{"meta":{"query_hash":"c448b840342a","filters":{"venue":"PLOS complex systems."},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/c448b840342a","api":"https://metacan.xera.ac/api/v1/cohort?venue=PLOS+complex+systems."},"results":[{"id":"W4405061251","doi":"10.1371/journal.pcsy.0000024","title":"Long-range temporal correlation development in resting-state fMRI signal in preterm infants: Scanned shortly after birth and at term-equivalent age","year":2024,"lang":"en","type":"article","venue":"PLOS complex systems.","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; BC Children's Hospital; University of Toronto; SickKids Foundation; Hospital for Sick Children; University of British Columbia","funders":"Canadian Institutes of Health Research; Cystic Fibrosis Canada","keywords":"Hurst exponent; Resting state fMRI; Correlation; White matter; Gestational age; Cerebellum; Psychology; Neuroscience; Medicine; Mathematics; Biology; Statistics; Magnetic resonance imaging","score_opus":0.04875232782787084,"score_gpt":0.25568521049498194,"score_spread":0.2069328826671111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405061251","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976064,0.00023745405,0.00019377752,0.00006704589,0.0004452838,0.0009695862,0.000046157606,0.00012569154,0.00030861833],"genre_scores_gemma":[0.99853534,0.000014729208,0.00003849921,0.000087006294,0.00004785864,0.00016913956,0.000029147574,0.00003629626,0.0010419654],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976659,0.00023220589,0.00063843396,0.0006665491,0.0004136234,0.00038328176],"domain_scores_gemma":[0.9994025,0.00019630668,0.00010250382,0.00018244227,0.000019676287,0.000096548116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029824994,0.00024560853,0.00029237088,0.00038139542,0.00009475988,0.00024167573,0.00013298664,0.000068304755,0.000040620045],"category_scores_gemma":[0.000059093723,0.0002202817,0.000034868837,0.0004080322,0.000074084994,0.0002991761,0.00017158453,0.00022018523,0.000036360023],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051342574,0.00013623817,0.91446936,0.0015548789,0.000016248725,0.0021923857,0.0023812796,0.0014106595,0.07524822,0.00012460048,0.00009804611,0.0018546234],"study_design_scores_gemma":[0.00060241745,0.00013529627,0.6978954,0.0015945393,0.00000792542,0.000099082776,0.000019957932,0.2977664,0.00079593196,0.000055197226,0.00063779484,0.00039009316],"about_ca_topic_score_codex":0.00009140403,"about_ca_topic_score_gemma":0.0010766014,"teacher_disagreement_score":0.29635572,"about_ca_system_score_codex":0.00033060784,"about_ca_system_score_gemma":0.00005043674,"threshold_uncertainty_score":0.8982827},"labels":[],"label_agreement":null},{"id":"W4406046433","doi":"10.1371/journal.pcsy.0000029","title":"Urban scaling with censored data","year":2025,"lang":"en","type":"article","venue":"PLOS complex systems.","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Division of Civil, Mechanical and Manufacturing Innovation; York University; National Science Foundation","keywords":"Scaling; Data science; Computer science; Econometrics; Mathematics","score_opus":0.13222096799389382,"score_gpt":0.3370689742477457,"score_spread":0.20484800625385186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406046433","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036198866,0.0054655126,0.007220176,0.0048690615,0.001663691,0.0021064302,0.00033798814,0.0010760039,0.9410623],"genre_scores_gemma":[0.9871445,0.000036312038,0.0004547389,0.00017867566,0.00037633168,0.000028123424,0.00005320127,0.000011310908,0.011716865],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99828404,0.00025728947,0.00027803265,0.00037276457,0.0004803797,0.00032748946],"domain_scores_gemma":[0.9987349,0.00029122978,0.000107628905,0.00058864965,0.0001962415,0.00008137083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039200412,0.00013331125,0.00031275715,0.000099615216,0.0009498011,0.00020497745,0.00063939625,0.000057924706,0.000071882605],"category_scores_gemma":[0.00021031102,0.00010878496,0.000026576168,0.000505335,0.00024625254,0.00021433349,0.00015432852,0.00009037176,0.00005516284],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059047652,0.00021488746,0.13226901,0.0002827913,0.0006834538,0.00001343217,0.019593852,0.000046096935,0.00015137298,0.4159805,0.4299207,0.00078488456],"study_design_scores_gemma":[0.00072888815,0.000029274921,0.0112928925,0.00039656027,0.00013880372,0.0000010685106,0.023537584,0.008658628,0.000017062288,0.00020753482,0.9546355,0.0003562254],"about_ca_topic_score_codex":0.0026156367,"about_ca_topic_score_gemma":0.0013504482,"teacher_disagreement_score":0.95094556,"about_ca_system_score_codex":0.000083440296,"about_ca_system_score_gemma":0.00017055134,"threshold_uncertainty_score":0.73051983},"labels":[],"label_agreement":null},{"id":"W4407690636","doi":"10.1371/journal.pcsy.0000034","title":"Signal demixing using multi-delay multi-layer reservoir computing","year":2025,"lang":"en","type":"article","venue":"PLOS complex systems.","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reservoir computing; Computer science; Layer (electronics); SIGNAL (programming language); Application layer; Distributed computing; Real-time computing; Materials science; Artificial intelligence; Operating system; Artificial neural network; Nanotechnology","score_opus":0.14347511255902629,"score_gpt":0.32692084814420636,"score_spread":0.18344573558518007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407690636","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14504674,0.0012773962,0.8501832,0.00023781369,0.0013143517,0.00068361795,0.0000035512694,0.00066762866,0.00058570923],"genre_scores_gemma":[0.8394766,0.0000041917856,0.1593901,0.00032135172,0.0003561238,0.000010301831,0.0000044773687,0.000035771922,0.0004010653],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954515,0.0006083263,0.0011073718,0.0011066612,0.00061639,0.0011097499],"domain_scores_gemma":[0.9973722,0.0005617251,0.00041354657,0.0010818596,0.00033466678,0.00023601856],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00085181854,0.0004944055,0.00077556935,0.0003947864,0.0011410107,0.00084889843,0.0023445578,0.00019551067,0.000009977929],"category_scores_gemma":[0.00007680381,0.00044839855,0.0002286131,0.0013680895,0.000089641086,0.00049135066,0.0020791893,0.0006160566,0.00003493282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027055516,0.00069434976,0.017354496,0.0010765572,0.0005135045,0.00035238126,0.00096857734,0.90133846,0.056029484,0.0148571795,0.0027547535,0.0040332167],"study_design_scores_gemma":[0.0009344167,0.000029848105,0.0016100041,0.0010437432,0.000025079305,0.00006174132,0.00009185657,0.99398804,0.0004645553,0.00005509368,0.0012238743,0.00047177952],"about_ca_topic_score_codex":0.00035498987,"about_ca_topic_score_gemma":0.000025091545,"teacher_disagreement_score":0.6944299,"about_ca_system_score_codex":0.00023477184,"about_ca_system_score_gemma":0.00016209527,"threshold_uncertainty_score":0.99979675},"labels":[],"label_agreement":null},{"id":"W4413269766","doi":"10.1371/journal.pcsy.0000057","title":"The impact of excitability heterogeneity and synaptic coupling on resilience and stability of a macro-scale brain network","year":2025,"lang":"en","type":"article","venue":"PLOS complex systems.","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; University of Ottawa; University Health Network; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Magnetoencephalography; Neuroscience; Coupling (piping); Network dynamics; Computer science; Resilience (materials science); Biological system; Psychology; Physics; Biology; Electroencephalography; Mathematics","score_opus":0.043957154205893495,"score_gpt":0.29253579186205236,"score_spread":0.24857863765615887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413269766","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99850976,0.00018527546,0.00016670111,0.00012217119,0.00011864934,0.0006020798,0.00005004134,0.000023282346,0.00022202347],"genre_scores_gemma":[0.9998834,0.000023347486,0.000012847462,0.00003159544,0.000015729645,0.00001599755,8.334284e-7,0.0000062050053,0.00001003279],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844325,0.0002815266,0.00042732045,0.00040503894,0.0002084776,0.00023441925],"domain_scores_gemma":[0.99695915,0.0022804486,0.00019681925,0.00044237007,0.00006528215,0.000055926055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006964046,0.0001398558,0.0003258954,0.000035172154,0.0002642697,0.00005230961,0.00017764606,0.000044579858,0.0000022884294],"category_scores_gemma":[0.0006416083,0.0000922256,0.00006773629,0.00027812482,0.00046530893,0.00005894073,0.00013696638,0.00011680026,3.4637472e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035941988,0.00016262176,0.1592252,0.0005082555,0.000039223716,0.0000010780021,0.00008243189,0.0050067953,0.829747,0.004508467,0.00006832693,0.00029118356],"study_design_scores_gemma":[0.00033315577,0.00044420583,0.41759327,0.00020064789,0.000017277638,0.00000745556,0.00007061392,0.566434,0.013433772,0.001323023,0.000015568152,0.00012697943],"about_ca_topic_score_codex":0.00019840118,"about_ca_topic_score_gemma":0.00008493796,"teacher_disagreement_score":0.8163132,"about_ca_system_score_codex":0.000058844354,"about_ca_system_score_gemma":0.00003699253,"threshold_uncertainty_score":0.37608507},"labels":[],"label_agreement":null},{"id":"W4414111978","doi":"10.1371/journal.pcsy.0000062","title":"Troika algorithm: Approximate optimization for accurate clique partitioning and clustering of weighted networks","year":2025,"lang":"en","type":"article","venue":"PLOS complex systems.","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Heuristics; Partition (number theory); Integer programming; Benchmark (surveying); Cluster analysis; Node (physics); Clique; Graph partition; Clique problem","score_opus":0.022092000194325598,"score_gpt":0.27239105772921884,"score_spread":0.25029905753489323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414111978","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027432134,0.00019375993,0.99462134,0.00003362376,0.000094737996,0.0007936274,0.000044218777,0.000109632776,0.0013658528],"genre_scores_gemma":[0.9224912,0.0000108683535,0.07650184,0.000016860617,0.00019689248,0.00036652666,0.00025930017,0.000022660923,0.00013388427],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987183,0.00009861938,0.00056117115,0.000283668,0.00009403415,0.00024416088],"domain_scores_gemma":[0.99910873,0.00012152404,0.00029930638,0.00024986605,0.0001764063,0.000044161934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021166919,0.00017988206,0.0004725696,0.00013422886,0.00018049953,0.000105076004,0.00014428237,0.00004754638,0.00004466132],"category_scores_gemma":[0.0000036614824,0.00018246657,0.000098972225,0.00029712063,0.000044181834,0.00011471884,0.00010671524,0.00008531747,2.847449e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000111064044,0.00047082052,0.014771056,0.0011221232,0.0017556992,9.734249e-7,0.00024295277,0.79935986,0.00078334915,0.15326494,0.0053023016,0.022814877],"study_design_scores_gemma":[0.0003960964,0.000027897662,0.00016792203,0.00028964295,0.00012100461,3.8537388e-7,0.000113241804,0.9969004,0.00018448477,0.0011613689,0.00048709812,0.00015045596],"about_ca_topic_score_codex":0.0001261408,"about_ca_topic_score_gemma":0.00000642494,"teacher_disagreement_score":0.91974795,"about_ca_system_score_codex":0.000028265766,"about_ca_system_score_gemma":0.000021312078,"threshold_uncertainty_score":0.744077},"labels":[],"label_agreement":null},{"id":"W4415181367","doi":"10.1371/journal.pcsy.0000071","title":"The shape of waning vaccinal immunity: Implications for control","year":2025,"lang":"en","type":"article","venue":"PLOS complex systems.","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Adolph C. and Mary Sprague Miller Institute for Basic Research in Science, University of California Berkeley; Gordon and Betty Moore Foundation; National Science Foundation","keywords":"Immunity; Vaccination; Pathogen; Pandemic; Immune system; Host (biology)","score_opus":0.09686647156876108,"score_gpt":0.3772382501164869,"score_spread":0.28037177854772577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415181367","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92046374,0.0071448227,0.018364556,0.00926581,0.00048243516,0.008025312,0.00023750616,0.00027333264,0.035742484],"genre_scores_gemma":[0.9957686,0.0000024806236,0.00007082481,0.0033935462,0.00009821819,0.000522485,0.000006332447,0.000014930899,0.00012258757],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988594,0.00009893294,0.0004097233,0.00016740014,0.00018890927,0.0002756509],"domain_scores_gemma":[0.99770296,0.0011457131,0.00010541205,0.0005635927,0.00045954096,0.000022785214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045562038,0.00010660436,0.0003615769,0.00012128994,0.0003485423,0.000047583926,0.00030784679,0.00005324984,0.0000055421237],"category_scores_gemma":[0.0003908754,0.00007441306,0.00012018982,0.00027946744,0.00006374484,0.000029077637,0.00006261592,0.0001510932,0.000012167315],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010580806,0.00042671012,0.1104594,0.0022751954,0.0012372932,0.000002412555,0.00026845103,0.000003359103,0.7578487,0.11183864,0.007100049,0.007481753],"study_design_scores_gemma":[0.011407525,0.0008531272,0.23461367,0.0012917832,0.00073573244,0.000057209705,0.0017318163,0.12269279,0.02139225,0.0028227975,0.60202545,0.00037584332],"about_ca_topic_score_codex":0.00019567585,"about_ca_topic_score_gemma":0.000021777661,"teacher_disagreement_score":0.7364564,"about_ca_system_score_codex":0.0000881156,"about_ca_system_score_gemma":0.00027294527,"threshold_uncertainty_score":0.30344766},"labels":[],"label_agreement":null},{"id":"W7110892247","doi":"10.1371/journal.pcsy.0000075","title":"Characteristics of immunity and disease-induced mortality synergistically complicate epidemiological dynamics","year":2025,"lang":"en","type":"article","venue":"PLOS complex systems.","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Adolph C. and Mary Sprague Miller Institute for Basic Research in Science, University of California Berkeley","keywords":"Immunity; Epidemiology; Mortality rate; Cohort; Immune system; Disease","score_opus":0.37696747699032096,"score_gpt":0.43084629410307934,"score_spread":0.05387881711275838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7110892247","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9645254,0.00022764852,0.028750608,0.0017779963,0.00017282255,0.0010886261,0.00049869897,0.00027936426,0.0026788148],"genre_scores_gemma":[0.9979642,0.000066335175,0.0011962177,0.00044215797,0.000050334587,0.00011503325,0.0000643973,0.000017715665,0.0000836142],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9959337,0.0011803492,0.0015992995,0.0005578541,0.0002753321,0.00045342863],"domain_scores_gemma":[0.9871919,0.010760251,0.0005877162,0.00091232563,0.00026874617,0.00027902002],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001636989,0.0003809531,0.0018744129,0.00008354939,0.00025984884,0.000030180001,0.0004779054,0.00017630693,0.000027599162],"category_scores_gemma":[0.029247183,0.00028592598,0.00018308026,0.0002509758,0.00048837595,0.000039172424,0.0007274971,0.00035026445,0.0000071422637],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007677867,0.00045114273,0.27052456,0.0026178283,0.00038536522,0.0000118465805,0.000023856972,0.0000080767895,0.00059941906,0.72385347,0.0012253772,0.00022229624],"study_design_scores_gemma":[0.00025067574,0.000067521214,0.81347287,0.00035949185,0.0002925922,0.0000017477796,0.00005249372,0.056902748,0.000004144262,0.12807249,0.00026102219,0.00026219033],"about_ca_topic_score_codex":0.00040141228,"about_ca_topic_score_gemma":0.000030232599,"teacher_disagreement_score":0.59578097,"about_ca_system_score_codex":0.00020470796,"about_ca_system_score_gemma":0.00006663144,"threshold_uncertainty_score":0.9999593},"labels":[],"label_agreement":null}]}