0.003899206],"study_design_scores_gemma":[0.01031177,0.004966266,0.02141881,0.0007586849,0.0001068326,0.0008389049,0.0009548417,0.6615741,0.142048,0.0009090271,0.154001,0.002111807],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9013285,0.001017677,0.09550599,0.00003678026,0.0006367839,0.001359834,0.00003226764,0.00001562046,0.00006652698],"genre_scores_gemma":[0.9962263,0.00006406483,0.002364401,0.00003505434,0.0004316159,0.0004041497,0.0001668306,0.00002086993,0.0002867376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7745776,"threshold_uncertainty_score":0.5594773,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2136317480","doi":"10.1186/1752-0509-5-124","title":"Integrating systems biology models and biomedical ontologies","year":2011,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":63,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"Biotechnology and Biological Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; European Commission","keywords":"SBML; Systems biology; Computer science; Markup language; Modelling biological systems; Systems medicine; Software; Granularity; Biological network; Semantics (computer science); Ontology; Synthetic biology; Open Biomedical Ontologies; Data science; Theoretical computer science; Computational biology; XML; Biology; Semantic Web; Programming language; Artificial intelligence; World Wide Web; Ontology-based data integration","retraction":null,"screen_n_in":null,"score":{"opus":0.08872993251183821,"gpt":0.3008347876630508,"spread":0.2121048551512126,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006612437,0.0003282763,0.0005637268,0.0001327475,0.0001287149,0.00002885045,0.0004156971,0.00101613,0.00000867281],"category_scores_gemma":[0.000483487,0.0002354035,0.00009314194,0.0001152687,0.001038786,0.000005467621,0.000306535,0.0001975183,0.00001507721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001935699,"about_ca_system_score_gemma":0.0001104171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001221409,"about_ca_topic_score_gemma":0.0001046359,"domain_scores_codex":[0.9974853,0.0004925595,0.0005898848,0.0007572491,0.00008026576,0.000594675],"domain_scores_gemma":[0.9988896,0.0001261086,0.0002235469,0.0004744276,0.00009884446,0.0001874918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009601064,0.0006928284,0.2497763,0.001172166,0.001238138,0.00005885344,0.002683094,0.00004822453,0.4237222,0.2564216,0.01182185,0.05140464],"study_design_scores_gemma":[0.01288306,0.02563282,0.02228364,0.001328075,0.0005586055,0.005281233,0.04538158,0.04303442,0.01581605,0.02347158,0.7965424,0.007786567],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7303561,0.03749063,0.2203396,0.0000849843,0.00389028,0.0006886384,0.0001349193,0.0002916213,0.006723208],"genre_scores_gemma":[0.9927626,0.000330448,0.005787138,0.00006537107,0.0004446164,0.0001299729,0.000150668,0.00002510797,0.0003040749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7847205,"threshold_uncertainty_score":0.9599476,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2015271344","doi":"10.1186/1752-0509-6-101","title":"Integrating external biological knowledge in the construction of regulatory networks from time-series expression data","year":2012,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of General Medical Sciences; National Institutes of Health; Western Canada Research Grid","keywords":"Computer science; Inference; Gene regulatory network; Data mining; Bayesian network; Regression; Time series; Regression analysis; Bayesian probability; Feature selection; Systems biology; Bayesian inference; Machine learning; Biological network; Dynamic Bayesian network; Artificial intelligence; Computational biology; Statistics; Mathematics; Biology; Gene expression","retraction":null,"screen_n_in":null,"score":{"opus":0.03275598549327609,"gpt":0.2741752154003971,"spread":0.241419229907121,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001044071,0.0001753887,0.0003188681,0.00005015602,0.00006131005,0.00001185958,0.0005837065,0.0003748856,0.00001764922],"category_scores_gemma":[0.00009724979,0.0001114846,0.00007867611,0.0001319411,0.000258709,0.00001143899,0.000335472,0.0001168218,0.000007334081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001392269,"about_ca_system_score_gemma":0.00004418748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000076041,"about_ca_topic_score_gemma":0.00007080084,"domain_scores_codex":[0.9977116,0.001088253,0.000464701,0.0003774154,0.00006558309,0.0002924333],"domain_scores_gemma":[0.9985967,0.0001076788,0.0002693674,0.0009277545,0.00004951485,0.00004901351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008971916,0.00006759165,0.5023956,0.00001440953,0.00005276431,3.259213e-7,0.0000856901,0.0002892528,0.4945732,0.0006432552,0.0007678893,0.00102031],"study_design_scores_gemma":[0.004115708,0.00155435,0.6608437,0.001104675,0.0004755725,0.0006636364,0.01290931,0.04433965,0.1735106,0.0007508302,0.09691454,0.002817394],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9636152,0.0183254,0.01704893,0.000005585104,0.0005459578,0.0001845025,0.00003921326,0.00001028554,0.0002248806],"genre_scores_gemma":[0.9949336,0.0001191925,0.002898564,0.00001130877,0.001362467,0.00002387954,0.0005902442,0.00001150084,0.0000492571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3210626,"threshold_uncertainty_score":0.4546212,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1964495361","doi":"10.1186/1752-0509-7-66","title":"FiloDetect: automatic detection of filopodia from fluorescence microscopy images","year":2013,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Cellular Mechanics and Interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":60,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa; Ottawa Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Ministero dello Sviluppo Economico; Canadian Institutes of Health Research; Mitacs; Ontario Ministry of Economic Development and Innovation; Government of Ontario","keywords":"Filopodia; Fluorescence microscope; Pseudopodia; Microscopy; Confocal microscopy; Biology; Actin; Computer science; Cell biology; Fluorescence; Pathology; Physics; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.00845599331761521,"gpt":0.2399856397349416,"spread":0.2315296464173264,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009365335,0.0001401825,0.0002065695,0.00005450592,0.00005320086,0.00002341741,0.0001782631,0.0002882507,0.0001602434],"category_scores_gemma":[0.0001097975,0.0001248594,0.00009596562,0.00006483183,0.00005708099,0.000005691133,0.00007543093,0.00009408613,0.0001216589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001440533,"about_ca_system_score_gemma":0.00003789942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001854668,"about_ca_topic_score_gemma":0.00007984414,"domain_scores_codex":[0.9989898,0.0001320317,0.0003317786,0.0003058572,0.00004835966,0.000192231],"domain_scores_gemma":[0.9992109,0.00003943096,0.0001868871,0.0003876457,0.0001225344,0.0000526278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000009571716,0.0000263265,0.0008416303,0.00002895593,0.00003195257,1.53361e-7,0.00001185899,0.000004047094,0.9970016,0.00002652456,0.0007728476,0.001244565],"study_design_scores_gemma":[0.00022132,0.0002652263,0.001966924,0.00002990133,0.0000139624,0.0000122508,0.0001026649,0.003344296,0.9894009,0.00009209809,0.004406015,0.0001443968],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9688809,0.00145791,0.02784616,0.00001359208,0.001048905,0.0003608103,0.0001078683,0.00002422028,0.0002596601],"genre_scores_gemma":[0.9976268,0.00005872318,0.001453056,0.0000219617,0.000198891,0.00009632258,0.0001622816,0.0000168758,0.0003651044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02874591,"threshold_uncertainty_score":0.5091619,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2900910515","doi":"10.1186/s12918-018-0624-4","title":"An interpretable boosting model to predict side effects of analgesics for osteoarthritis","year":2018,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":59,"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 Institutes of Health; National Natural Science Foundation of China","keywords":"Interpretability; Machine learning; Artificial intelligence; Osteoarthritis; Medicine; Boosting (machine learning); Predictive modelling; Computer science; Medical record; Internal medicine; Alternative medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.02334702948595664,"gpt":0.3211614191044852,"spread":0.2978143896185286,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006604627,0.0001430366,0.0003533268,0.0001367303,0.0001122563,0.00003815302,0.0007783662,0.0001420788,5.50942e-7],"category_scores_gemma":[0.000749545,0.0001319925,0.00005288704,0.0002058289,0.0000574893,0.0001308416,0.0001871387,0.00009173981,0.00001026502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004012495,"about_ca_system_score_gemma":0.0001317354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005564819,"about_ca_topic_score_gemma":0.000182569,"domain_scores_codex":[0.9982117,0.0003889941,0.000415151,0.0004914465,0.00009497412,0.0003977619],"domain_scores_gemma":[0.998037,0.0006489707,0.0001985228,0.0006976348,0.0002699276,0.0001479621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003705252,0.0002206879,0.3835484,0.00813657,0.000114802,0.00001224317,0.01188591,0.06566413,0.1120626,0.2365438,0.001397843,0.1800424],"study_design_scores_gemma":[0.0003471865,0.003143613,0.001660509,0.0002930469,0.000005375411,0.00001874794,0.00002522836,0.9916502,0.001600076,0.0006539593,0.0004526608,0.0001493666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1612091,0.0003039794,0.8359575,0.00005248655,0.001148153,0.0008317651,0.00001652387,0.0001430362,0.0003375174],"genre_scores_gemma":[0.9271202,9.772563e-7,0.07218194,0.0001335079,0.0003213373,0.0001572297,0.000007157241,0.00001492625,0.00006274154],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9259861,"threshold_uncertainty_score":0.5382497,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2053884941","doi":"10.1186/1752-0509-2-31","title":"An integrated genetic, genomic and systems approach defines gene networks regulated by the interaction of light and carbon signaling pathways in Arabidopsis","year":2008,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Light effects on plants","field":"Agricultural and Biological Sciences","cited_by":59,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"National Institute of General Medical Sciences; York University; U.S. Department of Energy; Division of Mathematical Sciences; National Institutes of Health; National Science Foundation","keywords":"Gene; Arabidopsis; Gene regulatory network; Biology; Transcription factor; Genetics; Microarray analysis techniques; Mutant; Context (archaeology); Computational biology; Regulation of gene expression; Gene expression; Systems biology","retraction":null,"screen_n_in":null,"score":{"opus":0.02541829073752535,"gpt":0.1998737445178092,"spread":0.1744554537802838,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003978993,0.0001788304,0.0003788909,0.00002989387,0.00009568607,0.00003216856,0.0001622658,0.000244113,0.000001079838],"category_scores_gemma":[0.00001741934,0.00006297424,0.0000252391,0.0002128031,0.00008534403,0.00004294489,0.0000386379,0.000114554,4.406152e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002706661,"about_ca_system_score_gemma":0.000008162529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005560909,"about_ca_topic_score_gemma":0.0002474246,"domain_scores_codex":[0.9983432,0.0005739236,0.0004143371,0.0003681753,0.00006379767,0.0002365619],"domain_scores_gemma":[0.9993382,0.0002398742,0.0002218806,0.0000889541,0.00005032907,0.00006079975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005196697,0.00003522085,0.1794172,0.00002768605,0.00001738568,0.000002073181,0.0001209967,0.0008753494,0.8189205,0.00002320617,0.00002352248,0.0004849349],"study_design_scores_gemma":[0.001029094,0.001444373,0.5928373,0.0002619108,0.00006409022,0.001627955,0.002883449,0.3744455,0.02352685,0.00002005117,0.001044281,0.0008151173],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919883,0.007087805,0.00004393567,0.00001171,0.0002481301,0.0005200159,0.00003246811,0.00003294809,0.00003468792],"genre_scores_gemma":[0.999388,0.0002180531,0.00003645472,0.000009051545,0.0001507717,0.00004855338,0.0001345642,0.000002321061,0.00001216454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7953936,"threshold_uncertainty_score":0.8406469,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2067424615","doi":"10.1186/1752-0509-3-21","title":"Protein evolution on a human signaling network","year":2009,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":56,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University; National Research Council Canada; Biotechnology Research Institute","funders":"","keywords":"Biology; Signaling proteins; Signal transduction; Systems biology; Computational biology; Cell biology; Genetics","retraction":null,"screen_n_in":null,"score":{"opus":0.01939417301594777,"gpt":0.2603768622740761,"spread":0.2409826892581284,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003625667,0.0001671608,0.0001938979,0.00003457201,0.0001478067,0.00002455005,0.0001763693,0.0003194694,0.000005042672],"category_scores_gemma":[0.00001788944,0.0001438203,0.00008364644,0.00007062832,0.00004080577,0.000001898188,0.00003496591,0.0001011014,0.00003436702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003878825,"about_ca_system_score_gemma":0.00004218918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002745774,"about_ca_topic_score_gemma":0.00001605168,"domain_scores_codex":[0.9988562,0.0001204774,0.0003338206,0.0002719685,0.00005477829,0.0003626842],"domain_scores_gemma":[0.9993885,0.000008725716,0.0001580541,0.0003341726,0.00004370853,0.00006685877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001558569,0.00007385766,0.002515237,0.00004516142,0.00005751404,0.000001379178,0.00002607403,0.009412994,0.8027654,0.1786679,0.004847093,0.001431508],"study_design_scores_gemma":[0.01540586,0.04002587,0.03579498,0.002170758,0.0002672648,0.0004982207,0.001052954,0.04095479,0.07252056,0.1349696,0.6480662,0.008272897],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9102864,0.002110743,0.07972308,0.00006279442,0.0006293416,0.0008931672,0.00001323483,0.00005381177,0.006227454],"genre_scores_gemma":[0.9968845,0.000003441734,0.0006085769,0.0001932622,0.001618226,0.0000350687,0.0001403341,0.00001135278,0.0005052087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7302448,"threshold_uncertainty_score":0.5864823,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2773435160","doi":"10.1186/s12918-017-0475-4","title":"Mining significant high utility gene regulation sequential patterns","year":2017,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Systems biology; Computational biology; Biology; Gene; Gene regulatory network; Regulation of gene expression; Computer science; Genetics; Gene expression","retraction":null,"screen_n_in":null,"score":{"opus":0.07164685017363992,"gpt":0.3035399434277415,"spread":0.2318930932541016,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000462936,0.0001101082,0.0001832223,0.00004225695,0.000423779,0.00030124,0.001153494,0.0001023698,0.000009871012],"category_scores_gemma":[0.00005610002,0.00009626151,0.00003914033,0.00004291984,0.00007722525,0.000229776,0.0003400974,0.00005281974,0.0000498655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002466413,"about_ca_system_score_gemma":0.00005782165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001573952,"about_ca_topic_score_gemma":0.0000508808,"domain_scores_codex":[0.9988005,0.0001195563,0.0002763643,0.0004858996,0.00008527857,0.0002324736],"domain_scores_gemma":[0.9979994,0.00006577592,0.0002992638,0.001503647,0.000066223,0.00006574377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002096739,0.0002209622,0.4264481,0.000179385,0.0001128224,0.00001842838,0.0007472204,0.0001543164,0.08090631,0.3264082,0.003491854,0.1612914],"study_design_scores_gemma":[0.0006534979,0.0001189401,0.5994933,0.00006098648,0.00001831812,0.00005492245,0.00007615369,0.3795893,0.005775925,0.001349383,0.01233717,0.0004720742],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2692627,0.00002855364,0.728929,0.0001333194,0.001081916,0.0001649103,0.00007841948,0.00008983626,0.0002313584],"genre_scores_gemma":[0.9658343,0.000002981279,0.0334384,0.00001453194,0.0003541242,0.00006425659,0.00008883609,0.000005810318,0.0001968078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6965716,"threshold_uncertainty_score":0.392543,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2076149854","doi":"10.1186/1752-0509-8-s3-s1","title":"A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets","year":2014,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"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":"Novo Nordisk Fonden","keywords":"Systems biology; Gene regulatory network; Computational biology; Lasso (programming language); Computer science; Group (periodic table); Biology; Gene; Genetics; Gene expression","retraction":null,"screen_n_in":null,"score":{"opus":0.01952872400703771,"gpt":0.2853913701429309,"spread":0.2658626461358932,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006908794,0.0002131536,0.0002936472,0.00004803281,0.000105741,0.00002725361,0.0002920866,0.0004252078,0.00001068039],"category_scores_gemma":[0.0001754325,0.0001922962,0.0001170868,0.00006371192,0.00005121322,0.000003979078,0.00008060618,0.00007369827,0.00001225197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002333216,"about_ca_system_score_gemma":0.00006924454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001294825,"about_ca_topic_score_gemma":0.0001128784,"domain_scores_codex":[0.9980997,0.0005110116,0.00035302,0.0006470973,0.00007169848,0.0003174507],"domain_scores_gemma":[0.9985857,0.0001767856,0.0002506883,0.0007986257,0.00007516395,0.0001130415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001840784,0.00005401307,0.008194759,0.0000246747,0.00004723944,1.355039e-7,0.000004959241,0.01050469,0.9673312,0.0001495823,0.01064072,0.002863968],"study_design_scores_gemma":[0.003287112,0.0003979617,0.01200621,0.00006711391,0.00008533165,0.000006210685,0.00003639945,0.6015868,0.1115335,0.00005801923,0.2703655,0.0005699052],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06792543,0.001335401,0.9289297,0.00003210034,0.0007746618,0.0004991262,0.0004139332,0.00004183817,0.0000477969],"genre_scores_gemma":[0.9568759,0.00001245527,0.03149372,0.0002758023,0.001275607,0.0003800695,0.009475236,0.0000425103,0.0001687412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.897436,"threshold_uncertainty_score":0.7841612,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2590094651","doi":"10.1186/s12918-017-0396-2","title":"Progesterone signalling in broiler skeletal muscle is associated with divergent feed efficiency","year":2017,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Adipose Tissue and Metabolism","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"National Institute of Food and Agriculture; Commonwealth Scientific and Industrial Research Organisation; McMaster University; U.S. Department of Agriculture","keywords":"Biology; Transcriptome; Skeletal muscle; Pectoralis Muscle; Cell biology; Gene isoform; Gene; Internal medicine; Gene expression; Endocrinology; Genetics; Anatomy","retraction":null,"screen_n_in":null,"score":{"opus":0.03996274336876313,"gpt":0.2925157949593408,"spread":0.2525530515905777,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003965351,0.0001791659,0.0005522053,0.00009640584,0.0001592497,0.00002738883,0.0001873948,0.0002115172,0.00005926099],"category_scores_gemma":[0.0001949717,0.000126568,0.00005961842,0.00007651182,0.0001383025,0.00006045321,0.00006709703,0.0001559495,0.00006760636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006442542,"about_ca_system_score_gemma":0.0001118901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008428804,"about_ca_topic_score_gemma":0.0002314586,"domain_scores_codex":[0.9986368,0.0001211027,0.0003268767,0.0003644133,0.00014142,0.0004094211],"domain_scores_gemma":[0.9990267,0.0000548857,0.0002836612,0.0004238942,0.00009545175,0.0001154718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001608186,0.0005933338,0.9233051,0.0002444354,0.0002638458,0.0001699572,0.001446935,0.00003166243,0.07007911,0.0006847877,0.0003624309,0.002657587],"study_design_scores_gemma":[0.004951889,0.0007750932,0.9792084,0.000606009,0.0001668437,0.00007688152,0.0002219603,0.0007745543,0.001216153,0.00001566571,0.01165678,0.000329802],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948616,0.002140896,0.0004335514,0.0001125711,0.0005190129,0.000747585,0.00001347716,0.00005019073,0.001121095],"genre_scores_gemma":[0.9968442,0.00002495424,0.0000841481,0.00006507372,0.0002413946,0.0000599118,0.0000304052,0.00002200584,0.002627851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06886295,"threshold_uncertainty_score":0.5161294,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2013715930","doi":"10.1186/1752-0509-7-s4-s6","title":"Sparse representation approaches for the classification of high-dimensional biological data","year":2013,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Dimensionality reduction; Sparse approximation; Artificial intelligence; Cluster analysis; Biological data; Machine learning; Kernel (algebra); Neural coding; External Data Representation; Curse of dimensionality; Dimension (graph theory); Kernel method; Pattern recognition (psychology); Data mining; Bioinformatics; Support vector machine; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.2673352193874908,"gpt":0.3366651418212119,"spread":0.06932992243372105,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000354917,0.0001037348,0.0001513374,0.000032687,0.00007728815,0.00001531117,0.000429144,0.0002023777,0.00001633505],"category_scores_gemma":[0.00021666,0.00006305955,0.00004932874,0.00007734822,0.0001455325,0.000006118461,0.0001433703,0.00003927201,0.00001200032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007626924,"about_ca_system_score_gemma":0.00006057527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001615944,"about_ca_topic_score_gemma":0.00001557859,"domain_scores_codex":[0.9987991,0.0002097727,0.0003222778,0.000460427,0.00006557762,0.0001428583],"domain_scores_gemma":[0.9985384,0.0001141287,0.0002506704,0.0009309505,0.0001315152,0.0000343083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001004781,0.00006059551,0.01080484,0.00002730684,0.00005173729,1.458546e-8,0.00001251777,0.0003531478,0.9580562,0.006813052,0.01725226,0.006467839],"study_design_scores_gemma":[0.003224246,0.001026509,0.6243702,0.00005369538,0.0001190626,0.00003931636,0.002395809,0.1282417,0.1101298,0.002158718,0.1274568,0.0007842365],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8244651,0.002521568,0.1692428,0.0006545495,0.0009679311,0.001749285,0.0001666137,0.00002089099,0.0002112705],"genre_scores_gemma":[0.9954484,0.00005964558,0.001177443,0.00004093246,0.0003560136,0.0005395415,0.002102444,0.000009433386,0.0002661353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8479264,"threshold_uncertainty_score":0.2571494,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2117238525","doi":"10.1186/1752-0509-2-66","title":"GridCell: a stochastic particle-based biological system simulator","year":2008,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Diffusion and Search Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Particle system; Computer science; Systems biology; Simulation; Computational biology; Biology; Computer graphics (images)","retraction":null,"screen_n_in":null,"score":{"opus":0.04503003592974317,"gpt":0.2723975257663894,"spread":0.2273674898366462,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003255657,0.0002397241,0.000344163,0.00005534952,0.0001761363,0.00001758399,0.0003050877,0.0003822812,0.00001612599],"category_scores_gemma":[0.0002047367,0.000184408,0.0001552279,0.000122552,0.0002713684,0.000002192148,0.0001195933,0.0001079251,0.0001338308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003973702,"about_ca_system_score_gemma":0.0001878147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006534863,"about_ca_topic_score_gemma":0.00001517576,"domain_scores_codex":[0.9980076,0.000404863,0.0004032084,0.0005517111,0.0001217654,0.0005108272],"domain_scores_gemma":[0.9989347,0.00009256448,0.0001189884,0.0005106251,0.0001202204,0.00022283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001113759,0.0005937985,0.1529105,0.0003122893,0.0001701857,0.00007824651,0.00008575302,0.03543301,0.793527,0.01337123,0.002118214,0.0002860042],"study_design_scores_gemma":[0.01123016,0.005598905,0.02150721,0.0002310204,0.00008072307,0.001358595,0.001261243,0.8772632,0.01726989,0.00004468161,0.06154229,0.002612027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9245905,0.0007832064,0.07309557,0.00002136188,0.0006344694,0.000442987,0.00005354089,0.00009804907,0.0002802585],"genre_scores_gemma":[0.9984801,0.00001624033,0.0002164627,0.0001247855,0.0003692006,0.00009335035,0.0001987678,0.00002639898,0.0004746277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8418303,"threshold_uncertainty_score":0.751994,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2108864800","doi":"10.1186/1752-0509-5-84","title":"Systems mapping: how to improve the genetic mapping of complex traits through design principles of biological systems","year":2011,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Higher Education Discipline Innovation Project; North Carolina State University; Division of Mathematical Sciences; National Science Foundation; University of North Carolina at Chapel Hill; Natural Sciences and Engineering Research Council of Canada; Ministry of Education, India","keywords":"Quantitative trait locus; Systems biology; Trait; Biology; Function (biology); Computational biology; Phenotype; Computer science; Genetics; Gene","retraction":null,"screen_n_in":null,"score":{"opus":0.2899950946786283,"gpt":0.2576924492287116,"spread":0.03230264544991673,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007655745,0.0002526406,0.0006087029,0.00003025513,0.000136894,0.00004059855,0.0006379026,0.0002800051,0.00001571836],"category_scores_gemma":[0.0001477497,0.00008721693,0.0001304377,0.0004059249,0.0001949167,0.00003264872,0.0001319516,0.00008087251,0.000009174801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002683953,"about_ca_system_score_gemma":0.00002137374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001079764,"about_ca_topic_score_gemma":0.00002930142,"domain_scores_codex":[0.9973066,0.0008438136,0.0007981,0.000475024,0.0001703027,0.000406199],"domain_scores_gemma":[0.9983699,0.0004689557,0.0006390202,0.0001800424,0.0002604543,0.00008166413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004309655,0.00008071105,0.02944348,0.0001572727,0.00007421966,8.029037e-7,0.0009673038,0.0003087296,0.9558741,0.01174741,0.0001635757,0.001139327],"study_design_scores_gemma":[0.0005272282,0.002661188,0.9155253,0.0003176411,0.00004074133,0.00006891005,0.02280408,0.005855239,0.007724494,0.0002218439,0.04354157,0.0007117579],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746973,0.001906965,0.01961231,0.00008604414,0.0008279571,0.002150803,0.0001239101,0.00005550667,0.0005391858],"genre_scores_gemma":[0.9977979,0.00003247494,0.001425432,0.00002185785,0.0003345082,0.000213577,0.00002661146,0.00000303817,0.000144604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9481496,"threshold_uncertainty_score":0.3556603,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2127025785","doi":"10.1186/1752-0509-4-90","title":"microRNA evolution in a human transcription factor and microRNA regulatory network","year":2010,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":40,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada; Biotechnology Research Institute","funders":"Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"microRNA; Biology; Gene regulatory network; Computational biology; Transcription factor; Gene; Systems biology; Regulation of gene expression; Genetics; Gene silencing; Gene expression","retraction":null,"screen_n_in":null,"score":{"opus":0.01146447177989992,"gpt":0.2446250041363504,"spread":0.2331605323564505,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002904351,0.0001941747,0.0002212088,0.00008602954,0.00009035509,0.00002234648,0.0001365035,0.0004977215,0.00001205816],"category_scores_gemma":[0.0000317932,0.0001943216,0.00007103344,0.00008997542,0.0001534132,0.000006554698,0.00004707161,0.0001457696,0.000006529034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003860773,"about_ca_system_score_gemma":0.00006868235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001605684,"about_ca_topic_score_gemma":0.0009567619,"domain_scores_codex":[0.9985649,0.0002095162,0.0003693782,0.0004777503,0.00005294853,0.0003255288],"domain_scores_gemma":[0.9993271,0.00001253181,0.0001488805,0.0003658403,0.00005704221,0.00008864741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004673607,0.00002440981,0.114021,0.00005227703,0.00001605582,5.566434e-7,0.00002180931,0.00003615854,0.8842764,0.001177015,0.0002379487,0.00008965463],"study_design_scores_gemma":[0.001555689,0.0001991448,0.9068105,0.00006294296,0.00002513758,0.0001012413,0.00005514647,0.0002149393,0.07278397,0.0003979733,0.01730365,0.0004896693],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935071,0.003192626,0.001907151,0.00001964346,0.0007714846,0.0004489573,0.00003492319,0.00002424887,0.00009380693],"genre_scores_gemma":[0.9984698,0.00001662111,0.0003230445,0.00002329325,0.000742552,0.00004645082,0.0002183594,0.00002521213,0.0001346712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8114924,"threshold_uncertainty_score":0.7924204,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2159184004","doi":"10.1186/s12918-014-0117-z","title":"A curated C. difficile strain 630 metabolic network: prediction of essential targets and inhibitors","year":2014,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Clostridium difficile and Clostridium perfringens research","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Sherbrooke","funders":"Université de Sherbrooke","keywords":"Clostridium difficile; Biology; Gene; Antibiotics; Strain (injury); Microbiology; Clostridium; Virulence; Computational biology; Organism; Model organism; Bacteria; Genetics","retraction":null,"screen_n_in":null,"score":{"opus":0.02422444213151222,"gpt":0.2810244811233744,"spread":0.2568000389918622,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006319298,0.0002008018,0.0006554634,0.0001640956,0.00008268376,0.00001584765,0.00008544639,0.0002836609,0.00004558181],"category_scores_gemma":[0.0003362352,0.0001602321,0.00009980107,0.000299939,0.000209886,0.00003233214,0.00008054036,0.0002083926,0.00001536994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003154423,"about_ca_system_score_gemma":0.0001294151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003783285,"about_ca_topic_score_gemma":0.00003388332,"domain_scores_codex":[0.998086,0.0002620507,0.0005885096,0.0003905483,0.0002072987,0.0004655681],"domain_scores_gemma":[0.9989038,0.0001879434,0.0002282386,0.0003097798,0.0001872177,0.0001830564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004634332,0.0002177265,0.08146263,0.0006538776,0.0002365274,0.000006131443,0.0001811932,0.0002319114,0.9046417,0.005180902,0.002695192,0.00402882],"study_design_scores_gemma":[0.02535786,0.008681455,0.2054743,0.001636607,0.001506483,0.001171872,0.003220142,0.124477,0.4446583,0.0003979465,0.1816651,0.001752886],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908258,0.005340557,0.001406174,0.00007144207,0.0007684994,0.0006524188,0.0001604344,0.0000781234,0.0006965101],"genre_scores_gemma":[0.9975463,0.000204051,0.00007599064,0.00001412749,0.001612847,0.00004677536,0.0002312633,0.00002434456,0.0002442904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4599833,"threshold_uncertainty_score":0.6534075,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2048939079","doi":"10.1186/1752-0509-3-20","title":"Using cell fate attractors to uncover transcriptional regulation of HL60 neutrophil differentiation","year":2009,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"National Institute of General Medical Sciences; National Institutes of Health","keywords":"Cellular differentiation; Cell fate determination; Biology; Acute promyelocytic leukemia; Retinoic acid; Cell biology; Cell; HL60; Cell type; Computational biology; Gene; Genetics; Transcription factor","retraction":null,"screen_n_in":null,"score":{"opus":0.02809685971942087,"gpt":0.2606957032679356,"spread":0.2325988435485147,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001583076,0.0001606109,0.0002589376,0.0001123416,0.00005021914,0.00001041423,0.0001258431,0.0002358461,0.00001262787],"category_scores_gemma":[0.00001187351,0.0001506073,0.0001549885,0.0001571448,0.00002981793,0.000004265589,0.00001844122,0.00003908394,0.000005247491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000033945,"about_ca_system_score_gemma":0.00005116026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004315068,"about_ca_topic_score_gemma":0.00002621339,"domain_scores_codex":[0.9987559,0.0001919414,0.0003922633,0.0003464789,0.000103419,0.0002100288],"domain_scores_gemma":[0.9992894,0.000009551269,0.0002053993,0.0003021138,0.0001226092,0.00007096001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00006159713,0.00004098467,0.02354302,0.00002080008,0.00003238822,9.499674e-8,0.0000168251,0.04146384,0.9343492,0.000288138,0.00008303628,0.0001000863],"study_design_scores_gemma":[0.001240721,0.0008477862,0.6158452,0.00004805225,0.0002104447,0.00001926648,0.00006786687,0.01175566,0.3629016,0.000253505,0.006210467,0.0005994106],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9471387,0.0007443658,0.0514319,0.00002054066,0.0003182806,0.0002123819,0.0000211018,0.000009774716,0.0001029752],"genre_scores_gemma":[0.9983073,0.00001429729,0.0007514593,0.00003843558,0.0003958399,0.00000585699,0.0002610808,0.00001315102,0.0002125741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5923022,"threshold_uncertainty_score":0.6141586,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2091451344","doi":"10.1186/1752-0509-1-17","title":"An in silico model of the ubiquitin-proteasome system that incorporates normal homeostasis and age-related decline","year":2007,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Ubiquitin and proteasome pathways","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ottawa; Health Canada; Ottawa Public Health","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Medical Research Council; Canadian Institutes of Health Research; Unilever","keywords":"Proteasome; Ubiquitin; Proteolysis; Cell biology; Systems biology; In silico; Biology; Protein degradation; Ubiquitin ligase; Chemistry; Biochemistry; Computational biology; Enzyme","retraction":null,"screen_n_in":null,"score":{"opus":0.0270920110565735,"gpt":0.2610538663135684,"spread":0.2339618552569949,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001492187,0.000237503,0.0003970127,0.0001149131,0.00008268602,0.00001941866,0.0003771875,0.0004846169,0.000002071049],"category_scores_gemma":[0.00006880031,0.0001738322,0.00008662001,0.0001805068,0.0002700356,0.000007945481,0.0002499158,0.0001508602,0.000002568983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002905244,"about_ca_system_score_gemma":0.0001041235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003342597,"about_ca_topic_score_gemma":0.0006563438,"domain_scores_codex":[0.9980344,0.0004024356,0.0005989,0.0004495823,0.0001139788,0.0004007336],"domain_scores_gemma":[0.998852,0.00005075756,0.000353529,0.0005477432,0.00008603685,0.0001099888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001850908,0.00006329999,0.1474784,0.0002901738,0.00003322457,0.000004742145,0.0001229385,0.0009199031,0.8464544,0.003669627,0.00001202499,0.0007660967],"study_design_scores_gemma":[0.00256925,0.0009202486,0.03322555,0.0003119033,0.00004596432,0.0002517276,0.001818327,0.01790535,0.9410732,0.0005138476,0.0006522792,0.0007122983],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931791,0.002746949,0.002353629,0.00002022922,0.0002446264,0.0007649381,0.0001054839,0.00002678388,0.0005582289],"genre_scores_gemma":[0.9990978,0.00004940389,0.0004173825,0.00005106692,0.0001190661,0.00005727888,0.0001006846,0.00002742926,0.00007987052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1142529,"threshold_uncertainty_score":0.7088673,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2141916481","doi":"10.1186/1752-0509-6-140","title":"A proof for loop-law constraints in stoichiometric metabolic networks","year":2012,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Azrieli Foundation","keywords":"Soundness; Constraint (computer-aided design); Computer science; Loop (graph theory); Metabolic network; Flux (metallurgy); Space (punctuation); Mathematical optimization; Mathematics; Chemistry; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.01786769928779158,"gpt":0.2581660535572926,"spread":0.240298354269501,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007092101,0.0001711436,0.0002937961,0.0001583028,0.00004082236,0.00001121871,0.0001266879,0.0002980233,0.00000402379],"category_scores_gemma":[0.0001589046,0.0001478249,0.0000820009,0.0002846459,0.000102014,0.00000450541,0.0000404013,0.00007773857,0.000004977835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001203979,"about_ca_system_score_gemma":0.00002945946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007882887,"about_ca_topic_score_gemma":0.0000373376,"domain_scores_codex":[0.9987381,0.0001244137,0.0003085962,0.0003125991,0.00003513486,0.0004811614],"domain_scores_gemma":[0.9994878,0.0000155602,0.00009502606,0.0002622924,0.00005880476,0.00008057001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008639567,0.0001500144,0.02112124,0.0001248663,0.0000862281,1.756428e-7,0.00002729643,0.001401121,0.955932,0.01619042,0.000499525,0.004380727],"study_design_scores_gemma":[0.003693279,0.0006309791,0.01338573,0.00007642598,0.0001176682,0.0003160388,0.0001749767,0.001963272,0.1907506,0.00004546903,0.7876145,0.00123106],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7836096,0.0508332,0.1587203,0.0000221568,0.004880298,0.001370798,0.00006515657,0.00004048841,0.0004580145],"genre_scores_gemma":[0.9961617,0.00009908771,0.0008825345,0.00004448388,0.002186122,0.0001804133,0.0001577239,0.00002208064,0.0002658818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.787115,"threshold_uncertainty_score":0.6028125,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1837138484","doi":"10.1186/s12918-015-0159-x","title":"Genome-scale resources for Thermoanaerobacterium saccharolyticum","year":2015,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Oak Ridge National Laboratory; Bioenergy Technologies Office; Biological and Environmental Research; Office of Science; UT-Battelle; Battelle; U.S. Department of Energy","keywords":"Genome; Biology; Xylose metabolism; Hemicellulose; Xylose; Computational biology; Gene; Genetics; Biochemistry; Cellulose; Fermentation","retraction":null,"screen_n_in":null,"score":{"opus":0.0312362229205171,"gpt":0.2279031533096432,"spread":0.1966669303891261,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002499894,0.0001146158,0.0001752285,0.00005870901,0.00003159859,0.00001960266,0.0001242226,0.000163281,0.00001440712],"category_scores_gemma":[0.00001434918,0.00009117802,0.00004887559,0.00006040679,0.00003770219,0.00003628314,0.0000213413,0.00005154837,0.0001247953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005180971,"about_ca_system_score_gemma":0.00001270058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002855123,"about_ca_topic_score_gemma":0.000006690029,"domain_scores_codex":[0.9993334,0.00004502408,0.0001823831,0.0001836878,0.00003960498,0.0002158629],"domain_scores_gemma":[0.9996045,0.00002063396,0.00003403082,0.0001970619,0.00005253177,0.00009120748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002781804,0.0000680083,0.01894163,0.001637517,0.0001759756,0.000001467509,0.001835575,0.002504715,0.9512922,0.0004976225,0.02154861,0.001218526],"study_design_scores_gemma":[0.0007350943,0.0001594885,0.002627287,0.00001103056,0.00001494759,0.0000246456,0.0007535308,0.004843711,0.00296629,0.00005509962,0.9875572,0.0002517243],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775171,0.003225612,0.009470064,0.0001199021,0.005251232,0.0006963163,0.0000541956,0.0005434509,0.003122172],"genre_scores_gemma":[0.9975228,0.00001778467,0.0003799305,0.00002734943,0.0009342326,0.00005512627,0.00003105273,0.0000216843,0.001010053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9660085,"threshold_uncertainty_score":0.3718132,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2129292461","doi":"10.1186/s12918-015-0190-y","title":"Genome-scale metabolic model of Rhodococcus jostii RHA1 (iMT1174) to study the accumulation of storage compounds during nitrogen-limited condition","year":2015,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Terry Fox Foundation; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Polyhydroxyalkanoates; Flux balance analysis; Glycogen; Rhodococcus; Systems biology; Biology; Chemistry; Computational biology; Biochemistry; Bacteria; Genetics; Enzyme","retraction":null,"screen_n_in":null,"score":{"opus":0.06489377148672268,"gpt":0.3055798407999291,"spread":0.2406860693132064,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006215443,0.0001672874,0.0003531245,0.0001119433,0.00005422661,0.000008796198,0.0002105892,0.0001450764,0.000001367447],"category_scores_gemma":[0.0001164718,0.000127041,0.00007541457,0.0001940202,0.00005833101,0.000005090458,0.00009878648,0.00006445883,0.000003496368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001703521,"about_ca_system_score_gemma":0.00005384129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001562834,"about_ca_topic_score_gemma":0.0000356827,"domain_scores_codex":[0.9986472,0.0002747304,0.0004619295,0.0003231076,0.0001005161,0.0001925066],"domain_scores_gemma":[0.9989399,0.000009257387,0.0002335739,0.0004770735,0.0002692922,0.0000709528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001272783,0.0001009778,0.00889828,0.00003443613,0.00009380652,1.003336e-7,0.0002970682,0.06438836,0.9259615,0.00004690253,0.00002491673,0.00002639321],"study_design_scores_gemma":[0.002618997,0.0009648991,0.05779908,0.00002468618,0.000219117,0.00004905132,0.001446881,0.00570819,0.9285078,0.00004966745,0.002139643,0.0004719966],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9837353,0.001364757,0.01350942,0.00001271341,0.0004611549,0.0007781319,0.00008939386,0.00001907016,0.00003012436],"genre_scores_gemma":[0.9988117,0.00001922572,0.0004815632,0.000008351167,0.0003666317,0.00005835247,0.0001585956,0.00001908821,0.00007654206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05868017,"threshold_uncertainty_score":0.5180581,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2017814498","doi":"10.1186/1752-0509-8-s3-s3","title":"Prediction of disease genes using tissue-specified gene-gene network","year":2014,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"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":"Program for New Century Excellent Talents in University; National Natural Science Foundation of China","keywords":"Gene regulatory network; Gene; Disease; Computational biology; Context (archaeology); Gene prediction; Biology; Biological network; Phenotype; Genetics; Bioinformatics; Gene expression; Pathology; Medicine; Genome","retraction":null,"screen_n_in":null,"score":{"opus":0.03017726675490346,"gpt":0.2423365511669398,"spread":0.2121592844120364,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004003996,0.0001782024,0.0002790336,0.00003762705,0.00008473821,0.00001416718,0.0001949501,0.0002696849,0.000006392259],"category_scores_gemma":[0.00002657652,0.0001592929,0.00008883874,0.00007620259,0.00009936972,0.000003021097,0.0001132372,0.00005308949,0.000007860906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001420749,"about_ca_system_score_gemma":0.00006852383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000381569,"about_ca_topic_score_gemma":0.00001184959,"domain_scores_codex":[0.9986557,0.0001708202,0.0004970118,0.0002909466,0.00006747332,0.0003180139],"domain_scores_gemma":[0.9990112,0.0000222103,0.0002687913,0.0004856317,0.00008721753,0.0001249814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005536785,0.00006422665,0.03809967,0.0002617663,0.0001820235,7.803581e-7,0.00003789079,0.05572928,0.8940775,0.004515579,0.002634495,0.003843071],"study_design_scores_gemma":[0.004700064,0.002530986,0.02412677,0.0002640113,0.0004160871,0.0001786739,0.0001800343,0.2681209,0.1632871,0.002932903,0.5313515,0.00191095],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5934759,0.007950778,0.3954145,0.000009816357,0.002030482,0.0004342945,0.000159669,0.00002389162,0.0005006727],"genre_scores_gemma":[0.9929271,0.000160194,0.003448543,0.00004673313,0.002602767,0.00002099422,0.0005886724,0.00002321407,0.0001817648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7307904,"threshold_uncertainty_score":0.6495776,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2168281812","doi":"10.1186/1752-0509-1-36","title":"Facile: a command-line network compiler for systems biology","year":2007,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Computer science; Scripting language; Compiler; Perl; Systems biology; Modelling biological systems; Line (geometry); Bifurcation; Simple (philosophy); MATLAB; Programming language; Theoretical computer science; Bioinformatics; Biology; Nonlinear system; Mathematics; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.02887046295059158,"gpt":0.2911497765064473,"spread":0.2622793135558557,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001827172,0.0004198786,0.0008109765,0.0001273316,0.0002324162,0.0000349539,0.000484425,0.0008472247,0.0000110429],"category_scores_gemma":[0.00009347911,0.0003665816,0.0003320842,0.0002588484,0.0002309301,0.000003110369,0.0001848662,0.00013028,0.00003723682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005159287,"about_ca_system_score_gemma":0.0001014874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001434291,"about_ca_topic_score_gemma":0.0003767797,"domain_scores_codex":[0.9966332,0.0004454526,0.0009358622,0.0008470836,0.0000912343,0.001047185],"domain_scores_gemma":[0.9979936,0.0002080556,0.0004249315,0.0008797296,0.0002818339,0.000211791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001387516,0.0002789707,0.4315229,0.0006638908,0.002023789,0.000008053489,0.0000610257,0.07112841,0.396569,0.02415984,0.07012047,0.002076121],"study_design_scores_gemma":[0.002329334,0.001306755,0.00249551,0.00006415438,0.0002020208,0.0001490211,0.0002326924,0.009400994,0.003621544,0.0001939902,0.9790534,0.0009506007],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4947713,0.02786318,0.4693958,0.00004660854,0.004663177,0.001850373,0.000272166,0.000109145,0.001028217],"genre_scores_gemma":[0.9906499,0.0001080121,0.001064647,0.0001295151,0.004529768,0.0002132592,0.001738648,0.00005924566,0.001506993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9089329,"threshold_uncertainty_score":0.9998786,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2798373489","doi":"10.1186/s12918-018-0573-y","title":"Improved flower pollination algorithm for identifying essential proteins","year":2018,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"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":"Pollination; Identification (biology); Computational biology; Computer science; Systems biology; Biology; Biological data; Interaction network; Gene; Algorithm; Machine learning; Bioinformatics; Genetics; Pollen; Botany","retraction":null,"screen_n_in":null,"score":{"opus":0.01593089043892229,"gpt":0.3077845931180571,"spread":0.2918537026791348,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004589029,0.0001676167,0.000186554,0.00007031862,0.0001627794,0.00004753005,0.0002246199,0.000315333,0.00001300722],"category_scores_gemma":[0.0002344789,0.0001493192,0.00009713849,0.0000697297,0.000119645,0.000005859112,0.0001044471,0.00006959607,0.0000291861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001975185,"about_ca_system_score_gemma":0.00007893817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007660689,"about_ca_topic_score_gemma":0.00008801717,"domain_scores_codex":[0.9988215,0.0001090106,0.0003757742,0.0003135018,0.00006354736,0.0003166409],"domain_scores_gemma":[0.9991041,0.00002315768,0.0002279322,0.0003346945,0.0002553936,0.00005472084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001096042,0.00006091549,0.00138873,0.0002528573,0.0001262319,2.638486e-7,0.0001691993,0.00002171523,0.9856738,0.001292524,0.001710596,0.009193511],"study_design_scores_gemma":[0.004029221,0.002968803,0.0006962933,0.0000933945,0.00008817117,0.000122809,0.0004710883,0.4650041,0.2886423,0.000163995,0.2366022,0.001117574],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05314318,0.0002175156,0.9430481,0.00002714611,0.001919781,0.001013554,0.00007751663,0.00004394421,0.0005093113],"genre_scores_gemma":[0.9047892,0.000007049544,0.08836946,0.0000903859,0.003556434,0.0003178752,0.0008398559,0.000042321,0.001987384],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8546786,"threshold_uncertainty_score":0.608906,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2626271019","doi":"10.1186/s12918-017-0438-9","title":"Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes","year":2017,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Adipose Tissue and Metabolism","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Institut universitaire de cardiologie et de pneumologie de Québec; Université Laval; Université de Montréal; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adipose tissue; Adipocyte; Type 2 diabetes; Biology; In silico; Obesity; Diabetes mellitus; Endocrinology; Internal medicine; Gene; Genetics; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.07524577428097552,"gpt":0.3581923635081294,"spread":0.2829465892271539,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003957722,0.00007718927,0.0003708423,0.00004397447,0.0000549807,0.000004015316,0.0001141693,0.0001330656,0.000004667315],"category_scores_gemma":[0.0003650203,0.00005174329,0.00005150199,0.00004120661,0.00007441967,0.00006155093,0.00002753907,0.00004850293,0.000002436372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001397144,"about_ca_system_score_gemma":0.00003866281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004193461,"about_ca_topic_score_gemma":0.00008721861,"domain_scores_codex":[0.9992449,0.00008093064,0.0003465782,0.0001428621,0.00005432768,0.0001304001],"domain_scores_gemma":[0.9989355,0.0001350694,0.0003476308,0.0004370472,0.0001280753,0.00001666042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002508335,0.0001173086,0.09030084,0.001075855,0.0001371665,5.285495e-7,0.0008282019,0.001565737,0.8797226,0.009527209,0.00009365176,0.01638009],"study_design_scores_gemma":[0.01035292,0.0034061,0.5908519,0.002603762,0.001250886,0.00002642403,0.001128786,0.1945005,0.1268015,0.007463063,0.06098682,0.0006273424],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9791965,0.009901582,0.008928597,0.00005342957,0.0006572478,0.001041514,0.00001075848,0.000008861019,0.0002015109],"genre_scores_gemma":[0.9982237,0.0001051083,0.000795761,0.000007434245,0.0002479367,0.00003525062,0.00002770688,0.00001072055,0.0005463902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7529211,"threshold_uncertainty_score":0.211003,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2043393386","doi":"10.1186/1752-0509-4-143","title":"Information propagation within the Genetic Network of Saccharomyces cerevisiae","year":2010,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary; University of Toronto","funders":"Academy of Finland","keywords":"Saccharomyces cerevisiae; Gene regulatory network; Gene; Cluster analysis; Core (optical fiber); Computational biology; Systems biology; Biology; Microarray; Genetics; Computer science; Gene expression; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.006906055701127504,"gpt":0.2196079605086411,"spread":0.2127019048075136,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005543416,0.0001325922,0.000200222,0.00003085036,0.00008768932,0.00002147355,0.000272614,0.0002358806,0.000009592321],"category_scores_gemma":[0.00009566223,0.00008822729,0.00009505743,0.0001604756,0.0001322809,0.000005564025,0.000075691,0.00009153723,0.00001802363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006017856,"about_ca_system_score_gemma":0.0001020538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005952697,"about_ca_topic_score_gemma":0.0001793186,"domain_scores_codex":[0.9988652,0.0002217868,0.0004850934,0.0001563259,0.00008489083,0.0001867264],"domain_scores_gemma":[0.9987913,0.00002511556,0.0004540193,0.0005170418,0.0001730182,0.00003945224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00008429902,0.00002940103,0.3362973,0.0001902255,0.0002698094,1.854664e-7,0.0001653555,0.03550553,0.6134305,0.008144973,0.003041334,0.002841098],"study_design_scores_gemma":[0.00341137,0.002020154,0.4507625,0.0002093839,0.0008157226,0.0005093021,0.001986024,0.06506851,0.1785388,0.002281604,0.2920382,0.002358451],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882455,0.001247322,0.008950195,0.00003471579,0.0008336793,0.0003917288,0.000007912785,0.00001241288,0.0002765566],"genre_scores_gemma":[0.9978909,0.00002691721,0.00098617,0.00003784548,0.0008052452,0.00005270728,0.0001225677,0.000009612075,0.00006802011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4348917,"threshold_uncertainty_score":0.3597804,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2594366819","doi":"10.1186/s12918-017-0411-7","title":"Systems biology combining human- and animal-data miRNA and mRNA data identifies new targets in ureteropelvic junction obstruction","year":2017,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Pediatric Urology and Nephrology Studies","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Hôtel-Dieu de Québec; Université Laval","funders":"Seventh Framework Programme; Fondation du Rein; Université de La Réunion; Fondation pour la Recherche Médicale; Institut National de la Santé et de la Recherche Médicale; Université Laval","keywords":"Systems biology; microRNA; Biology; Messenger RNA; Computational biology; Developmental biology; Cell biology; Genetics; Gene","retraction":null,"screen_n_in":null,"score":{"opus":0.140860536118812,"gpt":0.3633006117878476,"spread":0.2224400756690355,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001007506,0.00026294,0.0008062565,0.0002326445,0.0005315634,0.00005615203,0.00052608,0.0005678805,0.000005124326],"category_scores_gemma":[0.0005567953,0.0002164234,0.00002135001,0.00006029679,0.0007077602,0.0002996404,0.001139691,0.0003254451,0.00001378747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002800583,"about_ca_system_score_gemma":0.00007240163,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007344034,"about_ca_topic_score_gemma":0.001644297,"domain_scores_codex":[0.9975799,0.0003898981,0.0005785803,0.0009856875,0.00006249719,0.0004033933],"domain_scores_gemma":[0.9975569,0.0002261505,0.0004832472,0.00156537,0.00005945903,0.0001088438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003397522,0.00003155348,0.9816344,0.0002170947,0.0003084623,0.00002500905,0.0001671509,4.492505e-7,0.01287579,0.0006363208,0.00338071,0.0003832568],"study_design_scores_gemma":[0.004257235,0.0008591662,0.9783508,0.00008090496,0.0004272561,0.001050565,0.0006056299,0.001581328,0.0000246151,0.0003275109,0.01212365,0.0003113467],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9590213,0.03631334,0.0001649253,0.0005477543,0.002995789,0.0005760013,0.00007990231,0.00006634543,0.0002346465],"genre_scores_gemma":[0.9965091,0.001305099,0.00008274928,0.00006513638,0.001035585,0.00002355789,0.0005693569,0.00001756035,0.0003917957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03748787,"threshold_uncertainty_score":0.9992661,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2145833938","doi":"10.1186/1752-0509-5-169","title":"Removing bias against membrane proteins in interaction networks","year":2011,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Canadian Institutes of Health Research; Terry Fox Research Institute; Ontario Institute for Cancer Research; McMaster University","keywords":"Interaction network; Systems biology; Protein Interaction Networks; Protein–protein interaction; Computational biology; Biology; Membrane protein; Saccharomyces cerevisiae; Subnetwork; Biological network; Interactome; Drug target; Computer science; Yeast; Cell biology; Gene; Genetics; Membrane; Biochemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.04346742911988573,"gpt":0.2466257386540686,"spread":0.2031583095341828,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005014851,0.0001764997,0.0002330201,0.00008286367,0.0000478612,0.00001827318,0.0002039493,0.0003855498,0.00001074757],"category_scores_gemma":[0.00005043139,0.000154982,0.00007534884,0.00009910628,0.00005670757,0.000005791225,0.0001121757,0.0001576508,0.00002069259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002753341,"about_ca_system_score_gemma":0.00004702774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002819595,"about_ca_topic_score_gemma":0.0005058252,"domain_scores_codex":[0.9986715,0.0001711468,0.0004812924,0.0002926787,0.00003915754,0.0003442256],"domain_scores_gemma":[0.9993024,0.00001918225,0.0002126094,0.0003580759,0.0000429359,0.00006479418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002361349,0.0007742743,0.3217622,0.001025078,0.0006247828,0.00005006226,0.002482459,0.03165131,0.56506,0.0169688,0.005022381,0.05221732],"study_design_scores_gemma":[0.01338476,0.005195721,0.05136536,0.001834836,0.000157697,0.001059599,0.007397024,0.5418533,0.0671052,0.0015278,0.3026435,0.006475167],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8972754,0.001964603,0.07937695,0.00001419955,0.002144413,0.0009421143,0.00001082392,0.00004039974,0.01823106],"genre_scores_gemma":[0.9977738,0.000134026,0.001020835,0.0001152874,0.0004749737,0.00006895619,0.0001345025,0.00002021645,0.0002573525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.510202,"threshold_uncertainty_score":0.6319982,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2144670484","doi":"10.1186/s12918-014-0086-2","title":"Proteomics-based metabolic modeling and characterization of the cellulolytic bacterium Thermobifida fusca","year":2014,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"Genome Canada","keywords":"Bioprocess; Cellobiose; Metabolic network; Proteomics; Metabolic engineering; Metabolic flux analysis; Biology; Organism; Metabolic pathway; Computational biology; Bioconversion; Metabolomics; Biomass (ecology); Biofuel; Biotechnology; Systems biology; Model organism; Biochemical engineering; Biochemistry; Metabolism; Bioinformatics; Gene; Fermentation; Enzyme; Genetics; Ecology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.007596577772188778,"gpt":0.1912795707676538,"spread":0.183682992995465,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002847736,0.000119615,0.0001860894,0.000033475,0.00004366616,0.00001056331,0.0001174297,0.0001482338,0.000001350242],"category_scores_gemma":[0.00005435383,0.00008152713,0.0000520711,0.00006448686,0.00005401958,0.000002142506,0.00004285012,0.00004757345,0.000001155018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003428261,"about_ca_system_score_gemma":0.00003095533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004484783,"about_ca_topic_score_gemma":0.00000444694,"domain_scores_codex":[0.9991905,0.00016659,0.0002269544,0.0002455133,0.00003388723,0.0001365432],"domain_scores_gemma":[0.9994683,0.000003437607,0.0001241497,0.000316398,0.00006223193,0.0000255363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002088226,0.00001076646,0.001346966,0.00007663011,0.00001228862,6.63461e-9,0.00001100451,0.0006764804,0.9974412,0.0002194627,0.000001952938,0.0001823639],"study_design_scores_gemma":[0.0003502474,0.00008490168,0.004840218,0.00003108966,0.00002768433,0.00001074135,0.000008659114,0.02729247,0.9607447,0.00000718264,0.006448545,0.0001535538],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9487216,0.0003618226,0.04983139,0.00002862017,0.0006929429,0.0003114119,0.00001634021,0.00001166001,0.00002421422],"genre_scores_gemma":[0.9989157,0.00003583074,0.0003106314,0.00002522101,0.0004857003,0.00003020707,0.00006851885,0.00001513641,0.0001130933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05019407,"threshold_uncertainty_score":0.332458,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2131067027","doi":"10.1186/1752-0509-3-63","title":"The Symbiosis Interactome: a computational approach reveals novel components, functional interactions and modules in Sinorhizobium meliloti","year":2009,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Legume Nitrogen Fixing Symbiosis","field":"Agricultural and Biological Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"SickKids Foundation","funders":"Canadian Institutes of Health Research; Universität Bielefeld","keywords":"Interactome; Biology; Symbiosis; Computational biology; Sinorhizobium meliloti; Systems biology; Genetics; Gene; Bacteria","retraction":null,"screen_n_in":null,"score":{"opus":0.04125386431900009,"gpt":0.2422568134273476,"spread":0.2010029491083475,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004053112,0.000182625,0.0002637756,0.00004204135,0.0002975919,0.0001123307,0.0002199991,0.0001177293,0.0000139683],"category_scores_gemma":[0.00009805689,0.00007052689,0.00007950242,0.0002702612,0.0001048682,0.000119228,0.00006708691,0.0001792094,0.00002085575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007387561,"about_ca_system_score_gemma":0.000009241873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004810075,"about_ca_topic_score_gemma":0.0001939916,"domain_scores_codex":[0.9984481,0.0002740918,0.000445364,0.0003969777,0.0001288559,0.0003066366],"domain_scores_gemma":[0.9986122,0.0009666778,0.0001758671,0.00007689863,0.00009567507,0.00007269378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001840116,0.0004242563,0.1321954,0.00001748306,0.00006185105,8.148911e-7,0.00009251029,0.00004279217,0.845581,0.01861883,0.0008893251,0.001891778],"study_design_scores_gemma":[0.0004024032,0.0002113053,0.9933862,0.00005205096,0.00001375072,0.0001258811,0.0004381795,0.002352558,0.0002306326,0.001120911,0.001421234,0.0002448644],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970654,0.0005898457,0.0001330933,0.000924008,0.000470711,0.0003547107,0.00007593213,0.00005982641,0.0003265077],"genre_scores_gemma":[0.9986926,0.000007188166,0.0004475498,0.0001754484,0.0002520506,0.00005203234,0.0002494399,0.00000141262,0.0001222708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8611909,"threshold_uncertainty_score":0.2876003,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1973847338","doi":"10.1186/1752-0509-3-106","title":"Using the ratio of means as the effect size measure in combining results of microarray experiments","year":2009,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Public Health Ontario; University of Toronto; Institute for Clinical Evaluative Sciences; SickKids Foundation; Hospital for Sick Children","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Canada; Canadian Institutes of Health Research; Mitacs; Ontario Genomics; Ontario Genomics Institute","keywords":"Sample size determination; Measure (data warehouse); Random effects model; Statistics; Computer science; Data mining; Mathematics; Meta-analysis; Medicine; Internal medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.03625531079274392,"gpt":0.3191261644087999,"spread":0.282870853616056,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000663495,0.00009848156,0.0001830554,0.0000255648,0.00004573916,0.00000600416,0.0002253458,0.000139951,0.000001518316],"category_scores_gemma":[0.0002478044,0.0000546067,0.00006066315,0.00009997984,0.00008589923,0.000001614061,0.00002746949,0.00005592189,6.707641e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001291932,"about_ca_system_score_gemma":0.00006750623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001362523,"about_ca_topic_score_gemma":0.00001994632,"domain_scores_codex":[0.9985893,0.0006504254,0.0003598212,0.0002031231,0.00007429474,0.0001230793],"domain_scores_gemma":[0.9991774,0.00008143861,0.0002670198,0.0003975149,0.00005944696,0.00001721077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002756617,0.00001892627,0.0033755,0.00001172169,0.00001437282,8.080078e-8,0.0002454925,0.0002281498,0.9953172,0.0001717388,0.0001730119,0.0001681834],"study_design_scores_gemma":[0.001263901,0.0005017582,0.003357857,0.00006808263,0.00001040742,0.000008131512,0.000725953,0.0001891799,0.9915367,0.00001967099,0.002241937,0.00007645558],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993539,0.00274534,0.001722486,0.0001001942,0.0003034393,0.0004433602,0.00000861509,0.000003646605,0.001133918],"genre_scores_gemma":[0.9996362,0.000018525,0.00008504969,0.0000508046,0.00007039341,0.00002194505,0.00001498986,0.000005470338,0.00009667739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006097144,"threshold_uncertainty_score":0.2226797,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2021487982","doi":"10.1186/1752-0509-7-22","title":"Novel semantic similarity measure improves an integrative approach to predicting gene functional associations","year":2013,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto; Ontario Institute for Cancer Research","funders":"","keywords":"Semantic similarity; Computer science; Similarity (geometry); Gene ontology; Set (abstract data type); Annotation; Interactome; In silico; Measure (data warehouse); Gene regulatory network; Computational biology; Data mining; Biology; Artificial intelligence; Gene; Genetics","retraction":null,"screen_n_in":null,"score":{"opus":0.02504016857509755,"gpt":0.2374407114180293,"spread":0.2124005428429317,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004391273,0.0002093277,0.000257713,0.00005515249,0.0001714021,0.00006743085,0.0002136304,0.0003966227,0.000004885513],"category_scores_gemma":[0.0001345565,0.0001678449,0.00008791961,0.0001007844,0.00005507211,0.00001157457,0.0001187349,0.0001492717,0.00002372103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004192613,"about_ca_system_score_gemma":0.0001139626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004418099,"about_ca_topic_score_gemma":0.0001595906,"domain_scores_codex":[0.9986551,0.0001220845,0.000401518,0.0003869316,0.00009307408,0.0003412929],"domain_scores_gemma":[0.9990317,0.00003021096,0.0001884879,0.0003435377,0.0002558421,0.0001501806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003452495,0.0002097591,0.01996429,0.00005387287,0.000242472,6.521014e-8,0.0003433303,0.001955536,0.9703988,0.002126879,0.003555194,0.001115303],"study_design_scores_gemma":[0.007222489,0.0048003,0.3815294,0.0002140612,0.0004136302,0.0004474212,0.01273318,0.536658,0.02820096,0.002209505,0.0209509,0.004620153],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.349492,0.0003567901,0.6456949,0.00005098736,0.0008138758,0.0009559711,0.0001671015,0.00003878515,0.002429533],"genre_scores_gemma":[0.9886492,0.000004710519,0.008506202,0.0002407316,0.0008992587,0.0002274491,0.001049687,0.00001978367,0.0004030052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9421978,"threshold_uncertainty_score":0.6844515,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2119673989","doi":"10.1186/1752-0509-8-38","title":"Gene co-citation networks associated with worker sterility in honey bees","year":2014,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Insect and Arachnid Ecology and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Gene; Honey bee; Gene regulatory network; Genetics; Evolutionary biology; Gene expression; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.01574453719996572,"gpt":0.2548697135368471,"spread":0.2391251763368814,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005723602,0.0001480174,0.0002371486,0.00004973,0.00007718466,0.00001282558,0.000113028,0.0004508488,0.00001027259],"category_scores_gemma":[0.00008183296,0.000117798,0.00004285749,0.0000910549,0.0001089709,0.000003438825,0.00002864706,0.0001041007,0.000009569568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001985547,"about_ca_system_score_gemma":0.0000351093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005441773,"about_ca_topic_score_gemma":0.001033272,"domain_scores_codex":[0.9986207,0.0004652657,0.0002498911,0.0003230949,0.000039251,0.0003018076],"domain_scores_gemma":[0.9995114,0.00005264732,0.0001296191,0.0002065787,0.00005688265,0.0000428513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002848819,0.00008870455,0.8857934,0.000008572072,0.00002770837,0.000001531327,0.0000234529,0.0005024873,0.1127244,0.00006579162,0.0001753497,0.0003036993],"study_design_scores_gemma":[0.001703648,0.001045898,0.9799008,0.00004091532,0.0000296179,0.00002441338,0.00007618788,0.001595616,0.01347355,0.00002317404,0.001703403,0.0003827762],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932376,0.0002645054,0.005525162,0.00001097166,0.0003941562,0.0002466952,0.00001286523,0.00001916011,0.0002888886],"genre_scores_gemma":[0.9984477,0.00001154758,0.00008424452,0.00009722865,0.0002584926,0.00008511251,0.0006991515,0.0000131372,0.0003033787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09925084,"threshold_uncertainty_score":0.4803665,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2516458341","doi":"10.1186/s12918-016-0312-1","title":"Structured sparse CCA for brain imaging genetics via graph OSCAR","year":2016,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; Canadian Institutes of Health Research; Scheme for Promotion of Academic and Research Collaboration; University of Pennsylvania; U.S. National Library of Medicine; National Institute on Aging; University of Texas at Arlington; U.S. Department of Defense; National Institutes of Health; National Science Foundation","keywords":"Canonical correlation; Pairwise comparison; Correlation; Multivariate statistics; Imaging genetics; Artificial intelligence; Pattern recognition (psychology); Computer science; Graph; Genome-wide association study; Lasso (programming language); Computational biology; Mathematics; Neuroimaging; Machine learning; Biology; Single-nucleotide polymorphism; Genetics; Gene","retraction":null,"screen_n_in":null,"score":{"opus":0.04917084578615508,"gpt":0.28287425451385,"spread":0.2337034087276949,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003270094,0.0001958427,0.0002901573,0.0001308649,0.0001999196,0.00002149977,0.0002456693,0.00009524731,0.00001009147],"category_scores_gemma":[0.005285795,0.0001305734,0.0001088501,0.0001446152,0.0002709772,0.00006215661,0.0001049656,0.00005017088,0.00004449178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005833089,"about_ca_system_score_gemma":0.00004425142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000350025,"about_ca_topic_score_gemma":0.00008157574,"domain_scores_codex":[0.9981783,0.0003598929,0.0002773168,0.0006675229,0.000102273,0.0004147208],"domain_scores_gemma":[0.9917722,0.007584329,0.0001508292,0.0003521263,0.00007965622,0.00006084704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006214843,0.00001437786,0.03296143,0.00004528374,0.00001433639,0.000001883016,0.00003962159,0.00002106141,0.9478263,0.009670247,0.007295405,0.002047885],"study_design_scores_gemma":[0.007697811,0.001145856,0.03722452,0.0002007007,0.00008643639,0.0007652271,0.0003371626,0.005246452,0.3595383,0.06081919,0.5249648,0.001973582],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6131279,0.001706704,0.3601485,0.008922378,0.01202034,0.002323068,0.0005826174,0.0004506641,0.0007177886],"genre_scores_gemma":[0.9972019,0.00001244757,0.0004393838,0.001127529,0.000526492,0.0001660733,0.000002902893,0.00002676944,0.0004964625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5882881,"threshold_uncertainty_score":0.6327972,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2172187648","doi":"10.1186/1752-0509-8-46","title":"Combining test statistics and models in bootstrapped model rejection: it is a balancing act","year":2014,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Engineering Link (Canada)","funders":"Novo Nordisk Fonden; Vetenskapsrådet; Bundesministerium für Bildung und Forschung; European Commission","keywords":"Bootstrapping (finance); Computer science; Parametric statistics; Extension (predicate logic); Dimension (graph theory); Statistical hypothesis testing; Nonparametric statistics; Curse of dimensionality; Value (mathematics); Feature (linguistics); Statistics; Mathematics; Econometrics","retraction":null,"screen_n_in":null,"score":{"opus":0.01911938747784012,"gpt":0.2540747617919151,"spread":0.234955374314075,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004489889,0.0001825097,0.0003235272,0.00008510383,0.00006927925,0.00002317293,0.000119908,0.0002691606,0.00000256702],"category_scores_gemma":[0.00006995138,0.0001783296,0.00004852204,0.0001041923,0.00007157402,0.000003942343,0.00008178368,0.00008521842,0.000003360098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002248418,"about_ca_system_score_gemma":0.00007326835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001162538,"about_ca_topic_score_gemma":0.0003915661,"domain_scores_codex":[0.9986206,0.0001808263,0.0003671944,0.0004648827,0.00006599969,0.0003005302],"domain_scores_gemma":[0.9993077,0.00007200316,0.0001425333,0.0003339099,0.00006543485,0.00007845549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009611162,0.0001049363,0.5181378,0.0002470995,0.000178273,0.000002600837,0.0003220033,0.2508946,0.2186818,0.00291292,0.007180871,0.001240985],"study_design_scores_gemma":[0.0006711254,0.0002077769,0.002086153,0.00003620663,0.00003275696,0.00003384418,0.0001145402,0.9926712,0.001043099,0.0006848836,0.002152337,0.0002660741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6542764,0.001176175,0.343149,0.00005921704,0.0001440763,0.0002137269,0.00004667755,0.00001943527,0.0009153697],"genre_scores_gemma":[0.9964142,0.00009860829,0.002594469,0.0001655325,0.0001708173,0.00002919436,0.00009250302,0.00002203704,0.0004125673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7417766,"threshold_uncertainty_score":0.7272069,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2127073015","doi":"10.1186/1752-0509-6-112","title":"Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study","year":2012,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Genome Canada; University of Toronto; University of Calgary","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada","keywords":"Prostate cancer; microRNA; Computational biology; Cancer; Biology; Bioinformatics; Gene; Genetics","retraction":null,"screen_n_in":null,"score":{"opus":0.02091149046867685,"gpt":0.2858784713948351,"spread":0.2649669809261582,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003304964,0.0001568848,0.0001811204,0.00006588633,0.00007504228,0.00001074576,0.0000694399,0.000152243,0.000008286715],"category_scores_gemma":[0.00008531249,0.000138126,0.00005327521,0.00009380486,0.0000487572,0.000009334822,0.00006374609,0.00008454615,0.000005049621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000571593,"about_ca_system_score_gemma":0.00005880928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001524897,"about_ca_topic_score_gemma":0.0002800346,"domain_scores_codex":[0.9987074,0.0003295855,0.0003542504,0.0002917066,0.0000634926,0.0002535723],"domain_scores_gemma":[0.9991626,0.00002945691,0.0003268393,0.0002693303,0.0001459002,0.00006587382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002958296,0.0002052296,0.1986492,0.00008180579,0.0001059999,0.00000576808,0.0001049029,0.01147102,0.7883255,0.0000311962,0.00003915249,0.0006844276],"study_design_scores_gemma":[0.005996628,0.004174951,0.4306305,0.000681303,0.0002855639,0.00323405,0.006392471,0.002567359,0.5397643,0.00001977914,0.004695384,0.001557742],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954794,0.001204211,0.0014947,0.000003878709,0.0006943986,0.001075285,0.00002164167,0.00001539371,0.00001109502],"genre_scores_gemma":[0.9987859,0.00000493889,0.00005070466,0.00001330651,0.0006048295,0.0004075376,0.00004526404,0.00001963019,0.0000679613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2485612,"threshold_uncertainty_score":0.5632616,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2037935034","doi":"10.1186/s12918-015-0153-3","title":"Predicting internal cell fluxes at sub-optimal growth","year":2015,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of Illinois at Urbana-Champaign; McMaster University; National Science Foundation","keywords":"Flux balance analysis; Multicellular organism; Biomass (ecology); Dilution; Systems biology; Biochemical engineering; Flux (metallurgy); Biological system; Function (biology); Metabolic engineering; Metabolic flux analysis; Biology; Computational biology; Chemistry; Metabolism; Ecology; Evolutionary biology; Gene; Physics; Genetics; Biochemistry; Thermodynamics","retraction":null,"screen_n_in":null,"score":{"opus":0.01269482336113309,"gpt":0.2168918068780792,"spread":0.2041969835169461,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003208722,0.0001537742,0.0001754564,0.00004646129,0.00004247707,0.00001457391,0.000151713,0.0002134122,0.000002778282],"category_scores_gemma":[0.0001305109,0.0001309002,0.00006208508,0.00005550359,0.00005124531,0.000002595976,0.0001318757,0.00007053796,0.0000474441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002979366,"about_ca_system_score_gemma":0.00004442231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001889878,"about_ca_topic_score_gemma":0.00002855652,"domain_scores_codex":[0.9989842,0.0001077622,0.0002353889,0.0003637293,0.00005414411,0.0002547643],"domain_scores_gemma":[0.999456,0.000004677301,0.00009536943,0.000231686,0.0001084289,0.0001038025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006386756,0.00001958572,0.04441987,0.00003808827,0.00001947653,6.855973e-7,0.00003135269,0.0003048194,0.9509974,0.00004436976,0.004012852,0.00004761702],"study_design_scores_gemma":[0.0007334166,0.0004440779,0.001116944,0.00001989136,0.00002055731,0.000237906,0.0001016616,0.0004404981,0.9076591,0.000004438585,0.08895057,0.0002709303],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884816,0.003458082,0.004769837,0.00001624241,0.0024242,0.000143039,0.00002171697,0.00004485638,0.0006404438],"genre_scores_gemma":[0.9950482,0.0000678245,0.0004521892,0.00002153017,0.002136481,0.00001866981,0.0001261945,0.00001995668,0.002108982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08493772,"threshold_uncertainty_score":0.5337957,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2089539551","doi":"10.1186/1752-0509-7-87","title":"Modularity and evolutionary constraints in a baculovirus gene regulatory network","year":2013,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Viral Infectious Diseases and Gene Expression in Insects","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; CancerCare Manitoba Foundation","keywords":"Biology; ORFS; Genetics; Gene; Genome; Gene regulatory network; Computational biology; Systems biology; Open reading frame; Gene expression","retraction":null,"screen_n_in":null,"score":{"opus":0.01113880836845419,"gpt":0.2396480022588915,"spread":0.2285091938904373,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000161839,0.0001559526,0.0001993581,0.00004279587,0.00008223984,0.00002055788,0.0001009357,0.0002949582,0.00004929926],"category_scores_gemma":[0.00005220569,0.000139467,0.0000584618,0.00006833974,0.0002244622,0.000005317713,0.0001299854,0.00007566618,0.00002899963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001876676,"about_ca_system_score_gemma":0.00006660294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004622498,"about_ca_topic_score_gemma":0.00005490618,"domain_scores_codex":[0.9987105,0.0002512485,0.0002713106,0.0004060934,0.0000502011,0.0003107055],"domain_scores_gemma":[0.9994291,0.00002130081,0.00008591847,0.0002908196,0.0000603953,0.0001124763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00006537278,0.00008674598,0.4707005,0.00006203479,0.00005458956,0.000003610782,0.00001604835,0.001410089,0.5098162,0.001462095,0.01467181,0.001650972],"study_design_scores_gemma":[0.002680137,0.0007681955,0.964545,0.000139902,0.00002762025,0.0002991788,0.0001738597,0.003182309,0.006781018,0.004428509,0.01599314,0.0009811439],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886002,0.00823372,0.001280195,0.00001777474,0.0005628402,0.0004263161,0.00002791827,0.0000191621,0.0008318551],"genre_scores_gemma":[0.9982966,0.0001278859,0.000469657,0.0001391074,0.0004962619,0.0001667818,0.00009287347,0.0000136158,0.0001971822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5030351,"threshold_uncertainty_score":0.5687298,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2151484461","doi":"10.1186/1752-0509-8-60","title":"Gene perturbation and intervention in context-sensitive stochastic Boolean networks","year":2014,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Systems biology; Gene regulatory network; Perturbation (astronomy); Computational biology; Context (archaeology); Computer science; Theoretical computer science; Biological network; Boolean network; Intervention (counseling); Biology; Statistical physics; Mathematics; Gene; Psychology; Genetics; Algorithm; Physics; Boolean function; Gene expression","retraction":null,"screen_n_in":null,"score":{"opus":0.008619950761029931,"gpt":0.2289871581378344,"spread":0.2203672073768045,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005072709,0.0001467221,0.0002499832,0.00008048699,0.00004214371,0.00001616646,0.00007502078,0.0002419101,0.000001977771],"category_scores_gemma":[0.0001001489,0.0001375408,0.00007633127,0.00007802756,0.00008073258,0.000002569543,0.00006878492,0.00006267949,0.000004201146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002234596,"about_ca_system_score_gemma":0.00001316389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001065188,"about_ca_topic_score_gemma":0.0006801193,"domain_scores_codex":[0.9985531,0.0005009564,0.000301134,0.0003868006,0.00004030414,0.0002177071],"domain_scores_gemma":[0.9994657,0.00004503362,0.0001399846,0.0002283602,0.00006462791,0.00005627879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009931448,0.0003159883,0.2508439,0.0002812698,0.0008333815,0.000006325825,0.0004923768,0.2781619,0.3973589,0.009333369,0.001061055,0.06031836],"study_design_scores_gemma":[0.004244153,0.001481047,0.08317891,0.0002065967,0.0001767231,0.0001947383,0.001099765,0.8959492,0.007352977,0.0004040126,0.004640097,0.001071753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7421773,0.003094494,0.2542111,0.00001299521,0.0002461809,0.0001867274,0.00000299425,0.000009430915,0.0000587816],"genre_scores_gemma":[0.9988821,0.00003134912,0.00008651295,0.00005282641,0.000446311,0.00003131028,0.0001904115,0.00001552094,0.0002636891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6177873,"threshold_uncertainty_score":0.5608753,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2763400143","doi":"10.1186/s12918-018-0597-3","title":"Short linear motifs in intrinsically disordered regions modulate HOG signaling capacity","year":2018,"lang":"en","type":"article","venue":"BMC Systems Biology","topic":"Developmental Biology and Gene Regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Biology; Signal transduction; Computational biology; Cell biology; Genetics","retraction":null,"screen_n_in":null,"score":{"opus":0.02757349639756859,"gpt":0.2669509597774061,"spread":0.2393774633798375,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003653933,0.0001894538,0.0002520551,0.00009103838,0.0001025547,0.00001087564,0.0001901904,0.0004657304,0.000007218331],"category_scores_gemma":[0.0001015994,0.0001688294,0.00006829138,0.0001449167,0.000284125,0.000004178468,0.0001136437,0.00009616173,0.00004268693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002865693,"about_ca_system_score_gemma":0.00006439124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009995681,"about_ca_topic_score_gemma":0.0004625177,"domain_scores_codex":[0.9984447,0.0002696066,0.0003895597,0.0005033233,0.00005126066,0.0003415774],"domain_scores_gemma":[0.9994163,0.00002467964,0.00008090329,0.0003134963,0.00009620435,0.00006842786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001569646,0.00007455167,0.3106282,0.0000285748,0.00006274958,0.000001620243,0.00009269466,0.0003333277,0.6859393,0.001225246,0.0002010794,0.001255724],"study_design_scores_gemma":[0.003289482,0.002247769,0.5971038,0.0001970809,0.00005641093,0.0002853519,0.0004897824,0.00779372,0.3275256,0.002123406,0.05688513,0.002002463],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838575,0.0004167224,0.01428768,0.00005167522,0.0006204877,0.0003201353,0.00001786683,0.00002567146,0.000402332],"genre_scores_gemma":[0.9975236,0.000028865,0.001161557,0.00006004575,0.0005579626,0.00004325335,0.000301497,0.00001614504,0.0003070386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3584137,"threshold_uncertainty_score":0.6884664,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}